From 44e3c21c414cf7b843ed79b3cc3c76cadbd078da Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 16 Aug 2024 17:33:51 -0700 Subject: [PATCH 01/56] multiprocess initial commit --- .../models/non_mandatory_tour_frequency.py | 10 +- activitysim/abm/models/school_escorting.py | 5 +- activitysim/abm/models/stop_frequency.py | 12 +- activitysim/core/estimation.py | 35 +++++- activitysim/core/steps/output.py | 113 ++++++++++++++++++ 5 files changed, 165 insertions(+), 10 deletions(-) diff --git a/activitysim/abm/models/non_mandatory_tour_frequency.py b/activitysim/abm/models/non_mandatory_tour_frequency.py index e0fb4817ea..1189675973 100644 --- a/activitysim/abm/models/non_mandatory_tour_frequency.py +++ b/activitysim/abm/models/non_mandatory_tour_frequency.py @@ -288,14 +288,18 @@ def non_mandatory_tour_frequency( ) if estimator: - estimator.write_spec(model_settings, bundle_directory=True) + bundle_directory = True + # writing to separte subdirectory for each segment if multiprocessing + if state.settings.multiprocess: + bundle_directory = False + estimator.write_spec(model_settings, bundle_directory=bundle_directory) estimator.write_model_settings( - model_settings, model_settings_file_name, bundle_directory=True + model_settings, model_settings_file_name, bundle_directory=bundle_directory ) # preserving coefficients file name makes bringing back updated coefficients more straightforward estimator.write_coefficients(coefficients_df, segment_settings) estimator.write_choosers(chooser_segment) - estimator.write_alternatives(alternatives, bundle_directory=True) + estimator.write_alternatives(alternatives, bundle_directory=bundle_directory) # FIXME #interaction_simulate_estimation_requires_chooser_id_in_df_column # shuold we do it here or have interaction_simulate do it? diff --git a/activitysim/abm/models/school_escorting.py b/activitysim/abm/models/school_escorting.py index 22fea9e520..d8305740af 100644 --- a/activitysim/abm/models/school_escorting.py +++ b/activitysim/abm/models/school_escorting.py @@ -493,7 +493,10 @@ def school_escorting( coefficients_df, file_name=stage.upper() + "_COEFFICIENTS" ) estimator.write_choosers(choosers) - estimator.write_alternatives(alts, bundle_directory=True) + if state.settings.multiprocess: + estimator.write_alternatives(alts, bundle_directory=False) + else: + estimator.write_alternatives(alts, bundle_directory=True) # FIXME #interaction_simulate_estimation_requires_chooser_id_in_df_column # shuold we do it here or have interaction_simulate do it? diff --git a/activitysim/abm/models/stop_frequency.py b/activitysim/abm/models/stop_frequency.py index 2f0253f219..70755ff860 100644 --- a/activitysim/abm/models/stop_frequency.py +++ b/activitysim/abm/models/stop_frequency.py @@ -197,9 +197,15 @@ def stop_frequency( if estimator: estimator.write_spec(segment_settings, bundle_directory=False) - estimator.write_model_settings( - model_settings, model_settings_file_name, bundle_directory=True - ) + # writing to separte subdirectory for each segment if multiprocessing + if state.settings.multiprocess: + estimator.write_model_settings( + model_settings, model_settings_file_name, bundle_directory=False + ) + else: + estimator.write_model_settings( + model_settings, model_settings_file_name, bundle_directory=True + ) estimator.write_coefficients(coefficients_df, segment_settings) estimator.write_choosers(chooser_segment) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 6e02aca76a..124b33bd57 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -19,7 +19,13 @@ ESTIMATION_SETTINGS_FILE_NAME = "estimation.yaml" -def unlink_files(directory_path, file_types=("csv", "yaml")): +def unlink_files(directory_path, file_types=("csv", "yaml", "parquet")): + """ + Deletes existing files in directory_path with file_types extensions. + """ + if not os.path.exists(directory_path): + return + for file_name in os.listdir(directory_path): if file_name.endswith(file_types): file_path = os.path.join(directory_path, file_name) @@ -31,6 +37,16 @@ def unlink_files(directory_path, file_types=("csv", "yaml")): print(e) +def estimation_enabled(state): + """ + Returns True if estimation.yaml exists in the configs directory. + """ + settings = state.filesystem.read_model_settings( + ESTIMATION_SETTINGS_FILE_NAME, mandatory=False + ) + return settings is not None + + class Estimator: def __init__( self, state: workflow.State, bundle_name, model_name, estimation_table_recipes @@ -50,12 +66,12 @@ def __init__( os.makedirs(output_dir) # make directory if needed # delete estimation files - unlink_files(self.output_directory(), file_types=("csv", "yaml")) + unlink_files(self.output_directory(), file_types=("csv", "yaml", "parquet")) if self.bundle_name != self.model_name: # kind of inelegant to always delete these, but ok as they are redundantly recreated for each sub model unlink_files( self.output_directory(bundle_directory=True), - file_types=("csv", "yaml"), + file_types=("csv", "yaml", "parquet"), ) # FIXME - not required? @@ -139,6 +155,9 @@ def output_directory(self, bundle_directory=False): if self.bundle_name != self.model_name and not bundle_directory: dir = os.path.join(dir, self.model_name) + if self.state.settings.multiprocess: + dir = os.path.join(dir, self.state.get_injectable("pipeline_file_prefix")) + return dir def output_file_path(self, table_name, file_type=None, bundle_directory=False): @@ -546,6 +565,16 @@ def initialize_settings(self, state): ), "Index col '%s' not in survey_table '%s' in file: %s % (index_col, table_name, file_path)" df.set_index(index_col, inplace=True) + # if multiprocessing then only return the households that are in the pipeline + if state.settings.multiprocess: + pipeline_hh_ids = state.get_table("households").index + if table_name == "households": + df = df[df.index.isin(pipeline_hh_ids)] + assert pipeline_hh_ids.equals(df.index), "household_ids not equal between survey and pipeline" + else: + assert "household_id" in df.columns + df = df[df.household_id.isin(pipeline_hh_ids)] + # add the table df to survey_tables table_info["df"] = df diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index b9d7cc13d6..6116fda611 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -4,6 +4,9 @@ import logging import sys +import os +import shutil +from pathlib import Path import numpy as np import pandas as pd @@ -13,6 +16,7 @@ from activitysim.core import configuration, workflow from activitysim.core.workflow.checkpoint import CHECKPOINT_NAME +from activitysim.core.estimation import estimation_enabled logger = logging.getLogger(__name__) @@ -224,6 +228,111 @@ def write_data_dictionary(state: workflow.State) -> None: print(f"{info}\n", file=output_file) +def find_lowest_level_directories(starting_directory): + lowest_dirs = list() + + for root, dirs, files in os.walk(starting_directory): + if not dirs: + lowest_dirs.append(root) + + return lowest_dirs + + +def concat_and_write_edb(df_concat_dict, write_dir): + # concatenate the dataframes and output final file + for table_name, df_array in df_concat_dict.items(): + df = pd.concat(df_array) + if table_name.endswith(".csv"): + df.to_csv(os.path.join(write_dir, table_name), index=False) + elif table_name.endswith(".parquet"): + df.to_parquet(os.path.join(write_dir, table_name), index=True) + else: + raise ValueError(f"Unknown file type {table_name}") + + +def coalesce_estimation_data_bundles(state): + """ + In estimation mode, estimation data bundles are written to separate subdirectories for each subprocess. + This model will go through each subdirectory and move the files to the parent directory. + This will only occur if the lowest level directory contains the multiprocess step names. + """ + + logger.info("Coalescing Estimation Data Bundles") + + edb_dir = state.filesystem.get_output_dir("estimation_data_bundle") + + lowest_dirs = find_lowest_level_directories(edb_dir) + + multiprocessing_step_names = [step.name for step in state.settings.multiprocess_steps] + lowest_dirs = [dir for dir in lowest_dirs if any(step in dir for step in multiprocessing_step_names)] + + if len(lowest_dirs) == 0: + logger.info("No estimation data bundles to coalesce") + return + + prev_edb = None + df_concat_dict = {} + + # loop through each lowest level directory + for dir in lowest_dirs: + logger.debug(f"Coalescing {dir}") + # get the parent directory + cur_edb = Path(dir).parent.absolute() + + # check if we have moved onto a new EDB + is_same_edb = (cur_edb == prev_edb) + + for file in os.listdir(dir): + # get the file path + file_path = os.path.join(dir, file) + + # look for files that are duplicated across subprocesses + is_coefs_file = file.endswith(".csv") and "coef" in file + is_settings_file = file.endswith(".yaml") + is_spec_file = file.endswith(".csv") and "SPEC" in file + is_landuse_file = file.endswith("_landuse.csv") + is_size_terms_file = file.endswith("_size_terms.csv") + is_duplicate_file = ( + is_coefs_file + or is_spec_file + or is_settings_file + or is_landuse_file + or is_size_terms_file + ) + + if is_duplicate_file and not is_same_edb: + # copy the file to the parent directory + shutil.copy(file_path, os.path.join(cur_edb, file)) + + if (not is_same_edb) and (len(df_concat_dict) > 0) and (len(df_concat_dict[list(df_concat_dict.keys())[0]]) > 1): + concat_and_write_edb(df_concat_dict, cur_edb) + + # reset edb dir and dictionary + logger.info(f"Coalesced {cur_edb}") + prev_edb = cur_edb + df_concat_dict = {} + + if not is_duplicate_file: + # read file and store in dictionary + if file.endswith(".csv"): + df = pd.read_csv(file_path, low_memory=False) + elif file.endswith(".parquet"): + df = pd.read_parquet(file_path) + + if file in df_concat_dict.keys(): + df_concat_dict[file].append(df) + else: + df_concat_dict[file] = [df] + + # delete the directory now that we have gone through all the files + # os.rmdir(dir) + + # need to concatenate the last set of dataframes + concat_and_write_edb(df_concat_dict, cur_edb) + + return + + @workflow.step def write_tables(state: workflow.State) -> None: """ @@ -434,3 +543,7 @@ def map_func(x): parquet.write_table(dt, file_path) else: raise ValueError(f"unknown file_type {file_type}") + + is_estimation = estimation_enabled(state) + if state.settings.multiprocess and is_estimation: + coalesce_estimation_data_bundles(state) From 9b29350b85e3f914d441a35ad946469c44ec1f2e Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 16 Aug 2024 17:41:41 -0700 Subject: [PATCH 02/56] blacken --- .../models/non_mandatory_tour_frequency.py | 8 ++++-- activitysim/core/estimation.py | 4 ++- activitysim/core/steps/output.py | 26 +++++++++++++------ 3 files changed, 27 insertions(+), 11 deletions(-) diff --git a/activitysim/abm/models/non_mandatory_tour_frequency.py b/activitysim/abm/models/non_mandatory_tour_frequency.py index 1189675973..4d80c26baa 100644 --- a/activitysim/abm/models/non_mandatory_tour_frequency.py +++ b/activitysim/abm/models/non_mandatory_tour_frequency.py @@ -294,12 +294,16 @@ def non_mandatory_tour_frequency( bundle_directory = False estimator.write_spec(model_settings, bundle_directory=bundle_directory) estimator.write_model_settings( - model_settings, model_settings_file_name, bundle_directory=bundle_directory + model_settings, + model_settings_file_name, + bundle_directory=bundle_directory, ) # preserving coefficients file name makes bringing back updated coefficients more straightforward estimator.write_coefficients(coefficients_df, segment_settings) estimator.write_choosers(chooser_segment) - estimator.write_alternatives(alternatives, bundle_directory=bundle_directory) + estimator.write_alternatives( + alternatives, bundle_directory=bundle_directory + ) # FIXME #interaction_simulate_estimation_requires_chooser_id_in_df_column # shuold we do it here or have interaction_simulate do it? diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 124b33bd57..0de69b3d9e 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -570,7 +570,9 @@ def initialize_settings(self, state): pipeline_hh_ids = state.get_table("households").index if table_name == "households": df = df[df.index.isin(pipeline_hh_ids)] - assert pipeline_hh_ids.equals(df.index), "household_ids not equal between survey and pipeline" + assert pipeline_hh_ids.equals( + df.index + ), "household_ids not equal between survey and pipeline" else: assert "household_id" in df.columns df = df[df.household_id.isin(pipeline_hh_ids)] diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index 6116fda611..39e2d9650d 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -263,13 +263,19 @@ def coalesce_estimation_data_bundles(state): lowest_dirs = find_lowest_level_directories(edb_dir) - multiprocessing_step_names = [step.name for step in state.settings.multiprocess_steps] - lowest_dirs = [dir for dir in lowest_dirs if any(step in dir for step in multiprocessing_step_names)] + multiprocessing_step_names = [ + step.name for step in state.settings.multiprocess_steps + ] + lowest_dirs = [ + dir + for dir in lowest_dirs + if any(step in dir for step in multiprocessing_step_names) + ] if len(lowest_dirs) == 0: logger.info("No estimation data bundles to coalesce") return - + prev_edb = None df_concat_dict = {} @@ -280,7 +286,7 @@ def coalesce_estimation_data_bundles(state): cur_edb = Path(dir).parent.absolute() # check if we have moved onto a new EDB - is_same_edb = (cur_edb == prev_edb) + is_same_edb = cur_edb == prev_edb for file in os.listdir(dir): # get the file path @@ -293,8 +299,8 @@ def coalesce_estimation_data_bundles(state): is_landuse_file = file.endswith("_landuse.csv") is_size_terms_file = file.endswith("_size_terms.csv") is_duplicate_file = ( - is_coefs_file - or is_spec_file + is_coefs_file + or is_spec_file or is_settings_file or is_landuse_file or is_size_terms_file @@ -304,7 +310,11 @@ def coalesce_estimation_data_bundles(state): # copy the file to the parent directory shutil.copy(file_path, os.path.join(cur_edb, file)) - if (not is_same_edb) and (len(df_concat_dict) > 0) and (len(df_concat_dict[list(df_concat_dict.keys())[0]]) > 1): + if ( + (not is_same_edb) + and (len(df_concat_dict) > 0) + and (len(df_concat_dict[list(df_concat_dict.keys())[0]]) > 1) + ): concat_and_write_edb(df_concat_dict, cur_edb) # reset edb dir and dictionary @@ -543,7 +553,7 @@ def map_func(x): parquet.write_table(dt, file_path) else: raise ValueError(f"unknown file_type {file_type}") - + is_estimation = estimation_enabled(state) if state.settings.multiprocess and is_estimation: coalesce_estimation_data_bundles(state) From 3434c9540be1cea8f1c2623c049441ef6809b2d4 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 6 Sep 2024 09:18:32 -0700 Subject: [PATCH 03/56] parquet format for EDBs --- activitysim/core/estimation.py | 162 +++++++++++++++++++++++-------- activitysim/core/steps/output.py | 3 +- 2 files changed, 124 insertions(+), 41 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 0de69b3d9e..5b815183e7 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -5,6 +5,7 @@ import logging import os import shutil +from pathlib import Path import pandas as pd import yaml @@ -49,7 +50,12 @@ def estimation_enabled(state): class Estimator: def __init__( - self, state: workflow.State, bundle_name, model_name, estimation_table_recipes + self, + state: workflow.State, + bundle_name, + model_name, + estimation_table_recipes, + settings, ): logger.info("Initialize Estimator for'%s'" % (model_name,)) @@ -59,6 +65,7 @@ def __init__( self.settings_name = model_name self.estimation_table_recipes = estimation_table_recipes self.estimating = True + self.settings = settings # ensure the output data directory exists output_dir = self.output_directory() @@ -179,8 +186,43 @@ def output_file_path(self, table_name, file_type=None, bundle_directory=False): return os.path.join(output_dir, file_name) + def write_parquet(self, df, file_path, append=False): + """Convert DF to be parquet compliant and write to disk""" + # Ensure column names are strings for parquet + df.columns = df.columns.astype(str) + + assert (not os.path.isfile(file_path)) or ( + append == True + ), f"file already exists: {file_path}" + + # Explicitly set the data types of the columns + for col in df.columns: + if df[col].dtype == "object": + df[col] = df[col].astype(str) + elif df[col].dtype == "int": + df[col] = df[col].astype("int64") + elif df[col].dtype == "float": + df[col] = df[col].astype("float64") + elif df[col].dtype == "float16": # Handle halffloat type + df[col] = df[col].astype("float32") + else: + # Convert any other unsupported types to string + df[col] = df[col].astype(str) + + self.debug(f"writing table: {file_path}") + if append and os.path.isfile(file_path): + df.to_parquet(file_path, engine="fastparquet", append=True) + else: + df.to_parquet(file_path) + def write_table( - self, df, table_name, index=True, append=True, bundle_directory=False + self, + df, + table_name, + index=True, + append=True, + bundle_directory=False, + filetype="csv", ): """ @@ -192,6 +234,8 @@ def write_table( index: booelan append: boolean bundle_directory: boolean + filetype: str + csv or parquet """ @@ -205,21 +249,23 @@ def cache_table(df, table_name, append): else: self.tables[table_name] = df.copy() - def write_table(df, table_name, index, append, bundle_directory): - if table_name.endswith(".csv"): - # pass through filename without adding model or bundle name prefix - file_path = os.path.join( - self.output_directory(bundle_directory), table_name - ) - else: - file_path = self.output_file_path(table_name, "csv", bundle_directory) + def write_table(df, table_name, index, append, bundle_directory, filetype): + # remove file extension if present + table_name = Path(table_name).stem + # set new full file path with desired file type + file_path = self.output_file_path(table_name, filetype, bundle_directory) + + # check if file exists file_exists = os.path.isfile(file_path) if file_exists and not append: raise RuntimeError( "write_table %s append=False and file exists: %s" % (table_name, file_path) ) - df.to_csv(file_path, mode="a", index=index, header=(not file_exists)) + if filetype == "csv": + df.to_csv(file_path, mode="a", index=index, header=(not file_exists)) + else: + self.write_parquet(df, file_path, append) assert self.estimating @@ -232,18 +278,14 @@ def write_table(df, table_name, index, append, bundle_directory): self.debug("write_table cache: %s" % table_name) if write: - write_table(df, table_name, index, append, bundle_directory) + write_table(df, table_name, index, append, bundle_directory, filetype) self.debug("write_table write: %s" % table_name) def write_omnibus_table(self): if len(self.omnibus_tables) == 0: return - settings = self.state.filesystem.read_model_settings( - ESTIMATION_SETTINGS_FILE_NAME, mandatory=False - ) - - edbs_to_skip = settings.get("SKIP_BUNDLE_WRITE_FOR", []) + edbs_to_skip = self.settings.get("SKIP_BUNDLE_WRITE_FOR", []) if self.bundle_name in edbs_to_skip: self.debug(f"Skipping write to disk for {self.bundle_name}") return @@ -274,13 +316,20 @@ def write_omnibus_table(self): self.debug(f"sorting tables: {table_names}") df.sort_index(ascending=True, inplace=True, kind="mergesort") - file_path = self.output_file_path(omnibus_table, "csv") - assert not os.path.isfile(file_path) + filetype = self.settings.get("EDB_FILETYPE", "csv") + assert filetype in ["csv", "parquet"] - self.debug(f"writing table: {file_path}") - df.to_csv(file_path, mode="a", index=True, header=True) + if filetype == "csv": + file_path = self.output_file_path(omnibus_table, "csv") + assert not os.path.isfile(file_path) + + self.debug(f"writing table: {file_path}") + df.to_csv(file_path, mode="a", index=True, header=True) + else: + file_path = self.output_file_path(omnibus_table, "parquet") + self.write_parquet(df, file_path, append=False) - self.debug("write_omnibus_choosers: %s" % file_path) + self.debug("wrote_omnibus_choosers: %s" % file_path) def write_dict(self, d, dict_name, bundle_directory): assert self.estimating @@ -323,7 +372,7 @@ def write_coefficients( base_file_name = os.path.basename(file_name) assert self.estimating - self.write_table(coefficients_df, base_file_name, append=False) + self.write_table(coefficients_df, base_file_name, append=False, filetype="csv") def write_coefficients_template(self, model_settings): assert self.estimating @@ -334,22 +383,37 @@ def write_coefficients_template(self, model_settings): self.state.filesystem, model_settings ) tag = "coefficients_template" - self.write_table(coefficients_df, tag, append=False) + self.write_table(coefficients_df, tag, append=False, filetype="csv") def write_choosers(self, choosers_df): - self.write_table(choosers_df, "choosers", append=True) + self.write_table( + choosers_df, + "choosers", + append=True, + filetype=self.settings.get("EDB_FILETYPE", "csv"), + ) def write_choices(self, choices): if isinstance(choices, pd.Series): choices = choices.to_frame(name="model_choice") assert list(choices.columns) == ["model_choice"] - self.write_table(choices, "choices", append=True) + self.write_table( + choices, + "choices", + append=True, + filetype=self.settings.get("EDB_FILETYPE", "csv"), + ) def write_override_choices(self, choices): if isinstance(choices, pd.Series): choices = choices.to_frame(name="override_choice") assert list(choices.columns) == ["override_choice"] - self.write_table(choices, "override_choices", append=True) + self.write_table( + choices, + "override_choices", + append=True, + filetype=self.settings.get("EDB_FILETYPE", "csv"), + ) def write_constants(self, constants): self.write_dict(self, constants, "model_constants") @@ -463,10 +527,20 @@ def melt_alternatives(self, df): def write_interaction_expression_values(self, df): df = self.melt_alternatives(df) - self.write_table(df, "interaction_expression_values", append=True) + self.write_table( + df, + "interaction_expression_values", + append=True, + filetype=self.settings.get("EDB_FILETYPE", "csv"), + ) def write_expression_values(self, df): - self.write_table(df, "expression_values", append=True) + self.write_table( + df, + "expression_values", + append=True, + filetype=self.settings.get("EDB_FILETYPE", "csv"), + ) def write_alternatives(self, alternatives_df, bundle_directory=False): self.write_table( @@ -479,13 +553,19 @@ def write_alternatives(self, alternatives_df, bundle_directory=False): def write_interaction_sample_alternatives(self, alternatives_df): alternatives_df = self.melt_alternatives(alternatives_df) self.write_table( - alternatives_df, "interaction_sample_alternatives", append=True + alternatives_df, + "interaction_sample_alternatives", + append=True, + filetype=self.settings.get("EDB_FILETYPE", "csv"), ) def write_interaction_simulate_alternatives(self, interaction_df): interaction_df = self.melt_alternatives(interaction_df) self.write_table( - interaction_df, "interaction_simulate_alternatives", append=True + interaction_df, + "interaction_simulate_alternatives", + append=True, + filetype=self.settings.get("EDB_FILETYPE", "csv"), ) def get_survey_values(self, model_values, table_name, column_names): @@ -520,6 +600,7 @@ def __init__(self): self.estimation_table_recipes = {} self.model_estimation_table_types = {} self.estimating = {} + self.settings = None def initialize_settings(self, state): # FIXME - can't we just initialize in init and handle no-presence of settings file as not enabled @@ -527,23 +608,25 @@ def initialize_settings(self, state): return assert not self.settings_initialized - settings = state.filesystem.read_model_settings( + self.settings = state.filesystem.read_model_settings( ESTIMATION_SETTINGS_FILE_NAME, mandatory=False ) - if not settings: - # if the model settings file is not found, we are not in estimation mode. + if not self.settings: + # if the model self.settings file is not found, we are not in estimation mode. self.enabled = False else: - self.enabled = settings.get("enable", "True") - self.bundles = settings.get("bundles", []) + self.enabled = self.settings.get("enable", "True") + self.bundles = self.settings.get("bundles", []) - self.model_estimation_table_types = settings.get( + self.model_estimation_table_types = self.settings.get( "model_estimation_table_types", {} ) - self.estimation_table_recipes = settings.get("estimation_table_recipes", {}) + self.estimation_table_recipes = self.settings.get( + "estimation_table_recipes", {} + ) if self.enabled: - self.survey_tables = settings.get("survey_tables", {}) + self.survey_tables = self.settings.get("survey_tables", {}) for table_name, table_info in self.survey_tables.items(): assert ( "file_name" in table_info @@ -643,6 +726,7 @@ def begin_estimation( estimation_table_recipes=self.estimation_table_recipes[ model_estimation_table_type ], + settings=self.settings, ) return self.estimating[model_name] diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index 39e2d9650d..0306fcff4a 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -318,7 +318,6 @@ def coalesce_estimation_data_bundles(state): concat_and_write_edb(df_concat_dict, cur_edb) # reset edb dir and dictionary - logger.info(f"Coalesced {cur_edb}") prev_edb = cur_edb df_concat_dict = {} @@ -335,7 +334,7 @@ def coalesce_estimation_data_bundles(state): df_concat_dict[file] = [df] # delete the directory now that we have gone through all the files - # os.rmdir(dir) + shutil.rmtree(dir) # need to concatenate the last set of dataframes concat_and_write_edb(df_concat_dict, cur_edb) From 914b9ca7109cf478c29c2147df19baa2b6cfae02 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 20 Sep 2024 11:59:24 -0700 Subject: [PATCH 04/56] adding pkl, fixing edb concat and write --- activitysim/core/estimation.py | 35 ++++++++++++++++++------ activitysim/core/steps/output.py | 47 ++++++++++++++++++++++---------- 2 files changed, 60 insertions(+), 22 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 5b815183e7..24b5f3e532 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -186,7 +186,7 @@ def output_file_path(self, table_name, file_type=None, bundle_directory=False): return os.path.join(output_dir, file_name) - def write_parquet(self, df, file_path, append=False): + def write_parquet(self, df, file_path, index, append=False): """Convert DF to be parquet compliant and write to disk""" # Ensure column names are strings for parquet df.columns = df.columns.astype(str) @@ -211,9 +211,9 @@ def write_parquet(self, df, file_path, append=False): self.debug(f"writing table: {file_path}") if append and os.path.isfile(file_path): - df.to_parquet(file_path, engine="fastparquet", append=True) + df.to_parquet(file_path, engine="fastparquet", append=True, index=index) else: - df.to_parquet(file_path) + df.to_parquet(file_path, index=index) def write_table( self, @@ -235,7 +235,7 @@ def write_table( append: boolean bundle_directory: boolean filetype: str - csv or parquet + csv or parquet or pkl """ @@ -264,8 +264,20 @@ def write_table(df, table_name, index, append, bundle_directory, filetype): ) if filetype == "csv": df.to_csv(file_path, mode="a", index=index, header=(not file_exists)) + elif filetype == "parquet": + self.write_parquet(df, file_path, index, append) + elif filetype == "pkl": + if append: + # read the previous df and concat + prev_df = pd.read_pickle(file_path) + df = pd.concat([prev_df, df]) + if index == False: + df.reset_index(drop=True, inplace=True) + df.to_pickle(file_path) else: - self.write_parquet(df, file_path, append) + raise RuntimeError( + f"Unsupported filetype: {filetype}, allowed options are csv, parquet, pkl" + ) assert self.estimating @@ -317,7 +329,6 @@ def write_omnibus_table(self): df.sort_index(ascending=True, inplace=True, kind="mergesort") filetype = self.settings.get("EDB_FILETYPE", "csv") - assert filetype in ["csv", "parquet"] if filetype == "csv": file_path = self.output_file_path(omnibus_table, "csv") @@ -325,9 +336,17 @@ def write_omnibus_table(self): self.debug(f"writing table: {file_path}") df.to_csv(file_path, mode="a", index=True, header=True) - else: + + elif filetype == "parquet": file_path = self.output_file_path(omnibus_table, "parquet") - self.write_parquet(df, file_path, append=False) + self.write_parquet(df, file_path, index=True, append=False) + + elif filetype == "pkl": + file_path = self.output_file_path(omnibus_table, "pkl") + df.to_pickle(file_path) + + else: + raise RuntimeError(f"Unsupported filetype: {filetype}") self.debug("wrote_omnibus_choosers: %s" % file_path) diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index 0306fcff4a..d4ebccdb3b 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -242,10 +242,19 @@ def concat_and_write_edb(df_concat_dict, write_dir): # concatenate the dataframes and output final file for table_name, df_array in df_concat_dict.items(): df = pd.concat(df_array) + + # sort the dataframe by index + if df.index.name is not None: + df = df.sort_index() + else: + df = df.sort_values(by=df.columns[0]) + if table_name.endswith(".csv"): df.to_csv(os.path.join(write_dir, table_name), index=False) elif table_name.endswith(".parquet"): df.to_parquet(os.path.join(write_dir, table_name), index=True) + elif table_name.endswith(".pkl"): + df.to_pickle(os.path.join(write_dir, table_name)) else: raise ValueError(f"Unknown file type {table_name}") @@ -255,6 +264,7 @@ def coalesce_estimation_data_bundles(state): In estimation mode, estimation data bundles are written to separate subdirectories for each subprocess. This model will go through each subdirectory and move the files to the parent directory. This will only occur if the lowest level directory contains the multiprocess step names. + Only multiprocess step names are used because that's how EDBs are written in estimation mode. """ logger.info("Coalescing Estimation Data Bundles") @@ -284,18 +294,32 @@ def coalesce_estimation_data_bundles(state): logger.debug(f"Coalescing {dir}") # get the parent directory cur_edb = Path(dir).parent.absolute() + if prev_edb is None: + prev_edb = cur_edb # check if we have moved onto a new EDB is_same_edb = cur_edb == prev_edb - for file in os.listdir(dir): + # if we have moved onto a new EDB, concatenate the dataframes and write the final files + if ( + (not is_same_edb) + and (len(df_concat_dict) > 0) + and (len(df_concat_dict[list(df_concat_dict.keys())[0]]) > 1) + ): + concat_and_write_edb(df_concat_dict, prev_edb) + + # reset edb dir and dictionary + prev_edb = cur_edb + df_concat_dict = {} + + for i, file in enumerate(os.listdir(dir)): # get the file path file_path = os.path.join(dir, file) # look for files that are duplicated across subprocesses is_coefs_file = file.endswith(".csv") and "coef" in file is_settings_file = file.endswith(".yaml") - is_spec_file = file.endswith(".csv") and "SPEC" in file + is_spec_file = file.endswith(".csv") and ("spec" in file.lower()) is_landuse_file = file.endswith("_landuse.csv") is_size_terms_file = file.endswith("_size_terms.csv") is_duplicate_file = ( @@ -310,23 +334,18 @@ def coalesce_estimation_data_bundles(state): # copy the file to the parent directory shutil.copy(file_path, os.path.join(cur_edb, file)) - if ( - (not is_same_edb) - and (len(df_concat_dict) > 0) - and (len(df_concat_dict[list(df_concat_dict.keys())[0]]) > 1) - ): - concat_and_write_edb(df_concat_dict, cur_edb) - - # reset edb dir and dictionary - prev_edb = cur_edb - df_concat_dict = {} - if not is_duplicate_file: # read file and store in dictionary if file.endswith(".csv"): df = pd.read_csv(file_path, low_memory=False) elif file.endswith(".parquet"): df = pd.read_parquet(file_path) + elif file.endswith(".pkl"): + df = pd.read_pickle(file_path) + else: + raise ValueError( + f"Unknown file type found {file}, expect csv, parquet, or pkl" + ) if file in df_concat_dict.keys(): df_concat_dict[file].append(df) @@ -334,7 +353,7 @@ def coalesce_estimation_data_bundles(state): df_concat_dict[file] = [df] # delete the directory now that we have gone through all the files - shutil.rmtree(dir) + # shutil.rmtree(dir) # need to concatenate the last set of dataframes concat_and_write_edb(df_concat_dict, cur_edb) From d2e181f089a86f1db057db307bdbcb6ac0ad4989 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Mon, 23 Sep 2024 13:01:51 -0700 Subject: [PATCH 05/56] fixing double naming of coefficient files --- activitysim/core/estimation.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 24b5f3e532..1fb21522ee 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -176,7 +176,9 @@ def output_file_path(self, table_name, file_type=None, bundle_directory=False): if bundle_directory: file_name = f"{self.bundle_name}_{table_name}" else: - if self.model_name == self.bundle_name: + if '_coefficients' in table_name: + file_name = f"{table_name}" + elif self.model_name == self.bundle_name: file_name = f"{self.model_name}_{table_name}" else: file_name = f"{self.bundle_name}_{table_name}" From c138f0f1578e9111423a5e5aa451c3c150a7da63 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Mon, 23 Sep 2024 13:15:50 -0700 Subject: [PATCH 06/56] blacken --- activitysim/core/estimation.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 1fb21522ee..aedb845103 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -176,7 +176,7 @@ def output_file_path(self, table_name, file_type=None, bundle_directory=False): if bundle_directory: file_name = f"{self.bundle_name}_{table_name}" else: - if '_coefficients' in table_name: + if "_coefficients" in table_name: file_name = f"{table_name}" elif self.model_name == self.bundle_name: file_name = f"{self.model_name}_{table_name}" From 6d35f9fcfbf9193e9d5d751653fe6610130cbe9b Mon Sep 17 00:00:00 2001 From: David Hensle Date: Mon, 23 Sep 2024 16:03:11 -0700 Subject: [PATCH 07/56] fixing missing cdap coefficients file, write pickle function --- activitysim/abm/models/cdap.py | 2 +- activitysim/core/estimation.py | 58 ++++++++++++++++++++++++++-------- 2 files changed, 45 insertions(+), 15 deletions(-) diff --git a/activitysim/abm/models/cdap.py b/activitysim/abm/models/cdap.py index 6776c06c7f..2b9a105a5b 100644 --- a/activitysim/abm/models/cdap.py +++ b/activitysim/abm/models/cdap.py @@ -180,7 +180,7 @@ def cdap_simulate( estimator.write_coefficients(coefficients_df, model_settings) estimator.write_table( cdap_interaction_coefficients, - "interaction_coefficients", + "cdap_interaction_coefficients", index=False, append=False, ) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index aedb845103..6c88dcccd5 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -20,7 +20,7 @@ ESTIMATION_SETTINGS_FILE_NAME = "estimation.yaml" -def unlink_files(directory_path, file_types=("csv", "yaml", "parquet")): +def unlink_files(directory_path, file_types=("csv", "yaml", "parquet", "pkl")): """ Deletes existing files in directory_path with file_types extensions. """ @@ -33,9 +33,9 @@ def unlink_files(directory_path, file_types=("csv", "yaml", "parquet")): try: if os.path.isfile(file_path): os.unlink(file_path) - print(f"deleted {file_path}") + logger.debug(f"deleted {file_path}") except Exception as e: - print(e) + logger.error(e) def estimation_enabled(state): @@ -212,10 +212,40 @@ def write_parquet(self, df, file_path, index, append=False): df[col] = df[col].astype(str) self.debug(f"writing table: {file_path}") + # want parquet file to be exactly the same as df read from csv + # therefore we are resetting the index into a column if we want to keep it + # if we don't want to keep it, we are dropping it on write with index=False + if index: + df = df.reset_index(drop=False) + if append and os.path.isfile(file_path): - df.to_parquet(file_path, engine="fastparquet", append=True, index=index) + df.to_parquet(file_path, engine="fastparquet", append=True, index=False) + else: + df.to_parquet(file_path, index=False) + + def write_pickle(self, df, file_path, index, append=False): + """Write DF to disk as pickle""" + file_path = file_path.replace(".csv", ".pkl").replace(".parquet", ".pkl") + assert file_path.endswith(".pkl") + + # want pickle file to be exactly the same as df read from csv + # therefore we are resetting the index into a column if we want to keep it + # if we don't want to keep it, we are dropping it on write with index=False + if index: + df = df.reset_index(drop=False) else: - df.to_parquet(file_path, index=index) + df = df.reset_index(drop=True) + + assert (not os.path.isfile(file_path)) or ( + append == True + ), f"file already exists: {file_path}" + + if append: + # read the previous df and concat + prev_df = pd.read_pickle(file_path) + df = pd.concat([prev_df, df]) + + df.to_pickle(file_path) def write_table( self, @@ -267,15 +297,15 @@ def write_table(df, table_name, index, append, bundle_directory, filetype): if filetype == "csv": df.to_csv(file_path, mode="a", index=index, header=(not file_exists)) elif filetype == "parquet": - self.write_parquet(df, file_path, index, append) + try: + self.write_parquet(df, file_path, index, append) + except Exception as e: + logger.error( + f"Error writing parquet: {file_path} because {e}, falling back to pickle" + ) + self.write_pickle(df, file_path, index, append) elif filetype == "pkl": - if append: - # read the previous df and concat - prev_df = pd.read_pickle(file_path) - df = pd.concat([prev_df, df]) - if index == False: - df.reset_index(drop=True, inplace=True) - df.to_pickle(file_path) + self.write_pickle(df, file_path, index, append) else: raise RuntimeError( f"Unsupported filetype: {filetype}, allowed options are csv, parquet, pkl" @@ -345,7 +375,7 @@ def write_omnibus_table(self): elif filetype == "pkl": file_path = self.output_file_path(omnibus_table, "pkl") - df.to_pickle(file_path) + self.write_pickle(df, file_path, index=True, append=False) else: raise RuntimeError(f"Unsupported filetype: {filetype}") From 27c4ce48adc780ad024149096e4604c1bd09eb3b Mon Sep 17 00:00:00 2001 From: David Hensle Date: Tue, 24 Sep 2024 16:51:51 -0700 Subject: [PATCH 08/56] combact edb writing, index duplication, parquet datatypes --- activitysim/core/estimation.py | 43 ++++++++++++++++++++++++++++------ 1 file changed, 36 insertions(+), 7 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 6c88dcccd5..793f1e532b 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -199,14 +199,22 @@ def write_parquet(self, df, file_path, index, append=False): # Explicitly set the data types of the columns for col in df.columns: - if df[col].dtype == "object": - df[col] = df[col].astype(str) - elif df[col].dtype == "int": - df[col] = df[col].astype("int64") - elif df[col].dtype == "float": - df[col] = df[col].astype("float64") - elif df[col].dtype == "float16": # Handle halffloat type + if "int" in str(df[col].dtype): + pass + elif ( + df[col].dtype == "float16" + ): # Handle halffloat type not allowed in parquet df[col] = df[col].astype("float32") + elif "float" in str(df[col].dtype): + pass + elif df[col].dtype == "bool": + pass + elif df[col].dtype == "object": + # first try converting to numeric, if that fails, convert to string + try: + df[col] = pd.to_numeric(df[col], errors="raise") + except ValueError: + df[col] = df[col].astype(str) else: # Convert any other unsupported types to string df[col] = df[col].astype(str) @@ -216,6 +224,9 @@ def write_parquet(self, df, file_path, index, append=False): # therefore we are resetting the index into a column if we want to keep it # if we don't want to keep it, we are dropping it on write with index=False if index: + if df.index.name in df.columns: + # replace old index with new one + df.drop(columns=[df.index.name], inplace=True) df = df.reset_index(drop=False) if append and os.path.isfile(file_path): @@ -295,6 +306,9 @@ def write_table(df, table_name, index, append, bundle_directory, filetype): % (table_name, file_path) ) if filetype == "csv": + # check if index is in columns and drop it if so + if index and (df.index.name in df.columns): + df.drop(columns=df.index.name, inplace=True) df.to_csv(file_path, mode="a", index=index, header=(not file_exists)) elif filetype == "parquet": try: @@ -367,6 +381,9 @@ def write_omnibus_table(self): assert not os.path.isfile(file_path) self.debug(f"writing table: {file_path}") + # check if index is in columns and drop it if so + if df.index.name in df.columns: + df.drop(columns=df.index.name, inplace=True) df.to_csv(file_path, mode="a", index=True, header=True) elif filetype == "parquet": @@ -563,6 +580,18 @@ def melt_alternatives(self, df): # 31153,2,util_dist_0_1,1.0 # 31153,3,util_dist_0_1,1.0 + output_format = self.settings.get("EDB_ALTS_FILE_FORMAT", "verbose") + assert output_format in ["verbose", "compact"] + + if output_format == "compact": + # renumber the alt_id column to just count from 1 to n + # this loses the alt_id information, but drops all of the empty columns + # (can still get empty columns if not every chooser has same number of alts) + # (this can happen if the pick count > 1 and/or sampled alts are not included) + melt_df[alt_id_name] = melt_df.groupby([chooser_name, variable_column])[ + alt_id_name + ].cumcount() + melt_df = melt_df.set_index( [chooser_name, variable_column, alt_id_name] ).unstack(2) From cd3d07ea4fdad4883716117cb3519b2d38274276 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Wed, 25 Sep 2024 16:17:38 -0700 Subject: [PATCH 09/56] sorting dest choice bundles --- activitysim/abm/models/location_choice.py | 11 +++++++---- activitysim/core/estimation.py | 2 +- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/activitysim/abm/models/location_choice.py b/activitysim/abm/models/location_choice.py index 83e794b2be..98c01288c7 100644 --- a/activitysim/abm/models/location_choice.py +++ b/activitysim/abm/models/location_choice.py @@ -517,10 +517,13 @@ def run_location_sample( ["person_id", "alt_dest", "prob", "pick_count"] ].set_index("person_id") choices = choices.append(new_choices, ignore_index=False).sort_index() - # making probability the mean of all other sampled destinations by person - # FIXME is there a better way to do this? Does this even matter for estimation? - choices["prob"] = choices["prob"].fillna( - choices.groupby("person_id")["prob"].transform("mean") + # making prob 0 for missing rows so it does not influence model decision + choices["prob"] = choices["prob"].fillna(0) + # sort by person_id and alt_dest + choices = ( + choices.reset_index() + .sort_values(by=["person_id", "alt_dest"]) + .set_index("person_id") ) return choices diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 793f1e532b..84c9562ea8 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -571,7 +571,7 @@ def melt_alternatives(self, df): # mergesort is the only stable sort, and we want the expressions to appear in original df column order melt_df = ( pd.melt(df, id_vars=[chooser_name, alt_id_name]) - .sort_values(by=chooser_name, kind="mergesort") + .sort_values(by=[chooser_name, alt_id_name, "variable"], kind="mergesort") .rename(columns={"variable": variable_column}) ) From 8a1fa3c808aff85432ca568b62bc24addb05c6ee Mon Sep 17 00:00:00 2001 From: David Hensle Date: Wed, 25 Sep 2024 16:18:22 -0700 Subject: [PATCH 10/56] adding coalesce edbs as its own step --- activitysim/core/steps/output.py | 21 ++++++++++++++++++--- 1 file changed, 18 insertions(+), 3 deletions(-) diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index d4ebccdb3b..e8b5a4658d 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -259,7 +259,7 @@ def concat_and_write_edb(df_concat_dict, write_dir): raise ValueError(f"Unknown file type {table_name}") -def coalesce_estimation_data_bundles(state): +def _coalesce_estimation_data_bundles(state): """ In estimation mode, estimation data bundles are written to separate subdirectories for each subprocess. This model will go through each subdirectory and move the files to the parent directory. @@ -330,7 +330,7 @@ def coalesce_estimation_data_bundles(state): or is_size_terms_file ) - if is_duplicate_file and not is_same_edb: + if is_duplicate_file and not os.path.exists(os.path.join(cur_edb, file)): # copy the file to the parent directory shutil.copy(file_path, os.path.join(cur_edb, file)) @@ -572,6 +572,21 @@ def map_func(x): else: raise ValueError(f"unknown file_type {file_type}") + +@workflow.step +def coalesce_estimation_data_bundles(state: workflow.State) -> None: + """ + In estimation mode, estimation data bundles are written to separate subdirectories for each subprocess. + This model will go through each subdirectory and concat / copy the files to the parent directory. + This will only occur if the lowest level directory contains the multiprocess step names. + Only multiprocess step names are used because that's how EDBs are written in estimation mode. + + """ is_estimation = estimation_enabled(state) if state.settings.multiprocess and is_estimation: - coalesce_estimation_data_bundles(state) + _coalesce_estimation_data_bundles(state) + else: + logger.info( + "Not in estimation mode or not using multiprocess. Nothing to coalesce." + ) + return From e8c03e6b6fc95a5762ca06f435a2affe35e8b6f1 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 27 Sep 2024 16:45:52 -0700 Subject: [PATCH 11/56] CI testing initial commit --- .github/workflows/core_tests.yml | 53 ++++ activitysim/core/estimation.py | 8 +- activitysim/core/steps/output.py | 5 +- .../configs_estimation/.gitignore | 2 + .../estimation_template.yaml | 129 ++++++++ .../configs_estimation/logging.yaml | 67 +++++ .../configs_estimation/settings_template.yaml | 165 +++++++++++ .../test/test_edb_creation/outputs/.gitignore | 1 + .../survey_data/final_households.csv | 51 ++++ .../final_joint_tour_participants.csv | 8 + .../survey_data/final_persons.csv | 91 ++++++ .../survey_data/final_tours.csv | 118 ++++++++ .../survey_data/final_trips.csv | 278 ++++++++++++++++++ .../survey_data/override_households.csv | 51 ++++ .../override_joint_tour_participants.csv | 8 + .../survey_data/override_persons.csv | 91 ++++++ .../survey_data/override_tours.csv | 118 ++++++++ .../survey_data/override_trips.csv | 278 ++++++++++++++++++ .../survey_data/survey_households.csv | 51 ++++ .../survey_joint_tour_participants.csv | 8 + .../survey_data/survey_persons.csv | 91 ++++++ .../survey_data/survey_tours.csv | 118 ++++++++ .../survey_data/survey_trips.csv | 278 ++++++++++++++++++ .../test_edb_creation/test_edb_formation.py | 263 +++++++++++++++++ .../example_estimation/scripts/infer.py | 12 +- 25 files changed, 2338 insertions(+), 5 deletions(-) create mode 100644 activitysim/estimation/test/test_edb_creation/configs_estimation/.gitignore create mode 100644 activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml create mode 100644 activitysim/estimation/test/test_edb_creation/configs_estimation/logging.yaml create mode 100644 activitysim/estimation/test/test_edb_creation/configs_estimation/settings_template.yaml create mode 100644 activitysim/estimation/test/test_edb_creation/outputs/.gitignore create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/final_households.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/final_joint_tour_participants.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/final_persons.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/final_tours.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/final_trips.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/override_households.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/override_joint_tour_participants.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/override_persons.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/override_tours.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/override_trips.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/survey_households.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/survey_joint_tour_participants.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/survey_persons.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/survey_tours.csv create mode 100644 activitysim/estimation/test/test_edb_creation/survey_data/survey_trips.csv create mode 100644 activitysim/estimation/test/test_edb_creation/test_edb_formation.py diff --git a/.github/workflows/core_tests.yml b/.github/workflows/core_tests.yml index 134242cd67..6c95140e4e 100644 --- a/.github/workflows/core_tests.yml +++ b/.github/workflows/core_tests.yml @@ -438,6 +438,59 @@ jobs: - name: Test Estimation Mode run: | python -m pytest activitysim/estimation/test/test_larch_estimation.py --durations=0 + + + estimation_edb_creation: + needs: foundation + env: + python-version: "3.10" + label: linux-64 + defaults: + run: + shell: bash -l {0} + name: estimation_edb_creation_test + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Setup Mambaforge + uses: conda-incubator/setup-miniconda@v3 + with: + miniforge-variant: Mambaforge + miniforge-version: latest + activate-environment: asim-test + use-mamba: true + python-version: ${{ env.python-version }} + + - name: Set cache date for year and month + run: echo "DATE=$(date +'%Y%m')" >> $GITHUB_ENV + + - uses: actions/cache@v4 + with: + path: ${{ env.CONDA }}/envs + key: ${{ env.label }}-conda-${{ hashFiles('conda-environments/github-actions-tests.yml') }}-${{ env.DATE }}-${{ env.CACHE_NUMBER }} + id: cache + + - name: Update environment + run: | + mamba env update -n asim-test -f conda-environments/github-actions-tests.yml + if: steps.cache.outputs.cache-hit != 'true' + + - name: Install activitysim + # installing without dependencies is faster, we trust that all needed dependencies + # are in the conda environment defined above. Also, this avoids pip getting + # confused and reinstalling tables (pytables). + run: | + python -m pip install -e . --no-deps + + - name: Conda checkup + run: | + mamba info -a + mamba list + + - name: Test Estimation EDB Creation + run: | + python -m pytest activitysim/estimation/test/test_edb_creation/test_edb_formation.py --durations=0 develop-docbuild: needs: foundation diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 84c9562ea8..b79618509b 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -73,12 +73,11 @@ def __init__( os.makedirs(output_dir) # make directory if needed # delete estimation files - unlink_files(self.output_directory(), file_types=("csv", "yaml", "parquet")) + unlink_files(self.output_directory()) if self.bundle_name != self.model_name: # kind of inelegant to always delete these, but ok as they are redundantly recreated for each sub model unlink_files( self.output_directory(bundle_directory=True), - file_types=("csv", "yaml", "parquet"), ) # FIXME - not required? @@ -243,6 +242,9 @@ def write_pickle(self, df, file_path, index, append=False): # therefore we are resetting the index into a column if we want to keep it # if we don't want to keep it, we are dropping it on write with index=False if index: + if df.index.name in df.columns: + # replace old index with new one + df.drop(columns=[df.index.name], inplace=True) df = df.reset_index(drop=False) else: df = df.reset_index(drop=True) @@ -251,7 +253,7 @@ def write_pickle(self, df, file_path, index, append=False): append == True ), f"file already exists: {file_path}" - if append: + if append and os.path.isfile(file_path): # read the previous df and concat prev_df = pd.read_pickle(file_path) df = pd.concat([prev_df, df]) diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index e8b5a4658d..8875033472 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -304,7 +304,7 @@ def _coalesce_estimation_data_bundles(state): if ( (not is_same_edb) and (len(df_concat_dict) > 0) - and (len(df_concat_dict[list(df_concat_dict.keys())[0]]) > 1) + # and (len(df_concat_dict[list(df_concat_dict.keys())[0]]) > 1) ): concat_and_write_edb(df_concat_dict, prev_edb) @@ -313,6 +313,9 @@ def _coalesce_estimation_data_bundles(state): df_concat_dict = {} for i, file in enumerate(os.listdir(dir)): + + if "stop_frequency" in file: + print("debugging") # get the file path file_path = os.path.join(dir, file) diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/.gitignore b/activitysim/estimation/test/test_edb_creation/configs_estimation/.gitignore new file mode 100644 index 0000000000..e767d25cef --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/.gitignore @@ -0,0 +1,2 @@ +settings.yaml +estimation.yaml \ No newline at end of file diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml new file mode 100644 index 0000000000..7bf21b93ba --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml @@ -0,0 +1,129 @@ +EDB_ALTS_FILE_FORMAT: compact +EDB_FILETYPE: csv + +enable: True + +bundles: + - school_location + - workplace_location + - auto_ownership + - vehicle_type_choice + - free_parking + - cdap + - mandatory_tour_frequency + - mandatory_tour_scheduling_work + - mandatory_tour_scheduling_school + - joint_tour_frequency + - joint_tour_composition + - joint_tour_participation + - joint_tour_destination + - joint_tour_scheduling + - non_mandatory_tour_frequency + - non_mandatory_tour_destination + - non_mandatory_tour_scheduling + - tour_mode_choice + - atwork_subtour_frequency + - atwork_subtour_destination + - atwork_subtour_scheduling + - atwork_subtour_mode_choice + - stop_frequency + - trip_purpose + - trip_destination + - trip_scheduling + - trip_mode_choice + +# - atwork_subtour_mode_choice subtours.tour_mode + +survey_tables: + households: + file_name: override_households.csv + index_col: household_id + persons: + file_name: override_persons.csv + index_col: person_id + tours: + file_name: override_tours.csv + index_col: tour_id + joint_tour_participants: + file_name: override_joint_tour_participants.csv + index_col: participant_id + trips: + file_name: override_trips.csv + index_col: trip_id + +estimation_table_recipes: + + interaction_sample_simulate: + omnibus_tables: + choosers_combined: + - choices + - override_choices + - choosers + alternatives_combined: + - interaction_sample_alternatives + - interaction_expression_values + omnibus_tables_append_columns: [choosers_combined] + + interaction_simulate: + omnibus_tables: + choosers_combined: + - choices + - override_choices + - choosers + omnibus_tables_append_columns: [choosers_combined] + + simple_simulate: + omnibus_tables: + values_combined: + - choices + - override_choices + - expression_values + - choosers + omnibus_tables_append_columns: [values_combined] + + cdap_simulate: + omnibus_tables: + values_combined: + - choices + - override_choices + - choosers + omnibus_tables_append_columns: [values_combined] + + simple_probabilistic: + omnibus_tables: + values_combined: + - choices + - override_choices + - choosers + - probs + omnibus_tables_append_columns: [values_combined] + + +model_estimation_table_types: + school_location: interaction_sample_simulate + workplace_location: interaction_sample_simulate + auto_ownership: simple_simulate + vehicle_type_choice: interaction_simulate + free_parking: simple_simulate + cdap: cdap_simulate + mandatory_tour_frequency: simple_simulate + mandatory_tour_scheduling_work: interaction_sample_simulate + mandatory_tour_scheduling_school: interaction_sample_simulate + joint_tour_frequency: simple_simulate + joint_tour_composition: simple_simulate + joint_tour_participation: simple_simulate + joint_tour_destination: interaction_sample_simulate + joint_tour_scheduling: interaction_sample_simulate + non_mandatory_tour_frequency: interaction_simulate + non_mandatory_tour_destination: interaction_sample_simulate + non_mandatory_tour_scheduling: interaction_sample_simulate + tour_mode_choice: simple_simulate + atwork_subtour_frequency: simple_simulate + atwork_subtour_destination: interaction_sample_simulate + atwork_subtour_scheduling: interaction_sample_simulate + atwork_subtour_mode_choice: simple_simulate + stop_frequency: simple_simulate + trip_purpose: simple_probabilistic + trip_destination: interaction_sample_simulate + trip_scheduling: simple_probabilistic + trip_mode_choice: simple_simulate diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/logging.yaml b/activitysim/estimation/test/test_edb_creation/configs_estimation/logging.yaml new file mode 100644 index 0000000000..f4902943d6 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/logging.yaml @@ -0,0 +1,67 @@ +# Config for logging +# ------------------ +# See http://docs.python.org/2.7/library/logging.config.html#configuration-dictionary-schema + +logging: + version: 1 + disable_existing_loggers: true + + + # Configuring the default (root) logger is highly recommended + root: + level: NOTSET + handlers: [console, logfile, elogfile] + + loggers: + + estimation: + level: DEBUG + handlers: [console, elogfile] + propagate: false + + activitysim: + level: INFO + handlers: [console, logfile] + propagate: false + + orca: + level: WARN + handlers: [console, logfile] + propagate: false + + handlers: + + elogfile: + class: logging.FileHandler + filename: + get_log_file_path: 'estimation.log' + mode: w + formatter: fileFormatter + level: NOTSET + + logfile: + class: logging.FileHandler + filename: + get_log_file_path: 'activitysim.log' + mode: w + formatter: fileFormatter + level: NOTSET + + console: + class: logging.StreamHandler + stream: ext://sys.stdout + formatter: simpleFormatter + level: NOTSET + + formatters: + + simpleFormatter: + class: logging.Formatter + # format: '%(levelname)s - %(name)s - %(message)s' + format: '%(levelname)s - %(message)s' + datefmt: '%d/%m/%Y %H:%M:%S' + + fileFormatter: + class: logging.Formatter + format: '%(asctime)s - %(levelname)s - %(name)s - %(message)s' + datefmt: '%d/%m/%Y %H:%M:%S' diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/settings_template.yaml b/activitysim/estimation/test/test_edb_creation/configs_estimation/settings_template.yaml new file mode 100644 index 0000000000..75b9720c75 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/settings_template.yaml @@ -0,0 +1,165 @@ + +inherit_settings: True + +# assume enough RAM to not chunk +chunk_training_mode: disabled + +# input tables +input_table_list: + # + # households (table index 'household_id') + # + - tablename: households + filename: override_households.csv + index_col: household_id + keep_columns: + - home_zone_id + - income + - hhsize + - HHT + - auto_ownership + - num_workers + # + # persons (table index 'person_id') + # + - tablename: persons + filename: override_persons.csv + keep_columns: + - household_id + - age + - PNUM + - sex + - pemploy + - pstudent + - ptype + # + # land_use (table index 'zone_id') + # + - tablename: land_use + filename: land_use.csv + rename_columns: + # accept either TAZ or ZONE (but not both) + TAZ: zone_id + ZONE: zone_id + COUNTY: county_id + keep_columns: + - DISTRICT + - SD + - county_id + - TOTHH + - TOTPOP + - TOTACRE + - RESACRE + - CIACRE + - TOTEMP + - AGE0519 + - RETEMPN + - FPSEMPN + - HEREMPN + - OTHEMPN + - AGREMPN + - MWTEMPN + - PRKCST + - OPRKCST + - area_type + - HSENROLL + - COLLFTE + - COLLPTE + - TOPOLOGY + - TERMINAL + +write_raw_tables: False +rng_base_seed: 0 + +fail_fast: True + +use_shadow_pricing: False + +# turn writing of sample_tables on and off for all models +# (if True, tables will be written if DEST_CHOICE_SAMPLE_TABLE_NAME is specified in individual model settings) +want_dest_choice_sample_tables: False + +# number of households to simulate +households_sample_size: 0 + +# to resume after last successful checkpoint, specify resume_after: _ +#resume_after: initialize_households + +trace_hh_id: + +multiprocess: false +num_processes: 2 + + +output_tables: + h5_store: False + action: include + prefix: final_ + sort: True + tables: + - checkpoints + - accessibility + - land_use + - households + - persons + - tours + - trips + - joint_tour_participants + +resume_after: + +models: + - initialize_landuse + - initialize_households + - compute_accessibility + - school_location + - workplace_location + - auto_ownership_simulate + - free_parking + - cdap_simulate + - mandatory_tour_frequency + - mandatory_tour_scheduling + - joint_tour_frequency + - joint_tour_composition + - joint_tour_participation + - joint_tour_destination + - joint_tour_scheduling + - non_mandatory_tour_frequency + - non_mandatory_tour_destination + - non_mandatory_tour_scheduling + - tour_mode_choice_simulate + - atwork_subtour_frequency + - atwork_subtour_destination + - atwork_subtour_scheduling + - atwork_subtour_mode_choice + - stop_frequency + - trip_purpose + - trip_destination +# - trip_purpose_and_destination + - trip_scheduling + - trip_mode_choice +# - write_data_dictionary +# - track_skim_usage +# - write_trip_matrices + - write_tables + - coalesce_estimation_data_bundles + + +multiprocess_steps: + - name: mp_initialize + begin: initialize_landuse + - name: mp_accessibility + begin: compute_accessibility + slice: + tables: + - accessibility + # don't slice any tables not explicitly listed above in slice.tables + exclude: True + - name: mp_households + begin: school_location + slice: + tables: + - households + - persons + - name: mp_summarize + begin: write_tables \ No newline at end of file diff --git a/activitysim/estimation/test/test_edb_creation/outputs/.gitignore b/activitysim/estimation/test/test_edb_creation/outputs/.gitignore new file mode 100644 index 0000000000..5ed517c37a --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/outputs/.gitignore @@ -0,0 +1 @@ +/output*/ \ No newline at end of file diff --git a/activitysim/estimation/test/test_edb_creation/survey_data/final_households.csv b/activitysim/estimation/test/test_edb_creation/survey_data/final_households.csv new file mode 100644 index 0000000000..c91fceec9d --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/survey_data/final_households.csv @@ -0,0 +1,51 @@ 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b/activitysim/estimation/test/test_edb_creation/survey_data/final_joint_tour_participants.csv new file mode 100644 index 0000000000..7e7029f731 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/survey_data/final_joint_tour_participants.csv @@ -0,0 +1,8 @@ +"tour_id","household_id","person_id","participant_num","participant_id" +220958279,2223759,5389226,1,22095827901 +220958279,2223759,5389227,2,22095827902 +100798519,1173905,2458502,1,10079851903 +100798519,1173905,2458503,2,10079851904 +130727777,1402945,3188483,1,13072777702 +130727777,1402945,3188484,2,13072777703 +130727777,1402945,3188485,3,13072777704 diff --git a/activitysim/estimation/test/test_edb_creation/survey_data/final_persons.csv b/activitysim/estimation/test/test_edb_creation/survey_data/final_persons.csv new file mode 100644 index 0000000000..edfe675874 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/survey_data/final_persons.csv @@ -0,0 +1,91 @@ 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b/activitysim/estimation/test/test_edb_creation/survey_data/override_households.csv new file mode 100644 index 0000000000..b0910c7860 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/survey_data/override_households.csv @@ -0,0 +1,51 @@ +household_id,home_zone_id,income,hhsize,HHT,auto_ownership,num_workers,joint_tour_frequency +982875,16,30900,2,5,1,2,0_tours +1810015,16,99700,9,2,1,4,0_tours +1099626,20,58160,3,1,1,1,0_tours +763879,6,59220,1,4,1,0,0_tours +824207,18,51000,1,4,0,1,0_tours +2822230,8,0,1,0,0,1,0_tours +2821179,8,0,1,0,0,1,0_tours +1196298,25,31360,5,1,0,1,0_tours +1363467,24,58300,2,2,1,1,0_tours +386761,16,21000,3,1,1,2,0_tours +2223027,9,133000,2,1,0,2,0_tours +2832182,7,0,1,0,0,0,0_tours +2727273,20,118800,2,1,1,2,0_tours +1444715,14,60000,1,4,0,1,0_tours +112064,16,18000,1,6,1,1,0_tours +1952792,14,61900,1,4,1,1,0_tours +2223759,16,144100,2,1,0,2,1_Eat +2820538,8,0,1,0,0,1,0_tours +27726,10,24000,1,4,0,0,0_tours +570454,21,1500,1,4,0,0,0_tours 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a/activitysim/estimation/test/test_edb_creation/survey_data/override_joint_tour_participants.csv b/activitysim/estimation/test/test_edb_creation/survey_data/override_joint_tour_participants.csv new file mode 100644 index 0000000000..a19d8616a2 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/survey_data/override_joint_tour_participants.csv @@ -0,0 +1,8 @@ +survey_participant_id,survey_tour_id,household_id,person_id,participant_num,tour_id,participant_id +220958279010,2209582790,2223759,5389226,1,220958279,22095827901 +220958279020,2209582790,2223759,5389227,2,220958279,22095827902 +100798519030,1007985190,1173905,2458502,1,100798519,10079851903 +100798519040,1007985190,1173905,2458503,2,100798519,10079851904 +130727777020,1307277770,1402945,3188483,1,130727777,13072777702 +130727777030,1307277770,1402945,3188484,2,130727777,13072777703 +130727777040,1307277770,1402945,3188485,3,130727777,13072777704 diff --git a/activitysim/estimation/test/test_edb_creation/survey_data/override_persons.csv b/activitysim/estimation/test/test_edb_creation/survey_data/override_persons.csv new file mode 100644 index 0000000000..030bcafa71 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/survey_data/override_persons.csv @@ -0,0 +1,91 @@ +person_id,household_id,age,PNUM,sex,pemploy,pstudent,ptype,school_zone_id,workplace_zone_id,free_parking_at_work,cdap_activity,mandatory_tour_frequency,_escort,_shopping,_othmaint,_othdiscr,_eatout,_social,non_mandatory_tour_frequency +26686,26686,39,1,1,3,3,4,-1,-1,False,N,,0,0,1,0,1,0,12 +26844,26844,51,1,1,3,3,4,-1,-1,False,N,,0,0,0,0,0,1,2 +27726,27726,52,1,1,3,3,4,-1,-1,False,N,,0,0,0,1,0,0,1 +29625,29625,61,1,1,3,3,4,-1,-1,False,N,,0,1,0,0,0,0,16 +110675,110675,30,1,1,2,3,2,-1,19,False,H,,0,0,0,0,0,0,0 +112064,112064,48,1,2,2,3,2,-1,21,False,N,,0,1,0,1,0,0,17 +264107,226869,28,1,1,2,3,2,-1,24,False,M,work1,0,0,0,0,0,0,0 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+143309067,1433090670,3495343,1594621,eat,atwork,16,9,14,14,WALK,1433091020.0,143309102.0,,135,,3out_0in +171036547,1710365470,4171623,1810015,eat,atwork,7,21,10,10,WALK,1710365820.0,171036582.0,,85,,0out_1in +220958270,2209582700,5389226,2223759,eat,atwork,2,1,13,13,WALK,2209583050.0,220958305.0,,124,,0out_0in +307996473,3079964730,7512109,2820774,eat,atwork,8,2,10,10,WALK,3079965080.0,307996508.0,,85,,0out_1in diff --git a/activitysim/estimation/test/test_edb_creation/survey_data/override_trips.csv b/activitysim/estimation/test/test_edb_creation/survey_data/override_trips.csv new file mode 100644 index 0000000000..e2f36dab74 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/survey_data/override_trips.csv @@ -0,0 +1,278 @@ +trip_id,survey_trip_id,person_id,household_id,survey_tour_id,outbound,purpose,destination,origin,depart,trip_mode,tour_id,trip_num +8753057,87530570,26686,26686,10941320,True,eatout,5,8,19,WALK,1094132,1 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b/activitysim/estimation/test/test_edb_creation/test_edb_formation.py @@ -0,0 +1,263 @@ +import os +import pandas as pd +import numpy as np +import pandas.testing as pdt +import yaml + + +configs_estimation_dir = ( + "activitysim/estimation/test/test_edb_creation/configs_estimation" +) +configs_dir = "activitysim/examples/prototype_mtc/configs" +survey_data_dir = "activitysim/estimation/test/test_edb_creation/survey_data" +data_dir = "activitysim/examples/prototype_mtc/data" +base_output_dir = "activitysim/estimation/test/test_edb_creation/outputs" + + +def launch_est_example(output_dir, multiprocess, fileformat): + + # setting multiprocess setting + settings_template_file = os.path.join( + configs_estimation_dir, "settings_template.yaml" + ) + settings_file = os.path.join(configs_estimation_dir, "settings.yaml") + settings = yaml.safe_load(open(settings_template_file)) + assert multiprocess in [True, False] + settings["multiprocess"] = multiprocess + yaml.dump(settings, open(settings_file, "w")) + + # setting fileformat setting + settings_template_file = os.path.join( + configs_estimation_dir, "estimation_template.yaml" + ) + est_settings_file = os.path.join(configs_estimation_dir, "estimation.yaml") + est_settings = yaml.safe_load(open(settings_template_file)) + assert fileformat in ["csv", "parquet", "pkl"] + est_settings["EDB_FILETYPE"] = fileformat + yaml.dump(est_settings, open(est_settings_file, "w")) + + run_cmd = f"activitysim run -c {configs_estimation_dir} -c {configs_dir} -d {survey_data_dir} -d {data_dir} -o {base_output_dir}/{output_dir}" + print( + f"launching with options output_dir={output_dir} multiprocess={multiprocess} fileformat={fileformat}" + ) + print("launching from ", os.getcwd()) + result = os.system(run_cmd) + assert result == 0, "ActivitySim run failed" + + +def read_table(file_name): + if file_name.endswith(".csv"): + return pd.read_csv(file_name, low_memory=False) + elif file_name.endswith(".parquet"): + df = pd.read_parquet(file_name).reset_index(drop=True) + df.columns.name = None + return df + elif file_name.endswith(".pkl"): + df = pd.read_pickle(file_name).reset_index(drop=True) + df.columns = df.columns.astype(str) + df.columns.name = None + return df + else: + raise ValueError(f"Unsupported file format: {file_name}") + + +def process_table(df): + if "variable" == df.columns[1]: + # need to sort variable column + df = df.sort_values(by=[df.columns[0], "variable"]).reset_index(drop=True) + df.columns.name = None + + if "chunk_id" in df.columns: + # remove chunk_id column + df = df.drop(columns=["chunk_id"]) + + return df + + +def find_lowest_level_directories(starting_directory): + lowest_dirs = list() + + for root, dirs, files in os.walk(starting_directory): + if not dirs: + lowest_dirs.append(root) + + return lowest_dirs + + +def try_compare_with_same_dtypes(ser1, ser2, rtol, atol): + try: + concatenated = pd.concat([ser1, ser2]) + common_type = concatenated.dtype + pdt.assert_series_equal( + ser1.astype(common_type), + ser2.astype(common_type), + check_dtype=False, + rtol=rtol, + atol=atol, + ) + except (ValueError, AssertionError) as e: + return False + return True + + +def try_compare_with_numeric(ser1, ser2, rtol, atol): + try: + ser1_num = pd.to_numeric(ser1, errors="coerce") + ser2_num = pd.to_numeric(ser2, errors="coerce") + pdt.assert_series_equal( + ser1_num, ser2_num, check_dtype=False, rtol=rtol, atol=atol + ) + except AssertionError as e: + return False + return True + + +def try_compare_with_strings(ser1, ser2): + try: + pdt.assert_series_equal(ser1.astype(str), ser2.astype(str), check_dtype=False) + except AssertionError as e: + return False + return True + + +def try_compare_with_combination(ser1, ser2, rtol=1e-5, atol=1e-8): + """ + This is necessary because we have columns like this: + [index]: [0, 1, 2, 3, 4, 5, ...] + [left]: [False, False, 1, 6, AM, -1.3037984712857993, EA, ...] + [right]: [False, False, 1, 6, AM, -1.3037984712857994, EA, ...] + (notice the machine precision difference in the float) + """ + # replace annoying string values of bools + ser1 = ser1.replace({"True": True, "False": False}) + ser2 = ser2.replace({"True": True, "False": False}) + # Separate numerical and non-numerical values + ser1_num = pd.to_numeric(ser1, errors="coerce") + ser2_num = pd.to_numeric(ser2, errors="coerce") + ser1_non_num = ser1[ser1_num.isna()] + ser2_non_num = ser2[ser2_num.isna()] + ser1_num = ser1_num.dropna() + ser2_num = ser2_num.dropna() + try: + pdt.assert_series_equal( + ser1_num, ser2_num, check_dtype=False, rtol=rtol, atol=atol + ) + pdt.assert_series_equal(ser1_non_num, ser2_non_num, check_dtype=False) + except AssertionError as e: + return False + return True + + +def compare_dataframes_with_tolerance(df1, df2, rtol=1e-3, atol=1e-3): + dfs_are_same = True + e_msg = "" + try: + pdt.assert_frame_equal(df1, df2, check_dtype=False, rtol=rtol, atol=atol) + return dfs_are_same, e_msg + except AssertionError as e: + print(e) + print("trying to compare columns individually") + for col in df1.columns: + try: + if try_compare_with_same_dtypes(df1[col], df2[col], rtol, atol): + continue + elif try_compare_with_numeric(df1[col], df2[col], rtol, atol): + continue + elif try_compare_with_strings(df1[col], df2[col]): + continue + elif try_compare_with_combination( + df1[col], df2[col], rtol=rtol, atol=atol + ): + continue + else: + dfs_are_same = False + e_msg += f"Column '{col}' failed: {df1[col]} vs {df2[col]}\n" + print(f"Column '{col}' failed:\n {df1[col]} vs {df2[col]}\n") + except Exception as e: + dfs_are_same = False + e_msg = e + + return dfs_are_same, e_msg + + +def regress_EDBs(regress_folder, output_folder, fileformat="csv"): + edb_file = os.path.join(base_output_dir, regress_folder, "estimation_data_bundle") + + edb_dirs = find_lowest_level_directories(edb_file) + + for dir in edb_dirs: + dir_basename = dir.split("estimation_data_bundle")[1][1:] + output_dir = os.path.join( + base_output_dir, output_folder, "estimation_data_bundle", dir_basename + ) + + for file in os.listdir(dir): + if file.endswith(".yaml"): + continue + print(f"Regressing {file}") + + regress_path = os.path.join(dir, file) + output_path = os.path.join(output_dir, file) + + # regress against csv for parquet, but regress against parquet for pkl (faster) + if not os.path.exists(output_path) and (fileformat == "parquet"): + output_path = output_path.replace(".csv", ".parquet") + if not os.path.exists(output_path) and (fileformat == "pkl"): + output_path = output_path.replace(".parquet", ".pkl") + + try: + regress_df = read_table(regress_path) + output_df = read_table(output_path) + except FileNotFoundError as e: + assert False, f"File not found: {e}" + + regress_df = process_table(regress_df) + output_df = process_table(output_df) + + dfs_are_same, e = compare_dataframes_with_tolerance(regress_df, output_df) + if not dfs_are_same: + assert False, f"Regression test failed for {file} with error: {e}" + return + + +def test_generating_sp_csv(): + # first generate original tables + output_dir = "output_single_csv" + launch_est_example(output_dir, False, "csv") + + +def test_sp_parquet(): + # multiprocess = False, fileformat = "parquet" + output_dir = "output_single_parquet" + launch_est_example(output_dir, False, "parquet") + regress_EDBs("output_single_csv", output_dir, "parquet") + + +def test_sp_pkl(): + # multiprocess = False, fileformat = "pkl" + output_dir = "output_single_pkl" + launch_est_example(output_dir, False, "pkl") + regress_EDBs("output_single_parquet", output_dir, "pkl") + + +def test_mp_parquet(): + # multiprocess = True, fileformat = "parquet" + output_dir = "output_multiprocess_parquet" + launch_est_example(output_dir, True, "parquet") + regress_EDBs("output_single_parquet", output_dir, "parquet") + + +# def test_mp_csv(): +# # multiprocess = True, fileformat = "csv" +# output_dir = "output_multiprocess_csv" +# launch_est_example(output_dir, True, "csv") +# regress_EDBs("output_single_csv", output_dir, "csv") + + +if __name__ == "__main__": + + test_generating_sp_csv() + test_sp_parquet() + test_mp_parquet() + # test_mp_csv() + test_sp_pkl() diff --git a/activitysim/examples/example_estimation/scripts/infer.py b/activitysim/examples/example_estimation/scripts/infer.py index 6b6991992f..ab9def6429 100644 --- a/activitysim/examples/example_estimation/scripts/infer.py +++ b/activitysim/examples/example_estimation/scripts/infer.py @@ -165,6 +165,7 @@ def read_alts(): alts = read_alts() tour_types = list(alts.columns.values) + tour_types.remove("tot_tours") # tour_frequency is index in alts table alts["alt_id"] = alts.index @@ -806,7 +807,7 @@ def infer(state: workflow.State, configs_dir, input_dir, output_dir): assert skip_controls or check_controls("joint_tour_participants", "index") # patch_tour_ids - trips = patch_trip_ids(tours, trips) + trips = patch_trip_ids(state, tours, trips) survey_tables["trips"]["table"] = trips # so we can check_controls assert skip_controls or check_controls("trips", "index") @@ -860,4 +861,13 @@ def infer(state: workflow.State, configs_dir, input_dir, output_dir): if apply_controls: read_tables(input_dir, control_tables) +state = ( + workflow.State() + .initialize_filesystem( + configs_dir=(configs_dir,), + output_dir=output_dir, + data_dir=(data_dir,), + ) + .load_settings() +) infer(state, configs_dir, input_dir, output_dir) From 8d80e2e92b5ce38cb7ca09d7b8425ad45a7de557 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Mon, 7 Oct 2024 14:14:47 -0700 Subject: [PATCH 12/56] infer.py CI testing --- .../test/test_edb_creation/outputs/.gitignore | 3 +- .../outputs/infer_output/.gitignore | 1 + .../test_edb_creation/test_edb_formation.py | 31 +++++++++++++------ .../example_estimation/scripts/infer.py | 4 +-- 4 files changed, 27 insertions(+), 12 deletions(-) create mode 100644 activitysim/estimation/test/test_edb_creation/outputs/infer_output/.gitignore diff --git a/activitysim/estimation/test/test_edb_creation/outputs/.gitignore b/activitysim/estimation/test/test_edb_creation/outputs/.gitignore index 5ed517c37a..08194de49b 100644 --- a/activitysim/estimation/test/test_edb_creation/outputs/.gitignore +++ b/activitysim/estimation/test/test_edb_creation/outputs/.gitignore @@ -1 +1,2 @@ -/output*/ \ No newline at end of file +/output*/ +*.csv \ No newline at end of file diff --git a/activitysim/estimation/test/test_edb_creation/outputs/infer_output/.gitignore b/activitysim/estimation/test/test_edb_creation/outputs/infer_output/.gitignore new file mode 100644 index 0000000000..16f2dc5fa9 --- /dev/null +++ b/activitysim/estimation/test/test_edb_creation/outputs/infer_output/.gitignore @@ -0,0 +1 @@ +*.csv \ No newline at end of file diff --git a/activitysim/estimation/test/test_edb_creation/test_edb_formation.py b/activitysim/estimation/test/test_edb_creation/test_edb_formation.py index 81a803647d..9268ef41a2 100644 --- a/activitysim/estimation/test/test_edb_creation/test_edb_formation.py +++ b/activitysim/estimation/test/test_edb_creation/test_edb_formation.py @@ -220,6 +220,26 @@ def regress_EDBs(regress_folder, output_folder, fileformat="csv"): return +def test_infer(): + infer_file = r"activitysim/examples/example_estimation/scripts/infer.py" + data_dir = r"activitysim/estimation/test/test_edb_creation" + configs_dir = r"activitysim/examples/prototype_mtc/configs" + output_dir = r"activitysim/estimation/test/test_edb_creation/outputs/infer_output" + run_cmd = f"python {infer_file} {data_dir} {configs_dir} {output_dir}" + print(f"launching {run_cmd} from {os.getcwd()}") + result = os.system(run_cmd) + assert result == 0, "Infer.py run failed" + + for file in os.listdir(output_dir): + if not file.endswith(".csv"): + continue + print("Regressing ", file) + regress_df = pd.read_csv(os.path.join(data_dir, "survey_data", file)) + output_df = pd.read_csv(os.path.join(output_dir, file)) + + pdt.assert_frame_equal(regress_df, output_df) + + def test_generating_sp_csv(): # first generate original tables output_dir = "output_single_csv" @@ -247,17 +267,10 @@ def test_mp_parquet(): regress_EDBs("output_single_parquet", output_dir, "parquet") -# def test_mp_csv(): -# # multiprocess = True, fileformat = "csv" -# output_dir = "output_multiprocess_csv" -# launch_est_example(output_dir, True, "csv") -# regress_EDBs("output_single_csv", output_dir, "csv") - - if __name__ == "__main__": + test_infer() test_generating_sp_csv() + test_sp_pkl() test_sp_parquet() test_mp_parquet() - # test_mp_csv() - test_sp_pkl() diff --git a/activitysim/examples/example_estimation/scripts/infer.py b/activitysim/examples/example_estimation/scripts/infer.py index ab9def6429..02fbd97d8f 100644 --- a/activitysim/examples/example_estimation/scripts/infer.py +++ b/activitysim/examples/example_estimation/scripts/infer.py @@ -847,16 +847,16 @@ def infer(state: workflow.State, configs_dir, input_dir, output_dir): # python infer.py data args = sys.argv[1:] -assert len(args) == 2, "usage: python infer.py " +assert len(args) == 3, "usage: python infer.py " data_dir = args[0] configs_dir = args[1] +output_dir = args[2] with open(os.path.join(configs_dir, "constants.yaml")) as stream: CONSTANTS = yaml.load(stream, Loader=yaml.SafeLoader) input_dir = os.path.join(data_dir, "survey_data/") -output_dir = input_dir if apply_controls: read_tables(input_dir, control_tables) From 1459e485dc54995a18d7769102d97cdf7b78c4c5 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Tue, 8 Oct 2024 11:00:15 -0700 Subject: [PATCH 13/56] estimation sampling for non-mandatory and joint tours --- .../abm/models/util/tour_destination.py | 49 ++++++++++++++++--- .../estimation_template.yaml | 4 +- 2 files changed, 44 insertions(+), 9 deletions(-) diff --git a/activitysim/abm/models/util/tour_destination.py b/activitysim/abm/models/util/tour_destination.py index 0891b8d216..8feb6d55d8 100644 --- a/activitysim/abm/models/util/tour_destination.py +++ b/activitysim/abm/models/util/tour_destination.py @@ -9,7 +9,7 @@ from activitysim.abm.models.util import logsums as logsum from activitysim.abm.tables.size_terms import tour_destination_size_terms -from activitysim.core import config, los, simulate, tracing, workflow +from activitysim.core import estimation, config, los, simulate, tracing, workflow from activitysim.core.configuration.logit import TourLocationComponentSettings from activitysim.core.interaction_sample import interaction_sample from activitysim.core.interaction_sample_simulate import interaction_sample_simulate @@ -87,15 +87,17 @@ def _destination_sample( logger.info("running %s with %d tours", trace_label, len(choosers)) sample_size = model_settings.SAMPLE_SIZE - if state.settings.disable_destination_sampling or ( - estimator and estimator.want_unsampled_alternatives - ): - # FIXME interaction_sample will return unsampled complete alternatives with probs and pick_count + if estimator: + sample_size = model_settings.ESTIMATION_SAMPLE_SIZE logger.info( - "Estimation mode for %s using unsampled alternatives short_circuit_choices" - % (trace_label,) + f"Estimation mode for {trace_label} using sample size of {sample_size}" ) + + if state.settings.disable_destination_sampling: sample_size = 0 + logger.info( + f"SAMPLE_SIZE set to 0 for {trace_label} because disable_destination_sampling is set" + ) locals_d = { "skims": skims, @@ -179,6 +181,39 @@ def destination_sample( trace_label=trace_label, ) + # adding observed choice to alt set when running in estimation mode + if estimator: + # grabbing survey values + survey_tours = estimation.manager.get_survey_table("tours") + survey_choices = survey_tours[["destination", "person_id"]].reset_index() + survey_choices.columns = ["tour_id", alt_dest_col_name, "person_id"] + survey_choices = survey_choices[ + survey_choices["tour_id"].isin(choices.index) + & (survey_choices[alt_dest_col_name] > 0) + ] + # merging survey destination into table if not available + joined_data = survey_choices.merge( + choices, + on=["tour_id", alt_dest_col_name, "person_id"], + how="left", + indicator=True, + ) + missing_rows = joined_data[joined_data["_merge"] == "left_only"] + missing_rows["pick_count"] = 1 + if len(missing_rows) > 0: + new_choices = missing_rows[ + ["tour_id", alt_dest_col_name, "prob", "pick_count", "person_id"] + ].set_index("tour_id") + choices = choices.append(new_choices, ignore_index=False).sort_index() + # making prob 0 for missing rows so it does not influence model decision + choices["prob"] = choices["prob"].fillna(0) + # sort by tour_id and alt_dest + choices = ( + choices.reset_index() + .sort_values(by=["tour_id", alt_dest_col_name]) + .set_index("tour_id") + ) + return choices diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml index 7bf21b93ba..78b8e41590 100644 --- a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml @@ -1,5 +1,5 @@ -EDB_ALTS_FILE_FORMAT: compact -EDB_FILETYPE: csv +EDB_ALTS_FILE_FORMAT: compact # options: compact, verbose +EDB_FILETYPE: csv # options: csv, parquet, pkl enable: True From 3fd7851708623e16fae6b1875a8e0a1d64d725b9 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 11 Oct 2024 17:10:01 -0700 Subject: [PATCH 14/56] adding survey choice to choices_df in interaction_sample --- activitysim/abm/models/location_choice.py | 35 ----------- activitysim/abm/models/trip_destination.py | 14 +++-- .../abm/models/util/tour_destination.py | 33 ----------- activitysim/core/configuration/logit.py | 18 +++--- activitysim/core/estimation.py | 58 +++++++++++++++++++ activitysim/core/interaction_sample.py | 46 +++++++++++++++ 6 files changed, 121 insertions(+), 83 deletions(-) diff --git a/activitysim/abm/models/location_choice.py b/activitysim/abm/models/location_choice.py index 98c01288c7..26fa42187b 100644 --- a/activitysim/abm/models/location_choice.py +++ b/activitysim/abm/models/location_choice.py @@ -491,41 +491,6 @@ def run_location_sample( trace_label=trace_label, ) - # adding observed choice to alt set when running in estimation mode - if estimator: - # grabbing survey values - survey_persons = estimation.manager.get_survey_table("persons") - if "school_location" in trace_label: - survey_choices = survey_persons["school_zone_id"].reset_index() - elif ("workplace_location" in trace_label) and ("external" not in trace_label): - survey_choices = survey_persons["workplace_zone_id"].reset_index() - else: - return choices - survey_choices.columns = ["person_id", "alt_dest"] - survey_choices = survey_choices[ - survey_choices["person_id"].isin(choices.index) - & (survey_choices.alt_dest > 0) - ] - # merging survey destination into table if not available - joined_data = survey_choices.merge( - choices, on=["person_id", "alt_dest"], how="left", indicator=True - ) - missing_rows = joined_data[joined_data["_merge"] == "left_only"] - missing_rows["pick_count"] = 1 - if len(missing_rows) > 0: - new_choices = missing_rows[ - ["person_id", "alt_dest", "prob", "pick_count"] - ].set_index("person_id") - choices = choices.append(new_choices, ignore_index=False).sort_index() - # making prob 0 for missing rows so it does not influence model decision - choices["prob"] = choices["prob"].fillna(0) - # sort by person_id and alt_dest - choices = ( - choices.reset_index() - .sort_values(by=["person_id", "alt_dest"]) - .set_index("person_id") - ) - return choices diff --git a/activitysim/abm/models/trip_destination.py b/activitysim/abm/models/trip_destination.py index 2b6b5a2ff2..95b6ccde27 100644 --- a/activitysim/abm/models/trip_destination.py +++ b/activitysim/abm/models/trip_destination.py @@ -173,15 +173,17 @@ def _destination_sample( ) sample_size = model_settings.SAMPLE_SIZE - if state.settings.disable_destination_sampling or ( - estimator and estimator.want_unsampled_alternatives - ): - # FIXME interaction_sample will return unsampled complete alternatives with probs and pick_count + if estimator: + sample_size = model_settings.ESTIMATION_SAMPLE_SIZE logger.info( - f"Estimation mode for {trace_label} using " - f"unsampled alternatives short_circuit_choices" + f"Estimation mode for {trace_label} using sample size of {sample_size}" ) + + if state.settings.disable_destination_sampling: sample_size = 0 + logger.info( + f"SAMPLE_SIZE set to 0 for {trace_label} because disable_destination_sampling is set" + ) locals_dict = state.get_global_constants().copy() locals_dict.update(model_settings.CONSTANTS) diff --git a/activitysim/abm/models/util/tour_destination.py b/activitysim/abm/models/util/tour_destination.py index 8feb6d55d8..d07f27e4e2 100644 --- a/activitysim/abm/models/util/tour_destination.py +++ b/activitysim/abm/models/util/tour_destination.py @@ -181,39 +181,6 @@ def destination_sample( trace_label=trace_label, ) - # adding observed choice to alt set when running in estimation mode - if estimator: - # grabbing survey values - survey_tours = estimation.manager.get_survey_table("tours") - survey_choices = survey_tours[["destination", "person_id"]].reset_index() - survey_choices.columns = ["tour_id", alt_dest_col_name, "person_id"] - survey_choices = survey_choices[ - survey_choices["tour_id"].isin(choices.index) - & (survey_choices[alt_dest_col_name] > 0) - ] - # merging survey destination into table if not available - joined_data = survey_choices.merge( - choices, - on=["tour_id", alt_dest_col_name, "person_id"], - how="left", - indicator=True, - ) - missing_rows = joined_data[joined_data["_merge"] == "left_only"] - missing_rows["pick_count"] = 1 - if len(missing_rows) > 0: - new_choices = missing_rows[ - ["tour_id", alt_dest_col_name, "prob", "pick_count", "person_id"] - ].set_index("tour_id") - choices = choices.append(new_choices, ignore_index=False).sort_index() - # making prob 0 for missing rows so it does not influence model decision - choices["prob"] = choices["prob"].fillna(0) - # sort by tour_id and alt_dest - choices = ( - choices.reset_index() - .sort_values(by=["tour_id", alt_dest_col_name]) - .set_index("tour_id") - ) - return choices diff --git a/activitysim/core/configuration/logit.py b/activitysim/core/configuration/logit.py index d03bcab778..94233db262 100644 --- a/activitysim/core/configuration/logit.py +++ b/activitysim/core/configuration/logit.py @@ -187,6 +187,15 @@ class LocationComponentSettings(BaseLogitComponentSettings): SAMPLE_SIZE: int """This many candidate alternatives will be sampled for each choice.""" + ESTIMATION_SAMPLE_SIZE: int = 0 + """ + The number of alternatives to sample for estimation mode. + If zero, then all alternatives are used. + Truth alternative will be included in the sample. + Larch does not yet support sampling alternatives for estimation, + but this setting is still helpful for estimation mode runtime. + """ + LOGSUM_SETTINGS: Path """Settings for the logsum computation.""" @@ -233,15 +242,6 @@ class TourLocationComponentSettings(LocationComponentSettings, extra="forbid"): ORIG_ZONE_ID: str | None = None """This setting appears to do nothing...""" - ESTIMATION_SAMPLE_SIZE: int = 0 - """ - The number of alternatives to sample for estimation mode. - If zero, then all alternatives are used. - Truth alternative will be included in the sample. - Larch does not yet support sampling alternatives for estimation, - but this setting is still helpful for estimation mode runtime. - """ - class TourModeComponentSettings(TemplatedLogitComponentSettings, extra="forbid"): MODE_CHOICE_LOGSUM_COLUMN_NAME: str | None = None diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index b79618509b..73c65087c2 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -933,5 +933,63 @@ def get_survey_values(self, model_values, table_name, column_names): return values[column_name] if column_name else values + def get_survey_destination_chocies(self, state, choosers, trace_label): + """ + Returning the survey choices for the destination choice model. + This gets called from inside interaction_sample and is used to + ensure the choices include the override choices when sampling alternatives. + + Parameters + ---------- + state : workflow.State + trace_label : str + The model name. + + Returns + ------- + pd.Series : The survey choices for the destination choice model. + """ + model = trace_label.split(".")[0] + if model == "school_location": + survey_choices = manager.get_survey_values( + choosers.index, "persons", "school_zone_id" + ) + elif model == "workplace_location": + survey_choices = manager.get_survey_values( + choosers.index, "persons", "workplace_zone_id" + ) + elif model in [ + "joint_tour_destination", + "atwork_subtour_destination", + "non_mandatory_tour_destination", + ]: + survey_choices = manager.get_survey_values( + choosers.index, "tours", "destination" + ) + elif model == "trip_destination": + survey_choices = manager.get_survey_values( + choosers.index, "trips", "destination" + ) + elif model == "parking_location": + # need to grab parking location column name from its settings + from activitysim.abm.models.parking_location_choice import ( + ParkingLocationSettings, + ) + + model_settings = ParkingLocationSettings.read_settings_file( + state.filesystem, + "parking_location_choice.yaml", + ) + survey_choices = manager.get_survey_values( + choosers.index, "trips", model_settings.ALT_DEST_COL_NAME + ) + else: + # since this fucntion is called from inside interaction_sample, + # we don't want to return anything for other models that aren't destination choice + # not implemented models include scheduling models and tour_od_choice + logger.debug(f"Not grabbing survey choices for {model}.") + return None + return survey_choices + manager = EstimationManager() diff --git a/activitysim/core/interaction_sample.py b/activitysim/core/interaction_sample.py index cabcbeb64c..83ed39480b 100644 --- a/activitysim/core/interaction_sample.py +++ b/activitysim/core/interaction_sample.py @@ -8,6 +8,7 @@ import pandas as pd from activitysim.core import ( + estimation, chunk, interaction_simulate, logit, @@ -501,6 +502,51 @@ def _interaction_sample( chunk_sizer.log_df(trace_label, "choices_df", choices_df) + if estimation.manager.enabled and sample_size > 0: + # we need to ensure chosen alternative is included in the sample + survey_choices = estimation.manager.get_survey_destination_chocies( + state, choosers, trace_label + ) + if survey_choices is not None: + survey_choices.name = alt_col_name + survey_choices = survey_choices.dropna().astype( + choices_df[alt_col_name].dtype + ) + comparison = pd.merge( + survey_choices, + choices_df, + on=[choosers.index.name, alt_col_name], + how="left", + indicator=True, + ) + missing_choices = comparison[comparison["_merge"] == "left_only"] + # need to get prob of missing choices and add them to choices_df + if not missing_choices.empty: + probs_df = probs.reset_index().melt( + id_vars=[choosers.index.name], + var_name=alt_col_name, + value_name="prob", + ) + # probs are numbered 0..n-1 so we need to map back to alt ids + zone_map = pd.Series(alternatives.index).to_dict() + probs_df[alt_col_name] = probs_df[alt_col_name].map(zone_map) + # merge the probs onto the missing chocies + missing_choices = pd.merge( + missing_choices.drop(columns=["prob", "_merge"]), + probs_df, + on=[choosers.index.name, alt_col_name], + how="left", + ) + assert ( + missing_choices.prob.isna().sum() == 0 + ), f"survey choices with no probs: {missing_choices[missing_choices.prob.isna()]}" + del probs_df + # random number is not important, filling with 0 + missing_choices["rand"] = 0 + # merge survey choices back into choices_df and sort by chooser + choices_df = pd.concat([choices_df, missing_choices], ignore_index=True) + choices_df.sort_values(by=[choosers.index.name], inplace=True) + del probs chunk_sizer.log_df(trace_label, "probs", None) From 23ba66209a0dbbb3dd016c44781d208858d317f0 Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Tue, 15 Oct 2024 08:46:45 -0700 Subject: [PATCH 15/56] adding option to delete the mp edb subdirs --- activitysim/core/steps/output.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index 8875033472..b7f10a21dd 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -270,6 +270,9 @@ def _coalesce_estimation_data_bundles(state): logger.info("Coalescing Estimation Data Bundles") edb_dir = state.filesystem.get_output_dir("estimation_data_bundle") + estimation_settings = state.filesystem.read_model_settings( + "estimation.yaml", mandatory=False + ) lowest_dirs = find_lowest_level_directories(edb_dir) @@ -314,8 +317,6 @@ def _coalesce_estimation_data_bundles(state): for i, file in enumerate(os.listdir(dir)): - if "stop_frequency" in file: - print("debugging") # get the file path file_path = os.path.join(dir, file) @@ -356,7 +357,8 @@ def _coalesce_estimation_data_bundles(state): df_concat_dict[file] = [df] # delete the directory now that we have gone through all the files - # shutil.rmtree(dir) + if estimation_settings.get("DELETE_MP_SUBDIRS", True): + shutil.rmtree(dir) # need to concatenate the last set of dataframes concat_and_write_edb(df_concat_dict, cur_edb) From 0a1bd5c83c9baa220897a2b830511e65fa5972bc Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Mon, 21 Oct 2024 09:54:18 -0700 Subject: [PATCH 16/56] changes supporting sandag abm3 estimation mode --- activitysim/abm/models/cdap.py | 2 +- activitysim/abm/models/disaggregate_accessibility.py | 11 ++++++----- activitysim/abm/models/util/tour_destination.py | 4 +++- activitysim/core/estimation.py | 5 +++++ activitysim/core/interaction_sample.py | 6 +++--- 5 files changed, 18 insertions(+), 10 deletions(-) diff --git a/activitysim/abm/models/cdap.py b/activitysim/abm/models/cdap.py index 2b9a105a5b..120c01a30e 100644 --- a/activitysim/abm/models/cdap.py +++ b/activitysim/abm/models/cdap.py @@ -189,7 +189,7 @@ def cdap_simulate( spec = cdap.get_cached_spec(state, hhsize) estimator.write_table(spec, "spec_%s" % hhsize, append=False) if add_joint_tour_utility: - joint_spec = cdap.get_cached_joint_spec(hhsize) + joint_spec = cdap.get_cached_joint_spec(state, hhsize) estimator.write_table( joint_spec, "joint_spec_%s" % hhsize, append=False ) diff --git a/activitysim/abm/models/disaggregate_accessibility.py b/activitysim/abm/models/disaggregate_accessibility.py index 40265b798f..c5c723f920 100644 --- a/activitysim/abm/models/disaggregate_accessibility.py +++ b/activitysim/abm/models/disaggregate_accessibility.py @@ -753,11 +753,12 @@ def get_disaggregate_logsums( state.filesystem, model_name + ".yaml" ) model_settings.SAMPLE_SIZE = disagg_model_settings.DESTINATION_SAMPLE_SIZE - estimator = estimation.manager.begin_estimation(state, trace_label) - if estimator: - location_choice.write_estimation_specs( - state, estimator, model_settings, model_name + ".yaml" - ) + # estimator = estimation.manager.begin_estimation(state, trace_label) + # if estimator: + # location_choice.write_estimation_specs( + # state, estimator, model_settings, model_name + ".yaml" + # ) + estimator = None # Append table references in settings with "proto_" # This avoids having to make duplicate copies of config files for disagg accessibilities diff --git a/activitysim/abm/models/util/tour_destination.py b/activitysim/abm/models/util/tour_destination.py index d07f27e4e2..4709a99264 100644 --- a/activitysim/abm/models/util/tour_destination.py +++ b/activitysim/abm/models/util/tour_destination.py @@ -310,7 +310,9 @@ def choose_MAZ_for_TAZ(state: workflow.State, taz_sample, MAZ_size_terms, trace_ # taz_choices index values should be contiguous assert ( - taz_choices[chooser_id_col] == np.repeat(chooser_df.index, taz_sample_size) + (taz_choices[chooser_id_col] == np.repeat(chooser_df.index, taz_sample_size)) + # can get one extra if sampling in estimation mode + | (taz_choices[chooser_id_col] == np.repeat(chooser_df.index, taz_sample_size + 1)) ).all() # we need to choose a MAZ for each DEST_TAZ choice diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 73c65087c2..f08f6de4ec 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -683,6 +683,7 @@ def __init__(self): self.model_estimation_table_types = {} self.estimating = {} self.settings = None + self.enabled = False def initialize_settings(self, state): # FIXME - can't we just initialize in init and handle no-presence of settings file as not enabled @@ -949,6 +950,10 @@ def get_survey_destination_chocies(self, state, choosers, trace_label): ------- pd.Series : The survey choices for the destination choice model. """ + if "accessibilities" in trace_label: + # accessibilities models to not have survey values + return None + model = trace_label.split(".")[0] if model == "school_location": survey_choices = manager.get_survey_values( diff --git a/activitysim/core/interaction_sample.py b/activitysim/core/interaction_sample.py index 83ed39480b..c6f0a29247 100644 --- a/activitysim/core/interaction_sample.py +++ b/activitysim/core/interaction_sample.py @@ -537,10 +537,10 @@ def _interaction_sample( on=[choosers.index.name, alt_col_name], how="left", ) - assert ( - missing_choices.prob.isna().sum() == 0 - ), f"survey choices with no probs: {missing_choices[missing_choices.prob.isna()]}" + if missing_choices.prob.isna().sum() > 0: + logger.warning(f"Survey choices with no probs:\n {missing_choices[missing_choices.prob.isna()]}") del probs_df + missing_choices['prob'].fillna(0, inplace=True) # random number is not important, filling with 0 missing_choices["rand"] = 0 # merge survey choices back into choices_df and sort by chooser From 8a4b2816510a0db02320969eb427957323316001 Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Thu, 7 Nov 2024 14:55:21 -0800 Subject: [PATCH 17/56] running test sandag example through trip dest sample --- activitysim/abm/models/location_choice.py | 2 +- activitysim/abm/models/trip_destination.py | 48 +++++++++++++++ activitysim/abm/models/util/cdap.py | 6 +- .../abm/models/util/tour_destination.py | 58 +++++++++++++++++-- activitysim/core/estimation.py | 18 +++++- activitysim/core/interaction_sample.py | 52 +++++++---------- 6 files changed, 144 insertions(+), 40 deletions(-) diff --git a/activitysim/abm/models/location_choice.py b/activitysim/abm/models/location_choice.py index 26fa42187b..4d034db0ff 100644 --- a/activitysim/abm/models/location_choice.py +++ b/activitysim/abm/models/location_choice.py @@ -402,7 +402,7 @@ def location_presample( # choose a MAZ for each DEST_TAZ choice, choice probability based on MAZ size_term fraction of TAZ total maz_choices = tour_destination.choose_MAZ_for_TAZ( - state, taz_sample, MAZ_size_terms, trace_label + state, taz_sample, MAZ_size_terms, trace_label, model_settings ) assert DEST_MAZ in maz_choices diff --git a/activitysim/abm/models/trip_destination.py b/activitysim/abm/models/trip_destination.py index 95b6ccde27..6e49e5c79b 100644 --- a/activitysim/abm/models/trip_destination.py +++ b/activitysim/abm/models/trip_destination.py @@ -293,6 +293,7 @@ def choose_MAZ_for_TAZ( network_los, alt_dest_col_name, trace_label, + model_settings, ): """ Convert taz_sample table with TAZ zone sample choices to a table with a MAZ zone chosen for each TAZ @@ -532,6 +533,52 @@ def choose_MAZ_for_TAZ( transpose=False, ) + if estimation.manager.enabled and (model_settings.ESTIMATION_SAMPLE_SIZE > 0): + # want to ensure the override choice is in the choice set + survey_choices = estimation.manager.get_survey_destination_choices( + state, chooser_df, trace_label + ) + if survey_choices is not None: + assert ( + chooser_df.index == survey_choices.index + ).all(), "survey_choices index should match chooser_df index" + survey_choices.name = DEST_MAZ + survey_choices = survey_choices.dropna().astype(taz_choices[DEST_MAZ].dtype) + # merge maz_sizes onto survey choices + maz_sizes["MAZ_prob"] = maz_sizes.groupby(DEST_TAZ)["size_term"].transform( + lambda x: x / x.sum() + ) + survey_choices = pd.merge( + survey_choices.reset_index(), + maz_sizes[[DEST_MAZ, DEST_TAZ, "MAZ_prob"]], + on=[DEST_MAZ], + how="left", + ) + # merge TAZ_prob from taz_choices onto survey choices + survey_choices = pd.merge( + survey_choices, + # dropping duplicates to avoid duplicate rows as the same TAZ can be chosen multiple times + taz_choices[[chooser_id_col, DEST_TAZ, "TAZ_prob"]].drop_duplicates( + subset=[chooser_id_col, DEST_TAZ] + ), + on=[chooser_id_col, DEST_TAZ], + how="left", + ) + survey_choices["prob"] = ( + survey_choices["TAZ_prob"] * survey_choices["MAZ_prob"] + ) + + # Don't care about getting dest_TAZ correct as it gets dropped later + survey_choices.fillna(0, inplace=True) + + # merge survey choices back into choices_df and sort by chooser + taz_choices = pd.concat( + [taz_choices, survey_choices[taz_choices.columns]], ignore_index=True + ) + taz_choices.sort_values( + by=[chooser_id_col, DEST_TAZ], inplace=True, ignore_index=True + ) + taz_choices = taz_choices.drop(columns=["TAZ_prob", "MAZ_prob"]) taz_choices = taz_choices.groupby([chooser_id_col, DEST_MAZ]).agg( prob=("prob", "max"), pick_count=("prob", "count") @@ -605,6 +652,7 @@ def destination_presample( network_los, alt_dest_col_name, trace_label, + model_settings, ) assert alt_dest_col_name in maz_sample diff --git a/activitysim/abm/models/util/cdap.py b/activitysim/abm/models/util/cdap.py index f52713ebf6..f7d1d8c062 100644 --- a/activitysim/abm/models/util/cdap.py +++ b/activitysim/abm/models/util/cdap.py @@ -969,6 +969,7 @@ def household_activity_choices( spec, choosers, trace_label=trace_label, + have_trace_targets=(trace_hh_id in choosers.index), chunk_sizer=chunk_sizer, compute_settings=compute_settings, ) @@ -984,14 +985,15 @@ def household_activity_choices( interaction_coefficients, hhsize, trace_spec=(trace_hh_id in choosers.index), - trace_label=trace_label, + trace_label=tracing.extend_trace_label(trace_label, "joint"), ) joint_tour_utils = simulate.eval_utilities( state, joint_tour_spec, choosers, - trace_label=trace_label, + trace_label=tracing.extend_trace_label(trace_label, "joint"), + have_trace_targets=(trace_hh_id in choosers.index), chunk_sizer=chunk_sizer, compute_settings=compute_settings, ) diff --git a/activitysim/abm/models/util/tour_destination.py b/activitysim/abm/models/util/tour_destination.py index 4709a99264..5cfb02b342 100644 --- a/activitysim/abm/models/util/tour_destination.py +++ b/activitysim/abm/models/util/tour_destination.py @@ -234,7 +234,9 @@ def aggregate_size_terms(dest_size_terms, network_los): return MAZ_size_terms, TAZ_size_terms -def choose_MAZ_for_TAZ(state: workflow.State, taz_sample, MAZ_size_terms, trace_label): +def choose_MAZ_for_TAZ( + state: workflow.State, taz_sample, MAZ_size_terms, trace_label, model_settings +): """ Convert taz_sample table with TAZ zone sample choices to a table with a MAZ zone chosen for each TAZ choose MAZ probabilistically (proportionally by size_term) from set of MAZ zones in parent TAZ @@ -311,8 +313,6 @@ def choose_MAZ_for_TAZ(state: workflow.State, taz_sample, MAZ_size_terms, trace_ # taz_choices index values should be contiguous assert ( (taz_choices[chooser_id_col] == np.repeat(chooser_df.index, taz_sample_size)) - # can get one extra if sampling in estimation mode - | (taz_choices[chooser_id_col] == np.repeat(chooser_df.index, taz_sample_size + 1)) ).all() # we need to choose a MAZ for each DEST_TAZ choice @@ -457,6 +457,54 @@ def choose_MAZ_for_TAZ(state: workflow.State, taz_sample, MAZ_size_terms, trace_ transpose=False, ) + if estimation.manager.enabled and (model_settings.ESTIMATION_SAMPLE_SIZE > 0): + # want to ensure the override choice is in the choice set + survey_choices = estimation.manager.get_survey_destination_choices( + state, chooser_df, trace_label + ) + + if survey_choices is not None: + assert ( + chooser_df.index == survey_choices.index + ).all(), "survey_choices index should match chooser_df index" + survey_choices.name = DEST_MAZ + survey_choices = survey_choices.dropna().astype(taz_choices[DEST_MAZ].dtype) + # merge maz_sizes onto survey choices + MAZ_size_terms["MAZ_prob"] = MAZ_size_terms.groupby("dest_TAZ")[ + "size_term" + ].transform(lambda x: x / x.sum()) + survey_choices = pd.merge( + survey_choices.reset_index(), + MAZ_size_terms.rename(columns={"zone_id": DEST_MAZ}), + on=[DEST_MAZ], + how="left", + ) + # merge TAZ_prob from taz_choices onto survey choices + survey_choices = pd.merge( + survey_choices, + # dropping duplicates to avoid duplicate rows as the same TAZ can be chosen multiple times + taz_choices[[chooser_id_col, "dest_TAZ", "TAZ_prob"]].drop_duplicates( + subset=[chooser_id_col, "dest_TAZ"] + ), + on=[chooser_id_col, "dest_TAZ"], + how="left", + ) + + survey_choices["prob"] = ( + survey_choices["TAZ_prob"] * survey_choices["MAZ_prob"] + ) + + # Don't care about getting dest_TAZ correct as it gets dropped later + survey_choices.fillna(0, inplace=True) + + # merge survey choices back into choices_df and sort by chooser + taz_choices = pd.concat( + [taz_choices, survey_choices[taz_choices.columns]], ignore_index=True + ) + taz_choices.sort_values( + by=[chooser_id_col, "dest_TAZ"], inplace=True, ignore_index=True + ) + taz_choices = taz_choices.drop(columns=["TAZ_prob", "MAZ_prob"]) taz_choices = taz_choices.groupby([chooser_id_col, DEST_MAZ]).agg( prob=("prob", "max"), pick_count=("prob", "count") @@ -515,7 +563,9 @@ def destination_presample( ) # choose a MAZ for each DEST_TAZ choice, choice probability based on MAZ size_term fraction of TAZ total - maz_choices = choose_MAZ_for_TAZ(state, taz_sample, MAZ_size_terms, trace_label) + maz_choices = choose_MAZ_for_TAZ( + state, taz_sample, MAZ_size_terms, trace_label, model_settings + ) assert DEST_MAZ in maz_choices maz_choices = maz_choices.rename(columns={DEST_MAZ: alt_dest_col_name}) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index f08f6de4ec..43b677986a 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -934,7 +934,7 @@ def get_survey_values(self, model_values, table_name, column_names): return values[column_name] if column_name else values - def get_survey_destination_chocies(self, state, choosers, trace_label): + def get_survey_destination_choices(self, state, choosers, trace_label): """ Returning the survey choices for the destination choice model. This gets called from inside interaction_sample and is used to @@ -953,7 +953,7 @@ def get_survey_destination_chocies(self, state, choosers, trace_label): if "accessibilities" in trace_label: # accessibilities models to not have survey values return None - + model = trace_label.split(".")[0] if model == "school_location": survey_choices = manager.get_survey_values( @@ -994,6 +994,20 @@ def get_survey_destination_chocies(self, state, choosers, trace_label): # not implemented models include scheduling models and tour_od_choice logger.debug(f"Not grabbing survey choices for {model}.") return None + + if "presample.interaction_sample" in trace_label: + # presampling happens for destination choice of two-zone systems. + # They are pre-sampling TAZs but the survey value destination is MAZs. + land_use = state.get_table("land_use") + TAZ_col = "TAZ" if "TAZ" in land_use.columns else "taz" + assert ( + TAZ_col in land_use.columns + ), "Cannot find TAZ column in land_use table." + maz_to_taz_map = land_use[TAZ_col].to_dict() + # allow for unmapped TAZs + maz_to_taz_map[-1] = -1 + survey_choices = survey_choices.map(maz_to_taz_map) + return survey_choices diff --git a/activitysim/core/interaction_sample.py b/activitysim/core/interaction_sample.py index c6f0a29247..6d80e5a8c9 100644 --- a/activitysim/core/interaction_sample.py +++ b/activitysim/core/interaction_sample.py @@ -504,48 +504,38 @@ def _interaction_sample( if estimation.manager.enabled and sample_size > 0: # we need to ensure chosen alternative is included in the sample - survey_choices = estimation.manager.get_survey_destination_chocies( + survey_choices = estimation.manager.get_survey_destination_choices( state, choosers, trace_label ) if survey_choices is not None: + assert ( + survey_choices.index == choosers.index + ).all(), "survey_choices and choosers must have the same index" survey_choices.name = alt_col_name survey_choices = survey_choices.dropna().astype( choices_df[alt_col_name].dtype ) - comparison = pd.merge( + + # merge all survey choices onto choices_df + probs_df = probs.reset_index().melt( + id_vars=[choosers.index.name], + var_name=alt_col_name, + value_name="prob", + ) + # probs are numbered 0..n-1 so we need to map back to alt ids + zone_map = pd.Series(alternatives.index).to_dict() + probs_df[alt_col_name] = probs_df[alt_col_name].map(zone_map) + + survey_choices = pd.merge( survey_choices, - choices_df, + probs_df, on=[choosers.index.name, alt_col_name], how="left", - indicator=True, ) - missing_choices = comparison[comparison["_merge"] == "left_only"] - # need to get prob of missing choices and add them to choices_df - if not missing_choices.empty: - probs_df = probs.reset_index().melt( - id_vars=[choosers.index.name], - var_name=alt_col_name, - value_name="prob", - ) - # probs are numbered 0..n-1 so we need to map back to alt ids - zone_map = pd.Series(alternatives.index).to_dict() - probs_df[alt_col_name] = probs_df[alt_col_name].map(zone_map) - # merge the probs onto the missing chocies - missing_choices = pd.merge( - missing_choices.drop(columns=["prob", "_merge"]), - probs_df, - on=[choosers.index.name, alt_col_name], - how="left", - ) - if missing_choices.prob.isna().sum() > 0: - logger.warning(f"Survey choices with no probs:\n {missing_choices[missing_choices.prob.isna()]}") - del probs_df - missing_choices['prob'].fillna(0, inplace=True) - # random number is not important, filling with 0 - missing_choices["rand"] = 0 - # merge survey choices back into choices_df and sort by chooser - choices_df = pd.concat([choices_df, missing_choices], ignore_index=True) - choices_df.sort_values(by=[choosers.index.name], inplace=True) + survey_choices["rand"] = 0 + survey_choices["prob"].fillna(0, inplace=True) + choices_df = pd.concat([choices_df, survey_choices], ignore_index=True) + choices_df.sort_values(by=[choosers.index.name], inplace=True) del probs chunk_sizer.log_df(trace_label, "probs", None) From 6a50abb23eab38c70c9cdb049f2b6b6abbad66a4 Mon Sep 17 00:00:00 2001 From: Jeffrey Newman Date: Thu, 7 Nov 2024 17:22:46 -0600 Subject: [PATCH 18/56] Estimation Pydantic (#2) * pydantic for estimation settings * allow df as type in config * fix table_info * repair for Pydantic * df is attribute --- activitysim/core/estimation.py | 148 +++++++++++++++++++++++---------- 1 file changed, 103 insertions(+), 45 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 43b677986a..bb1f069e41 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -6,11 +6,13 @@ import os import shutil from pathlib import Path +from typing import Literal import pandas as pd -import yaml +from pydantic import model_validator from activitysim.core import simulate, workflow +from activitysim.core.configuration import PydanticReadable from activitysim.core.configuration.base import PydanticBase from activitysim.core.util import reindex from activitysim.core.yaml_tools import safe_dump @@ -48,14 +50,77 @@ def estimation_enabled(state): return settings is not None +class SurveyTableConfig(PydanticBase): + file_name: str + index_col: str + + # The dataframe is stored in the loaded config dynamically but not given + # directly in the config file, as it's not a simple serializable object that + # can be written in a YAML file. + class Config: + arbitrary_types_allowed = True + + df: pd.DataFrame | None = None + + +class EstimationTableRecipeConfig(PydanticBase): + omnibus_tables: dict[str, list[str]] + omnibus_tables_append_columns: list[str] + + +class EstimationConfig(PydanticReadable): + SKIP_BUNDLE_WRITE_FOR: list[str] = [] + EDB_FILETYPE: Literal["csv", "parquet", "pkl"] = "csv" + EDB_ALTS_FILE_FORMAT: Literal["verbose", "compact"] = "verbose" + + enable: bool = False + """Flag to enable estimation.""" + + bundles: list[str] = [] + """List of component names to create EDBs for.""" + + model_estimation_table_types: dict[str, str] = {} + """Mapping of component names to estimation table types. + + The keys of this mapping are the model component names, and the values are the + names of the estimation table recipes that should be used to generate the + estimation tables for the model component. The recipes are generally related + to the generic model types, such as 'simple_simulate', 'interaction_simulate', + 'interaction_sample_simulate', etc. + """ + + estimation_table_recipes: dict[str, EstimationTableRecipeConfig] = {} + """Mapping of estimation table recipe names to their configurations. + + The keys of this mapping are the names of the estimation table recipes. + The recipes are generally related to the generic model types, such as + 'simple_simulate', 'interaction_simulate', 'interaction_sample_simulate', + etc. The values are the configurations for the estimation table recipes. + """ + + survey_tables: dict[str, SurveyTableConfig] = {} + + # pydantic class validator to ensure that the model_estimation_table_types + # dictionary is a valid dictionary with string keys and string values, and + # that all the values are in the estimation_table_recipes dictionary + @model_validator(mode="after") + def validate_model_estimation_table_types(self): + for key, value in self.model_estimation_table_types.items(): + if value not in self.estimation_table_recipes: + raise ValueError( + f"model_estimation_table_types value '{value}' not in estimation_table_recipes" + ) + return self + + class Estimator: def __init__( self, state: workflow.State, - bundle_name, - model_name, - estimation_table_recipes, - settings, + bundle_name: str, + model_name: str, + estimation_table_recipe: EstimationTableRecipeConfig, + settings: EstimationConfig, ): logger.info("Initialize Estimator for'%s'" % (model_name,)) @@ -63,7 +128,7 @@ def __init__( self.bundle_name = bundle_name self.model_name = model_name self.settings_name = model_name - self.estimation_table_recipes = estimation_table_recipes + self.estimation_table_recipe = estimation_table_recipe self.estimating = True self.settings = settings @@ -84,10 +149,10 @@ def __init__( # assert 'override_choices' in self.model_settings, \ # "override_choices not found for %s in %s." % (model_name, ESTIMATION_SETTINGS_FILE_NAME) - self.omnibus_tables = self.estimation_table_recipes["omnibus_tables"] - self.omnibus_tables_append_columns = self.estimation_table_recipes[ - "omnibus_tables_append_columns" - ] + self.omnibus_tables = self.estimation_table_recipe.omnibus_tables + self.omnibus_tables_append_columns = ( + self.estimation_table_recipe.omnibus_tables_append_columns + ) self.tables = {} self.tables_to_cache = [ table_name @@ -345,7 +410,7 @@ def write_omnibus_table(self): if len(self.omnibus_tables) == 0: return - edbs_to_skip = self.settings.get("SKIP_BUNDLE_WRITE_FOR", []) + edbs_to_skip = self.settings.SKIP_BUNDLE_WRITE_FOR if self.bundle_name in edbs_to_skip: self.debug(f"Skipping write to disk for {self.bundle_name}") return @@ -376,7 +441,7 @@ def write_omnibus_table(self): self.debug(f"sorting tables: {table_names}") df.sort_index(ascending=True, inplace=True, kind="mergesort") - filetype = self.settings.get("EDB_FILETYPE", "csv") + filetype = self.settings.EDB_FILETYPE if filetype == "csv": file_path = self.output_file_path(omnibus_table, "csv") @@ -448,7 +513,7 @@ def write_coefficients_template(self, model_settings): assert self.estimating if isinstance(model_settings, PydanticBase): - model_settings = model_settings.dict() + model_settings = model_settings.model_dump() coefficients_df = simulate.read_model_coefficient_template( self.state.filesystem, model_settings ) @@ -460,7 +525,7 @@ def write_choosers(self, choosers_df): choosers_df, "choosers", append=True, - filetype=self.settings.get("EDB_FILETYPE", "csv"), + filetype=self.settings.EDB_FILETYPE, ) def write_choices(self, choices): @@ -471,7 +536,7 @@ def write_choices(self, choices): choices, "choices", append=True, - filetype=self.settings.get("EDB_FILETYPE", "csv"), + filetype=self.settings.EDB_FILETYPE, ) def write_override_choices(self, choices): @@ -482,7 +547,7 @@ def write_override_choices(self, choices): choices, "override_choices", append=True, - filetype=self.settings.get("EDB_FILETYPE", "csv"), + filetype=self.settings.EDB_FILETYPE, ) def write_constants(self, constants): @@ -521,7 +586,7 @@ def write_model_settings( ) assert not os.path.isfile(file_path) with open(file_path, "w") as f: - safe_dump(model_settings.dict(), f) + safe_dump(model_settings.model_dump(), f) else: if "include_settings" in model_settings: file_path = self.output_file_path( @@ -582,7 +647,7 @@ def melt_alternatives(self, df): # 31153,2,util_dist_0_1,1.0 # 31153,3,util_dist_0_1,1.0 - output_format = self.settings.get("EDB_ALTS_FILE_FORMAT", "verbose") + output_format = self.settings.EDB_ALTS_FILE_FORMAT assert output_format in ["verbose", "compact"] if output_format == "compact": @@ -613,7 +678,7 @@ def write_interaction_expression_values(self, df): df, "interaction_expression_values", append=True, - filetype=self.settings.get("EDB_FILETYPE", "csv"), + filetype=self.settings.EDB_FILETYPE, ) def write_expression_values(self, df): @@ -621,7 +686,7 @@ def write_expression_values(self, df): df, "expression_values", append=True, - filetype=self.settings.get("EDB_FILETYPE", "csv"), + filetype=self.settings.EDB_FILETYPE, ) def write_alternatives(self, alternatives_df, bundle_directory=False): @@ -638,7 +703,7 @@ def write_interaction_sample_alternatives(self, alternatives_df): alternatives_df, "interaction_sample_alternatives", append=True, - filetype=self.settings.get("EDB_FILETYPE", "csv"), + filetype=self.settings.EDB_FILETYPE, ) def write_interaction_simulate_alternatives(self, interaction_df): @@ -647,7 +712,7 @@ def write_interaction_simulate_alternatives(self, interaction_df): interaction_df, "interaction_simulate_alternatives", append=True, - filetype=self.settings.get("EDB_FILETYPE", "csv"), + filetype=self.settings.EDB_FILETYPE, ) def get_survey_values(self, model_values, table_name, column_names): @@ -679,8 +744,8 @@ class EstimationManager(object): def __init__(self): self.settings_initialized = False self.bundles = [] - self.estimation_table_recipes = {} - self.model_estimation_table_types = {} + self.estimation_table_recipes: dict[str, EstimationTableRecipeConfig] = {} + self.model_estimation_table_types: dict[str, str] = {} self.estimating = {} self.settings = None self.enabled = False @@ -691,40 +756,33 @@ def initialize_settings(self, state): return assert not self.settings_initialized - self.settings = state.filesystem.read_model_settings( - ESTIMATION_SETTINGS_FILE_NAME, mandatory=False + self.settings = EstimationConfig.read_settings_file( + state.filesystem, ESTIMATION_SETTINGS_FILE_NAME, mandatory=False ) if not self.settings: # if the model self.settings file is not found, we are not in estimation mode. self.enabled = False else: - self.enabled = self.settings.get("enable", "True") - self.bundles = self.settings.get("bundles", []) + self.enabled = self.settings.enable + self.bundles = self.settings.bundles - self.model_estimation_table_types = self.settings.get( - "model_estimation_table_types", {} - ) - self.estimation_table_recipes = self.settings.get( - "estimation_table_recipes", {} - ) + self.model_estimation_table_types = self.settings.model_estimation_table_types + self.estimation_table_recipes = self.settings.estimation_table_recipes if self.enabled: - self.survey_tables = self.settings.get("survey_tables", {}) + self.survey_tables = self.settings.survey_tables for table_name, table_info in self.survey_tables.items(): assert ( - "file_name" in table_info - ), "No file name specified for survey_table '%s' in %s" % ( - table_name, - ESTIMATION_SETTINGS_FILE_NAME, - ) + table_info.file_name + ), f"No file name specified for survey_table '{table_name}' in {ESTIMATION_SETTINGS_FILE_NAME}" file_path = state.filesystem.get_data_file_path( - table_info["file_name"], mandatory=True + table_info.file_name, mandatory=True ) assert os.path.exists( file_path ), "File for survey table '%s' not found: %s" % (table_name, file_path) df = pd.read_csv(file_path) - index_col = table_info.get("index_col") + index_col = table_info.index_col if index_col is not None: assert ( index_col in df.columns @@ -744,7 +802,7 @@ def initialize_settings(self, state): df = df[df.household_id.isin(pipeline_hh_ids)] # add the table df to survey_tables - table_info["df"] = df + table_info.df = df self.settings_initialized = True @@ -806,7 +864,7 @@ def begin_estimation( state, bundle_name, model_name, - estimation_table_recipes=self.estimation_table_recipes[ + estimation_table_recipe=self.estimation_table_recipes[ model_estimation_table_type ], settings=self.settings, @@ -824,7 +882,7 @@ def get_survey_table(self, table_name): "EstimationManager. get_survey_table: survey table '%s' not in survey_tables" % table_name ) - df = self.survey_tables[table_name].get("df") + df = self.survey_tables[table_name].df return df def get_survey_values(self, model_values, table_name, column_names): From 45ee4e88bd70217e3b2dfae0079bcd0d92034cab Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Thu, 7 Nov 2024 16:11:21 -0800 Subject: [PATCH 19/56] Estimation settings pydantic update --- activitysim/core/estimation.py | 15 +++++++++++++++ activitysim/core/steps/output.py | 8 ++++---- 2 files changed, 19 insertions(+), 4 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index bb1f069e41..c4a25c7a98 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -70,8 +70,23 @@ class EstimationTableRecipeConfig(PydanticBase): class EstimationConfig(PydanticReadable): SKIP_BUNDLE_WRITE_FOR: list[str] = [] + """List of bundle names to skip writing to disk. + + This is useful for saving disk space and decreasing runtime + if you do not care about the estimation output for all models. + """ EDB_FILETYPE: Literal["csv", "parquet", "pkl"] = "csv" EDB_ALTS_FILE_FORMAT: Literal["verbose", "compact"] = "verbose" + """Format of the alternatives table in the estimation data bundle. + + verbose: every possible alternative is listed in the table + compact: alternatives are renumbered from 1 to sample_size + """ + DELETE_MP_SUBDIRS: bool = True + """Flag to delete the multiprocessing subdirectories after coalescing the results. + + Typically only used for debugging purposes. + """ enable: bool = False """Flag to enable estimation.""" diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index b7f10a21dd..bc92732969 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -16,7 +16,7 @@ from activitysim.core import configuration, workflow from activitysim.core.workflow.checkpoint import CHECKPOINT_NAME -from activitysim.core.estimation import estimation_enabled +from activitysim.core.estimation import estimation_enabled, EstimationConfig logger = logging.getLogger(__name__) @@ -270,8 +270,8 @@ def _coalesce_estimation_data_bundles(state): logger.info("Coalescing Estimation Data Bundles") edb_dir = state.filesystem.get_output_dir("estimation_data_bundle") - estimation_settings = state.filesystem.read_model_settings( - "estimation.yaml", mandatory=False + estimation_settings = EstimationConfig.read_settings_file( + state.filesystem, "estimation.yaml", mandatory=True ) lowest_dirs = find_lowest_level_directories(edb_dir) @@ -357,7 +357,7 @@ def _coalesce_estimation_data_bundles(state): df_concat_dict[file] = [df] # delete the directory now that we have gone through all the files - if estimation_settings.get("DELETE_MP_SUBDIRS", True): + if estimation_settings.DELETE_MP_SUBDIRS: shutil.rmtree(dir) # need to concatenate the last set of dataframes From 4af3fa971ac86ac5ff37e4db430825b1b74ca937 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Mon, 11 Nov 2024 18:18:18 -0800 Subject: [PATCH 20/56] new compact formatting --- activitysim/core/estimation.py | 25 +++++++++++-------- .../estimation_template.yaml | 4 +-- 2 files changed, 16 insertions(+), 13 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index c4a25c7a98..36e760eced 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -665,14 +665,14 @@ def melt_alternatives(self, df): output_format = self.settings.EDB_ALTS_FILE_FORMAT assert output_format in ["verbose", "compact"] - if output_format == "compact": - # renumber the alt_id column to just count from 1 to n - # this loses the alt_id information, but drops all of the empty columns - # (can still get empty columns if not every chooser has same number of alts) - # (this can happen if the pick count > 1 and/or sampled alts are not included) - melt_df[alt_id_name] = melt_df.groupby([chooser_name, variable_column])[ - alt_id_name - ].cumcount() + # if output_format == "compact": + # # renumber the alt_id column to just count from 1 to n + # # this loses the alt_id information, but drops all of the empty columns + # # (can still get empty columns if not every chooser has same number of alts) + # # (this can happen if the pick count > 1 and/or sampled alts are not included) + # melt_df[alt_id_name] = melt_df.groupby([chooser_name, variable_column])[ + # alt_id_name + # ].cumcount() melt_df = melt_df.set_index( [chooser_name, variable_column, alt_id_name] @@ -688,7 +688,8 @@ def melt_alternatives(self, df): return melt_df def write_interaction_expression_values(self, df): - df = self.melt_alternatives(df) + if self.settings.EDB_ALTS_FILE_FORMAT == "verbose": + df = self.melt_alternatives(df) self.write_table( df, "interaction_expression_values", @@ -713,7 +714,8 @@ def write_alternatives(self, alternatives_df, bundle_directory=False): ) def write_interaction_sample_alternatives(self, alternatives_df): - alternatives_df = self.melt_alternatives(alternatives_df) + if self.settings.EDB_ALTS_FILE_FORMAT == "verbose": + alternatives_df = self.melt_alternatives(alternatives_df) self.write_table( alternatives_df, "interaction_sample_alternatives", @@ -722,7 +724,8 @@ def write_interaction_sample_alternatives(self, alternatives_df): ) def write_interaction_simulate_alternatives(self, interaction_df): - interaction_df = self.melt_alternatives(interaction_df) + if self.settings.EDB_ALTS_FILE_FORMAT == "verbose": + interaction_df = self.melt_alternatives(interaction_df) self.write_table( interaction_df, "interaction_simulate_alternatives", diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml index 78b8e41590..c5cf709257 100644 --- a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml @@ -62,7 +62,7 @@ estimation_table_recipes: alternatives_combined: - interaction_sample_alternatives - interaction_expression_values - omnibus_tables_append_columns: [choosers_combined] + omnibus_tables_append_columns: [choosers_combined, alternatives_combined] interaction_simulate: omnibus_tables: @@ -70,7 +70,7 @@ estimation_table_recipes: - choices - override_choices - choosers - omnibus_tables_append_columns: [choosers_combined] + omnibus_tables_append_columns: [choosers_combined, alternatives_combined] simple_simulate: omnibus_tables: From 36dfb455b9d3d9dae4d262319de36e79f7586a4b Mon Sep 17 00:00:00 2001 From: David Hensle Date: Mon, 11 Nov 2024 18:47:34 -0800 Subject: [PATCH 21/56] handling multiple columns for parquet write --- activitysim/core/estimation.py | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 36e760eced..213fbc44f4 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -277,26 +277,26 @@ def write_parquet(self, df, file_path, index, append=False): ), f"file already exists: {file_path}" # Explicitly set the data types of the columns - for col in df.columns: - if "int" in str(df[col].dtype): + for col_name, col_data in df.iteritems(): + if "int" in str(col_data.dtype): pass elif ( - df[col].dtype == "float16" + col_data.dtype == "float16" ): # Handle halffloat type not allowed in parquet - df[col] = df[col].astype("float32") - elif "float" in str(df[col].dtype): + df[col_name] = col_data.astype("float32") + elif "float" in str(col_data.dtype): pass - elif df[col].dtype == "bool": + elif col_data.dtype == "bool": pass - elif df[col].dtype == "object": + elif col_data.dtype == "object": # first try converting to numeric, if that fails, convert to string try: - df[col] = pd.to_numeric(df[col], errors="raise") + df[col_name] = pd.to_numeric(col_data, errors="raise") except ValueError: - df[col] = df[col].astype(str) + df[col_name] = col_data.astype(str) else: # Convert any other unsupported types to string - df[col] = df[col].astype(str) + df[col_name] = col_data.astype(str) self.debug(f"writing table: {file_path}") # want parquet file to be exactly the same as df read from csv From e4eb045d7fa47b881694a0dc173524b41f338a08 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Thu, 21 Nov 2024 16:40:28 -0800 Subject: [PATCH 22/56] dropping duplicate columns --- activitysim/core/estimation.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 213fbc44f4..2a57980ea1 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -453,6 +453,9 @@ def write_omnibus_table(self): else: df = pd.concat([self.tables[t] for t in table_names], axis=concat_axis) + # remove duplicated columns, keeping the first instance + df = df[df.columns.drop_duplicates()] + self.debug(f"sorting tables: {table_names}") df.sort_index(ascending=True, inplace=True, kind="mergesort") From b2972ccf69b42302bb70003f2ad3919751a80b8f Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 22 Nov 2024 09:42:45 -0800 Subject: [PATCH 23/56] actually removing duplicate columns --- activitysim/core/estimation.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 2a57980ea1..dfb6a766a9 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -454,7 +454,7 @@ def write_omnibus_table(self): df = pd.concat([self.tables[t] for t in table_names], axis=concat_axis) # remove duplicated columns, keeping the first instance - df = df[df.columns.drop_duplicates()] + df = df.loc[:, ~df.columns.duplicated()] self.debug(f"sorting tables: {table_names}") df.sort_index(ascending=True, inplace=True, kind="mergesort") From 8d4dd37c365bf91c2f581b882e029a42047268ad Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 22 Nov 2024 17:22:18 -0800 Subject: [PATCH 24/56] dfs with correct indexes and correct mp sorting --- activitysim/core/estimation.py | 17 +++++++++++++++++ activitysim/core/steps/output.py | 2 +- .../configs_estimation/estimation_template.yaml | 3 +++ 3 files changed, 21 insertions(+), 1 deletion(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index dfb6a766a9..8f2443bed5 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -456,6 +456,23 @@ def write_omnibus_table(self): # remove duplicated columns, keeping the first instance df = df.loc[:, ~df.columns.duplicated()] + # set index if not already set according to lowest level heirarchy + # df missing index is typically coming from interaction_simulate expression values + # important for sorting and thus for multiprocessing to be consistent with single + if df.index.name is None: + if "trip_id" in df.columns: + df.set_index("trip_id", inplace=True) + elif "tour_id" in df.columns: + df.set_index("tour_id", inplace=True) + elif "person_id" in df.columns: + df.set_index("person_id", inplace=True) + elif "household_id" in df.columns: + df.set_index("household_id", inplace=True) + else: + RuntimeError( + f"No index column found in omnibus table {omnibus_table}: {df}" + ) + self.debug(f"sorting tables: {table_names}") df.sort_index(ascending=True, inplace=True, kind="mergesort") diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index bc92732969..70c0612ac1 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -247,7 +247,7 @@ def concat_and_write_edb(df_concat_dict, write_dir): if df.index.name is not None: df = df.sort_index() else: - df = df.sort_values(by=df.columns[0]) + df = df.sort_values(by=df.columns[0], kind="mergesort") if table_name.endswith(".csv"): df.to_csv(os.path.join(write_dir, table_name), index=False) diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml index c5cf709257..34b612c4ce 100644 --- a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml @@ -1,5 +1,6 @@ EDB_ALTS_FILE_FORMAT: compact # options: compact, verbose EDB_FILETYPE: csv # options: csv, parquet, pkl +DELETE_MP_SUBDIRS: True enable: True @@ -70,6 +71,8 @@ estimation_table_recipes: - choices - override_choices - choosers + alternatives_combined: + - interaction_expression_values omnibus_tables_append_columns: [choosers_combined, alternatives_combined] simple_simulate: From 1fb41a8a63a077fdc935e99b817c0d78eada12f2 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Sat, 23 Nov 2024 15:01:57 -0800 Subject: [PATCH 25/56] ignore index on sort for mp coalesce edbs --- activitysim/core/steps/output.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/activitysim/core/steps/output.py b/activitysim/core/steps/output.py index 70c0612ac1..ea543c8aaf 100644 --- a/activitysim/core/steps/output.py +++ b/activitysim/core/steps/output.py @@ -247,7 +247,7 @@ def concat_and_write_edb(df_concat_dict, write_dir): if df.index.name is not None: df = df.sort_index() else: - df = df.sort_values(by=df.columns[0], kind="mergesort") + df = df.sort_values(by=df.columns[0], kind="mergesort", ignore_index=True) if table_name.endswith(".csv"): df.to_csv(os.path.join(write_dir, table_name), index=False) From 87b414f099e8ccc669287324d66b902c7406dc6f Mon Sep 17 00:00:00 2001 From: David Hensle Date: Thu, 5 Dec 2024 11:59:43 -0800 Subject: [PATCH 26/56] updating estimation checks to allow for non-zero household_sample_size --- activitysim/abm/models/joint_tour_frequency.py | 5 ++++- activitysim/abm/models/non_mandatory_tour_frequency.py | 4 +++- activitysim/abm/models/stop_frequency.py | 6 +++++- activitysim/abm/models/trip_destination.py | 2 ++ activitysim/core/estimation.py | 2 +- 5 files changed, 15 insertions(+), 4 deletions(-) diff --git a/activitysim/abm/models/joint_tour_frequency.py b/activitysim/abm/models/joint_tour_frequency.py index 1700c143b0..9d918c9558 100644 --- a/activitysim/abm/models/joint_tour_frequency.py +++ b/activitysim/abm/models/joint_tour_frequency.py @@ -192,8 +192,11 @@ def joint_tour_frequency( print(f"len(joint_tours) {len(joint_tours)}") different = False + # need to check households as well because the full survey sample may not be used + # (e.g. if we set household_sample_size in settings.yaml) survey_tours_not_in_tours = survey_tours[ ~survey_tours.index.isin(joint_tours.index) + & survey_tours.household_id.isin(households.index) ] if len(survey_tours_not_in_tours) > 0: print(f"survey_tours_not_in_tours\n{survey_tours_not_in_tours}") @@ -201,7 +204,7 @@ def joint_tour_frequency( tours_not_in_survey_tours = joint_tours[ ~joint_tours.index.isin(survey_tours.index) ] - if len(survey_tours_not_in_tours) > 0: + if len(tours_not_in_survey_tours) > 0: print(f"tours_not_in_survey_tours\n{tours_not_in_survey_tours}") different = True assert not different diff --git a/activitysim/abm/models/non_mandatory_tour_frequency.py b/activitysim/abm/models/non_mandatory_tour_frequency.py index 4d80c26baa..f656840e11 100644 --- a/activitysim/abm/models/non_mandatory_tour_frequency.py +++ b/activitysim/abm/models/non_mandatory_tour_frequency.py @@ -442,8 +442,10 @@ def non_mandatory_tour_frequency( if estimator: # make sure they created the right tours survey_tours = estimation.manager.get_survey_table("tours").sort_index() + # need the household_id check below incase household_sample_size != 0 non_mandatory_survey_tours = survey_tours[ - survey_tours.tour_category == "non_mandatory" + (survey_tours.tour_category == "non_mandatory") + & survey_tours.household_id.isin(persons.household_id) ] # need to remove the pure-escort tours from the survey tours table for comparison below if state.is_table("school_escort_tours"): diff --git a/activitysim/abm/models/stop_frequency.py b/activitysim/abm/models/stop_frequency.py index 70755ff860..6d24e3e468 100644 --- a/activitysim/abm/models/stop_frequency.py +++ b/activitysim/abm/models/stop_frequency.py @@ -277,7 +277,11 @@ def stop_frequency( survey_trips = estimation.manager.get_survey_table(table_name="trips") different = False - survey_trips_not_in_trips = survey_trips[~survey_trips.index.isin(trips.index)] + # need the check below on household_id incase household_sample_size != 0 + survey_trips_not_in_trips = survey_trips[ + ~survey_trips.index.isin(trips.index) + & survey_trips.household_id.isin(trips.household_id) + ] if len(survey_trips_not_in_trips) > 0: print(f"survey_trips_not_in_trips\n{survey_trips_not_in_trips}") different = True diff --git a/activitysim/abm/models/trip_destination.py b/activitysim/abm/models/trip_destination.py index 6e49e5c79b..c831faac19 100644 --- a/activitysim/abm/models/trip_destination.py +++ b/activitysim/abm/models/trip_destination.py @@ -1362,6 +1362,8 @@ def run_trip_destination( # expect all the same trips survey_trips = estimator.get_survey_table("trips").sort_index() + # need to check household_id incase household_sample_size != 0 + survey_trips = survey_trips[survey_trips.household_id.isin(trips.household_id)] assert survey_trips.index.equals(trips.index) first = survey_trips.trip_num == 1 diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 8f2443bed5..143f36f62d 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -831,7 +831,7 @@ def initialize_settings(self, state): if state.settings.multiprocess: pipeline_hh_ids = state.get_table("households").index if table_name == "households": - df = df[df.index.isin(pipeline_hh_ids)] + df = df.reindex(pipeline_hh_ids) assert pipeline_hh_ids.equals( df.index ), "household_ids not equal between survey and pipeline" From 3b4974c782e36141a4f8c2392f82f0514bb5979d Mon Sep 17 00:00:00 2001 From: Jeffrey Newman Date: Mon, 9 Dec 2024 15:39:47 -0600 Subject: [PATCH 27/56] Re-estimation (#3) * pydantic for estimation settings * allow df as type in config * fix table_info * auto ownership * repair for pydantic * update for ruff * updated for simple models * repair for Pydantic * simple simulate and location choice * df is attribute * scheduling * stop freq * test locations * cdap * nonmand_and_joint_tour_dest_choice * nonmand_tour_freq * fix ci to stop using mamba * test updates * use larch6 from pip * use numba for stop freq * fix for pandas 1.5 * fix stop freq test for numba * Sharrow Cache Dir Setting (#893) * setting necessary filesystem changes from settings file * set for multiprocessing * repair github actions * github action updates (#903) * script to make data * unified script for making data * remove older * bug * doc note * load from parquet if available * add original alt ids to EDB output when using compact * fix MP race * script arg to skip to EDB * clean up CDAP and blacken * refactor model_estimation_table_types change to estimation_table_types, to avoid pydantic namespace clash * repair drop_dupes * blacken * location choice with compact * choice_def for compact * spec changes for simple-simulate * re-estimation demo for auto ownership * clean up status messages * change name to stop pydantic warnings * edit configs * default estimation sample size is same as regular sample size * allow location alts not in cv format * dummy zones for location choice * update scheduling model estimation * various cleanup * stop freq * tidy build script * update 02 school location for larger example * update notebook 04 * editable model re-estimation for location choice * fix test names * update notebooks * cdap print filenames as loading * notebook 07 * tests thru 07 * notebooks 08 09 * build the data first * runnable script * change larch version dependency * keep pandas<2 * notebooks 10 11 * notebook 12 * remove odd print * add matplotlib * notebook 13 14 * test all the notebooks * add xlsxwriter to tests * notebook 15 * CDAP revise model spec demo * notebook 16 * notebook 17 * longer timeout * notebook 18 * notebook 19 * notebook 20 * smaller notebook 15 * configurable est mode setup * notebook 21 * notebook 22 * config sample size in GA * notebook 23 * updates for larch and graphviz * change default to compact * compare model 03 * test updates * rename test targets * repair_av_zq * move doctor up * add another repair * oops --------- Co-authored-by: David Hensle <51132108+dhensle@users.noreply.github.com> --- .github/workflows/branch-docs.yml | 2 +- .github/workflows/build_installer.yml | 4 +- .github/workflows/core_tests.yml | 145 +- .github/workflows/deployment.yml | 18 +- .github/workflows/test-deploy.yml | 10 +- activitysim/abm/models/location_choice.py | 3 +- activitysim/abm/models/trip_destination.py | 9 +- .../abm/models/util/tour_destination.py | 11 +- activitysim/cli/run.py | 5 +- activitysim/core/configuration/filesystem.py | 15 +- activitysim/core/configuration/logit.py | 7 +- activitysim/core/estimation.py | 51 +- activitysim/core/interaction_sample.py | 4 +- activitysim/core/mp_tasks.py | 1 + activitysim/core/workflow/state.py | 9 +- activitysim/estimation/larch/__init__.py | 15 +- .../estimation/larch/auto_ownership.py | 80 - activitysim/estimation/larch/cdap.py | 56 +- activitysim/estimation/larch/general.py | 97 +- .../estimation/larch/location_choice.py | 210 +- activitysim/estimation/larch/mode_choice.py | 25 +- .../estimation/larch/nonmand_tour_freq.py | 96 +- activitysim/estimation/larch/scheduling.py | 93 +- .../estimation/larch/simple_simulate.py | 100 +- .../estimation/larch/stop_frequency.py | 82 +- .../estimation_template.yaml | 2 +- .../estimation/test/test_larch_estimation.py | 24 +- .../test_larch_estimation/test_cdap_model.csv | 324 +- .../test_cdap_model_loglike.csv | 2 +- .../test_joint_tour_scheduling_loglike.csv | 2 +- ...twork_subtour_destination_BHHH_loglike.csv | 2 + ...rk_subtour_destination_BHHH_size_spec.csv} | 2 +- ...loc_atwork_subtour_destination_loglike.csv | 2 - ..._loc_atwork_subtour_scheduling_loglike.csv | 2 - ...ndatory_tour_destination_SLSQP_loglike.csv | 2 + ...tory_tour_destination_SLSQP_size_spec.csv} | 20 +- ...non_mandatory_tour_destination_loglike.csv | 2 - ..._non_mandatory_tour_scheduling_loglike.csv | 2 - .../test_loc_school_location_BHHH_loglike.csv | 2 + ...est_loc_school_location_BHHH_size_spec.csv | 23 + ...test_loc_school_location_SLSQP_loglike.csv | 2 + ...st_loc_school_location_SLSQP_size_spec.csv | 23 + .../test_loc_school_location_loglike.csv | 2 +- .../test_loc_school_location_size_spec.csv | 10 +- ...test_loc_trip_destination_BHHH_loglike.csv | 2 + ...t_loc_trip_destination_BHHH_size_spec.csv} | 16 +- .../test_loc_trip_destination_loglike.csv | 2 - ...t_loc_workplace_location_SLSQP_loglike.csv | 2 + ...oc_workplace_location_SLSQP_size_spec.csv} | 8 +- .../test_loc_workplace_location_loglike.csv | 2 - ..._atwork_subtour_destination_BHHH_None_.csv | 22 +- ...mandatory_tour_destination_SLSQP_None_.csv | 72 +- ...ation_model_school_location_BHHH_None_.csv | 21 + ...tion_model_school_location_SLSQP_None_.csv | 42 +- ...tion_model_trip_destination_BHHH_None_.csv | 48 + ...ion_model_trip_destination_SLSQP_0_12_.csv | 48 - ...n_model_workplace_location_SLSQP_None_.csv | 70 +- ...ndatory_tour_scheduling_school_loglike.csv | 2 +- ...mandatory_tour_scheduling_work_loglike.csv | 2 +- ..._non_mandatory_tour_scheduling_loglike.csv | 2 +- ...est_nonmand_and_joint_tour_dest_choice.csv | 72 +- ...and_and_joint_tour_dest_choice_loglike.csv | 2 +- .../test_nonmand_tour_freq.csv | 852 +- .../test_nonmand_tour_freq_loglike.csv | 16 +- ...model_atwork_subtour_scheduling_SLSQP_.csv | 50 - ...ing_model_joint_tour_scheduling_SLSQP_.csv | 120 +- ...andatory_tour_scheduling_school_SLSQP_.csv | 112 +- ..._mandatory_tour_scheduling_work_SLSQP_.csv | 128 +- ...l_non_mandatory_tour_scheduling_SLSQP_.csv | 180 +- .../test_school_location.csv | 42 +- .../test_school_location_loglike.csv | 2 +- .../test_school_location_size_spec.csv | 10 +- ...mulate_atwork_subtour_frequency_SLSQP_.csv | 222 +- ...atwork_subtour_frequency_SLSQP_loglike.csv | 2 +- ...t_simple_simulate_auto_ownership_BHHH_.csv | 2 +- ...est_simple_simulate_free_parking_BHHH_.csv | 2 +- ...simulate_joint_tour_composition_SLSQP_.csv | 64 +- ...e_joint_tour_composition_SLSQP_loglike.csv | 2 +- ...e_simulate_joint_tour_frequency_SLSQP_.csv | 154 +- ...mulate_joint_tour_participation_SLSQP_.csv | 120 +- ...imulate_mandatory_tour_frequency_BHHH_.csv | 108 +- ...mulate_mandatory_tour_frequency_SLSQP_.csv | 108 +- ...mandatory_tour_frequency_SLSQP_loglike.csv | 2 +- ...imple_simulate_trip_mode_choice_SLSQP_.csv | 546 +- .../test_stop_freq_model.csv | 378 +- .../test_stop_frequency_loglike.csv | 2 +- .../test_tour_and_subtour_mode_choice.csv | 604 +- .../test_workplace_location.csv | 70 +- .../test_workplace_location_loglike.csv | 2 +- .../test_workplace_location_size_spec.csv | 8 +- .../build_full_mtc_example.py | 195 + .../configs/estimation.yaml | 4 +- .../configs_estimation/estimation.yaml | 129 + .../configs_estimation/logging.yaml | 67 + .../configs_estimation/settings.yaml | 165 + .../notebooks/02_school_location.ipynb | 2156 +-- .../notebooks/03_work_location.ipynb | 5631 ++++---- .../notebooks/04_auto_ownership.ipynb | 5670 ++++++-- .../notebooks/05_free_parking.ipynb | 1003 +- .../notebooks/06_cdap.ipynb | 7651 +++++++--- .../notebooks/07_mand_tour_freq.ipynb | 3057 ++-- .../notebooks/08_work_tour_scheduling.ipynb | 2732 ++-- .../notebooks/09_school_tour_scheduling.ipynb | 3694 ++--- .../notebooks/10_joint_tour_freq.ipynb | 2543 ++-- .../notebooks/11_joint_tour_composition.ipynb | 2003 +-- .../12_joint_tour_participation.ipynb | 3320 +++-- .../13_joint_nonmand_tour_dest.ipynb | 3323 ++--- .../notebooks/14_joint_tour_scheduling.ipynb | 3824 ++--- .../notebooks/15_non_mand_tour_freq.ipynb | 11795 +++++++++++----- .../16_nonmand_tour_scheduling.ipynb | 3410 ++--- .../notebooks/17_tour_mode_choice.ipynb | 6278 ++++---- .../notebooks/18_atwork_subtour_freq.ipynb | 3380 +++-- .../notebooks/19_atwork_subtour_dest.ipynb | 1864 +-- .../20_atwork_subtour_scheduling.ipynb | 3425 ++--- .../notebooks/21_stop_frequency.ipynb | 5693 ++++---- .../notebooks/22_trip_dest.ipynb | 3497 +++-- .../notebooks/23_trip_mode_choice.ipynb | 5809 ++++---- .../notebooks/est_mode_setup.py | 83 + .../example_estimation/scripts/infer.py | 5 +- .../configs/tour_scheduling_school.csv | 2 +- .../configs/tour_scheduling_school.csv | 2 +- .../configs/estimation.yaml | 4 +- conda-environments/activitysim-dev-base.yml | 2 +- conda-environments/activitysim-dev.yml | 2 +- conda-environments/docbuild.yml | 2 +- conda-environments/github-actions-tests.yml | 2 + pyproject.toml | 10 +- 127 files changed, 56077 insertions(+), 42296 deletions(-) delete mode 100644 activitysim/estimation/larch/auto_ownership.py create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_BHHH_loglike.csv rename activitysim/estimation/test/test_larch_estimation/{test_loc_atwork_subtour_destination_size_spec.csv => test_loc_atwork_subtour_destination_BHHH_size_spec.csv} (97%) delete mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_loglike.csv delete mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_scheduling_loglike.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_SLSQP_loglike.csv rename activitysim/estimation/test/test_larch_estimation/{test_loc_non_mandatory_tour_destination_size_spec.csv => test_loc_non_mandatory_tour_destination_SLSQP_size_spec.csv} (51%) delete mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_loglike.csv delete mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_scheduling_loglike.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_school_location_BHHH_loglike.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_school_location_BHHH_size_spec.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_school_location_SLSQP_loglike.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_school_location_SLSQP_size_spec.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_loglike.csv rename activitysim/estimation/test/test_larch_estimation/{test_loc_trip_destination_size_spec.csv => test_loc_trip_destination_BHHH_size_spec.csv} (63%) delete mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_loglike.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_SLSQP_loglike.csv rename activitysim/estimation/test/test_larch_estimation/{test_loc_workplace_location_size_spec.csv => test_loc_workplace_location_SLSQP_size_spec.csv} (72%) delete mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_loglike.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_location_model_school_location_BHHH_None_.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_BHHH_None_.csv delete mode 100644 activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_SLSQP_0_12_.csv delete mode 100644 activitysim/estimation/test/test_larch_estimation/test_scheduling_model_atwork_subtour_scheduling_SLSQP_.csv create mode 100644 activitysim/examples/example_estimation/build_full_mtc_example.py create mode 100644 activitysim/examples/example_estimation/configs_estimation/estimation.yaml create mode 100644 activitysim/examples/example_estimation/configs_estimation/logging.yaml create mode 100644 activitysim/examples/example_estimation/configs_estimation/settings.yaml create mode 100644 activitysim/examples/example_estimation/notebooks/est_mode_setup.py diff --git a/.github/workflows/branch-docs.yml b/.github/workflows/branch-docs.yml index 7a4ab1f1ca..6447d047d1 100644 --- a/.github/workflows/branch-docs.yml +++ b/.github/workflows/branch-docs.yml @@ -15,7 +15,7 @@ jobs: run: shell: bash -l {0} steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 with: fetch-depth: 0 # get all tags, lets setuptools_scm do its thing diff --git a/.github/workflows/build_installer.yml b/.github/workflows/build_installer.yml index e6efa48145..cea4feca66 100644 --- a/.github/workflows/build_installer.yml +++ b/.github/workflows/build_installer.yml @@ -26,7 +26,7 @@ jobs: steps: - name: Checkout code - uses: actions/checkout@v3 + uses: actions/checkout@v4 - uses: conda-incubator/setup-miniconda@v3 with: @@ -47,7 +47,7 @@ jobs: shell: bash - name: Upload installer to Github artifact - uses: actions/upload-artifact@v3 + uses: actions/upload-artifact@v4 with: path: build/Activitysim-${{ inputs.version }}-${{ matrix.OS_NAME }}-${{ matrix.ARCH }}* name: Activitysim-${{ inputs.version }}-${{ matrix.OS_NAME }}-${{ matrix.ARCH }} diff --git a/.github/workflows/core_tests.yml b/.github/workflows/core_tests.yml index 6c95140e4e..3b1a03b9ed 100644 --- a/.github/workflows/core_tests.yml +++ b/.github/workflows/core_tests.yml @@ -26,13 +26,11 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Setup Mambaforge + - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-variant: Mambaforge miniforge-version: latest activate-environment: asim-test - use-mamba: true python-version: ${{ matrix.python-version }} - name: Set cache date for year and month @@ -46,7 +44,7 @@ jobs: - name: Update environment run: | - mamba env update -n asim-test -f conda-environments/github-actions-tests.yml + conda env update -n asim-test -f conda-environments/github-actions-tests.yml if: steps.cache.outputs.cache-hit != 'true' - name: Install activitysim @@ -58,8 +56,8 @@ jobs: - name: Conda checkup run: | - mamba info -a - mamba list + conda info -a + conda list - name: Lint with Black run: | @@ -111,13 +109,11 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Setup Mambaforge + - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-variant: Mambaforge miniforge-version: latest activate-environment: asim-test - use-mamba: true python-version: ${{ matrix.python-version }} - name: Set cache date for year and month @@ -131,7 +127,7 @@ jobs: - name: Update environment run: | - mamba env update -n asim-test -f conda-environments/github-actions-tests.yml + conda env update -n asim-test -f conda-environments/github-actions-tests.yml if: steps.cache.outputs.cache-hit != 'true' - name: Install activitysim @@ -143,8 +139,8 @@ jobs: - name: Conda checkup run: | - mamba info -a - mamba list + conda info -a + conda list - name: Lint with Black run: | @@ -194,13 +190,11 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Setup Mambaforge + - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-variant: Mambaforge miniforge-version: latest activate-environment: asim-test - use-mamba: true python-version: ${{ env.python-version }} - name: Set cache date for year and month @@ -214,7 +208,7 @@ jobs: - name: Update environment run: | - mamba env update -n asim-test -f conda-environments/github-actions-tests.yml + conda env update -n asim-test -f conda-environments/github-actions-tests.yml if: steps.cache.outputs.cache-hit != 'true' - name: Install activitysim @@ -226,8 +220,8 @@ jobs: - name: Conda checkup run: | - mamba info -a - mamba list + conda info -a + conda list # TODO: Cache sharrow compiled flows? The contents of __pycache__ appear to # be ignored, so this is not working as expected right now @@ -282,13 +276,11 @@ jobs: - name: Checkout ActivitySim uses: actions/checkout@v4 - - name: Setup Mambaforge + - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-variant: Mambaforge miniforge-version: latest activate-environment: asim-test - use-mamba: true python-version: ${{ env.python-version }} - name: Set cache date for year and month @@ -304,7 +296,7 @@ jobs: - name: Update environment run: | - mamba env update -n asim-test -f conda-environments/github-actions-tests.yml + conda env update -n asim-test -f conda-environments/github-actions-tests.yml if: steps.cache.outputs.cache-hit != 'true' - name: Install activitysim @@ -316,8 +308,8 @@ jobs: - name: Conda checkup run: | - mamba info -a - mamba list + conda info -a + conda list - name: Checkout Example uses: actions/checkout@v4 @@ -345,13 +337,11 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Setup Mambaforge + - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-variant: Mambaforge miniforge-version: latest activate-environment: asim-test - use-mamba: true python-version: ${{ env.python-version }} - name: Set cache date for year and month @@ -365,7 +355,7 @@ jobs: - name: Update environment run: | - mamba env update -n asim-test -f conda-environments/github-actions-tests.yml + conda env update -n asim-test -f conda-environments/github-actions-tests.yml if: steps.cache.outputs.cache-hit != 'true' - name: Install activitysim @@ -377,8 +367,8 @@ jobs: - name: Conda checkup run: | - mamba info -a - mamba list + conda info -a + conda list - name: Test Random Seed Generation run: | @@ -392,18 +382,16 @@ jobs: defaults: run: shell: bash -l {0} - name: estimation_mode_test + name: Estimation Mode Unit Tests runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - - name: Setup Mambaforge + - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-variant: Mambaforge miniforge-version: latest activate-environment: asim-test - use-mamba: true python-version: ${{ env.python-version }} - name: Set cache date for year and month @@ -417,11 +405,11 @@ jobs: - name: Update environment run: | - mamba env update -n asim-test -f conda-environments/github-actions-tests.yml + conda env update -n asim-test -f conda-environments/github-actions-tests.yml if: steps.cache.outputs.cache-hit != 'true' - - name: Install Larch - run: mamba install "larch>=5.7.1" + - name: Install Larch v6 + run: python -m pip install larch6 - name: Install activitysim # installing without dependencies is faster, we trust that all needed dependencies @@ -432,14 +420,75 @@ jobs: - name: Conda checkup run: | - mamba info -a - mamba list + conda info -a + conda list - name: Test Estimation Mode run: | python -m pytest activitysim/estimation/test/test_larch_estimation.py --durations=0 - - + + estimation_notebooks: + needs: foundation + env: + python-version: "3.10" + label: linux-64 + defaults: + run: + shell: bash -l {0} + name: Estimation Notebooks Test + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Setup Miniforge + uses: conda-incubator/setup-miniconda@v3 + with: + miniforge-version: latest + activate-environment: asim-test + python-version: ${{ env.python-version }} + + - name: Set cache date for year and month + run: echo "DATE=$(date +'%Y%m')" >> $GITHUB_ENV + + - uses: actions/cache@v4 + with: + path: ${{ env.CONDA }}/envs + key: ${{ env.label }}-conda-${{ hashFiles('conda-environments/github-actions-tests.yml') }}-${{ env.DATE }}-${{ env.CACHE_NUMBER }} + id: cache + + - name: Update environment + run: | + conda env update -n asim-test -f conda-environments/github-actions-tests.yml + if: steps.cache.outputs.cache-hit != 'true' + + - name: Install Graphviz + uses: ts-graphviz/setup-graphviz@v2 + + - name: Install Larch v6 + run: python -m pip install larch6 "pandas<2" pydot + + - name: Install activitysim + # installing without dependencies is faster, we trust that all needed dependencies + # are in the conda environment defined above. Also, this avoids pip getting + # confused and reinstalling tables (pytables). + run: | + python -m pip install -e . --no-deps + + - name: Conda checkup + run: | + conda info -a + conda list + + - name: Create Estimation Data + run: | + python activitysim/examples/example_estimation/notebooks/est_mode_setup.py --household_sample_size 5000 + + - name: Test Estimation Notebooks + run: | + python -m pytest activitysim/examples/example_estimation/notebooks/*.ipynb \ + --nbmake-timeout=3000 \ + --ignore=activitysim/examples/example_estimation/notebooks/01_estimation_mode.ipynb + estimation_edb_creation: needs: foundation env: @@ -453,13 +502,11 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Setup Mambaforge + - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-variant: Mambaforge miniforge-version: latest activate-environment: asim-test - use-mamba: true python-version: ${{ env.python-version }} - name: Set cache date for year and month @@ -473,7 +520,7 @@ jobs: - name: Update environment run: | - mamba env update -n asim-test -f conda-environments/github-actions-tests.yml + conda env update -n asim-test -f conda-environments/github-actions-tests.yml if: steps.cache.outputs.cache-hit != 'true' - name: Install activitysim @@ -485,8 +532,8 @@ jobs: - name: Conda checkup run: | - mamba info -a - mamba list + conda info -a + conda list - name: Test Estimation EDB Creation run: | @@ -505,15 +552,13 @@ jobs: with: fetch-depth: 0 # get all tags, lets setuptools_scm do its thing - name: Set up Python 3.10 - uses: actions/setup-python@v2 + uses: actions/setup-python@v5 with: python-version: "3.10" - name: Install dependencies uses: conda-incubator/setup-miniconda@v3 with: - miniforge-variant: Mambaforge miniforge-version: latest - use-mamba: true environment-file: conda-environments/docbuild.yml python-version: "3.10" activate-environment: docbuild diff --git a/.github/workflows/deployment.yml b/.github/workflows/deployment.yml index 2a0ef70c31..10652bba4d 100644 --- a/.github/workflows/deployment.yml +++ b/.github/workflows/deployment.yml @@ -13,10 +13,10 @@ jobs: runs-on: ubuntu-latest if: github.repository == 'ActivitySim/activitysim' steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 with: fetch-depth: 0 - - uses: actions/setup-python@v4 + - uses: actions/setup-python@v5 name: Install Python with: python-version: "3.10" @@ -39,7 +39,7 @@ jobs: else echo "✅ Looks good" fi - - uses: actions/upload-artifact@v3 + - uses: actions/upload-artifact@v4 with: name: releases path: dist @@ -48,11 +48,11 @@ jobs: needs: build-artifacts runs-on: ubuntu-latest steps: - - uses: actions/setup-python@v4 + - uses: actions/setup-python@v5 name: Install Python with: python-version: "3.10" - - uses: actions/download-artifact@v4.1.7 + - uses: actions/download-artifact@v4 with: name: releases path: dist @@ -84,13 +84,13 @@ jobs: run: shell: bash -l {0} steps: - - uses: actions/checkout@v3 - - uses: actions/download-artifact@v4.1.7 + - uses: actions/checkout@v4 + - uses: actions/download-artifact@v4 with: name: releases path: dist - name: Set up Python 3.10 - uses: actions/setup-python@v2 + uses: actions/setup-python@v5 with: python-version: "3.10" - name: Install dependencies @@ -132,7 +132,7 @@ jobs: if: github.event_name == 'release' runs-on: ubuntu-latest steps: - - uses: actions/download-artifact@v4.1.7 + - uses: actions/download-artifact@v4 with: name: releases path: dist diff --git a/.github/workflows/test-deploy.yml b/.github/workflows/test-deploy.yml index b4dbced254..bbcd938b35 100644 --- a/.github/workflows/test-deploy.yml +++ b/.github/workflows/test-deploy.yml @@ -12,10 +12,10 @@ jobs: build-artifacts: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 with: fetch-depth: 0 - - uses: actions/setup-python@v4 + - uses: actions/setup-python@v5 name: Install Python with: python-version: "3.10" @@ -43,7 +43,7 @@ jobs: else echo "✅ Looks good" fi - - uses: actions/upload-artifact@v3 + - uses: actions/upload-artifact@v4 with: name: releases path: dist @@ -52,11 +52,11 @@ jobs: needs: build-artifacts runs-on: ubuntu-latest steps: - - uses: actions/setup-python@v4 + - uses: actions/setup-python@v5 name: Install Python with: python-version: "3.10" - - uses: actions/download-artifact@v4.1.7 + - uses: actions/download-artifact@v4 with: name: releases path: dist diff --git a/activitysim/abm/models/location_choice.py b/activitysim/abm/models/location_choice.py index 4d034db0ff..bf36fa4cca 100644 --- a/activitysim/abm/models/location_choice.py +++ b/activitysim/abm/models/location_choice.py @@ -19,7 +19,6 @@ from activitysim.core.interaction_sample_simulate import interaction_sample_simulate from activitysim.core.util import reindex - """ The school/workplace location model predicts the zones in which various people will work or attend school. @@ -140,7 +139,7 @@ def _location_sample( sample_size = model_settings.SAMPLE_SIZE - if estimator: + if estimator and model_settings.ESTIMATION_SAMPLE_SIZE >= 0: sample_size = model_settings.ESTIMATION_SAMPLE_SIZE logger.info( f"Estimation mode for {trace_label} using sample size of {sample_size}" diff --git a/activitysim/abm/models/trip_destination.py b/activitysim/abm/models/trip_destination.py index c831faac19..30cb37e2ad 100644 --- a/activitysim/abm/models/trip_destination.py +++ b/activitysim/abm/models/trip_destination.py @@ -173,7 +173,7 @@ def _destination_sample( ) sample_size = model_settings.SAMPLE_SIZE - if estimator: + if estimator and model_settings.ESTIMATION_SAMPLE_SIZE >= 0: sample_size = model_settings.ESTIMATION_SAMPLE_SIZE logger.info( f"Estimation mode for {trace_label} using sample size of {sample_size}" @@ -533,7 +533,12 @@ def choose_MAZ_for_TAZ( transpose=False, ) - if estimation.manager.enabled and (model_settings.ESTIMATION_SAMPLE_SIZE > 0): + if estimation.manager.enabled and ( + model_settings.ESTIMATION_SAMPLE_SIZE > 0 + or ( + model_settings.ESTIMATION_SAMPLE_SIZE < 0 and model_settings.SAMPLE_SIZE > 0 + ) + ): # want to ensure the override choice is in the choice set survey_choices = estimation.manager.get_survey_destination_choices( state, chooser_df, trace_label diff --git a/activitysim/abm/models/util/tour_destination.py b/activitysim/abm/models/util/tour_destination.py index 5cfb02b342..4bbcb1cff4 100644 --- a/activitysim/abm/models/util/tour_destination.py +++ b/activitysim/abm/models/util/tour_destination.py @@ -9,7 +9,7 @@ from activitysim.abm.models.util import logsums as logsum from activitysim.abm.tables.size_terms import tour_destination_size_terms -from activitysim.core import estimation, config, los, simulate, tracing, workflow +from activitysim.core import config, estimation, los, simulate, tracing, workflow from activitysim.core.configuration.logit import TourLocationComponentSettings from activitysim.core.interaction_sample import interaction_sample from activitysim.core.interaction_sample_simulate import interaction_sample_simulate @@ -87,7 +87,7 @@ def _destination_sample( logger.info("running %s with %d tours", trace_label, len(choosers)) sample_size = model_settings.SAMPLE_SIZE - if estimator: + if estimator and model_settings.ESTIMATION_SAMPLE_SIZE >= 0: sample_size = model_settings.ESTIMATION_SAMPLE_SIZE logger.info( f"Estimation mode for {trace_label} using sample size of {sample_size}" @@ -457,7 +457,12 @@ def choose_MAZ_for_TAZ( transpose=False, ) - if estimation.manager.enabled and (model_settings.ESTIMATION_SAMPLE_SIZE > 0): + if estimation.manager.enabled and ( + model_settings.ESTIMATION_SAMPLE_SIZE > 0 + or ( + model_settings.ESTIMATION_SAMPLE_SIZE < 0 and model_settings.SAMPLE_SIZE > 0 + ) + ): # want to ensure the override choice is in the choice set survey_choices = estimation.manager.get_survey_destination_choices( state, chooser_df, trace_label diff --git a/activitysim/cli/run.py b/activitysim/cli/run.py index 03258be4b5..f54fb3b95d 100644 --- a/activitysim/cli/run.py +++ b/activitysim/cli/run.py @@ -362,7 +362,10 @@ def run(args): ] for cfg_key in np_info_keys: - info = np.__config__.get_info(cfg_key) + try: + info = np.__config__.get_info(cfg_key) + except AttributeError: + info = np.show_config("dicts").get(cfg_key, "MISSING") if info: for info_key in ["libraries"]: if info_key in info: diff --git a/activitysim/core/configuration/filesystem.py b/activitysim/core/configuration/filesystem.py index b55f0c4961..ba2049e31c 100644 --- a/activitysim/core/configuration/filesystem.py +++ b/activitysim/core/configuration/filesystem.py @@ -134,6 +134,18 @@ def _parse_arg(name, x): return self + def parse_settings(self, settings): + def _parse_setting(name, x): + v = getattr(settings, x, None) + if v is not None: + setattr(self, name, v) + + _parse_setting("cache_dir", "cache_dir") + _parse_setting("sharrow_cache_dir", "sharrow_cache_dir") + _parse_setting("profile_dir", "profile_dir") + _parse_setting("pipeline_file_name", "pipeline_file_name") + return + def get_working_subdir(self, subdir) -> Path: if self.working_dir: return self.working_dir.joinpath(subdir) @@ -157,7 +169,8 @@ def get_output_dir(self, subdir=None) -> Path: if subdir is not None: out = out.joinpath(subdir) if not out.exists(): - out.mkdir(parents=True) + out.mkdir(parents=True, exist_ok=True) + # we set exist_ok=True so we avoid multiprocess race conditions return out def get_output_file_path(self, file_name) -> Path: diff --git a/activitysim/core/configuration/logit.py b/activitysim/core/configuration/logit.py index 94233db262..594ecf353a 100644 --- a/activitysim/core/configuration/logit.py +++ b/activitysim/core/configuration/logit.py @@ -187,13 +187,12 @@ class LocationComponentSettings(BaseLogitComponentSettings): SAMPLE_SIZE: int """This many candidate alternatives will be sampled for each choice.""" - ESTIMATION_SAMPLE_SIZE: int = 0 + ESTIMATION_SAMPLE_SIZE: int = -1 """ The number of alternatives to sample for estimation mode. - If zero, then all alternatives are used. + If zero, then all alternatives are used. If negative, then the regular + `SAMPLE_SIZE` is used. Truth alternative will be included in the sample. - Larch does not yet support sampling alternatives for estimation, - but this setting is still helpful for estimation mode runtime. """ LOGSUM_SETTINGS: Path diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 143f36f62d..98bbb73f7c 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -72,19 +72,19 @@ class EstimationConfig(PydanticReadable): SKIP_BUNDLE_WRITE_FOR: list[str] = [] """List of bundle names to skip writing to disk. - This is useful for saving disk space and decreasing runtime + This is useful for saving disk space and decreasing runtime if you do not care about the estimation output for all models. """ EDB_FILETYPE: Literal["csv", "parquet", "pkl"] = "csv" - EDB_ALTS_FILE_FORMAT: Literal["verbose", "compact"] = "verbose" + EDB_ALTS_FILE_FORMAT: Literal["verbose", "compact"] = "compact" """Format of the alternatives table in the estimation data bundle. - + verbose: every possible alternative is listed in the table compact: alternatives are renumbered from 1 to sample_size """ DELETE_MP_SUBDIRS: bool = True """Flag to delete the multiprocessing subdirectories after coalescing the results. - + Typically only used for debugging purposes. """ @@ -94,7 +94,7 @@ class EstimationConfig(PydanticReadable): bundles: list[str] = [] """List of component names to create EDBs for.""" - model_estimation_table_types: dict[str, str] = {} + estimation_table_types: dict[str, str] = {} """Mapping of component names to estimation table types. The keys of this mapping are the model component names, and the values are the @@ -115,15 +115,15 @@ class EstimationConfig(PydanticReadable): survey_tables: dict[str, SurveyTableConfig] = {} - # pydantic class validator to ensure that the model_estimation_table_types + # pydantic class validator to ensure that the estimation_table_types # dictionary is a valid dictionary with string keys and string values, and # that all the values are in the estimation_table_recipes dictionary @model_validator(mode="after") - def validate_model_estimation_table_types(self): - for key, value in self.model_estimation_table_types.items(): + def validate_estimation_table_types(self): + for key, value in self.estimation_table_types.items(): if value not in self.estimation_table_recipes: raise ValueError( - f"model_estimation_table_types value '{value}' not in estimation_table_recipes" + f"estimation_table_types value '{value}' not in estimation_table_recipes" ) return self @@ -685,7 +685,24 @@ def melt_alternatives(self, df): output_format = self.settings.EDB_ALTS_FILE_FORMAT assert output_format in ["verbose", "compact"] + # original_alt_ids = None # if output_format == "compact": + # # preserve the original alt_ids in the EDB output + # original_alt_ids = melt_df[[chooser_name, alt_id_name]].drop_duplicates( + # ignore_index=True + # ) + # original_alt_ids = original_alt_ids.set_index( + # [chooser_name, alt_id_name], drop=False + # )[alt_id_name] + # original_alt_ids.index = pd.MultiIndex.from_arrays( + # [ + # original_alt_ids.index.get_level_values(0), + # original_alt_ids.groupby(level=0).cumcount(), + # ], + # names=[chooser_name, alt_id_name], + # ) + # original_alt_ids = original_alt_ids.unstack(1, fill_value=-1) + # # # renumber the alt_id column to just count from 1 to n # # this loses the alt_id information, but drops all of the empty columns # # (can still get empty columns if not every chooser has same number of alts) @@ -698,7 +715,13 @@ def melt_alternatives(self, df): [chooser_name, variable_column, alt_id_name] ).unstack(2) melt_df.columns = melt_df.columns.droplevel(0) - melt_df = melt_df.reset_index(1) + # if original_alt_ids is not None: + # original_alt_ids.index = pd.MultiIndex.from_arrays( + # [original_alt_ids.index, pd.Index(["alt_id"] * len(original_alt_ids))], + # names=melt_df.index.names, + # ) + # melt_df = pd.concat([melt_df, original_alt_ids], axis=0) + melt_df = melt_df.sort_index().reset_index(1) # person_id,expression,1,2,3,4,5,... # 31153,util_dist_0_1,0.75,0.46,0.27,0.63,0.48,... @@ -783,7 +806,7 @@ def __init__(self): self.settings_initialized = False self.bundles = [] self.estimation_table_recipes: dict[str, EstimationTableRecipeConfig] = {} - self.model_estimation_table_types: dict[str, str] = {} + self.estimation_table_types: dict[str, str] = {} self.estimating = {} self.settings = None self.enabled = False @@ -804,7 +827,7 @@ def initialize_settings(self, state): self.enabled = self.settings.enable self.bundles = self.settings.bundles - self.model_estimation_table_types = self.settings.model_estimation_table_types + self.estimation_table_types = self.settings.estimation_table_types self.estimation_table_recipes = self.settings.estimation_table_recipes if self.enabled: @@ -882,13 +905,13 @@ def begin_estimation( ), "Cant begin estimating %s - already estimating that model." % (model_name,) assert ( - bundle_name in self.model_estimation_table_types + bundle_name in self.estimation_table_types ), "No estimation_table_type for %s in %s." % ( bundle_name, ESTIMATION_SETTINGS_FILE_NAME, ) - model_estimation_table_type = self.model_estimation_table_types[bundle_name] + model_estimation_table_type = self.estimation_table_types[bundle_name] assert ( model_estimation_table_type in self.estimation_table_recipes diff --git a/activitysim/core/interaction_sample.py b/activitysim/core/interaction_sample.py index 6d80e5a8c9..a43f414106 100644 --- a/activitysim/core/interaction_sample.py +++ b/activitysim/core/interaction_sample.py @@ -8,14 +8,14 @@ import pandas as pd from activitysim.core import ( - estimation, chunk, + estimation, interaction_simulate, logit, simulate, tracing, - workflow, util, + workflow, ) from activitysim.core.configuration.base import ComputeSettings from activitysim.core.skim_dataset import DatasetWrapper diff --git a/activitysim/core/mp_tasks.py b/activitysim/core/mp_tasks.py index db92be1dad..7d31134bc0 100644 --- a/activitysim/core/mp_tasks.py +++ b/activitysim/core/mp_tasks.py @@ -887,6 +887,7 @@ def setup_injectables_and_logging(injectables, locutor: bool = True) -> workflow state = workflow.State() state = state.initialize_filesystem(**injectables) state.settings = injectables.get("settings", Settings()) + state.filesystem.parse_settings(state.settings) # register abm steps and other abm-specific injectables # by default, assume we are running activitysim.abm diff --git a/activitysim/core/workflow/state.py b/activitysim/core/workflow/state.py index f21810bb5f..dd81534605 100644 --- a/activitysim/core/workflow/state.py +++ b/activitysim/core/workflow/state.py @@ -478,15 +478,12 @@ def load_settings(self) -> State: include_stack=False, ) - # the settings can redefine the cache directories. - cache_dir = raw_settings.pop("cache_dir", None) - if cache_dir: - if self.filesystem.cache_dir != cache_dir: - logger.warning(f"settings file changes cache_dir to {cache_dir}") - self.filesystem.cache_dir = cache_dir settings_class = self.__class__.settings.member_type self.settings: Settings = settings_class.model_validate(raw_settings) + # need to parse any filesystem settings set in the settings file itself + self.filesystem.parse_settings(self.settings) + extra_settings = set(self.settings.__dict__) - set(settings_class.__fields__) if extra_settings: diff --git a/activitysim/estimation/larch/__init__.py b/activitysim/estimation/larch/__init__.py index 1d87e1ce12..76d1cb8e9c 100644 --- a/activitysim/estimation/larch/__init__.py +++ b/activitysim/estimation/larch/__init__.py @@ -1,4 +1,7 @@ -import larch +from __future__ import annotations + +import larch as lx +from packaging.version import Version from .cdap import * from .data_maker import * @@ -10,6 +13,12 @@ from .simple_simulate import * from .stop_frequency import * +# require larch version 6.0.0 or later +if Version(larch.__version__) < Version("6.0.0"): + raise ImportError( + f"activitysim estimation mode requires larch version 6.0.0 or later. Found {larch.__version__}" + ) + def component_model(name, *args, **kwargs): if isinstance(name, str): @@ -25,6 +34,6 @@ def component_model(name, *args, **kwargs): models.append(model) all_data.extend(data) if all_data: - return ModelGroup(models), all_data + return lx.ModelGroup(models), all_data else: - return ModelGroup(models) + return lx.ModelGroup(models) diff --git a/activitysim/estimation/larch/auto_ownership.py b/activitysim/estimation/larch/auto_ownership.py deleted file mode 100644 index b008683bec..0000000000 --- a/activitysim/estimation/larch/auto_ownership.py +++ /dev/null @@ -1,80 +0,0 @@ -import os -from typing import Collection - -import numpy as np -import pandas as pd -import yaml -from larch import DataFrames, Model, P, X -from larch.util import Dict - -from .general import ( - apply_coefficients, - dict_of_linear_utility_from_spec, - remove_apostrophes, -) -from .simple_simulate import simple_simulate_data - - -def auto_ownership_model( - name="auto_ownership", - edb_directory="output/estimation_data_bundle/{name}/", - return_data=False, -): - data = simple_simulate_data( - name=name, - edb_directory=edb_directory, - values_index_col="household_id", - ) - coefficients = data.coefficients - # coef_template = data.coef_template # not used - spec = data.spec - chooser_data = data.chooser_data - settings = data.settings - - altnames = list(spec.columns[3:]) - altcodes = range(len(altnames)) - - chooser_data = remove_apostrophes(chooser_data) - chooser_data.fillna(0, inplace=True) - - # Remove choosers with invalid observed choice - chooser_data = chooser_data[chooser_data["override_choice"] >= 0] - - m = Model() - # One of the alternatives is coded as 0, so - # we need to explicitly initialize the MNL nesting graph - # and set to root_id to a value other than zero. - m.initialize_graph(alternative_codes=altcodes, root_id=99) - - m.utility_co = dict_of_linear_utility_from_spec( - spec, - "Label", - dict(zip(altnames, altcodes)), - ) - - apply_coefficients(coefficients, m) - - d = DataFrames( - co=chooser_data, - av=True, - alt_codes=altcodes, - alt_names=altnames, - ) - - m.dataservice = d - m.choice_co_code = "override_choice" - - if return_data: - return ( - m, - Dict( - edb_directory=data.edb_directory, - chooser_data=chooser_data, - coefficients=coefficients, - spec=spec, - altnames=altnames, - altcodes=altcodes, - ), - ) - - return m diff --git a/activitysim/estimation/larch/cdap.py b/activitysim/estimation/larch/cdap.py index 0f0f41218a..018c6976da 100644 --- a/activitysim/estimation/larch/cdap.py +++ b/activitysim/estimation/larch/cdap.py @@ -10,16 +10,16 @@ import larch import numpy as np import pandas as pd +import xarray as xr import yaml -from larch import DataFrames, Model, P, X -from larch.log import logger_name +from larch import Dataset, Model, P, X from larch.model.model_group import ModelGroup from larch.util import Dict from ...abm.models.util import cdap from .general import apply_coefficients, explicit_value_parameters -_logger = logging.getLogger(logger_name) +_logger = logging.getLogger("larch") MAX_HHSIZE = 5 @@ -275,7 +275,7 @@ def cdap_joint_tour_utility(model, n_persons, alts, joint_coef, values): expression_value = "&".join(expression_list) # FIXME only apply to alternative if dependency satisfied - bug + raise NotImplementedError("bug") model.utility_co[anum] += X(expression_value) * P(coefficient) elif "_px" in expression: @@ -283,7 +283,7 @@ def cdap_joint_tour_utility(model, n_persons, alts, joint_coef, values): dependency_name = row.dependency.replace("x", str(pnum)) expression = row.Expression.replace("x", str(pnum)) # FIXME only apply to alternative if dependency satisfied - bug + raise NotImplementedError("bug") model.utility_co[anum] += X(expression) * P(coefficient) else: @@ -329,18 +329,29 @@ def cdap_split_data(households, values, add_joint): return cdap_data -def cdap_dataframes(households, values, add_joint): +def cdap_dataframes(households, values, add_joint) -> dict[int, Dataset]: data = cdap_split_data(households, values, add_joint) dfs = {} for hhsize in data.keys(): alts = generate_alternatives(hhsize, add_joint) - dfs[hhsize] = DataFrames( - co=data[hhsize], - alt_names=alts.keys(), - alt_codes=alts.values(), - av=1, - ch=data[hhsize].override_choice.map(alts), + dfs[hhsize] = Dataset.construct.from_idco( + data[hhsize], + alts=dict(zip(alts.values(), alts.keys())), ) + # convert override_choice to alternative code from alternative name + dfs[hhsize]["override_choice"] = xr.DataArray( + np.vectorize(alts.get)(dfs[hhsize].override_choice.data), + coords=dfs[hhsize].override_choice.coords, + dims=dfs[hhsize].override_choice.dims, + name="override_choice", + ) + # dfs[hhsize] = DataFrames( + # co=data[hhsize], + # alt_names=alts.keys(), + # alt_codes=alts.values(), + # av=1, + # ch=data[hhsize].override_choice.map(alts), + # ) return dfs @@ -388,11 +399,18 @@ def cdap_data( raise FileNotFoundError(edb_directory) def read_csv(filename, **kwargs): - filename = filename.format(name=name) - return pd.read_csv(os.path.join(edb_directory, filename), **kwargs) + filename = Path(edb_directory).joinpath(filename.format(name=name)).resolve() + if filename.with_suffix(".parquet").exists(): + if "comment" in kwargs: + del kwargs["comment"] + print(f"Reading {filename.with_suffix('.parquet')}") + return pd.read_parquet(filename.with_suffix(".parquet"), **kwargs) + print(f"Reading {filename}") + return pd.read_csv(filename, **kwargs) def read_yaml(filename, **kwargs): filename = filename.format(name=name) + print(f"Reading {os.path.join(edb_directory, filename)}") with open(os.path.join(edb_directory, filename), "rt") as f: return yaml.load(f, Loader=yaml.SafeLoader, **kwargs) @@ -436,7 +454,7 @@ def read_yaml(filename, **kwargs): except FileNotFoundError: joint_coef = None add_joint = False - print("Including joint tour utiltiy?:", add_joint) + print("Including joint tour utility?:", add_joint) spec1 = read_csv(spec1_file, comment="#") values = read_csv(chooser_data_file, comment="#") @@ -497,9 +515,9 @@ def cdap_model( cdap_dfs = cdap_dataframes(households, values, add_joint) m = {} _logger.info(f"building for model 1") - m[1] = Model(dataservice=cdap_dfs[1]) + m[1] = Model(datatree=cdap_dfs[1], compute_engine="numba") cdap_base_utility_by_person(m[1], n_persons=1, spec=spec1) - m[1].choice_any = True + m[1].choice_co_code = "override_choice" m[1].availability_any = True # Add cardinality into interaction_coef if not present @@ -510,13 +528,13 @@ def cdap_model( for s in range(2, MAX_HHSIZE + 1): # for s in [2, 3, 4, 5]: _logger.info(f"building for model {s}") - m[s] = Model(dataservice=cdap_dfs[s]) + m[s] = Model(datatree=cdap_dfs[s]) alts = generate_alternatives(s, add_joint) cdap_base_utility_by_person(m[s], s, spec1, alts, values.columns) cdap_interaction_utility(m[s], s, alts, interaction_coef, coefficients) # if add_joint: # cdap_joint_tour_utility(m[s], s, alts, d.joint_coef, values) - m[s].choice_any = True + m[s].choice_co_code = "override_choice" m[s].availability_any = True model = ModelGroup(m.values()) diff --git a/activitysim/estimation/larch/general.py b/activitysim/estimation/larch/general.py index 4e4fc3adfa..19fb76e18a 100644 --- a/activitysim/estimation/larch/general.py +++ b/activitysim/estimation/larch/general.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import logging import os from pathlib import Path @@ -5,13 +7,14 @@ import numpy as np import pandas as pd -from larch import DataFrames, Model, P, X # noqa: F401 -from larch.log import logger_name -from larch.model.abstract_model import AbstractChoiceModel +from larch import Model, P, X # noqa: F401 + +# from larch.log import logger_name +# from larch.model.abstract_model import AbstractChoiceModel from larch.model.tree import NestingTree from larch.util import Dict # noqa: F401 -_logger = logging.getLogger(logger_name) +_logger = logging.getLogger("larch") def cv_to_ca(alt_values, dtype="float64", required_labels=None): @@ -67,7 +70,12 @@ def cv_to_ca(alt_values, dtype="float64", required_labels=None): x_ca_tall = x_ca_tall.astype(dtype) # Unstack the variables dimension - x_ca = x_ca_tall.unstack(1) + x_ca = ( + x_ca_tall.reset_index() + .drop_duplicates() + .set_index(x_ca_tall.index.names) + .unstack(1) + ) # Code above added a dummy top level to columns, remove it here. x_ca.columns = x_ca.columns.droplevel(0) @@ -104,7 +112,9 @@ def str_repr(x): return x -def linear_utility_from_spec(spec, x_col, p_col, ignore_x=(), segment_id=None): +def linear_utility_from_spec( + spec, x_col, p_col, ignore_x=(), segment_id=None, x_validator=None, expr_col=None +): """ Create a linear function from a spec DataFrame. @@ -129,6 +139,13 @@ def linear_utility_from_spec(spec, x_col, p_col, ignore_x=(), segment_id=None): The CHOOSER_SEGMENT_COLUMN_NAME identified for ActivitySim. This value is ignored if `p_col` is a string, and required if `p_col` is a dict. + x_validator : Container, optional + A container of valid values for the x_col. If given, the + x_col values will be used if they are `in` the x_validator, + otherwise the value from `expr_col` will be used. + expr_col : str, optional + The name of the column to use when the x_col value is not + in the x_validator. Returns ------- @@ -144,6 +161,8 @@ def linear_utility_from_spec(spec, x_col, p_col, ignore_x=(), segment_id=None): x_col, seg_p_col, ignore_x, + x_validator=x_validator, + expr_col=expr_col, ) * X(f"{segment_id}=={str_repr(segval)}") return sum(partial_utility.values()) parts = [] @@ -156,6 +175,16 @@ def linear_utility_from_spec(spec, x_col, p_col, ignore_x=(), segment_id=None): _x = None else: raise + + # when a validator is given, use the expression column if the original + # x value is not in the validator + if _x is not None and _x not in ignore_x: + if x_validator is not None and _x not in x_validator: + _x = spec.loc[i, expr_col] + if _x.startswith("@"): + _x = _x[1:] + + # handle the parameter... _p = spec.loc[i, p_col] if _x is not None and (_x not in ignore_x) and not pd.isna(_p): @@ -194,7 +223,9 @@ def linear_utility_from_spec(spec, x_col, p_col, ignore_x=(), segment_id=None): return sum(parts) -def dict_of_linear_utility_from_spec(spec, x_col, p_col, ignore_x=()): +def dict_of_linear_utility_from_spec( + spec, x_col, p_col, ignore_x=(), x_validator=None, expr_col=None +): """ Create a linear function from a spec DataFrame. @@ -216,6 +247,13 @@ def dict_of_linear_utility_from_spec(spec, x_col, p_col, ignore_x=()): The CHOOSER_SEGMENT_COLUMN_NAME identified for ActivitySim. This value is ignored if `p_col` is a string, and required if `p_col` is a dict. + x_validator : Container, optional + A container of valid values for the x_col. If given, the + x_col values will be used if they are `in` the x_validator, + otherwise the value from `expr_col` will be used. + expr_col : str, optional + The name of the column to use when the x_col value is not + in the x_validator. Returns ------- @@ -224,7 +262,12 @@ def dict_of_linear_utility_from_spec(spec, x_col, p_col, ignore_x=()): utils = {} for altname, altcode in p_col.items(): utils[altcode] = linear_utility_from_spec( - spec, x_col, altname, ignore_x=ignore_x + spec, + x_col, + altname, + ignore_x=ignore_x, + x_validator=x_validator, + expr_col=expr_col, ) return utils @@ -288,15 +331,7 @@ def explicit_value_parameters(model): except Exception: pass else: - model.set_value( - i, - value=j, - initvalue=j, - nullvalue=j, - minimum=j, - maximum=j, - holdfast=True, - ) + model.lock_value(i, value=j) def apply_coefficients(coefficients, model, minimum=None, maximum=None): @@ -326,25 +361,22 @@ def apply_coefficients(coefficients, model, minimum=None, maximum=None): ) coefficients["constrain"] = "F" assert coefficients.index.name == "coefficient_name" - assert isinstance(model, AbstractChoiceModel) + # assert isinstance(model, AbstractChoiceModel) explicit_value_parameters(model) for i in coefficients.itertuples(): - if i.Index in model: + if i.Index in model.pnames: holdfast = i.constrain == "T" if holdfast: - minimum_ = i.value - maximum_ = i.value + model.lock_value(i.Index, value=i.value) else: - minimum_ = minimum - maximum_ = maximum - model.set_value( - i.Index, - value=i.value, - initvalue=i.value, - holdfast=holdfast, - minimum=minimum_, - maximum=maximum_, - ) + model.set_value( + i.Index, + value=i.value, + initvalue=i.value, + holdfast=holdfast, + minimum=minimum, + maximum=maximum, + ) def apply_coef_template(linear_utility, template_col, condition=None): @@ -419,7 +451,8 @@ def make_nest(cfg, parent_code=0): else: make_nest(a, parent_code=nest_names_to_codes[cfg["name"]]) - make_nest(nesting_settings) + if nesting_settings: + make_nest(nesting_settings) return tree diff --git a/activitysim/estimation/larch/location_choice.py b/activitysim/estimation/larch/location_choice.py index dca1e9ea4a..7d797a754e 100644 --- a/activitysim/estimation/larch/location_choice.py +++ b/activitysim/estimation/larch/location_choice.py @@ -1,15 +1,17 @@ from __future__ import annotations +import collections import os -from pathlib import Path -from typing import Collection import pickle +import warnings from datetime import datetime +from pathlib import Path +from typing import Collection import numpy as np import pandas as pd import yaml -from larch import DataFrames, Model, P, X +from larch import Dataset, Model, P, X from larch.util import Dict from .general import ( @@ -37,6 +39,23 @@ def size_coefficients_from_spec(size_spec): return size_coef +LocationChoiceData = collections.namedtuple( + "LocationChoiceData", + field_names=[ + "edb_directory", + "alt_values", + "chooser_data", + "coefficients", + "landuse", + "spec", + "size_spec", + "master_size_spec", + "model_selector", + "settings", + ], +) + + def location_choice_model( name="workplace_location", edb_directory="output/estimation_data_bundle/{name}/", @@ -50,7 +69,9 @@ def location_choice_model( return_data=False, alt_values_to_feather=False, chunking_size=None, -): + *, + alts_in_cv_format=False, +) -> Model | tuple[Model, LocationChoiceData]: model_selector = name.replace("_location", "") model_selector = model_selector.replace("_destination", "") model_selector = model_selector.replace("_subtour", "") @@ -60,8 +81,12 @@ def location_choice_model( edb_directory = edb_directory.format(name=name) def _read_csv(filename, **kwargs): - filename = filename.format(name=name) - return pd.read_csv(os.path.join(edb_directory, filename), **kwargs) + filename = Path(edb_directory).joinpath(filename.format(name=name)) + if filename.with_suffix(".parquet").exists(): + print("loading from", filename.with_suffix(".parquet")) + return pd.read_parquet(filename.with_suffix(".parquet"), **kwargs) + print("loading from", filename) + return pd.read_csv(filename, **kwargs) def _read_feather(filename, **kwargs): filename = filename.format(name=name) @@ -179,7 +204,10 @@ def _file_exists(filename): if label_column_name == "Expression": spec.insert(0, "Label", spec["Expression"].map(expression_labels)) - alt_values["variable"] = alt_values["variable"].map(expression_labels) + if alts_in_cv_format: + alt_values["variable"] = alt_values["variable"].map(expression_labels) + else: + alt_values = alt_values.rename(columns=expression_labels) label_column_name = "Label" if name == "trip_destination": @@ -194,44 +222,58 @@ def split(a, n): k, m = divmod(len(a), n) return (a[i * k + min(i, m) : (i + 1) * k + min(i + 1, m)] for i in range(n)) - # process x_ca with cv_to_ca with or without chunking - x_ca_pickle_file = "{name}_x_ca.pkl" - if chunking_size == None: - x_ca = cv_to_ca( - alt_values.set_index([chooser_index_name, alt_values.columns[1]]) - ) - elif _file_exists(x_ca_pickle_file): - # if pickle file from previous x_ca processing exist, load it to save time - time_start = datetime.now() - x_ca = _read_pickle(x_ca_pickle_file) - print( - f"x_ca data loaded from {name}_x_ca.fea - time elapsed {(datetime.now() - time_start).total_seconds()}" - ) - else: - time_start = datetime.now() - # calculate num_chunks based on chunking_size (or max number of rows per chunk) - num_chunks = int(len(alt_values) / chunking_size) - id_col_name = alt_values.columns[0] - all_ids = list(alt_values[id_col_name].unique()) - split_ids = list(split(all_ids, num_chunks)) - x_ca_list = [] - i = 0 - for chunk_ids in split_ids: - alt_values_i = alt_values[alt_values[id_col_name].isin(chunk_ids)] - x_ca_i = cv_to_ca( - alt_values_i.set_index([chooser_index_name, alt_values_i.columns[1]]) + if alts_in_cv_format: + # if alternatives are in CV format, convert them to CA format. + # The CV format has the chooser index as the first column and the variable name + # as the second column, with values for each alternative in the remaining columns. + # This format is inefficient and deprecated as of ActivitySim version 1.4. + + # process x_ca with cv_to_ca with or without chunking + x_ca_pickle_file = "{name}_x_ca.pkl" + if chunking_size == None: + x_ca = cv_to_ca( + alt_values.set_index([chooser_index_name, alt_values.columns[1]]) ) - x_ca_list.append(x_ca_i) + elif _file_exists(x_ca_pickle_file): + # if pickle file from previous x_ca processing exist, load it to save time + time_start = datetime.now() + x_ca = _read_pickle(x_ca_pickle_file) print( - f"\rx_ca_i compute done for chunk {i}/{num_chunks} - time elapsed {(datetime.now() - time_start).total_seconds()}" + f"x_ca data loaded from {name}_x_ca.fea - time elapsed {(datetime.now() - time_start).total_seconds()}" ) - i = i + 1 - x_ca = pd.concat(x_ca_list, axis=0) - # save final x_ca result as pickle file to save time for future data loading - _to_pickle(df=x_ca, filename=x_ca_pickle_file) - print( - f"x_ca compute done - time elapsed {(datetime.now() - time_start).total_seconds()}" - ) + else: + time_start = datetime.now() + # calculate num_chunks based on chunking_size (or max number of rows per chunk) + num_chunks = int(len(alt_values) / chunking_size) + id_col_name = alt_values.columns[0] + all_ids = list(alt_values[id_col_name].unique()) + split_ids = list(split(all_ids, num_chunks)) + x_ca_list = [] + i = 0 + for chunk_ids in split_ids: + alt_values_i = alt_values[alt_values[id_col_name].isin(chunk_ids)] + x_ca_i = cv_to_ca( + alt_values_i.set_index( + [chooser_index_name, alt_values_i.columns[1]] + ) + ) + x_ca_list.append(x_ca_i) + print( + f"\rx_ca_i compute done for chunk {i}/{num_chunks} - time elapsed {(datetime.now() - time_start).total_seconds()}" + ) + i = i + 1 + x_ca = pd.concat(x_ca_list, axis=0) + # save final x_ca result as pickle file to save time for future data loading + _to_pickle(df=x_ca, filename=x_ca_pickle_file) + print( + f"x_ca compute done - time elapsed {(datetime.now() - time_start).total_seconds()}" + ) + else: + # otherwise, we assume that the alternatives are already in the correct IDCA format with + # the cases and alternatives as the first two columns, and the variables as the + # remaining columns. This is a much more efficient format for the data. + assert alt_values.columns[0] == chooser_index_name + x_ca = alt_values.set_index([chooser_index_name, alt_values.columns[1]]) if CHOOSER_SEGMENT_COLUMN_NAME is not None: # label segments with names @@ -263,23 +305,39 @@ def split(a, n): # Remove choosers with invalid observed choice (appropriate total size value = 0) valid_observed_zone = x_co["total_size_segment"] > 0 + prior_n_cases = len(x_co) x_co = x_co[valid_observed_zone] x_ca = x_ca[x_ca.index.get_level_values(chooser_index_name).isin(x_co.index)] + after_n_cases = len(x_co) + if prior_n_cases != after_n_cases: + warnings.warn( + f"Removed {prior_n_cases - after_n_cases} choosers with invalid (zero-sized) observed choice", + stacklevel=2, + ) # Merge land use characteristics into CA data - try: - x_ca_1 = pd.merge(x_ca, landuse, on="zone_id", how="left") - except KeyError: - # Missing the zone_id variable? - # Use the alternative id's instead, which assumes no sampling of alternatives - x_ca_1 = pd.merge( - x_ca, - landuse, - left_on=x_ca.index.get_level_values(1), - right_index=True, - how="left", - ) - x_ca_1.index = x_ca.index + x_ca_1 = pd.merge( + x_ca, landuse, left_on=x_ca.index.get_level_values(1), right_index=True + ) + x_ca_1 = x_ca_1.sort_index() + + # relabel zones to reduce memory usage. + # We will core the original zone ids in a new column _original_zone_id, + # and create a new index with a dummy zone id. This way, if we have sampled + # only a subset of 30 zones, then we only need 30 unique alternatives in the + # data structure. + original_zone_ids = x_ca_1.index.get_level_values(1) + + dummy_zone_ids_index = pd.MultiIndex.from_arrays( + [ + x_ca_1.index.get_level_values(0), + x_ca_1.groupby(level=0).cumcount() + 1, + ], + names=[x_ca_1.index.names[0], "dummy_zone_id"], + ) + x_ca_1.index = dummy_zone_ids_index + x_ca_1["_original_zone_id"] = original_zone_ids + choice_def = {"choice_ca_var": "override_choice == _original_zone_id"} # Availability of choice zones if "util_no_attractions" in x_ca_1: @@ -287,22 +345,44 @@ def split(a, n): x_ca_1["util_no_attractions"] .apply(lambda x: False if x == 1 else True) .astype(np.int8) + .to_xarray() ) elif "@df['size_term']==0" in x_ca_1: av = ( x_ca_1["@df['size_term']==0"] .apply(lambda x: False if x == 1 else True) .astype(np.int8) + .to_xarray() + ) + elif expression_labels is not None and "@df['size_term']==0" in expression_labels: + av = ( + x_ca_1[expression_labels["@df['size_term']==0"]] + .apply(lambda x: False if x == 1 else True) + .astype(np.int8) + .to_xarray() ) else: - av = 1 + av = None assert len(x_co) > 0, "Empty chooser dataframe" assert len(x_ca_1) > 0, "Empty alternatives dataframe" - d = DataFrames(co=x_co, ca=x_ca_1, av=av) + d_ca = Dataset.construct.from_idca(x_ca_1) + d_co = Dataset.construct.from_idco(x_co) + d = d_ca.merge(d_co) + if av is not None: + d["_avail_"] = av + + m = Model(datatree=d, compute_engine="numba") + + # One of the alternatives might be coded as 0, so + # we need to explicitly initialize the MNL nesting graph + # and set to root_id to a value other than zero. + root_id = 0 + if root_id in d.dc.altids(): + root_id = -1 + m.initialize_graph(alternative_codes=d.dc.altids(), root_id=root_id) - m = Model(dataservice=d) if len(spec.columns) == 4 and all( spec.columns == ["Label", "Description", "Expression", "coefficient"] ): @@ -311,6 +391,8 @@ def split(a, n): x_col="Label", p_col=spec.columns[-1], ignore_x=("local_dist",), + x_validator=d, + expr_col="Expression", ) elif ( len(spec.columns) == 4 @@ -323,6 +405,8 @@ def split(a, n): x_col="Label", p_col=spec.columns[-1], ignore_x=("local_dist",), + x_validator=d, + expr_col="Expression", ) else: m.utility_ca = linear_utility_from_spec( @@ -331,6 +415,8 @@ def split(a, n): p_col=SEGMENT_IDS, ignore_x=("local_dist",), segment_id=CHOOSER_SEGMENT_COLUMN_NAME, + x_validator=d, + expr_col="Expression", ) if CHOOSER_SEGMENT_COLUMN_NAME is None: @@ -354,12 +440,16 @@ def split(a, n): apply_coefficients(coefficients, m, minimum=-25, maximum=25) apply_coefficients(size_coef, m, minimum=-6, maximum=6) - m.choice_co_code = "override_choice" + m.choice_def(choice_def) + if av is not None: + m.availability_ca_var = "_avail_" + else: + m.availability_any = True if return_data: return ( m, - Dict( + LocationChoiceData( edb_directory=Path(edb_directory), alt_values=alt_values, chooser_data=chooser_data, diff --git a/activitysim/estimation/larch/mode_choice.py b/activitysim/estimation/larch/mode_choice.py index a790075e14..5e15fd0e0a 100644 --- a/activitysim/estimation/larch/mode_choice.py +++ b/activitysim/estimation/larch/mode_choice.py @@ -1,11 +1,14 @@ +from __future__ import annotations + import os from pathlib import Path from typing import Collection import numpy as np import pandas as pd +import xarray as xr import yaml -from larch import DataFrames, Model, P, X +from larch import Dataset, Model, P, X from larch.util import Dict from .general import ( @@ -54,7 +57,10 @@ def mode_choice_model( purposes.remove("atwork") # Setup purpose specific models - m = {purpose: Model(graph=tree, title=purpose) for purpose in purposes} + m = { + purpose: Model(graph=tree, title=purpose, compute_engine="numba") + for purpose in purposes + } for alt_code, alt_name in tree.elemental_names().items(): # Read in base utility function for this alt_name u = linear_utility_from_spec( @@ -73,31 +79,32 @@ def mode_choice_model( for model in m.values(): explicit_value_parameters(model) + model.availability_ca_var = "_avail_" apply_coefficients(coefficients, m) avail = construct_availability( m[purposes[0]], chooser_data, data.alt_codes_to_names ) - d = DataFrames( - co=chooser_data, - av=avail, - alt_codes=data.alt_codes, - alt_names=data.alt_names, + d = Dataset.construct.from_idco( + chooser_data, alts=dict(zip(data.alt_codes, data.alt_names)) ) + d["_avail_"] = xr.DataArray(avail, dims=(d.dc.CASEID, d.dc.ALTID)) if "atwork" not in name: for purpose, model in m.items(): - model.dataservice = d.selector_co(f"tour_type=='{purpose}'") + model.datatree = d.dc.query_cases(f"tour_type=='{purpose}'") model.choice_co_code = "override_choice_code" else: for purpose, model in m.items(): - model.dataservice = d + model.datatree = d model.choice_co_code = "override_choice_code" from larch.model.model_group import ModelGroup mg = ModelGroup(m.values()) + explicit_value_parameters(mg) + apply_coefficients(coefficients, mg) if return_data: return ( diff --git a/activitysim/estimation/larch/nonmand_tour_freq.py b/activitysim/estimation/larch/nonmand_tour_freq.py index c0db830e26..ff6835c410 100644 --- a/activitysim/estimation/larch/nonmand_tour_freq.py +++ b/activitysim/estimation/larch/nonmand_tour_freq.py @@ -1,14 +1,16 @@ +from __future__ import annotations + +import glob import logging import os +import pickle +from datetime import datetime from pathlib import Path import pandas as pd import yaml -from larch import DataFrames, Model -from larch.log import logger_name +from larch import Dataset, Model from larch.util import Dict -import pickle -from datetime import datetime from .general import ( apply_coefficients, @@ -17,7 +19,7 @@ remove_apostrophes, ) -_logger = logging.getLogger(logger_name) +_logger = logging.getLogger("larch") def interaction_simulate_data( @@ -29,16 +31,47 @@ def interaction_simulate_data( coefficients_files="{segment_name}/{name}_coefficients_{segment_name}.csv", chooser_data_files="{segment_name}/{name}_choosers_combined.csv", alt_values_files="{segment_name}/{name}_interaction_expression_values.csv", - segment_subset=[], + segment_subset=(), ): edb_directory = edb_directory.format(name=name) def _read_csv(filename, **kwargs): - filename = filename.format(name=name) - return pd.read_csv(os.path.join(edb_directory, filename), **kwargs) + filename = Path(edb_directory).joinpath(filename.format(name=name)) + if filename.with_suffix(".parquet").exists(): + print("loading from", filename.with_suffix(".parquet")) + if "comment" in kwargs: + kwargs.pop("comment") + return pd.read_parquet(filename.with_suffix(".parquet"), **kwargs) + if filename.exists(): + print("loading from", filename) + return pd.read_csv(filename, **kwargs) + # if the file does not exist, try to load parquet from a subdirectory + search_glob = os.path.join( + edb_directory, "*", filename.with_suffix(".parquet").name + ) + files = glob.glob(search_glob) + if files: + print("loading from", files[0]) + return pd.read_parquet(files[0], **kwargs) + # otherwise try to load csv from a subdirectory + search_glob = os.path.join(edb_directory, "*", filename.name) + files = glob.glob(search_glob) + if files: + print("loading from", files[0]) + return pd.read_csv(files[0], **kwargs) + raise FileNotFoundError(f"File {filename} not found") settings_file = settings_file.format(name=name) - with open(os.path.join(edb_directory, settings_file), "r") as yf: + settings_file_resolved = os.path.join(edb_directory, settings_file) + if not os.path.exists(settings_file_resolved): + search_glob = os.path.join(edb_directory, "*", settings_file) + settings_files = glob.glob(search_glob) + if not settings_files: + raise FileNotFoundError(f"Settings file {settings_file} not found") + else: + settings_file_resolved = settings_files[0] + + with open(settings_file_resolved) as yf: settings = yaml.load( yf, Loader=yaml.SafeLoader, @@ -113,7 +146,7 @@ def link_same_value_coefficients(segment_names, coefficients, spec): def unavail_parameters(model): - return model.pf.index[(model.pf.value < -900) & (model.pf.holdfast != 0)] + return model.pnames[(model.pvals < -900) & (model.pholdfast != 0)] def unavail_data_cols(model): @@ -202,8 +235,10 @@ def nonmand_tour_freq_model( edb_directory="output/estimation_data_bundle/{name}/", return_data=False, condense_parameters=False, - segment_subset=[], + segment_subset=(), num_chunks=1, + *, + alts_in_cv_format=False, ): """ Prepare nonmandatory tour frequency models for estimation. @@ -243,10 +278,13 @@ def nonmand_tour_freq_model( alt_values = data.alt_values alt_def = data.alt_def + # deduplicate rows in alt_def + alt_def = alt_def[~alt_def.index.duplicated(keep="first")] + m = {} for segment_name in segment_names: print(f"Creating larch model for {segment_name}") - segment_model = m[segment_name] = Model() + segment_model = m[segment_name] = Model(compute_engine="numba") # One of the alternatives is coded as 0, so # we need to explicitly initialize the MNL nesting graph # and set to root_id to a value other than zero. @@ -267,21 +305,29 @@ def nonmand_tour_freq_model( .set_index("person_id") .rename(columns={"TAZ": "HOMETAZ"}) ) - print("\t performing cv to ca step") - # x_ca = cv_to_ca(alt_values[segment_name].set_index(["person_id", "variable"])) - x_ca = get_x_ca_df( - alt_values=alt_values[segment_name].set_index(["person_id", "variable"]), - name=segment_name, - edb_directory=edb_directory.format(name="non_mandatory_tour_frequency"), - num_chunks=num_chunks, - ) + if alts_in_cv_format: + print("\t performing cv to ca step") + x_ca = get_x_ca_df( + alt_values=alt_values[segment_name].set_index( + ["person_id", "variable"] + ), + name=segment_name, + edb_directory=edb_directory.format(name="non_mandatory_tour_frequency"), + num_chunks=num_chunks, + ) + else: + x_ca = alt_values[segment_name].set_index(["person_id", "alt_id"]) - d = DataFrames( - co=x_co, - ca=x_ca, - av=~unavail(segment_model, x_ca), + d_co = Dataset.construct.from_idco( + x_co, + alts=alt_def.index.rename("alt_id"), ) - m[segment_name].dataservice = d + x_ca["_avail_"] = ~unavail(segment_model, x_ca) + # we set crack to False here so that we do not dissolve zero variance IDCAs + d_ca = Dataset.construct.from_idca(x_ca, crack=False) + d = d_ca.merge(d_co) + m[segment_name].datatree = d + m[segment_name].availability_ca_var = "_avail_" if return_data: return m, data diff --git a/activitysim/estimation/larch/scheduling.py b/activitysim/estimation/larch/scheduling.py index ea2aef1b2b..74d87e8af5 100644 --- a/activitysim/estimation/larch/scheduling.py +++ b/activitysim/estimation/larch/scheduling.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import os from pathlib import Path from typing import Collection @@ -5,7 +7,7 @@ import numpy as np import pandas as pd import yaml -from larch import DataFrames, Model, P, X +from larch import Dataset, Model, P, X from larch.util import Dict from .general import ( @@ -28,6 +30,8 @@ def schedule_choice_model( chooser_file="{name}_choosers_combined.csv", settings_file="{name}_model_settings.yaml", return_data=False, + *, + alts_in_cv_format=False, ): model_selector = name.replace("_location", "") model_selector = model_selector.replace("_destination", "") @@ -36,14 +40,16 @@ def schedule_choice_model( edb_directory = edb_directory.format(name=name) def _read_csv(filename, optional=False, **kwargs): - filename = filename.format(name=name) - try: - return pd.read_csv(os.path.join(edb_directory, filename), **kwargs) - except FileNotFoundError: - if optional: - return None - else: - raise + filename = Path(edb_directory).joinpath(filename.format(name=name)) + if filename.with_suffix(".parquet").exists(): + print("loading from", filename.with_suffix(".parquet")) + return pd.read_parquet(filename.with_suffix(".parquet"), **kwargs) + if filename.exists(): + print("loading from", filename) + return pd.read_csv(filename, **kwargs) + if optional: + return None + raise FileNotFoundError(filename) settings_file = settings_file.format(name=name) with open(os.path.join(edb_directory, settings_file), "r") as yf: @@ -96,7 +102,7 @@ def _read_csv(filename, optional=False, **kwargs): else: raise ValueError("cannot find Label or Expression in spec file") - m = Model() + m = Model(compute_engine="numba") if len(spec.columns) == 4 and ( [c.lower() for c in spec.columns] == ["label", "description", "expression", "coefficient"] @@ -131,12 +137,16 @@ def _read_csv(filename, optional=False, **kwargs): apply_coefficients(coefficients, m, minimum=-25, maximum=25) chooser_index_name = chooser_data.columns[0] - x_co = chooser_data.set_index(chooser_index_name) + x_co = chooser_data.set_index(chooser_index_name).dropna(axis=1, how="all") alt_values.fillna(0, inplace=True) - x_ca = cv_to_ca( - alt_values.set_index([chooser_index_name, alt_values.columns[1]]), - required_labels=spec[label_column_name], - ) + if alts_in_cv_format: + x_ca = cv_to_ca( + alt_values.set_index([chooser_index_name, alt_values.columns[1]]), + required_labels=spec[label_column_name], + ) + else: + # the alternative code is "tdd" + x_ca = alt_values.set_index([chooser_index_name, "tdd"]) # if CHOOSER_SEGMENT_COLUMN_NAME is not None: # # label segments with names @@ -148,22 +158,36 @@ def _read_csv(filename, optional=False, **kwargs): # x_co["_segment_label"] = size_spec.index[0] alt_codes = np.arange(len(x_ca.index.levels[1])) + 1 - x_ca.index = x_ca.index.set_levels(alt_codes, 1) + x_ca.index = x_ca.index.set_levels(alt_codes, level=1) x_co["override_choice_plus1"] = x_co["override_choice"] + 1 x_co["model_choice_plus1"] = x_co["model_choice"] + 1 unavail_coefs = coefficients.query("(constrain == 'T') & (value < -900)").index unavail_data = [i.data for i in m.utility_ca if i.param in unavail_coefs] - if len(unavail_data): + + if "mode_choice_logsum" in x_ca and not len(unavail_data): + joint_avail = "~(mode_choice_logsum_missing)" + elif len(unavail_data): joint_unavail = "|".join(f"({i}>0)" for i in unavail_data) joint_avail = f"~({joint_unavail})" else: - joint_avail = 1 - - d = DataFrames(co=x_co, ca=x_ca, av=joint_avail) - m.dataservice = d + joint_avail = None + + # d = DataFrames(co=x_co, ca=x_ca, av=joint_avail) # larch 5.7 + d_ca = Dataset.construct.from_idca(x_ca) + if joint_avail == "~(mode_choice_logsum_missing)": + tmp = np.isnan(d_ca["mode_choice_logsum"]) + tmp = tmp.drop_vars(tmp.coords) + d_ca = d_ca.assign(mode_choice_logsum_missing=tmp) + d_co = Dataset.construct.from_idco(x_co) + d = d_ca.merge(d_co) + # if joint_avail is not None: + # d["_avail_"] = joint_avail + + m.datatree = d m.choice_co_code = "override_choice_plus1" - # m.choice_co_code = "model_choice_plus1" + if joint_avail is not None: + m.availability_ca_var = joint_avail if return_data: return ( @@ -216,38 +240,53 @@ def construct_availability_ca(model, chooser_data, alt_codes_to_names): return avail -def mandatory_tour_scheduling_work_model(return_data=False): +def mandatory_tour_scheduling_work_model( + edb_directory="output/estimation_data_bundle/{name}/", return_data=False +): return schedule_choice_model( name="mandatory_tour_scheduling_work", + edb_directory=edb_directory, return_data=return_data, coefficients_file="tour_scheduling_work_coefficients.csv", ) -def mandatory_tour_scheduling_school_model(return_data=False): +def mandatory_tour_scheduling_school_model( + edb_directory="output/estimation_data_bundle/{name}/", return_data=False +): return schedule_choice_model( name="mandatory_tour_scheduling_school", + edb_directory=edb_directory, return_data=return_data, coefficients_file="tour_scheduling_school_coefficients.csv", ) -def non_mandatory_tour_scheduling_model(return_data=False): +def non_mandatory_tour_scheduling_model( + edb_directory="output/estimation_data_bundle/{name}/", return_data=False +): return schedule_choice_model( name="non_mandatory_tour_scheduling", + edb_directory=edb_directory, return_data=return_data, ) -def joint_tour_scheduling_model(return_data=False): +def joint_tour_scheduling_model( + edb_directory="output/estimation_data_bundle/{name}/", return_data=False +): return schedule_choice_model( name="joint_tour_scheduling", + edb_directory=edb_directory, return_data=return_data, ) -def atwork_subtour_scheduling_model(return_data=False): +def atwork_subtour_scheduling_model( + edb_directory="output/estimation_data_bundle/{name}/", return_data=False +): return schedule_choice_model( name="atwork_subtour_scheduling", + edb_directory=edb_directory, return_data=return_data, ) diff --git a/activitysim/estimation/larch/simple_simulate.py b/activitysim/estimation/larch/simple_simulate.py index e7c5d07cdc..f75d9642cb 100644 --- a/activitysim/estimation/larch/simple_simulate.py +++ b/activitysim/estimation/larch/simple_simulate.py @@ -1,10 +1,14 @@ +from __future__ import annotations + +import collections import os from pathlib import Path +import larch import numpy as np import pandas as pd import yaml -from larch import DataFrames, Model +from larch import Model from larch.util import Dict from .general import ( @@ -30,7 +34,7 @@ def construct_availability(model, chooser_data, alt_codes_to_names): pandas.DataFrame """ avail = {} - for acode, aname in alt_codes_to_names.items(): + for acode, _aname in alt_codes_to_names.items(): unavail_cols = list( ( chooser_data[i.data] @@ -49,6 +53,37 @@ def construct_availability(model, chooser_data, alt_codes_to_names): return avail +SimpleSimulateData = collections.namedtuple( + "SimpleSimulateData", + field_names=[ + "edb_directory", + "settings", + "chooser_data", + "coefficients", + "coef_template", + "spec", + "alt_names", + "alt_codes", + "alt_names_to_codes", + "alt_codes_to_names", + ], +) + + +def read_spec(filename: str | os.PathLike) -> pd.DataFrame: + """Read a simple simulate spec file""" + print("loading spec from", filename) + spec = pd.read_csv(filename, comment="#") + spec = remove_apostrophes(spec, ["Label"]) + + # remove temp rows from spec, ASim uses them to calculate the other values written + # to the EDB, but they are not actually part of the utility function themselves. + spec = spec.loc[~spec.Expression.isna()] + spec = spec.loc[~spec.Expression.str.startswith("_")].copy() + + return spec + + def simple_simulate_data( name="tour_mode_choice", edb_directory="output/estimation_data_bundle/{name}/", @@ -58,15 +93,20 @@ def simple_simulate_data( settings_file="{name}_model_settings.yaml", chooser_data_file="{name}_values_combined.csv", values_index_col="tour_id", -): - edb_directory = edb_directory.format(name=name) +) -> SimpleSimulateData: + edb_directory = str(edb_directory).format(name=name) def _read_csv(filename, **kwargs): - filename = filename.format(name=name) - return pd.read_csv(os.path.join(edb_directory, filename), **kwargs) + filename = Path(edb_directory).joinpath(filename.format(name=name)) + if filename.with_suffix(".parquet").exists(): + print("loading from", filename.with_suffix(".parquet")) + return pd.read_parquet(filename.with_suffix(".parquet"), **kwargs) + if filename.exists(): + print("loading from", filename) + return pd.read_csv(filename, **kwargs) settings_file = settings_file.format(name=name) - with open(os.path.join(edb_directory, settings_file), "r") as yf: + with open(os.path.join(edb_directory, settings_file)) as yf: settings = yaml.load( yf, Loader=yaml.SafeLoader, @@ -86,23 +126,16 @@ def _read_csv(filename, **kwargs): except FileNotFoundError: coef_template = None - spec = _read_csv(spec_file, comment="#") - spec = remove_apostrophes(spec, ["Label"]) - - # remove temp rows from spec, ASim uses them to calculate the other values written - # to the EDB, but they are not actually part of the utility function themselves. - spec = spec.loc[~spec.Expression.isna()] - spec = spec.loc[~spec.Expression.str.startswith("_")].copy() + spec = read_spec(Path(edb_directory).joinpath(spec_file.format(name=name))) alt_names = list(spec.columns[3:]) alt_codes = np.arange(1, len(alt_names) + 1) - alt_names_to_codes = dict(zip(alt_names, alt_codes)) - alt_codes_to_names = dict(zip(alt_codes, alt_names)) + alt_names_to_codes = dict(zip(alt_names, alt_codes, strict=False)) + alt_codes_to_names = dict(zip(alt_codes, alt_names, strict=False)) chooser_data = _read_csv( chooser_data_file, - index_col=values_index_col, - ) + ).set_index(values_index_col) except Exception: # when an error happens in reading anything other than settings, print settings @@ -111,7 +144,7 @@ def _read_csv(filename, **kwargs): pprint(settings) raise - return Dict( + return SimpleSimulateData( edb_directory=Path(edb_directory), settings=settings, chooser_data=chooser_data, @@ -157,33 +190,40 @@ def simple_simulate_model( if settings.get("LOGIT_TYPE") == "NL": tree = construct_nesting_tree(data.alt_names, settings["NESTS"]) - m = Model(graph=tree) else: - m = Model(alts=data.alt_codes_to_names) + tree = construct_nesting_tree(data.alt_names_to_codes, {}) + m = Model(compute_engine="numba") m.utility_co = dict_of_linear_utility_from_spec( spec, "Label", - dict(zip(alt_names, alt_codes)), + dict(zip(alt_names, alt_codes, strict=False)), + x_validator=chooser_data, + expr_col="Expression", ) apply_coefficients(coefficients, m) if construct_avail: avail = construct_availability(m, chooser_data, data.alt_codes_to_names) + d = larch.Dataset.construct.from_idco( + pd.concat([chooser_data, avail], axis=1), + alts=dict(zip(alt_codes, alt_names, strict=False)), + ) else: avail = True + d = larch.Dataset.construct.from_idco( + chooser_data, alts=dict(zip(alt_codes, alt_names, strict=False)) + ) - d = DataFrames( - co=chooser_data, - av=avail, - alt_codes=alt_codes, - alt_names=alt_names, - ) - - m.dataservice = d + m.datatree = d.dc.as_tree("df") + m.graph = tree m.choice_co_code = "override_choice_code" + # set bounds on unbounded coefficients, so that they don't get big + # and cause numerical errors which some optimizers can't handle + m.set_cap(50) + if return_data: return ( m, diff --git a/activitysim/estimation/larch/stop_frequency.py b/activitysim/estimation/larch/stop_frequency.py index e580491e02..17c8bd5050 100644 --- a/activitysim/estimation/larch/stop_frequency.py +++ b/activitysim/estimation/larch/stop_frequency.py @@ -1,10 +1,12 @@ +from __future__ import annotations + import os from pathlib import Path import numpy as np import pandas as pd import yaml -from larch import DataFrames, Model +from larch import Dataset, Model from larch.util import Dict from .general import ( @@ -25,11 +27,29 @@ def stop_frequency_data( edb_directory = edb_directory.format(name=name) settings_file = settings_file.format(name=name) - with open(os.path.join(edb_directory, settings_file), "r") as yf: - settings = yaml.load( - yf, - Loader=yaml.SafeLoader, - ) + try: + with open(os.path.join(edb_directory, settings_file), "r") as yf: + settings = yaml.load( + yf, + Loader=yaml.SafeLoader, + ) + except FileNotFoundError: + # search in all first level subdirectories for the settings file + for subdir in os.listdir(edb_directory): + if os.path.isdir(os.path.join(edb_directory, subdir)): + try: + with open( + os.path.join(edb_directory, subdir, settings_file), "r" + ) as yf: + settings = yaml.load( + yf, + Loader=yaml.SafeLoader, + ) + break + except FileNotFoundError: + pass + else: + raise segments = [i["primary_purpose"] for i in settings["SPEC_SEGMENTS"]] @@ -109,10 +129,30 @@ def stop_frequency_data( seg_alt_names_to_codes.append(alt_names_to_codes) seg_alt_codes_to_names.append(alt_codes_to_names) - chooser_data = pd.read_csv( - seg_subdir / chooser_data_file.format(name=name), - index_col=values_index_col, - ) + # load parquet if available, otherwise pickle, or if all else fails csv + if ( + (seg_subdir / chooser_data_file.format(name=name)) + .with_suffix(".parquet") + .exists() + ): + chooser_data = pd.read_parquet( + (seg_subdir / chooser_data_file.format(name=name)).with_suffix( + ".parquet" + ), + ).set_index(values_index_col) + elif ( + (seg_subdir / chooser_data_file.format(name=name)) + .with_suffix(".pkl") + .exists() + ): + chooser_data = pd.read_pickle( + (seg_subdir / chooser_data_file.format(name=name)).with_suffix(".pkl"), + ).set_index(values_index_col) + else: + chooser_data = pd.read_csv( + seg_subdir / chooser_data_file.format(name=name), + index_col=values_index_col, + ) seg_chooser_data.append(chooser_data) return Dict( @@ -163,9 +203,9 @@ def stop_frequency_model( if settings.get("LOGIT_TYPE") == "NL": tree = construct_nesting_tree(data.alt_names[n], settings["NESTS"]) - m = Model(graph=tree) + m = Model(graph=tree, compute_engine="numba") else: - m = Model() + m = Model(compute_engine="numba") m.utility_co = dict_of_linear_utility_from_spec( spec, @@ -177,15 +217,19 @@ def stop_frequency_model( avail = True - d = DataFrames( - co=chooser_data, - av=avail, - alt_codes=alt_codes, - alt_names=alt_names, + d = Dataset.construct.from_idco( + chooser_data, alts=dict(zip(alt_codes, alt_names)) ) - - m.dataservice = d + # d = DataFrames( + # co=chooser_data, + # av=avail, + # alt_codes=alt_codes, + # alt_names=alt_names, + # ) + + m.datatree = d m.choice_co_code = "override_choice_code" + m.availability_any = True models.append(m) from larch.model.model_group import ModelGroup diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml index 34b612c4ce..ff50c99ab5 100644 --- a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml @@ -102,7 +102,7 @@ estimation_table_recipes: omnibus_tables_append_columns: [values_combined] -model_estimation_table_types: +estimation_table_types: school_location: interaction_sample_simulate workplace_location: interaction_sample_simulate auto_ownership: simple_simulate diff --git a/activitysim/estimation/test/test_larch_estimation.py b/activitysim/estimation/test/test_larch_estimation.py index 09355f8469..c0ed4a44d3 100644 --- a/activitysim/estimation/test/test_larch_estimation.py +++ b/activitysim/estimation/test/test_larch_estimation.py @@ -39,7 +39,7 @@ def _regression_check(dataframe_regression, df, basename=None, rtol=None): rtol = 0.1 dataframe_regression.check( df.select_dtypes("number") - .drop(columns=["holdfast"], errors="ignore") + .drop(columns=["holdfast", "minimum", "maximum"], errors="ignore") .clip(-9e9, 9e9), # pandas 1.3 handles int8 dtypes as actual numbers, so holdfast needs to be dropped manually # we're dropping it not adding to the regression check so older pandas will also work. @@ -73,7 +73,7 @@ def test_simple_simulate(est_data, num_regression, dataframe_regression, name, m m.load_data() m.doctor(repair_ch_av="-") loglike_prior = m.loglike() - r = m.maximize_loglike(method=method, options={"maxiter": 1000}) + r = m.maximize_loglike(method=method, options={"maxiter": 1000, "ftol": 1e-9}) num_regression.check( {"loglike_prior": loglike_prior, "loglike_converge": r.loglike}, basename=f"test_simple_simulate_{name}_{method}_loglike", @@ -87,9 +87,11 @@ def test_simple_simulate(est_data, num_regression, dataframe_regression, name, m [ ("workplace_location", "SLSQP", None), ("school_location", "SLSQP", None), + ("school_location", "BHHH", None), ("non_mandatory_tour_destination", "SLSQP", None), ("atwork_subtour_destination", "BHHH", None), - ("trip_destination", "SLSQP", 0.12), + ("trip_destination", "BHHH", None), + # ("trip_destination", "SLSQP", 0.12), # trip_destination model has unusual parameter variance on a couple # parameters when switching platforms, possibly related to default data # types and high standard errors. Most parameters and the overall @@ -103,12 +105,12 @@ def test_location_model( from activitysim.estimation.larch import component_model, update_size_spec m, data = component_model(name, return_data=True) - m.load_data() + m.doctor(repair_av_zq="-", repair_nan_utility=True) loglike_prior = m.loglike() - r = m.maximize_loglike(method=method, options={"maxiter": 1000}) + r = m.maximize_loglike(method=method, options={"maxiter": 1000, "ftol": 1.0e-8}) num_regression.check( {"loglike_prior": loglike_prior, "loglike_converge": r.loglike}, - basename=f"test_loc_{name}_loglike", + basename=f"test_loc_{name}_{method}_loglike", ) _regression_check(dataframe_regression, m.pf, rtol=rtol) size_spec = update_size_spec( @@ -119,7 +121,7 @@ def test_location_model( ) dataframe_regression.check( size_spec, - basename=f"test_loc_{name}_size_spec", + basename=f"test_loc_{name}_{method}_size_spec", default_tolerance=dict(atol=1e-6, rtol=5e-2) # set a little loose, as there is sometimes a little variance in these # results when switching backend implementations. @@ -143,7 +145,7 @@ def test_scheduling_model(est_data, num_regression, dataframe_regression, name, m.load_data() m.doctor(repair_ch_av="-") loglike_prior = m.loglike() - r = m.maximize_loglike(method=method) + r = m.maximize_loglike(method=method, options={"maxiter": 1000, "ftol": 1.0e-9}) num_regression.check( {"loglike_prior": loglike_prior, "loglike_converge": r.loglike}, basename=f"test_{name}_loglike", @@ -158,7 +160,7 @@ def test_stop_freq_model(est_data, num_regression, dataframe_regression): m, data = component_model(name, return_data=True) m.load_data() loglike_prior = m.loglike() - r = m.maximize_loglike() + r = m.maximize_loglike(method="SLSQP", options={"maxiter": 1000, "ftol": 1.0e-9}) num_regression.check( {"loglike_prior": loglike_prior, "loglike_converge": r.loglike}, basename=f"test_{name}_loglike", @@ -222,7 +224,7 @@ def test_cdap_model(est_data, num_regression, dataframe_regression): m = cdap_model() m.load_data() loglike_prior = m.loglike() - r = m.maximize_loglike(method="SLSQP", options={"maxiter": 1000}) + r = m.maximize_loglike(method="SLSQP", options={"maxiter": 1000, "ftol": 1.0e-7}) num_regression.check( {"loglike_prior": loglike_prior, "loglike_converge": r.loglike}, basename="test_cdap_model_loglike", @@ -260,7 +262,7 @@ def test_tour_and_subtour_mode_choice(est_data, num_regression, dataframe_regres m.load_data() m.doctor(repair_ch_av="-") loglike_prior = m.loglike() - r = m.maximize_loglike(method="SLSQP", options={"maxiter": 1000}) + r = m.maximize_loglike(method="SLSQP", options={"maxiter": 1000, "ftol": 1.0e-9}) num_regression.check( {"loglike_prior": loglike_prior, "loglike_converge": r.loglike}, basename="test_tour_mode_choice_loglike", diff --git a/activitysim/estimation/test/test_larch_estimation/test_cdap_model.csv b/activitysim/estimation/test/test_larch_estimation/test_cdap_model.csv index a9e237b235..400eb2fb9c 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_cdap_model.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_cdap_model.csv @@ -1,162 +1,162 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_UNAVAILABLE,-999,-999,0,-999,-999,-999 -coef_child_who_is_in_school_or_too_young_for_school_interaction_with_off_peak_accessibility_to_retail_N,0.87159546592932291,0.08233,0,,,0.87159546592932291 -coef_driving_age_child_who_is_in_school_asc_M,0.74815228797618816,2.3309186849999999,0,,,0.74815228797618816 -coef_driving_age_child_who_is_in_school_asc_N,-9.0640177490324412,-0.59911911200000001,0,,,-9.0640177490324412 -coef_driving_age_child_who_is_in_school_interaction_income_between_50k_and_100k_H,-0.90601686275009163,-0.50309999999999999,0,,,-0.90601686275009163 -coef_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H,0.42727506400961712,0.64749999999999996,0,,,0.42727506400961712 -coef_driving_age_child_who_is_in_school_interaction_with_income_more_than_100k_H,-1.7272824609972235,-2.0459999999999998,0,,,-1.7272824609972235 -coef_driving_age_child_who_is_in_school_interaction_with_less_than_20k_H,0.45396678614268526,1.3069999999999999,0,,,0.45396678614268526 -coef_full_time_worker_asc_M,0.98435866822120488,1.3787345790000001,0,,,0.98435866822120488 -coef_full_time_worker_asc_N,0.73324510331920412,0.62266239099999998,0,,,0.73324510331920412 -coef_full_time_worker_interaction_with_age_less_than_40_M,0.44443952843908197,0.20910000000000001,0,,,0.44443952843908197 -coef_full_time_worker_interaction_with_female_gender_M,0.038410812572387439,-0.12590000000000001,0,,,0.038410812572387439 -coef_full_time_worker_interaction_with_fewer_cars_than_workers_H,0.41538570763618882,0.50390000000000001,0,,,0.41538570763618882 -coef_full_time_worker_interaction_with_income_less_than_20k_H,0.44991051165021323,0.53129999999999999,0,,,0.44991051165021323 -coef_full_time_worker_intraction_with_peak_accessibility_to_all_employment_M,0.15132046128679377,0.1212,0,,,0.15132046128679377 -coef_non_working_adult_asc_N,0.61315184259117572,0.59464538600000005,0,,,0.61315184259117572 -coef_non_working_adult_interaction_with_female_gender_M,-0.74299999999999999,-0.74299999999999999,0,,,-0.74299999999999999 -coef_non_working_adult_interaction_with_fewer_cars_than_workers_H,0.80008083982324651,0.89649999999999996,0,,,0.80008083982324651 -coef_non_working_adult_interaction_with_income_between_50k_and_100k_H,-1.135877229516298,-0.56020000000000003,0,,,-1.135877229516298 -coef_non_working_adult_interaction_with_income_more_than_100k_H,-0.53695636446511075,-0.71879999999999999,0,,,-0.53695636446511075 -coef_non_working_adult_interaction_with_more_cars_than_workers_M,0.65149999999999997,0.65149999999999997,0,,,0.65149999999999997 -coef_non_working_adult_interaction_with_more_cars_than_workers_N,1.4756696612117433,0.81679999999999997,0,,,1.4756696612117433 -coef_non_working_adult_interaction_with_peak_accessibility_to_all_employment_M,0.23139999999999999,0.23139999999999999,0,,,0.23139999999999999 -coef_non_working_adult_retired_or_univ_student_interaction_with_off_peak_accessibility_to_all_employment_N,0.05369614335005668,0.072069999999999995,0,,,0.05369614335005668 -coef_part_time_worker_asc_M,4.6632375293425374,-0.71882373799999999,0,,,4.6632375293425374 -coef_part_time_worker_asc_N,0.63327669200378511,0.63603246700000005,0,,,0.63327669200378511 -coef_part_time_worker_interaction_with_income_between_50k_and_100k_H,0.084764438455744495,-0.4032,0,,,0.084764438455744495 -coef_part_time_worker_interaction_with_income_less_than_20k_H,0.38471102017852971,0.32319999999999999,0,,,0.38471102017852971 -coef_part_time_worker_interaction_with_income_more_than_100k_H,-1.3396802216835464,-0.35339999999999999,0,,,-1.3396802216835464 -coef_part_time_worker_interaction_with_income_more_than_100k_N,0.57320315896108665,0.42070000000000002,0,,,0.57320315896108665 -coef_part_time_worker_interaction_with_peak_accessibility_to_all_employment_M,-0.22927275954114743,0.20039999999999999,0,,,-0.22927275954114743 -coef_pre_driving_age_child_who_is_in_school_asc_M,3.9697740814213565,3.295863529,0,,,3.9697740814213565 -coef_pre_driving_age_child_who_is_in_school_asc_N,-6.9669814176755258,0.57142433999999998,0,,,-6.9669814176755258 -coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_M,-1.5862536567965162,-0.71409999999999996,0,,,-1.5862536567965162 -coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_N,-1.1444471156694567,-0.67200000000000004,0,,,-1.1444471156694567 -coef_pre_driving_age_child_who_is_in_school_interaction_with_age_6_to_9_M,-0.71694326641444928,-0.29430000000000001,0,,,-0.71694326641444928 -coef_pre_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H,1.0962667615224149,0.58620000000000005,0,,,1.0962667615224149 -coef_pre_driving_age_child_who_is_too_young_for_school_asc_M,0.92486435043901694,1.052531189,0,,,0.92486435043901694 -coef_pre_driving_age_child_who_is_too_young_for_school_asc_N,-8.6130259294995177,-0.83756777599999999,0,,,-8.6130259294995177 -coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_0_to_1_M,-0.94468281293415513,-0.45150000000000001,0,,,-0.94468281293415513 -coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_4_to_5_M,0.23268035055770159,0.61070000000000002,0,,,0.23268035055770159 -coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_fewer_cars_than_workers_H,-0.056007934757943807,0.50609999999999999,0,,,-0.056007934757943807 -coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_between_50k_and_100k_H,-0.71502868941234388,-0.57079999999999997,0,,,-0.71502868941234388 -coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_more_than_100k_H,-0.7760438496909059,-0.61860000000000004,0,,,-0.7760438496909059 -coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_more_cars_than_workers_N,0.77447196962877585,0.29909999999999998,0,,,0.77447196962877585 -coef_retired_asc_N,1.1425900456454805,0.408202071,0,,,1.1425900456454805 -coef_retired_interaction_with_age_more_than_80_H,1.1363693439466673,0.76659999999999995,0,,,1.1363693439466673 -coef_retired_interaction_with_female_M,0.47689999999999999,0.47689999999999999,0,,,0.47689999999999999 -coef_retired_interaction_with_fewer_cars_than_workers_H,1.1295952477348739,0.54959999999999998,0,,,1.1295952477348739 -coef_retired_interaction_with_income_less_than_20k_H,0.65398902348188781,0.53300000000000003,0,,,0.65398902348188781 -coef_retired_interaction_with_more_cars_than_workers_M,2.992,2.992,0,,,2.992 -coef_retired_interaction_with_more_cars_than_workers_N,0.76262176538305015,1.056,0,,,0.76262176538305015 -coef_retired_interaction_with_peak_accessibility_to_all_employment_M,0.2792,0.2792,0,,,0.2792 -coef_university_student_asc_M,2.1206612172447477,2.3535951759999998,0,,,2.1206612172447477 -coef_university_student_asc_N,0.47323909115586493,0.609709846,0,,,0.47323909115586493 --999.0,-999,-999,-999,-999,-999,-999 -coef_H_11,1.5446242163709172,1.6259999999999999,0,,,1.5446242163709172 -coef_H_12,0.15833568776463425,0.74070000000000003,0,,,0.15833568776463425 -coef_H_13,1.5389002358533881,1.1830000000000001,0,,,1.5389002358533881 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+coef_non_working_adult_asc_N,0.5032527423546157,0.5032527423546157,0.59464538600000005,0 +coef_non_working_adult_interaction_with_female_gender_M,-0.74299999999999999,-0.74299999999999999,-0.74299999999999999,0 +coef_non_working_adult_interaction_with_fewer_cars_than_workers_H,0.79550405235037291,0.79550405235037291,0.89649999999999996,0 +coef_non_working_adult_interaction_with_income_between_50k_and_100k_H,-1.1335473989478433,-1.1335473989478433,-0.56020000000000003,0 +coef_non_working_adult_interaction_with_income_more_than_100k_H,-0.52876095625819419,-0.52876095625819419,-0.71879999999999999,0 +coef_non_working_adult_interaction_with_more_cars_than_workers_M,0.65149999999999997,0.65149999999999997,0.65149999999999997,0 +coef_non_working_adult_interaction_with_more_cars_than_workers_N,1.4789652448709654,1.4789652448709654,0.81679999999999997,0 +coef_non_working_adult_interaction_with_peak_accessibility_to_all_employment_M,0.23139999999999999,0.23139999999999999,0.23139999999999999,0 +coef_non_working_adult_retired_or_univ_student_interaction_with_off_peak_accessibility_to_all_employment_N,0.064939130822218152,0.064939130822218152,0.072069999999999995,0 +coef_part_time_worker_asc_M,6.3592603940417298,6.3592603940417298,-0.71882373799999999,0 +coef_part_time_worker_asc_N,0.62900096289821572,0.62900096289821572,0.63603246700000005,0 +coef_part_time_worker_interaction_with_income_between_50k_and_100k_H,0.083715416192307907,0.083715416192307907,-0.4032,0 +coef_part_time_worker_interaction_with_income_less_than_20k_H,0.37591205189659627,0.37591205189659627,0.32319999999999999,0 +coef_part_time_worker_interaction_with_income_more_than_100k_H,-1.344577739113451,-1.344577739113451,-0.35339999999999999,0 +coef_part_time_worker_interaction_with_income_more_than_100k_N,0.57926282447447563,0.57926282447447563,0.42070000000000002,0 +coef_part_time_worker_interaction_with_peak_accessibility_to_all_employment_M,-0.36291295851748201,-0.36291295851748201,0.20039999999999999,0 +coef_pre_driving_age_child_who_is_in_school_asc_M,3.9364917022114958,3.9364917022114958,3.295863529,0 +coef_pre_driving_age_child_who_is_in_school_asc_N,-1.4901825824862984,-1.4901825824862984,0.57142433999999998,0 +coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_M,-1.560760489357776,-1.560760489357776,-0.71409999999999996,0 +coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_N,-1.1582880792288159,-1.1582880792288159,-0.67200000000000004,0 +coef_pre_driving_age_child_who_is_in_school_interaction_with_age_6_to_9_M,-0.69702865509680834,-0.69702865509680834,-0.29430000000000001,0 +coef_pre_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H,1.0807804461266468,1.0807804461266468,0.58620000000000005,0 +coef_pre_driving_age_child_who_is_too_young_for_school_asc_M,0.93791299554872232,0.93791299554872232,1.052531189,0 +coef_pre_driving_age_child_who_is_too_young_for_school_asc_N,-3.1168217219705499,-3.1168217219705499,-0.83756777599999999,0 +coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_0_to_1_M,-0.97840886625486712,-0.97840886625486712,-0.45150000000000001,0 +coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_4_to_5_M,0.22680433121070148,0.22680433121070148,0.61070000000000002,0 +coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_fewer_cars_than_workers_H,-0.064351049344718039,-0.064351049344718039,0.50609999999999999,0 +coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_between_50k_and_100k_H,-0.70378572103967652,-0.70378572103967652,-0.57079999999999997,0 +coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_more_than_100k_H,-0.77304583320350251,-0.77304583320350251,-0.61860000000000004,0 +coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_more_cars_than_workers_N,0.69633632402948109,0.69633632402948109,0.29909999999999998,0 +coef_retired_asc_N,1.0264990433635548,1.0264990433635548,0.408202071,0 +coef_retired_interaction_with_age_more_than_80_H,1.1355402656793447,1.1355402656793447,0.76659999999999995,0 +coef_retired_interaction_with_female_M,0.47689999999999999,0.47689999999999999,0.47689999999999999,0 +coef_retired_interaction_with_fewer_cars_than_workers_H,1.1284456224788169,1.1284456224788169,0.54959999999999998,0 +coef_retired_interaction_with_income_less_than_20k_H,0.65094671152574535,0.65094671152574535,0.53300000000000003,0 +coef_retired_interaction_with_more_cars_than_workers_M,2.992,2.992,2.992,0 +coef_retired_interaction_with_more_cars_than_workers_N,0.76654574573265821,0.76654574573265821,1.056,0 +coef_retired_interaction_with_peak_accessibility_to_all_employment_M,0.2792,0.2792,0.2792,0 +coef_university_student_asc_M,2.1131909971292351,2.1131909971292351,2.3535951759999998,0 +coef_university_student_asc_N,0.35532700566947006,0.35532700566947006,0.609709846,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_cdap_model_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_cdap_model_loglike.csv index dcd755572e..cf7fc482c4 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_cdap_model_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_cdap_model_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-2460.72797581254872057,-2335.77494762967762654 +0,-2460.7280651590818,-2336.352120296393 diff --git a/activitysim/estimation/test/test_larch_estimation/test_joint_tour_scheduling_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_joint_tour_scheduling_loglike.csv index a8e60cc389..c5a6e449eb 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_joint_tour_scheduling_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_joint_tour_scheduling_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-1295.3015770898169,-175.64109886722656 +0,-185.1805538740314,-163.38981780168791 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_BHHH_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_BHHH_loglike.csv new file mode 100644 index 0000000000..90f36e10ea --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_BHHH_loglike.csv @@ -0,0 +1,2 @@ +,loglike_prior,loglike_converge +0,-1604.7051182769926,-1393.2868770044743 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_BHHH_size_spec.csv similarity index 97% rename from activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_size_spec.csv rename to activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_BHHH_size_spec.csv index 55915d90aa..1472d05ed2 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_size_spec.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_BHHH_size_spec.csv @@ -12,7 +12,7 @@ 10,othmaint,non_mandatory,0,0.48199999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 11,social,non_mandatory,0,0.52200000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 12,othdiscr,non_mandatory,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 -13,atwork,atwork,0,0.80359528369795752,0,0.19640471630204245,0,0,0,0,0,0,0 +13,atwork,atwork,0,0.9565182592635646,0,0.043481740736435397,0,0,0,0,0,0,0 14,work,trip,0,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0,0,0,0 15,escort,trip,0.001,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46400000000000002,0.16600000000000001,0,0 16,shopping,trip,0.001,0.999,0,0,0,0,0,0,0,0,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_loglike.csv deleted file mode 100644 index eb025e263b..0000000000 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_destination_loglike.csv +++ /dev/null @@ -1,2 +0,0 @@ -,loglike_prior,loglike_converge -0,-2334.2258751965092,-2329.8700459477177 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_scheduling_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_scheduling_loglike.csv deleted file mode 100644 index 65489ba050..0000000000 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_atwork_subtour_scheduling_loglike.csv +++ /dev/null @@ -1,2 +0,0 @@ -,loglike_prior,loglike_converge -0,-6685.5153616099333,-1437.800794640111 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_SLSQP_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_SLSQP_loglike.csv new file mode 100644 index 0000000000..77c3090874 --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_SLSQP_loglike.csv @@ -0,0 +1,2 @@ +,loglike_prior,loglike_converge +0,-8511.5032542114423,-7720.5833427253137 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_SLSQP_size_spec.csv similarity index 51% rename from activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_size_spec.csv rename to activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_SLSQP_size_spec.csv index af3285fe26..9aee2eecc1 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_size_spec.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_SLSQP_size_spec.csv @@ -1,23 +1,23 @@ ,segment,model_selector,TOTHH,RETEMPN,FPSEMPN,HEREMPN,OTHEMPN,AGREMPN,MWTEMPN,AGE0519,HSENROLL,COLLFTE,COLLPTE -0,work_low,workplace,0,0.12912912912912916,0.19319319319319325,0.38338338338338335,0.12012012012012015,0.010010010010010012,0.1641641641641641,0,0,0,0 -1,work_med,workplace,0,0.12012012012012013,0.19719719719719711,0.32532532532532538,0.13913913913913917,0.0080080080080080097,0.21021021021021022,0,0,0,0 +0,work_low,workplace,0,0.12912912912912911,0.19319319319319317,0.38338338338338335,0.12012012012012011,0.01001001001001001,0.16416416416416416,0,0,0,0 +1,work_med,workplace,0,0.12012012012012012,0.19719719719719719,0.32532532532532532,0.13913913913913914,0.0080080080080080079,0.21021021021021019,0,0,0,0 2,work_high,workplace,0,0.11,0.20699999999999999,0.28399999999999997,0.154,0.0060000000000000001,0.23899999999999999,0,0,0,0 3,work_veryhigh,workplace,0,0.092999999999999999,0.27000000000000002,0.24099999999999999,0.14599999999999999,0.0040000000000000001,0.246,0,0,0,0 -4,university,school,0,0,0,0,0,0,0,0,0,0.59200000000000008,0.40799999999999997 +4,university,school,0,0,0,0,0,0,0,0,0,0.59199999999999997,0.40799999999999997 5,gradeschool,school,0,0,0,0,0,0,0,1,0,0,0 6,highschool,school,0,0,0,0,0,0,0,0,1,0,0 -7,escort,non_mandatory,0,0.34195879720614686,0,0.13084293500721081,0,0,0,0.47127943957016599,0.055918828216476292,0,0 +7,escort,non_mandatory,0,0.46217099216294472,0,0.076417211673566368,0,0,0,0.45632020794852418,0.0050915882149647294,0,0 8,shopping,non_mandatory,0,1,0,0,0,0,0,0,0,0,0 -9,eatout,non_mandatory,0,0.65324866493964562,0,0.34675133506035422,0,0,0,0,0,0,0 -10,othmaint,non_mandatory,0,0.4233662207110353,0,0.57663377928896464,0,0,0,0,0,0,0 -11,social,non_mandatory,0,0.41656965799658413,0,0.58343034200341592,0,0,0,0,0,0,0 -12,othdiscr,non_mandatory,0.29737723981663911,0.27581414711676105,0,0.23370128672645701,0.12262191040591303,0,0,0,0.070485415934229814,0,0 +9,eatout,non_mandatory,0,0.90706301951236668,0,0.092936980487633311,0,0,0,0,0,0,0 +10,othmaint,non_mandatory,0,0.93116571483751687,0,0.068834285162483244,0,0,0,0,0,0,0 +11,social,non_mandatory,0,0.92391195421170202,0,0.076088045788297989,0,0,0,0,0,0,0 +12,othdiscr,non_mandatory,0.52511273726308272,0.27498108262234988,0,0.023448766399240456,0.15609458779050345,0,0,0,0.020362825924823438,0,0 13,atwork,atwork,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 14,work,trip,0,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0,0,0,0 -15,escort,trip,0.0010000000000000002,0.22500000000000003,0,0.14400000000000002,0,0,0,0.46399999999999997,0.16600000000000004,0,0 +15,escort,trip,0.001,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46400000000000002,0.16600000000000001,0,0 16,shopping,trip,0.001,0.999,0,0,0,0,0,0,0,0,0 17,eatout,trip,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 18,othmaint,trip,0.001,0.48099999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 19,social,trip,0.001,0.52100000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 20,othdiscr,trip,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 -21,univ,trip,0.000999000999000999,0,0,0,0,0,0,0,0,0.59140859140859148,0.4075924075924075 +21,univ,trip,0.00099900099900099922,0,0,0,0,0,0,0,0,0.59140859140859148,0.40759240759240761 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_loglike.csv deleted file mode 100644 index c5df93cabd..0000000000 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_destination_loglike.csv +++ /dev/null @@ -1,2 +0,0 @@ -,loglike_prior,loglike_converge -0,-12819.670044726949,-12802.203974292237 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_scheduling_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_scheduling_loglike.csv deleted file mode 100644 index d774c94c68..0000000000 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_non_mandatory_tour_scheduling_loglike.csv +++ /dev/null @@ -1,2 +0,0 @@ -,loglike_prior,loglike_converge -0,-12689.271731526222,-9843.6723572271876 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_BHHH_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_BHHH_loglike.csv new file mode 100644 index 0000000000..61faa0892d --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_BHHH_loglike.csv @@ -0,0 +1,2 @@ +,loglike_prior,loglike_converge +0,-3150.9027927232128,-2472.1256126886806 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_BHHH_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_BHHH_size_spec.csv new file mode 100644 index 0000000000..b5a4700325 --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_BHHH_size_spec.csv @@ -0,0 +1,23 @@ +,segment,model_selector,TOTHH,RETEMPN,FPSEMPN,HEREMPN,OTHEMPN,AGREMPN,MWTEMPN,AGE0519,HSENROLL,COLLFTE,COLLPTE +0,work_low,workplace,0,0.12912912912912911,0.19319319319319317,0.38338338338338335,0.12012012012012011,0.01001001001001001,0.16416416416416416,0,0,0,0 +1,work_med,workplace,0,0.12012012012012012,0.19719719719719719,0.32532532532532532,0.13913913913913914,0.0080080080080080079,0.21021021021021019,0,0,0,0 +2,work_high,workplace,0,0.11,0.20699999999999999,0.28399999999999997,0.154,0.0060000000000000001,0.23899999999999999,0,0,0,0 +3,work_veryhigh,workplace,0,0.092999999999999999,0.27000000000000002,0.24099999999999999,0.14599999999999999,0.0040000000000000001,0.246,0,0,0,0 +4,university,school,0,0,0,0,0,0,0,0,0,1,0 +5,gradeschool,school,0,0,0,0,0,0,0,1,0,0,0 +6,highschool,school,0,0,0,0,0,0,0,0,1,0,0 +7,escort,non_mandatory,0,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46500000000000002,0.16600000000000001,0,0 +8,shopping,non_mandatory,0,1,0,0,0,0,0,0,0,0,0 +9,eatout,non_mandatory,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 +10,othmaint,non_mandatory,0,0.48199999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 +11,social,non_mandatory,0,0.52200000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 +12,othdiscr,non_mandatory,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 +13,atwork,atwork,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 +14,work,trip,0,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0,0,0,0 +15,escort,trip,0.001,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46400000000000002,0.16600000000000001,0,0 +16,shopping,trip,0.001,0.999,0,0,0,0,0,0,0,0,0 +17,eatout,trip,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 +18,othmaint,trip,0.001,0.48099999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 +19,social,trip,0.001,0.52100000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 +20,othdiscr,trip,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 +21,univ,trip,0.00099900099900099922,0,0,0,0,0,0,0,0,0.59140859140859148,0.40759240759240761 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_SLSQP_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_SLSQP_loglike.csv new file mode 100644 index 0000000000..11f796f1c2 --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_SLSQP_loglike.csv @@ -0,0 +1,2 @@ +,loglike_prior,loglike_converge +0,-3150.9027927232128,-2472.5944704127669 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_SLSQP_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_SLSQP_size_spec.csv new file mode 100644 index 0000000000..569194ef5e --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_SLSQP_size_spec.csv @@ -0,0 +1,23 @@ +,segment,model_selector,TOTHH,RETEMPN,FPSEMPN,HEREMPN,OTHEMPN,AGREMPN,MWTEMPN,AGE0519,HSENROLL,COLLFTE,COLLPTE +0,work_low,workplace,0,0.12912912912912911,0.19319319319319317,0.38338338338338335,0.12012012012012011,0.01001001001001001,0.16416416416416416,0,0,0,0 +1,work_med,workplace,0,0.12012012012012012,0.19719719719719719,0.32532532532532532,0.13913913913913914,0.0080080080080080079,0.21021021021021019,0,0,0,0 +2,work_high,workplace,0,0.11,0.20699999999999999,0.28399999999999997,0.154,0.0060000000000000001,0.23899999999999999,0,0,0,0 +3,work_veryhigh,workplace,0,0.092999999999999999,0.27000000000000002,0.24099999999999999,0.14599999999999999,0.0040000000000000001,0.246,0,0,0,0 +4,university,school,0,0,0,0,0,0,0,0,0,0.99583037710619249,0.004169622893807531 +5,gradeschool,school,0,0,0,0,0,0,0,1,0,0,0 +6,highschool,school,0,0,0,0,0,0,0,0,1,0,0 +7,escort,non_mandatory,0,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46500000000000002,0.16600000000000001,0,0 +8,shopping,non_mandatory,0,1,0,0,0,0,0,0,0,0,0 +9,eatout,non_mandatory,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 +10,othmaint,non_mandatory,0,0.48199999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 +11,social,non_mandatory,0,0.52200000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 +12,othdiscr,non_mandatory,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 +13,atwork,atwork,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 +14,work,trip,0,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0,0,0,0 +15,escort,trip,0.001,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46400000000000002,0.16600000000000001,0,0 +16,shopping,trip,0.001,0.999,0,0,0,0,0,0,0,0,0 +17,eatout,trip,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 +18,othmaint,trip,0.001,0.48099999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 +19,social,trip,0.001,0.52100000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 +20,othdiscr,trip,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 +21,univ,trip,0.00099900099900099922,0,0,0,0,0,0,0,0,0.59140859140859148,0.40759240759240761 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_loglike.csv index 645ce49776..2e9a9a9bb2 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-4070.349038545839,-4058.2217927321499 +0,-3150.9027927232128,-2472.12561268868057596 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_size_spec.csv index 06a6f09b3b..569194ef5e 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_size_spec.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_school_location_size_spec.csv @@ -1,9 +1,9 @@ ,segment,model_selector,TOTHH,RETEMPN,FPSEMPN,HEREMPN,OTHEMPN,AGREMPN,MWTEMPN,AGE0519,HSENROLL,COLLFTE,COLLPTE -0,work_low,workplace,0,0.12912912912912916,0.19319319319319325,0.38338338338338335,0.12012012012012015,0.010010010010010012,0.1641641641641641,0,0,0,0 -1,work_med,workplace,0,0.12012012012012013,0.19719719719719711,0.32532532532532538,0.13913913913913917,0.0080080080080080097,0.21021021021021022,0,0,0,0 +0,work_low,workplace,0,0.12912912912912911,0.19319319319319317,0.38338338338338335,0.12012012012012011,0.01001001001001001,0.16416416416416416,0,0,0,0 +1,work_med,workplace,0,0.12012012012012012,0.19719719719719719,0.32532532532532532,0.13913913913913914,0.0080080080080080079,0.21021021021021019,0,0,0,0 2,work_high,workplace,0,0.11,0.20699999999999999,0.28399999999999997,0.154,0.0060000000000000001,0.23899999999999999,0,0,0,0 3,work_veryhigh,workplace,0,0.092999999999999999,0.27000000000000002,0.24099999999999999,0.14599999999999999,0.0040000000000000001,0.246,0,0,0,0 -4,university,school,0,0,0,0,0,0,0,0,0,0.66488586546020301,0.33511413453979705 +4,university,school,0,0,0,0,0,0,0,0,0,0.99583037710619249,0.004169622893807531 5,gradeschool,school,0,0,0,0,0,0,0,1,0,0,0 6,highschool,school,0,0,0,0,0,0,0,0,1,0,0 7,escort,non_mandatory,0,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46500000000000002,0.16600000000000001,0,0 @@ -14,10 +14,10 @@ 12,othdiscr,non_mandatory,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 13,atwork,atwork,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 14,work,trip,0,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0,0,0,0 -15,escort,trip,0.0010000000000000002,0.22500000000000003,0,0.14400000000000002,0,0,0,0.46399999999999997,0.16600000000000004,0,0 +15,escort,trip,0.001,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46400000000000002,0.16600000000000001,0,0 16,shopping,trip,0.001,0.999,0,0,0,0,0,0,0,0,0 17,eatout,trip,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 18,othmaint,trip,0.001,0.48099999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 19,social,trip,0.001,0.52100000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 20,othdiscr,trip,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 -21,univ,trip,0.000999000999000999,0,0,0,0,0,0,0,0,0.59140859140859148,0.4075924075924075 +21,univ,trip,0.00099900099900099922,0,0,0,0,0,0,0,0,0.59140859140859148,0.40759240759240761 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_loglike.csv new file mode 100644 index 0000000000..b6a4640e0d --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_loglike.csv @@ -0,0 +1,2 @@ +,loglike_prior,loglike_converge +0,-21837.014551855944,-8695.4742987000536 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_size_spec.csv similarity index 63% rename from activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_size_spec.csv rename to activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_size_spec.csv index 04abb0cc9c..ebfe3d5b78 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_size_spec.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_size_spec.csv @@ -13,11 +13,11 @@ 11,social,non_mandatory,0,0.52200000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 12,othdiscr,non_mandatory,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 13,atwork,atwork,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 -14,work,trip,0,0.24014195523694865,0.00059525239425258316,0.0025343890988937991,0.0013168081587181715,0.75481634271693376,0.00059525239425293412,0,0,0,0 -15,escort,trip,0.0025746521059848222,0.31583599496207332,0,0.0063819245118687607,0,0,0,0.56721029531390887,0.10799713310616434,0,0 -16,shopping,trip,0.28745939613255439,0.71254060386744567,0,0,0,0,0,0,0,0,0 -17,eatout,trip,0,0.98157984232483642,0,0.018420157675163609,0,0,0,0,0,0,0 -18,othmaint,trip,0.066897386356299673,0.76728057159935903,0,0.16582204204434134,0,0,0,0,0,0,0 -19,social,trip,0.028735588735319624,0.90003600813919549,0,0.071228403125484938,0,0,0,0,0,0,0 -20,othdiscr,trip,0.27326163859230651,0.71190812297572337,0,0.0026878884184924783,0.0094544615949851765,0,0,0,0.0026878884184924428,0,0 -21,univ,trip,0.16785552148845903,0,0,0,0,0,0,0,0,0.41607223925575049,0.41607223925579045 +14,work,trip,0,0.50988404412746136,2.8830314727604896e-146,0,1.2350245131417982e-12,0.48708399966352267,0.0030319562077810091,0,0,0,0 +15,escort,trip,0.99999999999752021,4.6306836616861319e-13,0,1.8807680387063182e-13,0,0,0,1.4480163162588933e-12,3.8063890886682389e-13,0,0 +16,shopping,trip,0.99999999865706501,1.3429349752304603e-09,0,0,0,0,0,0,0,0,0 +17,eatout,trip,0,1,0,0,0,0,0,0,0,0,0 +18,othmaint,trip,0.99999999998646205,9.0646768310272159e-12,0,4.4735228850332918e-12,0,0,0,0,0,0,0 +19,social,trip,0.99999999999998024,1.5851156966866637e-14,0,3.8443449490946144e-15,0,0,0,0,0,0,0 +20,othdiscr,trip,0.96881871015685461,0.031181191433995798,0,0,0,0,0,0,9.8409149668972833e-08,0,0 +21,univ,trip,1,0,0,0,0,0,0,0,0,4.8326974397473536e-21,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_loglike.csv deleted file mode 100644 index 7bed7a2ee0..0000000000 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_loglike.csv +++ /dev/null @@ -1,2 +0,0 @@ -,loglike_prior,loglike_converge -0,-27955.701284580879,-12569.486100216422 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_SLSQP_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_SLSQP_loglike.csv new file mode 100644 index 0000000000..4068e18c58 --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_SLSQP_loglike.csv @@ -0,0 +1,2 @@ +,loglike_prior,loglike_converge +0,-8694.1663931267794,-7268.5499545875718 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_SLSQP_size_spec.csv similarity index 72% rename from activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_size_spec.csv rename to activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_SLSQP_size_spec.csv index b568bafc7b..2ef299a31a 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_size_spec.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_SLSQP_size_spec.csv @@ -1,8 +1,8 @@ ,segment,model_selector,TOTHH,RETEMPN,FPSEMPN,HEREMPN,OTHEMPN,AGREMPN,MWTEMPN,AGE0519,HSENROLL,COLLFTE,COLLPTE -0,work_low,workplace,0,0.04331096924066484,0.17606247084331519,0.37453642466033488,0.16935644669165648,0.000968861288590913,0.23576482727543777,0,0,0,0 -1,work_med,workplace,0,0.11999183383359351,0.14366373395357587,0.25125860903337882,0.079402445282216183,0.0024785834941433989,0.40320479440309209,0,0,0,0 -2,work_high,workplace,0,0.15790294154771911,0.19045576988955706,0.29641460514585227,0.1682066889662423,0.0063903077215986892,0.18062968672903063,0,0,0,0 -3,work_veryhigh,workplace,0,0.062641019242734242,0.11667678718376452,0.13342796655219047,0.056368476597385232,0.51025642529636983,0.12062932512755588,0,0,0,0 +0,work_low,workplace,0,0.81009695995589714,0.015566120986122242,0.038205865646079792,0.059310593251792124,0.061254339173986733,0.015566120986122242,0,0,0,0 +1,work_med,workplace,0,0.8281013406144393,0.017105484027381986,0.031082288899413148,0.052366292140338909,0.054239110291044855,0.017105484027382,0,0,0,0 +2,work_high,workplace,0,0.83264652845133025,0.018762949054789986,0.021130105260407248,0.064579726133974238,0.044117742044708114,0.018762949054789986,0,0,0,0 +3,work_veryhigh,workplace,0,0.85877445882802128,0.022889127413081023,0.032513950668635973,0.027093642194477335,0.035839693482703265,0.022889127413081023,0,0,0,0 4,university,school,0,0,0,0,0,0,0,0,0,0.59199999999999997,0.40799999999999997 5,gradeschool,school,0,0,0,0,0,0,0,1,0,0,0 6,highschool,school,0,0,0,0,0,0,0,0,1,0,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_loglike.csv deleted file mode 100644 index 71e9b13b18..0000000000 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_workplace_location_loglike.csv +++ /dev/null @@ -1,2 +0,0 @@ -,loglike_prior,loglike_converge -0,-13535.154991016063,-13520.930381371694 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_atwork_subtour_destination_BHHH_None_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_atwork_subtour_destination_BHHH_None_.csv index f40a770d1b..69549a8874 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_location_model_atwork_subtour_destination_BHHH_None_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_location_model_atwork_subtour_destination_BHHH_None_.csv @@ -1,11 +1,11 @@ -,value,initvalue,nullvalue,minimum,maximum,best -atwork_HEREMPN,-1.7073243906685389,-1.3547956940605197,0,-6,6,-1.7073243906685389 -atwork_RETEMPN,-0.29840603581475661,-0.29840603581475661,0,-0.29840603581475661,-0.29840603581475661,-0.29840603581475661 -coef_distance_piecewise_linear_for_15_plus_miles,-0.20450000000000218,-0.20449999999999999,0,-25,25,-0.20450000000000218 -coef_distance_piecewise_linear_from_0_to_1_miles,-1.3641542578406347,-0.79259999999999997,0,-25,25,-1.3641542578406347 -coef_distance_piecewise_linear_from_1_to_2_miles,-0.73953227083074224,-0.79259999999999997,0,-25,25,-0.73953227083074224 -coef_distance_piecewise_linear_from_2_to_5_miles,-0.50452550250971084,-0.51970000000000005,0,-25,25,-0.50452550250971084 -coef_distance_piecewise_linear_from_5_to_15_miles,-0.073402957716087874,-0.20449999999999999,0,-25,25,-0.073402957716087874 -coef_mode_choice_logsum,0.50327067752307442,0.51359999999999995,0,-25,25,0.50327067752307442 -coef_no_attractions_atwork_size_variable_is_0,-999,-999,0,-999,-999,-999 -coef_sample_of_alternatives_correction_factor,1,1,0,1,1,1 +param_name,value,best,initvalue,nullvalue +atwork_HEREMPN,-3.389364816281855,-3.389364816281855,-1.3547956943511963,0 +atwork_RETEMPN,-0.29840603470802307,-0.29840603470802307,-0.29840603470802307,0 +coef_distance_piecewise_linear_for_15_plus_miles,-0.20450000464916254,-0.20450000464916254,-0.20450000464916229,0 +coef_distance_piecewise_linear_from_0_to_1_miles,-0.40672843393342367,-0.40672843393342367,-0.79259997606277466,0 +coef_distance_piecewise_linear_from_1_to_2_miles,0.46709869805144771,0.46709869805144771,-0.79259997606277466,0 +coef_distance_piecewise_linear_from_2_to_5_miles,0.11788881847828234,0.11788881847828234,-0.51969999074935913,0 +coef_distance_piecewise_linear_from_5_to_15_miles,0.25609050297480096,0.25609050297480096,-0.20450000464916229,0 +coef_mode_choice_logsum,0.73082605315228077,0.73082605315228077,0.51359999179840088,0 +coef_no_attractions_atwork_size_variable_is_0,-999,-999,-999,0 +coef_sample_of_alternatives_correction_factor,1,1,1,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_non_mandatory_tour_destination_SLSQP_None_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_non_mandatory_tour_destination_SLSQP_None_.csv index e771c163a3..20b6225820 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_location_model_non_mandatory_tour_destination_SLSQP_None_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_location_model_non_mandatory_tour_destination_SLSQP_None_.csv @@ -1,36 +1,36 @@ -,value,initvalue,nullvalue,minimum,maximum,best --999,-999,-999,-999,-999,-999,-999 -0,0,0,0,0,0,0 -1,1,1,1,1,1,1 -coef_eatout_dist_0_2,-0.84467402735490316,-0.56089999999999995,0,-25,25,-0.84467402735490316 -coef_eatout_dist_2_5,-0.19454520781373841,-0.31919999999999998,0,-25,25,-0.19454520781373841 -coef_eatout_dist_5_plus,-0.24629159495698957,-0.12379999999999999,0,-25,25,-0.24629159495698957 -coef_escort_dist_0_2,0.2228884413970586,-0.14990000000000001,0,-25,25,0.2228884413970586 -coef_escort_dist_2_5,-0.81521338400578147,-0.86709999999999998,0,-25,25,-0.81521338400578147 -coef_escort_dist_5_plus,-0.2563656478267789,-0.2137,0,-25,25,-0.2563656478267789 -coef_mode_logsum,0.65403821794149997,0.67549999999999999,0,-25,25,0.65403821794149997 -coef_othdiscr_dist_0_2,-0.18332164122229277,-0.16769999999999999,0,-25,25,-0.18332164122229277 -coef_othdiscr_dist_2_5,-0.57243431566525749,-0.4955,0,-25,25,-0.57243431566525749 -coef_othdiscr_dist_5_plus,0.022109773636770347,-0.1193,0,-25,25,0.022109773636770347 -coef_othmaint_dist_2_5,-0.56157171580357979,-0.60550000000000004,0,-25,25,-0.56157171580357979 -coef_othmaint_dist_5_plus,-0.22835432716850948,-0.10929999999999999,0,-25,25,-0.22835432716850948 -coef_shopping_dist_2_5,-0.62326413831589389,-0.5655,0,-25,25,-0.62326413831589389 -coef_shopping_dist_5_plus,-0.15909882569148343,-0.1832,0,-25,25,-0.15909882569148343 -coef_social_dist_2_5,-0.22738363386509225,-0.34849999999999998,0,-25,25,-0.22738363386509225 -coef_social_dist_5_plus,-0.17253037782714531,-0.13059999999999999,0,-25,25,-0.17253037782714531 -eatout_HEREMPN,-0.93175594508470749,-1.3547956940605197,0,-6,6,-0.93175594508470749 -eatout_RETEMPN,-0.29840603581475661,-0.29840603581475661,0,-0.29840603581475661,-0.29840603581475661,-0.29840603581475661 -escort_AGE0519,-1.1709029084521012,-0.7657178733947807,0,-6,6,-1.1709029084521012 -escort_HEREMPN,-2.4523610869729757,-1.9379419794061366,0,-6,6,-2.4523610869729757 -escort_HSENROLL,-3.3024337875479479,-1.7957674906255938,0,-6,6,-3.3024337875479479 -escort_RETEMPN,-1.4916548767777169,-1.4916548767777169,0,-1.4916548767777169,-1.4916548767777169,-1.4916548767777169 -othdiscr_HEREMPN,-1.6192946896579288,-1.3019532126861397,0,-6,6,-1.6192946896579288 -othdiscr_HSENROLL,-2.8175790455412613,-2.322787800311565,0,-6,6,-2.8175790455412613 -othdiscr_OTHEMPN,-2.264214574744007,-1.8018098050815563,0,-6,6,-2.264214574744007 -othdiscr_RETEMPN,-1.4536083464363203,-1.5511690043101247,0,-6,6,-1.4536083464363203 -othdiscr_TOTHH,-1.3783261914707137,-1.3783261914707137,0,-1.3783261914707137,-1.3783261914707137,-1.3783261914707137 -othmaint_HEREMPN,-0.42083070691744962,-0.65778003672265395,0,-6,6,-0.42083070691744962 -othmaint_RETEMPN,-0.72981116493153675,-0.72981116493153675,0,-0.72981116493153675,-0.72981116493153675,-0.72981116493153675 -shopping_RETEMPN,0,0,0,0,0,0 -social_HEREMPN,-0.31321849637618082,-0.73814454649068106,0,-6,6,-0.31321849637618082 -social_RETEMPN,-0.65008769109949827,-0.65008769109949827,0,-0.65008769109949827,-0.65008769109949827,-0.65008769109949827 +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +0,0,0,0,0 +1,1,1,1,0 +coef_eatout_dist_0_2,-0.36241753757283562,-0.36241753757283562,-0.56089997291564941,0 +coef_eatout_dist_2_5,0.1455948784794848,0.1455948784794848,-0.31920000910758972,0 +coef_eatout_dist_5_plus,-0.10347949759758775,-0.10347949759758775,-0.12380000203847885,0 +coef_escort_dist_0_2,0.37311835505986723,0.37311835505986723,-0.14990000426769257,0 +coef_escort_dist_2_5,0.021780514441237811,0.021780514441237811,-0.86710000038146973,0 +coef_escort_dist_5_plus,-0.11719861112519546,-0.11719861112519546,-0.21369999647140503,0 +coef_mode_logsum,0.58058639629827868,0.58058639629827868,0.67549997568130493,0 +coef_othdiscr_dist_0_2,-0.034089264034826726,-0.034089264034826726,-0.16769999265670776,0 +coef_othdiscr_dist_2_5,-0.064582241662395776,-0.064582241662395776,-0.49549999833106995,0 +coef_othdiscr_dist_5_plus,0.12360016041678727,0.12360016041678727,-0.1193000003695488,0 +coef_othmaint_dist_2_5,0.047194485653217981,0.047194485653217981,-0.6054999828338623,0 +coef_othmaint_dist_5_plus,-0.070139812280223396,-0.070139812280223396,-0.10930000245571136,0 +coef_shopping_dist_2_5,-0.084141591614817768,-0.084141591614817768,-0.56550002098083496,0 +coef_shopping_dist_5_plus,0.023925641427879701,0.023925641427879701,-0.18320000171661377,0 +coef_social_dist_2_5,0.15872711881616419,0.15872711881616419,-0.34850001335144043,0 +coef_social_dist_5_plus,-0.056983193388194325,-0.056983193388194325,-0.13060000538825989,0 +eatout_HEREMPN,-2.5766963293863645,-2.5766963293863645,-1.3547956943511963,0 +eatout_RETEMPN,-0.29840603470802307,-0.29840603470802307,-0.29840603470802307,0 +escort_AGE0519,-1.504395034914503,-1.504395034914503,-0.76571786403656006,0 +escort_HEREMPN,-3.2913818539226063,-3.2913818539226063,-1.9379420280456543,0 +escort_HSENROLL,-6,-6,-1.7957675457000732,0 +escort_RETEMPN,-1.4916548728942871,-1.4916548728942871,-1.4916548728942871,0 +othdiscr_HEREMPN,-4.4871212668473426,-4.4871212668473426,-1.3019531965255737,0 +othdiscr_HSENROLL,-4.6282281748496779,-4.6282281748496779,-2.3227877616882324,0 +othdiscr_OTHEMPN,-2.5914769992848368,-2.5914769992848368,-1.8018097877502441,0 +othdiscr_RETEMPN,-2.0252368499435924,-2.0252368499435924,-1.5511690378189087,0 +othdiscr_TOTHH,-1.3783261775970459,-1.3783261775970459,-1.3783261775970459,0 +othmaint_HEREMPN,-3.3345464979357597,-3.3345464979357597,-0.65778005123138428,0 +othmaint_RETEMPN,-0.72981119155883789,-0.72981119155883789,-0.72981119155883789,0 +shopping_RETEMPN,0,0,0,0 +social_HEREMPN,-3.1468133266863965,-3.1468133266863965,-0.73814451694488525,0 +social_RETEMPN,-0.65008771419525146,-0.65008771419525146,-0.65008771419525146,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_school_location_BHHH_None_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_school_location_BHHH_None_.csv new file mode 100644 index 0000000000..33b657c2c3 --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_location_model_school_location_BHHH_None_.csv @@ -0,0 +1,21 @@ +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +1,1,1,1,0 +coef_grade_dist_0_1,0.080031235198373782,0.080031235198373782,-1.6418999433517456,0 +coef_grade_dist_15_up,-0.046010368210409304,-0.046010368210409304,-0.046000000089406967,0 +coef_grade_dist_5_15,0.011795679963699891,0.011795679963699891,-0.20309999585151672,0 +coef_high_dist_0_1,-0.48267138976026713,-0.48267138976026713,-0.95230001211166382,0 +coef_high_dist_15_up,-0.18818654818448871,-0.18818654818448871,-0.18819999694824219,0 +coef_high_dist_5_15,-0.12203943917498229,-0.12203943917498229,-0.19300000369548798,0 +coef_high_grade_dist_1_2,-0.2740077638163641,-0.2740077638163641,-0.56999999284744263,0 +coef_high_grade_dist_2_5,-0.12717991662132286,-0.12717991662132286,-0.56999999284744263,0 +coef_mode_logsum,0.28675535602711366,0.28675535602711366,0.53579998016357422,0 +coef_univ_dist_0_1,-0.20246864835878667,-0.20246864835878667,-3.2451000213623047,0 +coef_univ_dist_15_up,-0.072999830047635036,-0.072999830047635036,-0.072999998927116394,0 +coef_univ_dist_1_2,-0.50654663083945994,-0.50654663083945994,-2.7011001110076904,0 +coef_univ_dist_2_5,0.095856729554638809,0.095856729554638809,-0.57069998979568481,0 +coef_univ_dist_5_15,-0.1412133832985831,-0.1412133832985831,-0.50019997358322144,0 +gradeschool_AGE0519,0,0,0,0 +highschool_HSENROLL,0,0,0,0 +university_COLLFTE,-0.52424865961074829,-0.52424865961074829,-0.52424865961074829,0 +university_COLLPTE,-1275009.279056468,-1275009.279056468,-0.89648813009262085,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_school_location_SLSQP_None_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_school_location_SLSQP_None_.csv index a8d3375aba..1f4a5bf905 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_location_model_school_location_SLSQP_None_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_location_model_school_location_SLSQP_None_.csv @@ -1,21 +1,21 @@ -,value,initvalue,nullvalue,minimum,maximum,best --999,-999,-999,-999,-999,-999,-999 -1,1,1,1,1,1,1 -coef_grade_dist_0_1,-1.8247870973053,-1.6418999999999999,0,-25,25,-1.8247870973053 -coef_grade_dist_15_up,-0.045999999999999999,-0.045999999999999999,0,-25,25,-0.045999999999999999 -coef_grade_dist_5_15,-0.14366307042924978,-0.2031,0,-25,25,-0.14366307042924978 -coef_high_dist_0_1,-2.1639997502226276,-0.95230000000000004,0,-25,25,-2.1639997502226276 -coef_high_dist_15_up,-0.18820000000000001,-0.18820000000000001,0,-25,25,-0.18820000000000001 -coef_high_dist_5_15,-0.10033338505701977,-0.193,0,-25,25,-0.10033338505701977 -coef_high_grade_dist_1_2,-0.74768688779537662,-0.56999999999999995,0,-25,25,-0.74768688779537662 -coef_high_grade_dist_2_5,-0.66638573965332526,-0.56999999999999995,0,-25,25,-0.66638573965332526 -coef_mode_logsum,0.37504471661044059,0.53580000000000005,0,-25,25,0.37504471661044059 -coef_univ_dist_0_1,-3.3138919948169607,-3.2450999999999999,0,-25,25,-3.3138919948169607 -coef_univ_dist_15_up,-0.072999999999999995,-0.072999999999999995,0,-25,25,-0.072999999999999995 -coef_univ_dist_1_2,-2.8752075620640434,-2.7010999999999998,0,-25,25,-2.8752075620640434 -coef_univ_dist_2_5,-0.45544418705038636,-0.57069999999999999,0,-25,25,-0.45544418705038636 -coef_univ_dist_5_15,-0.57189713873239967,-0.50019999999999998,0,-25,25,-0.57189713873239967 -gradeschool_AGE0519,0,0,0,0,0,0 -highschool_HSENROLL,0,0,0,0,0,0 -university_COLLFTE,-0.52424864409813143,-0.52424864409813143,0,-0.52424864409813143,-0.52424864409813143,-0.52424864409813143 -university_COLLPTE,-1.2091557399547264,-0.89648810457797545,0,-6,6,-1.2091557399547264 +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +1,1,1,1,0 +coef_grade_dist_0_1,0.097116326549615037,0.097116329571923371,-1.6418999433517456,0 +coef_grade_dist_15_up,-0.046000000089406967,-0.046000000089406967,-0.046000000089406967,0 +coef_grade_dist_5_15,0.012514539653739084,0.012514539708327558,-0.20309999585151672,0 +coef_high_dist_0_1,-0.4391430660668546,-0.43914306516185797,-0.95230001211166382,0 +coef_high_dist_15_up,-0.18819999694824219,-0.18819999694824219,-0.18819999694824219,0 +coef_high_dist_5_15,-0.12223669864939674,-0.12223669850105187,-0.19300000369548798,0 +coef_high_grade_dist_1_2,-0.27721668286846185,-0.27721668361053109,-0.56999999284744263,0 +coef_high_grade_dist_2_5,-0.12625067319470287,-0.12625067314690649,-0.56999999284744263,0 +coef_mode_logsum,0.28931317404209661,0.28931317414746177,0.53579998016357422,0 +coef_univ_dist_0_1,-0.34044181122123379,-0.34044180684505398,-3.2451000213623047,0 +coef_univ_dist_15_up,-0.072999998927116394,-0.072999998927116394,-0.072999998927116394,0 +coef_univ_dist_1_2,-0.42252956674554115,-0.42252956729334301,-2.7011001110076904,0 +coef_univ_dist_2_5,0.092094672169464362,0.092094672140662429,-0.57069998979568481,0 +coef_univ_dist_5_15,-0.14137251312653148,-0.14137251329149328,-0.50019997358322144,0 +gradeschool_AGE0519,0,0,0,0 +highschool_HSENROLL,0,0,0,0 +university_COLLFTE,-0.52424865961074829,-0.52424865961074829,-0.52424865961074829,0 +university_COLLPTE,-6,-6,-0.89648813009262085,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_BHHH_None_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_BHHH_None_.csv new file mode 100644 index 0000000000..23e3026cfb --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_BHHH_None_.csv @@ -0,0 +1,48 @@ +param_name,value,best,initvalue,nullvalue +coef_UNAVAILABLE,-999,-999,-999,0 +coef_distance_joint,-0.30113542396064802,-0.30113542396064802,-0.12380000203847885,0 +coef_mode_choice_logsum,0.082682967088151746,0.082682967088151746,1.8209999799728394,0 +coef_one,1,1,1,0 +coef_prox_dest_outbound_work,6.4877761350612664,6.4877761350612664,-0.25999999046325684,0 +coef_prox_home_inbound_work,-0.42511543980575345,-0.42511543980575345,-0.15000000596046448,0 +coef_prox_home_outbound_work,6.4721898798728912,6.4721898798728912,-0.37999999523162842,0 +coef_util_distance_atwork,-0.12262386654203787,-0.12262386654203787,-0.12233459949493408,0 +coef_util_distance_eatout,-0.31527866138216842,-0.31527866138216842,-0.10289999842643738,0 +coef_util_distance_escort,-0.20896432406414306,-0.20896432406414306,-0.14910000562667847,0 +coef_util_distance_othdiscr,-0.32948687106831859,-0.32948687106831859,-0.12617222964763641,0 +coef_util_distance_othmaint,-0.18983651887636419,-0.18983651887636419,-0.096199996769428253,0 +coef_util_distance_school,-0.10589786663451535,-0.10589786663451535,-0.10559999942779541,0 +coef_util_distance_shopping,-0.31439120424553951,-0.31439120424553951,-0.11919999867677689,0 +coef_util_distance_social,-0.21252031645681738,-0.21252031645681738,-0.13289999961853027,0 +coef_util_distance_univ,-0.16366566512380015,-0.16366566512380015,-0.061299998313188553,0 +coef_util_distance_work_inbound,-6.9206223055934686,-6.9206223055934686,0.14781327545642853,0 +coef_util_distance_work_outbound,-0.15694164906466096,-0.15694164906466096,-0.049725916236639023,0 +eatout_HEREMPN,-819.1055252552693,-819.1055252552693,-1.3547956943511963,0 +eatout_RETEMPN,-0.29840603470802307,-0.29840603470802307,-0.29840603470802307,0 +escort_AGE0519,-34.168581928799881,-34.168581928799881,-0.76787072420120239,0 +escort_HEREMPN,-36.209681359186099,-36.209681359186099,-1.9379420280456543,0 +escort_HSENROLL,-35.504680589841293,-35.504680589841293,-1.7957675457000732,0 +escort_RETEMPN,-35.308657067519476,-35.308657067519476,-1.4916548728942871,0 +escort_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +othdiscr_HEREMPN,-1590.2443769893835,-1590.2443769893835,-1.3019531965255737,0 +othdiscr_HSENROLL,-17.480780456151027,-17.480780456151027,-2.3227877616882324,0 +othdiscr_OTHEMPN,-4066.3792692241386,-4066.3792692241386,-1.8018097877502441,0 +othdiscr_RETEMPN,-4.8145886079817819,-4.8145886079817819,-1.5511690378189087,0 +othdiscr_TOTHH,-1.3783261775970459,-1.3783261775970459,-1.3783261775970459,0 +othmaint_HEREMPN,-33.040600275142353,-33.040600275142353,-0.65778005123138428,0 +othmaint_RETEMPN,-32.334391297442174,-32.334391297442174,-0.73188799619674683,0 +othmaint_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +shopping_RETEMPN,-27.336163711692908,-27.336163711692908,-0.0010005002841353416,0 +shopping_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +social_HEREMPN,-40.099928545719862,-40.099928545719862,-0.73814451694488525,0 +social_RETEMPN,-38.683289277404818,-38.683289277404818,-0.65200525522232056,0 +social_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +univ_COLLFTE,-53.686637539870517,-53.686637539870517,-0.52424865961074829,0 +univ_COLLPTE,-18324.145024591242,-18324.145024591242,-0.89648813009262085,0 +univ_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +work_AGREMPN,-0.045746743293575393,-0.045746743293575393,0,0 +work_FPSEMPN,-334.44500929829275,-334.44500929829275,0,0 +work_HEREMPN,-11947.426957365406,-11947.426957365406,0,0 +work_MWTEMPN,-5.1249753110793721,-5.1249753110793721,0,0 +work_OTHEMPN,-26.746358353776838,-26.746358353776838,0,0 +work_RETEMPN,0,0,0,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_SLSQP_0_12_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_SLSQP_0_12_.csv deleted file mode 100644 index abe98d47df..0000000000 --- a/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_SLSQP_0_12_.csv +++ /dev/null @@ -1,48 +0,0 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_UNAVAILABLE,-999,-999,0,-999,-999,-999 -coef_distance_joint,-0.37640163363394014,-0.12379999999999999,0,-25,25,-0.37640163363394014 -coef_mode_choice_logsum,0.16302637352162752,1.821,0,-25,25,0.16302637352162752 -coef_one,1,1,0,1,1,1 -coef_prox_dest_outbound_work,-0.59976096803081336,-0.26000000000000001,0,-25,25,-0.59976096803081336 -coef_prox_home_inbound_work,-0.17411187178992643,-0.14999999999999999,0,-25,25,-0.17411187178992643 -coef_prox_home_outbound_work,-0.76295690223363544,-0.38,0,-25,25,-0.76295690223363544 -coef_util_distance_atwork,-0.122334597,-0.122334597,0,-25,25,-0.122334597 -coef_util_distance_eatout,-0.36619050394180647,-0.10290000000000001,0,-25,25,-0.36619050394180647 -coef_util_distance_escort,-0.33778430073643445,-0.14910000000000001,0,-25,25,-0.33778430073643445 -coef_util_distance_othdiscr,-0.40879077774005879,-0.126172224,0,-25,25,-0.40879077774005879 -coef_util_distance_othmaint,-0.2579687786027548,-0.096199999999999994,0,-25,25,-0.2579687786027548 -coef_util_distance_school,-0.1056,-0.1056,0,-25,25,-0.1056 -coef_util_distance_shopping,-0.39048426507116651,-0.1192,0,-25,25,-0.39048426507116651 -coef_util_distance_social,-0.33876758749031255,-0.13289999999999999,0,-25,25,-0.33876758749031255 -coef_util_distance_univ,-0.18638287666609779,-0.0613,0,-25,25,-0.18638287666609779 -coef_util_distance_work_inbound,0.14549074690265271,0.147813278663948,0,-25,25,0.14549074690265271 -coef_util_distance_work_outbound,-0.30050379136271688,-0.049725915742290003,0,-25,25,-0.30050379136271688 -eatout_HEREMPN,-4.2741238026831576,-1.3547956940605197,0,-6,6,-4.2741238026831576 -eatout_RETEMPN,-0.29840603581475661,-0.29840603581475661,0,-0.29840603581475661,-0.29840603581475661,-0.29840603581475661 -escort_AGE0519,-1.5127395733276923,-0.76787072675588175,0,-6,6,-1.5127395733276923 -escort_HEREMPN,-5.9999999999999591,-1.9379419794061366,0,-6,6,-5.9999999999999591 -escort_HSENROLL,-3.1713650180398978,-1.7957674906255938,0,-6,6,-3.1713650180398978 -escort_RETEMPN,-2.0982466239249806,-1.4916548767777169,0,-6,6,-2.0982466239249806 -escort_TOTHH,-6.9077552789821368,-6.9077552789821368,0,-6.9077552789821368,-6.9077552789821368,-6.9077552789821368 -othdiscr_HEREMPN,-5.9999999999999867,-1.3019532126861397,0,-6,6,-5.9999999999999867 -othdiscr_HSENROLL,-6,-2.322787800311565,0,-6,6,-6 -othdiscr_OTHEMPN,-4.7422691542793025,-1.8018098050815563,0,-6,6,-4.7422691542793025 -othdiscr_RETEMPN,-0.42080704850071809,-1.5511690043101247,0,-6,6,-0.42080704850071809 -othdiscr_TOTHH,-1.3783261914707137,-1.3783261914707137,0,-1.3783261914707137,-1.3783261914707137,-1.3783261914707137 -othmaint_HEREMPN,-5.9999999999977494,-0.65778003672265395,0,-6,6,-5.9999999999977494 -othmaint_RETEMPN,-4.4680626390475311,-0.73188800887637595,0,-6,6,-4.4680626390475311 -othmaint_TOTHH,-6.9077552789821368,-6.9077552789821368,0,-6.9077552789821368,-6.9077552789821368,-6.9077552789821368 -shopping_RETEMPN,-5.9999999999990461,-0.0010005003335835344,0,-6,6,-5.9999999999990461 -shopping_TOTHH,-6.9077552789821368,-6.9077552789821368,0,-6.9077552789821368,-6.9077552789821368,-6.9077552789821368 -social_HEREMPN,-5.9999999999996891,-0.73814454649068106,0,-6,6,-5.9999999999996891 -social_RETEMPN,-3.4634568876043041,-0.65200523722877013,0,-6,6,-3.4634568876043041 -social_TOTHH,-6.9077552789821368,-6.9077552789821368,0,-6.9077552789821368,-6.9077552789821368,-6.9077552789821368 -univ_COLLFTE,-5.9999999999981588,-0.52424864409813143,0,-6,6,-5.9999999999981588 -univ_COLLPTE,-5.9999999999980629,-0.89648810457797545,0,-6,6,-5.9999999999980629 -univ_TOTHH,-6.9077552789821368,-6.9077552789821368,0,-6.9077552789821368,-6.9077552789821368,-6.9077552789821368 -work_AGREMPN,1.1452442363377451,0,0,-6,6,1.1452442363377451 -work_FPSEMPN,-5.9999999999998632,0,0,-6,6,-5.9999999999998632 -work_HEREMPN,-4.5512776072689656,0,0,-6,6,-4.5512776072689656 -work_MWTEMPN,-5.9999999999992735,0,0,-6,6,-5.9999999999992735 -work_OTHEMPN,-5.2060194818516452,0,0,-6,6,-5.2060194818516452 -work_RETEMPN,0,0,0,0,0,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_workplace_location_SLSQP_None_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_workplace_location_SLSQP_None_.csv index 4fbab98906..d4b8d728d6 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_location_model_workplace_location_SLSQP_None_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_location_model_workplace_location_SLSQP_None_.csv @@ -1,35 +1,35 @@ -,value,initvalue,nullvalue,minimum,maximum,best --999,-999,-999,-999,-999,-999,-999 -1,1,1,1,1,1,1 -coef_dist_0_1,-1.0822922946274103,-0.84279999999999999,0,-25,25,-1.0822922946274103 -coef_dist_0_5_high,0.1207879915621165,0.14999999999999999,0,-25,25,0.1207879915621165 -coef_dist_15_up,-0.091700000000000004,-0.091700000000000004,0,-25,25,-0.091700000000000004 -coef_dist_1_2,-0.24766620079389307,-0.31040000000000001,0,-25,25,-0.24766620079389307 -coef_dist_2_5,-0.3685512775196465,-0.37830000000000003,0,-25,25,-0.3685512775196465 -coef_dist_5_15,-0.15169975841932976,-0.1285,0,-25,25,-0.15169975841932976 -coef_dist_5_up_high,-0.015068815366553389,0.02,0,-25,25,-0.015068815366553389 -coef_mode_logsum,0.1608428973358158,0.29999999999999999,0,-25,25,0.1608428973358158 -work_high_AGREMPN,-5.414473039484391,-5.1159958097540823,0,-6,6,-5.414473039484391 -work_high_FPSEMPN,-2.0198354749074623,-1.575036485716768,0,-6,6,-2.0198354749074623 -work_high_HEREMPN,-1.5774962961301324,-1.258781040820931,0,-6,6,-1.5774962961301324 -work_high_MWTEMPN,-2.0728064576402221,-1.4312917270506265,0,-6,6,-2.0728064576402221 -work_high_OTHEMPN,-2.1440619487784449,-1.870802676568508,0,-6,6,-2.1440619487784449 -work_high_RETEMPN,-2.2072749131897207,-2.2072749131897207,0,-2.2072749131897207,-2.2072749131897207,-2.2072749131897207 -work_low_AGREMPN,-5.8479826351063204,-4.6051701859880909,0,-6,6,-5.8479826351063204 -work_low_FPSEMPN,-0.64550992870675994,-1.6450650900772514,0,-6,6,-0.64550992870675994 -work_low_HEREMPN,0.10934025159883133,-0.95972028980149104,0,-6,6,0.10934025159883133 -work_low_MWTEMPN,-0.35351399513998311,-1.8078888511579385,0,-6,6,-0.35351399513998311 -work_low_OTHEMPN,-0.68434316293298214,-2.120263536200091,0,-6,6,-0.68434316293298214 -work_low_RETEMPN,-2.0479428746204649,-2.0479428746204649,0,-2.0479428746204649,-2.0479428746204649,-2.0479428746204649 -work_med_AGREMPN,-6,-4.8283137373023015,0,-6,6,-6 -work_med_FPSEMPN,-1.9402118373687092,-1.6245515502441485,0,-6,6,-1.9402118373687092 -work_med_HEREMPN,-1.3812045016840873,-1.1239300966523995,0,-6,6,-1.3812045016840873 -work_med_MWTEMPN,-0.90824261771266779,-1.5606477482646683,0,-6,6,-0.90824261771266779 -work_med_OTHEMPN,-2.533158060495702,-1.9732813458514451,0,-6,6,-2.533158060495702 -work_med_RETEMPN,-2.120263536200091,-2.120263536200091,0,-2.120263536200091,-2.120263536200091,-2.120263536200091 -work_veryhigh_AGREMPN,-0.27766271475654764,-5.521460917862246,0,-6,6,-0.27766271475654764 -work_veryhigh_FPSEMPN,-1.7531684994723506,-1.3093333199837622,0,-6,6,-1.7531684994723506 -work_veryhigh_HEREMPN,-1.6190143529862893,-1.422958345491482,0,-6,6,-1.6190143529862893 -work_veryhigh_MWTEMPN,-1.7198536938187046,-1.4024237430497744,0,-6,6,-1.7198536938187046 -work_veryhigh_OTHEMPN,-2.4806660321461727,-1.9241486572738007,0,-6,6,-2.4806660321461727 -work_veryhigh_RETEMPN,-2.375155785828881,-2.375155785828881,0,-2.375155785828881,-2.375155785828881,-2.375155785828881 +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +1,1,1,1,0 +coef_dist_0_1,-0.29614981943016305,-0.29614981943016305,-0.84280002117156982,0 +coef_dist_0_5_high,-0.037934685148704593,-0.037934685148704593,0.15000000596046448,0 +coef_dist_15_up,-0.091700002551078796,-0.091700002551078796,-0.091700002551078796,0 +coef_dist_1_2,0.36470038809157851,0.36470038809157851,-0.31040000915527344,0 +coef_dist_2_5,0.074882919278809829,0.074882919278809829,-0.3783000111579895,0 +coef_dist_5_15,0.042000918183646346,0.042000918183646346,-0.12849999964237213,0 +coef_dist_5_up_high,-0.09087337502871097,-0.09087337502871097,0.019999999552965164,0 +coef_mode_logsum,0.30896144806031556,0.30896144806031556,0.30000001192092896,0 +work_high_AGREMPN,-5.1450221148210131,-5.1450221148210131,-5.1159958839416504,0 +work_high_FPSEMPN,-6,-6,-1.5750365257263184,0 +work_high_HEREMPN,-5.8811853171285584,-5.8811853171285584,-1.2587810754776001,0 +work_high_MWTEMPN,-6,-6,-1.4312916994094849,0 +work_high_OTHEMPN,-4.7639836057101634,-4.7639836057101634,-1.870802640914917,0 +work_high_RETEMPN,-2.2072749137878418,-2.2072749137878418,-2.2072749137878418,0 +work_low_AGREMPN,-4.6300621303951566,-4.6300621303951566,-4.6051702499389648,0 +work_low_FPSEMPN,-6,-6,-1.6450650691986084,0 +work_low_HEREMPN,-5.1021077661983387,-5.1021077661983387,-0.95972031354904175,0 +work_low_MWTEMPN,-6,-6,-1.8078888654708862,0 +work_low_OTHEMPN,-4.6623088926077152,-4.6623088926077152,-2.1202635765075684,0 +work_low_RETEMPN,-2.0479428768157959,-2.0479428768157959,-2.0479428768157959,0 +work_med_AGREMPN,-4.8459968751410516,-4.8459968751410516,-4.8283138275146484,0 +work_med_FPSEMPN,-6,-6,-1.62455153465271,0 +work_med_HEREMPN,-5.4027609472499369,-5.4027609472499369,-1.1239300966262817,0 +work_med_MWTEMPN,-5.9999999999999991,-5.9999999999999991,-1.56064772605896,0 +work_med_OTHEMPN,-4.8811360108806872,-4.8811360108806872,-1.9732813835144043,0 +work_med_RETEMPN,-2.1202635765075684,-2.1202635765075684,-2.1202635765075684,0 +work_veryhigh_AGREMPN,-5.5516059766686876,-5.5516059766686876,-5.521461009979248,0 +work_veryhigh_FPSEMPN,-6,-6,-1.309333324432373,0 +work_veryhigh_HEREMPN,-5.6489927637825792,-5.6489927637825792,-1.4229583740234375,0 +work_veryhigh_MWTEMPN,-6,-6,-1.4024237394332886,0 +work_veryhigh_OTHEMPN,-5.8313629173672439,-5.8313629173672439,-1.9241486787796021,0 +work_veryhigh_RETEMPN,-2.3751556873321533,-2.3751556873321533,-2.3751556873321533,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_mandatory_tour_scheduling_school_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_mandatory_tour_scheduling_school_loglike.csv index e76a45b3fb..13b40bf6a1 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_mandatory_tour_scheduling_school_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_mandatory_tour_scheduling_school_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-2475.6453326598094,-2344.7409183750583 +0,-2372.124053104777,-2329.0008675965573 diff --git a/activitysim/estimation/test/test_larch_estimation/test_mandatory_tour_scheduling_work_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_mandatory_tour_scheduling_work_loglike.csv index 6970d3e666..66fdd2bfd0 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_mandatory_tour_scheduling_work_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_mandatory_tour_scheduling_work_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-9138.134506637969,-8404.2487574734187 +0,-8343.7438769575056,-8319.0773809188413 diff --git a/activitysim/estimation/test/test_larch_estimation/test_non_mandatory_tour_scheduling_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_non_mandatory_tour_scheduling_loglike.csv index 3282b45e71..027ad8ce1f 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_non_mandatory_tour_scheduling_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_non_mandatory_tour_scheduling_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-12772.911183835131,-9506.0541725800285 +0,-9330.0289068958136,-9291.4339963381062 diff --git a/activitysim/estimation/test/test_larch_estimation/test_nonmand_and_joint_tour_dest_choice.csv b/activitysim/estimation/test/test_larch_estimation/test_nonmand_and_joint_tour_dest_choice.csv index 5a8bf11db5..95558980d2 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_nonmand_and_joint_tour_dest_choice.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_nonmand_and_joint_tour_dest_choice.csv @@ -1,36 +1,36 @@ -,value,initvalue,nullvalue,minimum,maximum,best --999,-999,-999,-999,-999,-999,-999 -0,0,0,0,0,0,0 -1,1,1,1,1,1,1 -coef_eatout_dist_0_2,-0.76797916075917105,-0.56089999999999995,0,-25,25,-0.76797916075917105 -coef_eatout_dist_2_5,-0.22644636259204301,-0.31919999999999998,0,-25,25,-0.22644636259204301 -coef_eatout_dist_5_plus,-0.18814992028058361,-0.12379999999999999,0,-25,25,-0.18814992028058361 -coef_escort_dist_0_2,0.22669529391335932,-0.14990000000000001,0,-25,25,0.22669529391335932 -coef_escort_dist_2_5,-0.81349761658617425,-0.86709999999999998,0,-25,25,-0.81349761658617425 -coef_escort_dist_5_plus,-0.25505635884043121,-0.2137,0,-25,25,-0.25505635884043121 -coef_mode_logsum,0.66293335178956303,0.67549999999999999,0,-25,25,0.66293335178956303 -coef_othdiscr_dist_0_2,-0.20320115406190975,-0.16769999999999999,0,-25,25,-0.20320115406190975 -coef_othdiscr_dist_2_5,-0.55094376688046098,-0.4955,0,-25,25,-0.55094376688046098 -coef_othdiscr_dist_5_plus,-0.00014599013956733095,-0.1193,0,-25,25,-0.00014599013956733095 -coef_othmaint_dist_2_5,-0.57993229022084924,-0.60550000000000004,0,-25,25,-0.57993229022084924 -coef_othmaint_dist_5_plus,-0.22966135112433173,-0.10929999999999999,0,-25,25,-0.22966135112433173 -coef_shopping_dist_2_5,-0.62979386608506294,-0.5655,0,-25,25,-0.62979386608506294 -coef_shopping_dist_5_plus,-0.13065191570180024,-0.1832,0,-25,25,-0.13065191570180024 -coef_social_dist_2_5,-0.24518547406208724,-0.34849999999999998,0,-25,25,-0.24518547406208724 -coef_social_dist_5_plus,-0.19021662093061398,-0.13059999999999999,0,-25,25,-0.19021662093061398 -eatout_HEREMPN,-0.94688018419944264,-1.3547956940605197,0,-6,6,-0.94688018419944264 -eatout_RETEMPN,-0.29840603581475661,-0.29840603581475661,0,-0.29840603581475661,-0.29840603581475661,-0.29840603581475661 -escort_AGE0519,-1.1713218472625264,-0.7657178733947807,0,-6,6,-1.1713218472625264 -escort_HEREMPN,-2.4501503469929982,-1.9379419794061366,0,-6,6,-2.4501503469929982 -escort_HSENROLL,-3.3045642735486878,-1.7957674906255938,0,-6,6,-3.3045642735486878 -escort_RETEMPN,-1.4916548767777169,-1.4916548767777169,0,-1.4916548767777169,-1.4916548767777169,-1.4916548767777169 -othdiscr_HEREMPN,-1.5849006741800804,-1.3019532126861397,0,-6,6,-1.5849006741800804 -othdiscr_HSENROLL,-2.4667805407825685,-2.322787800311565,0,-6,6,-2.4667805407825685 -othdiscr_OTHEMPN,-2.3703426620470296,-1.8018098050815563,0,-6,6,-2.3703426620470296 -othdiscr_RETEMPN,-1.2385802852918961,-1.5511690043101247,0,-6,6,-1.2385802852918961 -othdiscr_TOTHH,-1.3783261914707137,-1.3783261914707137,0,-1.3783261914707137,-1.3783261914707137,-1.3783261914707137 -othmaint_HEREMPN,-0.66895307929197778,-0.65778003672265395,0,-6,6,-0.66895307929197778 -othmaint_RETEMPN,-0.72981116493153675,-0.72981116493153675,0,-0.72981116493153675,-0.72981116493153675,-0.72981116493153675 -shopping_RETEMPN,0,0,0,0,0,0 -social_HEREMPN,-0.3028654470570214,-0.73814454649068106,0,-6,6,-0.3028654470570214 -social_RETEMPN,-0.65008769109949827,-0.65008769109949827,0,-0.65008769109949827,-0.65008769109949827,-0.65008769109949827 +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +0,0,0,0,0 +1,1,1,1,0 +coef_eatout_dist_0_2,-0.27121792391961891,-0.27121792391961891,-0.56089997291564941,0 +coef_eatout_dist_2_5,0.10608796923916697,0.10608796923916697,-0.31920000910758972,0 +coef_eatout_dist_5_plus,-0.030055040831786589,-0.030055040831786589,-0.12380000203847885,0 +coef_escort_dist_0_2,0.36566723960275005,0.36566723960275005,-0.14990000426769257,0 +coef_escort_dist_2_5,0.028378662901016108,0.028378662901016108,-0.86710000038146973,0 +coef_escort_dist_5_plus,-0.11708701992134836,-0.11708701992134836,-0.21369999647140503,0 +coef_mode_logsum,0.59887430720061385,0.59887430720061385,0.67549997568130493,0 +coef_othdiscr_dist_0_2,-0.034497995271121927,-0.034497995271121927,-0.16769999265670776,0 +coef_othdiscr_dist_2_5,-0.050531906736139574,-0.050531906736139574,-0.49549999833106995,0 +coef_othdiscr_dist_5_plus,0.10722115306679328,0.10722115306679328,-0.1193000003695488,0 +coef_othmaint_dist_2_5,0.021990226822960424,0.021990226822960424,-0.6054999828338623,0 +coef_othmaint_dist_5_plus,-0.069040145806240003,-0.069040145806240003,-0.10930000245571136,0 +coef_shopping_dist_2_5,-0.088053277034711469,-0.088053277034711469,-0.56550002098083496,0 +coef_shopping_dist_5_plus,0.053178032652148891,0.053178032652148891,-0.18320000171661377,0 +coef_social_dist_2_5,0.13875731050537282,0.13875731050537282,-0.34850001335144043,0 +coef_social_dist_5_plus,-0.093851542275907265,-0.093851542275907265,-0.13060000538825989,0 +eatout_HEREMPN,-2.6485746777114287,-2.6485746777114287,-1.3547956943511963,0 +eatout_RETEMPN,-0.29840603470802307,-0.29840603470802307,-0.29840603470802307,0 +escort_AGE0519,-1.5700822201838556,-1.5700822201838556,-0.76571786403656006,0 +escort_HEREMPN,-3.381566795567077,-3.381566795567077,-1.9379420280456543,0 +escort_HSENROLL,-5.5115296809721706,-5.5115296809721706,-1.7957675457000732,0 +escort_RETEMPN,-1.4916548728942871,-1.4916548728942871,-1.4916548728942871,0 +othdiscr_HEREMPN,-4.3767539149782362,-4.3767539149782362,-1.3019531965255737,0 +othdiscr_HSENROLL,-4.0323913073099753,-4.0323913073099753,-2.3227877616882324,0 +othdiscr_OTHEMPN,-2.6010090126387664,-2.6010090126387664,-1.8018097877502441,0 +othdiscr_RETEMPN,-1.8907979924961573,-1.8907979924961573,-1.5511690378189087,0 +othdiscr_TOTHH,-1.3783261775970459,-1.3783261775970459,-1.3783261775970459,0 +othmaint_HEREMPN,-3.5067524801333883,-3.5067524801333883,-0.65778005123138428,0 +othmaint_RETEMPN,-0.72981119155883789,-0.72981119155883789,-0.72981119155883789,0 +shopping_RETEMPN,0,0,0,0 +social_HEREMPN,-3.1930226314841379,-3.1930226314841379,-0.73814451694488525,0 +social_RETEMPN,-0.65008771419525146,-0.65008771419525146,-0.65008771419525146,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_nonmand_and_joint_tour_dest_choice_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_nonmand_and_joint_tour_dest_choice_loglike.csv index 3d4d12de95..60449226e2 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_nonmand_and_joint_tour_dest_choice_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_nonmand_and_joint_tour_dest_choice_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-13284.574594749327,-13268.709190928732 +0,-8815.2207980563562,-8000.0090578510162 diff --git a/activitysim/estimation/test/test_larch_estimation/test_nonmand_tour_freq.csv b/activitysim/estimation/test/test_larch_estimation/test_nonmand_tour_freq.csv index c69badeb95..a5798dcdaa 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_nonmand_tour_freq.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_nonmand_tour_freq.csv @@ -1,426 +1,426 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_0_auto_household_and_escorting_tour,-2,-2,0,-2,-2,-2 -coef_1_escort_tour_constant,0.3190372575850004,0.0298,0,,,0.3190372575850004 -coef_1_plus_eating_out_tours_constant,-1.0128556061868639,0.0097000000000000003,0,,,-1.0128556061868639 -coef_1_plus_maintenance_tours_constant,-2.8426429307763517,0.1202,0,,,-2.8426429307763517 -coef_1_plus_other_discretionary_tours_constant,10.543978753178383,0.74119999999999997,0,,,10.543978753178383 -coef_1_plus_shopping_tours_constant,7.1839137908242963,0.47739999999999999,0,,,7.1839137908242963 -coef_1_plus_visting_tours_constant,-0.3208195851541456,0.052200000000000003,0,,,-0.3208195851541456 -coef_2_plus_escort_tours_constant,0.60671030252342817,0.74019999999999997,0,,,0.60671030252342817 -coef_at_home_pre_driving_school_kid_and_escorting_tour,-0.92647632492670284,-0.27460000000000001,0,,,-0.92647632492670284 -coef_at_home_pre_school_kid_and_discretionary_tour,-0.65566150836617298,-0.4703,0,,,-0.65566150836617298 -coef_at_home_pre_school_kid_and_escorting_tour,-0.79299240501544976,-1.5674999999999999,0,,,-0.79299240501544976 -coef_auto_access_to_retail_and_discretionary,-1.0508623054596398,0.084400000000000003,0,,,-1.0508623054596398 -coef_auto_access_to_retail_and_maintenance,0.27881164131795588,0.074899999999999994,0,,,0.27881164131795588 -coef_auto_access_to_retail_and_shopping,-0.6308268427373509,0.1067,0,,,-0.6308268427373509 -coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,0.16837878665395392,0.13039999999999999,0,,,0.16837878665395392 -coef_female_and_escorting_tour,0.60135724689113756,0.18240000000000001,0,,,0.60135724689113756 -coef_female_and_tour_frequency_is_1,-0.31583892945263869,-0.076600000000000001,0,,,-0.31583892945263869 -coef_female_and_tour_frequency_is_2,-0.5828100966419405,-0.1062,0,,,-0.5828100966419405 -coef_female_and_tour_frequency_is_5,0.022734817568325703,-0.32740000000000002,0,,,0.022734817568325703 -coef_high_income_group_and_discretionary_tour,-0.060443076774255075,0.25650000000000001,0,,,-0.060443076774255075 -coef_high_income_group_and_eating_out_tour,0.72620905564966565,0.55810000000000004,0,,,0.72620905564966565 -coef_high_income_group_and_tour_frequency_is_1,1.1372979170796778,0.51890000000000003,0,,,1.1372979170796778 -coef_high_income_group_and_tour_frequency_is_2,2.2159303224114666,1.1335999999999999,0,,,2.2159303224114666 -coef_high_income_group_and_tour_frequency_is_5_plus,0.10501223044514314,1.3898999999999999,0,,,0.10501223044514314 -coef_high_income_group_and_visiting_tour,-0.86265476671748431,-0.24229999999999999,0,,,-0.86265476671748431 -coef_logged_maximum_residual_window_tour_frequency_is_1,1.3354533697510027,1.2562,0,,,1.3354533697510027 -coef_logged_maximum_residual_window_tour_frequency_is_2,1.4260046446625716,1.2867999999999999,0,,,1.4260046446625716 -coef_logged_maximum_residual_window_tour_frequency_is_5_plus,0.64024624278385667,1.3993,0,,,0.64024624278385667 -coef_mediumhigh_income_group_and_tour_frequency_is_1,1.0937153306192198,0.49809999999999999,0,,,1.0937153306192198 -coef_mediumhigh_income_group_and_tour_frequency_is_2,1.8148765360700809,0.83450000000000002,0,,,1.8148765360700809 -coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,1.0390643994599666,1.0213000000000001,0,,,1.0390643994599666 -coef_number_of_joint_eating_out_tours,-9.9809215555613431,-0.58660000000000001,0,,,-9.9809215555613431 -coef_number_of_mandatory_tours_and_tour_frequency_is_2,-1.4334081077188456,-0.88870000000000005,0,,,-1.4334081077188456 -coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-1.6366589797047477,-2.3342999999999998,0,,,-1.6366589797047477 -coef_presence_of_driving_school_kid_and_discretionary_tour,0.38403906373496743,-0.39629999999999999,0,,,0.38403906373496743 -coef_presence_of_driving_school_kid_and_escorting_tour,-0.21108592167092743,0.36009999999999998,0,,,-0.21108592167092743 -coef_presence_of_full_time_worker_and_discretionary_tour,-0.78342819804391672,-0.66700000000000004,0,,,-0.78342819804391672 -coef_presence_of_full_time_worker_and_eating_out_tour,-0.74762089644693475,-0.35709999999999997,0,,,-0.74762089644693475 -coef_presence_of_full_time_worker_and_maintenance_tour,-0.34233564267666977,-0.16850000000000001,0,,,-0.34233564267666977 -coef_presence_of_full_time_worker_and_shopping_tour,-0.63058521173008519,-0.30590000000000001,0,,,-0.63058521173008519 -coef_presence_of_non_worker_and_discretionary_tour,-1.2669707808842081,-0.42809999999999998,0,,,-1.2669707808842081 -coef_presence_of_non_worker_and_eating_out_tour,-0.44503023956321403,-0.2014,0,,,-0.44503023956321403 -coef_presence_of_non_worker_and_escorting_tour,-0.85427331034949039,-0.48149999999999998,0,,,-0.85427331034949039 -coef_presence_of_non_worker_and_maintenance_tour,-0.20935037072535292,-0.32369999999999999,0,,,-0.20935037072535292 -coef_presence_of_non_worker_and_shopping_tour,-0.84441949424610041,-0.41599999999999998,0,,,-0.84441949424610041 -coef_presence_of_part_time_worker_and_discretionary_tour,-0.041239276355498081,-0.2102,0,,,-0.041239276355498081 -coef_presence_of_part_time_worker_and_maintenance_tour,-0.18336221092296712,-0.15840000000000001,0,,,-0.18336221092296712 -coef_presence_of_part_time_worker_and_shopping_tour,-0.14852190396109033,-0.15409999999999999,0,,,-0.14852190396109033 -coef_presence_of_pre_driving_school_kid_and_discretionary_tour,-0.12585844615812486,-0.39589999999999997,0,,,-0.12585844615812486 -coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.4021102250286928,1.3974,0,,,1.4021102250286928 -coef_presence_of_pre_school_kid_and_discretionary_tour,-0.017076036823995389,-0.5081,0,,,-0.017076036823995389 -coef_presence_of_pre_school_kid_and_eating_out_tour,-0.84547304246409216,-0.42249999999999999,0,,,-0.84547304246409216 -coef_presence_of_pre_school_kid_and_escorting_tour,0.74822720714906121,0.68420000000000003,0,,,0.74822720714906121 -coef_presence_of_pre_school_kid_and_shopping_tour,-0.006143364129761947,-0.20799999999999999,0,,,-0.006143364129761947 -coef_presence_of_retiree_and_discretionary_tour,-0.5968298706214118,-0.91039999999999999,0,,,-0.5968298706214118 -coef_presence_of_retiree_and_eating_out_tour,-1.2874101904899586,-0.57079999999999997,0,,,-1.2874101904899586 -coef_presence_of_retiree_and_escorting_tour,-12.931599172963331,-0.80800000000000005,0,,,-12.931599172963331 -coef_presence_of_university_student_and_discretionary_tour,-0.40727682870124049,-0.85509999999999997,0,,,-0.40727682870124049 -coef_total_number_of_tours_is_1,-7.5238510045347198,-7.3571999999999997,0,,,-7.5238510045347198 -coef_total_number_of_tours_is_2,-10.052745008623061,-10.647,0,,,-10.052745008623061 -coef_total_number_of_tours_is_3,-11.089117141589441,-13.500500000000001,0,,,-11.089117141589441 -coef_total_number_of_tours_is_4,-12.79747158559379,-16.3965,0,,,-12.79747158559379 -coef_total_number_of_tours_is_5,-21.780097785311945,-19.6843,0,,,-21.780097785311945 -coef_total_number_of_tours_is_6_plus,-999,-999,0,-999,-999,-999 -coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0.07445921318512129,0.022599999999999999,0,,,0.07445921318512129 -coef_urban_and_discretionary_tour,0,0,0,0,0,0 -coef_urban_and_escorting_tour,-0.40934213736815739,-0.43159999999999998,0,,,-0.40934213736815739 -coef_walk_access_to_retail_and_discretionary,0.16052040097513201,0.0567,0,,,0.16052040097513201 -coef_walk_access_to_retail_and_eating_out,0.21128946397868445,0.14499999999999999,0,,,0.21128946397868445 -coef_walk_access_to_retail_and_escorting,-0.10528530451785624,0.045100000000000001,0,,,-0.10528530451785624 -coef_walk_access_to_retail_and_shopping,0.030181871306816859,0.033000000000000002,0,,,0.030181871306816859 -coef_zero_car_ownership_and_tour_frequency_is_5_plus,-0.22749157163698558,-0.34860000000000002,0,,,-0.22749157163698558 -coef_0_auto_household_and_escorting_tour,-2,-2,0,-2,-2,-2 -coef_1_escort_tour_constant,0.77792661515451589,0.5272,0,,,0.77792661515451589 -coef_1_plus_eating_out_tours_constant,1.6650752768925599,0.69140000000000001,0,,,1.6650752768925599 -coef_1_plus_maintenance_tours_constant,1.2147335336677649,0.55330000000000001,0,,,1.2147335336677649 -coef_1_plus_other_discretionary_tours_constant,1.7838713459166913,0.79890000000000005,0,,,1.7838713459166913 -coef_1_plus_shopping_tours_constant,1.5216128214649225,0.75690000000000002,0,,,1.5216128214649225 -coef_1_plus_visting_tours_constant,1.0454819231998753,0.14050000000000001,0,,,1.0454819231998753 -coef_2_plus_escort_tours_constant,1.8826614596684659,1.5987,0,,,1.8826614596684659 -coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,0.049231503501832231,-0.54979999999999996,0,,,0.049231503501832231 -coef_female_and_discretionary_tour,0.4392516750827225,0.30719999999999997,0,,,0.4392516750827225 -coef_female_and_shopping_tour,0.75313279306505232,0.45240000000000002,0,,,0.75313279306505232 -coef_high_income_group_and_discretionary_tour,0.23650597334594267,0.29599999999999999,0,,,0.23650597334594267 -coef_high_income_group_and_maintenance_tour,1.3851001428210838,0.67630000000000001,0,,,1.3851001428210838 -coef_high_income_group_and_shopping_tour,0.8194174808417779,0.70660000000000001,0,,,0.8194174808417779 -coef_high_income_group_and_tour_frequency_is_1,1.1457147075553702,0.86819999999999997,0,,,1.1457147075553702 -coef_high_income_group_and_tour_frequency_is_2,1.3475187007328813,1.5362,0,,,1.3475187007328813 -coef_high_income_group_and_tour_frequency_is_5_plus,1.4989029758459638,1.9331,0,,,1.4989029758459638 -coef_high_income_group_and_visiting_tour,-0.51731565603377461,-0.68679999999999997,0,,,-0.51731565603377461 -coef_logged_maximum_residual_window_tour_frequency_is_1,0.7685190519346432,1.5748,0,,,0.7685190519346432 -coef_logged_maximum_residual_window_tour_frequency_is_5_plus,1.2439948002596291,2.0026000000000002,0,,,1.2439948002596291 -coef_mediumhigh_income_group_and_shopping_tour,0.6050472895465131,0.44209999999999999,0,,,0.6050472895465131 -coef_mediumlow_income_group_and_tour_frequency_is_1,0.78437721900423418,0.59809999999999997,0,,,0.78437721900423418 -coef_mediumlow_income_group_and_tour_frequency_is_2,0.77646590224476053,0.91779999999999995,0,,,0.77646590224476053 -coef_mediumlow_income_group_and_tour_frequency_is_5_plus,0.85089808758167285,1.7539,0,,,0.85089808758167285 -coef_number_of_joint_tours_and_tour_frequency_is_4,-1.3476574161190644,-1.1986000000000001,0,,,-1.3476574161190644 -coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,0,-999,-999,-999 -coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.98906870125269652,-0.23899999999999999,0,,,-0.98906870125269652 -coef_number_of_mandatory_tours_and_tour_frequency_is_2,-2.8297942396940736,-1.8208,0,,,-2.8297942396940736 -coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-2.7856768576922941,-2.5922999999999998,0,,,-2.7856768576922941 -coef_presence_of_driving_school_kid_and_escorting_tour,1.029446605173121,0.41639999999999999,0,,,1.029446605173121 -coef_presence_of_full_time_worker_and_maintenance_tour,-0.48499903259305888,-0.31309999999999999,0,,,-0.48499903259305888 -coef_presence_of_non_worker_and_discretionary_tour,-0.55680343236172403,-1.0370999999999999,0,,,-0.55680343236172403 -coef_presence_of_non_worker_and_eating_out_tour,-0.23160785989506891,-0.65449999999999997,0,,,-0.23160785989506891 -coef_presence_of_non_worker_and_escorting_tour,-0.61711333679139824,-0.52629999999999999,0,,,-0.61711333679139824 -coef_presence_of_part_time_worker_and_maintenance_tour,-1.0349086974724879,-0.56210000000000004,0,,,-1.0349086974724879 -coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.8088903614971785,1.5794999999999999,0,,,1.8088903614971785 -coef_presence_of_pre_school_kid_and_escorting_tour,0.29170166111444701,0.54139999999999999,0,,,0.29170166111444701 -coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,0.3086114999500732,-0.15590000000000001,0,,,0.3086114999500732 -coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-0.53068484571189922,-0.56810000000000005,0,,,-0.53068484571189922 -coef_presence_of_retiree_and_eating_out_tour,0.10920851120872498,-1.389,0,,,0.10920851120872498 -coef_presence_of_retiree_and_escorting_tour,-0.46115035352397654,-0.75160000000000005,0,,,-0.46115035352397654 -coef_presence_of_university_student_and_eating_out_tour,-1.7593233495192167,-1.4318,0,,,-1.7593233495192167 -coef_total_number_of_tours_is_1,-6.8126152336072634,-7.6391,0,,,-6.8126152336072634 -coef_total_number_of_tours_is_2,-9.848059513629396,-10.4557,0,,,-9.848059513629396 -coef_total_number_of_tours_is_3,-12.828277375142353,-14.0176,0,,,-12.828277375142353 -coef_total_number_of_tours_is_4,-17.097027294518412,-16.971699999999998,0,,,-17.097027294518412 -coef_urban_and_discretionary_tour,0,0,0,0,0,0 -coef_urban_and_escorting_tour,0.42574953449141995,-0.39290000000000003,0,,,0.42574953449141995 -coef_walk_access_to_retail_and_tour_frequency_is_1,0.080139740576734939,0.089899999999999994,0,,,0.080139740576734939 -coef_walk_access_to_retail_and_tour_frequency_is_2,0.10381957230648611,0.1447,0,,,0.10381957230648611 -coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0.050631059321334597,0.34789999999999999,0,,,0.050631059321334597 -coef_0_auto_household_and_escorting_tour,-2,-2,0,-2,-2,-2 -coef_1_escort_tour_constant,1.8515063856421023,1.7028000000000001,0,,,1.8515063856421023 -coef_1_plus_eating_out_tours_constant,-13.970900895148123,2.0722999999999998,0,,,-13.970900895148123 -coef_1_plus_maintenance_tours_constant,-0.33803118769084733,0.33479999999999999,0,,,-0.33803118769084733 -coef_1_plus_other_discretionary_tours_constant,-1.4739923019690557,1.3389,0,,,-1.4739923019690557 -coef_1_plus_shopping_tours_constant,2.0188727174813774,1.8403,0,,,2.0188727174813774 -coef_1_plus_visting_tours_constant,1.1323634825734481,1.2172000000000001,0,,,1.1323634825734481 -coef_2_plus_escort_tours_constant,2.7388802993288452,2.8378999999999999,0,,,2.7388802993288452 -coef_auto_access_to_retail_and_discretionary,0.6683734729533154,0.094,0,,,0.6683734729533154 -coef_auto_access_to_retail_and_eating_out,3.3138758891504487,0.1018,0,,,3.3138758891504487 -coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-1.1118144810513726,-0.58099999999999996,0,,,-1.1118144810513726 -coef_female_and_discretionary_tour,-0.25441035312551963,-0.3266,0,,,-0.25441035312551963 -coef_female_and_eatingout_tour,-0.67597119919881721,-0.65680000000000005,0,,,-0.67597119919881721 -coef_female_and_tour_frequency_is_1,-0.50912757178913237,0.097299999999999998,0,,,-0.50912757178913237 -coef_female_and_tour_frequency_is_2,0.67536539039172305,0.2361,0,,,0.67536539039172305 -coef_female_and_tour_frequency_is_5,1.992028104740627,1.9001999999999999,0,,,1.992028104740627 -coef_high_income_group_and_eating_out_tour,-1.7911774479045783,-0.72070000000000001,0,,,-1.7911774479045783 -coef_high_income_group_and_shopping_tour,0.0036422160874866197,0.56930000000000003,0,,,0.0036422160874866197 -coef_high_income_group_and_tour_frequency_is_1,1.4404498701731279,0.39860000000000001,0,,,1.4404498701731279 -coef_high_income_group_and_tour_frequency_is_2,0.83745190593386265,0.80089999999999995,0,,,0.83745190593386265 -coef_high_income_group_and_tour_frequency_is_5_plus,-16.251792370439588,0.82540000000000002,0,,,-16.251792370439588 -coef_high_income_group_and_visiting_tour,-0.82404884406611401,-0.36940000000000001,0,,,-0.82404884406611401 -coef_logged_maximum_residual_window_tour_frequency_is_0,0.2804768002125545,1.1858,0,,,0.2804768002125545 -coef_logged_maximum_residual_window_tour_frequency_is_5_plus,2.3895231997864537,1.4842,0,,,2.3895231997864537 -coef_mediumhigh_income_group_and_tour_frequency_is_1,0.50210130383758622,0.1109,0,,,0.50210130383758622 -coef_mediumhigh_income_group_and_tour_frequency_is_2,2.1358136364876388,0.39140000000000003,0,,,2.1358136364876388 -coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,3.8895054347112406,0.61370000000000002,0,,,3.8895054347112406 -coef_number_of_joint_discretionary_tours,-12.752183693752794,0.67130000000000001,0,,,-12.752183693752794 -coef_number_of_joint_shopping_tours,-26.373288193463711,-0.71299999999999997,0,,,-26.373288193463711 -coef_number_of_joint_tours_and_tour_frequency_is_2,-13.926155494658921,-0.31530000000000002,0,,,-13.926155494658921 -coef_number_of_joint_tours_and_tour_frequency_is_3,-1.3634750179314692,-0.73509999999999998,0,,,-1.3634750179314692 -coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,0,-999,-999,-999 -coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.80994304158323804,-0.1852,0,,,-0.80994304158323804 -coef_number_of_mandatory_tours_and_tour_frequency_is_2,-1.9296858293686057,-0.87529999999999997,0,,,-1.9296858293686057 -coef_number_of_mandatory_tours_and_tour_frequency_is_3,-3.1165358610084146,-1.6157999999999999,0,,,-3.1165358610084146 -coef_presence_of_full_time_worker_and_discretionary_tour,-1.0912632357636489,-0.48330000000000001,0,,,-1.0912632357636489 -coef_presence_of_full_time_worker_and_eating_out_tour,0.77587232422920438,-0.52510000000000001,0,,,0.77587232422920438 -coef_presence_of_full_time_worker_and_shopping_tour,-0.47914248744882598,-0.77280000000000004,0,,,-0.47914248744882598 -coef_presence_of_non_worker_and_discretionary_tour,-0.59191766592824591,0.97809999999999997,0,,,-0.59191766592824591 -coef_presence_of_non_worker_and_tour_frequency_is_1,0.20739098927232799,-0.85060000000000002,0,,,0.20739098927232799 -coef_presence_of_non_worker_and_tour_frequency_is_5,-0.10809095623412202,-1.1803999999999999,0,,,-0.10809095623412202 -coef_presence_of_part_time_worker_and_eating_out_tour,-3.2046073684551888,-1.9795,0,,,-3.2046073684551888 -coef_presence_of_part_time_worker_and_escorting_tour,-2.2247073118309659,-1.8212999999999999,0,,,-2.2247073118309659 -coef_presence_of_part_time_worker_and_shopping_tour,-0.72896673490600039,-0.51990000000000003,0,,,-0.72896673490600039 -coef_presence_of_pre_driving_school_kid_and_escorting_tour,-0.075902664875801412,0.94889999999999997,0,,,-0.075902664875801412 -coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0.072697095095962505,0.38629999999999998,0,,,0.072697095095962505 -coef_presence_of_pre_school_kid_and_escorting_tour,1.7499151704017379,2.1465000000000001,0,,,1.7499151704017379 -coef_presence_of_pre_school_kid_and_maintenance_tour,-0.61302038898844102,0.96940000000000004,0,,,-0.61302038898844102 -coef_presence_of_pre_school_kid_and_shopping_tour,0.4218433052411511,1.3134999999999999,0,,,0.4218433052411511 -coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,-2.0284687546419584,-0.99609999999999999,0,,,-2.0284687546419584 -coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,-0.79737893556046791,-1.9096,0,,,-0.79737893556046791 -coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-0.31913117480031128,-2.8469000000000002,0,,,-0.31913117480031128 -coef_presence_of_university_student_and_discretionary_tour,0.090801806893705261,-0.6542,0,,,0.090801806893705261 -coef_presence_of_university_student_and_eating_out_tour,-0.42835318314992721,-0.65290000000000004,0,,,-0.42835318314992721 -coef_total_number_of_tours_is_1,-8.5863403053428833,-6.2138,0,,,-8.5863403053428833 -coef_total_number_of_tours_is_2,-11.31949482279566,-8.9079999999999995,0,,,-11.31949482279566 -coef_total_number_of_tours_is_3,-14.109861113838994,-12.3261,0,,,-14.109861113838994 -coef_total_number_of_tours_is_4,-17.545826976965291,-15.811400000000001,0,,,-17.545826976965291 -coef_transit_access_to_retail_and_discretionary,0,0,0,0,0,0 -coef_transit_access_to_retail_and_maintenance,0.25755159606468364,0.031399999999999997,0,,,0.25755159606468364 -coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0.20705109302348529,0.066400000000000001,0,,,0.20705109302348529 -coef_urban_and_discretionary_tour,-1.8565923019691735,0.95630000000000004,0,,,-1.8565923019691735 -coef_urban_and_eatingout_tour,-15.36320089514812,0.68000000000000005,0,,,-15.36320089514812 -coef_urban_and_escorting_tour,0.80226698426219045,0.85160000000000002,0,,,0.80226698426219045 -coef_urban_and_maintenance_tour,0.35876881230913166,1.0316000000000001,0,,,0.35876881230913166 -coef_urban_and_shopping_tour,0.71157271748139417,0.53300000000000003,0,,,0.71157271748139417 -coef_urban_and_tour_frequency_is_1,-3.5373403053428834,-1.1648000000000001,0,,,-3.5373403053428834 -coef_urban_and_tour_frequency_is_2,-4.7291948227956535,-2.3176999999999999,0,,,-4.7291948227956535 -coef_urban_and_tour_frequency_is_5_plus,-6.0208880908118116,-2.5026999999999999,0,,,-6.0208880908118116 -coef_walk_access_to_retail_and_shopping,0.10237878294870741,0.097199999999999995,0,,,0.10237878294870741 -coef_0_auto_household_and_escorting_tour,-2,-2,0,-2,-2,-2 -coef_1_escort_tour_constant,-4.6370945761626077,-0.062899999999999998,0,,,-4.6370945761626077 -coef_1_plus_eating_out_tours_constant,-4.7784926750203027,-0.1429,0,,,-4.7784926750203027 -coef_1_plus_maintenance_tours_constant,-9.9288535518266823,-0.065299999999999997,0,,,-9.9288535518266823 -coef_1_plus_other_discretionary_tours_constant,-4.8073687191051899,0.33339999999999997,0,,,-4.8073687191051899 -coef_1_plus_shopping_tours_constant,-4.0132353551593232,0.46829999999999999,0,,,-4.0132353551593232 -coef_1_plus_visting_tours_constant,-4.8733834129994724,-0.12720000000000001,0,,,-4.8733834129994724 -coef_2_plus_escort_tours_constant,-8.967938948525461,0.92730000000000001,0,,,-8.967938948525461 -coef_at_home_pre_driving_school_kid_and_escorting_tour,-0.85247075086999724,-1.1479999999999999,0,,,-0.85247075086999724 -coef_at_home_pre_school_kid_and_eating_out_tour,0.60985731009359834,-0.3926,0,,,0.60985731009359834 -coef_at_home_pre_school_kid_and_escorting_tour,-0.061265250325528015,-0.13730000000000001,0,,,-0.061265250325528015 -coef_auto_access_to_retail_and_maintenance,0.61777145381329102,0.095600000000000004,0,,,0.61777145381329102 -coef_car_shortage_vs_workers_and_tour_frequency_is_1,-0.33803024620733235,-0.36230000000000001,0,,,-0.33803024620733235 -coef_car_shortage_vs_workers_and_tour_frequency_is_2,-1.4819665998101139,-1.272,0,,,-1.4819665998101139 -coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-2.5557207485506246,-1.9307000000000001,0,,,-2.5557207485506246 -coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,3.121774566538436,0.77380000000000004,0,,,3.121774566538436 -coef_female_and_maintenance_tour,-0.24639047530045038,-0.24640000000000001,0,,,-0.24639047530045038 -coef_female_and_tour_frequency_is_1,0.74864834160230664,0.39019999999999999,0,,,0.74864834160230664 -coef_female_and_tour_frequency_is_2,0.67696554036131518,0.5323,0,,,0.67696554036131518 -coef_female_and_tour_frequency_is_3,1.281698729380099,0.74519999999999997,0,,,1.281698729380099 -coef_female_and_tour_frequency_is_5,2.3807456280650667,1.1294,0,,,2.3807456280650667 -coef_high_income_group_and_discretionary_tour,0.51835922730368678,0.88460000000000005,0,,,0.51835922730368678 -coef_high_income_group_and_eating_out_tour,1.5486575358906367,0.70860000000000001,0,,,1.5486575358906367 -coef_high_income_group_and_shopping_tour,0.72862383681691834,0.97760000000000002,0,,,0.72862383681691834 -coef_high_income_group_and_tour_frequency_is_2,19.097882832130001,1.0632999999999999,0,,,19.097882832130001 -coef_high_income_group_and_tour_frequency_is_3,19.408558066997916,1.7742,0,,,19.408558066997916 -coef_high_income_group_and_tour_frequency_is_5_plus,19.832444995943295,2.3940999999999999,0,,,19.832444995943295 -coef_high_income_group_and_visiting_tour,-0.54232747274109727,-0.94489999999999996,0,,,-0.54232747274109727 -coef_logged_maximum_residual_window_tour_frequency_is_1,6.5467446485012912,1.7637,0,,,6.5467446485012912 -coef_logged_maximum_residual_window_tour_frequency_is_5_plus,7.3593803409865783,1.7927999999999999,0,,,7.3593803409865783 -coef_mediumhigh_income_group_and_discretionary_tour,0.18835358603238547,0.50090000000000001,0,,,0.18835358603238547 -coef_mediumhigh_income_group_and_eating_out_tour,-0.18198447365326542,0.46310000000000001,0,,,-0.18198447365326542 -coef_mediumhigh_income_group_and_shopping_tour,1.2220802803491335,0.89059999999999995,0,,,1.2220802803491335 -coef_mediumhigh_income_group_and_tour_frequency_is_1,19.971750133805212,0.74260000000000004,0,,,19.971750133805212 -coef_mediumhigh_income_group_and_tour_frequency_is_2,19.468344647994446,0.85460000000000003,0,,,19.468344647994446 -coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,19.731739849414112,1.0791999999999999,0,,,19.731739849414112 -coef_mediumhigh_income_group_and_visiting_tour,0.027868052585523006,-0.26700000000000002,0,,,0.027868052585523006 -coef_mediumlow_income_group_and_discretionary_tour,-0.31620776069124212,0.17069999999999999,0,,,-0.31620776069124212 -coef_mediumlow_income_group_and_eating_out_tour,0.64577775646714697,0.27660000000000001,0,,,0.64577775646714697 -coef_mediumlow_income_group_and_shopping_tour,0.55581824053699758,0.77339999999999998,0,,,0.55581824053699758 -coef_mediumlow_income_group_and_tour_frequency_is_1,17.934259369140999,0.57089999999999996,0,,,17.934259369140999 -coef_mediumlow_income_group_and_tour_frequency_is_5_plus,18.117542759840582,0.83150000000000002,0,,,18.117542759840582 -coef_number_of_joint_eating_out_tours,-13.182546391318507,-0.77270000000000005,0,,,-13.182546391318507 -coef_number_of_joint_shopping_tours,-16.839997040358107,-0.23910000000000001,0,,,-16.839997040358107 -coef_number_of_joint_tours_and_tour_frequency_is_1,-7.786577241296107,-0.1699,0,,,-7.786577241296107 -coef_number_of_joint_tours_and_tour_frequency_is_2,-9.7470048997804675,-0.42849999999999999,0,,,-9.7470048997804675 -coef_number_of_joint_tours_and_tour_frequency_is_3,-9.2917736869942509,-0.65510000000000002,0,,,-9.2917736869942509 -coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-9.5554593661807772,-1.0410999999999999,0,,,-9.5554593661807772 -coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.67659999999999998,-0.67659999999999998,0,,,-0.67659999999999998 -coef_number_of_mandatory_tours_and_tour_frequency_is_3,-1.0518000000000001,-1.0518000000000001,0,,,-1.0518000000000001 -coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-999,-999,0,-999,-999,-999 -coef_presence_of_full_time_worker_and_eating_out_tour,-1.3147958654758525,-0.4667,0,,,-1.3147958654758525 -coef_presence_of_full_time_worker_and_escorting_tour,0.35065195049774833,0.3947,0,,,0.35065195049774833 -coef_presence_of_non_worker_and_eating_out_tour,-0.40882607128740478,-0.49759999999999999,0,,,-0.40882607128740478 -coef_presence_of_non_worker_and_tour_frequency_is_1,1.8072738927257486,-0.37630000000000002,0,,,1.8072738927257486 -coef_presence_of_non_worker_and_tour_frequency_is_2,1.6043590091288431,-0.71899999999999997,0,,,1.6043590091288431 -coef_presence_of_non_worker_and_tour_frequency_is_5,2.2189804494458247,-1.0228999999999999,0,,,2.2189804494458247 -coef_presence_of_part_time_worker_and_discretionary_tour,-0.47082010921072343,-0.35449999999999998,0,,,-0.47082010921072343 -coef_presence_of_part_time_worker_and_escorting_tour,-0.93192205579588727,-0.58609999999999995,0,,,-0.93192205579588727 -coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.6418290951424679,1.3773,0,,,1.6418290951424679 -coef_presence_of_pre_school_kid_and_escorting_tour,0.7399830171990065,0.71940000000000004,0,,,0.7399830171990065 -coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,-3.592889456087303,0.14860000000000001,0,,,-3.592889456087303 -coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,-3.4708451274125283,0.48399999999999999,0,,,-3.4708451274125283 -coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-3.861870451391785,-0.71609999999999996,0,,,-3.861870451391785 -coef_presence_of_retiree_and_eating_out_tour,-1.019099347827936,-0.69110000000000005,0,,,-1.019099347827936 -coef_presence_of_retiree_and_tour_frequency_is_1,2.0287807170341305,-0.46400000000000002,0,,,2.0287807170341305 -coef_presence_of_retiree_and_tour_frequency_is_5,1.9825418671121779,-0.47949999999999998,0,,,1.9825418671121779 -coef_total_number_of_tours_is_1,-23.000695056294269,-8.9791000000000007,0,,,-23.000695056294269 -coef_total_number_of_tours_is_2,-21.149512681682054,-12.024800000000001,0,,,-21.149512681682054 -coef_total_number_of_tours_is_3,-20.410765355763306,-14.851599999999999,0,,,-20.410765355763306 -coef_total_number_of_tours_is_4,-18.774647425097385,-17.703700000000001,0,,,-18.774647425097385 -coef_urban_and_discretionary_tour,0,0,0,0,0,0 -coef_walk_access_to_retail_and_discretionary,0.21406620307694346,0.077200000000000005,0,,,0.21406620307694346 -coef_walk_access_to_retail_and_shopping,0.039842855774011393,0.059799999999999999,0,,,0.039842855774011393 -coef_walk_access_to_retail_and_tour_frequency_is_1,-0.50693837400775899,0.071300000000000002,0,,,-0.50693837400775899 -coef_walk_access_to_retail_and_tour_frequency_is_2,-0.40382295711954785,0.12559999999999999,0,,,-0.40382295711954785 -coef_walk_access_to_retail_and_tour_frequency_is_5_plus,-0.26053331276767533,0.15079999999999999,0,,,-0.26053331276767533 -coef_0_auto_household_and_escorting_tour,-2,-2,0,-2,-2,-2 -coef_1_escort_tour_constant,-2.730596441707033,-0.3992,0,,,-2.730596441707033 -coef_1_plus_eating_out_tours_constant,-2.5833046285296968,0.024500000000000001,0,,,-2.5833046285296968 -coef_1_plus_maintenance_tours_constant,-2.2992187432888329,0.1046,0,,,-2.2992187432888329 -coef_1_plus_other_discretionary_tours_constant,-2.2431962112746411,0.42820000000000003,0,,,-2.2431962112746411 -coef_1_plus_shopping_tours_constant,-1.9166425444609607,0.59470000000000001,0,,,-1.9166425444609607 -coef_1_plus_visting_tours_constant,-2.3440181385910446,0.27889999999999998,0,,,-2.3440181385910446 -coef_2_plus_escort_tours_constant,-4.9359365117262612,0.51749999999999996,0,,,-4.9359365117262612 -coef_car_surplus_vs_workers_and_tour_frequency_is_1,3.0947542803847758,0.79649999999999999,0,,,3.0947542803847758 -coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,3.4758535212559294,2.1301999999999999,0,,,3.4758535212559294 -coef_female_and_discretionary_tour,0.54152756838822758,0.49540000000000001,0,,,0.54152756838822758 -coef_female_and_maintenance_tour,0.70832787326060975,0.74239999999999995,0,,,0.70832787326060975 -coef_female_and_shopping_tour,0.60931588761842026,0.96879999999999999,0,,,0.60931588761842026 -coef_female_and_tour_frequency_is_1,-2.5191550523228474,-0.93479999999999996,0,,,-2.5191550523228474 -coef_female_and_tour_frequency_is_2,-2.7271688013300479,-1.3028,0,,,-2.7271688013300479 -coef_female_and_tour_frequency_is_5,-4.1602031889993674,-2.266,0,,,-4.1602031889993674 -coef_high_income_group_and_discretionary_tour,0.92588438224313008,1.0095000000000001,0,,,0.92588438224313008 -coef_high_income_group_and_eating_out_tour,1.6244927835124816,1.4842,0,,,1.6244927835124816 -coef_high_income_group_and_maintenance_tour,1.0061046178584812,1.3794999999999999,0,,,1.0061046178584812 -coef_high_income_group_and_shopping_tour,1.1051711361584451,1.0949,0,,,1.1051711361584451 -coef_high_income_group_and_visiting_tour,-0.65666362660607858,-0.51370000000000005,0,,,-0.65666362660607858 -coef_logged_maximum_residual_window_tour_frequency_is_1,2.9665568629163652,1.8357000000000001,0,,,2.9665568629163652 -coef_logged_maximum_residual_window_tour_frequency_is_2,5.581416234805145,2.2707000000000002,0,,,5.581416234805145 -coef_logged_maximum_residual_window_tour_frequency_is_5_plus,31.909531343908711,4.4023000000000003,0,,,31.909531343908711 -coef_mediumhigh_income_group_and_eating_out_tour,0.96427913024112555,1.181,0,,,0.96427913024112555 -coef_mediumhigh_income_group_and_maintenance_tour,0.46535126543893468,0.76480000000000004,0,,,0.46535126543893468 -coef_mediumhigh_income_group_and_visiting_tour,-0.47816865355794147,-0.43680000000000002,0,,,-0.47816865355794147 -coef_mediumlow_income_group_and_eating_out_tour,0.87748591593357028,0.97689999999999999,0,,,0.87748591593357028 -coef_number_of_joint_shopping_tours,-0.29099820983920754,-0.80720000000000003,0,,,-0.29099820983920754 -coef_number_of_joint_tours_and_tour_frequency_is_2,-6.3271431915064547,-0.94999999999999996,0,,,-6.3271431915064547 -coef_number_of_joint_tours_and_tour_frequency_is_3,-85.627388567464422,-7.1429999999999998,0,,,-85.627388567464422 -coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,0,-999,-999,-999 -coef_number_of_mandatory_tours_and_tour_frequency_is_3,-5.0195999999999996,-5.0195999999999996,0,,,-5.0195999999999996 -coef_presence_of_full_time_worker_and_discretionary_tour,-0.33198445309738206,-0.48349999999999999,0,,,-0.33198445309738206 -coef_presence_of_full_time_worker_and_shopping_tour,-0.20732525834821677,-0.3609,0,,,-0.20732525834821677 -coef_presence_of_non_worker_and_discretionary_tour,-0.084103900991314984,-0.56030000000000002,0,,,-0.084103900991314984 -coef_presence_of_non_worker_and_eating_out_tour,-0.70153618577934562,-0.78800000000000003,0,,,-0.70153618577934562 -coef_presence_of_non_worker_and_tour_frequency_is_1,1.1906806536749803,0.224,0,,,1.1906806536749803 -coef_presence_of_non_worker_and_tour_frequency_is_2,1.3741954582206455,0.24360000000000001,0,,,1.3741954582206455 -coef_presence_of_non_worker_and_tour_frequency_is_3,2.1568221868185788,0.62,0,,,2.1568221868185788 -coef_presence_of_non_worker_and_tour_frequency_is_5,3.6943030762883984,3.3742000000000001,0,,,3.6943030762883984 -coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.6828802924993791,1.4903,0,,,1.6828802924993791 -coef_presence_of_pre_school_kid_and_escorting_tour,0.64181265687243838,0.50270000000000004,0,,,0.64181265687243838 -coef_presence_of_retiree_and_eating_out_tour,-0.9446797599672041,-0.92820000000000003,0,,,-0.9446797599672041 -coef_presence_of_retiree_and_tour_frequency_is_1,0.32142426327796303,-0.44579999999999997,0,,,0.32142426327796303 -coef_presence_of_retiree_and_tour_frequency_is_5,-0.05124161320643273,-0.53149999999999997,0,,,-0.05124161320643273 -coef_total_number_of_tours_is_1,-14.532344602813701,-8.5684000000000005,0,,,-14.532344602813701 -coef_total_number_of_tours_is_2,-15.267479639550283,-12.7416,0,,,-15.267479639550283 -coef_total_number_of_tours_is_3,-15.029318290282511,-15.097799999999999,0,,,-15.029318290282511 -coef_total_number_of_tours_is_4,-14.905139738811323,-19.543900000000001,0,,,-14.905139738811323 -coef_total_number_of_tours_is_5,-27.549766404642561,-20.7897,0,,,-27.549766404642561 -coef_urban_and_discretionary_tour,0,0,0,0,0,0 -coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0.69108202810785446,0.061600000000000002,0,,,0.69108202810785446 -coef_0_auto_household_and_escorting_tour,-289.81943839376481,-2,0,,,-289.81943839376481 -coef_1_escort_tour_constant,-6434.9613170821285,-0.49340000000000001,0,,,-6434.9613170821285 -coef_1_plus_eating_out_tours_constant,-3885.4119129943556,-0.024199999999999999,0,,,-3885.4119129943556 -coef_1_plus_maintenance_tours_constant,-1195.8070135696348,-0.43440000000000001,0,,,-1195.8070135696348 -coef_1_plus_other_discretionary_tours_constant,-2406.8061209898142,-0.26019999999999999,0,,,-2406.8061209898142 -coef_1_plus_shopping_tours_constant,-2389.30594524151,0.53200000000000003,0,,,-2389.30594524151 -coef_1_plus_visting_tours_constant,-2389.3059957968449,0.23669999999999999,0,,,-2389.3059957968449 -coef_2_plus_escort_tours_constant,-5667.6854005226833,1.4155,0,,,-5667.6854005226833 -coef_auto_access_to_retail_and_tour_frequency_is_5_plus,-44.188372748106481,0.1004,0,,,-44.188372748106481 -coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-17232.832070588393,-0.63690000000000002,0,,,-17232.832070588393 -coef_car_surplus_vs_workers_and_tour_frequency_is_1,-4035.619541886927,0.29020000000000001,0,,,-4035.619541886927 -coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,15225.992542144893,2.0352000000000001,0,,,15225.992542144893 -coef_high_income_group_and_discretionary_tour,4481.0843932231746,2.327,0,,,4481.0843932231746 -coef_high_income_group_and_eating_out_tour,-3157.2738344019517,0.49159999999999998,0,,,-3157.2738344019517 -coef_high_income_group_and_maintenance_tour,4461.4848620401744,0.3982,0,,,4461.4848620401744 -coef_high_income_group_and_shopping_tour,4461.3908032762156,0.24429999999999999,0,,,4461.3908032762156 -coef_high_income_group_and_visiting_tour,4461.3908519450242,0.2858,0,,,4461.3908519450242 -coef_logged_maximum_residual_window_tour_frequency_is_1,16.594329465647881,1.3298000000000001,0,,,16.594329465647881 -coef_logged_maximum_residual_window_tour_frequency_is_2,-19742.937757107196,1.3758999999999999,0,,,-19742.937757107196 -coef_logged_maximum_residual_window_tour_frequency_is_5_plus,-11491.665678473473,3.2808000000000002,0,,,-11491.665678473473 -coef_mediumhigh_income_group_and_discretionary_tour,572.84750941634763,1.405,0,,,572.84750941634763 -coef_mediumlow_income_group_and_discretionary_tour,-4429.9422108889057,0.91690000000000005,0,,,-4429.9422108889057 -coef_number_of_joint_tours_and_tour_frequency_is_1,-4180.3539679243559,-0.2162,0,,,-4180.3539679243559 -coef_number_of_joint_tours_and_tour_frequency_is_2,-1606.5028797398816,-0.35870000000000002,0,,,-1606.5028797398816 -coef_number_of_joint_tours_and_tour_frequency_is_3,-109.81932871468001,-4.2701000000000002,0,,,-109.81932871468001 -coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,0,-999,-999,-999 -coef_number_of_mandatory_tours_and_tour_frequency_is_1,-16877.023969621659,-0.23400000000000001,0,,,-16877.023969621659 -coef_number_of_mandatory_tours_and_tour_frequency_is_2,12620.764595473987,-0.92310000000000003,0,,,12620.764595473987 -coef_number_of_mandatory_tours_and_tour_frequency_is_3,-4861.9979116103832,-6.5834999999999999,0,,,-4861.9979116103832 -coef_presence_of_driving_school_kid_and_discretionary_tour,-578.87207263924711,-0.92020000000000002,0,,,-578.87207263924711 -coef_presence_of_driving_school_kid_and_eating_out_tour,6.3817283359748718,-0.63770000000000004,0,,,6.3817283359748718 -coef_presence_of_non_worker_and_tour_frequency_is_2,878.00882728962233,-0.65710000000000002,0,,,878.00882728962233 -coef_presence_of_non_worker_and_tour_frequency_is_5,-1944.9226435678067,-1.4044000000000001,0,,,-1944.9226435678067 -coef_presence_of_pre_driving_school_kid_and_eating_out_tour,-164.90625497529834,-1.5698000000000001,0,,,-164.90625497529834 -coef_presence_of_pre_school_kid_and_eating_out_tour,313.47630877463621,-0.29870000000000002,0,,,313.47630877463621 -coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,4033.5668708392936,-0.32190000000000002,0,,,4033.5668708392936 -coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,10149.331976157329,-1.0873999999999999,0,,,10149.331976157329 -coef_presence_of_university_student_and_discretionary_tour,3906.3784034663036,-1.2834000000000001,0,,,3906.3784034663036 -coef_total_number_of_tours_is_1,15200.662336544106,-7.1505999999999998,0,,,15200.662336544106 -coef_total_number_of_tours_is_2,-1638.5561861275439,-11.1214,0,,,-1638.5561861275439 -coef_total_number_of_tours_is_3,-14010.60832366959,-13.175000000000001,0,,,-14010.60832366959 -coef_urban_and_discretionary_tour,0,0,0,0,0,0 -coef_urban_and_maintenance_tour,-1194.333213569586,1.0394000000000001,0,,,-1194.333213569586 -coef_0_auto_household_and_escorting_tour,-2,-2,0,-2,-2,-2 -coef_1_escort_tour_constant,-1.5720814237734582,-0.75509999999999999,0,,,-1.5720814237734582 -coef_1_plus_eating_out_tours_constant,-2.2222102013387453,1.1145,0,,,-2.2222102013387453 -coef_1_plus_maintenance_tours_constant,-1.4971354138568955,-0.50600000000000001,0,,,-1.4971354138568955 -coef_1_plus_other_discretionary_tours_constant,0.090817823541839565,0.46339999999999998,0,,,0.090817823541839565 -coef_1_plus_shopping_tours_constant,1.4746879181605808,0.4783,0,,,1.4746879181605808 -coef_1_plus_visting_tours_constant,-1.7926081421309932,-0.40060000000000001,0,,,-1.7926081421309932 -coef_2_plus_escort_tours_constant,-2.0596227390284212,-0.0086,0,,,-2.0596227390284212 -coef_auto_access_to_retail_and_escorting,0.55510802136078319,0.062899999999999998,0,,,0.55510802136078319 -coef_high_income_group_and_eating_out_tour,-1.3619797807034295,-0.70099999999999996,0,,,-1.3619797807034295 -coef_high_income_group_and_shopping_tour,-3.7366703425339884,-0.65059999999999996,0,,,-3.7366703425339884 -coef_high_income_group_and_tour_frequency_is_5_plus,16.017262145435474,2.0175000000000001,0,,,16.017262145435474 -coef_logged_maximum_residual_window_tour_frequency_is_5_plus,1.5260250309714616,1.5603,0,,,1.5260250309714616 -coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,15.096813647053857,1.5197000000000001,0,,,15.096813647053857 -coef_mediumlow_income_group_and_tour_frequency_is_5_plus,14.227758877255997,1.0872999999999999,0,,,14.227758877255997 -coef_number_of_joint_maintenance_tours,-1.3475999999999999,-1.3475999999999999,0,,,-1.3475999999999999 -coef_number_of_joint_tours_and_tour_frequency_is_2,-1.1971153311644798,-0.6149,0,,,-1.1971153311644798 -coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,0,-999,-999,-999 -coef_number_of_mandatory_tours_and_tour_frequency_is_1,-9.8896793584290901,-1.0330999999999999,0,,,-9.8896793584290901 -coef_number_of_mandatory_tours_and_tour_frequency_is_3,-10.675107092433787,-2.7444999999999999,0,,,-10.675107092433787 -coef_presence_of_full_time_worker_and_discretionary_tour,0.16721747201730811,0.75260000000000005,0,,,0.16721747201730811 -coef_presence_of_non_worker_and_eating_out_tour,-1.2956623157773164,-1.3073999999999999,0,,,-1.2956623157773164 -coef_presence_of_non_worker_and_shopping_tour,-1.353669617377284,-0.64500000000000002,0,,,-1.353669617377284 -coef_presence_of_non_worker_and_tour_frequency_is_5,-0.43468555779873808,0.2177,0,,,-0.43468555779873808 -coef_presence_of_part_time_worker_and_discretionary_tour,-0.34215511287271527,0.37209999999999999,0,,,-0.34215511287271527 -coef_presence_of_pre_driving_school_kid_and_shopping_tour,1.4153790711463878,0.9365,0,,,1.4153790711463878 -coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,0.29018085236023033,-0.22639999999999999,0,,,0.29018085236023033 -coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,0.32894398996272695,-0.44390000000000002,0,,,0.32894398996272695 -coef_total_number_of_tours_is_1,-11.291182385016718,-7.4863,0,,,-11.291182385016718 -coef_total_number_of_tours_is_2,-13.228339349370408,-10.718,0,,,-13.228339349370408 -coef_total_number_of_tours_is_3,-14.184904611232321,-13.788399999999999,0,,,-14.184904611232321 -coef_urban_and_discretionary_tour,0,0,0,0,0,0 -coef_urban_and_escorting_tour,-4.4838269018301071,0.43519999999999998,0,,,-4.4838269018301071 -coef_walk_access_to_retail_and_eating_out,0.40010315143817771,0.073800000000000004,0,,,0.40010315143817771 -coef_0_auto_household_and_escorting_tour,-2,-2,0,-2,-2,-2 -coef_1_escort_tour_constant,0.17965076785235903,0.36220000000000002,0,,,0.17965076785235903 -coef_1_plus_eating_out_tours_constant,0.20482664652109922,0.96120000000000005,0,,,0.20482664652109922 -coef_1_plus_maintenance_tours_constant,0.073169219104483346,0.67879999999999996,0,,,0.073169219104483346 -coef_1_plus_other_discretionary_tours_constant,1.1336617402336022,1.4935,0,,,1.1336617402336022 -coef_1_plus_shopping_tours_constant,0.78536748101077303,1.6919,0,,,0.78536748101077303 -coef_1_plus_visting_tours_constant,-0.01128610640731513,0.44240000000000002,0,,,-0.01128610640731513 -coef_2_plus_escort_tours_constant,1.7444288874445422,2.2219000000000002,0,,,1.7444288874445422 -coef_discretionary_tour,0.54316174023360153,0.90300000000000002,0,,,0.54316174023360153 -coef_escorting_tour,1.3535085427415612,2.4910000000000001,0,,,1.3535085427415612 -coef_maintenance_tour,0.41636921910448493,1.022,0,,,0.41636921910448493 -coef_presence_of_full_time_worker_and_escorting_tour,-0.61349175561144009,-0.89300000000000002,0,,,-0.61349175561144009 -coef_presence_of_non_worker_and_discretionary_tour,0.01387890311352221,0.79100000000000004,0,,,0.01387890311352221 -coef_presence_of_non_worker_and_eating_out_tour,1.1150524768977683,1.157,0,,,1.1150524768977683 -coef_presence_of_non_worker_and_escorting_tour,0.89099305834953102,0.89000000000000001,0,,,0.89099305834953102 -coef_presence_of_non_worker_and_shopping_tour,0.23105344171814296,0.80800000000000005,0,,,0.23105344171814296 -coef_presence_of_part_time_worker_and_eating_out_tour,1.3926752534763249,1.0369999999999999,0,,,1.3926752534763249 -coef_presence_of_part_time_worker_and_shopping_tour,1.0440437570455019,1.155,0,,,1.0440437570455019 -coef_total_number_of_tours_is_1,-4.4367465516985458,-5.7590000000000003,0,,,-4.4367465516985458 -coef_total_number_of_tours_is_2,-9.0395579310490177,-11.516999999999999,0,,,-9.0395579310490177 -coef_total_number_of_tours_is_3,-12.714428561518217,-17.276,0,,,-12.714428561518217 -coef_total_number_of_tours_is_4,-29.080351094611324,-23.035,0,,,-29.080351094611324 -coef_total_number_of_tours_is_6_plus,-999,-999,0,-999,-999,-999 -coef_urban_and_discretionary_tour,0,0,0,0,0,0 -coef_visiting_or_social_tour,0.31531389359268519,0.76900000000000002,0,,,0.31531389359268519 +param_name,value,best,initvalue,nullvalue +coef_0_auto_household_and_escorting_tour,-2,-2,-2,0 +coef_1_escort_tour_constant,0.4427992642013524,0.4427992642013524,0.029799999669194221,0 +coef_1_plus_eating_out_tours_constant,-0.55916615444423889,-0.55916615444423889,0.0097000002861022949,0 +coef_1_plus_maintenance_tours_constant,-0.048218934526752716,-0.048218934526752716,0.12020000070333481,0 +coef_1_plus_other_discretionary_tours_constant,1.1187985007824965,1.1187985007824965,0.74119997024536133,0 +coef_1_plus_shopping_tours_constant,0.80935601218553088,0.80935601218553088,0.47740000486373901,0 +coef_1_plus_visting_tours_constant,0.32772255127625538,0.32772255127625538,0.052200000733137131,0 +coef_2_plus_escort_tours_constant,0.86516558906506291,0.86516558906506291,0.7401999831199646,0 +coef_at_home_pre_driving_school_kid_and_escorting_tour,-1.1058628439891163,-1.1058628439891163,-0.27459999918937683,0 +coef_at_home_pre_school_kid_and_discretionary_tour,-0.70795142385539511,-0.70795142385539511,-0.47029998898506165,0 +coef_at_home_pre_school_kid_and_escorting_tour,-0.59160407292839623,-0.59160407292839623,-1.5674999952316284,0 +coef_auto_access_to_retail_and_discretionary,0.045130482105384076,0.045130482105384076,0.084399998188018799,0 +coef_auto_access_to_retail_and_maintenance,0.066126086285235641,0.066126086285235641,0.074900001287460327,0 +coef_auto_access_to_retail_and_shopping,0.12409575232027123,0.12409575232027123,0.10670000314712524,0 +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,0.17885689584708081,0.17885689584708081,0.13040000200271606,0 +coef_female_and_escorting_tour,0.56410426544507486,0.56410426544507486,0.18240000307559967,0 +coef_female_and_tour_frequency_is_1,-0.30708391029855547,-0.30708391029855547,-0.076600000262260437,0 +coef_female_and_tour_frequency_is_2,-0.55559756867326349,-0.55559756867326349,-0.10620000213384628,0 +coef_female_and_tour_frequency_is_5,0.018075964162005607,0.018075964162005607,-0.32739999890327454,0 +coef_high_income_group_and_discretionary_tour,-0.091486067503143295,-0.091486067503143295,0.2565000057220459,0 +coef_high_income_group_and_eating_out_tour,0.72625729628634217,0.72625729628634217,0.55809998512268066,0 +coef_high_income_group_and_tour_frequency_is_1,1.155230706967018,1.155230706967018,0.51889997720718384,0 +coef_high_income_group_and_tour_frequency_is_2,2.3389197436575069,2.3389197436575069,1.1335999965667725,0 +coef_high_income_group_and_tour_frequency_is_5_plus,0.47586062840136895,0.47586062840136895,1.3898999691009521,0 +coef_high_income_group_and_visiting_tour,-0.86542592778132377,-0.86542592778132377,-0.24230000376701355,0 +coef_logged_maximum_residual_window_tour_frequency_is_1,1.3596125256366514,1.3596125256366514,1.2561999559402466,0 +coef_logged_maximum_residual_window_tour_frequency_is_2,1.4369987512243636,1.4369987512243636,1.2868000268936157,0 +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,0.84347379326069005,0.84347379326069005,1.3992999792098999,0 +coef_mediumhigh_income_group_and_tour_frequency_is_1,1.1094796643673868,1.1094796643673868,0.49810001254081726,0 +coef_mediumhigh_income_group_and_tour_frequency_is_2,1.9181926670959439,1.9181926670959439,0.8345000147819519,0 +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,1.3393581345532311,1.3393581345532311,1.0212999582290649,0 +coef_number_of_joint_eating_out_tours,-1.7726850801344511,-1.7726850801344511,-0.58660000562667847,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-1.4026438175955793,-1.4026438175955793,-0.88870000839233398,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-2.025313408839498,-2.025313408839498,-2.3343000411987305,0 +coef_presence_of_driving_school_kid_and_discretionary_tour,0.33629833566221962,0.33629833566221962,-0.39629998803138733,0 +coef_presence_of_driving_school_kid_and_escorting_tour,-0.19071865882881728,-0.19071865882881728,0.36010000109672546,0 +coef_presence_of_full_time_worker_and_discretionary_tour,-0.75882600647076048,-0.75882600647076048,-0.66699999570846558,0 +coef_presence_of_full_time_worker_and_eating_out_tour,-0.73960069695319364,-0.73960069695319364,-0.35710000991821289,0 +coef_presence_of_full_time_worker_and_maintenance_tour,-0.38630750284054705,-0.38630750284054705,-0.16850000619888306,0 +coef_presence_of_full_time_worker_and_shopping_tour,-0.60182073500121425,-0.60182073500121425,-0.30590000748634338,0 +coef_presence_of_non_worker_and_discretionary_tour,-1.2394724190464534,-1.2394724190464534,-0.42809998989105225,0 +coef_presence_of_non_worker_and_eating_out_tour,-0.43749171051759073,-0.43749171051759073,-0.20139999687671661,0 +coef_presence_of_non_worker_and_escorting_tour,-0.92810302506396747,-0.92810302506396747,-0.48149999976158142,0 +coef_presence_of_non_worker_and_maintenance_tour,-0.25135759242376515,-0.25135759242376515,-0.32370001077651978,0 +coef_presence_of_non_worker_and_shopping_tour,-0.81193650011085927,-0.81193650011085927,-0.41600000858306885,0 +coef_presence_of_part_time_worker_and_discretionary_tour,-0.037914012004716779,-0.037914012004716779,-0.2101999968290329,0 +coef_presence_of_part_time_worker_and_maintenance_tour,-0.18845880952367774,-0.18845880952367774,-0.15839999914169312,0 +coef_presence_of_part_time_worker_and_shopping_tour,-0.13360094221187135,-0.13360094221187135,-0.15410000085830688,0 +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,-0.098195561407346782,-0.098195561407346782,-0.39590001106262207,0 +coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.4005304562436685,1.4005304562436685,1.3974000215530396,0 +coef_presence_of_pre_school_kid_and_discretionary_tour,0.0018788117570303462,0.0018788117570303462,-0.50809997320175171,0 +coef_presence_of_pre_school_kid_and_eating_out_tour,-0.86481034258984602,-0.86481034258984602,-0.42250001430511475,0 +coef_presence_of_pre_school_kid_and_escorting_tour,0.74141629258937403,0.74141629258937403,0.6841999888420105,0 +coef_presence_of_pre_school_kid_and_shopping_tour,-0.018826868013972368,-0.018826868013972368,-0.20800000429153442,0 +coef_presence_of_retiree_and_discretionary_tour,-0.56414341094868059,-0.56414341094868059,-0.91039997339248657,0 +coef_presence_of_retiree_and_eating_out_tour,-1.2971397912010263,-1.2971397912010263,-0.57080000638961792,0 +coef_presence_of_retiree_and_escorting_tour,-3.9791405866488541,-3.9791405866488541,-0.80800002813339233,0 +coef_presence_of_university_student_and_discretionary_tour,-0.35370106427869641,-0.35370106427869641,-0.85509997606277466,0 +coef_total_number_of_tours_is_1,-8.0929871920905487,-8.0929871920905487,-7.3572001457214355,0 +coef_total_number_of_tours_is_2,-11.373665685061901,-11.373665685061901,-10.647000312805176,0 +coef_total_number_of_tours_is_3,-13.230959643793058,-13.230959643793058,-13.500499725341797,0 +coef_total_number_of_tours_is_4,-15.595277265944466,-15.595277265944466,-16.396499633789062,0 +coef_total_number_of_tours_is_5,-19.867033359049749,-19.867033359049749,-19.684299468994141,0 +coef_total_number_of_tours_is_6_plus,-999,-999,-999,0 +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0.050586414602862534,0.050586414602862534,0.022600000724196434,0 +coef_urban_and_discretionary_tour,0,0,0,0 +coef_urban_and_escorting_tour,0.23133047198776119,0.23133047198776119,-0.43160000443458557,0 +coef_walk_access_to_retail_and_discretionary,0.035768845177126592,0.035768845177126592,0.056699998676776886,0 +coef_walk_access_to_retail_and_eating_out,0.23990162152188213,0.23990162152188213,0.14499999582767487,0 +coef_walk_access_to_retail_and_escorting,-0.12003056391798796,-0.12003056391798796,0.045099999755620956,0 +coef_walk_access_to_retail_and_shopping,-0.045608290266312995,-0.045608290266312995,0.032999999821186066,0 +coef_zero_car_ownership_and_tour_frequency_is_5_plus,-0.2160690015503576,-0.2160690015503576,-0.34860000014305115,0 +coef_0_auto_household_and_escorting_tour,-2,-2,-2,0 +coef_1_escort_tour_constant,0.78022647864874106,0.78022647864874106,0.52719998359680176,0 +coef_1_plus_eating_out_tours_constant,1.6369882471832848,1.6369882471832848,0.69139999151229858,0 +coef_1_plus_maintenance_tours_constant,1.2611597485996247,1.2611597485996247,0.55330002307891846,0 +coef_1_plus_other_discretionary_tours_constant,1.8042028984875396,1.8042028984875396,0.79890000820159912,0 +coef_1_plus_shopping_tours_constant,1.4577278573241144,1.4577278573241144,0.75690001249313354,0 +coef_1_plus_visting_tours_constant,1.0730718283709404,1.0730718283709404,0.14049999415874481,0 +coef_2_plus_escort_tours_constant,1.8729239069881625,1.8729239069881625,1.5987000465393066,0 +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,0.047550202162169208,0.047550202162169208,-0.54979997873306274,0 +coef_female_and_discretionary_tour,0.44246508408459873,0.44246508408459873,0.30720001459121704,0 +coef_female_and_shopping_tour,0.72280754095601429,0.72280754095601429,0.45239999890327454,0 +coef_high_income_group_and_discretionary_tour,0.17993929507162121,0.17993929507162121,0.29600000381469727,0 +coef_high_income_group_and_maintenance_tour,1.2972259045977341,1.2972259045977341,0.67629998922348022,0 +coef_high_income_group_and_shopping_tour,0.87248673602279736,0.87248673602279736,0.70660001039505005,0 +coef_high_income_group_and_tour_frequency_is_1,1.2363061506956392,1.2363061506956392,0.86820000410079956,0 +coef_high_income_group_and_tour_frequency_is_2,1.3997702009895265,1.3997702009895265,1.5362000465393066,0 +coef_high_income_group_and_tour_frequency_is_5_plus,1.5247592588483323,1.5247592588483323,1.9330999851226807,0 +coef_high_income_group_and_visiting_tour,-0.58407376090955276,-0.58407376090955276,-0.68680000305175781,0 +coef_logged_maximum_residual_window_tour_frequency_is_1,0.78207461828672042,0.78207461828672042,1.5748000144958496,0 +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,1.2295616602720314,1.2295616602720314,2.0025999546051025,0 +coef_mediumhigh_income_group_and_shopping_tour,0.64569736253979326,0.64569736253979326,0.44209998846054077,0 +coef_mediumlow_income_group_and_tour_frequency_is_1,0.88613463643879131,0.88613463643879131,0.59810000658035278,0 +coef_mediumlow_income_group_and_tour_frequency_is_2,0.84850399647408248,0.84850399647408248,0.91780000925064087,0 +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,0.87831822891977274,0.87831822891977274,1.7539000511169434,0 +coef_number_of_joint_tours_and_tour_frequency_is_4,-1.2633997095537546,-1.2633997095537546,-1.1986000537872314,0 +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,-999,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.94282353171733657,-0.94282353171733657,-0.23899999260902405,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-2.7338328554607796,-2.7338328554607796,-1.8207999467849731,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-2.6682909569935234,-2.6682909569935234,-2.5922999382019043,0 +coef_presence_of_driving_school_kid_and_escorting_tour,1.0188615044012985,1.0188615044012985,0.41639998555183411,0 +coef_presence_of_full_time_worker_and_maintenance_tour,-0.48961457222493282,-0.48961457222493282,-0.31310001015663147,0 +coef_presence_of_non_worker_and_discretionary_tour,-0.57727792649553333,-0.57727792649553333,-1.0370999574661255,0 +coef_presence_of_non_worker_and_eating_out_tour,-0.21267685745459988,-0.21267685745459988,-0.65450000762939453,0 +coef_presence_of_non_worker_and_escorting_tour,-0.59185572336636527,-0.59185572336636527,-0.52630001306533813,0 +coef_presence_of_part_time_worker_and_maintenance_tour,-1.0186820306196382,-1.0186820306196382,-0.56209999322891235,0 +coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.7856557294189983,1.7856557294189983,1.5794999599456787,0 +coef_presence_of_pre_school_kid_and_escorting_tour,0.27408822617776946,0.27408822617776946,0.54140001535415649,0 +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,0.30438027742581492,0.30438027742581492,-0.15590000152587891,0 +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-0.52997357567752201,-0.52997357567752201,-0.5680999755859375,0 +coef_presence_of_retiree_and_eating_out_tour,0.057141478624328376,0.057141478624328376,-1.3890000581741333,0 +coef_presence_of_retiree_and_escorting_tour,-0.44904086319222258,-0.44904086319222258,-0.75160002708435059,0 +coef_presence_of_university_student_and_eating_out_tour,-1.819545601982254,-1.819545601982254,-1.4318000078201294,0 +coef_total_number_of_tours_is_1,-7.0159278521309831,-7.0159278521309831,-7.6391000747680664,0 +coef_total_number_of_tours_is_2,-10.006686059458314,-10.006686059458314,-10.455699920654297,0 +coef_total_number_of_tours_is_3,-12.780090082076166,-12.780090082076166,-14.017600059509277,0 +coef_total_number_of_tours_is_4,-17.006726946049447,-17.006726946049447,-16.971700668334961,0 +coef_urban_and_discretionary_tour,0,0,0,0 +coef_urban_and_escorting_tour,0.40857422586786191,0.40857422586786191,-0.39289999008178711,0 +coef_walk_access_to_retail_and_tour_frequency_is_1,0.091591528383907397,0.091591528383907397,0.089900001883506775,0 +coef_walk_access_to_retail_and_tour_frequency_is_2,0.12013944932753479,0.12013944932753479,0.14470000565052032,0 +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0.043892915968164865,0.043892915968164865,0.34790000319480896,0 +coef_0_auto_household_and_escorting_tour,-2,-2,-2,0 +coef_1_escort_tour_constant,1.8320083268912393,1.8320081212504946,1.7028000354766846,0 +coef_1_plus_eating_out_tours_constant,-13.842117153486281,-13.842113426324161,2.0722999572753906,0 +coef_1_plus_maintenance_tours_constant,-0.36965786889297769,-0.36965847869322271,0.33480000495910645,0 +coef_1_plus_other_discretionary_tours_constant,-1.2004258495977875,-1.2004252032682035,1.3388999700546265,0 +coef_1_plus_shopping_tours_constant,1.9630014272782856,1.9630010920712406,1.8402999639511108,0 +coef_1_plus_visting_tours_constant,1.0077266905164448,1.0077264438102758,1.2172000408172607,0 +coef_2_plus_escort_tours_constant,2.7101792728099783,2.7101793241888337,2.837899923324585,0 +coef_auto_access_to_retail_and_discretionary,0.60576917052564894,0.60576901559373153,0.093999996781349182,0 +coef_auto_access_to_retail_and_eating_out,3.2803304602848562,3.2803296298812761,0.10180000215768814,0 +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-1.1286721006590705,-1.1286716773156127,-0.58099997043609619,0 +coef_female_and_discretionary_tour,-0.27866976927760068,-0.27866980957578169,-0.32659998536109924,0 +coef_female_and_eatingout_tour,-0.71346970397905807,-0.71346918819904392,-0.65679997205734253,0 +coef_female_and_tour_frequency_is_1,-0.48821855191385899,-0.48821751083893139,0.097300000488758087,0 +coef_female_and_tour_frequency_is_2,0.70828217386581849,0.70828183909772424,0.23610000312328339,0 +coef_female_and_tour_frequency_is_5,2.0698314021941049,2.0698320315070937,1.9002000093460083,0 +coef_high_income_group_and_eating_out_tour,-1.7871396439814193,-1.7871393359274383,-0.72070002555847168,0 +coef_high_income_group_and_shopping_tour,-0.0097579376258961487,-0.0097578081985406004,0.56929999589920044,0 +coef_high_income_group_and_tour_frequency_is_1,1.4527093121517425,1.4527099923825588,0.3986000120639801,0 +coef_high_income_group_and_tour_frequency_is_2,0.90039297576289479,0.90039284655601348,0.80089998245239258,0 +coef_high_income_group_and_tour_frequency_is_5_plus,-6.947254854872086,-6.9472539654420844,0.82539999485015869,0 +coef_high_income_group_and_visiting_tour,-0.77942127489278434,-0.77942163984758739,-0.36939999461174011,0 +coef_logged_maximum_residual_window_tour_frequency_is_0,0.26793790497643488,0.26793818025889998,1.1857999563217163,0 +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,2.4020620521081604,2.4020617768256951,1.4842000007629395,0 +coef_mediumhigh_income_group_and_tour_frequency_is_1,0.4738896197844194,0.4738898434218578,0.11089999973773956,0 +coef_mediumhigh_income_group_and_tour_frequency_is_2,2.1475070128100544,2.1475072544785649,0.39140000939369202,0 +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,3.9137980844922171,3.9137982636389732,0.61369997262954712,0 +coef_number_of_joint_discretionary_tours,-6.8227040161278429,-6.8227030499165631,0.67129999399185181,0 +coef_number_of_joint_shopping_tours,-4.5845196404815836,-4.5845189614516721,-0.71299999952316284,0 +coef_number_of_joint_tours_and_tour_frequency_is_2,-9.1761287341051698,-9.1761275454648299,-0.31529998779296875,0 +coef_number_of_joint_tours_and_tour_frequency_is_3,-1.7257215207841496,-1.7257219586505792,-0.73509997129440308,0 +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,-999,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.64122576357731442,-0.64122588480735709,-0.18520000576972961,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-1.7823789287319811,-1.7823796487869576,-0.87529999017715454,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-2.9941269208431893,-2.9941272442555316,-1.6158000230789185,0 +coef_presence_of_full_time_worker_and_discretionary_tour,-1.1123947161390522,-1.1123952221405766,-0.48330000042915344,0 +coef_presence_of_full_time_worker_and_eating_out_tour,0.7644158078010701,0.76441605865788576,-0.5250999927520752,0 +coef_presence_of_full_time_worker_and_shopping_tour,-0.47330099399200232,-0.4733010233040793,-0.7728000283241272,0 +coef_presence_of_non_worker_and_discretionary_tour,-0.59088716119227658,-0.59088747572415357,0.9781000018119812,0 +coef_presence_of_non_worker_and_tour_frequency_is_1,0.1878408165883074,0.18784146495376636,-0.85060000419616699,0 +coef_presence_of_non_worker_and_tour_frequency_is_5,-0.17945867023496131,-0.17945929629633911,-1.180400013923645,0 +coef_presence_of_part_time_worker_and_eating_out_tour,-3.2345296325509101,-3.234529777482781,-1.9795000553131104,0 +coef_presence_of_part_time_worker_and_escorting_tour,-2.2546395276485063,-2.2546394925137023,-1.8213000297546387,0 +coef_presence_of_part_time_worker_and_shopping_tour,-0.7496461309021506,-0.74964534531823057,-0.51990002393722534,0 +coef_presence_of_pre_driving_school_kid_and_escorting_tour,-0.083989210795650721,-0.083989664675771999,0.94889998435974121,0 +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0.053444488601664397,0.053444497296591398,0.38629999756813049,0 +coef_presence_of_pre_school_kid_and_escorting_tour,1.725644687339964,1.7256441682495762,2.1465001106262207,0 +coef_presence_of_pre_school_kid_and_maintenance_tour,-0.5795847743089354,-0.57958494820750939,0.96939998865127563,0 +coef_presence_of_pre_school_kid_and_shopping_tour,0.45827102667224523,0.45827002311694837,1.3135000467300415,0 +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,-2.0326667193288683,-2.0326652307764594,-0.99610000848770142,0 +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,-0.71238012908852999,-0.71237818006976983,-1.9096000194549561,0 +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-0.20193836611977739,-0.201935994121831,-2.8468999862670898,0 +coef_presence_of_university_student_and_discretionary_tour,0.066507097009832913,0.066507630930055919,-0.65420001745223999,0 +coef_presence_of_university_student_and_eating_out_tour,-0.42018064953666173,-0.42018066679895533,-0.65289998054504395,0 +coef_total_number_of_tours_is_1,-8.6552470544456295,-8.6552472298372294,-6.2137999534606934,0 +coef_total_number_of_tours_is_2,-11.339670857033484,-11.33967023685339,-8.9079999923706055,0 +coef_total_number_of_tours_is_3,-14.129960972164627,-14.129960682683405,-12.32610034942627,0 +coef_total_number_of_tours_is_4,-17.475109164095372,-17.475108877724633,-15.811400413513184,0 +coef_transit_access_to_retail_and_discretionary,0,0,0,0 +coef_transit_access_to_retail_and_maintenance,0.25155766645491617,0.25155779901079267,0.031399998813867569,0 +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0.20940431632076822,0.20940454322004187,0.066399998962879181,0 +coef_urban_and_discretionary_tour,-1.5830257994345194,-1.5830251531049353,0.95630002021789551,0 +coef_urban_and_eatingout_tour,-15.234417103609095,-15.234413376446975,0.68000000715255737,0 +coef_urban_and_escorting_tour,0.72536698170688063,0.72536687882384698,0.85159999132156372,0 +coef_urban_and_maintenance_tour,0.32714212462203368,0.32714151482178866,1.0315999984741211,0 +coef_urban_and_shopping_tour,0.65570145569778049,0.65570112049073548,0.53299999237060547,0 +coef_urban_and_tour_frequency_is_1,-3.606247148859373,-3.6062473242509725,-1.1648000478744507,0 +coef_urban_and_tour_frequency_is_2,-4.7493707738730677,-4.7493701536929747,-2.3176999092102051,0 +coef_urban_and_tour_frequency_is_5_plus,-5.9702694637288616,-5.9702688878768999,-2.5027000904083252,0 +coef_walk_access_to_retail_and_shopping,0.10528331492362221,0.1052833269153322,0.097199998795986176,0 +coef_0_auto_household_and_escorting_tour,-2,-2,-2,0 +coef_1_escort_tour_constant,-1.8969002612948864,-1.8972809252170171,-0.06289999932050705,0 +coef_1_plus_eating_out_tours_constant,-2.0443889188163173,-2.0448333669216079,-0.1429000049829483,0 +coef_1_plus_maintenance_tours_constant,-7.7254359495798148,-7.7270897339714733,-0.065300002694129944,0 +coef_1_plus_other_discretionary_tours_constant,-2.0647872487949561,-2.0651921993347462,0.33340001106262207,0 +coef_1_plus_shopping_tours_constant,-1.282411214400667,-1.2827907558560692,0.46830001473426819,0 +coef_1_plus_visting_tours_constant,-2.1187265722127613,-2.119130128830065,-0.12720000743865967,0 +coef_2_plus_escort_tours_constant,-3.4882178837837579,-3.4889221159472918,0.92729997634887695,0 +coef_at_home_pre_driving_school_kid_and_escorting_tour,-0.83394458908199209,-0.83391904211683632,-1.1480000019073486,0 +coef_at_home_pre_school_kid_and_eating_out_tour,0.6315649245505468,0.63153544170594222,-0.39259999990463257,0 +coef_at_home_pre_school_kid_and_escorting_tour,-0.08455563088757391,-0.084558517582898715,-0.13729999959468842,0 +coef_auto_access_to_retail_and_maintenance,0.67210093938356752,0.67223833895969887,0.095600001513957977,0 +coef_car_shortage_vs_workers_and_tour_frequency_is_1,0.22076749188228875,0.22093605520065349,-0.36230000853538513,0 +coef_car_shortage_vs_workers_and_tour_frequency_is_2,-0.9349732023831957,-0.93482141743941694,-1.2719999551773071,0 +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-2.0213316139356832,-2.0212701718601216,-1.9306999444961548,0 +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,3.5090722695093683,3.5095724879606411,0.77380001544952393,0 +coef_female_and_maintenance_tour,-0.24827336118817248,-0.24851003473203095,-0.24639999866485596,0 +coef_female_and_tour_frequency_is_1,0.55537913022754337,0.55558571844411853,0.39019998908042908,0 +coef_female_and_tour_frequency_is_2,0.4700121436993433,0.47033652415332988,0.53229999542236328,0 +coef_female_and_tour_frequency_is_3,1.0935778897473212,1.0937278933542067,0.74519997835159302,0 +coef_female_and_tour_frequency_is_5,2.1058304843489379,2.1060351207036332,1.1294000148773193,0 +coef_high_income_group_and_discretionary_tour,0.53542200030194598,0.53532544473639576,0.88459998369216919,0 +coef_high_income_group_and_eating_out_tour,1.5430004952789953,1.5430357486801614,0.70859998464584351,0 +coef_high_income_group_and_shopping_tour,0.72248005627607348,0.72246863725799271,0.97759997844696045,0 +coef_high_income_group_and_tour_frequency_is_2,4.8659060743107148,4.8667865382550879,1.0633000135421753,0 +coef_high_income_group_and_tour_frequency_is_3,5.1569073742137981,5.1577005315354292,1.7741999626159668,0 +coef_high_income_group_and_tour_frequency_is_5_plus,5.5695995714955888,5.5703869156647645,2.3940999507904053,0 +coef_high_income_group_and_visiting_tour,-0.55652923789707232,-0.55654488685220238,-0.94489997625350952,0 +coef_logged_maximum_residual_window_tour_frequency_is_1,6.8143657923425485,6.815671298679093,1.763700008392334,0 +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,7.4778936905915021,7.4792750296860024,1.7927999496459961,0 +coef_mediumhigh_income_group_and_discretionary_tour,0.19484718211939026,0.1949087350001007,0.50089997053146362,0 +coef_mediumhigh_income_group_and_eating_out_tour,-0.17900832259277194,-0.17895101978739814,0.46309998631477356,0 +coef_mediumhigh_income_group_and_shopping_tour,1.2056310249094397,1.2056460380629153,0.89060002565383911,0 +coef_mediumhigh_income_group_and_tour_frequency_is_1,6.1357755555537432,6.1368619389686074,0.74260002374649048,0 +coef_mediumhigh_income_group_and_tour_frequency_is_2,5.6203221150091016,5.621312928169897,0.85460001230239868,0 +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,5.902275082711002,5.9033024674122805,1.0792000293731689,0 +coef_mediumhigh_income_group_and_visiting_tour,0.0072888420909105259,0.0072425497797064513,-0.2669999897480011,0 +coef_mediumlow_income_group_and_discretionary_tour,-0.29540295644751735,-0.29532964571554288,0.17069999873638153,0 +coef_mediumlow_income_group_and_eating_out_tour,0.65802264858986625,0.65793719500149939,0.27660000324249268,0 +coef_mediumlow_income_group_and_shopping_tour,0.5503864174305747,0.55034836543703713,0.77340000867843628,0 +coef_mediumlow_income_group_and_tour_frequency_is_1,3.6362917244942166,3.6370680682721321,0.57090002298355103,0 +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,3.8030230281375874,3.8037930038540892,0.83149999380111694,0 +coef_number_of_joint_eating_out_tours,-5.7578659480764109,-5.7590292220149779,-0.77270001173019409,0 +coef_number_of_joint_shopping_tours,-10.86032878033782,-10.862820539578552,-0.23909999430179596,0 +coef_number_of_joint_tours_and_tour_frequency_is_1,-3.5806784726726657,-3.5814001794995587,-0.16990000009536743,0 +coef_number_of_joint_tours_and_tour_frequency_is_2,-5.1193513695195279,-5.1202366413321725,-0.42849999666213989,0 +coef_number_of_joint_tours_and_tour_frequency_is_3,-4.6446726603410955,-4.6456045066231875,-0.65509998798370361,0 +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-4.8470304959707029,-4.8478742633711249,-1.041100025177002,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.67659997940063477,-0.67659997940063477,-0.67659997940063477,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-1.051800012588501,-1.051800012588501,-1.051800012588501,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-999,-999,-999,0 +coef_presence_of_full_time_worker_and_eating_out_tour,-1.3129272099813087,-1.3129546317286533,-0.4666999876499176,0 +coef_presence_of_full_time_worker_and_escorting_tour,0.34977167501271478,0.3497410147889421,0.39469999074935913,0 +coef_presence_of_non_worker_and_eating_out_tour,-0.40015678475147548,-0.40015646938307892,-0.49759998917579651,0 +coef_presence_of_non_worker_and_tour_frequency_is_1,1.2564012158056577,1.2568441721992365,-0.37630000710487366,0 +coef_presence_of_non_worker_and_tour_frequency_is_2,1.0428547824447958,1.0433986649176088,-0.71899998188018799,0 +coef_presence_of_non_worker_and_tour_frequency_is_5,1.6729377444156812,1.673362537920315,-1.0228999853134155,0 +coef_presence_of_part_time_worker_and_discretionary_tour,-0.46853620786950861,-0.46851175171192849,-0.35449999570846558,0 +coef_presence_of_part_time_worker_and_escorting_tour,-0.91620401760820491,-0.91626917282183395,-0.58609998226165771,0 +coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.645226868283342,1.6452028413894657,1.3773000240325928,0 +coef_presence_of_pre_school_kid_and_escorting_tour,0.73413015866674558,0.73411877105653434,0.71939998865127563,0 +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,-4.2717006949434637,-4.2727718042560454,0.14859999716281891,0 +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,-4.1531060929831938,-4.1542847014169757,0.48399999737739563,0 +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-4.0092293410093136,-4.0100024764367959,-0.71609997749328613,0 +coef_presence_of_retiree_and_eating_out_tour,-0.98695379970331221,-0.98695373145616694,-0.69110000133514404,0 +coef_presence_of_retiree_and_tour_frequency_is_1,2.3328682638704601,2.3340717788338958,-0.46399998664855957,0 +coef_presence_of_retiree_and_tour_frequency_is_5,2.2895526967814139,2.2902926082161419,-0.47949999570846558,0 +coef_total_number_of_tours_is_1,-14.862387943118435,-14.863701190898123,-8.979100227355957,0 +coef_total_number_of_tours_is_2,-15.76114107396082,-15.762046562760142,-12.024800300598145,0 +coef_total_number_of_tours_is_3,-17.754112538361621,-17.754634820463089,-14.85159969329834,0 +coef_total_number_of_tours_is_4,-18.779593636700369,-18.779689721119343,-17.703699111938477,0 +coef_urban_and_discretionary_tour,0,0,0,0 +coef_walk_access_to_retail_and_discretionary,0.21083331596043739,0.21082887854988322,0.07720000296831131,0 +coef_walk_access_to_retail_and_shopping,0.042414728322429048,0.042410061719515363,0.059799998998641968,0 +coef_walk_access_to_retail_and_tour_frequency_is_1,-0.73146719824169415,-0.73175969660042617,0.071299999952316284,0 +coef_walk_access_to_retail_and_tour_frequency_is_2,-0.6224679003604594,-0.62275823201236125,0.12559999525547028,0 +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,-0.48317718182460601,-0.48343535149985983,0.15080000460147858,0 +coef_0_auto_household_and_escorting_tour,-2,-2,-2,0 +coef_1_escort_tour_constant,-1.3838956479528135,-1.3838955598311522,-0.39919999241828918,0 +coef_1_plus_eating_out_tours_constant,-1.2251820468944299,-1.2251815896798568,0.024499999359250069,0 +coef_1_plus_maintenance_tours_constant,-0.9467390901603373,-0.94673868292188801,0.10459999740123749,0 +coef_1_plus_other_discretionary_tours_constant,-0.95705700168035457,-0.95705640502785616,0.42820000648498535,0 +coef_1_plus_shopping_tours_constant,-0.56851096405906976,-0.56851065297640646,0.59469997882843018,0 +coef_1_plus_visting_tours_constant,-0.99997515158264494,-0.99997480861181898,0.27889999747276306,0 +coef_2_plus_escort_tours_constant,-2.2472239741783695,-2.2472230312575778,0.51749998331069946,0 +coef_car_surplus_vs_workers_and_tour_frequency_is_1,2.6263187421217502,2.6263182643290257,0.79650002717971802,0 +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,3.0138266039361694,3.0138263991996164,2.1301999092102051,0 +coef_female_and_discretionary_tour,0.57421820949821378,0.57421776265903679,0.49540001153945923,0 +coef_female_and_maintenance_tour,0.7032371772890682,0.70323730968090981,0.74239999055862427,0 +coef_female_and_shopping_tour,0.60749249967525931,0.60749236436044163,0.96880000829696655,0 +coef_female_and_tour_frequency_is_1,-2.3057887932980217,-2.3057879644985477,-0.93480002880096436,0 +coef_female_and_tour_frequency_is_2,-2.5245735788315185,-2.5245730541075631,-1.3028000593185425,0 +coef_female_and_tour_frequency_is_5,-3.9777594453014777,-3.9777585979711256,-2.2660000324249268,0 +coef_high_income_group_and_discretionary_tour,0.96176887062837879,0.9617690305973885,1.0095000267028809,0 +coef_high_income_group_and_eating_out_tour,1.6107399863189256,1.6107399132659015,1.4842000007629395,0 +coef_high_income_group_and_maintenance_tour,0.99860462074351897,0.99860457400478175,1.3795000314712524,0 +coef_high_income_group_and_shopping_tour,1.0955552497273626,1.0955552433296207,1.0949000120162964,0 +coef_high_income_group_and_visiting_tour,-0.62823584789675457,-0.62823569014018499,-0.51370000839233398,0 +coef_logged_maximum_residual_window_tour_frequency_is_1,2.0411409487638097,2.0411408722900823,1.8357000350952148,0 +coef_logged_maximum_residual_window_tour_frequency_is_2,5.0543518983412508,5.0543512662707899,2.2706999778747559,0 +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,5.1028111260779792,5.1028109074006487,4.4022998809814453,0 +coef_mediumhigh_income_group_and_eating_out_tour,0.9601832770329618,0.96018319037111421,1.1809999942779541,0 +coef_mediumhigh_income_group_and_maintenance_tour,0.46026894334674823,0.46026867052213322,0.76480001211166382,0 +coef_mediumhigh_income_group_and_visiting_tour,-0.47448562479929113,-0.47448576085276917,-0.43680000305175781,0 +coef_mediumlow_income_group_and_eating_out_tour,0.8587186097762155,0.85871850010116635,0.97689998149871826,0 +coef_number_of_joint_shopping_tours,-0.34163048458137285,-0.34163086120064357,-0.80720001459121704,0 +coef_number_of_joint_tours_and_tour_frequency_is_2,-7.40575378545664,-7.4057519268091907,-0.94999998807907104,0 +coef_number_of_joint_tours_and_tour_frequency_is_3,-8.2528437399202961,-8.2528434839801079,-7.1430001258850098,0 +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,-999,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-5.0195999145507812,-5.0195999145507812,-5.0195999145507812,0 +coef_presence_of_full_time_worker_and_discretionary_tour,-0.32502706520068697,-0.3250272176315594,-0.48350000381469727,0 +coef_presence_of_full_time_worker_and_shopping_tour,-0.18718310533550805,-0.18718290004050162,-0.36090001463890076,0 +coef_presence_of_non_worker_and_discretionary_tour,-0.080381601681135048,-0.080381489052422414,-0.56029999256134033,0 +coef_presence_of_non_worker_and_eating_out_tour,-0.71343718792066768,-0.71343705083784981,-0.78799998760223389,0 +coef_presence_of_non_worker_and_tour_frequency_is_1,1.3664318707961971,1.3664313016982996,0.22400000691413879,0 +coef_presence_of_non_worker_and_tour_frequency_is_2,1.5541568438314686,1.5541565822514429,0.24359999597072601,0 +coef_presence_of_non_worker_and_tour_frequency_is_3,2.3378066705431362,2.3378063973066343,0.62000000476837158,0 +coef_presence_of_non_worker_and_tour_frequency_is_5,3.886799486754084,3.8867989469114872,3.3742001056671143,0 +coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.6990307296529008,1.6990305339512453,1.4903000593185425,0 +coef_presence_of_pre_school_kid_and_escorting_tour,0.64317839301043844,0.64317845433272425,0.50269997119903564,0 +coef_presence_of_retiree_and_eating_out_tour,-0.93915814650169016,-0.93915820457557886,-0.92820000648498535,0 +coef_presence_of_retiree_and_tour_frequency_is_1,0.53309324048384155,0.53309327034571541,-0.44580000638961792,0 +coef_presence_of_retiree_and_tour_frequency_is_5,0.15143338882997009,0.15143298802740426,-0.53149998188018799,0 +coef_total_number_of_tours_is_1,-12.29669710898526,-12.296696353770589,-8.5684003829956055,0 +coef_total_number_of_tours_is_2,-14.366430853959836,-14.366430219226835,-12.741600036621094,0 +coef_total_number_of_tours_is_3,-15.470851663726473,-15.47085200579302,-15.097800254821777,0 +coef_total_number_of_tours_is_4,-16.697442099429654,-16.697442489781661,-19.543899536132812,0 +coef_total_number_of_tours_is_5,-23.975944547216859,-23.975943616807008,-20.789699554443359,0 +coef_urban_and_discretionary_tour,0,0,0,0 +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0.50908621780365026,0.50908614236387195,0.061599999666213989,0 +coef_0_auto_household_and_escorting_tour,-2.4007662488833401,-2.4007662488833401,-2,0 +coef_1_escort_tour_constant,-11.100045881453859,-11.100045881453859,-0.49340000748634338,0 +coef_1_plus_eating_out_tours_constant,-12.674000548814972,-12.674000548814972,-0.024199999868869781,0 +coef_1_plus_maintenance_tours_constant,1.4021937042970116,1.4021937042970116,-0.43439999222755432,0 +coef_1_plus_other_discretionary_tours_constant,-2.4760858637499221,-2.4760858637499221,-0.26019999384880066,0 +coef_1_plus_shopping_tours_constant,5.1109144099794959,5.1109144099794959,0.53200000524520874,0 +coef_1_plus_visting_tours_constant,5.1132912897133904,5.1132912897133904,0.23669999837875366,0 +coef_2_plus_escort_tours_constant,-4.7231718945294894,-4.7231718945294894,1.4155000448226929,0 +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,-2.8928262121700787,-2.8928262121700787,0.10040000081062317,0 +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-23.462489242832998,-23.462489242832998,-0.63690000772476196,0 +coef_car_surplus_vs_workers_and_tour_frequency_is_1,-11.054245969090358,-11.054245969090358,0.29019999504089355,0 +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,26.810453753037919,26.810453753037919,2.0352001190185547,0 +coef_high_income_group_and_discretionary_tour,9.3746353630306327,9.3746353630306327,2.3269999027252197,0 +coef_high_income_group_and_eating_out_tour,-8.894067988889379,-8.894067988889379,0.49160000681877136,0 +coef_high_income_group_and_maintenance_tour,-0.37810556759048242,-0.37810556759048242,0.39820000529289246,0 +coef_high_income_group_and_shopping_tour,-0.46662150365308386,-0.46662150365308386,0.2442999929189682,0 +coef_high_income_group_and_visiting_tour,-0.46885622247201569,-0.46885622247201569,0.28580000996589661,0 +coef_logged_maximum_residual_window_tour_frequency_is_1,15.538672905979983,15.538672905979983,1.329800009727478,0 +coef_logged_maximum_residual_window_tour_frequency_is_2,-15.31294086052077,-15.31294086052077,1.3759000301361084,0 +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,-2.8783154540415228,-2.8783154540415228,3.2808001041412354,0 +coef_mediumhigh_income_group_and_discretionary_tour,2.8464215562810216,2.8464215562810216,1.4049999713897705,0 +coef_mediumlow_income_group_and_discretionary_tour,-7.8393223758039596,-7.8393223758039596,0.91689997911453247,0 +coef_number_of_joint_tours_and_tour_frequency_is_1,-6.5374366056093152,-6.5374366056093152,-0.21619999408721924,0 +coef_number_of_joint_tours_and_tour_frequency_is_2,-4.4265938354565844,-4.4265938354565844,-0.35870000720024109,0 +coef_number_of_joint_tours_and_tour_frequency_is_3,-4.2928228670338138,-4.2928228670338138,-4.2701001167297363,0 +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,-999,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-20.768569059727319,-20.768569059727319,-0.23399999737739563,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_2,13.166961657521094,13.166961657521094,-0.92309999465942383,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-9.1884865390771271,-9.1884865390771271,-6.5834999084472656,0 +coef_presence_of_driving_school_kid_and_discretionary_tour,-1.5287699271825661,-1.5287699271825661,-0.92019999027252197,0 +coef_presence_of_driving_school_kid_and_eating_out_tour,-0.67899286342910536,-0.67899286342910536,-0.63770002126693726,0 +coef_presence_of_non_worker_and_tour_frequency_is_2,7.8203518915786985,7.8203518915786985,-0.65710002183914185,0 +coef_presence_of_non_worker_and_tour_frequency_is_5,-2.3380879397360088,-2.3380879397360088,-1.4043999910354614,0 +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,-2.8548975360289837,-2.8548975360289837,-1.5698000192642212,0 +coef_presence_of_pre_school_kid_and_eating_out_tour,-1.1155840296979183,-1.1155840296979183,-0.2987000048160553,0 +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,7.9990670481874249,7.9990670481874249,-0.32190001010894775,0 +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,9.8647248326504506,9.8647248326504506,-1.087399959564209,0 +coef_presence_of_university_student_and_discretionary_tour,4.5866749933879518,4.5866749933879518,-1.2834000587463379,0 +coef_total_number_of_tours_is_1,5.7323576505278915,5.7323576505278915,-7.1505999565124512,0 +coef_total_number_of_tours_is_2,-13.716885058175075,-13.716885058175075,-11.121399879455566,0 +coef_total_number_of_tours_is_3,-24.558188200243801,-24.558188200243801,-13.175000190734863,0 +coef_urban_and_discretionary_tour,0,0,0,0 +coef_urban_and_maintenance_tour,2.8759936780232791,2.8759936780232791,1.0393999814987183,0 +coef_0_auto_household_and_escorting_tour,-2,-2,-2,0 +coef_1_escort_tour_constant,-0.80019821892406418,-0.80019821892406418,-0.75510001182556152,0 +coef_1_plus_eating_out_tours_constant,-2.2137830257191138,-2.2137830257191138,1.1145000457763672,0 +coef_1_plus_maintenance_tours_constant,-0.87384629825268301,-0.87384629825268301,-0.50599998235702515,0 +coef_1_plus_other_discretionary_tours_constant,0.6794818887801406,0.6794818887801406,0.46340000629425049,0 +coef_1_plus_shopping_tours_constant,1.9914236119221842,1.9914236119221842,0.47830000519752502,0 +coef_1_plus_visting_tours_constant,-1.1732951429240632,-1.1732951429240632,-0.40059998631477356,0 +coef_2_plus_escort_tours_constant,-0.52085404537857938,-0.52085404537857938,-0.0086000002920627594,0 +coef_auto_access_to_retail_and_escorting,0.14995921405552753,0.14995921405552753,0.06289999932050705,0 +coef_high_income_group_and_eating_out_tour,-1.2746622030953361,-1.2746622030953361,-0.70099997520446777,0 +coef_high_income_group_and_shopping_tour,-3.6565535610834519,-3.6565535610834519,-0.65060001611709595,0 +coef_high_income_group_and_tour_frequency_is_5_plus,8.6597646574930796,8.6597646574930796,2.0174999237060547,0 +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,1.56299641940097,1.56299641940097,1.5602999925613403,0 +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,7.735469931243947,7.735469931243947,1.5197000503540039,0 +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,6.8720130507569017,6.8720130507569017,1.0872999429702759,0 +coef_number_of_joint_maintenance_tours,-1.347599983215332,-1.347599983215332,-1.347599983215332,0 +coef_number_of_joint_tours_and_tour_frequency_is_2,-1.2555358714256173,-1.2555358714256173,-0.61489999294281006,0 +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,-999,-999,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-5.0803581001504661,-5.0803581001504661,-1.0331000089645386,0 +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-5.8935586600908669,-5.8935586600908669,-2.7444999217987061,0 +coef_presence_of_full_time_worker_and_discretionary_tour,0.19647967582561615,0.19647967582561615,0.75260001420974731,0 +coef_presence_of_non_worker_and_eating_out_tour,-1.3548917345809393,-1.3548917345809393,-1.3073999881744385,0 +coef_presence_of_non_worker_and_shopping_tour,-1.3398609967955151,-1.3398609967955151,-0.64499998092651367,0 +coef_presence_of_non_worker_and_tour_frequency_is_5,-0.42351455281362266,-0.42351455281362266,0.21770000457763672,0 +coef_presence_of_part_time_worker_and_discretionary_tour,-0.33314199741532502,-0.33314199741532502,0.37209999561309814,0 +coef_presence_of_pre_driving_school_kid_and_shopping_tour,1.4440737444047911,1.4440737444047911,0.93650001287460327,0 +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,0.29958946114398161,0.29958946114398161,-0.22640000283718109,0 +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,0.32067429398079011,0.32067429398079011,-0.44389998912811279,0 +coef_total_number_of_tours_is_1,-9.4531005722326533,-9.4531005722326533,-7.486299991607666,0 +coef_total_number_of_tours_is_2,-11.996770119024941,-11.996770119024941,-10.718000411987305,0 +coef_total_number_of_tours_is_3,-13.550028148803801,-13.550028148803801,-13.788399696350098,0 +coef_urban_and_discretionary_tour,0,0,0,0 +coef_urban_and_escorting_tour,-0.6344062915018166,-0.6344062915018166,0.43520000576972961,0 +coef_walk_access_to_retail_and_eating_out,0.48030056947070726,0.48030056947070726,0.073799997568130493,0 +coef_0_auto_household_and_escorting_tour,-2,-2,-2,0 +coef_1_escort_tour_constant,0.39617684877862708,0.39617684877862708,0.36219999194145203,0 +coef_1_plus_eating_out_tours_constant,1.4990449238097932,1.4990449238097932,0.96119999885559082,0 +coef_1_plus_maintenance_tours_constant,0.71287833893706021,0.71287833893706021,0.67879998683929443,0 +coef_1_plus_other_discretionary_tours_constant,1.7799792001679569,1.7799792001679569,1.4934999942779541,0 +coef_1_plus_shopping_tours_constant,2.0942830938898398,2.0942830938898398,1.6919000148773193,0 +coef_1_plus_visting_tours_constant,0.62786207413189388,0.62786207413189388,0.4424000084400177,0 +coef_2_plus_escort_tours_constant,2.1826221262636776,2.1826221262636776,2.2218999862670898,0 +coef_discretionary_tour,1.1894792030289798,1.1894792030289798,0.90299999713897705,0 +coef_escorting_tour,2.4464210738878447,2.4464210738878447,2.4909999370574951,0 +coef_maintenance_tour,1.0560783072750726,1.0560783072750726,1.0219999551773071,0 +coef_presence_of_full_time_worker_and_escorting_tour,-0.6300922367614431,-0.6300922367614431,-0.89300000667572021,0 +coef_presence_of_non_worker_and_discretionary_tour,-0.0080480967981517125,-0.0080480967981517125,0.79100000858306885,0 +coef_presence_of_non_worker_and_eating_out_tour,1.1025455434303448,1.1025455434303448,1.156999945640564,0 +coef_presence_of_non_worker_and_escorting_tour,0.86673078874996601,0.86673078874996601,0.88999998569488525,0 +coef_presence_of_non_worker_and_shopping_tour,0.20878201493509621,0.20878201493509621,0.80800002813339233,0 +coef_presence_of_part_time_worker_and_eating_out_tour,1.3767801830490909,1.3767801830490909,1.0369999408721924,0 +coef_presence_of_part_time_worker_and_shopping_tour,1.0143615015555587,1.0143615015555587,1.1549999713897705,0 +coef_total_number_of_tours_is_1,-5.7103540103201968,-5.7103540103201968,-5.7589998245239258,0 +coef_total_number_of_tours_is_2,-11.596952013557841,-11.596952013557841,-11.517000198364258,0 +coef_total_number_of_tours_is_3,-16.568257064319742,-16.568257064319742,-17.275999069213867,0 +coef_total_number_of_tours_is_4,-23.18757470591768,-23.18757470591768,-23.034999847412109,0 +coef_total_number_of_tours_is_6_plus,-999,-999,-999,0 +coef_urban_and_discretionary_tour,0,0,0,0 +coef_visiting_or_social_tour,0.95446205949299312,0.95446205949299312,0.76899999380111694,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_nonmand_tour_freq_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_nonmand_tour_freq_loglike.csv index 7e2418fafd..9dea4a6b40 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_nonmand_tour_freq_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_nonmand_tour_freq_loglike.csv @@ -1,9 +1,9 @@ ,loglike_prior,loglike_converge -0,-36.842915290359244,-13.427352349597697 -1,-1867.7130849406183,-1831.0744991065408 -2,-1076.3668030822264,-1038.9605638228181 -3,-877.44304962652359,-856.8595081575636 -4,-230.6429613110198,-225.00971520122775 -5,-806.81758251120061,-787.40004316431327 -6,-277.18561139007045,-256.78783280769073 -7,-358.3650717429976,-324.85841724064665 +0,-36.842915240821576,-13.63752199393485 +1,-1867.7130819595852,-1832.6445382071518 +2,-1076.3667995930466,-1039.2235240389089 +3,-877.44304860975865,-856.98760672658591 +4,-230.64296021604497,-225.07312798066818 +5,-806.81757896884028,-787.83786863094554 +6,-277.18561178415462,-256.90644089706086 +7,-358.36507163326337,-324.9104211327566 diff --git a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_atwork_subtour_scheduling_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_atwork_subtour_scheduling_SLSQP_.csv deleted file mode 100644 index 1e5284852c..0000000000 --- a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_atwork_subtour_scheduling_SLSQP_.csv +++ /dev/null @@ -1,50 +0,0 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_am_peak_end,-1.3731693426269276,-2.928312295,0,-25,25,-1.3731693426269276 -coef_am_peak_start_at_6,-20.592813760446127,-6.1567178269999996,0,-25,25,-20.592813760446127 -coef_am_peak_start_at_7,-2.8269839190766564,-4.0617081419999996,0,-25,25,-2.8269839190766564 -coef_am_peak_start_at_8,-1.1965282925054144,-2.330535201,0,-25,25,-1.1965282925054144 -coef_am_peak_start_at_9,-1.6198974929815253,-1.881593386,0,-25,25,-1.6198974929815253 -coef_dummy_for_business_related_purpose_and_duration_from_0_to_1,-0.66312907740821159,-1.5429999999999999,0,-25,25,-0.66312907740821159 -coef_dummy_for_eating_out_purpose_and_departure_at_11,1.1518273421311946,1.5109999999999999,0,-25,25,1.1518273421311946 -coef_dummy_for_eating_out_purpose_and_departure_at_12,2.6254363230451085,2.7210000000000001,0,-25,25,2.6254363230451085 -coef_dummy_for_eating_out_purpose_and_departure_at_13,2.36098076410833,2.1219999999999999,0,-25,25,2.36098076410833 -coef_dummy_for_eating_out_purpose_and_duration_of_1_hour,0.31040519075637613,0.39989999999999998,0,-25,25,0.31040519075637613 -coef_duration_of_0_hours,9.9599848609439601,-0.90668151200000002,0,-25,25,9.9599848609439601 -coef_duration_of_11_to_13_hours,-0.37405450634311865,0.29999999999999999,0,-25,25,-0.37405450634311865 -coef_duration_of_14_to_18_hours,0,0,0,0,0,0 -coef_duration_of_1_hour,0,0,0,0,0,0 -coef_duration_of_2_to_3_hours,9.1812833977279276,-1.3621758020000001,0,-25,25,9.1812833977279276 -coef_duration_of_4_to_5_hours,-0.48314094706644228,-0.81961761600000005,0,-25,25,-0.48314094706644228 -coef_duration_of_6_to_7_hours,10.535613300026082,1.088111072,0,-25,25,10.535613300026082 -coef_duration_of_8_to_10_hours,10.402182684572614,1.734038505,0,-25,25,10.402182684572614 -coef_duration_shift_for_business_related_,0.60004385998820309,0.2646,0,-25,25,0.60004385998820309 -coef_duration_shift_for_first_sub_tour_of_same_work_tour,0.31988469057309121,-0.3992,0,-25,25,0.31988469057309121 -coef_duration_shift_for_inbound_auto_travel_time_off_peak,-0.11857498443158188,0.0098099999999999993,0,-25,25,-0.11857498443158188 -coef_duration_shift_for_number_of_individual_nonmandatory_tours,0.0098944086043264642,-0.042200000000000001,0,-25,25,0.0098944086043264642 -coef_duration_shift_for_number_of_joint_tours,-0.57768141215671864,-0.24970000000000001,0,-25,25,-0.57768141215671864 -coef_duration_shift_for_number_of_mandatory_tours,-1.0587875726336362,-0.7702,0,-25,25,-1.0587875726336362 -coef_duration_shift_for_outbound_auto_travel_time_off_peak,0.1453238873904982,0.0098099999999999993,0,-25,25,0.1453238873904982 -coef_duration_shift_for_subsequent_sub_tour_of_same_work_tour,-10.333603350935554,-0.18440000000000001,0,-25,25,-10.333603350935554 -coef_early_end_at_5_6,-25,-2.928312295,0,-25,25,-25 -coef_early_start_at_5,-2.2040675056867611,-7.7655484760000002,0,-25,25,-2.2040675056867611 -coef_evening_end_at_19_20_21,-4.5210371252389265,-2.3199822600000002,0,-25,25,-4.5210371252389265 -coef_evening_start_at_19_20_21,-0.32574110086394298,-1.015090023,0,-25,25,-0.32574110086394298 -coef_late_end_at_22_23,-11.516564630810274,-2.3199822600000002,0,-25,25,-11.516564630810274 -coef_late_start_at_22_23,-5.1429250271310103,-0.73757005399999997,0,-25,25,-5.1429250271310103 -coef_midday_end_at_10_11_12,-1.3051956922349568,-2.2972643740000001,0,-25,25,-1.3051956922349568 -coef_midday_end_at_13_14,0,0,0,0,0,0 -coef_midday_start_at_10_11_12,0,0,0,0,0,0 -coef_midday_start_at_13_14_15,-1.0515620376346457,-0.77502157999999999,0,-25,25,-1.0515620376346457 -coef_pm_peak_end_at_15,-1.4329808631274803,-0.57834445700000003,0,-25,25,-1.4329808631274803 -coef_pm_peak_end_at_16,-2.0551088799651303,-1.09408722,0,-25,25,-2.0551088799651303 -coef_pm_peak_end_at_17,-2.4042523970600072,-1.1658466000000001,0,-25,25,-2.4042523970600072 -coef_pm_peak_end_at_18,-3.5003721078254548,-1.4961310809999999,0,-25,25,-3.5003721078254548 -coef_pm_peak_start_at_16_17_18,-0.7985883513777744,-0.227528489,0,-25,25,-0.7985883513777744 -coef_start_shift_for_business_related_,-0.083357458155514152,-0.1113,0,-25,25,-0.083357458155514152 -coef_start_shift_for_first_sub_tour_of_same_work_tour,-0.16832429973206386,-0.54330000000000001,0,-25,25,-0.16832429973206386 -coef_start_shift_for_inbound_auto_travel_time_off_peak,-0.09901878555282706,0.00064999999999999997,0,-25,25,-0.09901878555282706 -coef_start_shift_for_number_of_individual_nonmandatory_tours,0.026776673811965086,-0.012800000000000001,0,-25,25,0.026776673811965086 -coef_start_shift_for_number_of_joint_tours,-0.019721699715671427,-0.0206,0,-25,25,-0.019721699715671427 -coef_start_shift_for_number_of_mandatory_tours,0.059018046122538706,-0.019300000000000001,0,-25,25,0.059018046122538706 -coef_start_shift_for_outbound_auto_travel_time_off_peak,0.10034873691181434,0.00064999999999999997,0,-25,25,0.10034873691181434 -coef_start_shift_for_subsequent_sub_tour_of_same_work_tour,-0.36020623998165718,-0.18440000000000001,0,-25,25,-0.36020623998165718 diff --git a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_joint_tour_scheduling_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_joint_tour_scheduling_SLSQP_.csv index 091e76401e..51f0e05222 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_joint_tour_scheduling_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_joint_tour_scheduling_SLSQP_.csv @@ -1,60 +1,60 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction,-0.028774249414067657,-0.025700000000000001,0,-25,25,-0.028774249414067657 -coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction,0.91901966813332936,-0.02734,0,-25,25,0.91901966813332936 -coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction,0.03464166423412067,0.0084419999999999999,0,-25,25,0.03464166423412067 -coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction,-18.311237242705495,-0.059299999999999999,0,-25,25,-18.311237242705495 -coef_adult_with_children_in_hh_arrive_19_21,0.04436348324103874,0.33600000000000002,0,-25,25,0.04436348324103874 -coef_arrival_constants_am_peak,4.7614100686980576,-8.7288800000000002,0,-25,25,4.7614100686980576 -coef_arrival_constants_early,24.924968513710187,-8.7288800000000002,0,-25,25,24.924968513710187 -coef_arrival_constants_evening,-4.3200714359409025,-2.7489400000000002,0,-25,25,-4.3200714359409025 -coef_arrival_constants_late,-9.6327188982749732,-4.2425300000000004,0,-25,25,-9.6327188982749732 -coef_arrival_constants_midday_1,0,0,0,0,0,0 -coef_arrival_constants_midday_2,2.6541662776744461,1.40804,0,-25,25,2.6541662776744461 -coef_arrival_constants_pm_peak_1,1.8388653479429438,1.0203599999999999,0,-25,25,1.8388653479429438 -coef_arrival_constants_pm_peak_2,1.4625561851708289,1.06863,0,-25,25,1.4625561851708289 -coef_arrival_constants_pm_peak_3,0,0,0,0,0,0 -coef_arrival_constants_pm_peak_4,-1.2333276504506303,-0.59626000000000001,0,-25,25,-1.2333276504506303 -coef_departure_constants_am_peak_1,-25,-11.595050000000001,0,-25,25,-25 -coef_departure_constants_am_peak_2,-4.2487039295223656,-9.0051900000000007,0,-25,25,-4.2487039295223656 -coef_departure_constants_am_peak_3,0.75112055157913948,-2.7331500000000002,0,-25,25,0.75112055157913948 -coef_departure_constants_am_peak_4,1.3921313310397618,0.26654,0,-25,25,1.3921313310397618 -coef_departure_constants_early,-24.394585604972157,-14.477080000000001,0,-25,25,-24.394585604972157 -coef_departure_constants_evening,-14.12448484303447,-18.987369999999999,0,-25,25,-14.12448484303447 -coef_departure_constants_late,-19.873640270611908,-20.27807,0,-25,25,-19.873640270611908 -coef_departure_constants_midday_1,0,0,0,0,0,0 -coef_departure_constants_midday_2,-4.3735430875047783,-1.6026,0,-25,25,-4.3735430875047783 -coef_departure_constants_pm_peak,-12.231456579430871,-17.695979999999999,0,-25,25,-12.231456579430871 -coef_destination_in_cbd_duration_shift_effects,0.56926682397665584,0.1067,0,-25,25,0.56926682397665584 -coef_discretionary_tour_duration_lt_2_hours,-0.96979691863694628,-0.69740000000000002,0,-25,25,-0.96979691863694628 -coef_duration_constants_0_to_1_hours,-2.7866437326016174,-2.2282600000000001,0,-25,25,-2.7866437326016174 -coef_duration_constants_11_to_13_hours,-5.6834374392880065,-0.81518999999999997,0,-25,25,-5.6834374392880065 -coef_duration_constants_14_to_18_hours,-2.7347130621577005,-2.7384400000000002,0,-25,25,-2.7347130621577005 -coef_duration_constants_2_to_3_hours,0,0,0,0,0,0 -coef_duration_constants_4_to_5_hours,0.35927958946513583,-0.56174000000000002,0,-25,25,0.35927958946513583 -coef_duration_constants_6_to_7_hours,0.25829995673545386,-0.65547,0,-25,25,0.25829995673545386 -coef_duration_constants_8_to_10_hours,-10.443272918037978,-0.74061999999999995,0,-25,25,-10.443272918037978 -coef_eat_out_tour_departure_shift_effects,-0.026030105628492072,0.075490000000000002,0,-25,25,-0.026030105628492072 -coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect,-1.6735672025262123,-0.2364,0,-25,25,-1.6735672025262123 -coef_free_flow_round_trip_auto_time_shift_effects_duration,0.016957888892283637,0.0031949999999999999,0,-25,25,0.016957888892283637 -coef_maintenance_tour_depart_before_7,1.1216498838609328,-0.88260000000000005,0,-25,25,1.1216498838609328 -coef_maintenance_tour_departure_shift_effects,-0.16045036076756827,-0.1489,0,-25,25,-0.16045036076756827 -coef_maintenance_tour_duration_shift_effects,-0.15774061753063057,-0.083720000000000003,0,-25,25,-0.15774061753063057 -coef_number_of_joint_tours_departure_shift_effects,1.3426208902212988,0.052080000000000001,0,-25,25,1.3426208902212988 -coef_number_of_mandatory_tours_departure_shift_effects,0.073116531424716663,0.046730000000000001,0,-25,25,0.073116531424716663 -coef_school_child_age_16_plus_departure_shift_effects,0.072660000000000002,0.072660000000000002,0,-25,25,0.072660000000000002 -coef_school_child_age_16_plus_duration_shift_effects,0.20949999999999999,0.20949999999999999,0,-25,25,0.20949999999999999 -coef_school_child_age_under_16_departure_shift_effects,0.22437768613209164,0.04657,0,-25,25,0.22437768613209164 -coef_school_child_age_under_16_duration_shift_effects,-0.55690620785460743,0.32719999999999999,0,-25,25,-0.55690620785460743 -coef_school_child_under_16_arrive_after_22,-6.2179802555750401,-1.1799999999999999,0,-25,25,-6.2179802555750401 -coef_shopping_tour_arrive_after_22,-6.8841149173847738,-0.60270000000000001,0,-25,25,-6.8841149173847738 -coef_shopping_tour_depart_before_8,1.6329282274649815,-1.0369999999999999,0,-25,25,1.6329282274649815 -coef_shopping_tour_departure_shift_effects,-0.032901677188934476,-0.060150000000000002,0,-25,25,-0.032901677188934476 -coef_shopping_tour_duration_lt_2_hours,0.069480688387001235,0.51680000000000004,0,-25,25,0.069480688387001235 -coef_shopping_tour_duration_shift_effects,-0.41367749415560207,-0.1208,0,-25,25,-0.41367749415560207 -coef_some_previously_scheduled_tour_begins_in_this_arrival_hour,0.46823426868427825,-0.3992,0,-25,25,0.46823426868427825 -coef_some_previously_scheduled_tour_ends_in_this_departure_hour,0.26003373330967577,-0.45619999999999999,0,-25,25,0.26003373330967577 -coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect,-0.015340339657372392,-0.1731,0,-25,25,-0.015340339657372392 -coef_unavailable,-999,-999,0,-999,-999,-999 -coef_university_student_arrive_after_22,-9.1734571378829219,0.54659999999999997,0,-25,25,-9.1734571378829219 -coef_visit_tour_departure_shift_effects,-0.11236540231411092,0.096879999999999994,0,-25,25,-0.11236540231411092 -coef_visit_tour_duration_shift_effects,-0.13492097024550309,0.1638,0,-25,25,-0.13492097024550309 +param_name,value,best,initvalue,nullvalue +coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction,-0.025656219142801435,-0.025656219142801435,-0.025699999183416367,0 +coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction,-0.025716469680719514,-0.025716469680719514,-0.027340000495314598,0 +coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction,0.008442354676521463,0.008442354676521463,0.0084419995546340942,0 +coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction,-0.05935757810299315,-0.05935757810299315,-0.059300001710653305,0 +coef_adult_with_children_in_hh_arrive_19_21,0.5355161653253353,0.5355161653253353,0.335999995470047,0 +coef_arrival_constants_am_peak,-2.4250190851365487,-2.4250190851365487,-8.7288799285888672,0 +coef_arrival_constants_early,2.2958899169886267,2.2958899169886267,-8.7288799285888672,0 +coef_arrival_constants_evening,-3.3154480276617018,-3.3154480276617018,-2.7489399909973145,0 +coef_arrival_constants_late,-8.3307149468221589,-8.3307149468221589,-4.2425298690795898,0 +coef_arrival_constants_midday_1,0,0,0,0 +coef_arrival_constants_midday_2,1.5294906566988582,1.5294906566988582,1.4080400466918945,0 +coef_arrival_constants_pm_peak_1,1.2175035036665733,1.2175035036665733,1.020359992980957,0 +coef_arrival_constants_pm_peak_2,1.2998241903588883,1.2998241903588883,1.0686299800872803,0 +coef_arrival_constants_pm_peak_3,0,0,0,0 +coef_arrival_constants_pm_peak_4,-0.84944529895620147,-0.84944529895620147,-0.59626001119613647,0 +coef_departure_constants_am_peak_1,-24.483912895120231,-24.483912895120231,-11.595049858093262,0 +coef_departure_constants_am_peak_2,-17.791981333117047,-17.791981333117047,-9.0051898956298828,0 +coef_departure_constants_am_peak_3,-4.1499437678248832,-4.1499437678248832,-2.7331500053405762,0 +coef_departure_constants_am_peak_4,-0.2038777988755586,-0.2038777988755586,0.26653999090194702,0 +coef_departure_constants_early,-24.999999999999986,-24.999999999999986,-14.477080345153809,0 +coef_departure_constants_evening,-24.057955302201297,-24.057955302201297,-18.987369537353516,0 +coef_departure_constants_late,-25,-25,-20.278070449829102,0 +coef_departure_constants_midday_1,0,0,0,0 +coef_departure_constants_midday_2,-2.6945721193468217,-2.6945721193468217,-1.6025999784469604,0 +coef_departure_constants_pm_peak,-22.802101526690983,-22.802101526690983,-17.695980072021484,0 +coef_destination_in_cbd_duration_shift_effects,0.57637590919194726,0.57637590919194726,0.10670000314712524,0 +coef_discretionary_tour_duration_lt_2_hours,-1.2587487442550029,-1.2587487442550029,-0.69739997386932373,0 +coef_duration_constants_0_to_1_hours,-2.7292315354064538,-2.7292315354064538,-2.2282600402832031,0 +coef_duration_constants_11_to_13_hours,-16.641361610345623,-16.641361610345623,-0.81519001722335815,0 +coef_duration_constants_14_to_18_hours,-4.2019174642931754,-4.2019174642931754,-2.7384400367736816,0 +coef_duration_constants_2_to_3_hours,0,0,0,0 +coef_duration_constants_4_to_5_hours,0.041336040196562979,0.041336040196562979,-0.56173998117446899,0 +coef_duration_constants_6_to_7_hours,-0.28010083544612574,-0.28010083544612574,-0.65547001361846924,0 +coef_duration_constants_8_to_10_hours,-11.834841336602297,-11.834841336602297,-0.74062001705169678,0 +coef_eat_out_tour_departure_shift_effects,-0.191471104246424,-0.191471104246424,0.075489997863769531,0 +coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect,-0.65914361514389619,-0.65914361514389619,-0.23639999330043793,0 +coef_free_flow_round_trip_auto_time_shift_effects_duration,0.0103470192509738,0.0103470192509738,0.0031950001139193773,0 +coef_maintenance_tour_depart_before_7,-0.6995036880611385,-0.6995036880611385,-0.88260000944137573,0 +coef_maintenance_tour_departure_shift_effects,-0.51463329667967828,-0.51463329667967828,-0.14890000224113464,0 +coef_maintenance_tour_duration_shift_effects,-0.37483619241205374,-0.37483619241205374,-0.083719998598098755,0 +coef_number_of_joint_tours_departure_shift_effects,0.5518545554827089,0.5518545554827089,0.052080001682043076,0 +coef_number_of_mandatory_tours_departure_shift_effects,0.15108304860381977,0.15108304860381977,0.046730000525712967,0 +coef_school_child_age_16_plus_departure_shift_effects,0.072659999132156372,0.072659999132156372,0.072659999132156372,0 +coef_school_child_age_16_plus_duration_shift_effects,0.20949999988079071,0.20949999988079071,0.20949999988079071,0 +coef_school_child_age_under_16_departure_shift_effects,0.90140346155759687,0.90140346155759687,0.046569999307394028,0 +coef_school_child_age_under_16_duration_shift_effects,-0.36276804513883948,-0.36276804513883948,0.32719999551773071,0 +coef_school_child_under_16_arrive_after_22,-25,-25,-1.1799999475479126,0 +coef_shopping_tour_arrive_after_22,-16.816060937232734,-16.816060937232734,-0.60269999504089355,0 +coef_shopping_tour_depart_before_8,0.8484680406149383,0.8484680406149383,-1.0369999408721924,0 +coef_shopping_tour_departure_shift_effects,-0.35167841899554614,-0.35167841899554614,-0.06015000119805336,0 +coef_shopping_tour_duration_lt_2_hours,0.1873898983230104,0.1873898983230104,0.51679998636245728,0 +coef_shopping_tour_duration_shift_effects,-0.63534186935788817,-0.63534186935788817,-0.12080000340938568,0 +coef_some_previously_scheduled_tour_begins_in_this_arrival_hour,-0.25327854790648219,-0.25327854790648219,-0.39919999241828918,0 +coef_some_previously_scheduled_tour_ends_in_this_departure_hour,-0.35052002043887132,-0.35052002043887132,-0.4562000036239624,0 +coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect,-0.035834399723830755,-0.035834399723830755,-0.17309999465942383,0 +coef_unavailable,-999,-999,-999,0 +coef_university_student_arrive_after_22,-15.517205687701349,-15.517205687701349,0.54659998416900635,0 +coef_visit_tour_departure_shift_effects,-0.34370578081497799,-0.34370578081497799,0.096879996359348297,0 +coef_visit_tour_duration_shift_effects,-0.33210961592070104,-0.33210961592070104,0.16380000114440918,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_mandatory_tour_scheduling_school_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_mandatory_tour_scheduling_school_SLSQP_.csv index 93c03c449c..047fcd6a31 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_mandatory_tour_scheduling_school_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_mandatory_tour_scheduling_school_SLSQP_.csv @@ -1,56 +1,56 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction,11.716776044898809,-0.0030490000000000001,0,-25,25,11.716776044898809 -coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction,-0.58735581754454202,-0.52710000000000001,0,-25,25,-0.58735581754454202 -coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction,9.2169111822551333,0.089749999999999996,0,-25,25,9.2169111822551333 -coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction,-15.186947397585952,-0.44,0,-25,25,-15.186947397585952 -coef_all_adults_ft_worker_duration,0.0083360428258746171,0.10929999999999999,0,-25,25,0.0083360428258746171 -coef_arrival_constants_am_peak,-2.2525597933199202,-2.4287183990000001,0,-25,25,-2.2525597933199202 -coef_arrival_constants_early,-1.0600927435131249,-2.4287183990000001,0,-25,25,-1.0600927435131249 -coef_arrival_constants_evening,-1.024968926440146,-0.87014690400000005,0,-25,25,-1.024968926440146 -coef_arrival_constants_late,-1.3622777646923283,-1.7520004899999999,0,-25,25,-1.3622777646923283 -coef_arrival_constants_midday_1,-1.3329442334964623,-1.237908768,0,-25,25,-1.3329442334964623 -coef_arrival_constants_midday_2,-0.56302790885535348,-0.53976893100000001,0,-25,25,-0.56302790885535348 -coef_arrival_constants_pm_peak_1,0,0,0,0,0,0 -coef_arrival_constants_pm_peak_2,-0.47120087260372584,-0.38916924800000002,0,-25,25,-0.47120087260372584 -coef_arrival_constants_pm_peak_3,-0.2889635829589125,-0.198120349,0,-25,25,-0.2889635829589125 -coef_arrival_constants_pm_peak_4,-0.42904089312882804,-0.25362468399999999,0,-25,25,-0.42904089312882804 -coef_departure_constants_am_peak_1,-1.8402276885639066,-1.6176440560000001,0,-25,25,-1.8402276885639066 -coef_departure_constants_am_peak_2,0,0,0,0,0,0 -coef_departure_constants_am_peak_3,-0.14762834941122654,-0.073826841000000004,0,-25,25,-0.14762834941122654 -coef_departure_constants_am_peak_4,-2.0052907227909373,-2.0805707689999999,0,-25,25,-2.0052907227909373 -coef_departure_constants_early,-3.6385102149182318,-3.8206624040000001,0,-25,25,-3.6385102149182318 -coef_departure_constants_evening,-5.1709311530899091,-5.2302878359999996,0,-25,25,-5.1709311530899091 -coef_departure_constants_late,-25,-11.88604728,0,-25,25,-25 -coef_departure_constants_midday_1,-3.235655391222839,-2.9857394570000002,0,-25,25,-3.235655391222839 -coef_departure_constants_midday_2,-3.7122959166670451,-3.6284346460000001,0,-25,25,-3.7122959166670451 -coef_departure_constants_pm_peak,-2.9909526474284074,-3.1025051499999998,0,-25,25,-2.9909526474284074 -coef_duration_constants_0_to_2_hours,-1.3817519840859342,-1.409955689,0,-25,25,-1.3817519840859342 -coef_duration_constants_10_hours,-0.85439568067710703,-0.90478898299999999,0,-25,25,-0.85439568067710703 -coef_duration_constants_11_hours,-1.0970644700531507,-1.5211626039999999,0,-25,25,-1.0970644700531507 -coef_duration_constants_12_to_13_hours,-2.6774099148644868,-2.4184889169999999,0,-25,25,-2.6774099148644868 -coef_duration_constants_14_to_18_hours,-2.6488356018470931,-2.5031372950000002,0,-25,25,-2.6488356018470931 -coef_duration_constants_3_to_4_hours,-0.56119226026187308,-0.74589325200000001,0,-25,25,-0.56119226026187308 -coef_duration_constants_5_to_6_hours,-0.52869720683509602,-0.56763662199999998,0,-25,25,-0.52869720683509602 -coef_duration_constants_7_to_8_hours,0,0,0,0,0,0 -coef_duration_constants_9_hours,-0.47578654406256893,-0.65080668399999997,0,-25,25,-0.47578654406256893 -coef_first_of_2plus_school_lt_6_hours,0.36465272850981928,1.4870000000000001,0,-25,25,0.36465272850981928 -coef_first_of_2plus_school_tours_departure,-0.28345842741237504,-0.30020000000000002,0,-25,25,-0.28345842741237504 -coef_first_of_2plus_school_tours_duration,-0.0072205064801072029,-0.1593,0,-25,25,-0.0072205064801072029 -coef_ft_worker_departure,0.39710000000000001,0.39710000000000001,0,-25,25,0.39710000000000001 -coef_ft_worker_duration,-0.1908,-0.1908,0,-25,25,-0.1908 -coef_hh_income_early_departure,-12.781415662231149,-0.88370000000000004,0,-25,25,-12.781415662231149 -coef_hh_income_late_arrival,0.13481375603358139,-0.3533,0,-25,25,0.13481375603358139 -coef_mode_choice_logsum,-0.15485890248282916,2.1269999999999998,0,-25,25,-0.15485890248282916 -coef_non_worker_departure,0.55389999999999995,0.55389999999999995,0,-25,25,0.55389999999999995 -coef_previous_tour_begins_this_arrival_hour,-5.5053579900953125,-1.1020000000000001,0,-25,25,-5.5053579900953125 -coef_previous_tour_ends_this_departure_hour,-15.038466619861389,-0.59950000000000003,0,-25,25,-15.038466619861389 -coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours,-24.999999999999979,-16.670000000000002,0,-25,25,-24.999999999999979 -coef_roundtrip_auto_time_to_work,0.0053019952333040361,0.0031949999999999999,0,-25,25,0.0053019952333040361 -coef_school_plus_work_tours_by_student_lt_6_hours,-1.1660913354672906,1.73,0,-25,25,-1.1660913354672906 -coef_school_plus_work_tours_by_worker_lt_6_hours,-0.75409133546729057,2.1419999999999999,0,-25,25,-0.75409133546729057 -coef_student_driver_duration,-0.0068046815074113429,0.034639999999999997,0,-25,25,-0.0068046815074113429 -coef_subsequent_2plus_school_tours_duration,-0.21896654709477803,-0.23380000000000001,0,-25,25,-0.21896654709477803 -coef_subsequent_of_2plus_school_lt_6_hours,24.999999999999982,2.1419999999999999,0,-25,25,24.999999999999982 -coef_subsequent_tour_must_start_after_previous_tour_ends,-100,-100,0,-100,-100,-100 -coef_univ_departure,0.22263900806749343,0.28000000000000003,0,-25,25,0.22263900806749343 -coef_univ_duration,-0.41672805296299825,-0.29070000000000001,0,-25,25,-0.41672805296299825 +param_name,value,best,initvalue,nullvalue +coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction,0.080775447776812753,0.080774252667694169,-0.0030489999335259199,0 +coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction,-0.51836135663447769,-0.51836174434913773,-0.52710002660751343,0 +coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction,0.73433095650246494,0.73432154552615458,0.089749999344348907,0 +coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction,-0.99378159059164084,-0.99377515349106949,-0.43999999761581421,0 +coef_all_adults_ft_worker_duration,0.033395472694728347,0.033395444616199747,0.10930000245571136,0 +coef_arrival_constants_am_peak,-2.1992574993931737,-2.1992595446798857,-2.4287183284759521,0 +coef_arrival_constants_early,-1.0152816371137836,-1.0152823898389056,-2.4287183284759521,0 +coef_arrival_constants_evening,-1.089014071549075,-1.089012444258362,-0.87014693021774292,0 +coef_arrival_constants_late,-1.4094125261836428,-1.4094104317113427,-1.7520004510879517,0 +coef_arrival_constants_midday_1,-1.3102781509339738,-1.3102792663184144,-1.2379087209701538,0 +coef_arrival_constants_midday_2,-0.5570164575887101,-0.55701686342809786,-0.53976893424987793,0 +coef_arrival_constants_pm_peak_1,0,0,0,0 +coef_arrival_constants_pm_peak_2,-0.48446733503368733,-0.48446736247771904,-0.38916924595832825,0 +coef_arrival_constants_pm_peak_3,-0.31506510944596333,-0.31506390971297477,-0.1981203556060791,0 +coef_arrival_constants_pm_peak_4,-0.4718642141386703,-0.4718634888383082,-0.25362467765808105,0 +coef_departure_constants_am_peak_1,-1.8553572932845479,-1.8553571741469013,-1.6176440715789795,0 +coef_departure_constants_am_peak_2,0,0,0,0 +coef_departure_constants_am_peak_3,-0.14106707640383398,-0.14106757305590037,-0.07382684201002121,0 +coef_departure_constants_am_peak_4,-1.9882913840565575,-1.988292157571423,-2.0805706977844238,0 +coef_departure_constants_early,-3.6786226227417624,-3.6786220135061134,-3.8206624984741211,0 +coef_departure_constants_evening,-5.2925208449121817,-5.2925240767147788,-5.230288028717041,0 +coef_departure_constants_late,-11.916832030849566,-11.916831561227097,-11.88604736328125,0 +coef_departure_constants_midday_1,-3.2113751054704132,-3.2113771777110944,-2.9857394695281982,0 +coef_departure_constants_midday_2,-3.6981526513555871,-3.6981547479895061,-3.6284346580505371,0 +coef_departure_constants_pm_peak,-2.9973467155658162,-2.9973494814295885,-3.1025052070617676,0 +coef_duration_constants_0_to_2_hours,-1.3996475888297963,-1.3996458652500943,-1.4099557399749756,0 +coef_duration_constants_10_hours,-0.82164737941042931,-0.82164784328828933,-0.90478897094726562,0 +coef_duration_constants_11_hours,-1.0464064831927971,-1.0464075406530777,-1.5211626291275024,0 +coef_duration_constants_12_to_13_hours,-2.5901815246633957,-2.5901814921437252,-2.4184889793395996,0 +coef_duration_constants_14_to_18_hours,-2.5870585605577858,-2.5870607126569682,-2.5031373500823975,0 +coef_duration_constants_3_to_4_hours,-0.56514744374131198,-0.56514595486014574,-0.74589323997497559,0 +coef_duration_constants_5_to_6_hours,-0.53548913813929444,-0.53548808091419775,-0.56763660907745361,0 +coef_duration_constants_7_to_8_hours,0,0,0,0 +coef_duration_constants_9_hours,-0.45285392800018198,-0.4528543455236822,-0.65080666542053223,0 +coef_first_of_2plus_school_lt_6_hours,0.024871811138907744,0.024881803705537723,1.4869999885559082,0 +coef_first_of_2plus_school_tours_departure,-0.29460766022668305,-0.29460728950989984,-0.30019998550415039,0 +coef_first_of_2plus_school_tours_duration,-0.10138864589931282,-0.10138705511807192,-0.15929999947547913,0 +coef_ft_worker_departure,0.39710000157356262,0.39710000157356262,0.39710000157356262,0 +coef_ft_worker_duration,-0.19079999625682831,-0.19079999625682831,-0.19079999625682831,0 +coef_hh_income_early_departure,-2.4518333628592055,-2.4518122384333916,-0.88370001316070557,0 +coef_hh_income_late_arrival,0.0099574185770053714,0.0099600258474820229,-0.35330000519752502,0 +coef_mode_choice_logsum,0.10646038792012041,0.10645974892637354,2.127000093460083,0 +coef_non_worker_departure,0.55390000343322754,0.55390000343322754,0.55390000343322754,0 +coef_previous_tour_begins_this_arrival_hour,-1.1044099604419229,-1.1044099196469588,-1.1019999980926514,0 +coef_previous_tour_ends_this_departure_hour,-0.98618911184573188,-0.98618197798375551,-0.59950000047683716,0 +coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours,-16.801395249039167,-16.801393279303245,-16.670000076293945,0 +coef_roundtrip_auto_time_to_work,0.0052250922026635376,0.0052251100813601051,0.0031950001139193773,0 +coef_school_plus_work_tours_by_student_lt_6_hours,1.7724913916824447,1.7724908031221758,1.7300000190734863,0 +coef_school_plus_work_tours_by_worker_lt_6_hours,2.1844913325546376,2.1844907439943686,2.1419999599456787,0 +coef_student_driver_duration,-0.0049771487710083039,-0.0049771201652761641,0.034639999270439148,0 +coef_subsequent_2plus_school_tours_duration,-0.22458834432940281,-0.22458959182491992,-0.23379999399185181,0 +coef_subsequent_of_2plus_school_lt_6_hours,2.8438198153956726,2.8438099345673602,2.1419999599456787,0 +coef_subsequent_tour_must_start_after_previous_tour_ends,-100,-100,-100,0 +coef_univ_departure,0.23875445577073184,0.23875440862293787,0.2800000011920929,0 +coef_univ_duration,-0.40329629710371528,-0.40329638768202386,-0.29069998860359192,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_mandatory_tour_scheduling_work_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_mandatory_tour_scheduling_work_SLSQP_.csv index 9465192ef9..70e5cc97c5 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_mandatory_tour_scheduling_work_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_mandatory_tour_scheduling_work_SLSQP_.csv @@ -1,64 +1,64 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction,25,0.36270000000000002,0,-25,25,25 -coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction,0.67172411345437255,-0.1012,0,-25,25,0.67172411345437255 -coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction,-0.2705642011106818,0.17710000000000001,0,-25,25,-0.2705642011106818 -coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction,2.3126663890343506,-0.21229999999999999,0,-25,25,2.3126663890343506 -coef_arrival_constants_am_peak,-2.5608583720316691,-1.854520626,0,-25,25,-2.5608583720316691 -coef_arrival_constants_early,0,0,0,0,0,0 -coef_arrival_constants_evening,-0.11313543070951976,0.103566251,0,-25,25,-0.11313543070951976 -coef_arrival_constants_late,-1.2047708015331426,-0.96595733900000003,0,-25,25,-1.2047708015331426 -coef_arrival_constants_midday_1,-0.4666152062959858,-0.49597203699999998,0,-25,25,-0.4666152062959858 -coef_arrival_constants_midday_2,-0.37297675905912303,-0.37855408099999999,0,-25,25,-0.37297675905912303 -coef_arrival_constants_pm_peak_1,0,0,0,0,0,0 -coef_arrival_constants_pm_peak_2,0.20356469833981647,0.27608389999999999,0,-25,25,0.20356469833981647 -coef_arrival_constants_pm_peak_3,0.55940049285496218,0.699587132,0,-25,25,0.55940049285496218 -coef_arrival_constants_pm_peak_4,0.69955932869966053,0.79928937700000002,0,-25,25,0.69955932869966053 -coef_departure_constants_am_peak_1,-0.65012576984935755,-0.61618090599999997,0,-25,25,-0.65012576984935755 -coef_departure_constants_am_peak_2,0,0,0,0,0,0 -coef_departure_constants_am_peak_3,-0.32740035887947389,-0.254714726,0,-25,25,-0.32740035887947389 -coef_departure_constants_am_peak_4,-1.2190845361495699,-1.2513460240000001,0,-25,25,-1.2190845361495699 -coef_departure_constants_early,-0.92470832388900248,-0.95272526999999996,0,-25,25,-0.92470832388900248 -coef_departure_constants_evening,-1.8906229365299492,-1.610513243,0,-25,25,-1.8906229365299492 -coef_departure_constants_late,-2.9986176789858154,-2.8834152230000001,0,-25,25,-2.9986176789858154 -coef_departure_constants_midday_1,-1.8241536006077277,-1.7058689920000001,0,-25,25,-1.8241536006077277 -coef_departure_constants_midday_2,-1.8783523324805591,-1.6935705830000001,0,-25,25,-1.8783523324805591 -coef_departure_constants_pm_peak,-1.6396663560770837,-1.4399919619999999,0,-25,25,-1.6396663560770837 -coef_destination_in_cbd_departure_shift_effects,0.04109611455586798,0.047169999999999997,0,-25,25,0.04109611455586798 -coef_destination_in_cbd_duration_shift_effects,0.10130692865710192,0.086790000000000006,0,-25,25,0.10130692865710192 -coef_destination_in_cbd_early_departure_interaction,-0.38984353468069122,-0.45660000000000001,0,-25,25,-0.38984353468069122 -coef_destination_in_cbd_late_arrival_interaction,-0.27055298689359897,-0.2334,0,-25,25,-0.27055298689359897 -coef_duration_constants_0_to_2_hours,-2.1189652588431978,-2.5282663900000002,0,-25,25,-2.1189652588431978 -coef_duration_constants_10_hours,0,0,0,0,0,0 -coef_duration_constants_11_hours,-0.35443610468830039,-0.34779539100000001,0,-25,25,-0.35443610468830039 -coef_duration_constants_12_to_13_hours,-1.1153352032051054,-1.0082223459999999,0,-25,25,-1.1153352032051054 -coef_duration_constants_14_to_18_hours,-1.8418267064323726,-1.701858847,0,-25,25,-1.8418267064323726 -coef_duration_constants_3_to_4_hours,-0.63573505547017051,-0.91897445700000002,0,-25,25,-0.63573505547017051 -coef_duration_constants_5_to_6_hours,-0.35577473775309831,-0.71855028799999998,0,-25,25,-0.35577473775309831 -coef_duration_constants_7_to_8_hours,-0.033757586303302736,-0.139623566,0,-25,25,-0.033757586303302736 -coef_duration_constants_9_hours,0.12934760728519379,0.055706243000000003,0,-25,25,0.12934760728519379 -coef_first_of_2plus_work_tours_departure_shift_effects,-0.27106753260112321,-0.30330000000000001,0,-25,25,-0.27106753260112321 -coef_first_of_2plus_work_tours_duration_lt_8_hrs,1.8948098471889567,1.98,0,-25,25,1.8948098471889567 -coef_first_of_2plus_work_tours_duration_shift_effects,-0.29362220747793244,-0.18609999999999999,0,-25,25,-0.29362220747793244 -coef_free_flow_round_trip_auto_time_shift_effects_departure,0.00054374628944530747,-0.00114,0,-25,25,0.00054374628944530747 -coef_free_flow_round_trip_auto_time_shift_effects_duration,0.0040398779948456849,0.0022100000000000002,0,-25,25,0.0040398779948456849 -coef_full_time_worker_10_to_12_departure_interaction,-0.66614758973349719,-0.51819999999999999,0,-25,25,-0.66614758973349719 -coef_full_time_worker_duration_lt_9_hours_interaction,-1.3694302807642016,-1.2569999999999999,0,-25,25,-1.3694302807642016 -coef_household_income_departure_shift_effects,0.00011200417166098945,0.00020799999999999999,0,-25,25,0.00011200417166098945 -coef_household_income_early_departure_interaction,-0.57489507784478577,-0.4854,0,-25,25,-0.57489507784478577 -coef_household_income_late_arrival_interaction,0.036426020508396037,-0.38390000000000002,0,-25,25,0.036426020508396037 -coef_mode_choice_logsum,0.20613495321472861,1.0269999999999999,0,-25,25,0.20613495321472861 -coef_non_working_adult_duration_shift_effects,-0.1207,-0.1207,0,-25,25,-0.1207 -coef_part_time_worker_13_to_15_arrival_interaction,0.33677938786979689,0.54330000000000001,0,-25,25,0.33677938786979689 -coef_part_time_worker_departure_shift_effects,0.089714285580281661,0.067360000000000003,0,-25,25,0.089714285580281661 -coef_previously_scheduled_tour_begins_in_this_arrival_hour,-6.6033938783133914,-1.3340000000000001,0,-25,25,-6.6033938783133914 -coef_previously_scheduled_tour_ends_in_this_departure_hour,2.4216789099176217,-0.89349999999999996,0,-25,25,2.4216789099176217 -coef_remaining_tours_to_be_scheduled_div_number_of_unscheduled_hours,-6.3408961734536069,-18.68,0,-25,25,-6.3408961734536069 -coef_rural_household_early_departure_interaction,0.40389999999999998,0.40389999999999998,0,-25,25,0.40389999999999998 -coef_rural_household_late_arrival_interaction,-0.34510000000000002,-0.34510000000000002,0,-25,25,-0.34510000000000002 -coef_subsequent_2plus_work_departure_tours_shift_effects,0.015346535529312815,-0.53810000000000002,0,-25,25,0.015346535529312815 -coef_subsequent_2plus_work_duration_tours_shift_effects,-0.12773109887960765,-0.31740000000000002,0,-25,25,-0.12773109887960765 -coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs,3.5917959509926001,2.5819999999999999,0,-25,25,3.5917959509926001 -coef_subsequent_tour_must_start_after_previous_tour_ends,-100,-100,0,-100,-100,-100 -coef_tours_by_student_duration_lt_8_hrs,14.705420185896203,2.5819999999999999,0,-25,25,14.705420185896203 -coef_tours_by_worker_duration_lt_8_hrs,13.036020185896209,0.91259999999999997,0,-25,25,13.036020185896209 -coef_university_student_departure_shift_effects,0.052139288632078368,0.05747,0,-25,25,0.052139288632078368 +param_name,value,best,initvalue,nullvalue +coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction,0.61251353990327295,0.61251327841360381,0.36269998550415039,0 +coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction,-0.48096392277398275,-0.48096399411879609,-0.10119999945163727,0 +coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction,-0.2616069716319126,-0.26160684847759125,0.17710000276565552,0 +coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction,-0.21226499679315533,-0.2122651617637292,-0.21230000257492065,0 +coef_arrival_constants_am_peak,-2.5606473297230243,-2.5606476523528108,-1.8545206785202026,0 +coef_arrival_constants_early,0,0,0,0 +coef_arrival_constants_evening,-0.052167725404331296,-0.052167735953000123,0.1035662516951561,0 +coef_arrival_constants_late,-1.1308494423719302,-1.1308494377605862,-0.96595734357833862,0 +coef_arrival_constants_midday_1,-0.49891346385413454,-0.49891340446037452,-0.49597203731536865,0 +coef_arrival_constants_midday_2,-0.41039411498088946,-0.41039409639542923,-0.3785540759563446,0 +coef_arrival_constants_pm_peak_1,0,0,0,0 +coef_arrival_constants_pm_peak_2,0.19372908430399155,0.19372906136658175,0.27608388662338257,0 +coef_arrival_constants_pm_peak_3,0.56028646263237181,0.5602864708684514,0.69958710670471191,0 +coef_arrival_constants_pm_peak_4,0.71571247641605751,0.71571248954657329,0.79928940534591675,0 +coef_departure_constants_am_peak_1,-0.64620733049904744,-0.6462073659079336,-0.6161808967590332,0 +coef_departure_constants_am_peak_2,0,0,0,0 +coef_departure_constants_am_peak_3,-0.32992168661687343,-0.32992174133643332,-0.2547147274017334,0 +coef_departure_constants_am_peak_4,-1.2230313612788632,-1.2230313737462095,-1.2513459920883179,0 +coef_departure_constants_early,-0.91653242223268816,-0.91653247537180627,-0.95272529125213623,0 +coef_departure_constants_evening,-1.5545124755865074,-1.5545123072441225,-1.6105132102966309,0 +coef_departure_constants_late,-3.4650976197335996,-3.4650970444155127,-2.8834152221679688,0 +coef_departure_constants_midday_1,-1.8459227529362676,-1.845922814199904,-1.7058689594268799,0 +coef_departure_constants_midday_2,-1.872714720755712,-1.8727145745963636,-1.693570613861084,0 +coef_departure_constants_pm_peak,-1.5304306861299761,-1.5304305915064496,-1.4399919509887695,0 +coef_destination_in_cbd_departure_shift_effects,0.046972898038599296,0.046972900170898703,0.047169998288154602,0 +coef_destination_in_cbd_duration_shift_effects,0.10546600473625205,0.10546600158406226,0.086790002882480621,0 +coef_destination_in_cbd_early_departure_interaction,-0.36454380057515523,-0.36454382109906797,-0.45660001039505005,0 +coef_destination_in_cbd_late_arrival_interaction,-0.34125580756261459,-0.34125584021066124,-0.23340000212192535,0 +coef_duration_constants_0_to_2_hours,-2.3611872557258775,-2.3611872136185283,-2.528266429901123,0 +coef_duration_constants_10_hours,0,0,0,0 +coef_duration_constants_11_hours,-0.36305106792718905,-0.36305106353810024,-0.34779539704322815,0 +coef_duration_constants_12_to_13_hours,-1.1336847773846157,-1.1336846557009517,-1.0082223415374756,0 +coef_duration_constants_14_to_18_hours,-1.846775754300668,-1.8467757187472769,-1.7018588781356812,0 +coef_duration_constants_3_to_4_hours,-0.69884369798611612,-0.69884383804256189,-0.91897445917129517,0 +coef_duration_constants_5_to_6_hours,-0.36088550481193393,-0.36088561328123253,-0.71855026483535767,0 +coef_duration_constants_7_to_8_hours,-0.034562406928364778,-0.03456241250333917,-0.13962356746196747,0 +coef_duration_constants_9_hours,0.12410673449583931,0.12410671848676948,0.055706243962049484,0 +coef_first_of_2plus_work_tours_departure_shift_effects,-0.27939395433691766,-0.27939398231314772,-0.30329999327659607,0 +coef_first_of_2plus_work_tours_duration_lt_8_hrs,1.6819917313175938,1.681991727718217,1.9800000190734863,0 +coef_first_of_2plus_work_tours_duration_shift_effects,-0.26704509800964044,-0.26704506536823513,-0.18610000610351562,0 +coef_free_flow_round_trip_auto_time_shift_effects_departure,-4.6712935036587893e-05,-4.6713265092855231e-05,-0.0011399999493733048,0 +coef_free_flow_round_trip_auto_time_shift_effects_duration,0.0034709225619443279,0.0034709219570404487,0.0022100000642240047,0 +coef_full_time_worker_10_to_12_departure_interaction,-0.67084155893679287,-0.67084150978347679,-0.51819998025894165,0 +coef_full_time_worker_duration_lt_9_hours_interaction,-1.3707861942780288,-1.3707861874425684,-1.2569999694824219,0 +coef_household_income_departure_shift_effects,9.8289823547548591e-05,9.8289830800329784e-05,0.00020799999765586108,0 +coef_household_income_early_departure_interaction,-0.59011172274320045,-0.59011172534232015,-0.48539999127388,0 +coef_household_income_late_arrival_interaction,-0.018847335744915452,-0.018847292627549972,-0.383899986743927,0 +coef_mode_choice_logsum,0.41216509072053042,0.41216516341709108,1.0269999504089355,0 +coef_non_working_adult_duration_shift_effects,-0.12070000171661377,-0.12070000171661377,-0.12070000171661377,0 +coef_part_time_worker_13_to_15_arrival_interaction,0.32725200921090258,0.32725199183573034,0.54329997301101685,0 +coef_part_time_worker_departure_shift_effects,0.089866833957687201,0.089866835119917624,0.067359998822212219,0 +coef_previously_scheduled_tour_begins_in_this_arrival_hour,-1.3452365484106898,-1.3452365345169786,-1.3339999914169312,0 +coef_previously_scheduled_tour_ends_in_this_departure_hour,-0.62131382592128181,-0.62131390854231106,-0.89349997043609619,0 +coef_remaining_tours_to_be_scheduled_div_number_of_unscheduled_hours,-18.639061018727794,-18.639061062575436,-18.680000305175781,0 +coef_rural_household_early_departure_interaction,0.40389999747276306,0.40389999747276306,0.40389999747276306,0 +coef_rural_household_late_arrival_interaction,-0.34509998559951782,-0.34509998559951782,-0.34509998559951782,0 +coef_subsequent_2plus_work_departure_tours_shift_effects,-0.3844333665111534,-0.38443334417322472,-0.53810000419616699,0 +coef_subsequent_2plus_work_duration_tours_shift_effects,-0.38214881037696108,-0.38214876273993459,-0.3174000084400177,0 +coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs,1.2383538709437807,1.2383542865170418,2.5820000171661377,0 +coef_subsequent_tour_must_start_after_previous_tour_ends,-100,-100,-100,0 +coef_tours_by_student_duration_lt_8_hrs,2.6806620027310135,2.6806618957074346,2.5820000171661377,0 +coef_tours_by_worker_duration_lt_8_hrs,1.0112619663960221,1.0112618593724432,0.91259998083114624,0 +coef_university_student_departure_shift_effects,0.068330955102533286,0.068330906364886979,0.05747000128030777,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_non_mandatory_tour_scheduling_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_non_mandatory_tour_scheduling_SLSQP_.csv index 68cc071e89..3c8980345c 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_non_mandatory_tour_scheduling_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_scheduling_model_non_mandatory_tour_scheduling_SLSQP_.csv @@ -1,90 +1,90 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction,0.4470328861441506,-0.025700000000000001,0,-25,25,0.4470328861441506 -coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction,0.56540266502429914,-0.02734,0,-25,25,0.56540266502429914 -coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction,1.0259323894447316,0.0084419999999999999,0,-25,25,1.0259323894447316 -coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction,0.39614317482379957,-0.059299999999999999,0,-25,25,0.39614317482379957 -coef_adult_with_children_in_hh_arrive_19_21,0.31331407963369601,0.33600000000000002,0,-25,25,0.31331407963369601 -coef_arrival_constants_am_peak,0.29950075228772494,-1.814822602,0,-25,25,0.29950075228772494 -coef_arrival_constants_early,2.725267289110473,-0.051990748000000003,0,-25,25,2.725267289110473 -coef_arrival_constants_evening,0,0,0,0,0,0 -coef_arrival_constants_late,-1.1446323020070934,-0.86667131500000005,0,-25,25,-1.1446323020070934 -coef_arrival_constants_midday_1,1.3878018540712422,0.00037150099999999999,0,-25,25,1.3878018540712422 -coef_arrival_constants_midday_2,1.5044255895039795,0.53211603100000004,0,-25,25,1.5044255895039795 -coef_arrival_constants_pm_peak_1,1.3575212925702953,0.62848156700000002,0,-25,25,1.3575212925702953 -coef_arrival_constants_pm_peak_2,1.5579462028570845,0.65052141600000002,0,-25,25,1.5579462028570845 -coef_arrival_constants_pm_peak_3,1.0806181769202525,0.40289440599999998,0,-25,25,1.0806181769202525 -coef_arrival_constants_pm_peak_4,0.69735759210419612,0.154213293,0,-25,25,0.69735759210419612 -coef_departure_constants_am_peak_1,-0.52735012006812276,-0.65416357300000005,0,-25,25,-0.52735012006812276 -coef_departure_constants_am_peak_2,1.1919565496484956,0.554282571,0,-25,25,1.1919565496484956 -coef_departure_constants_am_peak_3,1.4522880996476126,1.0505610869999999,0,-25,25,1.4522880996476126 -coef_departure_constants_am_peak_4,1.5114204226663379,0.97156822799999998,0,-25,25,1.5114204226663379 -coef_departure_constants_early,-0.92104869293940328,-1.7401356610000001,0,-25,25,-0.92104869293940328 -coef_departure_constants_evening,-1.892558890126933,-1.856475096,0,-25,25,-1.892558890126933 -coef_departure_constants_late,-5.6265216713840269,-8.2288801409999994,0,-25,25,-5.6265216713840269 -coef_departure_constants_midday_1,1.3642337556324493,0.88199198599999995,0,-25,25,1.3642337556324493 -coef_departure_constants_midday_2,0.64556751877721019,0.411103634,0,-25,25,0.64556751877721019 -coef_departure_constants_pm_peak,0,0,0,0,0,0 -coef_destination_in_cbd_duration_shift_effects,0.11545735776937631,0.1067,0,-25,25,0.11545735776937631 -coef_discretionary_tour_duration_lt_2_hours,-0.28570443543294716,-0.69740000000000002,0,-25,25,-0.28570443543294716 -coef_duration_constants_0_to_1_hours,0,0,0,0,0,0 -coef_duration_constants_11_to_13_hours,-1.0074136237311473,-0.955635554,0,-25,25,-1.0074136237311473 -coef_duration_constants_14_to_18_hours,-2.9449650044604194,-1.042580879,0,-25,25,-2.9449650044604194 -coef_duration_constants_2_to_3_hours,0.3987726313758776,0.051385565000000001,0,-25,25,0.3987726313758776 -coef_duration_constants_4_to_5_hours,-0.27952507767146284,-0.59395132100000003,0,-25,25,-0.27952507767146284 -coef_duration_constants_6_to_7_hours,-0.65619904538586438,-0.95115532800000002,0,-25,25,-0.65619904538586438 -coef_duration_constants_8_to_10_hours,-0.62326492676484069,-0.828108399,0,-25,25,-0.62326492676484069 -coef_eat_out_tour_departure_shift_effects,0.10408922995281709,0.075490000000000002,0,-25,25,0.10408922995281709 -coef_escort_tour_arrival_constants_am_peak,0,0,0,0,0,0 -coef_escort_tour_arrival_constants_early,0,0,0,0,0,0 -coef_escort_tour_arrival_constants_evening,-0.8931637699400693,-0.53691872799999996,0,-25,25,-0.8931637699400693 -coef_escort_tour_arrival_constants_late,-1.1770797692787565,-1.008290213,0,-25,25,-1.1770797692787565 -coef_escort_tour_arrival_constants_midday_1,0,0,0,0,0,0 -coef_escort_tour_arrival_constants_midday_2,0,0,0,0,0,0 -coef_escort_tour_arrival_constants_pm_peak_1,0,0,0,0,0,0 -coef_escort_tour_arrival_constants_pm_peak_2,0,0,0,0,0,0 -coef_escort_tour_arrival_constants_pm_peak_3,0,0,0,0,0,0 -coef_escort_tour_arrival_constants_pm_peak_4,0,0,0,0,0,0 -coef_escort_tour_departure_constants_am_peak_1,0.48291466233476604,-1.1123577529999999,0,-25,25,0.48291466233476604 -coef_escort_tour_departure_constants_am_peak_2,2.0132225505169186,0.69878818499999995,0,-25,25,2.0132225505169186 -coef_escort_tour_departure_constants_am_peak_3,2.1327074544894873,1.1962688130000001,0,-25,25,2.1327074544894873 -coef_escort_tour_departure_constants_am_peak_4,0.29911257358855436,-0.22525822100000001,0,-25,25,0.29911257358855436 -coef_escort_tour_departure_constants_early,-0.5151665525123571,-1.7401356610000001,0,-25,25,-0.5151665525123571 -coef_escort_tour_departure_constants_evening,-4.7638859598327503,-3.9487328110000002,0,-25,25,-4.7638859598327503 -coef_escort_tour_departure_constants_late,-6.5766274559402813,-8.2288801409999994,0,-25,25,-6.5766274559402813 -coef_escort_tour_departure_constants_midday_1,0.64080123578544568,0.028662017000000001,0,-25,25,0.64080123578544568 -coef_escort_tour_departure_constants_midday_2,0,0,0,0,0,0 -coef_escort_tour_departure_constants_pm_peak,-1.78947739154685,-1.180140161,0,-25,25,-1.78947739154685 -coef_escort_tour_duration_constants_0_to_1_hours,0,0,0,0,0,0 -coef_escort_tour_duration_constants_11_to_13_hours,-6.4203324936004007,-2.9743649759999999,0,-25,25,-6.4203324936004007 -coef_escort_tour_duration_constants_14_to_18_hours,-9.2410499900666672,-2.5074471460000001,0,-25,25,-9.2410499900666672 -coef_escort_tour_duration_constants_2_to_3_hours,-2.600430326093385,-2.0420138969999999,0,-25,25,-2.600430326093385 -coef_escort_tour_duration_constants_4_to_5_hours,-3.5279045037998431,-2.880293896,0,-25,25,-3.5279045037998431 -coef_escort_tour_duration_constants_6_to_7_hours,-3.9930263301758195,-2.9735337309999998,0,-25,25,-3.9930263301758195 -coef_escort_tour_duration_constants_8_to_10_hours,-5.1822459061747068,-3.0202137580000001,0,-25,25,-5.1822459061747068 -coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect,-0.30486234400858059,-0.2364,0,-25,25,-0.30486234400858059 -coef_free_flow_round_trip_auto_time_shift_effects_duration,0.0050429319781780269,0.0047410000000000004,0,-25,25,0.0050429319781780269 -coef_maintenance_tour_depart_before_7,0.052350894248540496,-0.88260000000000005,0,-25,25,0.052350894248540496 -coef_maintenance_tour_departure_shift_effects,-0.041432645424667555,-0.1489,0,-25,25,-0.041432645424667555 -coef_maintenance_tour_duration_shift_effects,-0.11717847942290449,-0.083720000000000003,0,-25,25,-0.11717847942290449 -coef_number_of_escort_tours_departure_shift_effects,0.1003621581289256,0.020129999999999999,0,-25,25,0.1003621581289256 -coef_number_of_individual_non_mandatory_tours_excluding_escort_departure_shift_effects,0.098215723941853808,0.038960000000000002,0,-25,25,0.098215723941853808 -coef_number_of_joint_tours_departure_shift_effects,0.12273335177942903,0.052080000000000001,0,-25,25,0.12273335177942903 -coef_number_of_mandatory_tours_departure_shift_effects,0.1726876041064854,0.046730000000000001,0,-25,25,0.1726876041064854 -coef_ratio_of_individual_non_mandatory_tours_to_be_scheduled_to_number_of_unscheduled_hours,5.7502384461866223,-13.630000000000001,0,-25,25,5.7502384461866223 -coef_school_child_age_16_plus_departure_shift_effects,0.002334001767561128,0.072660000000000002,0,-25,25,0.002334001767561128 -coef_school_child_age_16_plus_duration_shift_effects,0.30512330091593426,0.20949999999999999,0,-25,25,0.30512330091593426 -coef_school_child_age_under_16_departure_shift_effects,0.1028104094868405,0.04657,0,-25,25,0.1028104094868405 -coef_school_child_age_under_16_duration_shift_effects,0.33667040040989843,0.32719999999999999,0,-25,25,0.33667040040989843 -coef_school_child_under_16_arrive_after_22,-0.29870062575080597,-1.1799999999999999,0,-25,25,-0.29870062575080597 -coef_shopping_tour_arrive_after_22,-2.4414941640980703,-0.60270000000000001,0,-25,25,-2.4414941640980703 -coef_shopping_tour_depart_before_8,-0.84790437236499061,-1.0369999999999999,0,-25,25,-0.84790437236499061 -coef_shopping_tour_departure_shift_effects,0.0090862416686240035,-0.060150000000000002,0,-25,25,0.0090862416686240035 -coef_shopping_tour_duration_lt_2_hours,0.912982413595951,0.51680000000000004,0,-25,25,0.912982413595951 -coef_shopping_tour_duration_shift_effects,-0.08012681553606732,-0.1208,0,-25,25,-0.08012681553606732 -coef_some_previously_scheduled_tour_begins_in_this_arrival_hour,-0.004765610611209883,-0.3992,0,-25,25,-0.004765610611209883 -coef_some_previously_scheduled_tour_ends_in_this_departure_hour,-0.28646699211356075,-0.45619999999999999,0,-25,25,-0.28646699211356075 -coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect,-0.10477927540016083,-0.1731,0,-25,25,-0.10477927540016083 -coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends,-999,-999,0,-999,-999,-999 -coef_university_student_arrive_after_22,-0.4840281170137713,0.54659999999999997,0,-25,25,-0.4840281170137713 -coef_visit_tour_departure_shift_effects,0.1674492151765343,0.096879999999999994,0,-25,25,0.1674492151765343 -coef_visit_tour_duration_shift_effects,0.15890840399796446,0.1638,0,-25,25,0.15890840399796446 +param_name,value,best,initvalue,nullvalue +coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction,-0.37873530652415688,-0.37876029334525779,-0.025699999183416367,0 +coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction,-0.12409933488783795,-0.12412525709082863,-0.027340000495314598,0 +coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction,0.16013173725389518,0.16011972294122639,0.0084419995546340942,0 +coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction,-0.057675497288593967,-0.057678856669874018,-0.059300001710653305,0 +coef_adult_with_children_in_hh_arrive_19_21,0.26358073098680268,0.26357366595375664,0.335999995470047,0 +coef_arrival_constants_am_peak,-1.618479614096983,-1.6184779227729857,-1.8148225545883179,0 +coef_arrival_constants_early,0.012632463274022693,0.012638163573529756,-0.051990747451782227,0 +coef_arrival_constants_evening,0,0,0,0 +coef_arrival_constants_late,-0.77439458777380288,-0.77440113819912593,-0.86667132377624512,0 +coef_arrival_constants_midday_1,0.16302672327058698,0.16302166341062885,0.0003715009952429682,0 +coef_arrival_constants_midday_2,0.60562412779331609,0.60561823037837537,0.53211605548858643,0 +coef_arrival_constants_pm_peak_1,0.66305388881325122,0.66304628483786687,0.62848156690597534,0 +coef_arrival_constants_pm_peak_2,0.9403736312996136,0.94036844970191236,0.65052139759063721,0 +coef_arrival_constants_pm_peak_3,0.57943549534338168,0.57943058291341509,0.40289440751075745,0 +coef_arrival_constants_pm_peak_4,0.32882206659224378,0.32881862675984186,0.15421329438686371,0 +coef_departure_constants_am_peak_1,-0.8444053940276266,-0.8443867382251623,-0.65416359901428223,0 +coef_departure_constants_am_peak_2,0.61095352829384308,0.6109683536427154,0.554282546043396,0 +coef_departure_constants_am_peak_3,0.89783495233382704,0.89783925656317809,1.0505610704421997,0 +coef_departure_constants_am_peak_4,0.97678705420018241,0.97679068633385335,0.97156822681427002,0 +coef_departure_constants_early,-1.5655173152332842,-1.5655400591434045,-1.740135669708252,0 +coef_departure_constants_evening,-1.6745782734879573,-1.6745908894768251,-1.8564751148223877,0 +coef_departure_constants_late,-5.8677842794743897,-5.867810078393469,-8.2288799285888672,0 +coef_departure_constants_midday_1,0.90219691225188225,0.90220256652108655,0.88199198246002197,0 +coef_departure_constants_midday_2,0.33966490947802791,0.339668134288378,0.41110363602638245,0 +coef_departure_constants_pm_peak,0,0,0,0 +coef_destination_in_cbd_duration_shift_effects,0.12481964214980576,0.12482003975020485,0.10670000314712524,0 +coef_discretionary_tour_duration_lt_2_hours,-0.49111660197637685,-0.49110487979747403,-0.69739997386932373,0 +coef_duration_constants_0_to_1_hours,0,0,0,0 +coef_duration_constants_11_to_13_hours,-0.71826442870005769,-0.71826950153593283,-0.95563554763793945,0 +coef_duration_constants_14_to_18_hours,-1.3448264303153219,-1.3448138847159017,-1.0425808429718018,0 +coef_duration_constants_2_to_3_hours,0.18806168958819869,0.18807127149669869,0.051385566592216492,0 +coef_duration_constants_4_to_5_hours,-0.47110934268158594,-0.4711057056246632,-0.59395134449005127,0 +coef_duration_constants_6_to_7_hours,-0.82518931580282029,-0.82518905004791432,-0.95115530490875244,0 +coef_duration_constants_8_to_10_hours,-0.69268933767290863,-0.6927031726601327,-0.82810837030410767,0 +coef_eat_out_tour_departure_shift_effects,0.051316259249107425,0.051316222550347332,0.075489997863769531,0 +coef_escort_tour_arrival_constants_am_peak,0,0,0,0 +coef_escort_tour_arrival_constants_early,0,0,0,0 +coef_escort_tour_arrival_constants_evening,-0.71223140451440192,-0.71223691887938245,-0.53691869974136353,0 +coef_escort_tour_arrival_constants_late,-0.72737915035423661,-0.72736904512133638,-1.00829017162323,0 +coef_escort_tour_arrival_constants_midday_1,0,0,0,0 +coef_escort_tour_arrival_constants_midday_2,0,0,0,0 +coef_escort_tour_arrival_constants_pm_peak_1,0,0,0,0 +coef_escort_tour_arrival_constants_pm_peak_2,0,0,0,0 +coef_escort_tour_arrival_constants_pm_peak_3,0,0,0,0 +coef_escort_tour_arrival_constants_pm_peak_4,0,0,0,0 +coef_escort_tour_departure_constants_am_peak_1,-1.4235419252088168,-1.4235406297742828,-1.1123577356338501,0 +coef_escort_tour_departure_constants_am_peak_2,0.42531847435099135,0.42534779985548571,0.69878816604614258,0 +coef_escort_tour_departure_constants_am_peak_3,0.83882621454109263,0.83887850091215199,1.1962687969207764,0 +coef_escort_tour_departure_constants_am_peak_4,-0.83712685138635567,-0.83714012331863175,-0.22525821626186371,0 +coef_escort_tour_departure_constants_early,-2.860916885051735,-2.8608848408720089,-1.740135669708252,0 +coef_escort_tour_departure_constants_evening,-3.9409129509835932,-3.9409128427055573,-3.948732852935791,0 +coef_escort_tour_departure_constants_late,-5.7702770461708415,-5.77029206272538,-8.2288799285888672,0 +coef_escort_tour_departure_constants_midday_1,-0.1390533603155775,-0.1390075193706598,0.028662016615271568,0 +coef_escort_tour_departure_constants_midday_2,0,0,0,0 +coef_escort_tour_departure_constants_pm_peak,-1.4131855726269698,-1.4131494988499986,-1.1801401376724243,0 +coef_escort_tour_duration_constants_0_to_1_hours,0,0,0,0 +coef_escort_tour_duration_constants_11_to_13_hours,-3.9202328149945442,-3.9202404500970576,-2.9743649959564209,0 +coef_escort_tour_duration_constants_14_to_18_hours,-3.5604092863860122,-3.5604047727293211,-2.5074472427368164,0 +coef_escort_tour_duration_constants_2_to_3_hours,-2.421823365334085,-2.421833770793457,-2.0420138835906982,0 +coef_escort_tour_duration_constants_4_to_5_hours,-3.0455000043621441,-3.0455133085082999,-2.8802938461303711,0 +coef_escort_tour_duration_constants_6_to_7_hours,-3.1421992928711329,-3.1422099147681193,-2.9735336303710938,0 +coef_escort_tour_duration_constants_8_to_10_hours,-3.7497784769391589,-3.7497803018839528,-3.0202138423919678,0 +coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect,-0.25834434616162955,-0.25834415314457576,-0.23639999330043793,0 +coef_free_flow_round_trip_auto_time_shift_effects_duration,0.0065276813016913781,0.0065276968976601671,0.0047410000115633011,0 +coef_maintenance_tour_depart_before_7,-0.5056248112333217,-0.50561957768539378,-0.88260000944137573,0 +coef_maintenance_tour_departure_shift_effects,-0.14454038609055034,-0.14454021307852283,-0.14890000224113464,0 +coef_maintenance_tour_duration_shift_effects,-0.12686493168577978,-0.12686440360779777,-0.083719998598098755,0 +coef_number_of_escort_tours_departure_shift_effects,0.010507493295063721,0.010508213446682341,0.02012999914586544,0 +coef_number_of_individual_non_mandatory_tours_excluding_escort_departure_shift_effects,0.044135687848751132,0.044135987290636135,0.03895999863743782,0 +coef_number_of_joint_tours_departure_shift_effects,0.084912280527453296,0.08491252930940224,0.052080001682043076,0 +coef_number_of_mandatory_tours_departure_shift_effects,0.049914049123035174,0.049914648254726204,0.046730000525712967,0 +coef_ratio_of_individual_non_mandatory_tours_to_be_scheduled_to_number_of_unscheduled_hours,-14.166516751822661,-14.166519647615067,-13.630000114440918,0 +coef_school_child_age_16_plus_departure_shift_effects,-0.1010476102967722,-0.10104136957996175,0.072659999132156372,0 +coef_school_child_age_16_plus_duration_shift_effects,0.27141008329162575,0.27140733987575305,0.20949999988079071,0 +coef_school_child_age_under_16_departure_shift_effects,0.040466224371894295,0.040465357220666222,0.046569999307394028,0 +coef_school_child_age_under_16_duration_shift_effects,0.32700056448616932,0.32699981446388821,0.32719999551773071,0 +coef_school_child_under_16_arrive_after_22,-0.2464951245477969,-0.2464607983596627,-1.1799999475479126,0 +coef_shopping_tour_arrive_after_22,-2.0657698295000624,-2.065800932685089,-0.60269999504089355,0 +coef_shopping_tour_depart_before_8,-1.1138212368924993,-1.1138115434095399,-1.0369999408721924,0 +coef_shopping_tour_departure_shift_effects,-0.067931916027145156,-0.067931597698885862,-0.06015000119805336,0 +coef_shopping_tour_duration_lt_2_hours,0.67436877539980855,0.67440552001221821,0.51679998636245728,0 +coef_shopping_tour_duration_shift_effects,-0.10944476789632213,-0.10943885166753625,-0.12080000340938568,0 +coef_some_previously_scheduled_tour_begins_in_this_arrival_hour,-0.30742282105349766,-0.30742665676699332,-0.39919999241828918,0 +coef_some_previously_scheduled_tour_ends_in_this_departure_hour,-0.42079038970222704,-0.42079362641039114,-0.4562000036239624,0 +coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect,-0.15663240624251576,-0.15663237202517855,-0.17309999465942383,0 +coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends,-999,-999,-999,0 +coef_university_student_arrive_after_22,-0.75698586492006881,-0.7570144484766741,0.54659998416900635,0 +coef_visit_tour_departure_shift_effects,0.093345651330126359,0.093345498661509735,0.096879996359348297,0 +coef_visit_tour_duration_shift_effects,0.15548956158347038,0.15549039376025442,0.16380000114440918,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_school_location.csv b/activitysim/estimation/test/test_larch_estimation/test_school_location.csv index 9149b65cb7..33b657c2c3 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_school_location.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_school_location.csv @@ -1,21 +1,21 @@ -,value,initvalue,nullvalue,minimum,maximum,best --999,-999,-999,-999,-999,-999,-999 -1,1,1,1,1,1,1 -coef_grade_dist_0_1,-1.8247599716114487,-1.6418999999999999,0,-25,25,-1.8247599716114487 -coef_grade_dist_15_up,-0.045999999999986392,-0.045999999999999999,0,-25,25,-0.045999999999986392 -coef_grade_dist_5_15,-0.14366066473346295,-0.2031,0,-25,25,-0.14366066473346295 -coef_high_dist_0_1,-2.1639631787042557,-0.95230000000000004,0,-25,25,-2.1639631787042557 -coef_high_dist_15_up,-0.18819999999999787,-0.18820000000000001,0,-25,25,-0.18819999999999787 -coef_high_dist_5_15,-0.10033006353999419,-0.193,0,-25,25,-0.10033006353999419 -coef_high_grade_dist_1_2,-0.747678833666925,-0.56999999999999995,0,-25,25,-0.747678833666925 -coef_high_grade_dist_2_5,-0.66638388058588283,-0.56999999999999995,0,-25,25,-0.66638388058588283 -coef_mode_logsum,0.37505355574886973,0.53580000000000005,0,-25,25,0.37505355574886973 -coef_univ_dist_0_1,-3.3133821471324696,-3.2450999999999999,0,-25,25,-3.3133821471324696 -coef_univ_dist_15_up,-0.072999999999999995,-0.072999999999999995,0,-25,25,-0.072999999999999995 -coef_univ_dist_1_2,-2.8750960133089687,-2.7010999999999998,0,-25,25,-2.8750960133089687 -coef_univ_dist_2_5,-0.45559440871309681,-0.57069999999999999,0,-25,25,-0.45559440871309681 -coef_univ_dist_5_15,-0.5718644285076383,-0.50019999999999998,0,-25,25,-0.5718644285076383 -gradeschool_AGE0519,0,0,0,0,0,0 -highschool_HSENROLL,0,0,0,0,0,0 -university_COLLFTE,-0.52424864409813143,-0.52424864409813143,0,-0.52424864409813143,-0.52424864409813143,-0.52424864409813143 -university_COLLPTE,-1.2088722041237281,-0.89648810457797545,0,-6,6,-1.2088722041237281 +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +1,1,1,1,0 +coef_grade_dist_0_1,0.080031235198373782,0.080031235198373782,-1.6418999433517456,0 +coef_grade_dist_15_up,-0.046010368210409304,-0.046010368210409304,-0.046000000089406967,0 +coef_grade_dist_5_15,0.011795679963699891,0.011795679963699891,-0.20309999585151672,0 +coef_high_dist_0_1,-0.48267138976026713,-0.48267138976026713,-0.95230001211166382,0 +coef_high_dist_15_up,-0.18818654818448871,-0.18818654818448871,-0.18819999694824219,0 +coef_high_dist_5_15,-0.12203943917498229,-0.12203943917498229,-0.19300000369548798,0 +coef_high_grade_dist_1_2,-0.2740077638163641,-0.2740077638163641,-0.56999999284744263,0 +coef_high_grade_dist_2_5,-0.12717991662132286,-0.12717991662132286,-0.56999999284744263,0 +coef_mode_logsum,0.28675535602711366,0.28675535602711366,0.53579998016357422,0 +coef_univ_dist_0_1,-0.20246864835878667,-0.20246864835878667,-3.2451000213623047,0 +coef_univ_dist_15_up,-0.072999830047635036,-0.072999830047635036,-0.072999998927116394,0 +coef_univ_dist_1_2,-0.50654663083945994,-0.50654663083945994,-2.7011001110076904,0 +coef_univ_dist_2_5,0.095856729554638809,0.095856729554638809,-0.57069998979568481,0 +coef_univ_dist_5_15,-0.1412133832985831,-0.1412133832985831,-0.50019997358322144,0 +gradeschool_AGE0519,0,0,0,0 +highschool_HSENROLL,0,0,0,0 +university_COLLFTE,-0.52424865961074829,-0.52424865961074829,-0.52424865961074829,0 +university_COLLPTE,-1275009.279056468,-1275009.279056468,-0.89648813009262085,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_school_location_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_school_location_loglike.csv index cf413cb0ad..61faa0892d 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_school_location_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_school_location_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-4070.349038545839,-4058.2217953154559 +0,-3150.9027927232128,-2472.1256126886806 diff --git a/activitysim/estimation/test/test_larch_estimation/test_school_location_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_school_location_size_spec.csv index 44852f23f4..b5a4700325 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_school_location_size_spec.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_school_location_size_spec.csv @@ -1,9 +1,9 @@ ,segment,model_selector,TOTHH,RETEMPN,FPSEMPN,HEREMPN,OTHEMPN,AGREMPN,MWTEMPN,AGE0519,HSENROLL,COLLFTE,COLLPTE -0,work_low,workplace,0,0.12912912912912916,0.19319319319319325,0.38338338338338335,0.12012012012012015,0.010010010010010012,0.1641641641641641,0,0,0,0 -1,work_med,workplace,0,0.12012012012012013,0.19719719719719711,0.32532532532532538,0.13913913913913917,0.0080080080080080097,0.21021021021021022,0,0,0,0 +0,work_low,workplace,0,0.12912912912912911,0.19319319319319317,0.38338338338338335,0.12012012012012011,0.01001001001001001,0.16416416416416416,0,0,0,0 +1,work_med,workplace,0,0.12012012012012012,0.19719719719719719,0.32532532532532532,0.13913913913913914,0.0080080080080080079,0.21021021021021019,0,0,0,0 2,work_high,workplace,0,0.11,0.20699999999999999,0.28399999999999997,0.154,0.0060000000000000001,0.23899999999999999,0,0,0,0 3,work_veryhigh,workplace,0,0.092999999999999999,0.27000000000000002,0.24099999999999999,0.14599999999999999,0.0040000000000000001,0.246,0,0,0,0 -4,university,school,0,0,0,0,0,0,0,0,0,0.66475996651277125,0.33524003348722875 +4,university,school,0,0,0,0,0,0,0,0,0,1,0 5,gradeschool,school,0,0,0,0,0,0,0,1,0,0,0 6,highschool,school,0,0,0,0,0,0,0,0,1,0,0 7,escort,non_mandatory,0,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46500000000000002,0.16600000000000001,0,0 @@ -14,10 +14,10 @@ 12,othdiscr,non_mandatory,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 13,atwork,atwork,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 14,work,trip,0,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0.16666666666666666,0,0,0,0 -15,escort,trip,0.0010000000000000002,0.22500000000000003,0,0.14400000000000002,0,0,0,0.46399999999999997,0.16600000000000004,0,0 +15,escort,trip,0.001,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46400000000000002,0.16600000000000001,0,0 16,shopping,trip,0.001,0.999,0,0,0,0,0,0,0,0,0 17,eatout,trip,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 18,othmaint,trip,0.001,0.48099999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 19,social,trip,0.001,0.52100000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 20,othdiscr,trip,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 -21,univ,trip,0.000999000999000999,0,0,0,0,0,0,0,0,0.59140859140859148,0.4075924075924075 +21,univ,trip,0.00099900099900099922,0,0,0,0,0,0,0,0,0.59140859140859148,0.40759240759240761 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_atwork_subtour_frequency_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_atwork_subtour_frequency_SLSQP_.csv index b05f6c9283..a34334c190 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_atwork_subtour_frequency_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_atwork_subtour_frequency_SLSQP_.csv @@ -1,111 +1,111 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coefficient_at_work_sub_tour_asc_business1,1.4214079856419304,-0.53720000000000001,0,,,1.4214079856419304 -coefficient_at_work_sub_tour_asc_business2,-0.13077793218906725,-2.1337000000000002,0,,,-0.13077793218906725 -coefficient_at_work_sub_tour_asc_eat,5.8090564007216319,0.85760000000000003,0,,,5.8090564007216319 -coefficient_at_work_sub_tour_asc_eat_business,-23.415365723862234,-0.97209999999999996,0,,,-23.415365723862234 -coefficient_at_work_sub_tour_asc_maint,12.910479269683176,-0.61980000000000002,0,,,12.910479269683176 -coefficient_auto_accessibility_to_retail_for_work_taz_business1,-0.23508337555533637,0.053400000000000003,0,,,-0.23508337555533637 -coefficient_auto_accessibility_to_retail_for_work_taz_business2,2.9511349220652563,0.1067,0,,,2.9511349220652563 -coefficient_auto_accessibility_to_retail_for_work_taz_eat,-0.7610481619548336,0.014999999999999999,0,,,-0.7610481619548336 -coefficient_auto_accessibility_to_retail_for_work_taz_eat_business,1.5155478484531482,0.0683,0,,,1.5155478484531482 -coefficient_auto_accessibility_to_retail_for_work_taz_maint,-3.2006512330401198,0.026499999999999999,0,,,-3.2006512330401198 -coefficient_dummy_for_drive_alone_mode_for_work_tour_business1,3.9438022928732326,0.99009999999999998,0,,,3.9438022928732326 -coefficient_dummy_for_drive_alone_mode_for_work_tour_business2,-7.2851228526180369,1.9802,0,,,-7.2851228526180369 -coefficient_dummy_for_drive_alone_mode_for_work_tour_eat,3.2162405355786916,0.48039999999999999,0,,,3.2162405355786916 -coefficient_dummy_for_drive_alone_mode_for_work_tour_eat_business,2.3334830273468778,1.4704999999999999,0,,,2.3334830273468778 -coefficient_dummy_for_drive_alone_mode_for_work_tour_maint,3.8657969968183186,1.153,0,,,3.8657969968183186 -coefficient_dummy_for_full_time_worker_business1,-11.365293683630657,-7.375,0,,,-11.365293683630657 -coefficient_dummy_for_full_time_worker_business2,-13.833915024299738,-14.279999999999999,0,,,-13.833915024299738 -coefficient_dummy_for_full_time_worker_eat,-9.545917028191262,-7.2800000000000002,0,,,-9.545917028191262 -coefficient_dummy_for_full_time_worker_eat_business,-11.192168369499433,-14.789999999999999,0,,,-11.192168369499433 -coefficient_dummy_for_full_time_worker_maint,-5.8807058943821362,-8.093,0,,,-5.8807058943821362 -coefficient_dummy_for_non_full_time_worker_business1,-2.3700983307274996,-8.3190000000000008,0,,,-2.3700983307274996 -coefficient_dummy_for_non_full_time_worker_business2,-12.723162907889261,-14.279999999999999,0,,,-12.723162907889261 -coefficient_dummy_for_non_full_time_worker_eat,-1.3866265710866461,-8.6039999999999992,0,,,-1.3866265710866461 -coefficient_dummy_for_non_full_time_worker_eat_business,-40.831097354363017,-14.789999999999999,0,,,-40.831097354363017 -coefficient_dummy_for_non_full_time_worker_maint,3.1039851640661054,-8.2140000000000004,0,,,3.1039851640661054 -coefficient_dummy_for_non_workers_business1,-5,-5,0,-5,-5,-5 -coefficient_dummy_for_non_workers_business2,-5,-5,0,-5,-5,-5 -coefficient_dummy_for_non_workers_eat,0,0,0,0,0,0 -coefficient_dummy_for_non_workers_eat_business,-5,-5,0,-5,-5,-5 -coefficient_dummy_for_non_workers_maint,-5,-5,0,-5,-5,-5 -coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business1,0,0,0,0,0,0 -coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business2,0,0,0,0,0,0 -coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat,0,0,0,0,0,0 -coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat_business,0,0,0,0,0,0 -coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_maint,-0.44654348916818676,-0.35730000000000001,0,,,-0.44654348916818676 -coefficient_high_hh_income_dummy_business1,-5.6994858911518085,1.0660000000000001,0,,,-5.6994858911518085 -coefficient_high_hh_income_dummy_business2,18.177579828448355,2.1320000000000001,0,,,18.177579828448355 -coefficient_high_hh_income_dummy_eat,-5.3601399728515835,0.86929999999999996,0,,,-5.3601399728515835 -coefficient_high_hh_income_dummy_eat_business,5.9493499938492986,1.9353,0,,,5.9493499938492986 -coefficient_high_hh_income_dummy_maint,-6.8996039582959119,0.1651,0,,,-6.8996039582959119 -coefficient_individual_discretionary_tours_made_by_full_time_worker_business1,-1.4238674423340238,0.70450000000000002,0,,,-1.4238674423340238 -coefficient_individual_discretionary_tours_made_by_full_time_worker_business2,19.497249614698436,1.409,0,,,19.497249614698436 -coefficient_individual_discretionary_tours_made_by_full_time_worker_eat,-1.4579805637692655,0.2334,0,,,-1.4579805637692655 -coefficient_individual_discretionary_tours_made_by_full_time_worker_eat_business,-11.112941997302819,0.93789999999999996,0,,,-11.112941997302819 -coefficient_individual_discretionary_tours_made_by_full_time_worker_maint,-1.7115596112922862,0.50609999999999999,0,,,-1.7115596112922862 -coefficient_individual_discretionary_tours_made_by_part_time_worker_business1,1.7016751707114186,0.70450000000000002,0,,,1.7016751707114186 -coefficient_individual_discretionary_tours_made_by_part_time_worker_business2,1.5313378193861862,1.409,0,,,1.5313378193861862 -coefficient_individual_discretionary_tours_made_by_part_time_worker_eat,0.98156496358878631,0.67759999999999998,0,,,0.98156496358878631 -coefficient_individual_discretionary_tours_made_by_part_time_worker_eat_business,0.21527427337992269,1.3821000000000001,0,,,0.21527427337992269 -coefficient_individual_discretionary_tours_made_by_part_time_worker_maint,0.24944777293344775,0.50609999999999999,0,,,0.24944777293344775 -coefficient_individual_eating_out_tours_made_by_person_business1,0.42490805390828246,0.54339999999999999,0,,,0.42490805390828246 -coefficient_individual_eating_out_tours_made_by_person_business2,16.88422034232115,1.0868,0,,,16.88422034232115 -coefficient_individual_eating_out_tours_made_by_person_eat,-0.21103858651833801,0.54910000000000003,0,,,-0.21103858651833801 -coefficient_individual_eating_out_tours_made_by_person_eat_business,-13.757488989198457,1.0925,0,,,-13.757488989198457 -coefficient_individual_eating_out_tours_made_by_person_maint,0.84779917948707073,0.91659999999999997,0,,,0.84779917948707073 -coefficient_log_of_the_work_tour_duration_business1,10.797431417603184,1.1419999999999999,0,,,10.797431417603184 -coefficient_log_of_the_work_tour_duration_business2,-41.041133510722389,2.2839999999999998,0,,,-41.041133510722389 -coefficient_log_of_the_work_tour_duration_eat,9.912073454627409,1.55,0,,,9.912073454627409 -coefficient_log_of_the_work_tour_duration_eat_business,19.216017820975473,2.6920000000000002,0,,,19.216017820975473 -coefficient_log_of_the_work_tour_duration_maint,10.442610817511719,1.659,0,,,10.442610817511719 -coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business1,5.2452009890599847,-0.1903,0,,,5.2452009890599847 -coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business2,-5.9574096875877984,-0.38059999999999999,0,,,-5.9574096875877984 -coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat,5.7343399360868084,0.051999999999999998,0,,,5.7343399360868084 -coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat_business,-11.365551805409792,-0.24229999999999999,0,,,-11.365551805409792 -coefficient_main_shop_escort_tours_allocated_to_full_time_worker_maint,5.726820567850968,0.14460000000000001,0,,,5.726820567850968 -coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business1,-14.379203352289357,-0.1903,0,,,-14.379203352289357 -coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business2,0.18243743982694705,-0.38059999999999999,0,,,0.18243743982694705 -coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat,6.6450879837969055,-0.30990000000000001,0,,,6.6450879837969055 -coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat_business,-0.49226068812509693,-0.50019999999999998,0,,,-0.49226068812509693 -coefficient_main_shop_escort_tours_allocated_to_part_time_worker_maint,6.3906386167906994,-0.27229999999999999,0,,,6.3906386167906994 -coefficient_medium_hh_income_dummy_business1,-3.2862939594211058,0.55549999999999999,0,,,-3.2862939594211058 -coefficient_medium_hh_income_dummy_business2,2.0060702575802463,1.111,0,,,2.0060702575802463 -coefficient_medium_hh_income_dummy_eat,-2.5300981505732136,0.60999999999999999,0,,,-2.5300981505732136 -coefficient_medium_hh_income_dummy_eat_business,10.500987924287303,1.1655,0,,,10.500987924287303 -coefficient_medium_hh_income_dummy_maint,-3.0959660718740842,0.1527,0,,,-3.0959660718740842 -coefficient_participation_in_joint_discretionary_tours_business1,0.88783303805250202,-0.26369999999999999,0,,,0.88783303805250202 -coefficient_participation_in_joint_discretionary_tours_business2,-0.41998352565813962,-0.52739999999999998,0,,,-0.41998352565813962 -coefficient_participation_in_joint_discretionary_tours_eat,-0.24481723660555421,0.35880000000000001,0,,,-0.24481723660555421 -coefficient_participation_in_joint_discretionary_tours_eat_business,-2.7238766448704519,0.095100000000000004,0,,,-2.7238766448704519 -coefficient_participation_in_joint_discretionary_tours_maint,2.7458443690817487,0.58220000000000005,0,,,2.7458443690817487 -coefficient_participation_in_joint_shop_main_eat_tours_business1,3.5611554115337705,0.083000000000000004,0,,,3.5611554115337705 -coefficient_participation_in_joint_shop_main_eat_tours_business2,-0.28005028801856696,0.16600000000000001,0,,,-0.28005028801856696 -coefficient_participation_in_joint_shop_main_eat_tours_eat,1.988636928413654,0.24579999999999999,0,,,1.988636928413654 -coefficient_participation_in_joint_shop_main_eat_tours_eat_business,-6.5451744879809857,0.32879999999999998,0,,,-6.5451744879809857 -coefficient_participation_in_joint_shop_main_eat_tours_maint,2.1793324360516571,0.080299999999999996,0,,,2.1793324360516571 -coefficient_two_work_tours_by_person_business1,3.6940239753295181,0.37530000000000002,0,,,3.6940239753295181 -coefficient_two_work_tours_by_person_business2,-4.1046837844384205,0.75060000000000004,0,,,-4.1046837844384205 -coefficient_two_work_tours_by_person_eat,1.927236938048462,-0.98619999999999997,0,,,1.927236938048462 -coefficient_two_work_tours_by_person_eat_business,-5.4249750305237576,-0.6109,0,,,-5.4249750305237576 -coefficient_two_work_tours_by_person_maint,3.2059979015841251,-0.23119999999999999,0,,,3.2059979015841251 -coefficient_walk_accessibility_to_retail_for_work_taz_business1,0,0,0,0,0,0 -coefficient_walk_accessibility_to_retail_for_work_taz_business2,0,0,0,0,0,0 -coefficient_walk_accessibility_to_retail_for_work_taz_eat,0.053293769108333916,0.059999999999999998,0,,,0.053293769108333916 -coefficient_walk_accessibility_to_retail_for_work_taz_eat_business,-0.46901654329224335,0.059999999999999998,0,,,-0.46901654329224335 -coefficient_walk_accessibility_to_retail_for_work_taz_maint,0.39304906249970034,0.040000000000000001,0,,,0.39304906249970034 -coefficient_workplace_suburban_area_dummy_business1,-0.11020000000000001,-0.11020000000000001,0,,,-0.11020000000000001 -coefficient_workplace_suburban_area_dummy_business2,-0.22040000000000001,-0.22040000000000001,0,,,-0.22040000000000001 -coefficient_workplace_suburban_area_dummy_eat,-0.29160000000000003,-0.29160000000000003,0,,,-0.29160000000000003 -coefficient_workplace_suburban_area_dummy_eat_business,-0.40179999999999999,-0.40179999999999999,0,,,-0.40179999999999999 -coefficient_workplace_suburban_area_dummy_maint,0,0,0,0,0,0 -coefficient_workplace_urban_area_dummy_business1,1.7351079856418732,-0.2235,0,,,1.7351079856418732 -coefficient_workplace_urban_area_dummy_business2,1.5559220678109973,-0.44700000000000001,0,,,1.5559220678109973 -coefficient_workplace_urban_area_dummy_eat,4.5332564007214371,-0.41820000000000002,0,,,4.5332564007214371 -coefficient_workplace_urban_area_dummy_eat_business,-23.084965723862449,-0.64170000000000005,0,,,-23.084965723862449 -coefficient_workplace_urban_area_dummy_maint,13.382379269683053,-0.1479,0,,,13.382379269683053 -coefficient_zero_cars_owned_by_hh_dummy_business1,-0.5268759138584419,-0.33910000000000001,0,,,-0.5268759138584419 -coefficient_zero_cars_owned_by_hh_dummy_business2,0,0,0,0,0,0 -coefficient_zero_cars_owned_by_hh_dummy_eat,0,0,0,0,0,0 -coefficient_zero_cars_owned_by_hh_dummy_eat_business,-19.11629098153702,-0.33910000000000001,0,,,-19.11629098153702 -coefficient_zero_cars_owned_by_hh_dummy_maint,0.55934969853310723,0.1762,0,,,0.55934969853310723 +param_name,value,best,initvalue,nullvalue +coefficient_at_work_sub_tour_asc_business1,-4.6364509649106624,-4.636450908579854,-0.53719997406005859,0 +coefficient_at_work_sub_tour_asc_business2,-1.8249400470488537,-1.8249400513348371,-2.133699893951416,0 +coefficient_at_work_sub_tour_asc_eat,-1.2025517519916142,-1.2025517383789965,0.85759997367858887,0 +coefficient_at_work_sub_tour_asc_eat_business,-2.4601386278749016,-2.460138609917645,-0.97210001945495605,0 +coefficient_at_work_sub_tour_asc_maint,6.7188815064577412,6.718881422843042,-0.61979997158050537,0 +coefficient_auto_accessibility_to_retail_for_work_taz_business1,1.5195960607537637,1.5195960534758026,0.053399998694658279,0 +coefficient_auto_accessibility_to_retail_for_work_taz_business2,0.39623374265129618,0.3962337362698467,0.10670000314712524,0 +coefficient_auto_accessibility_to_retail_for_work_taz_eat,1.244843971401054,1.2448439700604323,0.014999999664723873,0 +coefficient_auto_accessibility_to_retail_for_work_taz_eat_business,-1.4936433037222552,-1.4936433133522584,0.068300001323223114,0 +coefficient_auto_accessibility_to_retail_for_work_taz_maint,-1.3971304685665173,-1.397130443936482,0.026499999687075615,0 +coefficient_dummy_for_drive_alone_mode_for_work_tour_business1,2.5403075484019295,2.5403075438954636,0.99010002613067627,0 +coefficient_dummy_for_drive_alone_mode_for_work_tour_business2,-1.5471111587719255,-1.5471111364437549,1.9802000522613525,0 +coefficient_dummy_for_drive_alone_mode_for_work_tour_eat,1.8134290820782721,1.8134290762249321,0.48039999604225159,0 +coefficient_dummy_for_drive_alone_mode_for_work_tour_eat_business,0.81302147728988705,0.81302147967997473,1.4704999923706055,0 +coefficient_dummy_for_drive_alone_mode_for_work_tour_maint,2.4545531149456474,2.4545531005871952,1.1529999971389771,0 +coefficient_dummy_for_full_time_worker_business1,-10.835277488785893,-10.83527745465712,-7.375,0 +coefficient_dummy_for_full_time_worker_business2,-13.651388366502351,-13.651388372174022,-14.279999732971191,0 +coefficient_dummy_for_full_time_worker_eat,-9.4982645189968196,-9.4982645055658654,-7.2800002098083496,0 +coefficient_dummy_for_full_time_worker_eat_business,-12.473124948668486,-12.473124950259384,-14.789999961853027,0 +coefficient_dummy_for_full_time_worker_maint,-5.3599449936662609,-5.3599450339634185,-8.0930004119873047,0 +coefficient_dummy_for_non_full_time_worker_business1,-8.9579737462053064,-8.9579737240032706,-8.319000244140625,0 +coefficient_dummy_for_non_full_time_worker_business2,-14.599851252537475,-14.599851251151787,-14.279999732971191,0 +coefficient_dummy_for_non_full_time_worker_eat,-8.4458875080344917,-8.445887507852829,-8.6040000915527344,0 +coefficient_dummy_for_non_full_time_worker_eat_business,-18.594913583457473,-18.594913563909319,-14.789999961853027,0 +coefficient_dummy_for_non_full_time_worker_maint,-3.6083736885127893,-3.6083737318303313,-8.2139997482299805,0 +coefficient_dummy_for_non_workers_business1,-5,-5,-5,0 +coefficient_dummy_for_non_workers_business2,-5,-5,-5,0 +coefficient_dummy_for_non_workers_eat,0,0,0,0 +coefficient_dummy_for_non_workers_eat_business,-5,-5,-5,0 +coefficient_dummy_for_non_workers_maint,-5,-5,-5,0 +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business1,0,0,0,0 +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business2,0,0,0,0 +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat,0,0,0,0 +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat_business,0,0,0,0 +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_maint,-0.41501623497381018,-0.4150162451792187,-0.35730001330375671,0 +coefficient_high_hh_income_dummy_business1,-0.33979337120056141,-0.33979335118765108,1.0659999847412109,0 +coefficient_high_hh_income_dummy_business2,4.2112639057799823,4.2112638870883581,2.1319999694824219,0 +coefficient_high_hh_income_dummy_eat,0.023039749877190804,0.023039775965731642,0.86930000782012939,0 +coefficient_high_hh_income_dummy_eat_business,3.7450872508803248,3.745087211197407,1.9352999925613403,0 +coefficient_high_hh_income_dummy_maint,-1.471897587383632,-1.471897575110541,0.16509999334812164,0 +coefficient_individual_discretionary_tours_made_by_full_time_worker_business1,-0.258886010731674,-0.25888602469708244,0.70450001955032349,0 +coefficient_individual_discretionary_tours_made_by_full_time_worker_business2,10.013216960858641,10.013216913800566,1.409000039100647,0 +coefficient_individual_discretionary_tours_made_by_full_time_worker_eat,-0.27143991243306015,-0.27143990533123996,0.23340000212192535,0 +coefficient_individual_discretionary_tours_made_by_full_time_worker_eat_business,-5.1450511716765561,-5.1450511394525638,0.93790000677108765,0 +coefficient_individual_discretionary_tours_made_by_full_time_worker_maint,-0.54693979952226501,-0.54693977782459402,0.50609999895095825,0 +coefficient_individual_discretionary_tours_made_by_part_time_worker_business1,1.5008073499859345,1.5008073606710928,0.70450001955032349,0 +coefficient_individual_discretionary_tours_made_by_part_time_worker_business2,1.3725147779808102,1.3725147781405138,1.409000039100647,0 +coefficient_individual_discretionary_tours_made_by_part_time_worker_eat,0.8707190441243009,0.8707190632298788,0.67760002613067627,0 +coefficient_individual_discretionary_tours_made_by_part_time_worker_eat_business,0.75707630852833474,0.75707631165373623,1.382099986076355,0 +coefficient_individual_discretionary_tours_made_by_part_time_worker_maint,0.17818258918958901,0.17818255611374761,0.50609999895095825,0 +coefficient_individual_eating_out_tours_made_by_person_business1,1.2291884533614996,1.2291884357040239,0.54339998960494995,0 +coefficient_individual_eating_out_tours_made_by_person_business2,5.3890915350859343,5.3890915063685627,1.0867999792098999,0 +coefficient_individual_eating_out_tours_made_by_person_eat,0.59241286979897301,0.59241286727354991,0.54909998178482056,0 +coefficient_individual_eating_out_tours_made_by_person_eat_business,-4.6396338093217437,-4.6396337749049197,1.0924999713897705,0 +coefficient_individual_eating_out_tours_made_by_person_maint,1.6173408620021299,1.6173408764855761,0.91659998893737793,0 +coefficient_log_of_the_work_tour_duration_business1,2.8745950964750677,2.8745950289586566,1.1419999599456787,0 +coefficient_log_of_the_work_tour_duration_business2,-9.4213725166497184,-9.4213723813479699,2.2839999198913574,0 +coefficient_log_of_the_work_tour_duration_eat,2.0174558496514647,2.0174558005400733,1.5499999523162842,0 +coefficient_log_of_the_work_tour_duration_eat_business,11.401343306668366,11.401343332337083,2.6919999122619629,0 +coefficient_log_of_the_work_tour_duration_maint,2.4549780473709193,2.4549780030282569,1.659000039100647,0 +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business1,1.1088398218159976,1.1088398127197108,-0.19030000269412994,0 +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business2,-0.57516973946012429,-0.575169738593175,-0.38060000538825989,0 +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat,1.5872866399810972,1.5872866248218596,0.052000001072883606,0 +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat_business,-4.2886646505292108,-4.2886646240189545,-0.24230000376701355,0 +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_maint,1.5511079213734775,1.5511079182517966,0.14460000395774841,0 +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business1,-6.3194536970520918,-6.3194536671381956,-0.19030000269412994,0 +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business2,-0.45741583885508108,-0.45741583852963658,-0.38060000538825989,0 +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat,3.0910693656661703,3.0910693473970023,-0.30989998579025269,0 +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat_business,-0.85983485391771264,-0.85983485226518608,-0.50019997358322144,0 +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_maint,2.8923350517436197,2.8923350381209207,-0.27230000495910645,0 +coefficient_medium_hh_income_dummy_business1,-1.1331895926048559,-1.1331895937415595,0.55549997091293335,0 +coefficient_medium_hh_income_dummy_business2,0.81318352183524256,0.81318352315710596,1.1109999418258667,0 +coefficient_medium_hh_income_dummy_eat,-0.34741746210681906,-0.3474174464669022,0.61000001430511475,0 +coefficient_medium_hh_income_dummy_eat_business,5.121964519155811,5.1219645052482301,1.1655000448226929,0 +coefficient_medium_hh_income_dummy_maint,-0.85984100745095871,-0.8598410093684542,0.15270000696182251,0 +coefficient_participation_in_joint_discretionary_tours_business1,0.30193135342719479,0.30193135643871699,-0.26370000839233398,0 +coefficient_participation_in_joint_discretionary_tours_business2,-0.59379173063206181,-0.59379173033201538,-0.52740001678466797,0 +coefficient_participation_in_joint_discretionary_tours_eat,-0.97053293091235093,-0.9705329212314463,0.35879999399185181,0 +coefficient_participation_in_joint_discretionary_tours_eat_business,-0.5490816124017508,-0.54908160890359503,0.095100000500679016,0 +coefficient_participation_in_joint_discretionary_tours_maint,2.0564748805838153,2.056474864093186,0.58219999074935913,0 +coefficient_participation_in_joint_shop_main_eat_tours_business1,1.8768257580478833,1.8768257619258122,0.082999996840953827,0 +coefficient_participation_in_joint_shop_main_eat_tours_business2,0.055786350132296811,0.055786350662721744,0.16599999368190765,0 +coefficient_participation_in_joint_shop_main_eat_tours_eat,0.31370718460939551,0.31370718509133344,0.24580000340938568,0 +coefficient_participation_in_joint_shop_main_eat_tours_eat_business,-1.8724721811608103,-1.8724721667874074,0.32879999279975891,0 +coefficient_participation_in_joint_shop_main_eat_tours_maint,0.53005287839341431,0.53005285912971956,0.080300003290176392,0 +coefficient_two_work_tours_by_person_business1,0.78174817096251792,0.78174816097861666,0.37529999017715454,0 +coefficient_two_work_tours_by_person_business2,0.67460859753132585,0.67460859786572203,0.75059998035430908,0 +coefficient_two_work_tours_by_person_eat,-0.96831618429168598,-0.96831618402710151,-0.98619997501373291,0 +coefficient_two_work_tours_by_person_eat_business,-1.4448302925402916,-1.4448302854771486,-0.61089998483657837,0 +coefficient_two_work_tours_by_person_maint,0.25438972433601764,0.2543897266577953,-0.23119999468326569,0 +coefficient_walk_accessibility_to_retail_for_work_taz_business1,0,0,0,0 +coefficient_walk_accessibility_to_retail_for_work_taz_business2,0,0,0,0 +coefficient_walk_accessibility_to_retail_for_work_taz_eat,0.024318701408312954,0.024318700872964293,0.059999998658895493,0 +coefficient_walk_accessibility_to_retail_for_work_taz_eat_business,-0.098985033594679236,-0.098985043830151581,0.059999998658895493,0 +coefficient_walk_accessibility_to_retail_for_work_taz_maint,0.37714309948187719,0.37714309907729421,0.039999999105930328,0 +coefficient_workplace_suburban_area_dummy_business1,-0.11020000278949738,-0.11020000278949738,-0.11020000278949738,0 +coefficient_workplace_suburban_area_dummy_business2,-0.22040000557899475,-0.22040000557899475,-0.22040000557899475,0 +coefficient_workplace_suburban_area_dummy_eat,-0.29159998893737793,-0.29159998893737793,-0.29159998893737793,0 +coefficient_workplace_suburban_area_dummy_eat_business,-0.4018000066280365,-0.4018000066280365,-0.4018000066280365,0 +coefficient_workplace_suburban_area_dummy_maint,0,0,0,0 +coefficient_workplace_urban_area_dummy_business1,-4.3227509893008715,-4.3227509329700631,-0.22349999845027924,0 +coefficient_workplace_urban_area_dummy_business2,-0.13824014999799764,-0.13824015428398095,-0.44699999690055847,0 +coefficient_workplace_urban_area_dummy_eat,-2.4783517118896161,-2.4783516982769984,-0.41819998621940613,0 +coefficient_workplace_urban_area_dummy_eat_business,-2.1297386377930989,-2.1297386198358423,-0.64170002937316895,0 +coefficient_workplace_urban_area_dummy_maint,7.1907814778236281,7.1907813942089289,-0.14790000021457672,0 +coefficient_zero_cars_owned_by_hh_dummy_business1,-0.48372662658348159,-0.48372661407098899,-0.33910000324249268,0 +coefficient_zero_cars_owned_by_hh_dummy_business2,0,0,0,0 +coefficient_zero_cars_owned_by_hh_dummy_eat,0,0,0,0 +coefficient_zero_cars_owned_by_hh_dummy_eat_business,-7.372632298534227,-7.3726322561599522,-0.33910000324249268,0 +coefficient_zero_cars_owned_by_hh_dummy_maint,0.53982915542758059,0.53982913595117754,0.17620000243186951,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_atwork_subtour_frequency_SLSQP_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_atwork_subtour_frequency_SLSQP_loglike.csv index 2f32cb32aa..b0b7c83312 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_atwork_subtour_frequency_SLSQP_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_atwork_subtour_frequency_SLSQP_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-339.26475293528824,-311.08163243830268 +0,-339.26475419242206,-311.72832904369682 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_auto_ownership_BHHH_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_auto_ownership_BHHH_.csv index 36f7acad3f..a45f944823 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_auto_ownership_BHHH_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_auto_ownership_BHHH_.csv @@ -1,4 +1,4 @@ -,value,initvalue,nullvalue,minimum,maximum,best +param_name,value,initvalue,nullvalue,minimum,maximum,best coef_cars1_asc,4.7447107380921025,1.1865000000000001,0,,,4.7447107380921025 coef_cars1_asc_county,-0.56599882256075029,-0.56599999999999995,0,,,-0.56599882256075029 coef_cars1_asc_marin,-0.24339921273778259,-0.24340000000000001,0,,,-0.24339921273778259 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_free_parking_BHHH_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_free_parking_BHHH_.csv index d721934bd3..ab1d9efd30 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_free_parking_BHHH_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_free_parking_BHHH_.csv @@ -1,4 +1,4 @@ -,value,initvalue,nullvalue,minimum,maximum,holdfast,best +param_name,value,initvalue,nullvalue,minimum,maximum,holdfast,best 0.0,0,0,0,0,0,1,0 coef_asc_alameda,-0.10920000000000001,-0.10920000000000001,0,,,0,-0.10920000000000001 coef_asc_san_francisco,-2.4563318326358723,-2.6402999999999999,0,,,0,-2.4563318326358723 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_composition_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_composition_SLSQP_.csv index 40c2da343d..f6db0bb7da 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_composition_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_composition_SLSQP_.csv @@ -1,32 +1,32 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_asc_children,121.62774629212394,5.3517000000000001,0,,,121.62774629212394 -coef_asc_mixed,-88.249612624384525,5.6289999999999996,0,,,-88.249612624384525 -coef_household_has_more_cars_than_workers_adults,-40.894264494991035,1.3859999999999999,0,,,-40.894264494991035 -coef_household_has_more_cars_than_workers_mixed,153.8152034125998,0.751,0,,,153.8152034125998 -coef_household_in_suburban_area_adults,0.51049999999999995,0.51049999999999995,0,,,0.51049999999999995 -coef_household_in_suburban_area_mixed,0.1283,0.1283,0,,,0.1283 -coef_household_in_urban_area,-21.823333667739977,0.57410000000000005,0,,,-21.823333667739977 -coef_log_max_overlap_of_adults_time_windows,-36.285976396423372,1.1919999999999999,0,,,-36.285976396423372 -coef_log_max_overlap_of_childrens_time_windows,283.69666707732551,1.841,0,,,283.69666707732551 -coef_log_max_overlap_of_time_windows,196.72857307970887,1.958,0,,,196.72857307970887 -coef_low_income_households_adults,-16.894953557817836,1.248,0,,,-16.894953557817836 -coef_low_income_households_mixed,-3.1435928555076917,0.57550000000000001,0,,,-3.1435928555076917 -coef_medium_income_households,-161.72738528562726,0.83689999999999998,0,,,-161.72738528562726 -coef_number_of_children_too_young_for_school_children,-110.04828004959086,0.73060000000000003,0,,,-110.04828004959086 -coef_number_of_children_too_young_for_school_mixed,9.5393263775476171,0.79059999999999997,0,,,9.5393263775476171 -coef_number_of_driving_age_children_children,-172.31193722793208,-0.26669999999999999,0,,,-172.31193722793208 -coef_number_of_driving_age_children_mixed,184.76140753321386,-0.93989999999999996,0,,,184.76140753321386 -coef_number_of_full_time_workers_adults,185.49031080785167,1.024,0,,,185.49031080785167 -coef_number_of_full_time_workers_mixed,50.943192997924122,0.3624,0,,,50.943192997924122 -coef_number_of_non_workers_adults,40.041010494333662,0.62629999999999997,0,,,40.041010494333662 -coef_number_of_non_workers_mixed,-96.438665924994751,-0.37240000000000001,0,,,-96.438665924994751 -coef_number_of_part_time_workers_adults,47.088158071231007,0.54120000000000001,0,,,47.088158071231007 -coef_number_of_part_time_workers_mixed,58.958712458292865,0.31640000000000001,0,,,58.958712458292865 -coef_number_of_pre_driving_age_children_children,12.678858152945852,0.73060000000000003,0,,,12.678858152945852 -coef_number_of_pre_driving_age_children_mixed,158.96026734481441,0.35320000000000001,0,,,158.96026734481441 -coef_number_of_university_students,-5.007830161412854,0.82450000000000001,0,,,-5.007830161412854 -coef_tour_purpose_is_discretionary_adults,0.76480000000000004,0.76480000000000004,0,,,0.76480000000000004 -coef_tour_purpose_is_discretionary_children,0.5101,0.5101,0,,,0.5101 -coef_tour_purpose_is_eating_out_children,-0.96779999999999999,-0.96779999999999999,0,,,-0.96779999999999999 -coef_tour_purpose_is_eating_out_mixed,-0.80269999999999997,-0.80269999999999997,0,,,-0.80269999999999997 -coef_unavailable,-999,-999,0,-999,-999,-999 +param_name,value,best,initvalue,nullvalue +coef_asc_children,31.580459657771478,31.580459657771478,5.3516998291015625,0 +coef_asc_mixed,-8.4815755302186577,-8.4815755302186577,5.629000186920166,0 +coef_household_has_more_cars_than_workers_adults,-14.008943838901908,-14.008943838901908,1.3860000371932983,0 +coef_household_has_more_cars_than_workers_mixed,25.695328937041246,25.695328937041246,0.75099998712539673,0 +coef_household_in_suburban_area_adults,0.51050001382827759,0.51050001382827759,0.51050001382827759,0 +coef_household_in_suburban_area_mixed,0.12829999625682831,0.12829999625682831,0.12829999625682831,0 +coef_household_in_urban_area,-11.544084093965571,-11.544084093965571,0.57410001754760742,0 +coef_log_max_overlap_of_adults_time_windows,-25.921679816393258,-25.921679816393258,1.1920000314712524,0 +coef_log_max_overlap_of_childrens_time_windows,50,50,1.840999960899353,0 +coef_log_max_overlap_of_time_windows,43.185336045455792,43.185336045455792,1.9579999446868896,0 +coef_low_income_households_adults,-4.7176489111037725,-4.7176489111037725,1.2480000257492065,0 +coef_low_income_households_mixed,-9.0408081421508903,-9.0408081421508903,0.5755000114440918,0 +coef_medium_income_households,-34.499486089811263,-34.499486089811263,0.83689999580383301,0 +coef_number_of_children_too_young_for_school_children,-13.855996312009184,-13.855996312009184,0.73059999942779541,0 +coef_number_of_children_too_young_for_school_mixed,4.4802268807421637,4.4802268807421637,0.7906000018119812,0 +coef_number_of_driving_age_children_children,-46.217713310558153,-46.217713310558153,-0.26669999957084656,0 +coef_number_of_driving_age_children_mixed,50,50,-0.9398999810218811,0 +coef_number_of_full_time_workers_adults,28.469430749747154,28.469430749747154,1.0240000486373901,0 +coef_number_of_full_time_workers_mixed,2.5181990493930466,2.5181990493930466,0.36239999532699585,0 +coef_number_of_non_workers_adults,6.8107526564830181,6.8107526564830181,0.62629997730255127,0 +coef_number_of_non_workers_mixed,-27.464491079595931,-27.464491079595931,-0.37239998579025269,0 +coef_number_of_part_time_workers_adults,12.100761555344075,12.100761555344075,0.54119998216629028,0 +coef_number_of_part_time_workers_mixed,-2.6898434127139574,-2.6898434127139574,0.31639999151229858,0 +coef_number_of_pre_driving_age_children_children,6.9278442677705971,6.9278442677705971,0.73059999942779541,0 +coef_number_of_pre_driving_age_children_mixed,34.880087194025478,34.880087194025478,0.35319998860359192,0 +coef_number_of_university_students,-3.4995325852033643,-3.4995325852033643,0.82450002431869507,0 +coef_tour_purpose_is_discretionary_adults,0.76480001211166382,0.76480001211166382,0.76480001211166382,0 +coef_tour_purpose_is_discretionary_children,0.51010000705718994,0.51010000705718994,0.51010000705718994,0 +coef_tour_purpose_is_eating_out_children,-0.96780002117156982,-0.96780002117156982,-0.96780002117156982,0 +coef_tour_purpose_is_eating_out_mixed,-0.8026999831199646,-0.8026999831199646,-0.8026999831199646,0 +coef_unavailable,-999,-999,-999,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_composition_SLSQP_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_composition_SLSQP_loglike.csv index 449c94c47f..1db96994d6 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_composition_SLSQP_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_composition_SLSQP_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-9.9910306200781598,-9.7865975960368618e-07 +0,-9.9910303886936802,-0.01512359141580788 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_frequency_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_frequency_SLSQP_.csv index f6102d3c39..833d9f4425 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_frequency_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_frequency_SLSQP_.csv @@ -1,77 +1,77 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_asc_0_tours,0,0,0,0,0,0 -coef_asc_1_Disc,-5.8578427473231667,-5.4805999999999999,0,,,-5.8578427473231667 -coef_asc_1_Eat,-5.140469329663599,-6.3757000000000001,0,,,-5.140469329663599 -coef_asc_1_Main,-4.843654155024959,-5.7389000000000001,0,,,-4.843654155024959 -coef_asc_1_Shop,-7.2448952266310895,-6.0148999999999999,0,,,-7.2448952266310895 -coef_asc_1_Visit,-5.9621489630619173,-5.8818000000000001,0,,,-5.9621489630619173 -coef_asc_2_tours,-15.379573080742464,-14.457599999999999,0,,,-15.379573080742464 -coef_drivingAgeStuMandMaxThree_disc,0.26420610778627868,0.19320000000000001,0,,,0.26420610778627868 -coef_drivingAgeStuMandMaxThree_maint,-0.20497838559876363,-0.32369999999999999,0,,,-0.20497838559876363 -coef_fewerCarsThanDrivers_maint,-0.23616022935294756,0.46100000000000002,0,,,-0.23616022935294756 -coef_fewerCarsThanDrivers_shopping,0.61204166063349064,0.25230000000000002,0,,,0.61204166063349064 -coef_fullTimeHomeMaxThree_zero_tours,2.0014370751255011,1.175,0,,,2.0014370751255011 -coef_fullTimeMandMaxThree_maint,-0.46248818198458952,-0.3009,0,,,-0.46248818198458952 -coef_fullTimeMandMaxThree_shopping,0.14353937037596973,-0.2424,0,,,0.14353937037596973 -coef_fullTimeNonMandMaxThree_disc,0.21817599548271277,0.1275,0,,,0.21817599548271277 -coef_fullTimeNonMandMaxThree_eatout,0.32573071809647042,0.22750000000000001,0,,,0.32573071809647042 -coef_fullTimeNonMandMaxThree_maint,0.75962622449225758,0.31730000000000003,0,,,0.75962622449225758 -coef_fullTimeNonMandMaxThree_shopping,-0.88812895503399825,0.20519999999999999,0,,,-0.88812895503399825 -coef_fullTimeNonMandMaxThree_visiting,0.78859263531566071,0.64449999999999996,0,,,0.78859263531566071 -coef_incomeBetween50And100_disc,0.0083529208127054756,0.31669999999999998,0,,,0.0083529208127054756 -coef_incomeBetween50And100_eatout,0.1031885654385253,0.29770000000000002,0,,,0.1031885654385253 -coef_incomeGreaterThan100_disc,0.62493454802487425,0.48599999999999999,0,,,0.62493454802487425 -coef_incomeGreaterThan100_eatout,0.63535874552918015,0.44919999999999999,0,,,0.63535874552918015 -coef_incomeMissing_dummy_always_zero_disc,0.37230000000000002,0.37230000000000002,0,,,0.37230000000000002 -coef_incomeMissing_dummy_always_zero_eatout,0.27800000000000002,0.27800000000000002,0,,,0.27800000000000002 -coef_logTimeWindowOverlapAdultChild_disc,0.1502559618722121,0.22120000000000001,0,,,0.1502559618722121 -coef_logTimeWindowOverlapAdultChild_eatout,-0.32038060987279043,0.092100000000000001,0,,,-0.32038060987279043 -coef_logTimeWindowOverlapAdultChild_maint,0.26959218597469214,0.24429999999999999,0,,,0.26959218597469214 -coef_logTimeWindowOverlapAdultChild_shopping,-0.41532462974126461,0.1086,0,,,-0.41532462974126461 -coef_logTimeWindowOverlapAdult_disc,0.55965786525579331,0.34279999999999999,0,,,0.55965786525579331 -coef_logTimeWindowOverlapAdult_eatout,0.56061433677445105,0.48559999999999998,0,,,0.56061433677445105 -coef_logTimeWindowOverlapAdult_maint,0.4376387335084278,0.37140000000000001,0,,,0.4376387335084278 -coef_logTimeWindowOverlapAdult_shopping,0.86405876135539128,0.59450000000000003,0,,,0.86405876135539128 -coef_logTimeWindowOverlapChild_disc,-0.1693892803512011,0.1162,0,,,-0.1693892803512011 -coef_logTimeWindowOverlapChild_maint,-0.010378552711083917,0.17599999999999999,0,,,-0.010378552711083917 -coef_logTimeWindowOverlapChild_shopping,1.0366536984300598,0.1416,0,,,1.0366536984300598 -coef_moreCarsThanWorkers_eatout,0.079480888637893488,0.38250000000000001,0,,,0.079480888637893488 -coef_moreCarsThanWorkers_shopping,-0.62780216023973168,-0.30270000000000002,0,,,-0.62780216023973168 -coef_nonWorkerHomeMaxThree_zero_tours,-0.16941211649357898,1.514,0,,,-0.16941211649357898 -coef_nonWorkerNonMandMaxThree_disc,-0.11901239265508992,0.28710000000000002,0,,,-0.11901239265508992 -coef_nonWorkerNonMandMaxThree_eatout,-0.35447708036701164,0.182,0,,,-0.35447708036701164 -coef_nonWorkerNonMandMaxThree_maint,0.37255083379371662,0.46429999999999999,0,,,0.37255083379371662 -coef_nonWorkerNonMandMaxThree_shopping,0.52326322821604476,0.70779999999999998,0,,,0.52326322821604476 -coef_nonWorkerNonMandMaxThree_visiting,-0.35989963706226813,0.54749999999999999,0,,,-0.35989963706226813 -coef_partTimeHomeMaxThree_zero_tours,1.7000746681627035,1.4470000000000001,0,,,1.7000746681627035 -coef_partTimeNonMandMaxThree_disc,0.22644058039117623,0.49790000000000001,0,,,0.22644058039117623 -coef_partTimeNonMandMaxThree_eatout,-15.770618924654787,0.3765,0,,,-15.770618924654787 -coef_partTimeNonMandMaxThree_maint,0.12155923236230654,0.2452,0,,,0.12155923236230654 -coef_partTimeNonMandMaxThree_shopping,-0.19149733628062993,0.18659999999999999,0,,,-0.19149733628062993 -coef_partTimeNonMandMaxThree_visiting,0.34840797626260722,0.13320000000000001,0,,,0.34840797626260722 -coef_preDrivingAgeMandMaxThree_disc,0.58830436658291341,0.38619999999999999,0,,,0.58830436658291341 -coef_preDrivingAgeMandMaxThree_maint,0.05724992253344495,0.22989999999999999,0,,,0.05724992253344495 -coef_preDrivingHomeMaxThree_preschool_and_school_zero_tours,-0.26493959294530756,0.53000000000000003,0,,,-0.26493959294530756 -coef_preDrivingNonMandMaxThree_disc,0.46978892402747974,0.53310000000000002,0,,,0.46978892402747974 -coef_preDrivingNonMandMaxThree_eatout,-13.674346835309482,0.3851,0,,,-13.674346835309482 -coef_preDrivingNonMandMaxThree_maint,-0.4780031657291039,0.6482,0,,,-0.4780031657291039 -coef_preDrivingNonMandMaxThree_shopping,0.0054016798205857386,0.5474,0,,,0.0054016798205857386 -coef_preDrivingNonMandMaxThree_visiting,-1.7283257423524336,0.6008,0,,,-1.7283257423524336 -coef_retireeHomeMaxThree_zero_tours,0.3072054262466079,0.60529999999999995,0,,,0.3072054262466079 -coef_retireeNonMandMaxThree_disc,0.59539272893690953,0.61360000000000003,0,,,0.59539272893690953 -coef_retireeNonMandMaxThree_eatout,0.33706472938654847,0.4264,0,,,0.33706472938654847 -coef_retireeNonMandMaxThree_maint,0.93064231251598528,0.90500000000000003,0,,,0.93064231251598528 -coef_retireeNonMandMaxThree_shopping,0.95235573746714874,0.94099999999999995,0,,,0.95235573746714874 -coef_retireeNonMandMaxThree_visiting,0.17432279378364646,0.55789999999999995,0,,,0.17432279378364646 -coef_timeWindowOverlapAdultChild_visiting,0.14049394553264929,0.025600000000000001,0,,,0.14049394553264929 -coef_timeWindowOverlapAdult_visiting,0.11030183056319119,0.0596,0,,,0.11030183056319119 -coef_timeWindowOverlapChild_visiting,-0.060644638255823571,0.0091999999999999998,0,,,-0.060644638255823571 -coef_universityHomeMaxThree_univ_and_driving_zero_tours,-0.41040663722807053,0.56850000000000001,0,,,-0.41040663722807053 -coef_universityNonMandMaxThree_disc,-0.14472811802653573,0.75460000000000005,0,,,-0.14472811802653573 -coef_universityNonMandMaxThree_eatout,-14.080266896152475,0.40970000000000001,0,,,-14.080266896152475 -coef_universityNonMandMaxThree_maint,-0.4377287237690044,0.26429999999999998,0,,,-0.4377287237690044 -coef_universityNonMandMaxThree_shopping,1.1340537653332554,0.76480000000000004,0,,,1.1340537653332554 -coef_universityNonMandMaxThree_visiting,-18.048773540202976,0.28089999999999998,0,,,-18.048773540202976 -coef_walkRetailAccessibility_eatout,-0.027362834622908064,0.062,0,,,-0.027362834622908064 -coef_zeroAutomobiles_disc,-0.53993914183433878,-0.90900000000000003,0,,,-0.53993914183433878 -coef_zeroAutomobiles_visiting,-18.311268197408783,-0.97999999999999998,0,,,-18.311268197408783 +param_name,value,best,initvalue,nullvalue +coef_asc_0_tours,0,0,0,0 +coef_asc_1_Disc,-5.9160878944391584,-5.9160871584456292,-5.4805998802185059,0 +coef_asc_1_Eat,-5.05602837728296,-5.0560299542489355,-6.3756999969482422,0 +coef_asc_1_Main,-4.8254586155918471,-4.8254584245546122,-5.7389001846313477,0 +coef_asc_1_Shop,-7.4469694983528809,-7.4469670187782491,-6.0149002075195312,0 +coef_asc_1_Visit,-5.9551540139107804,-5.9551539232808333,-5.8818001747131348,0 +coef_asc_2_tours,-15.797075280937081,-15.797070989460588,-14.457599639892578,0 +coef_drivingAgeStuMandMaxThree_disc,0.27124464344272958,0.27124444259441294,0.1932000070810318,0 +coef_drivingAgeStuMandMaxThree_maint,-0.20737041043238222,-0.2073702201780428,-0.32370001077651978,0 +coef_fewerCarsThanDrivers_maint,-0.23816146636980665,-0.23816149718467414,0.460999995470047,0 +coef_fewerCarsThanDrivers_shopping,0.61694158860106285,0.61694159482964805,0.25229999423027039,0 +coef_fullTimeHomeMaxThree_zero_tours,1.996135901304358,1.9961359267238226,1.1749999523162842,0 +coef_fullTimeMandMaxThree_maint,-0.46241893261416922,-0.46241924052217082,-0.30090001225471497,0 +coef_fullTimeMandMaxThree_shopping,0.16560459271309827,0.16560432789309174,-0.24240000545978546,0 +coef_fullTimeNonMandMaxThree_disc,0.20480561409516004,0.20480581045554858,0.12749999761581421,0 +coef_fullTimeNonMandMaxThree_eatout,0.33389502103327529,0.33389509678618362,0.22750000655651093,0 +coef_fullTimeNonMandMaxThree_maint,0.76952765626273956,0.76952794806055913,0.31729999184608459,0 +coef_fullTimeNonMandMaxThree_shopping,-0.98031955850826391,-0.98031911603182831,0.20520000159740448,0 +coef_fullTimeNonMandMaxThree_visiting,0.76906716737028125,0.76906729748219271,0.6445000171661377,0 +coef_incomeBetween50And100_disc,0.0095094226633637528,0.0095095849856016851,0.31670001149177551,0 +coef_incomeBetween50And100_eatout,0.090560692608283727,0.09056083387775557,0.29769998788833618,0 +coef_incomeGreaterThan100_disc,0.62453536178251734,0.62453510934345091,0.48600000143051147,0 +coef_incomeGreaterThan100_eatout,0.63786709459088209,0.63786734556950364,0.44920000433921814,0 +coef_incomeMissing_dummy_always_zero_disc,0.37229999899864197,0.37229999899864197,0.37229999899864197,0 +coef_incomeMissing_dummy_always_zero_eatout,0.27799999713897705,0.27799999713897705,0.27799999713897705,0 +coef_logTimeWindowOverlapAdultChild_disc,0.15109942470522381,0.15109971903599334,0.22120000422000885,0 +coef_logTimeWindowOverlapAdultChild_eatout,-0.32364532221490494,-0.32364510943311381,0.092100001871585846,0 +coef_logTimeWindowOverlapAdultChild_maint,0.27843409869332575,0.27843422542528723,0.2442999929189682,0 +coef_logTimeWindowOverlapAdultChild_shopping,-0.42145916023520369,-0.42145897391197473,0.10859999805688858,0 +coef_logTimeWindowOverlapAdult_disc,0.5845950974994687,0.5845947676478761,0.34279999136924744,0 +coef_logTimeWindowOverlapAdult_eatout,0.54628409582637161,0.5462840489123495,0.48559999465942383,0 +coef_logTimeWindowOverlapAdult_maint,0.43015346279128713,0.43015341420863468,0.37139999866485596,0 +coef_logTimeWindowOverlapAdult_shopping,0.94448584150730952,0.94448492089225045,0.59450000524520874,0 +coef_logTimeWindowOverlapChild_disc,-0.18532337973096763,-0.18532355001439704,0.11620000004768372,0 +coef_logTimeWindowOverlapChild_maint,-0.010727634274141281,-0.010727832451482898,0.17599999904632568,0 +coef_logTimeWindowOverlapChild_shopping,1.0468422941706472,1.0468423276707255,0.14159999787807465,0 +coef_moreCarsThanWorkers_eatout,0.076914343292072182,0.076914576167953802,0.38249999284744263,0 +coef_moreCarsThanWorkers_shopping,-0.59564874997193351,-0.59564894067055596,-0.30270001292228699,0 +coef_nonWorkerHomeMaxThree_zero_tours,-0.17003939484477312,-0.17003948323362453,1.5140000581741333,0 +coef_nonWorkerNonMandMaxThree_disc,-0.13432804559300732,-0.13432811971898589,0.28709998726844788,0 +coef_nonWorkerNonMandMaxThree_eatout,-0.33401066087685138,-0.33401068347396745,0.18199999630451202,0 +coef_nonWorkerNonMandMaxThree_maint,0.37323111519137453,0.37323093350637826,0.4643000066280365,0 +coef_nonWorkerNonMandMaxThree_shopping,0.49264301488042911,0.49264292085137712,0.70779997110366821,0 +coef_nonWorkerNonMandMaxThree_visiting,-0.36437091579618403,-0.36437083429284089,0.54750001430511475,0 +coef_partTimeHomeMaxThree_zero_tours,1.7312454999054936,1.7312459096132369,1.4470000267028809,0 +coef_partTimeNonMandMaxThree_disc,0.23705977049445798,0.23705989380574119,0.49790000915527344,0 +coef_partTimeNonMandMaxThree_eatout,-5.6531002354715127,-5.6530850270781112,0.37650001049041748,0 +coef_partTimeNonMandMaxThree_maint,0.11494946476265139,0.11494961705361134,0.24519999325275421,0 +coef_partTimeNonMandMaxThree_shopping,-0.20746715181319589,-0.20746695386959577,0.18659999966621399,0 +coef_partTimeNonMandMaxThree_visiting,0.32137505891849261,0.32137524780407384,0.13320000469684601,0 +coef_preDrivingAgeMandMaxThree_disc,0.60675129362611258,0.60675111363025258,0.38620001077651978,0 +coef_preDrivingAgeMandMaxThree_maint,0.043178367483864805,0.043178519613054106,0.22990000247955322,0 +coef_preDrivingHomeMaxThree_preschool_and_school_zero_tours,-0.25725057670419188,-0.25725026315677951,0.52999997138977051,0 +coef_preDrivingNonMandMaxThree_disc,0.49100040690235336,0.49100032365079044,0.53310000896453857,0 +coef_preDrivingNonMandMaxThree_eatout,-3.5007131527538413,-3.5007016569353477,0.38510000705718994,0 +coef_preDrivingNonMandMaxThree_maint,-0.47732053847248312,-0.47732051937471986,0.64819997549057007,0 +coef_preDrivingNonMandMaxThree_shopping,-0.0012986266652305054,-0.0012987293702714738,0.54739999771118164,0 +coef_preDrivingNonMandMaxThree_visiting,-1.6293887060843797,-1.6293896015520914,0.60079997777938843,0 +coef_retireeHomeMaxThree_zero_tours,0.34966179334551972,0.34966146316807412,0.60530000925064087,0 +coef_retireeNonMandMaxThree_disc,0.59640088460538709,0.59640107482430083,0.61360001564025879,0 +coef_retireeNonMandMaxThree_eatout,0.3499795761045531,0.34997959789937416,0.42640000581741333,0 +coef_retireeNonMandMaxThree_maint,0.93716736904164089,0.93716740436084434,0.90499997138977051,0 +coef_retireeNonMandMaxThree_shopping,0.9325100820582326,0.93251039206065178,0.94099998474121094,0 +coef_retireeNonMandMaxThree_visiting,0.1668284024031404,0.16682870749583406,0.55790001153945923,0 +coef_timeWindowOverlapAdultChild_visiting,0.13881492846958488,0.13881496732242621,0.025599999353289604,0 +coef_timeWindowOverlapAdult_visiting,0.11182157577140597,0.11182154572794807,0.059599999338388443,0 +coef_timeWindowOverlapChild_visiting,-0.059018654499507453,-0.05901868676849447,0.0092000002041459084,0 +coef_universityHomeMaxThree_univ_and_driving_zero_tours,-0.3806558129102493,-0.38065581874970073,0.56849998235702515,0 +coef_universityNonMandMaxThree_disc,-0.15852221488464341,-0.15852211136829161,0.75459998846054077,0 +coef_universityNonMandMaxThree_eatout,-4.1215214477423272,-4.1215091850562358,0.40970000624656677,0 +coef_universityNonMandMaxThree_maint,-0.46680029014718827,-0.46680012462022286,0.26429998874664307,0 +coef_universityNonMandMaxThree_shopping,1.1067199892366495,1.1067201908411548,0.76480001211166382,0 +coef_universityNonMandMaxThree_visiting,-5.6416612820161021,-5.6416452449924739,0.28090000152587891,0 +coef_walkRetailAccessibility_eatout,-0.035796009413743196,-0.035795796225119095,0.061999998986721039,0 +coef_zeroAutomobiles_disc,-0.52859607918243423,-0.52859621558900038,-0.9089999794960022,0 +coef_zeroAutomobiles_visiting,-5.8405847342282176,-5.8405705977466207,-0.98000001907348633,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_participation_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_participation_SLSQP_.csv index c60173aa06..b9a0635d75 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_participation_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_joint_tour_participation_SLSQP_.csv @@ -1,60 +1,60 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_adult_log_of_max_window_overlap_with_a_child_mixed,4.5940415543572257,2.1890000000000001,0,,,4.5940415543572257 -coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party,1.6916936883427531,0.84360000000000002,0,,,1.6916936883427531 -coef_adult_more_automobiles_than_workers_adult_only_party,0.31139003577268975,-0.21329999999999999,0,,,0.31139003577268975 -coef_adult_more_automobiles_than_workers_mixed_party,-1.8020541380547712,-0.60309999999999997,0,,,-1.8020541380547712 -coef_adult_number_of_joint_tours_adult_only,-2.1332672475172423,-0.32419999999999999,0,,,-2.1332672475172423 -coef_adult_number_of_joint_tours_mixed,-12.011984079880781,-0.3584,0,,,-12.011984079880781 -coef_adult_number_of_other_adults_in_the_household_adults_only_party,0,0,0,0,0,0 -coef_adult_number_of_other_adults_in_the_household_mixed_party,0,0,0,0,0,0 -coef_child_log_of_max_window_overlap_with_a_child_child,1.296,1.296,0,,,1.296 -coef_child_log_of_max_window_overlap_with_an_adult_mixed,1.538,1.538,0,,,1.538 -coef_child_more_automobiles_than_workers_child_only_party,-0.4214,-0.4214,0,,,-0.4214 -coef_child_more_automobiles_than_workers_mixed_party,-1.5765541380547705,-0.37759999999999999,0,,,-1.5765541380547705 -coef_child_number_of_joint_tours_child_only,25.834459257330721,0.1047,0,,,25.834459257330721 -coef_child_number_of_joint_tours_mixed,89.315973889991952,-0.50890000000000002,0,,,89.315973889991952 -coef_child_number_of_other_children_in_the_household_child_only_party,0,0,0,0,0,0 -coef_child_number_of_other_children_in_the_household_mixed,0,0,0,0,0,0 -coef_child_too_young_for_school_children_only_party,-2.786,-2.786,0,,,-2.786 -coef_child_too_young_for_school_mixed_party,12.484734556961985,-1.893,0,,,12.484734556961985 -coef_child_too_young_for_school_specific_to_discretionary_joint_tours,0.12839999999999999,0.12839999999999999,0,,,0.12839999999999999 -coef_child_too_young_for_school_specific_to_eating_out_joint_tours,0.65890000000000004,0.65890000000000004,0,,,0.65890000000000004 -coef_driving_age_student_children_only_party,-1.8220000000000001,-1.8220000000000001,0,,,-1.8220000000000001 -coef_driving_age_student_mixed_party,-131.65706593958799,-1.353,0,,,-131.65706593958799 -coef_driving_age_student_specific_to_discretionary_joint_tours,-0.66749999999999998,-0.66749999999999998,0,,,-0.66749999999999998 -coef_driving_age_student_specific_to_eating_out_joint_tours,2.3439999999999999,2.3439999999999999,0,,,2.3439999999999999 -coef_dummy_for_high_income_for_adult_in_adult_party,0.1318998436337066,-0.16819999999999999,0,,,0.1318998436337066 -coef_dummy_for_high_income_for_adult_in_mixed_party,-0.38289361131114391,-0.02613,0,,,-0.38289361131114391 -coef_dummy_for_high_income_for_child_in_children_party,-0.56189999999999996,-0.56189999999999996,0,,,-0.56189999999999996 -coef_dummy_for_high_income_for_child_in_mixed_party,-0.50956361131120043,-0.15279999999999999,0,,,-0.50956361131120043 -coef_full_time_worker_mixed_party,-50.846659765191049,-3.5659999999999998,0,,,-50.846659765191049 -coef_full_time_worker_mixed_party_not,0.5,0.5,0,0.5,0.5,0.5 -coef_full_time_worker_specific_to_discretionary_joint_tours,0.43919999999999998,0.43919999999999998,0,,,0.43919999999999998 -coef_full_time_worker_specific_to_discretionary_joint_tours_not,0.5,0.5,0,0.5,0.5,0.5 -coef_full_time_worker_specific_to_eating_out_joint_tours,0.7157,0.7157,0,,,0.7157 -coef_full_time_worker_specific_to_eating_out_joint_tours_not,0.5,0.5,0,0.5,0.5,0.5 -coef_household_in_suburban_area_adult_adult_only_party,0,0,0,0,0,0 -coef_household_in_suburban_area_adult_mixed_party,-0.060069999999999998,-0.060069999999999998,0,,,-0.060069999999999998 -coef_household_in_suburban_area_child_child_only_party,0,0,0,0,0,0 -coef_household_in_suburban_area_child_mixed_party,0,0,0,0,0,0 -coef_household_in_urban_area_adult_adult_only_party,0,0,0,0,0,0 -coef_household_in_urban_area_adult_mixed_party,55.591278075644887,-0.13700000000000001,0,,,55.591278075644887 -coef_household_in_urban_area_child_child_only_party,26.939759257330742,1.21,0,,,26.939759257330742 -coef_household_in_urban_area_child_mixed_party,-101.1258709375923,0.62649999999999995,0,,,-101.1258709375923 -coef_non_worker_adults_only_party,-4.0792805161736174,-3.1640000000000001,0,,,-4.0792805161736174 -coef_non_worker_mixed_party,76.628151288066263,0.71519999999999995,0,,,76.628151288066263 -coef_non_worker_specific_to_discretionary_joint_tours,-0.1835,-0.1835,0,,,-0.1835 -coef_non_worker_specific_to_eating_out_joint_tours,0.16170000000000001,0.16170000000000001,0,,,0.16170000000000001 -coef_part_time_worker_adults_only_party,-3.2478258169504657,-3.5659999999999998,0,,,-3.2478258169504657 -coef_part_time_worker_adults_only_party_not,0.5,0.5,0,0.5,0.5,0.5 -coef_part_time_worker_mixed_party,70.07529311830892,-0.36549999999999999,0,,,70.07529311830892 -coef_part_time_worker_specific_to_discretionary_joint_tours,0.28499999999999998,0.28499999999999998,0,,,0.28499999999999998 -coef_part_time_worker_specific_to_eating_out_joint_tours,2.1880000000000002,2.1880000000000002,0,,,2.1880000000000002 -coef_pre_driving_age_student_children_only_party,25.008059257330711,-0.72170000000000001,0,,,25.008059257330711 -coef_pre_driving_age_student_mixed_party,12.421960445033344,-1.752,0,,,12.421960445033344 -coef_pre_driving_age_student_specific_to_discretionary_joint_tours,0.66259999999999997,0.66259999999999997,0,,,0.66259999999999997 -coef_pre_driving_age_student_specific_to_eating_out_joint_tours,1.391,1.391,0,,,1.391 -coef_unavailable,-999,-999,0,-999,-999,-999 -coef_university_student_mixed_party,-52.255368272022992,-3.0409999999999999,0,,,-52.255368272022992 -coef_university_student_specific_to_discretionary_joint_tours,0,0,0,0,0,0 -coef_university_student_specific_to_eating_out_joint_tours,-0.81999999999999995,-0.81999999999999995,0,,,-0.81999999999999995 +param_name,value,best,initvalue,nullvalue +coef_adult_log_of_max_window_overlap_with_a_child_mixed,4.5951782780582482,4.5951781033354839,2.1889998912811279,0 +coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party,1.6633592801800163,1.6633593140698184,0.84359997510910034,0 +coef_adult_more_automobiles_than_workers_adult_only_party,0.31066873854811811,0.31066870271882263,-0.21330000460147858,0 +coef_adult_more_automobiles_than_workers_mixed_party,-1.8032448224599575,-1.803244785082267,-0.6031000018119812,0 +coef_adult_number_of_joint_tours_adult_only,-2.0764783287527235,-2.0764784513924197,-0.32420000433921814,0 +coef_adult_number_of_joint_tours_mixed,-4.6560544367999661,-4.6560542069402064,-0.35839998722076416,0 +coef_adult_number_of_other_adults_in_the_household_adults_only_party,0,0,0,0 +coef_adult_number_of_other_adults_in_the_household_mixed_party,0,0,0,0 +coef_child_log_of_max_window_overlap_with_a_child_child,1.2960000038146973,1.2960000038146973,1.2960000038146973,0 +coef_child_log_of_max_window_overlap_with_an_adult_mixed,1.5379999876022339,1.5379999876022339,1.5379999876022339,0 +coef_child_more_automobiles_than_workers_child_only_party,-0.42140001058578491,-0.42140001058578491,-0.42140001058578491,0 +coef_child_more_automobiles_than_workers_mixed_party,-1.5777448348577667,-1.5777447974800762,-0.37760001420974731,0 +coef_child_number_of_joint_tours_child_only,13.579540492742831,13.579540463017146,0.1046999990940094,0 +coef_child_number_of_joint_tours_mixed,20.015257060305416,20.01525831304766,-0.508899986743927,0 +coef_child_number_of_other_children_in_the_household_child_only_party,0,0,0,0 +coef_child_number_of_other_children_in_the_household_mixed,0,0,0,0 +coef_child_too_young_for_school_children_only_party,-2.7860000133514404,-2.7860000133514404,-2.7860000133514404,0 +coef_child_too_young_for_school_mixed_party,8.3656227270333634,8.3656222958055366,-1.8930000066757202,0 +coef_child_too_young_for_school_specific_to_discretionary_joint_tours,0.12839999794960022,0.12839999794960022,0.12839999794960022,0 +coef_child_too_young_for_school_specific_to_eating_out_joint_tours,0.65890002250671387,0.65890002250671387,0.65890002250671387,0 +coef_driving_age_student_children_only_party,-1.8220000267028809,-1.8220000267028809,-1.8220000267028809,0 +coef_driving_age_student_mixed_party,-50,-50,-1.3530000448226929,0 +coef_driving_age_student_specific_to_discretionary_joint_tours,-0.66750001907348633,-0.66750001907348633,-0.66750001907348633,0 +coef_driving_age_student_specific_to_eating_out_joint_tours,2.3440001010894775,2.3440001010894775,2.3440001010894775,0 +coef_dummy_for_high_income_for_adult_in_adult_party,0.12621381061004386,0.12621385992786305,-0.16820000112056732,0 +coef_dummy_for_high_income_for_adult_in_mixed_party,-0.38299804175110763,-0.38299804898262102,-0.026130000129342079,0 +coef_dummy_for_high_income_for_child_in_children_party,-0.56190001964569092,-0.56190001964569092,-0.56190001964569092,0 +coef_dummy_for_high_income_for_child_in_mixed_party,-0.50966803537514371,-0.5096680426066571,-0.15279999375343323,0 +coef_full_time_worker_mixed_party,-18.56632640293509,-18.566326638673267,-3.5659999847412109,0 +coef_full_time_worker_mixed_party_not,0.5,0.5,0.5,0 +coef_full_time_worker_specific_to_discretionary_joint_tours,0.4392000138759613,0.4392000138759613,0.4392000138759613,0 +coef_full_time_worker_specific_to_discretionary_joint_tours_not,0.5,0.5,0.5,0 +coef_full_time_worker_specific_to_eating_out_joint_tours,0.71569997072219849,0.71569997072219849,0.71569997072219849,0 +coef_full_time_worker_specific_to_eating_out_joint_tours_not,0.5,0.5,0.5,0 +coef_household_in_suburban_area_adult_adult_only_party,0,0,0,0 +coef_household_in_suburban_area_adult_mixed_party,-0.06007000058889389,-0.06007000058889389,-0.06007000058889389,0 +coef_household_in_suburban_area_child_child_only_party,0,0,0,0 +coef_household_in_suburban_area_child_mixed_party,0,0,0,0 +coef_household_in_urban_area_adult_adult_only_party,0,0,0,0 +coef_household_in_urban_area_adult_mixed_party,15.95349033775349,15.953490704515609,-0.13699999451637268,0 +coef_household_in_urban_area_child_child_only_party,14.684840531795903,14.684840502070218,1.2100000381469727,0 +coef_household_in_urban_area_child_mixed_party,-27.706374555887564,-27.706375390127885,0.62650001049041748,0 +coef_non_worker_adults_only_party,-4.0512566140539823,-4.0512566665328293,-3.1640000343322754,0 +coef_non_worker_mixed_party,24.232596176450738,24.232596639515961,0.71520000696182251,0 +coef_non_worker_specific_to_discretionary_joint_tours,-0.1835000067949295,-0.1835000067949295,-0.1835000067949295,0 +coef_non_worker_specific_to_eating_out_joint_tours,0.16169999539852142,0.16169999539852142,0.16169999539852142,0 +coef_part_time_worker_adults_only_party,-3.2257432923239446,-3.2257432422956698,-3.5659999847412109,0 +coef_part_time_worker_adults_only_party_not,0.5,0.5,0.5,0 +coef_part_time_worker_mixed_party,22.126834905159047,22.126835266655284,-0.36550000309944153,0 +coef_part_time_worker_specific_to_discretionary_joint_tours,0.28499999642372131,0.28499999642372131,0.28499999642372131,0 +coef_part_time_worker_specific_to_eating_out_joint_tours,2.187999963760376,2.187999963760376,2.187999963760376,0 +coef_pre_driving_age_student_children_only_party,12.753140480965085,12.7531404512394,-0.72170001268386841,0 +coef_pre_driving_age_student_mixed_party,8.3035034193009718,8.3035030162498487,-1.7519999742507935,0 +coef_pre_driving_age_student_specific_to_discretionary_joint_tours,0.66259998083114624,0.66259998083114624,0.66259998083114624,0 +coef_pre_driving_age_student_specific_to_eating_out_joint_tours,1.3910000324249268,1.3910000324249268,1.3910000324249268,0 +coef_unavailable,-999,-999,-999,0 +coef_university_student_mixed_party,-19.976674136225505,-19.976674380042439,-3.0409998893737793,0 +coef_university_student_specific_to_discretionary_joint_tours,0,0,0,0 +coef_university_student_specific_to_eating_out_joint_tours,-0.81999999284744263,-0.81999999284744263,-0.81999999284744263,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_BHHH_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_BHHH_.csv index 3f5af851e4..2c5dc3ee14 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_BHHH_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_BHHH_.csv @@ -1,54 +1,54 @@ -,value,initvalue,nullvalue,minimum,maximum,best -0,0,0,0,0,0,0 -coef_can_walk_to_work_and_school,0.072221053570087068,0.1391,0,,,0.072221053570087068 -coef_can_walk_to_work_school2,1.368189229871656,0.71140000000000003,0,,,1.368189229871656 -coef_can_walk_to_work_work2,0.6511271300905388,0.52680000000000005,0,,,0.6511271300905388 -coef_driving_age_child_school2_asc,-10.76072459479807,-3.1360000000000001,0,,,-10.76072459479807 -coef_driving_age_child_work_and_school_asc,-58.117517308879499,-4.4362000000000004,0,,,-58.117517308879499 -coef_female_school1,0.2474431563125136,0.15920000000000001,0,,,0.2474431563125136 -coef_female_school2,-0.3012348896462545,0.114,0,,,-0.3012348896462545 -coef_female_work1,-2.2434862184806872,0.17369999999999999,0,,,-2.2434862184806872 -coef_female_work2,-0.3875204207258891,-0.22550000000000001,0,,,-0.3875204207258891 -coef_female_work_and_school,-3.2183973184973143,-0.34420000000000001,0,,,-3.2183973184973143 -coef_few_cars_than_drivers_school2,-0.86352025026207002,-0.57589999999999997,0,,,-0.86352025026207002 -coef_ft_worker_work2_asc,-15.631616769904962,-3.3780999999999999,0,,,-15.631616769904962 -coef_hh_income_gt_50k_school1,0.034700030521069632,0.034700000000000002,0,,,0.034700030521069632 -coef_hh_income_gt_50k_student_work_and_school,-0.92170661372181706,-0.0528,0,,,-0.92170661372181706 -coef_hh_income_gt_50k_work,-1.4190912531326889,-0.0528,0,,,-1.4190912531326889 -coef_hh_income_gt_50k_worker_work_and_school,0.034699971829526256,0.034700000000000002,0,,,0.034699971829526256 -coef_home_urban_school1,-0.13610000344523163,-0.1361,0,,,-0.13610000344523163 -coef_home_urban_school2,-11.830881608079386,0.317,0,,,-11.830881608079386 -coef_home_urban_work1,24.254352793957736,-0.28310000000000002,0,,,24.254352793957736 -coef_home_urban_work2,12.738503782102926,0.23080000000000001,0,,,12.738503782102926 -coef_home_urban_work_and_school,-2.9755482471380152,-0.35089999999999999,0,,,-2.9755482471380152 -coef_no_cars_in_hh_school2,-0.6201622889361833,-1.413,0,,,-0.6201622889361833 -coef_no_cars_in_hh_work2,-0.72588656952288921,-1.306,0,,,-0.72588656952288921 -coef_no_cars_in_hh_work_and_school,-0.7768760244151115,-1.302,0,,,-0.7768760244151115 -coef_non_family_hh_category1,-0.25000005548208493,-0.25,0,,,-0.25000005548208493 -coef_non_family_hh_category2,-18.224089926229215,-0.1792,0,,,-18.224089926229215 -coef_non_student_goes_to_school,3.883000012592801,3.883,0,,,3.883000012592801 -coef_num_non_workers_in_hh_school1,0.25739997881575821,0.25740000000000002,0,,,0.25739997881575821 -coef_num_preschool_in_hh_school1,-0.13350001004490689,-0.13350000000000001,0,,,-0.13350001004490689 -coef_num_preschool_in_hh_school2,0.35689505282246176,-0.55769999999999997,0,,,0.35689505282246176 -coef_num_preschool_in_hh_work1,-2.9320917687605954,0.21909999999999999,0,,,-2.9320917687605954 -coef_num_preschool_in_hh_work2,0.22500429804995042,-0.14779999999999999,0,,,0.22500429804995042 -coef_num_preschool_in_hh_work_and_school,-291.65982798845073,-0.12509999999999999,0,,,-291.65982798845073 -coef_num_under_16_not_at_school_school2,-0.63862137361032489,0.086599999999999996,0,,,-0.63862137361032489 -coef_num_under_16_not_at_school_work2,-0.11866867638023079,0.1804,0,,,-0.11866867638023079 -coef_num_under_16_not_at_school_work_and_school,-18.884178394306563,-0.19550000000000001,0,,,-18.884178394306563 -coef_pre_driving_age_child_school2_asc,7.0553066040769048,-3.9702999999999999,0,,,7.0553066040769048 -coef_pt_worker_work2_asc,-14.856919777024819,-3.0476000000000001,0,,,-14.856919777024819 -coef_round_trip_auto_time_to_work_school2,0.064396584422453232,-0.0033999999999999998,0,,,0.064396584422453232 -coef_round_trip_auto_time_to_work_work2,-0.025902525682352791,-0.0035000000000000001,0,,,-0.025902525682352791 -coef_round_trip_auto_time_to_work_work_and_school,-0.02180773780300839,-0.0030999999999999999,0,,,-0.02180773780300839 -coef_student_employed,61.497344836308677,3.0139999999999998,0,,,61.497344836308677 -coef_unavailable,-999,-999,0,-999,-999,-999 -coef_under_35_school1,0.7218,0.7218,0,,,0.7218 -coef_under_35_school2,27.445525973793494,1.2749999999999999,0,,,27.445525973793494 -coef_under_35_work1,1.0375724814647256,-0.46289999999999998,0,,,1.0375724814647256 -coef_under_35_work2,-0.25382084017500217,-0.13750000000000001,0,,,-0.25382084017500217 -coef_under_35_work_and_school,2.256932391854527,0.97609999999999997,0,,,2.256932391854527 -coef_univ_school2_asc,-19.291663549848391,-3.7429000000000001,0,,,-19.291663549848391 -coef_univ_work1_asc,26.703452792641354,2.1659999999999999,0,,,26.703452792641354 -coef_univ_work2_asc,35.174040311644283,-1.3965000000000001,0,,,35.174040311644283 -coef_univ_work_and_school_asc,51.163969004277625,0.10730000000000001,0,,,51.163969004277625 +param_name,value,best,initvalue,nullvalue +0,0,0,0,0 +coef_can_walk_to_work_and_school,0.071963467898163519,0.071963467898163519,0.13910000026226044,0 +coef_can_walk_to_work_school2,1.3682146498522929,1.3682146498522929,0.71139997243881226,0 +coef_can_walk_to_work_work2,0.65113800717686054,0.65113800717686054,0.52679997682571411,0 +coef_driving_age_child_school2_asc,-10.760724267208685,-10.760724267208685,-3.1359999179840088,0 +coef_driving_age_child_work_and_school_asc,-58.117542193724134,-58.117542193724134,-4.4362001419067383,0 +coef_female_school1,0.24693966666339068,0.24693966666339068,0.15919999778270721,0 +coef_female_school2,-0.30156175637229587,-0.30156175637229587,0.11400000005960464,0 +coef_female_work1,-2.2432731743178365,-2.2432731743178365,0.1737000048160553,0 +coef_female_work2,-0.38747695440528995,-0.38747695440528995,-0.22550000250339508,0 +coef_female_work_and_school,-3.2184568767600301,-3.2184568767600301,-0.34419998526573181,0 +coef_few_cars_than_drivers_school2,-0.86287494081897043,-0.86287494081897043,-0.57590001821517944,0 +coef_ft_worker_work2_asc,-15.631596564333391,-15.631596564333391,-3.3780999183654785,0 +coef_hh_income_gt_50k_school1,0.034699998903999218,0.034699998903999218,0.034699998795986176,0 +coef_hh_income_gt_50k_student_work_and_school,-0.92151889984559776,-0.92151889984559776,-0.052799999713897705,0 +coef_hh_income_gt_50k_work,-1.4188850438199954,-1.4188850438199954,-0.052799999713897705,0 +coef_hh_income_gt_50k_worker_work_and_school,0.034699998835916637,0.034699998835916637,0.034699998795986176,0 +coef_home_urban_school1,-0.1360999941739981,-0.1360999941739981,-0.13609999418258667,0 +coef_home_urban_school2,-11.831044462083096,-11.831044462083096,0.31700000166893005,0 +coef_home_urban_work1,24.254289912474832,24.254289912474832,-0.28310000896453857,0 +coef_home_urban_work2,12.738486792776087,12.738486792776087,0.23080000281333923,0 +coef_home_urban_work_and_school,-2.9754582133928946,-2.9754582133928946,-0.35089999437332153,0 +coef_no_cars_in_hh_school2,-0.62062284302473281,-0.62062284302473281,-1.4129999876022339,0 +coef_no_cars_in_hh_work2,-0.72590052527502258,-0.72590052527502258,-1.3059999942779541,0 +coef_no_cars_in_hh_work_and_school,-0.77649868370275865,-0.77649868370275865,-1.3020000457763672,0 +coef_non_family_hh_category1,-0.25000000001603168,-0.25000000001603168,-0.25,0 +coef_non_family_hh_category2,-18.224086954408719,-18.224086954408719,-0.17919999361038208,0 +coef_non_student_goes_to_school,3.8829998970263762,3.8829998970263762,3.8829998970031738,0 +coef_num_non_workers_in_hh_school1,0.2574000060601766,0.2574000060601766,0.25740000605583191,0 +coef_num_preschool_in_hh_school1,-0.1334999948664459,-0.1334999948664459,-0.13349999487400055,0 +coef_num_preschool_in_hh_school2,0.35679291623910225,0.35679291623910225,-0.55769997835159302,0 +coef_num_preschool_in_hh_work1,-2.9311650176345023,-2.9311650176345023,0.21909999847412109,0 +coef_num_preschool_in_hh_work2,0.22506526227617765,0.22506526227617765,-0.14779999852180481,0 +coef_num_preschool_in_hh_work_and_school,-1120.7076517335183,-1120.7076517335183,-0.12510000169277191,0 +coef_num_under_16_not_at_school_school2,-0.63850525564048144,-0.63850525564048144,0.08659999817609787,0 +coef_num_under_16_not_at_school_work2,-0.11879303600656704,-0.11879303600656704,0.18039999902248383,0 +coef_num_under_16_not_at_school_work_and_school,-72.572511675156974,-72.572511675156974,-0.19550000131130219,0 +coef_pre_driving_age_child_school2_asc,7.0553915333001287,7.0553915333001287,-3.9702999591827393,0 +coef_pt_worker_work2_asc,-14.85688697195045,-14.85688697195045,-3.0476000308990479,0 +coef_round_trip_auto_time_to_work_school2,0.064402441888329359,0.064402441888329359,-0.0034000000450760126,0 +coef_round_trip_auto_time_to_work_work2,-0.025903740882998762,-0.025903740882998762,-0.0035000001080334187,0 +coef_round_trip_auto_time_to_work_work_and_school,-0.021807011903415791,-0.021807011903415791,-0.0031000000890344381,0 +coef_student_employed,61.49730201724514,61.49730201724514,3.0139999389648438,0 +coef_unavailable,-999,-999,-999,0 +coef_under_35_school1,0.72180002927780151,0.72180002927780151,0.72180002927780151,0 +coef_under_35_school2,27.44527439728251,27.44527439728251,1.2749999761581421,0 +coef_under_35_work1,1.0377437873346973,1.0377437873346973,-0.46290001273155212,0 +coef_under_35_work2,-0.25384424363084357,-0.25384424363084357,-0.13750000298023224,0 +coef_under_35_work_and_school,2.2567986605803032,2.2567986605803032,0.97610002756118774,0 +coef_univ_school2_asc,-19.29191150330508,-19.29191150330508,-3.7428998947143555,0 +coef_univ_work1_asc,26.703389810868742,26.703389810868742,2.1659998893737793,0 +coef_univ_work2_asc,35.173970384221057,35.173970384221057,-1.3964999914169312,0 +coef_univ_work_and_school_asc,51.164083831710279,51.164083831710279,0.10729999840259552,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_SLSQP_.csv index fd8238225b..457583ab1e 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_SLSQP_.csv @@ -1,54 +1,54 @@ -,value,initvalue,nullvalue,minimum,maximum,best -0,0,0,0,0,0,0 -coef_can_walk_to_work_and_school,0.071630314724926147,0.1391,0,,,0.071630314724926147 -coef_can_walk_to_work_school2,1.3680922080710298,0.71140000000000003,0,,,1.3680922080710298 -coef_can_walk_to_work_work2,0.65112015867036332,0.52680000000000005,0,,,0.65112015867036332 -coef_driving_age_child_school2_asc,-13.067731116342266,-3.1360000000000001,0,,,-13.067731116342266 -coef_driving_age_child_work_and_school_asc,-12.605997463132249,-4.4362000000000004,0,,,-12.605997463132249 -coef_female_school1,0.24708609009193822,0.15920000000000001,0,,,0.24708609009193822 -coef_female_school2,-0.30133903622407632,0.114,0,,,-0.30133903622407632 -coef_female_work1,-2.2427478904369504,0.17369999999999999,0,,,-2.2427478904369504 -coef_female_work2,-0.38741093683095679,-0.22550000000000001,0,,,-0.38741093683095679 -coef_female_work_and_school,-3.2182798790112783,-0.34420000000000001,0,,,-3.2182798790112783 -coef_few_cars_than_drivers_school2,-0.86245057209463027,-0.57589999999999997,0,,,-0.86245057209463027 -coef_ft_worker_work2_asc,-5.5179331616722695,-3.3780999999999999,0,,,-5.5179331616722695 -coef_hh_income_gt_50k_school1,0.034700000000000002,0.034700000000000002,0,,,0.034700000000000002 -coef_hh_income_gt_50k_student_work_and_school,-0.92117498986723134,-0.0528,0,,,-0.92117498986723134 -coef_hh_income_gt_50k_work,-1.418550817944235,-0.0528,0,,,-1.418550817944235 -coef_hh_income_gt_50k_worker_work_and_school,0.034700000000000002,0.034700000000000002,0,,,0.034700000000000002 -coef_home_urban_school1,-0.1361,-0.1361,0,,,-0.1361 -coef_home_urban_school2,-8.4556148704436787,0.317,0,,,-8.4556148704436787 -coef_home_urban_work1,4.0267960749153291,-0.28310000000000002,0,,,4.0267960749153291 -coef_home_urban_work2,2.6248540229034232,0.23080000000000001,0,,,2.6248540229034232 -coef_home_urban_work_and_school,-0.44707001996924778,-0.35089999999999999,0,,,-0.44707001996924778 -coef_no_cars_in_hh_school2,-0.62046508539739775,-1.413,0,,,-0.62046508539739775 -coef_no_cars_in_hh_work2,-0.72596662468976358,-1.306,0,,,-0.72596662468976358 -coef_no_cars_in_hh_work_and_school,-0.77593437523044428,-1.302,0,,,-0.77593437523044428 -coef_non_family_hh_category1,-0.25,-0.25,0,,,-0.25 -coef_non_family_hh_category2,5.0007710032851715,-0.1792,0,,,5.0007710032851715 -coef_non_student_goes_to_school,3.883,3.883,0,,,3.883 -coef_num_non_workers_in_hh_school1,0.25740000000000002,0.25740000000000002,0,,,0.25740000000000002 -coef_num_preschool_in_hh_school1,-0.13350000000000001,-0.13350000000000001,0,,,-0.13350000000000001 -coef_num_preschool_in_hh_school2,0.35665962262224188,-0.55769999999999997,0,,,0.35665962262224188 -coef_num_preschool_in_hh_work1,-2.9305005867030882,0.21909999999999999,0,,,-2.9305005867030882 -coef_num_preschool_in_hh_work2,0.22517317861058084,-0.14779999999999999,0,,,0.22517317861058084 -coef_num_preschool_in_hh_work_and_school,-29.197568875282681,-0.12509999999999999,0,,,-29.197568875282681 -coef_num_under_16_not_at_school_school2,-0.63829340447675476,0.086599999999999996,0,,,-0.63829340447675476 -coef_num_under_16_not_at_school_work2,-0.11899114846640058,0.1804,0,,,-0.11899114846640058 -coef_num_under_16_not_at_school_work_and_school,-15.357906680125023,-0.19550000000000001,0,,,-15.357906680125023 -coef_pre_driving_age_child_school2_asc,3.6797262862761189,-3.9702999999999999,0,,,3.6797262862761189 -coef_pt_worker_work2_asc,-4.7432419645081501,-3.0476000000000001,0,,,-4.7432419645081501 -coef_round_trip_auto_time_to_work_school2,0.064410816444162883,-0.0033999999999999998,0,,,0.064410816444162883 -coef_round_trip_auto_time_to_work_work2,-0.025905460423305656,-0.0035000000000000001,0,,,-0.025905460423305656 -coef_round_trip_auto_time_to_work_work_and_school,-0.021803756470739271,-0.0030999999999999999,0,,,-0.021803756470739271 -coef_student_employed,13.457255204029515,3.0139999999999998,0,,,13.457255204029515 -coef_unavailable,-999,-999,0,-999,-999,-999 -coef_under_35_school1,0.7218,0.7218,0,,,0.7218 -coef_under_35_school2,15.011164063565253,1.2749999999999999,0,,,15.011164063565253 -coef_under_35_work1,1.0382419681378368,-0.46289999999999998,0,,,1.0382419681378368 -coef_under_35_work2,-0.25387498090125782,-0.13750000000000001,0,,,-0.25387498090125782 -coef_under_35_work_and_school,2.2570354258963481,0.97609999999999997,0,,,2.2570354258963481 -coef_univ_school2_asc,-10.233810040377643,-3.7429000000000001,0,,,-10.233810040377643 -coef_univ_work1_asc,6.475896074915326,2.1659999999999999,0,,,6.475896074915326 -coef_univ_work2_asc,4.8330291490834876,-1.3965000000000001,0,,,4.8330291490834876 -coef_univ_work_and_school_asc,8.1809274431629717,0.10730000000000001,0,,,8.1809274431629717 +param_name,value,best,initvalue,nullvalue +0,0,0,0,0 +coef_can_walk_to_work_and_school,0.20132027468875283,0.20132027468479921,0.13910000026226044,0 +coef_can_walk_to_work_school2,0.96010731757888212,0.96010731757834789,0.71139997243881226,0 +coef_can_walk_to_work_work2,0.73122607984567289,0.73122607983903865,0.52679997682571411,0 +coef_driving_age_child_school2_asc,-5.7172473630323095,-5.7172473630089566,-3.1359999179840088,0 +coef_driving_age_child_work_and_school_asc,-4.4775478428522311,-4.477547842857807,-4.4362001419067383,0 +coef_female_school1,-1.1179750622419278,-1.117975062224638,0.15919999778270721,0 +coef_female_school2,-0.48952027651274382,-0.48952027650816798,0.11400000005960464,0 +coef_female_work1,-2.0511063704156607,-2.0511063703883035,0.1737000048160553,0 +coef_female_work2,-0.41490266839201562,-0.4149026683981944,-0.22550000250339508,0 +coef_female_work_and_school,-2.9966902230088177,-2.9966902229830907,-0.34419998526573181,0 +coef_few_cars_than_drivers_school2,-0.55452509049148058,-0.55452509048768461,-0.57590001821517944,0 +coef_ft_worker_work2_asc,-3.8025869871232629,-3.8025869871213596,-3.3780999183654785,0 +coef_hh_income_gt_50k_school1,0.034699998795986176,0.034699998795986176,0.034699998795986176,0 +coef_hh_income_gt_50k_student_work_and_school,-0.17920043049685666,-0.17920043049604578,-0.052799999713897705,0 +coef_hh_income_gt_50k_work,-0.66212675917984232,-0.66212675918375841,-0.052799999713897705,0 +coef_hh_income_gt_50k_worker_work_and_school,0.034699998795986176,0.034699998795986176,0.034699998795986176,0 +coef_home_urban_school1,-0.13609999418258667,-0.13609999418258667,-0.13609999418258667,0 +coef_home_urban_school2,-2.1094338222937941,-2.1094338222674192,0.31700000166893005,0 +coef_home_urban_work1,0.34863867027519652,0.34863867026166911,-0.28310000896453857,0 +coef_home_urban_work2,0.76429400769443512,0.76429400769779043,0.23080000281333923,0 +coef_home_urban_work_and_school,-0.33420724299781907,-0.33420724299927923,-0.35089999437332153,0 +coef_no_cars_in_hh_school2,-0.3281459638377332,-0.32814596385333328,-1.4129999876022339,0 +coef_no_cars_in_hh_work2,-0.66209007579299561,-0.66209007577665158,-1.3059999942779541,0 +coef_no_cars_in_hh_work_and_school,-0.92494433055696312,-0.92494433055322656,-1.3020000457763672,0 +coef_non_family_hh_category1,-0.25,-0.25,-0.25,0 +coef_non_family_hh_category2,0.49350779245951959,0.49350779245352627,-0.17919999361038208,0 +coef_non_student_goes_to_school,3.8829998970031738,3.8829998970031738,3.8829998970031738,0 +coef_num_non_workers_in_hh_school1,0.25740000605583191,0.25740000605583191,0.25740000605583191,0 +coef_num_preschool_in_hh_school1,-0.13349999487400055,-0.13349999487400055,-0.13349999487400055,0 +coef_num_preschool_in_hh_school2,0.73590985242441875,0.73590985242576534,-0.55769997835159302,0 +coef_num_preschool_in_hh_work1,-1.6486490740351119,-1.6486490740275117,0.21909999847412109,0 +coef_num_preschool_in_hh_work2,0.24670839988109913,0.2467083998803998,-0.14779999852180481,0 +coef_num_preschool_in_hh_work_and_school,-2.4290259678800297,-2.4290259678663575,-0.12510000169277191,0 +coef_num_under_16_not_at_school_school2,-0.91329132598172835,-0.9132913259601626,0.08659999817609787,0 +coef_num_under_16_not_at_school_work2,-0.11459202927007101,-0.11459202927135456,0.18039999902248383,0 +coef_num_under_16_not_at_school_work_and_school,-2.3336601463508013,-2.3336601463331874,-0.19550000131130219,0 +coef_pre_driving_age_child_school2_asc,-2.6428722793019959,-2.6428722793097204,-3.9702999591827393,0 +coef_pt_worker_work2_asc,-3.0303892540032376,-3.0303892539968387,-3.0476000308990479,0 +coef_round_trip_auto_time_to_work_school2,0.064069158794420475,0.064069158793510952,-0.0034000000450760126,0 +coef_round_trip_auto_time_to_work_work2,-0.020202184952509333,-0.020202184952801051,-0.0035000001080334187,0 +coef_round_trip_auto_time_to_work_work_and_school,-0.015315391311272412,-0.015315391311409078,-0.0031000000890344381,0 +coef_student_employed,4.6032016663231561,4.6032016663032218,3.0139999389648438,0 +coef_unavailable,-999,-999,-999,0 +coef_under_35_school1,0.72180002927780151,0.72180002927780151,0.72180002927780151,0 +coef_under_35_school2,2.1398332789937333,2.1398332789898835,1.2749999761581421,0 +coef_under_35_work1,1.1194222799903866,1.1194222799688391,-0.46290001273155212,0 +coef_under_35_work2,-0.24674628169467161,-0.24674628168879748,-0.13750000298023224,0 +coef_under_35_work_and_school,2.7433316694686765,2.7433316694426049,0.97610002756118774,0 +coef_univ_school2_asc,-4.9155139535095262,-4.9155139534987793,-3.7428998947143555,0 +coef_univ_work1_asc,2.797738568613517,2.7977385685999896,2.1659998893737793,0 +coef_univ_work2_asc,-0.45572969467386271,-0.45572969467880964,-1.3964999914169312,0 +coef_univ_work_and_school_asc,0.16534045072359432,0.16534045072771017,0.10729999840259552,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_SLSQP_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_SLSQP_loglike.csv index f22660c1eb..a593ed1541 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_SLSQP_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_mandatory_tour_frequency_SLSQP_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-434.77803538920688,-410.22015020484497 +0,-434.77803587138652,-412.67417109099858 diff --git a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_trip_mode_choice_SLSQP_.csv b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_trip_mode_choice_SLSQP_.csv index 706cb99d17..a54d7e8e1c 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_trip_mode_choice_SLSQP_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_simple_simulate_trip_mode_choice_SLSQP_.csv @@ -1,273 +1,273 @@ -,value,initvalue,nullvalue,minimum,maximum,best --999,-999,-999,-999,-999,-999,-999 -1,1,1,1,1,1,1 -coef_age010_trn,0.36055093747501515,0,0,,,0.36055093747501515 -coef_age1619_da,0.34452990003908374,0,0,,,0.34452990003908374 -coef_age16p_sr,-0.15188561974324261,0,0,,,-0.15188561974324261 -coef_bike_ASC_rh,-7,-7,0,-7,-7,-7 -coef_bike_ASC_walk_work,-2.6591723273807126,-1.8332999999999999,0,,,-2.6591723273807126 -coef_drive_transit_ASC_commuter_work,0.42650515313601794,0.4012,0,,,0.42650515313601794 -coef_drive_transit_ASC_express_work,-0.35539999999999999,-0.35539999999999999,0,,,-0.35539999999999999 -coef_drive_transit_ASC_ferry_work,0.52769999999999995,0.52769999999999995,0,,,0.52769999999999995 -coef_drive_transit_ASC_heavyrail_work,-11.994127899898398,0.3538,0,,,-11.994127899898398 -coef_drive_transit_ASC_lightrail_work,-10.300240827222716,0.46210000000000001,0,,,-10.300240827222716 -coef_drive_transit_ASC_rh,-162.17158272141376,-4.25,0,,,-162.17158272141376 -coef_hhsize1_sr,-0.89092943199297148,-0.73460000000000003,0,,,-0.89092943199297148 -coef_hhsize2_sr,0.039652734237525036,0,0,,,0.039652734237525036 -coef_ivt_work,-0.010154908820341358,-0.021999999999999999,0,,,-0.010154908820341358 -coef_joint_auto_ASC_rh_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_auto_ASC_sr2_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_auto_ASC_sr3p_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_auto_ASC_walk_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_bike_ASC_rh_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_bike_ASC_walk_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_drive_transit_ASC_commuter_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_drive_transit_ASC_express_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_drive_transit_ASC_ferry_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_drive_transit_ASC_heavyrail_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_drive_transit_ASC_lightrail_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_drive_transit_ASC_rh_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_ride_hail_ASC_sr2_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_ride_hail_ASC_sr3p_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_ride_hail_ASC_taxi_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_ride_hail_ASC_tnc_shared,0,0,0,,,0 -coef_joint_ride_hail_ASC_tnc_single_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_ride_hail_ASC_walk_transit,0,0,0,,,0 -coef_joint_ride_hail_ASC_walk_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_ASC_rh_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_commuter_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_express_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_ferry_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_heavyrail_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_lightrail_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_rh_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_sr2_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_sr3p_work_univ_school_escort_atwork,0,0,0,,,0 -coef_joint_walk_transit_ASC_walk_work_univ_school_escort_atwork,0,0,0,,,0 -coef_nest_AUTO,0.71999999999999997,0.71999999999999997,1,0.71999999999999997,0.71999999999999997,0.71999999999999997 -coef_nest_AUTO_DRIVEALONE,0.34999999999999998,0.34999999999999998,1,0.34999999999999998,0.34999999999999998,0.34999999999999998 -coef_nest_AUTO_SHAREDRIDE2,0.34999999999999998,0.34999999999999998,1,0.34999999999999998,0.34999999999999998,0.34999999999999998 -coef_nest_AUTO_SHAREDRIDE3,0.34999999999999998,0.34999999999999998,1,0.34999999999999998,0.34999999999999998,0.34999999999999998 -coef_nest_NONMOTORIZED,0.71999999999999997,0.71999999999999997,1,0.71999999999999997,0.71999999999999997,0.71999999999999997 -coef_nest_RIDEHAIL,0.35999999999999999,0.35999999999999999,1,0.35999999999999999,0.35999999999999999,0.35999999999999999 -coef_nest_TRANSIT,0.71999999999999997,0.71999999999999997,1,0.71999999999999997,0.71999999999999997,0.71999999999999997 -coef_nest_TRANSIT_DRIVEACCESS,0.5,0.5,1,0.5,0.5,0.5 -coef_nest_TRANSIT_WALKACCESS,0.5,0.5,1,0.5,0.5,0.5 -coef_ride_hail_ASC_sr2_work,-24.964152977906629,-6.1079999999999997,0,,,-24.964152977906629 -coef_ride_hail_ASC_sr3p_work_escort_shopping_othmaint_atwork,-29.66185425032911,-7,0,,,-29.66185425032911 -coef_ride_hail_ASC_taxi_work,-2.5195664524629127,-2.3849999999999998,0,,,-2.5195664524629127 -coef_ride_hail_ASC_tnc_shared,23.268241084943003,0,0,,,23.268241084943003 -coef_ride_hail_ASC_tnc_single_work,23.984210218237873,0.73499999999999999,0,,,23.984210218237873 -coef_ride_hail_ASC_walk_transit,22.114586690634976,0,0,,,22.114586690634976 -coef_ride_hail_ASC_walk_work,21.771187507152565,0.2858,0,,,21.771187507152565 -coef_sov_ASC_rh_work_atwork,-7,-7,0,-7,-7,-7 -coef_sov_ASC_sr2_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork,-999,-999,0,-999,-999,-999 -coef_sov_ASC_sr3p_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork,-999,-999,0,-999,-999,-999 -coef_sov_ASC_walk_work,-3.007257338441883,-0.83979999999999999,0,,,-3.007257338441883 -coef_sr2_ASC_rh_work_school_escort_shopping_eatout_othmaint_social_othdiscr_atwork,-7,-7,0,-7,-7,-7 -coef_sr2_ASC_sr2_work,0.19745747776996045,0.0149,0,,,0.19745747776996045 -coef_sr2_ASC_sr3p,-999,-999,0,-999,-999,-999 -coef_sr2_ASC_walk_work,-2.2229353369557856,0.126,0,,,-2.2229353369557856 -coef_sr3p_ASC_rh_work,-71.917699999999996,-71.917699999999996,0,,,-71.917699999999996 -coef_sr3p_ASC_sr2_work,-0.95395070192885023,-1.1956,0,,,-0.95395070192885023 -coef_sr3p_ASC_sr3p_work,0.0022823628108995749,-0.18360000000000001,0,,,0.0022823628108995749 -coef_sr3p_ASC_walk_work,-2.3566238207046379,0.21709999999999999,0,,,-2.3566238207046379 -coef_walk_ASC_rh,-7,-7,0,-7,-7,-7 -coef_walk_transit_ASC_commuter_work,0.4012,0.4012,0,,,0.4012 -coef_walk_transit_ASC_express_work,-0.35539999999999999,-0.35539999999999999,0,,,-0.35539999999999999 -coef_walk_transit_ASC_ferry_work,0.52769999999999995,0.52769999999999995,0,,,0.52769999999999995 -coef_walk_transit_ASC_heavyrail_work,0.50253917060490561,0.3538,0,,,0.50253917060490561 -coef_walk_transit_ASC_lightrail_work,0.63259254210688642,0.46210000000000001,0,,,0.63259254210688642 -coef_walk_transit_ASC_rh_work,-2.8695420596058572,-3.7408000000000001,0,,,-2.8695420596058572 -coef_walk_transit_ASC_sr2_work,-2.2566861984974196,-3.6631,0,,,-2.2566861984974196 -coef_walk_transit_ASC_sr3p_work,-2.6534480546215211,-4.1314000000000002,0,,,-2.6534480546215211 -coef_walk_transit_ASC_walk_work,-0.39143818330516583,0.44319999999999998,0,,,-0.39143818330516583 -coef_bike_ASC_walk_univ,-0.33989999999999998,-0.33989999999999998,0,,,-0.33989999999999998 -coef_drive_transit_ASC_commuter_univ_school,0.90820000000000001,0.90820000000000001,0,,,0.90820000000000001 -coef_drive_transit_ASC_express_univ_school,0.32240000000000002,0.32240000000000002,0,,,0.32240000000000002 -coef_drive_transit_ASC_ferry_univ_school,1.7237,1.7237,0,,,1.7237 -coef_drive_transit_ASC_heavyrail_univ_school,0.84899999999999998,0.84899999999999998,0,,,0.84899999999999998 -coef_drive_transit_ASC_lightrail_univ_school,1.4436,1.4436,0,,,1.4436 -coef_ivt_univ_school,-0.0082670637836597533,-0.027099999999999999,0,,,-0.0082670637836597533 -coef_ride_hail_ASC_sr2_univ,-4.3372000000000002,-4.3372000000000002,0,,,-4.3372000000000002 -coef_ride_hail_ASC_sr3p_univ,-4.9219999999999997,-4.9219999999999997,0,,,-4.9219999999999997 -coef_ride_hail_ASC_taxi_univ,-1.5993999999999999,-1.5993999999999999,0,,,-1.5993999999999999 -coef_ride_hail_ASC_tnc_single_univ,0.1081,0.1081,0,,,0.1081 -coef_ride_hail_ASC_walk_univ_escort_shopping_othmaint,-26.322181448888141,-7,0,,,-26.322181448888141 -coef_sov_ASC_rh_univ,-6.649,-6.649,0,,,-6.649 -coef_sov_ASC_walk_univ,-1.0579000000000001,-1.0579000000000001,0,,,-1.0579000000000001 -coef_sr2_ASC_rh_univ,-6.6897000000000002,-6.6897000000000002,0,,,-6.6897000000000002 -coef_sr2_ASC_sr2_univ,0.4304,0.4304,0,,,0.4304 -coef_sr2_ASC_walk_univ,1.3041,1.3041,0,,,1.3041 -coef_sr3p_ASC_rh_univ_escort_shopping_eatout_othmaint_social_othdiscr,-7,-7,0,-7,-7,-7 -coef_sr3p_ASC_sr2_univ,-0.31169999999999998,-0.31169999999999998,0,,,-0.31169999999999998 -coef_sr3p_ASC_sr3p_univ,0.62929999999999997,0.62929999999999997,0,,,0.62929999999999997 -coef_sr3p_ASC_walk_univ,1.6793,1.6793,0,,,1.6793 -coef_walk_transit_ASC_commuter_univ_school,0.90820000000000001,0.90820000000000001,0,,,0.90820000000000001 -coef_walk_transit_ASC_express_univ_school,0.32240000000000002,0.32240000000000002,0,,,0.32240000000000002 -coef_walk_transit_ASC_ferry_univ_school,1.7237,1.7237,0,,,1.7237 -coef_walk_transit_ASC_heavyrail_univ_school,0.86656489716508533,0.84899999999999998,0,,,0.86656489716508533 -coef_walk_transit_ASC_lightrail_univ_school,1.5673078514811689,1.4436,0,,,1.5673078514811689 -coef_walk_transit_ASC_rh_univ,-4.2690999999999999,-4.2690999999999999,0,,,-4.2690999999999999 -coef_walk_transit_ASC_sr2_univ,-4.0049999999999999,-4.0049999999999999,0,,,-4.0049999999999999 -coef_walk_transit_ASC_sr3p_univ,-28.697199999999999,-28.697199999999999,0,,,-28.697199999999999 -coef_walk_transit_ASC_walk_univ,-1.0310999999999999,-1.0310999999999999,0,,,-1.0310999999999999 -coef_bike_ASC_walk_school,-106.06311357570786,-2.0331999999999999,0,,,-106.06311357570786 -coef_ride_hail_ASC_sr2_school,-17.561865296747161,-1.5869,0,,,-17.561865296747161 -coef_ride_hail_ASC_sr3p_school,-17.869354547202143,-2.5362,0,,,-17.869354547202143 -coef_ride_hail_ASC_taxi_school,-1.6385208722849591,-0.58689999999999998,0,,,-1.6385208722849591 -coef_ride_hail_ASC_tnc_single_school,23.693954665409134,0.3201,0,,,23.693954665409134 -coef_ride_hail_ASC_walk_school,-17.881587989266929,0.245,0,,,-17.881587989266929 -coef_sov_ASC_rh_school,-126.45615738910647,-5.6548999999999996,0,,,-126.45615738910647 -coef_sov_ASC_walk_school,-3.1154322443821076,-71.8977,0,,,-3.1154322443821076 -coef_sr2_ASC_sr2_school,-0.54053965419989403,-1.9335,0,,,-0.54053965419989403 -coef_sr2_ASC_walk_school,-2.0412093694429427,-1.0362,0,,,-2.0412093694429427 -coef_sr3p_ASC_rh_school,-167.92322922478724,-6.6714000000000002,0,,,-167.92322922478724 -coef_sr3p_ASC_sr2_school,-1.0175286592825254,-2.7406999999999999,0,,,-1.0175286592825254 -coef_sr3p_ASC_sr3p_school,0.19312416588689055,-1.7718,0,,,0.19312416588689055 -coef_sr3p_ASC_walk_school,-2.4447403802047534,-1.2126999999999999,0,,,-2.4447403802047534 -coef_walk_transit_ASC_rh_school,-4.3619869330314502,-7,0,,,-4.3619869330314502 -coef_walk_transit_ASC_sr2_school,-2.270274862864051,-4.2961,0,,,-2.270274862864051 -coef_walk_transit_ASC_sr3p_school,-2.4067383334703436,-3.8664999999999998,0,,,-2.4067383334703436 -coef_walk_transit_ASC_walk_school,-1.4950397618009084,-1.1828000000000001,0,,,-1.4950397618009084 -coef_bike_ASC_walk_escort,-13.520327232125497,-13.520300000000001,0,,,-13.520327232125497 -coef_drive_transit_ASC_commuter_escort,0.54420000000000002,0.54420000000000002,0,,,0.54420000000000002 -coef_drive_transit_ASC_express_escort,0.75470000000000004,0.75470000000000004,0,,,0.75470000000000004 -coef_drive_transit_ASC_ferry_escort,0.60050000000000003,0.60050000000000003,0,,,0.60050000000000003 -coef_drive_transit_ASC_heavyrail_escort,-14.234170107485145,0.56730000000000003,0,,,-14.234170107485145 -coef_drive_transit_ASC_lightrail_escort,0.5252,0.5252,0,,,0.5252 -coef_ivt_escort_shopping_eatout_othdiscr_atwork,-0.011935317751590301,-0.027900000000000001,0,,,-0.011935317751590301 -coef_ride_hail_ASC_sr2_escort_shopping_othmaint,-23.87393437250816,-5.6482999999999999,0,,,-23.87393437250816 -coef_ride_hail_ASC_taxi_escort_shopping_othmaint,-3.6645734090143596,-3.6629,0,,,-3.6645734090143596 -coef_ride_hail_ASC_tnc_single_escort_shopping_othmaint,24.219922267784732,0.78790000000000004,0,,,24.219922267784732 -coef_sov_ASC_rh_escort_shopping_eatout_othmaint_social_othdiscr,0,0,0,0,0,0 -coef_sov_ASC_sr2_escort,0,0,0,0,0,0 -coef_sov_ASC_sr3p_escort,0,0,0,0,0,0 -coef_sov_ASC_walk_escort,0,0,0,0,0,0 -coef_sr2_ASC_sr2_escort,0.48842589140865728,0.3533,0,,,0.48842589140865728 -coef_sr2_ASC_walk_escort,-25.486556155436141,-2.0528,0,,,-25.486556155436141 -coef_sr3p_ASC_sr2_escort,-0.20651374838779549,-0.26819999999999999,0,,,-0.20651374838779549 -coef_sr3p_ASC_sr3p_escort,0.89578731133543399,0.73580000000000001,0,,,0.89578731133543399 -coef_sr3p_ASC_walk_escort,-3.4160479693862773,-1.0075000000000001,0,,,-3.4160479693862773 -coef_walk_transit_ASC_commuter_escort,0.54420000000000002,0.54420000000000002,0,,,0.54420000000000002 -coef_walk_transit_ASC_express_escort,0.75470000000000004,0.75470000000000004,0,,,0.75470000000000004 -coef_walk_transit_ASC_ferry_escort,0.60050000000000003,0.60050000000000003,0,,,0.60050000000000003 -coef_walk_transit_ASC_heavyrail_escort,0.85028037339339679,0.56730000000000003,0,,,0.85028037339339679 -coef_walk_transit_ASC_lightrail_escort,1.12520509210183,0.5252,0,,,1.12520509210183 -coef_walk_transit_ASC_rh_escort_shopping_othmaint,-2.3595754865729988,-3.1135999999999999,0,,,-2.3595754865729988 -coef_walk_transit_ASC_sr2_escort,-1.0205990135822081,-2.6284000000000001,0,,,-1.0205990135822081 -coef_walk_transit_ASC_sr3p_escort,-184.69692639910483,-3.2073999999999998,0,,,-184.69692639910483 -coef_walk_transit_ASC_walk_escort,-88.120508523406016,-0.99739999999999995,0,,,-88.120508523406016 -coef_bike_ASC_walk_shopping,-23.156539428413335,-1.0245,0,,,-23.156539428413335 -coef_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork,0.51290000000000002,0.51290000000000002,0,,,0.51290000000000002 -coef_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork,0.66479999999999995,0.66479999999999995,0,,,0.66479999999999995 -coef_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork,0.64659999999999995,0.64659999999999995,0,,,0.64659999999999995 -coef_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork,0.5403,0.5403,0,,,0.5403 -coef_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork,0.53920000000000001,0.53920000000000001,0,,,0.53920000000000001 -coef_joint_auto_ASC_rh_shopping_eatout_othmaint_social_othdiscr,-7,-7,0,,,-7 -coef_joint_auto_ASC_sr2_shopping,2.7753435280365912,0.58750000000000002,0,,,2.7753435280365912 -coef_joint_auto_ASC_sr3p_shopping,-19.06434075519855,-19.045400000000001,0,,,-19.06434075519855 -coef_joint_auto_ASC_walk_shopping,-23.468835890078797,-23.468800000000002,0,,,-23.468835890078797 -coef_joint_bike_ASC_rh_shopping_eatout_othmaint_social_othdiscr,-12.3057,-12.3057,0,,,-12.3057 -coef_joint_bike_ASC_walk_shopping,-7.0476000000000001,-7.0476000000000001,0,,,-7.0476000000000001 -coef_joint_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr,0.51290000000000002,0.51290000000000002,0,,,0.51290000000000002 -coef_joint_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr,0.66479999999999995,0.66479999999999995,0,,,0.66479999999999995 -coef_joint_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr,0.64659999999999995,0.64659999999999995,0,,,0.64659999999999995 -coef_joint_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr,0.5403,0.5403,0,,,0.5403 -coef_joint_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr,0.53920000000000001,0.53920000000000001,0,,,0.53920000000000001 -coef_joint_drive_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr,4.6138000000000003,4.6138000000000003,0,,,4.6138000000000003 -coef_joint_ride_hail_ASC_sr2_shopping_eatout_othmaint_social_othdiscr,-7,-7,0,,,-7 -coef_joint_ride_hail_ASC_sr3p_shopping_eatout_othmaint_social_othdiscr,-7,-7,0,,,-7 -coef_joint_ride_hail_ASC_taxi_shopping_eatout_othmaint_social_othdiscr,-7,-7,0,,,-7 -coef_joint_ride_hail_ASC_tnc_single_shopping_eatout_othmaint_social_othdiscr,-4.7339000000000002,-4.7339000000000002,0,,,-4.7339000000000002 -coef_joint_ride_hail_ASC_walk_shopping_eatout_othmaint_social_othdiscr,-7,-7,0,,,-7 -coef_joint_walk_ASC_rh_shopping_eatout_othmaint_social_othdiscr,-3.0362,-3.0362,0,,,-3.0362 -coef_joint_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr,0.51290000000000002,0.51290000000000002,0,,,0.51290000000000002 -coef_joint_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr,0.66479999999999995,0.66479999999999995,0,,,0.66479999999999995 -coef_joint_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr,0.64659999999999995,0.64659999999999995,0,,,0.64659999999999995 -coef_joint_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr,21.596514314322803,0.5403,0,,,21.596514314322803 -coef_joint_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr,0.92447712850041863,0.53920000000000001,0,,,0.92447712850041863 -coef_joint_walk_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr,3.132294016909416,1.2265999999999999,0,,,3.132294016909416 -coef_joint_walk_transit_ASC_sr2_shopping,-21.576802070713498,-21.576799999999999,0,,,-21.576802070713498 -coef_joint_walk_transit_ASC_sr3p_shopping,-25.595300009753458,-25.595300000000002,0,,,-25.595300009753458 -coef_joint_walk_transit_ASC_walk_shopping,-101.70152139850924,-0.54720000000000002,0,,,-101.70152139850924 -coef_sov_ASC_walk_shopping,-3.7867423367407271,-1.4765999999999999,0,,,-3.7867423367407271 -coef_sr2_ASC_sr2_shopping,1.7463545613015568,1.3765000000000001,0,,,1.7463545613015568 -coef_sr2_ASC_walk_shopping,-3.6530756986244408,-0.11169999999999999,0,,,-3.6530756986244408 -coef_sr3p_ASC_sr2_shopping,0.33630630204547912,-0.078100000000000003,0,,,0.33630630204547912 -coef_sr3p_ASC_sr3p_shopping,1.6427397418976948,1.3394999999999999,0,,,1.6427397418976948 -coef_sr3p_ASC_walk_shopping,-3.9191286556878429,-0.50790000000000002,0,,,-3.9191286556878429 -coef_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork,0.51290000000000002,0.51290000000000002,0,,,0.51290000000000002 -coef_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork,0.66479999999999995,0.66479999999999995,0,,,0.66479999999999995 -coef_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork,0.64659999999999995,0.64659999999999995,0,,,0.64659999999999995 -coef_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork,0.92621641961993106,0.5403,0,,,0.92621641961993106 -coef_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork,0.83136133693868486,0.53920000000000001,0,,,0.83136133693868486 -coef_walk_transit_ASC_sr2_shopping,-2.1233168743409747,-4.0114999999999998,0,,,-2.1233168743409747 -coef_walk_transit_ASC_sr3p_shopping,-91.093530857559287,-4.3852000000000002,0,,,-91.093530857559287 -coef_walk_transit_ASC_walk_shopping,-0.81350805532373194,-0.1943,0,,,-0.81350805532373194 -coef_bike_ASC_walk_eatout,-174.81611515878677,-2.6989999999999998,0,,,-174.81611515878677 -coef_joint_auto_ASC_sr2_eatout_othmaint_social_othdiscr,0.38104442976260161,-0.063399999999999998,0,,,0.38104442976260161 -coef_joint_auto_ASC_sr3p_eatout_othmaint_social_othdiscr,0.38908646769235944,-0.16250000000000001,0,,,0.38908646769235944 -coef_joint_auto_ASC_walk_eatout_othmaint_social_othdiscr,-4.3794314087625494,-0.71440000000000003,0,,,-4.3794314087625494 -coef_joint_bike_ASC_walk_eatout,-15.5588,-15.5588,0,,,-15.5588 -coef_joint_walk_transit_ASC_sr2_eatout,-14.914319758236871,-14.913399999999999,0,,,-14.914319758236871 -coef_joint_walk_transit_ASC_sr3p_eatout,-16.758772307649721,-16.758700000000001,0,,,-16.758772307649721 -coef_joint_walk_transit_ASC_walk_eatout,1.1018580418672292,2.3016999999999999,0,,,1.1018580418672292 -coef_ride_hail_ASC_sr2_eatout_social_othdiscr,-16.851845961332685,-5.9691999999999998,0,,,-16.851845961332685 -coef_ride_hail_ASC_sr3p_eatout_social_othdiscr,-11.873288203497911,-6.7199,0,,,-11.873288203497911 -coef_ride_hail_ASC_taxi_eatout_social_othdiscr,-2.5632427324461902,-2.5543,0,,,-2.5632427324461902 -coef_ride_hail_ASC_tnc_single_eatout_social_othdiscr,23.995880104391915,0.82740000000000002,0,,,23.995880104391915 -coef_ride_hail_ASC_walk_eatout_social_othdiscr,-17.718714023749605,-3.3603000000000001,0,,,-17.718714023749605 -coef_sov_ASC_walk_eatout,-2.6337956057242367,-1.3443000000000001,0,,,-2.6337956057242367 -coef_sr2_ASC_sr2_eatout,1.1016400029858922,0.99709999999999999,0,,,1.1016400029858922 -coef_sr2_ASC_walk_eatout,-4.5471769897543872,-0.072900000000000006,0,,,-4.5471769897543872 -coef_sr3p_ASC_sr2_eatout,-0.21320006188848084,-0.31780000000000003,0,,,-0.21320006188848084 -coef_sr3p_ASC_sr3p_eatout,1.474080431715626,1.3323,0,,,1.474080431715626 -coef_sr3p_ASC_walk_eatout,-2.5082484326697068,-0.043400000000000001,0,,,-2.5082484326697068 -coef_walk_transit_ASC_rh_eatout_social_othdiscr,-2.6584911065153216,-4.7507999999999999,0,,,-2.6584911065153216 -coef_walk_transit_ASC_sr2_eatout,-2.0069285824622241,-3.1434000000000002,0,,,-2.0069285824622241 -coef_walk_transit_ASC_sr3p_eatout,-2.5231634577013793,-3.8519999999999999,0,,,-2.5231634577013793 -coef_walk_transit_ASC_walk_eatout,0.16642876905750803,1.3504,0,,,0.16642876905750803 -coef_bike_ASC_walk_othmaint,-0.784009151847747,-0.5706,0,,,-0.784009151847747 -coef_ivt_othmaint_social,-0.012116004199731105,-0.017500000000000002,0,,,-0.012116004199731105 -coef_joint_bike_ASC_walk_othmaint,-13.5192,-13.5192,0,,,-13.5192 -coef_joint_walk_transit_ASC_sr2_othmaint,-11.323061152682898,-5.3230000000000004,0,,,-11.323061152682898 -coef_joint_walk_transit_ASC_sr3p_othmaint,-44.010114035526179,-3.9563000000000001,0,,,-44.010114035526179 -coef_joint_walk_transit_ASC_walk_othmaint,-73.569639938685185,1.1876,0,,,-73.569639938685185 -coef_sov_ASC_walk_othmaint,-4.4263069274933464,-1.2992999999999999,0,,,-4.4263069274933464 -coef_sr2_ASC_sr2_othmaint,0.93483638812856495,0.85740000000000005,0,,,0.93483638812856495 -coef_sr2_ASC_walk_othmaint,-3.1386920238871761,-0.59889999999999999,0,,,-3.1386920238871761 -coef_sr3p_ASC_sr2_othmaint,0.042063533996837946,-0.29580000000000001,0,,,0.042063533996837946 -coef_sr3p_ASC_sr3p_othmaint,1.1283362600967743,0.95269999999999999,0,,,1.1283362600967743 -coef_sr3p_ASC_walk_othmaint,-5.0664087819757082,0.042200000000000001,0,,,-5.0664087819757082 -coef_walk_transit_ASC_sr2_othmaint,-34.674600000130781,-34.674599999999998,0,,,-34.674600000130781 -coef_walk_transit_ASC_sr3p_othmaint,-29.385800207697873,-29.3858,0,,,-29.385800207697873 -coef_walk_transit_ASC_walk_othmaint,-0.28811698789154394,0.7248,0,,,-0.28811698789154394 -coef_bike_ASC_walk_social,-13.240952180972661,-13.2384,0,,,-13.240952180972661 -coef_joint_bike_ASC_walk_social,-26.171399999999998,-26.171399999999998,0,,,-26.171399999999998 -coef_joint_walk_transit_ASC_sr2_social,-20.502199999999998,-20.502199999999998,0,,,-20.502199999999998 -coef_joint_walk_transit_ASC_sr3p_social,-34.7378,-34.7378,0,,,-34.7378 -coef_joint_walk_transit_ASC_walk_social,-2.3852136661883132,-2.1301000000000001,0,,,-2.3852136661883132 -coef_sov_ASC_walk_social,-25.269332635237305,-1.8077000000000001,0,,,-25.269332635237305 -coef_sr2_ASC_sr2_social,0.76826858270381293,0.56630000000000003,0,,,0.76826858270381293 -coef_sr2_ASC_walk_social,-2.8506566329280796,-0.79320000000000002,0,,,-2.8506566329280796 -coef_sr3p_ASC_sr2_social,-0.12234716443959485,-0.15559999999999999,0,,,-0.12234716443959485 -coef_sr3p_ASC_sr3p_social,1.2106868400711996,0.83309999999999995,0,,,1.2106868400711996 -coef_sr3p_ASC_walk_social,-3.0801131342084651,-0.31340000000000001,0,,,-3.0801131342084651 -coef_walk_transit_ASC_sr2_social,-2.0645343270844863,-3.3662999999999998,0,,,-2.0645343270844863 -coef_walk_transit_ASC_sr3p_social,-21.63090014868768,-21.6309,0,,,-21.63090014868768 -coef_walk_transit_ASC_walk_social,-2.3146041098832506,-0.7651,0,,,-2.3146041098832506 -coef_bike_ASC_walk_othdiscr,-1.3971872234012017,-1.3576999999999999,0,,,-1.3971872234012017 -coef_joint_bike_ASC_walk_othdiscr,-14.444000000000001,-14.444000000000001,0,,,-14.444000000000001 -coef_joint_walk_transit_ASC_sr2_othdiscr,-14.9801,-14.9801,0,,,-14.9801 -coef_joint_walk_transit_ASC_sr3p_othdiscr,-16.735567652638597,-16.735399999999998,0,,,-16.735567652638597 -coef_joint_walk_transit_ASC_walk_othdiscr,-25.948044836941285,-0.0023999999999999998,0,,,-25.948044836941285 -coef_sov_ASC_walk_othdiscr,-4.9397828512902819,-1.5507,0,,,-4.9397828512902819 -coef_sr2_ASC_sr2_othdiscr,0.85570357875378389,0.74780000000000002,0,,,0.85570357875378389 -coef_sr2_ASC_walk_othdiscr,-2.4704700572535603,-0.026800000000000001,0,,,-2.4704700572535603 -coef_sr3p_ASC_sr2_othdiscr,-0.41762969659077742,-0.61419999999999997,0,,,-0.41762969659077742 -coef_sr3p_ASC_sr3p_othdiscr,0.84494437659483101,0.73980000000000001,0,,,0.84494437659483101 -coef_sr3p_ASC_walk_othdiscr,-5.841028145506157,-0.5272,0,,,-5.841028145506157 -coef_walk_transit_ASC_sr2_othdiscr,-1.2322243797539427,-2.7589999999999999,0,,,-1.2322243797539427 -coef_walk_transit_ASC_sr3p_othdiscr,-1.1992638422488842,-2.5125999999999999,0,,,-1.1992638422488842 -coef_walk_transit_ASC_walk_othdiscr,-0.98049723049553139,-0.49969999999999998,0,,,-0.98049723049553139 +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +1,1,1,1,0 +coef_age010_trn,0.35767627741145724,0.35767627741145724,0,0 +coef_age1619_da,0.34333578772407369,0.34333578772407369,0,0 +coef_age16p_sr,-0.14184142530409971,-0.14184142530409971,0,0 +coef_bike_ASC_rh,-7,-7,-7,0 +coef_bike_ASC_walk_eatout,-4.6307472236220351,-4.6307472236220351,-2.6989999999999998,0 +coef_bike_ASC_walk_escort,-13.520300035676909,-13.520300035676909,-13.520300000000001,0 +coef_bike_ASC_walk_othdiscr,-1.3990818215431378,-1.3990818215431378,-1.3576999999999999,0 +coef_bike_ASC_walk_othmaint,-0.7890931685689252,-0.7890931685689252,-0.5706,0 +coef_bike_ASC_walk_school,-4.9873103152859581,-4.9873103152859581,-2.0331999999999999,0 +coef_bike_ASC_walk_shopping,-11.171180371928761,-11.171180371928761,-1.0245,0 +coef_bike_ASC_walk_social,-13.238403309075121,-13.238403309075121,-13.2384,0 +coef_bike_ASC_walk_univ,-0.33989999999999998,-0.33989999999999998,-0.33989999999999998,0 +coef_bike_ASC_walk_work,-2.662073727736936,-2.662073727736936,-1.8332999999999999,0 +coef_drive_transit_ASC_commuter_escort,0.54420000000000002,0.54420000000000002,0.54420000000000002,0 +coef_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork,0.51290000000000002,0.51290000000000002,0.51290000000000002,0 +coef_drive_transit_ASC_commuter_univ_school,0.90820000000000001,0.90820000000000001,0.90820000000000001,0 +coef_drive_transit_ASC_commuter_work,0.42637620615946842,0.42637620615946842,0.4012,0 +coef_drive_transit_ASC_express_escort,0.75470000000000004,0.75470000000000004,0.75470000000000004,0 +coef_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork,0.66479999999999995,0.66479999999999995,0.66479999999999995,0 +coef_drive_transit_ASC_express_univ_school,0.32240000000000002,0.32240000000000002,0.32240000000000002,0 +coef_drive_transit_ASC_express_work,-0.35539999999999999,-0.35539999999999999,-0.35539999999999999,0 +coef_drive_transit_ASC_ferry_escort,0.60050000000000003,0.60050000000000003,0.60050000000000003,0 +coef_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork,0.64659999999999995,0.64659999999999995,0.64659999999999995,0 +coef_drive_transit_ASC_ferry_univ_school,1.7237,1.7237,1.7237,0 +coef_drive_transit_ASC_ferry_work,0.52769999999999995,0.52769999999999995,0.52769999999999995,0 +coef_drive_transit_ASC_heavyrail_escort,-9.989800530770955,-9.989800530770955,0.56730000000000003,0 +coef_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork,0.5403,0.5403,0.5403,0 +coef_drive_transit_ASC_heavyrail_univ_school,0.84899999999999998,0.84899999999999998,0.84899999999999998,0 +coef_drive_transit_ASC_heavyrail_work,-8.7062475359294247,-8.7062475359294247,0.3538,0 +coef_drive_transit_ASC_lightrail_escort,0.5252,0.5252,0.5252,0 +coef_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork,0.53920000000000001,0.53920000000000001,0.53920000000000001,0 +coef_drive_transit_ASC_lightrail_univ_school,1.4436,1.4436,1.4436,0 +coef_drive_transit_ASC_lightrail_work,-7.4071143692385562,-7.4071143692385562,0.46210000000000001,0 +coef_drive_transit_ASC_rh,-8.0109041770487206,-8.0109041770487206,-4.25,0 +coef_hhsize1_sr,-0.89082809363303117,-0.89082809363303117,-0.73460000000000003,0 +coef_hhsize2_sr,0.039673604461434211,0.039673604461434211,0,0 +coef_ivt_escort_shopping_eatout_othdiscr_atwork,-0.011939751587626005,-0.011939751587626005,-0.027900000000000001,0 +coef_ivt_othmaint_social,-0.012113122493485196,-0.012113122493485196,-0.017500000000000002,0 +coef_ivt_univ_school,-0.0082684909559910397,-0.0082684909559910397,-0.027099999999999999,0 +coef_ivt_work,-0.010154800227496609,-0.010154800227496609,-0.021999999999999999,0 +coef_joint_auto_ASC_rh_shopping_eatout_othmaint_social_othdiscr,-7,-7,-7,0 +coef_joint_auto_ASC_rh_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_auto_ASC_sr2_eatout_othmaint_social_othdiscr,0.37182968511460945,0.37182968511460945,-0.063399999999999998,0 +coef_joint_auto_ASC_sr2_shopping,2.7630522022711443,2.7630522022711443,0.58750000000000002,0 +coef_joint_auto_ASC_sr2_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_auto_ASC_sr3p_eatout_othmaint_social_othdiscr,0.37976650225041186,0.37976650225041186,-0.16250000000000001,0 +coef_joint_auto_ASC_sr3p_shopping,-19.04542622913733,-19.04542622913733,-19.045400000000001,0 +coef_joint_auto_ASC_sr3p_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_auto_ASC_walk_eatout_othmaint_social_othdiscr,-4.375671164481866,-4.375671164481866,-0.71440000000000003,0 +coef_joint_auto_ASC_walk_shopping,-23.468800060392848,-23.468800060392848,-23.468800000000002,0 +coef_joint_auto_ASC_walk_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_bike_ASC_rh_shopping_eatout_othmaint_social_othdiscr,-12.3057,-12.3057,-12.3057,0 +coef_joint_bike_ASC_rh_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_bike_ASC_walk_eatout,-15.5588,-15.5588,-15.5588,0 +coef_joint_bike_ASC_walk_othdiscr,-14.444000000000001,-14.444000000000001,-14.444000000000001,0 +coef_joint_bike_ASC_walk_othmaint,-13.5192,-13.5192,-13.5192,0 +coef_joint_bike_ASC_walk_shopping,-7.0476000000000001,-7.0476000000000001,-7.0476000000000001,0 +coef_joint_bike_ASC_walk_social,-26.171399999999998,-26.171399999999998,-26.171399999999998,0 +coef_joint_bike_ASC_walk_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr,0.51290000000000002,0.51290000000000002,0.51290000000000002,0 +coef_joint_drive_transit_ASC_commuter_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr,0.66479999999999995,0.66479999999999995,0.66479999999999995,0 +coef_joint_drive_transit_ASC_express_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr,0.64659999999999995,0.64659999999999995,0.64659999999999995,0 +coef_joint_drive_transit_ASC_ferry_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr,0.5403,0.5403,0.5403,0 +coef_joint_drive_transit_ASC_heavyrail_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr,0.53920000000000001,0.53920000000000001,0.53920000000000001,0 +coef_joint_drive_transit_ASC_lightrail_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_drive_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr,4.6138000000000003,4.6138000000000003,4.6138000000000003,0 +coef_joint_drive_transit_ASC_rh_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_ride_hail_ASC_sr2_shopping_eatout_othmaint_social_othdiscr,-7,-7,-7,0 +coef_joint_ride_hail_ASC_sr2_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_ride_hail_ASC_sr3p_shopping_eatout_othmaint_social_othdiscr,-7,-7,-7,0 +coef_joint_ride_hail_ASC_sr3p_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_ride_hail_ASC_taxi_shopping_eatout_othmaint_social_othdiscr,-7,-7,-7,0 +coef_joint_ride_hail_ASC_taxi_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_ride_hail_ASC_tnc_shared,0,0,0,0 +coef_joint_ride_hail_ASC_tnc_single_shopping_eatout_othmaint_social_othdiscr,-4.7339000000000002,-4.7339000000000002,-4.7339000000000002,0 +coef_joint_ride_hail_ASC_tnc_single_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_ride_hail_ASC_walk_shopping_eatout_othmaint_social_othdiscr,-7,-7,-7,0 +coef_joint_ride_hail_ASC_walk_transit,0,0,0,0 +coef_joint_ride_hail_ASC_walk_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_ASC_rh_shopping_eatout_othmaint_social_othdiscr,-3.0362,-3.0362,-3.0362,0 +coef_joint_walk_ASC_rh_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr,0.51290000000000002,0.51290000000000002,0.51290000000000002,0 +coef_joint_walk_transit_ASC_commuter_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr,0.66479999999999995,0.66479999999999995,0.66479999999999995,0 +coef_joint_walk_transit_ASC_express_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr,0.64659999999999995,0.64659999999999995,0.64659999999999995,0 +coef_joint_walk_transit_ASC_ferry_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr,13.389850481098479,13.389850481098479,0.5403,0 +coef_joint_walk_transit_ASC_heavyrail_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr,0.98274193315609293,0.98274193315609293,0.53920000000000001,0 +coef_joint_walk_transit_ASC_lightrail_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr,3.183325294252882,3.183325294252882,1.2265999999999999,0 +coef_joint_walk_transit_ASC_rh_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_sr2_eatout,-14.913401266030013,-14.913401266030013,-14.913399999999999,0 +coef_joint_walk_transit_ASC_sr2_othdiscr,-14.9801,-14.9801,-14.9801,0 +coef_joint_walk_transit_ASC_sr2_othmaint,-5.3309700517325718,-5.3309700517325718,-5.3230000000000004,0 +coef_joint_walk_transit_ASC_sr2_shopping,-21.576800002987216,-21.576800002987216,-21.576799999999999,0 +coef_joint_walk_transit_ASC_sr2_social,-20.502199999999998,-20.502199999999998,-20.502199999999998,0 +coef_joint_walk_transit_ASC_sr2_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_sr3p_eatout,-16.758700099536259,-16.758700099536259,-16.758700000000001,0 +coef_joint_walk_transit_ASC_sr3p_othdiscr,-16.735400264288284,-16.735400264288284,-16.735399999999998,0 +coef_joint_walk_transit_ASC_sr3p_othmaint,-4.0140180305790336,-4.0140180305790336,-3.9563000000000001,0 +coef_joint_walk_transit_ASC_sr3p_shopping,-25.595300000014014,-25.595300000014014,-25.595300000000002,0 +coef_joint_walk_transit_ASC_sr3p_social,-34.7378,-34.7378,-34.7378,0 +coef_joint_walk_transit_ASC_sr3p_work_univ_school_escort_atwork,0,0,0,0 +coef_joint_walk_transit_ASC_walk_eatout,1.1571199957158329,1.1571199957158329,2.3016999999999999,0 +coef_joint_walk_transit_ASC_walk_othdiscr,-0.043211155305850707,-0.043211155305850707,-0.0023999999999999998,0 +coef_joint_walk_transit_ASC_walk_othmaint,-5.4736104658626115,-5.4736104658626115,1.1876,0 +coef_joint_walk_transit_ASC_walk_shopping,-5.9428639820608167,-5.9428639820608167,-0.54720000000000002,0 +coef_joint_walk_transit_ASC_walk_social,-2.2714573374616625,-2.2714573374616625,-2.1301000000000001,0 +coef_joint_walk_transit_ASC_walk_work_univ_school_escort_atwork,0,0,0,0 +coef_nest_AUTO,0.71999999999999997,0.71999999999999997,0.71999999999999997,1 +coef_nest_AUTO_DRIVEALONE,0.34999999999999998,0.34999999999999998,0.34999999999999998,1 +coef_nest_AUTO_SHAREDRIDE2,0.34999999999999998,0.34999999999999998,0.34999999999999998,1 +coef_nest_AUTO_SHAREDRIDE3,0.34999999999999998,0.34999999999999998,0.34999999999999998,1 +coef_nest_NONMOTORIZED,0.71999999999999997,0.71999999999999997,0.71999999999999997,1 +coef_nest_RIDEHAIL,0.35999999999999999,0.35999999999999999,0.35999999999999999,1 +coef_nest_TRANSIT,0.71999999999999997,0.71999999999999997,0.71999999999999997,1 +coef_nest_TRANSIT_DRIVEACCESS,0.5,0.5,0.5,1 +coef_nest_TRANSIT_WALKACCESS,0.5,0.5,0.5,1 +coef_ride_hail_ASC_sr2_eatout_social_othdiscr,-6.4237650755245772,-6.4237650755245772,-5.9691999999999998,0 +coef_ride_hail_ASC_sr2_escort_shopping_othmaint,-8.6681239587327461,-8.6681239587327461,-5.6482999999999999,0 +coef_ride_hail_ASC_sr2_school,-9.8588042940530691,-9.8588042940530691,-1.5869,0 +coef_ride_hail_ASC_sr2_univ,-4.3372000000000002,-4.3372000000000002,-4.3372000000000002,0 +coef_ride_hail_ASC_sr2_work,-8.7370618957514985,-8.7370618957514985,-6.1079999999999997,0 +coef_ride_hail_ASC_sr3p_eatout_social_othdiscr,-6.8871198658131894,-6.8871198658131894,-6.7199,0 +coef_ride_hail_ASC_sr3p_school,-7.667321296853344,-7.667321296853344,-2.5362,0 +coef_ride_hail_ASC_sr3p_univ,-4.9219999999999997,-4.9219999999999997,-4.9219999999999997,0 +coef_ride_hail_ASC_sr3p_work_escort_shopping_othmaint_atwork,-8.4993141583621394,-8.4993141583621394,-7,0 +coef_ride_hail_ASC_taxi_eatout_social_othdiscr,-2.5631373967196924,-2.5631373967196924,-2.5543,0 +coef_ride_hail_ASC_taxi_escort_shopping_othmaint,-3.6639503613758153,-3.6639503613758153,-3.6629,0 +coef_ride_hail_ASC_taxi_school,-1.9540410876610597,-1.9540410876610597,-0.58689999999999998,0 +coef_ride_hail_ASC_taxi_univ,-1.5993999999999999,-1.5993999999999999,-1.5993999999999999,0 +coef_ride_hail_ASC_taxi_work,-2.4992280746351052,-2.4992280746351052,-2.3849999999999998,0 +coef_ride_hail_ASC_tnc_shared,6.4746604585247001,6.4746604585247001,0,0 +coef_ride_hail_ASC_tnc_single_eatout_social_othdiscr,7.2023280939010208,7.2023280939010208,0.82740000000000002,0 +coef_ride_hail_ASC_tnc_single_escort_shopping_othmaint,7.4263660209874116,7.4263660209874116,0.78790000000000004,0 +coef_ride_hail_ASC_tnc_single_school,6.9003930265898461,6.9003930265898461,0.3201,0 +coef_ride_hail_ASC_tnc_single_univ,0.1081,0.1081,0.1081,0 +coef_ride_hail_ASC_tnc_single_work,7.1906030498215934,7.1906030498215934,0.73499999999999999,0 +coef_ride_hail_ASC_walk_eatout_social_othdiscr,-8.2700256968569796,-8.2700256968569796,-3.3603000000000001,0 +coef_ride_hail_ASC_walk_school,-13.75516439764165,-13.75516439764165,0.245,0 +coef_ride_hail_ASC_walk_transit,5.320919867286813,5.320919867286813,0,0 +coef_ride_hail_ASC_walk_univ_escort_shopping_othmaint,-7.9623896833175234,-7.9623896833175234,-7,0 +coef_ride_hail_ASC_walk_work,4.9774767261374491,4.9774767261374491,0.2858,0 +coef_sov_ASC_rh_escort_shopping_eatout_othmaint_social_othdiscr,0,0,0,0 +coef_sov_ASC_rh_school,-10.949190676763848,-10.949190676763848,-5.6548999999999996,0 +coef_sov_ASC_rh_univ,-6.649,-6.649,-6.649,0 +coef_sov_ASC_rh_work_atwork,-7,-7,-7,0 +coef_sov_ASC_sr2_escort,0,0,0,0 +coef_sov_ASC_sr2_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork,-999,-999,-999,0 +coef_sov_ASC_sr3p_escort,0,0,0,0 +coef_sov_ASC_sr3p_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork,-999,-999,-999,0 +coef_sov_ASC_walk_eatout,-2.6351638383156661,-2.6351638383156661,-1.3443000000000001,0 +coef_sov_ASC_walk_escort,0,0,0,0 +coef_sov_ASC_walk_othdiscr,-4.9362989098824706,-4.9362989098824706,-1.5507,0 +coef_sov_ASC_walk_othmaint,-4.4203686413898176,-4.4203686413898176,-1.2992999999999999,0 +coef_sov_ASC_walk_school,-3.1150166914376998,-3.1150166914376998,-71.8977,0 +coef_sov_ASC_walk_shopping,-3.790711593714617,-3.790711593714617,-1.4765999999999999,0 +coef_sov_ASC_walk_social,-15.183480636962726,-15.183480636962726,-1.8077000000000001,0 +coef_sov_ASC_walk_univ,-1.0579000000000001,-1.0579000000000001,-1.0579000000000001,0 +coef_sov_ASC_walk_work,-3.0071231001560492,-3.0071231001560492,-0.83979999999999999,0 +coef_sr2_ASC_rh_univ,-6.6897000000000002,-6.6897000000000002,-6.6897000000000002,0 +coef_sr2_ASC_rh_work_school_escort_shopping_eatout_othmaint_social_othdiscr_atwork,-7,-7,-7,0 +coef_sr2_ASC_sr2_eatout,1.0915911218889376,1.0915911218889376,0.99709999999999999,0 +coef_sr2_ASC_sr2_escort,0.4783058163607723,0.4783058163607723,0.3533,0 +coef_sr2_ASC_sr2_othdiscr,0.84570279022463457,0.84570279022463457,0.74780000000000002,0 +coef_sr2_ASC_sr2_othmaint,0.92430088713320557,0.92430088713320557,0.85740000000000005,0 +coef_sr2_ASC_sr2_school,-0.55142467432696085,-0.55142467432696085,-1.9335,0 +coef_sr2_ASC_sr2_shopping,1.7357779332652892,1.7357779332652892,1.3765000000000001,0 +coef_sr2_ASC_sr2_social,0.75821484443712639,0.75821484443712639,0.56630000000000003,0 +coef_sr2_ASC_sr2_univ,0.4304,0.4304,0.4304,0 +coef_sr2_ASC_sr2_work,0.18734725740026195,0.18734725740026195,0.0149,0 +coef_sr2_ASC_sr3p,-999,-999,-999,0 +coef_sr2_ASC_walk_eatout,-4.5472515289454529,-4.5472515289454529,-0.072900000000000006,0 +coef_sr2_ASC_walk_escort,-23.318883212926828,-23.318883212926828,-2.0528,0 +coef_sr2_ASC_walk_othdiscr,-2.4714996184390858,-2.4714996184390858,-0.026800000000000001,0 +coef_sr2_ASC_walk_othmaint,-3.1513689512096983,-3.1513689512096983,-0.59889999999999999,0 +coef_sr2_ASC_walk_school,-2.0520641973448814,-2.0520641973448814,-1.0362,0 +coef_sr2_ASC_walk_shopping,-3.6616557867959929,-3.6616557867959929,-0.11169999999999999,0 +coef_sr2_ASC_walk_social,-2.8345061083015142,-2.8345061083015142,-0.79320000000000002,0 +coef_sr2_ASC_walk_univ,1.3041,1.3041,1.3041,0 +coef_sr2_ASC_walk_work,-2.2227044743770445,-2.2227044743770445,0.126,0 +coef_sr3p_ASC_rh_school,-10.730125238227592,-10.730125238227592,-6.6714000000000002,0 +coef_sr3p_ASC_rh_univ_escort_shopping_eatout_othmaint_social_othdiscr,-7,-7,-7,0 +coef_sr3p_ASC_rh_work,-71.917699999999996,-71.917699999999996,-71.917699999999996,0 +coef_sr3p_ASC_sr2_eatout,-0.22504507680807895,-0.22504507680807895,-0.31780000000000003,0 +coef_sr3p_ASC_sr2_escort,-0.21630087392009059,-0.21630087392009059,-0.26819999999999999,0 +coef_sr3p_ASC_sr2_othdiscr,-0.42794642963477558,-0.42794642963477558,-0.61419999999999997,0 +coef_sr3p_ASC_sr2_othmaint,0.027657045664653299,0.027657045664653299,-0.29580000000000001,0 +coef_sr3p_ASC_sr2_school,-1.0402498584452382,-1.0402498584452382,-2.7406999999999999,0 +coef_sr3p_ASC_sr2_shopping,0.32506049110749652,0.32506049110749652,-0.078100000000000003,0 +coef_sr3p_ASC_sr2_social,-0.13140596327177012,-0.13140596327177012,-0.15559999999999999,0 +coef_sr3p_ASC_sr2_univ,-0.31169999999999998,-0.31169999999999998,-0.31169999999999998,0 +coef_sr3p_ASC_sr2_work,-0.96412449274578071,-0.96412449274578071,-1.1956,0 +coef_sr3p_ASC_sr3p_eatout,1.4628559194582083,1.4628559194582083,1.3323,0 +coef_sr3p_ASC_sr3p_escort,0.88601825802048151,0.88601825802048151,0.73580000000000001,0 +coef_sr3p_ASC_sr3p_othdiscr,0.83449788039660122,0.83449788039660122,0.73980000000000001,0 +coef_sr3p_ASC_sr3p_othmaint,1.1154991293213483,1.1154991293213483,0.95269999999999999,0 +coef_sr3p_ASC_sr3p_school,0.17070219167279393,0.17070219167279393,-1.7718,0 +coef_sr3p_ASC_sr3p_shopping,1.6317620662617456,1.6317620662617456,1.3394999999999999,0 +coef_sr3p_ASC_sr3p_social,1.2011521984245512,1.2011521984245512,0.83309999999999995,0 +coef_sr3p_ASC_sr3p_univ,0.62929999999999997,0.62929999999999997,0.62929999999999997,0 +coef_sr3p_ASC_sr3p_work,-0.0078556547449509153,-0.0078556547449509153,-0.18360000000000001,0 +coef_sr3p_ASC_walk_eatout,-2.5139966855713642,-2.5139966855713642,-0.043400000000000001,0 +coef_sr3p_ASC_walk_escort,-3.4006765281458122,-3.4006765281458122,-1.0075000000000001,0 +coef_sr3p_ASC_walk_othdiscr,-5.8689862851164607,-5.8689862851164607,-0.5272,0 +coef_sr3p_ASC_walk_othmaint,-5.0613355985663731,-5.0613355985663731,0.042200000000000001,0 +coef_sr3p_ASC_walk_school,-2.4681086096393896,-2.4681086096393896,-1.2126999999999999,0 +coef_sr3p_ASC_walk_shopping,-3.9238148057027744,-3.9238148057027744,-0.50790000000000002,0 +coef_sr3p_ASC_walk_social,-3.0951059771109648,-3.0951059771109648,-0.31340000000000001,0 +coef_sr3p_ASC_walk_univ,1.6793,1.6793,1.6793,0 +coef_sr3p_ASC_walk_work,-2.3560377610366339,-2.3560377610366339,0.21709999999999999,0 +coef_walk_ASC_rh,-7,-7,-7,0 +coef_walk_transit_ASC_commuter_escort,0.54420000000000002,0.54420000000000002,0.54420000000000002,0 +coef_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork,0.51290000000000002,0.51290000000000002,0.51290000000000002,0 +coef_walk_transit_ASC_commuter_univ_school,0.90820000000000001,0.90820000000000001,0.90820000000000001,0 +coef_walk_transit_ASC_commuter_work,0.4012,0.4012,0.4012,0 +coef_walk_transit_ASC_express_escort,0.75470000000000004,0.75470000000000004,0.75470000000000004,0 +coef_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork,0.66479999999999995,0.66479999999999995,0.66479999999999995,0 +coef_walk_transit_ASC_express_univ_school,0.32240000000000002,0.32240000000000002,0.32240000000000002,0 +coef_walk_transit_ASC_express_work,-0.35539999999999999,-0.35539999999999999,-0.35539999999999999,0 +coef_walk_transit_ASC_ferry_escort,0.60050000000000003,0.60050000000000003,0.60050000000000003,0 +coef_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork,0.64659999999999995,0.64659999999999995,0.64659999999999995,0 +coef_walk_transit_ASC_ferry_univ_school,1.7237,1.7237,1.7237,0 +coef_walk_transit_ASC_ferry_work,0.52769999999999995,0.52769999999999995,0.52769999999999995,0 +coef_walk_transit_ASC_heavyrail_escort,0.82721493724592188,0.82721493724592188,0.56730000000000003,0 +coef_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork,0.92635472370348126,0.92635472370348126,0.5403,0 +coef_walk_transit_ASC_heavyrail_univ_school,0.86667504489837865,0.86667504489837865,0.84899999999999998,0 +coef_walk_transit_ASC_heavyrail_work,0.5025352261009528,0.5025352261009528,0.3538,0 +coef_walk_transit_ASC_lightrail_escort,1.1220737240827967,1.1220737240827967,0.5252,0 +coef_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork,0.83144252485479686,0.83144252485479686,0.53920000000000001,0 +coef_walk_transit_ASC_lightrail_univ_school,1.5673106432418389,1.5673106432418389,1.4436,0 +coef_walk_transit_ASC_lightrail_work,0.63258933455537403,0.63258933455537403,0.46210000000000001,0 +coef_walk_transit_ASC_rh_eatout_social_othdiscr,-2.6606459058042766,-2.6606459058042766,-4.7507999999999999,0 +coef_walk_transit_ASC_rh_escort_shopping_othmaint,-2.3584519726828503,-2.3584519726828503,-3.1135999999999999,0 +coef_walk_transit_ASC_rh_school,-4.3651480868436616,-4.3651480868436616,-7,0 +coef_walk_transit_ASC_rh_univ,-4.2690999999999999,-4.2690999999999999,-4.2690999999999999,0 +coef_walk_transit_ASC_rh_work,-2.8694950408844635,-2.8694950408844635,-3.7408000000000001,0 +coef_walk_transit_ASC_sr2_eatout,-2.0166783466764731,-2.0166783466764731,-3.1434000000000002,0 +coef_walk_transit_ASC_sr2_escort,-0.99918778660088436,-0.99918778660088436,-2.6284000000000001,0 +coef_walk_transit_ASC_sr2_othdiscr,-1.239023652712798,-1.239023652712798,-2.7589999999999999,0 +coef_walk_transit_ASC_sr2_othmaint,-34.674600000000112,-34.674600000000112,-34.674599999999998,0 +coef_walk_transit_ASC_sr2_school,-2.274826392672725,-2.274826392672725,-4.2961,0 +coef_walk_transit_ASC_sr2_shopping,-2.1328304552358719,-2.1328304552358719,-4.0114999999999998,0 +coef_walk_transit_ASC_sr2_social,-2.0833502428062123,-2.0833502428062123,-3.3662999999999998,0 +coef_walk_transit_ASC_sr2_univ,-4.0049999999999999,-4.0049999999999999,-4.0049999999999999,0 +coef_walk_transit_ASC_sr2_work,-2.2668862736328519,-2.2668862736328519,-3.6631,0 +coef_walk_transit_ASC_sr3p_eatout,-2.5264121576158045,-2.5264121576158045,-3.8519999999999999,0 +coef_walk_transit_ASC_sr3p_escort,-5.8381371662273835,-5.8381371662273835,-3.2073999999999998,0 +coef_walk_transit_ASC_sr3p_othdiscr,-1.2063771576374867,-1.2063771576374867,-2.5125999999999999,0 +coef_walk_transit_ASC_sr3p_othmaint,-29.385800000282099,-29.385800000282099,-29.3858,0 +coef_walk_transit_ASC_sr3p_school,-2.4112913709689163,-2.4112913709689163,-3.8664999999999998,0 +coef_walk_transit_ASC_sr3p_shopping,-9.3867562985269899,-9.3867562985269899,-4.3852000000000002,0 +coef_walk_transit_ASC_sr3p_social,-21.630900000230085,-21.630900000230085,-21.6309,0 +coef_walk_transit_ASC_sr3p_univ,-28.697199999999999,-28.697199999999999,-28.697199999999999,0 +coef_walk_transit_ASC_sr3p_work,-2.6637022892916695,-2.6637022892916695,-4.1314000000000002,0 +coef_walk_transit_ASC_walk_eatout,0.16644232569851822,0.16644232569851822,1.3504,0 +coef_walk_transit_ASC_walk_escort,-7.2572232561591434,-7.2572232561591434,-0.99739999999999995,0 +coef_walk_transit_ASC_walk_othdiscr,-0.97975419372738359,-0.97975419372738359,-0.49969999999999998,0 +coef_walk_transit_ASC_walk_othmaint,-0.28905978556563527,-0.28905978556563527,0.7248,0 +coef_walk_transit_ASC_walk_school,-1.4956108248781241,-1.4956108248781241,-1.1828000000000001,0 +coef_walk_transit_ASC_walk_shopping,-0.81195924640993355,-0.81195924640993355,-0.1943,0 +coef_walk_transit_ASC_walk_social,-2.3212936443153995,-2.3212936443153995,-0.7651,0 +coef_walk_transit_ASC_walk_univ,-1.0310999999999999,-1.0310999999999999,-1.0310999999999999,0 +coef_walk_transit_ASC_walk_work,-0.39145632958685811,-0.39145632958685811,0.44319999999999998,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_stop_freq_model.csv b/activitysim/estimation/test/test_larch_estimation/test_stop_freq_model.csv index fe3ad8745e..8226d916b6 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_stop_freq_model.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_stop_freq_model.csv @@ -1,189 +1,189 @@ -,value,initvalue,nullvalue,minimum,maximum,best -coef_alternative_specific_constant_for_outbound_stops_1out_0in,-0.64459225156448208,-0.83299999999999996,0,,,-0.64459225156448208 -coef_alternative_specific_constant_for_outbound_stops_2out_0in,-2.4255802366653585,-2.613,0,,,-2.4255802366653585 -coef_alternative_specific_constant_for_outbound_stops_3out_0in,-3.5820111930695417,-3.9340000000000002,0,,,-3.5820111930695417 -coef_alternative_specific_constant_for_return_stops_0out_1in,-0.3361407605068179,-0.44500000000000001,0,,,-0.3361407605068179 -coef_alternative_specific_constant_for_return_stops_0out_2in,-1.4776978296906871,-1.7749999999999999,0,,,-1.4776978296906871 -coef_alternative_specific_constant_for_return_stops_0out_3in,-1.8942287851285506,-2.1389999999999998,0,,,-1.8942287851285506 -coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,-0.066082964956457158,0,0,,,-0.066082964956457158 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,0.39410022765664782,0.69499999999999995,0,,,0.39410022765664782 -coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,-1.9991650147668323,-1.9299999999999999,0,,,-1.9991650147668323 -coef_dummy_for_all_stops_made_by_transit,-0.67359832175323664,-0.69999999999999996,0,,,-0.67359832175323664 -coef_dummy_for_distance_in_miles,0.044964434234324543,0.01,0,,,0.044964434234324543 -coef_dummy_for_distance_less_than_20_miles,-0.706160965748858,-0.22,0,,,-0.706160965748858 -coef_dummy_for_female,0.28231394503923868,0.22,0,,,0.28231394503923868 -coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,0.71316112803981435,0.59999999999999998,0,,,0.71316112803981435 -coef_dummy_for_walking_to_all_stops,-1.4873003617932004,-1.54,0,,,-1.4873003617932004 -coef_evening_arrival_19_00_interacted_with_return_tours,0.60673724793430617,0.31,0,,,0.60673724793430617 -coef_high_income_hh,0.24000000000001878,0.23999999999999999,0,,,0.24000000000001878 -coef_mid_to_high_income_hh,0.22999999999999904,0.23000000000000001,0,,,0.22999999999999904 -coef_middle_to_low_income_hh,0.16999999999999266,0.17000000000000001,0,,,0.16999999999999266 -coef_no_stops_if_tour_mode_is_drivetransit,-999,-999,0,,,-999 -coef_num_kids_between_5_and_15_including_years_old,0.092924351471183969,0.080000000000000002,0,,,0.092924351471183969 -coef_number_of_adults_16_years_old_,0.077365010457442138,0.029999999999999999,0,,,0.077365010457442138 -coef_number_of_cars_number_of_workers,-0.066249623271299782,0.16,0,,,-0.066249623271299782 -coef_number_of_escort_tours_tours_undertaken_by_the_person,0.096330730862920849,0.20000000000000001,0,,,0.096330730862920849 -coef_number_of_hh_persons,-0.33185226515031135,-0.31,0,,,-0.33185226515031135 -coef_number_of_school_tours_tours_undertaken_by_the_person,0.08642823107614464,-1.55,0,,,0.08642823107614464 -coef_number_of_shop_tours_undertaken_by_the_houshold,-0.32741940681713538,-0.050000000000000003,0,,,-0.32741940681713538 -coef_number_of_students_in_hh,0.31650418957116999,0.20999999999999999,0,,,0.31650418957116999 -coef_number_of_subtours_in_the_tour,0.33666132961145517,0.19,0,,,0.33666132961145517 -coef_number_of_university_tours_tours_undertaken_by_the_person,-0.48000000000000226,-0.47999999999999998,0,,,-0.48000000000000226 -coef_number_of_work_tours_undertaken_by_the_person,-0.17466645120795349,-0.14999999999999999,0,,,-0.17466645120795349 -coef_presence_of_kids_between_0_and_4_including_years_old,0.56261491842472322,0.73999999999999999,0,,,0.56261491842472322 -coef_presence_of_kids_between_5_and_15_including_years_old,0.1165493262082634,0.26000000000000001,0,,,0.1165493262082634 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_school,-1.7790649191402255,-2.1230000000000002,0,,,-1.7790649191402255 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_school,-4.234917600900892,-3.798,0,,,-4.234917600900892 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_school,-6.1101913112134891,-5.8499999999999996,0,,,-6.1101913112134891 -coef_alternative_specific_constant_for_return_stops_0out_1in_school,-1.2575756776155038,-1.206,0,,,-1.2575756776155038 -coef_alternative_specific_constant_for_return_stops_0out_2in_school,-2.7008487973600204,-2.6720000000000002,0,,,-2.7008487973600204 -coef_alternative_specific_constant_for_return_stops_0out_3in_school,-3.1227065529446167,-3.3639999999999999,0,,,-3.1227065529446167 -coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,1.474045133717242,0.70099999999999996,0,,,1.474045133717242 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_school,1.992911512841014,1.135,0,,,1.992911512841014 -coef_arrival_later_than_17_00_,1.3670454388826592,1.8376999999999999,0,,,1.3670454388826592 -coef_dummy_for_distance_in_miles_school,0.095083267583630102,0.043799999999999999,0,,,0.095083267583630102 -coef_dummy_for_female_school,0.68909925924380133,0.40989999999999999,0,,,0.68909925924380133 -coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,1.9145027660467904,0.95489999999999997,0,,,1.9145027660467904 -coef_dummy_for_walking_to_all_stops_school,-1.514711575382329,-1.8163,0,,,-1.514711575382329 -coef_number_of_cars_number_of_workers_school,0.29163991408877671,0.53310000000000002,0,,,0.29163991408877671 -coef_number_of_escort_tours_tours_undertaken_by_the_person_school,2.311650198005148,1.2364999999999999,0,,,2.311650198005148 -coef_number_of_hh_persons_school,-0.59762555971611364,-0.50600000000000001,0,,,-0.59762555971611364 -coef_presence_of_kids_between_5_and_15_including_years_old_school,0.025364840519008454,0.32990000000000003,0,,,0.025364840519008454 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_univ,-2.1635923818442357,-2.6280000000000001,0,,,-2.1635923818442357 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_univ,-3.922683293550401,-3.7410000000000001,0,,,-3.922683293550401 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_univ,-4.4868172910452992,-4.9809999999999999,0,,,-4.4868172910452992 -coef_alternative_specific_constant_for_return_stops_0out_1in_univ,-1.5298270302866508,-2.0030000000000001,0,,,-1.5298270302866508 -coef_alternative_specific_constant_for_return_stops_0out_2in_univ,-3.3006601948863188,-3.5099999999999998,0,,,-3.3006601948863188 -coef_alternative_specific_constant_for_return_stops_0out_3in_univ,-3.7075364155245767,-3.677,0,,,-3.7075364155245767 -coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_univ,1.8522535636157311,1.272,0,,,1.8522535636157311 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_univ,1.8679561735778554,1.871,0,,,1.8679561735778554 -coef_arrival_later_than_17_00__univ,0.38609418401942114,0.38900000000000001,0,,,0.38609418401942114 -coef_dummy_for_female_univ,0.51916166319197454,0.7349,0,,,0.51916166319197454 -coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__univ,1.0828661743516874,0.84340000000000004,0,,,1.0828661743516874 -coef_hh_accesibility_for_inbound_tours_interaction,0.24105038323693603,0.24809999999999999,0,,,0.24105038323693603 -coef_number_of_escort_tours_tours_undertaken_by_the_person_univ,1.8575681307186125,0.90180000000000005,0,,,1.8575681307186125 -coef_number_of_hh_persons_univ,-0.33066321661527537,-0.28270000000000001,0,,,-0.33066321661527537 -coef_number_of_vehicles,0.26364695030485774,0.17030000000000001,0,,,0.26364695030485774 -coef_presence_of_kids_between_5_and_15_including_years_old_univ,-0.044568923553371873,0.68230000000000002,0,,,-0.044568923553371873 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_social,-2.311541928791784,-1.081,0,,,-2.311541928791784 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_social,-3.971643113248795,-2.8740000000000001,0,,,-3.971643113248795 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_social,-14.469243911405519,-4.5519999999999996,0,,,-14.469243911405519 -coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,-2.3802074504942019,-1.7829999999999999,0,,,-2.3802074504942019 -coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,-4.719796104655666,-4.0670000000000002,0,,,-4.719796104655666 -coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,-11.749677886071149,-4.9980000000000002,0,,,-11.749677886071149 -coef_alternative_specific_constant_for_return_stops_0out_1in_social,0.20587483859873654,-1.1200000000000001,0,,,0.20587483859873654 -coef_alternative_specific_constant_for_return_stops_0out_2in_social,-2.5883343811753692,-2.7639999999999998,0,,,-2.5883343811753692 -coef_alternative_specific_constant_for_return_stops_0out_3in_social,-3.3206409198297089,-3.4510000000000001,0,,,-3.3206409198297089 -coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,-1.6522833462248787,-1.329,0,,,-1.6522833462248787 -coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,-4.1415469266822509,-2.7960000000000003,0,,,-4.1415469266822509 -coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,-4.0471873952483204,-3.379,0,,,-4.0471873952483204 -coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_social,2.4766471322901977,0.496,0,,,2.4766471322901977 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_social,-1.7322797167348338,0.88200000000000001,0,,,-1.7322797167348338 -coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,0.33004028360351806,0,0,,,0.33004028360351806 -coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,-4.3574765624568856,0.51800000000000002,0,,,-4.3574765624568856 -coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,-1.4567085446015828,1.4970000000000001,0,,,-1.4567085446015828 -coef_arrival_later_than_17_00__social,-0.46270836809978866,-0.45000000000000001,0,,,-0.46270836809978866 -coef_at_least_one_kid_and_one_adult_participate_in_the_tour,1.9188835397128035,0.37,0,,,1.9188835397128035 -coef_dummy_for_a_return_visiting_tour,-1.5149329165512258,-0.64000000000000001,0,,,-1.5149329165512258 -coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,0.47207475952054606,0.44,0,,,0.47207475952054606 -coef_dummy_for_an_outbound_visiting_tour,0.23539836860732627,-0.68999999999999995,0,,,0.23539836860732627 -coef_dummy_for_distance_in_miles_social,-0.072029213636538594,-0.01,0,,,-0.072029213636538594 -coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,1.1553718422199695,1.3100000000000001,0,,,1.1553718422199695 -coef_dummy_for_walking_to_all_stops_social,-2.0728871373961595,-1.73,0,,,-2.0728871373961595 -coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,-0.050333392255275736,-0.46000000000000002,0,,,-0.050333392255275736 -coef_number_of_shop_tours_undertaken_by_the_person,-0.17568161789582087,-0.23999999999999999,0,,,-0.17568161789582087 -coef_number_of_vehicles_social,-0.15477794105663009,-0.19,0,,,-0.15477794105663009 -coef_number_of_work_tours_undertaken_by_the_person_social,-0.0089584068199000319,-0.28000000000000003,0,,,-0.0089584068199000319 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_shopping,-1.4838947085615379,-1.339,0,,,-1.4838947085615379 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_shopping,-3.2620315739726551,-3.1099999999999999,0,,,-3.2620315739726551 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_shopping,-4.4603602952393357,-4.4870000000000001,0,,,-4.4603602952393357 -coef_alternative_specific_constant_for_return_stops_0out_1in_shopping,-1.2344970570494438,-1.179,0,,,-1.2344970570494438 -coef_alternative_specific_constant_for_return_stops_0out_2in_shopping,-2.4998350943155576,-2.3050000000000002,0,,,-2.4998350943155576 -coef_alternative_specific_constant_for_return_stops_0out_3in_shopping,-3.0179726864409173,-3.024,0,,,-3.0179726864409173 -coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_shopping,0.51786237531360479,0.252,0,,,0.51786237531360479 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_shopping,-0.13999198594270704,0.51400000000000001,0,,,-0.13999198594270704 -coef_dummy_for_distance_in_miles_shopping,0.023954475817419198,0.028899999999999999,0,,,0.023954475817419198 -coef_dummy_for_distance_less_than_5_miles,0.16375057013711192,0.37680000000000002,0,,,0.16375057013711192 -coef_dummy_for_female_shopping,0.33555842166191147,0.1721,0,,,0.33555842166191147 -coef_dummy_for_only_adults_participate_in_the_tour,1.8328392426308462,0.19020000000000001,0,,,1.8328392426308462 -coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__shopping,3.0901330214553973,0.90559999999999996,0,,,3.0901330214553973 -coef_dummy_for_walking_to_all_stops_shopping,-1.8757970066056326,-1.4907999999999999,0,,,-1.8757970066056326 -coef_num_kids_between_5_and_15_including_years_old_shopping,-0.041573431257791199,0.0482,0,,,-0.041573431257791199 -coef_number_of_hh_persons_shopping,-0.086440021903122138,-0.1522,0,,,-0.086440021903122138 -coef_number_of_maintenace_tours_tours_undertaken_by_the_person,-0.32594276341704287,-0.19769999999999999,0,,,-0.32594276341704287 -coef_number_of_shop_tours_undertaken_by_the_houshold_shopping,0.148064037095576,-0.073300000000000004,0,,,0.148064037095576 -coef_number_of_university_tours_tours_undertaken_by_the_person_shopping,-0.67089999999999317,-0.67090000000000005,0,,,-0.67089999999999317 -coef_number_of_work_tours_undertaken_by_the_person_shopping,-0.43852307225491766,-0.54799999999999993,0,,,-0.43852307225491766 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout,-1.8947544828670186,-2.1899999999999999,0,,,-1.8947544828670186 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_eatout,-12.056169150387893,-4.516,0,,,-12.056169150387893 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_eatout,-3.6615505167080027,-5.2549999999999999,0,,,-3.6615505167080027 -coef_alternative_specific_constant_for_return_stops_0out_1in_eatout,-1.7027857761249232,-1.7609999999999999,0,,,-1.7027857761249232 -coef_alternative_specific_constant_for_return_stops_0out_2in_eatout,-2.9579857808480341,-3.6970000000000001,0,,,-2.9579857808480341 -coef_alternative_specific_constant_for_return_stops_0out_3in_eatout,-4.7624817489674145,-4.7169999999999996,0,,,-4.7624817489674145 -coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_eatout,-7.6049863056520284,0.93999999999999995,0,,,-7.6049863056520284 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_eatout,-6.3461221747969292,2.0259999999999998,0,,,-6.3461221747969292 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort,-2.2250757954780624,-2.173,0,,,-2.2250757954780624 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_escort,-4.7895755848191897,-4.2939999999999996,0,,,-4.7895755848191897 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_escort,-4.7102122245889007,-4.758,0,,,-4.7102122245889007 -coef_alternative_specific_constant_for_return_stops_0out_1in_escort,-1.2974740994833047,-0.96799999999999997,0,,,-1.2974740994833047 -coef_alternative_specific_constant_for_return_stops_0out_2in_escort,-2.384295363242952,-2.4100000000000001,0,,,-2.384295363242952 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_escort,-4.200646186979724,-1.8069999999999999,0,,,-4.200646186979724 -coef_dummy_for_distance_less_than_5_miles_escort,0.28109442258515044,0.32000000000000001,0,,,0.28109442258515044 -coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__escort,1.399121270410205,0.58999999999999997,0,,,1.399121270410205 -coef_dummy_for_walking_to_all_stops_escort,-0.33797126945456507,-1.9099999999999999,0,,,-0.33797126945456507 -coef_number_of_escort_tours_tours_undertaken_by_the_person_escort,-0.25348532544405961,-0.14999999999999999,0,,,-0.25348532544405961 -coef_number_of_hh_persons_escort,-0.17640711121772834,-0.23999999999999999,0,,,-0.17640711121772834 -coef_number_of_students_in_hh_escort,0.15956368405077143,0.19,0,,,0.15956368405077143 -coef_number_of_work_tours_undertaken_by_the_person_escort,-0.15468473406122965,-0.28999999999999998,0,,,-0.15468473406122965 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_othmaint,-1.7954028317479085,-1.7609999999999999,0,,,-1.7954028317479085 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_othmaint,-2.9624065700982283,-3.661,0,,,-2.9624065700982283 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_othmaint,-3.5347850519252844,-5.4260000000000002,0,,,-3.5347850519252844 -coef_alternative_specific_constant_for_return_stops_0out_1in_othmaint,-0.31247075228968507,-0.58499999999999996,0,,,-0.31247075228968507 -coef_alternative_specific_constant_for_return_stops_0out_2in_othmaint,-0.55780644045958916,-1.48,0,,,-0.55780644045958916 -coef_alternative_specific_constant_for_return_stops_0out_3in_othmaint,-1.4356606147103497,-2.4620000000000002,0,,,-1.4356606147103497 -coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othmaint,-0.36815794089018233,0.41399999999999998,0,,,-0.36815794089018233 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othmaint,-9.3990479541430307,0.48799999999999999,0,,,-9.3990479541430307 -coef_dummy_for_distance_in_miles_othmaint,0.10402635612778853,0.027300000000000001,0,,,0.10402635612778853 -coef_dummy_for_distance_less_than_20_miles_,-1.1515269947782993,-0.40799999999999997,0,,,-1.1515269947782993 -coef_dummy_for_female_othmaint,0.25071759069742156,0.30120000000000002,0,,,0.25071759069742156 -coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othmaint,0.15444184637909519,0.51339999999999997,0,,,0.15444184637909519 -coef_dummy_for_walking_to_all_stops_othmaint,-2.3023894742054765,-1.4329000000000001,0,,,-2.3023894742054765 -coef_middle_to_low_income_hh_,0.16999999999999751,0.17000000000000001,0,,,0.16999999999999751 -coef_number_of_maintenace_tours_undertaken_by_the_houshold,-0.28330678921194874,-0.046800000000000001,0,,,-0.28330678921194874 -coef_number_of_persons_participating_in_the_tour_return_stops_interaction,0.86852209944195768,0.4904,0,,,0.86852209944195768 -coef_number_of_shool_tours_tours_undertaken_by_the_person,-8.3600381729826356,-1.4135,0,,,-8.3600381729826356 -coef_number_of_shop_tours_undertaken_by_the_person_othmaint,-0.2135166522304546,-0.14280000000000001,0,,,-0.2135166522304546 -coef_number_of_university_tours_tours_undertaken_by_the_person_othmaint,-0.62519999999999998,-0.62519999999999998,0,,,-0.62519999999999998 -coef_number_of_work_tours_undertaken_by_the_person_othmaint,-0.37594536286827945,-0.36399999999999999,0,,,-0.37594536286827945 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr,-1.4221678878531314,-1.581,0,,,-1.4221678878531314 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_othdiscr,-2.8848210033043737,-3.323,0,,,-2.8848210033043737 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_othdiscr,-4.252076697537615,-4.6230000000000002,0,,,-4.252076697537615 -coef_alternative_specific_constant_for_return_stops_0out_1in_othdiscr,-1.0106467090607749,-0.92100000000000004,0,,,-1.0106467090607749 -coef_alternative_specific_constant_for_return_stops_0out_2in_othdiscr,-2.4905380449227463,-2.3359999999999999,0,,,-2.4905380449227463 -coef_alternative_specific_constant_for_return_stops_0out_3in_othdiscr,-2.9393725902979506,-2.927,0,,,-2.9393725902979506 -coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othdiscr,0.93746509917896281,0.86299999999999999,0,,,0.93746509917896281 -coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othdiscr,0.1562826739961867,0.93899999999999995,0,,,0.1562826739961867 -coef_arrival_later_than_17_00__othdiscr,-0.36444328163105733,-0.63829999999999998,0,,,-0.36444328163105733 -coef_dummy_for_distance_in_miles_othdiscr,0.050978615843919654,-0.022499999999999999,0,,,0.050978615843919654 -coef_dummy_for_distance_less_than_10_miles_,-0.041691234906133287,0.37559999999999999,0,,,-0.041691234906133287 -coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othdiscr,0.24111825316596613,0.83350000000000002,0,,,0.24111825316596613 -coef_dummy_for_walking_to_all_stops_othdiscr,-2.0711353545710396,-2.4578000000000002,0,,,-2.0711353545710396 -coef_number_of_maintenace_tours_tours_undertaken_by_the_person_othdiscr,-0.63013749629210336,-0.3715,0,,,-0.63013749629210336 -coef_number_of_shool_tours_tours_undertaken_by_the_person_othdiscr,-0.60717706214459344,-0.81759999999999999,0,,,-0.60717706214459344 -coef_number_of_shop_tours_undertaken_by_the_person_othdiscr,-0.61831778671278581,-0.629,0,,,-0.61831778671278581 -coef_number_of_work_tours_undertaken_by_the_person_othdiscr,-0.48765485585276552,-0.61529999999999996,0,,,-0.48765485585276552 -coef_alternative_specific_constant_for_outbound_stops_1out_0in_atwork,-3.4794056872571746,-3.8959999999999999,0,,,-3.4794056872571746 -coef_alternative_specific_constant_for_outbound_stops_2out_0in_atwork,-5.1779127909529326,-5.7089999999999996,0,,,-5.1779127909529326 -coef_alternative_specific_constant_for_outbound_stops_3out_0in_atwork,-6.8972239265618009,-7.3610000000000007,0,,,-6.8972239265618009 -coef_alternative_specific_constant_for_return_stops_0out_1in_atwork,-3.4084307916883305,-3.6709999999999998,0,,,-3.4084307916883305 -coef_alternative_specific_constant_for_return_stops_0out_2in_atwork,-5.5993645137153578,-5.3879999999999999,0,,,-5.5993645137153578 -coef_alternative_specific_constant_for_return_stops_0out_3in_atwork,-7.6012050846491075,-6.21,0,,,-7.6012050846491075 -coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_atwork,2.1051947898870833,2.1269999999999998,0,,,2.1051947898870833 -coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,0.27000000000000002,0.27000000000000002,0,,,0.27000000000000002 -coef_middle_to_low_income_hh__atwork,0.60212861030437703,0.45000000000000001,0,,,0.60212861030437703 -coef_number_of_eating_tours_tours_undertaken_by_the_person,-0.2548910504386343,-0.28000000000000003,0,,,-0.2548910504386343 -coef_primary_destination_accessibility_log_of_it_,0.17070563536066408,0.17999999999999999,0,,,0.17070563536066408 -coef_subtour_departure_less_than_or_equal_to_11am,0.2690647561783549,0.31,0,,,0.2690647561783549 -coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,-0.15252472133506134,0.02,0,,,-0.15252472133506134 -coef_subtour_duration_in_hours_integer_,0.68175040347788651,0.56000000000000005,0,,,0.68175040347788651 -coef_subtour_return_time_greater_or_equal_to_2pm,1.5555725209500013,0.34000000000000002,0,,,1.5555725209500013 +param_name,value,best,initvalue,nullvalue +coef_alternative_specific_constant_for_outbound_stops_1out_0in,-0.64664292294462322,-0.64664292294462322,-0.83300000429153442,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_atwork,-3.4646908445777185,-3.4646908445777185,-3.8959999084472656,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout,-1.9002755809567333,-1.9002755809567333,-2.190000057220459,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort,-2.2236727981595754,-2.2236727981595754,-2.1730000972747803,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr,-1.4225160376379478,-1.4225160376379478,-1.5809999704360962,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_othmaint,-1.7982672995567395,-1.7982672995567395,-1.7610000371932983,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_school,-1.7843866978905401,-1.7843866978905401,-2.122999906539917,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_shopping,-1.4865329275382189,-1.4865329275382189,-1.3389999866485596,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_social,-2.4183081291403341,-2.4183081291403341,-1.0809999704360962,0 +coef_alternative_specific_constant_for_outbound_stops_1out_0in_univ,-2.1599604516652944,-2.1599604516652944,-2.628000020980835,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in,-2.4294460976186265,-2.4294460976186265,-2.6129999160766602,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_atwork,-5.162092909819334,-5.162092909819334,-5.7090001106262207,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_eatout,-12.348235464701929,-12.348235464701929,-4.5159997940063477,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_escort,-4.7869220327015922,-4.7869220327015922,-4.2940001487731934,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_othdiscr,-2.8878858646220089,-2.8878858646220089,-3.3229999542236328,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_othmaint,-2.9665698636514888,-2.9665698636514888,-3.6610000133514404,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_school,-4.2448419370273394,-4.2448419370273394,-3.7980000972747803,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_shopping,-3.2674224134549679,-3.2674224134549679,-3.1099998950958252,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_social,-4.083061579914375,-4.083061579914375,-2.874000072479248,0 +coef_alternative_specific_constant_for_outbound_stops_2out_0in_univ,-3.9124510768537806,-3.9124510768537806,-3.7409999370574951,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in,-3.5882985172757271,-3.5882985172757271,-3.9340000152587891,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_atwork,-6.8802912288167422,-6.8802912288167422,-7.3610000610351562,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_eatout,-3.6740988604843077,-3.6740988604843077,-5.255000114440918,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_escort,-4.7119993374061275,-4.7119993374061275,-4.7579998970031738,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_othdiscr,-4.2547457784063534,-4.2547457784063534,-4.6230001449584961,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_othmaint,-3.5457191991847736,-3.5457191991847736,-5.4260001182556152,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_school,-6.1404126227480189,-6.1404126227480189,-5.8499999046325684,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_shopping,-4.4728129557270648,-4.4728129557270648,-4.4869999885559082,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_social,-14.181486266726454,-14.181486266726454,-4.5520000457763672,0 +coef_alternative_specific_constant_for_outbound_stops_3out_0in_univ,-4.4862998759715698,-4.4862998759715698,-4.9809999465942383,0 +coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,-2.3818839828880933,-2.3818839828880933,-1.7829999923706055,0 +coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,-4.7211128189494742,-4.7211128189494742,-4.0669999122619629,0 +coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,-11.512801227605346,-11.512801227605346,-4.9980001449584961,0 +coef_alternative_specific_constant_for_return_stops_0out_1in,-0.33835620803188837,-0.33835620803188837,-0.44499999284744263,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_atwork,-3.3927653179415662,-3.3927653179415662,-3.6710000038146973,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_eatout,-1.7128159843448749,-1.7128159843448749,-1.7610000371932983,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_escort,-1.2952840546510411,-1.2952840546510411,-0.96799999475479126,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_othdiscr,-1.0109237306426695,-1.0109237306426695,-0.92100000381469727,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_othmaint,-0.31261766892443127,-0.31261766892443127,-0.58499997854232788,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_school,-1.263001355242064,-1.263001355242064,-1.2059999704360962,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_shopping,-1.2369710581521229,-1.2369710581521229,-1.1790000200271606,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_social,0.17362744454328641,0.17362744454328641,-1.1200000047683716,0 +coef_alternative_specific_constant_for_return_stops_0out_1in_univ,-1.5271071961686673,-1.5271071961686673,-2.003000020980835,0 +coef_alternative_specific_constant_for_return_stops_0out_2in,-1.4815144916155247,-1.4815144916155247,-1.7749999761581421,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_atwork,-5.5866314294429644,-5.5866314294429644,-5.3880000114440918,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_eatout,-2.9694905231062454,-2.9694905231062454,-3.6970000267028809,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_escort,-2.382475901775571,-2.382475901775571,-2.4100000858306885,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_othdiscr,-2.4932337056093066,-2.4932337056093066,-2.3359999656677246,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_othmaint,-0.559549687865037,-0.559549687865037,-1.4800000190734863,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_school,-2.7043554260825506,-2.7043554260825506,-2.6719999313354492,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_shopping,-2.5050450260948609,-2.5050450260948609,-2.3050000667572021,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_social,-2.6165947696422243,-2.6165947696422243,-2.7639999389648438,0 +coef_alternative_specific_constant_for_return_stops_0out_2in_univ,-3.3021693186962295,-3.3021693186962295,-3.5099999904632568,0 +coef_alternative_specific_constant_for_return_stops_0out_3in,-1.8983525585535195,-1.8983525585535195,-2.1389999389648438,0 +coef_alternative_specific_constant_for_return_stops_0out_3in_atwork,-7.5705523838869704,-7.5705523838869704,-6.2100000381469727,0 +coef_alternative_specific_constant_for_return_stops_0out_3in_eatout,-4.796417149118664,-4.796417149118664,-4.7170000076293945,0 +coef_alternative_specific_constant_for_return_stops_0out_3in_othdiscr,-2.9420323763794887,-2.9420323763794887,-2.9270000457763672,0 +coef_alternative_specific_constant_for_return_stops_0out_3in_othmaint,-1.4387779329032728,-1.4387779329032728,-2.4619998931884766,0 +coef_alternative_specific_constant_for_return_stops_0out_3in_school,-3.1370907253356171,-3.1370907253356171,-3.3640000820159912,0 +coef_alternative_specific_constant_for_return_stops_0out_3in_shopping,-3.0227423732428385,-3.0227423732428385,-3.0239999294281006,0 +coef_alternative_specific_constant_for_return_stops_0out_3in_social,-3.365589571395263,-3.365589571395263,-3.4509999752044678,0 +coef_alternative_specific_constant_for_return_stops_0out_3in_univ,-3.7066457714767771,-3.7066457714767771,-3.6770000457763672,0 +coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,-1.6502808127233042,-1.6502808127233042,-1.3289999961853027,0 +coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,-4.1259435861090799,-4.1259435861090799,-2.7960000038146973,0 +coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,-4.0391454462416165,-4.0391454462416165,-3.3789999485015869,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,-0.063749295179186538,-0.063749295179186538,0,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,1.488754315051501,1.488754315051501,0.70099997520446777,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_atwork,2.075702350960686,2.075702350960686,2.127000093460083,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_eatout,-7.6034666858545901,-7.6034666858545901,0.93999999761581421,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othdiscr,0.94069720899608722,0.94069720899608722,0.86299997568130493,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othmaint,-0.36444527841576962,-0.36444527841576962,0.414000004529953,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_shopping,0.52573690053968991,0.52573690053968991,0.25200000405311584,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_social,2.4865763319224596,2.4865763319224596,0.49599999189376831,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_univ,1.8527731047949576,1.8527731047949576,1.2719999551773071,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,0.4026073230010761,0.4026073230010761,0.69499999284744263,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_eatout,-6.1299064789603026,-6.1299064789603026,2.0260000228881836,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_escort,-3.7134719215772845,-3.7134719215772845,-1.8070000410079956,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othdiscr,0.17361191938538348,0.17361191938538348,0.93900001049041748,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othmaint,-9.4707846262842086,-9.4707846262842086,0.48800000548362732,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_school,2.0224057350148397,2.0224057350148397,1.1349999904632568,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_shopping,-0.12757312512048605,-0.12757312512048605,0.51399999856948853,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_social,-1.3744527120467618,-1.3744527120467618,0.88200002908706665,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_univ,1.8597722433784889,1.8597722433784889,1.8710000514984131,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,0.32162618139688331,0.32162618139688331,0,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,-4.2949115331788805,-4.2949115331788805,0.51800000667572021,0 +coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,-1.3125472274782721,-1.3125472274782721,1.496999979019165,0 +coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,-1.9993783388249304,-1.9993783388249304,-1.9299999475479126,0 +coef_arrival_later_than_17_00_,1.3712401433259278,1.3712401433259278,1.8377000093460083,0 +coef_arrival_later_than_17_00__othdiscr,-0.36182578620009853,-0.36182578620009853,-0.63830000162124634,0 +coef_arrival_later_than_17_00__social,-0.45958068481537828,-0.45958068481537828,-0.44999998807907104,0 +coef_arrival_later_than_17_00__univ,0.3855005796150392,0.3855005796150392,0.38899999856948853,0 +coef_at_least_one_kid_and_one_adult_participate_in_the_tour,1.8868763384626477,1.8868763384626477,0.37000000476837158,0 +coef_dummy_for_a_return_visiting_tour,-1.4902612723336455,-1.4902612723336455,-0.63999998569488525,0 +coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,0.4774633750050547,0.4774633750050547,0.43999999761581421,0 +coef_dummy_for_all_stops_made_by_transit,-0.67365004739838075,-0.67365004739838075,-0.69999998807907104,0 +coef_dummy_for_an_outbound_visiting_tour,0.33371222702629083,0.33371222702629083,-0.68999999761581421,0 +coef_dummy_for_distance_in_miles,0.04459896461230884,0.04459896461230884,0.0099999997764825821,0 +coef_dummy_for_distance_in_miles_othdiscr,0.050994204723024648,0.050994204723024648,-0.022500000894069672,0 +coef_dummy_for_distance_in_miles_othmaint,0.10425996435025388,0.10425996435025388,0.027300000190734863,0 +coef_dummy_for_distance_in_miles_school,0.095129477447622096,0.095129477447622096,0.043800000101327896,0 +coef_dummy_for_distance_in_miles_shopping,0.024311169311439184,0.024311169311439184,0.028899999335408211,0 +coef_dummy_for_distance_in_miles_social,-0.071016613228709641,-0.071016613228709641,-0.0099999997764825821,0 +coef_dummy_for_distance_less_than_10_miles_,-0.042062943317224627,-0.042062943317224627,0.37560001015663147,0 +coef_dummy_for_distance_less_than_20_miles,-0.69994214881030159,-0.69994214881030159,-0.2199999988079071,0 +coef_dummy_for_distance_less_than_20_miles_,-1.1529791304602006,-1.1529791304602006,-0.40799999237060547,0 +coef_dummy_for_distance_less_than_5_miles,0.16605718344134035,0.16605718344134035,0.37680000066757202,0 +coef_dummy_for_distance_less_than_5_miles_escort,0.27909765242825124,0.27909765242825124,0.31999999284744263,0 +coef_dummy_for_female,0.28229839587426708,0.28229839587426708,0.2199999988079071,0 +coef_dummy_for_female_othmaint,0.25086336764451594,0.25086336764451594,0.30120000243186951,0 +coef_dummy_for_female_school,0.69500027366692196,0.69500027366692196,0.4099000096321106,0 +coef_dummy_for_female_shopping,0.33523175540304978,0.33523175540304978,0.17209999263286591,0 +coef_dummy_for_female_univ,0.51700991234531735,0.51700991234531735,0.73489999771118164,0 +coef_dummy_for_only_adults_participate_in_the_tour,1.823935137209177,1.823935137209177,0.19020000100135803,0 +coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,0.27000001072883606,0.27000001072883606,0.27000001072883606,0 +coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,0.71310000535072282,0.71310000535072282,0.60000002384185791,0 +coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,1.1559795820114029,1.1559795820114029,1.309999942779541,0 +coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,1.9112642049973785,1.9112642049973785,0.95490002632141113,0 +coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__escort,1.4016231431941613,1.4016231431941613,0.5899999737739563,0 +coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othdiscr,0.23693003799296872,0.23693003799296872,0.83350002765655518,0 +coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othmaint,0.15461331684851626,0.15461331684851626,0.51340001821517944,0 +coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__shopping,3.0905565103897032,3.0905565103897032,0.90560001134872437,0 +coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__univ,1.0776052104148675,1.0776052104148675,0.84340000152587891,0 +coef_dummy_for_walking_to_all_stops,-1.4898874048260706,-1.4898874048260706,-1.5399999618530273,0 +coef_dummy_for_walking_to_all_stops_escort,-0.34448329904128916,-0.34448329904128916,-1.9099999666213989,0 +coef_dummy_for_walking_to_all_stops_othdiscr,-2.0623131666705032,-2.0623131666705032,-2.4577999114990234,0 +coef_dummy_for_walking_to_all_stops_othmaint,-2.2984130311760791,-2.2984130311760791,-1.4328999519348145,0 +coef_dummy_for_walking_to_all_stops_school,-1.5166153192565364,-1.5166153192565364,-1.8163000345230103,0 +coef_dummy_for_walking_to_all_stops_shopping,-1.8770352536650028,-1.8770352536650028,-1.4908000230789185,0 +coef_dummy_for_walking_to_all_stops_social,-2.069393000920547,-2.069393000920547,-1.7300000190734863,0 +coef_evening_arrival_19_00_interacted_with_return_tours,0.606474995858996,0.606474995858996,0.31000000238418579,0 +coef_hh_accesibility_for_inbound_tours_interaction,0.24072323322804254,0.24072323322804254,0.24809999763965607,0 +coef_high_income_hh,0.23999999463558197,0.23999999463558197,0.23999999463558197,0 +coef_mid_to_high_income_hh,0.23000000417232513,0.23000000417232513,0.23000000417232513,0 +coef_middle_to_low_income_hh,0.17000000178813934,0.17000000178813934,0.17000000178813934,0 +coef_middle_to_low_income_hh_,0.17000000178813934,0.17000000178813934,0.17000000178813934,0 +coef_middle_to_low_income_hh__atwork,0.5862265411484473,0.5862265411484473,0.44999998807907104,0 +coef_no_stops_if_tour_mode_is_drivetransit,-999,-999,-999,0 +coef_num_kids_between_5_and_15_including_years_old,0.091794962859674076,0.091794962859674076,0.079999998211860657,0 +coef_num_kids_between_5_and_15_including_years_old_shopping,-0.041937522351757225,-0.041937522351757225,0.048200000077486038,0 +coef_number_of_adults_16_years_old_,0.077287692445891232,0.077287692445891232,0.029999999329447746,0 +coef_number_of_cars_number_of_workers,-0.066693087232745682,-0.066693087232745682,0.15999999642372131,0 +coef_number_of_cars_number_of_workers_school,0.29115625638327919,0.29115625638327919,0.53310000896453857,0 +coef_number_of_eating_tours_tours_undertaken_by_the_person,-0.25037573867732094,-0.25037573867732094,-0.2800000011920929,0 +coef_number_of_escort_tours_tours_undertaken_by_the_person,0.09806050880270635,0.09806050880270635,0.20000000298023224,0 +coef_number_of_escort_tours_tours_undertaken_by_the_person_escort,-0.25353945421619623,-0.25353945421619623,-0.15000000596046448,0 +coef_number_of_escort_tours_tours_undertaken_by_the_person_school,2.3120956941836317,2.3120956941836317,1.2365000247955322,0 +coef_number_of_escort_tours_tours_undertaken_by_the_person_univ,1.830804423840976,1.830804423840976,0.90179997682571411,0 +coef_number_of_hh_persons,-0.33185754187761923,-0.33185754187761923,-0.31000000238418579,0 +coef_number_of_hh_persons_escort,-0.17646847789383999,-0.17646847789383999,-0.23999999463558197,0 +coef_number_of_hh_persons_school,-0.59789398459025822,-0.59789398459025822,-0.50599998235702515,0 +coef_number_of_hh_persons_shopping,-0.086269571752504437,-0.086269571752504437,-0.15219999849796295,0 +coef_number_of_hh_persons_univ,-0.3306926246943428,-0.3306926246943428,-0.28270000219345093,0 +coef_number_of_maintenace_tours_tours_undertaken_by_the_person,-0.32592941005324705,-0.32592941005324705,-0.19769999384880066,0 +coef_number_of_maintenace_tours_tours_undertaken_by_the_person_othdiscr,-0.63285637282069895,-0.63285637282069895,-0.37149998545646667,0 +coef_number_of_maintenace_tours_undertaken_by_the_houshold,-0.28437497321740485,-0.28437497321740485,-0.046799998730421066,0 +coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,-0.073331456006935747,-0.073331456006935747,-0.46000000834465027,0 +coef_number_of_persons_participating_in_the_tour_return_stops_interaction,0.86868810623690584,0.86868810623690584,0.49039998650550842,0 +coef_number_of_school_tours_tours_undertaken_by_the_person,0.13029516970232355,0.13029516970232355,-1.5499999523162842,0 +coef_number_of_shool_tours_tours_undertaken_by_the_person,-8.132575401995668,-8.132575401995668,-1.4134999513626099,0 +coef_number_of_shool_tours_tours_undertaken_by_the_person_othdiscr,-0.6130966929400905,-0.6130966929400905,-0.81760001182556152,0 +coef_number_of_shop_tours_undertaken_by_the_houshold,-0.32765232732837346,-0.32765232732837346,-0.05000000074505806,0 +coef_number_of_shop_tours_undertaken_by_the_houshold_shopping,0.14836308529667627,0.14836308529667627,-0.073299996554851532,0 +coef_number_of_shop_tours_undertaken_by_the_person,-0.17448403101684509,-0.17448403101684509,-0.23999999463558197,0 +coef_number_of_shop_tours_undertaken_by_the_person_othdiscr,-0.61731020325001096,-0.61731020325001096,-0.62900000810623169,0 +coef_number_of_shop_tours_undertaken_by_the_person_othmaint,-0.20994314934766711,-0.20994314934766711,-0.14280000329017639,0 +coef_number_of_students_in_hh,0.31655751614649219,0.31655751614649219,0.20999999344348907,0 +coef_number_of_students_in_hh_escort,0.15949746173262461,0.15949746173262461,0.18999999761581421,0 +coef_number_of_subtours_in_the_tour,0.33681763025289185,0.33681763025289185,0.18999999761581421,0 +coef_number_of_university_tours_tours_undertaken_by_the_person,-0.47999998927116394,-0.47999998927116394,-0.47999998927116394,0 +coef_number_of_university_tours_tours_undertaken_by_the_person_othmaint,-0.62519997358322144,-0.62519997358322144,-0.62519997358322144,0 +coef_number_of_university_tours_tours_undertaken_by_the_person_shopping,-0.67089998722076416,-0.67089998722076416,-0.67089998722076416,0 +coef_number_of_vehicles,0.26376160794948833,0.26376160794948833,0.17030000686645508,0 +coef_number_of_vehicles_social,-0.15425969899603631,-0.15425969899603631,-0.18999999761581421,0 +coef_number_of_work_tours_undertaken_by_the_person,-0.17654196807499356,-0.17654196807499356,-0.15000000596046448,0 +coef_number_of_work_tours_undertaken_by_the_person_escort,-0.1509302945890815,-0.1509302945890815,-0.28999999165534973,0 +coef_number_of_work_tours_undertaken_by_the_person_othdiscr,-0.49002581553862051,-0.49002581553862051,-0.61529999971389771,0 +coef_number_of_work_tours_undertaken_by_the_person_othmaint,-0.37756033423406382,-0.37756033423406382,-0.36399999260902405,0 +coef_number_of_work_tours_undertaken_by_the_person_shopping,-0.43906376866089675,-0.43906376866089675,-0.54799997806549072,0 +coef_number_of_work_tours_undertaken_by_the_person_social,-0.0062244254965315264,-0.0062244254965315264,-0.2800000011920929,0 +coef_presence_of_kids_between_0_and_4_including_years_old,0.56347076554717646,0.56347076554717646,0.74000000953674316,0 +coef_presence_of_kids_between_5_and_15_including_years_old,0.1180989290788108,0.1180989290788108,0.25999999046325684,0 +coef_presence_of_kids_between_5_and_15_including_years_old_school,0.02961104507186792,0.02961104507186792,0.32989999651908875,0 +coef_presence_of_kids_between_5_and_15_including_years_old_univ,-0.046419488763570535,-0.046419488763570535,0.68229997158050537,0 +coef_primary_destination_accessibility_log_of_it_,0.17066218967701827,0.17066218967701827,0.18000000715255737,0 +coef_subtour_departure_less_than_or_equal_to_11am,0.26747568517112724,0.26747568517112724,0.31000000238418579,0 +coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,-0.15255084910340322,-0.15255084910340322,0.019999999552965164,0 +coef_subtour_duration_in_hours_integer_,0.68168671797342328,0.68168671797342328,0.56000000238418579,0 +coef_subtour_return_time_greater_or_equal_to_2pm,1.5553971310301449,1.5553971310301449,0.34000000357627869,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_stop_frequency_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_stop_frequency_loglike.csv index c888032785..d60deb239c 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_stop_frequency_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_stop_frequency_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-6184.4158915598673,-6090.2588006296801 +0,-6184.4158913795764,-6090.2665603871901 diff --git a/activitysim/estimation/test/test_larch_estimation/test_tour_and_subtour_mode_choice.csv b/activitysim/estimation/test/test_larch_estimation/test_tour_and_subtour_mode_choice.csv index eb7dd67ad4..8d8064cbb4 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_tour_and_subtour_mode_choice.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_tour_and_subtour_mode_choice.csv @@ -1,302 +1,302 @@ -,value,initvalue,nullvalue,minimum,maximum,best --999,-999,-999,-999,-999,-999,-999 -1,1,1,1,1,1,1 -bike_ASC_auto_deficient_eatout,-95.05184217157273,-1.5691105999999999,0,,,-95.05184217157273 -bike_ASC_auto_sufficient_eatout,-1.464117844170342,-1.2003470999999999,0,,,-1.464117844170342 -bike_ASC_no_auto_eatout,7.2018489969700603,0.86807095999999995,0,,,7.2018489969700603 -coef_age010_trn_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work,0.71970855821176882,0,0,,,0.71970855821176882 -coef_age1619_da_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work,-0.019079686463276232,0,0,,,-0.019079686463276232 -coef_age16p_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social,-1.1399641109136807,-1.3660000000000001,0,,,-1.1399641109136807 -coef_hhsize1_sr_multiplier_eatout_escort_othdiscr_othmaint_school_shopping_social_univ_atwork,0.020999157406492247,0,0,,,0.020999157406492247 -coef_hhsize2_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,-0.0039274834138578957,0,0,,,-0.0039274834138578957 -coef_ivt_eatout_escort_othdiscr_othmaint_shopping_social,-0.016936905425988552,-0.017500000000000002,0,,,-0.016936905425988552 -coef_nest_AUTO,0.71999999999999997,0.71999999999999997,1,0.71999999999999997,0.71999999999999997,0.71999999999999997 -coef_nest_AUTO_DRIVEALONE,0.34999999999999998,0.34999999999999998,1,0.34999999999999998,0.34999999999999998,0.34999999999999998 -coef_nest_AUTO_SHAREDRIDE2,0.34999999999999998,0.34999999999999998,1,0.34999999999999998,0.34999999999999998,0.34999999999999998 -coef_nest_AUTO_SHAREDRIDE3,0.34999999999999998,0.34999999999999998,1,0.34999999999999998,0.34999999999999998,0.34999999999999998 -coef_nest_NONMOTORIZED,0.71999999999999997,0.71999999999999997,1,0.71999999999999997,0.71999999999999997,0.71999999999999997 -coef_nest_RIDEHAIL,0.35999999999999999,0.35999999999999999,1,0.35999999999999999,0.35999999999999999,0.35999999999999999 -coef_nest_TRANSIT,0.71999999999999997,0.71999999999999997,1,0.71999999999999997,0.71999999999999997,0.71999999999999997 -coef_nest_TRANSIT_DRIVEACCESS,0.5,0.5,1,0.5,0.5,0.5 -coef_nest_TRANSIT_WALKACCESS,0.5,0.5,1,0.5,0.5,0.5 -commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork,-38.790613234584711,0.72701850000000001,0,,,-38.790613234584711 -drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork,0.94012379999999995,0.94012379999999995,0,,,0.94012379999999995 -drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork,-25.934367224180519,0.76895475000000002,0,,,-25.934367224180519 -drive_transit_ASC_auto_deficient_eatout,14.683282344019709,0.59980610000000001,0,,,14.683282344019709 -drive_transit_ASC_auto_sufficient_eatout,12.110507359997341,-0.96951586000000001,0,,,12.110507359997341 -drive_transit_ASC_no_auto_all,0,0,0,,,0 -drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social,0.5534042664919846,0.52500000000000002,0,,,0.5534042664919846 -express_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork,-61.526574455540178,0.96923159999999997,0,,,-61.526574455540178 -heavy_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork,-11.341188179738285,0.77061210000000002,0,,,-11.341188179738285 -joint_bike_ASC_auto_deficient_all,-154.53293340147803,-6.0764149999999999,0,,,-154.53293340147803 -joint_bike_ASC_auto_sufficient_all,-108.23845192023519,-6.3760656999999998,0,,,-108.23845192023519 -joint_bike_ASC_no_auto_all,-47.716366793432869,-2.8671598,0,,,-47.716366793432869 -joint_drive_transit_ASC_auto_deficient_all,-36.092321468347947,-5.9632215000000004,0,,,-36.092321468347947 -joint_drive_transit_ASC_auto_sufficient_all,-24.112388481073179,-8.0452849999999998,0,,,-24.112388481073179 -joint_drive_transit_ASC_no_auto_all,0,0,0,0,0,0 -joint_sr2_ASC_auto_deficient_all,0,0,0,0,0,0 -joint_sr2_ASC_auto_sufficient_all,0,0,0,0,0,0 -joint_sr2_ASC_no_auto_all,0,0,0,0,0,0 -joint_sr3p_ASC_auto_deficient_all,-5.3440373640659899,-1.8841692000000001,0,,,-5.3440373640659899 -joint_sr3p_ASC_auto_sufficient_all,-3.3313993635418799,-2.234826,0,,,-3.3313993635418799 -joint_sr3p_ASC_no_auto_all,0.97681497679456009,0.56306710000000004,0,,,0.97681497679456009 -joint_taxi_ASC_auto_deficient_all,-45.521802684568371,-9.8156999999999996,0,,,-45.521802684568371 -joint_taxi_ASC_auto_sufficient_all,-11.709899999999999,-11.709899999999999,0,-11.709899999999999,-11.709899999999999,-11.709899999999999 -joint_taxi_ASC_no_auto_all,-12.836772689761483,-4.5792000000000002,0,,,-12.836772689761483 -joint_tnc_shared_ASC_auto_deficient_all,-37.818891366620065,-11.1572,0,,,-37.818891366620065 -joint_tnc_shared_ASC_auto_sufficient_all,-13.205,-13.205,0,-13.205,-13.205,-13.205 -joint_tnc_shared_ASC_no_auto_all,-24.544220954818456,-4.3002000000000002,0,,,-24.544220954818456 -joint_tnc_single_ASC_auto_deficient_all,-51.742391051044301,-9.8961000000000006,0,,,-51.742391051044301 -joint_tnc_single_ASC_auto_sufficient_all,-14.0159,-14.0159,0,-14.0159,-14.0159,-14.0159 -joint_tnc_single_ASC_no_auto_all,-16.690109945634145,-4.4916999999999998,0,,,-16.690109945634145 -joint_walk_ASC_auto_deficient_all,-1.3109169286458668,-1.9607706,0,,,-1.3109169286458668 -joint_walk_ASC_auto_sufficient_all,-3.6267323534729816,-3.2352156999999999,0,,,-3.6267323534729816 -joint_walk_ASC_no_auto_all,0.96782165602250947,-0.21274700999999999,0,,,0.96782165602250947 -joint_walk_transit_ASC_auto_deficient_all,4.47692459281539,-5.1634482999999998,0,,,4.47692459281539 -joint_walk_transit_ASC_auto_sufficient_all,-18.266087843452436,-18.264534000000001,0,,,-18.266087843452436 -joint_walk_transit_ASC_no_auto_all,13.576834007614055,0.62292415000000001,0,,,13.576834007614055 -local_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork,-12.586753852403735,-0.090703264000000006,0,,,-12.586753852403735 -sr2_ASC_auto_deficient_eatout,0.23544005287595454,0.58823449999999999,0,,,0.23544005287595454 -sr2_ASC_auto_sufficient_eatout,0.45709380576692815,0.86280555000000003,0,,,0.45709380576692815 -sr2_ASC_no_auto_all,5.3017687689662525,0,0,,,5.3017687689662525 -sr3p_ASC_auto_deficient_eatout,-0.084427303598265835,0.046052360000000001,0,,,-0.084427303598265835 -sr3p_ASC_auto_sufficient_eatout,0.5022326090064464,0.84685960000000005,0,,,0.5022326090064464 -sr3p_ASC_no_auto_eatout,5.8000711004385348,0.3219998,0,,,5.8000711004385348 -taxi_ASC_auto_deficient_eatout_othdiscr_social,-34.267917620077426,-3.1316999999999999,0,,,-34.267917620077426 -taxi_ASC_auto_sufficient_eatout_othdiscr_social,-2.3771385102751132,-3.0373999999999999,0,,,-2.3771385102751132 -taxi_ASC_no_auto_eatout_othdiscr_social,-25.802108248945846,0.99229999999999996,0,,,-25.802108248945846 -tnc_shared_ASC_auto_deficient_eatout_othdiscr_social,-2.9229081712184213,-4.3575999999999997,0,,,-2.9229081712184213 -tnc_shared_ASC_auto_sufficient_eatout_othdiscr_social,-3.4681630975727953,-3.6638000000000002,0,,,-3.4681630975727953 -tnc_shared_ASC_no_auto_eatout_othdiscr_social,5.5019116236636574,0.64639999999999997,0,,,5.5019116236636574 -tnc_single_ASC_auto_deficient_eatout_othdiscr_social,-30.032668619901013,-2.9622999999999999,0,,,-30.032668619901013 -tnc_single_ASC_auto_sufficient_eatout_othdiscr_social,-2.0882587225999232,-2.3239000000000001,0,,,-2.0882587225999232 -tnc_single_ASC_no_auto_eatout_othdiscr_social,6.6972430765281166,1.6852,0,,,6.6972430765281166 -walk_ASC_auto_deficient_eatout,2.9644622570813723,3.2746050000000002,0,,,2.9644622570813723 -walk_ASC_auto_sufficient_eatout,0.80408030631941008,1.5516903,0,,,0.80408030631941008 -walk_ASC_no_auto_eatout,10.214310524095858,5.1251173000000003,0,,,10.214310524095858 -walk_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork,0.94012379999999995,0.94012379999999995,0,,,0.94012379999999995 -walk_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork,-11.57159128546653,0.76895475000000002,0,,,-11.57159128546653 -walk_transit_ASC_auto_deficient_eatout,12.342017037167501,-0.038963240000000003,0,,,12.342017037167501 -walk_transit_ASC_auto_sufficient_eatout,10.754005322077003,-1.1126906000000001,0,,,10.754005322077003 -walk_transit_ASC_no_auto_eatout,20.50374109308898,2.5936368000000001,0,,,20.50374109308898 -walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social,0.69084760274299939,0.52500000000000002,0,,,0.69084760274299939 -bike_ASC_auto_deficient_escort,-80.815682010385316,-4.5279280000000002,0,,,-80.815682010385316 -bike_ASC_auto_sufficient_escort,-4.2321601413248553,-5.0631084,0,,,-4.2321601413248553 -bike_ASC_no_auto_escort,-82.613015375494186,-0.71621199999999996,0,,,-82.613015375494186 -drive_transit_ASC_auto_deficient_escort,12.026459792966101,-1.1537067000000001,0,,,12.026459792966101 -drive_transit_ASC_auto_sufficient_escort,-38.422040468436286,-4.6014246999999999,0,,,-38.422040468436286 -sr2_ASC_auto_deficient_escort,-0.028872449257253224,0,0,,,-0.028872449257253224 -sr2_ASC_auto_sufficient_escort,-0.44574542118914673,0,0,,,-0.44574542118914673 -sr3p_ASC_auto_deficient_escort,-0.24177007008960669,-0.40818766000000001,0,,,-0.24177007008960669 -sr3p_ASC_auto_sufficient_escort,-0.57332666707255331,-0.057412530000000003,0,,,-0.57332666707255331 -sr3p_ASC_no_auto_escort,-48.558116584856315,-1.8129267,0,,,-48.558116584856315 -taxi_ASC_auto_deficient_escort_othmaint_shopping,0.22119642025031605,0.17660000000000001,0,,,0.22119642025031605 -taxi_ASC_auto_sufficient_escort_othmaint_shopping,-1.8747078913779172,-1.8055000000000001,0,,,-1.8747078913779172 -taxi_ASC_no_auto_escort_othmaint_shopping,7.3609237955139406,1.8938999999999999,0,,,7.3609237955139406 -tnc_shared_ASC_auto_deficient_escort_othmaint_shopping,-0.24413343003260302,-0.38629999999999998,0,,,-0.24413343003260302 -tnc_shared_ASC_auto_sufficient_escort_othmaint_shopping,-2.7057545852498914,-2.4365000000000001,0,,,-2.7057545852498914 -tnc_shared_ASC_no_auto_escort_othmaint_shopping,6.659950525915475,0.93610000000000004,0,,,6.659950525915475 -tnc_single_ASC_auto_deficient_escort_othmaint_shopping,0.8961844796143621,0.67479999999999996,0,,,0.8961844796143621 -tnc_single_ASC_auto_sufficient_escort_othmaint_shopping,-1.7457428565324109,-1.45,0,,,-1.7457428565324109 -tnc_single_ASC_no_auto_escort_othmaint_shopping,7.4428007891764407,1.8605,0,,,7.4428007891764407 -walk_ASC_auto_deficient_escort,-103.0336443777916,-0.90204656000000005,0,,,-103.0336443777916 -walk_ASC_auto_sufficient_escort,-2.1951400279195017,-0.81160659999999996,0,,,-2.1951400279195017 -walk_ASC_no_auto_escort,7.3688522520263184,2.8012068000000001,0,,,7.3688522520263184 -walk_transit_ASC_auto_deficient_escort,8.7582882394391213,-4.9607039999999998,0,,,8.7582882394391213 -walk_transit_ASC_auto_sufficient_escort,7.5679819008069709,-4.9348470000000004,0,,,7.5679819008069709 -walk_transit_ASC_no_auto_escort,-44.292550039991539,-2.2172081000000001,0,,,-44.292550039991539 -bike_ASC_auto_deficient_othdiscr,0.22855250662092905,-0.092468339999999996,0,,,0.22855250662092905 -bike_ASC_auto_sufficient_othdiscr,-1.9167540400011813,-1.0714596999999999,0,,,-1.9167540400011813 -bike_ASC_no_auto_othdiscr,5.4577562038310869,-0.37642320000000001,0,,,5.4577562038310869 -drive_transit_ASC_auto_deficient_othdiscr,-61.370153497008388,0.31993080000000002,0,,,-61.370153497008388 -drive_transit_ASC_auto_sufficient_othdiscr,11.330970889251063,-0.37859169999999998,0,,,11.330970889251063 -sr2_ASC_auto_deficient_othdiscr,0.73863776841688022,0.6601513,0,,,0.73863776841688022 -sr2_ASC_auto_sufficient_othdiscr,0.1229837233438586,0.49684616999999998,0,,,0.1229837233438586 -sr3p_ASC_auto_deficient_othdiscr,0.935476440999231,1.0470965999999999,0,,,0.935476440999231 -sr3p_ASC_auto_sufficient_othdiscr,0.24598820830201615,0.58850205,0,,,0.24598820830201615 -sr3p_ASC_no_auto_othdiscr,6.4061820861081387,0.27216901999999998,0,,,6.4061820861081387 -walk_ASC_auto_deficient_othdiscr,1.6258274516143363,2.2494074999999998,0,,,1.6258274516143363 -walk_ASC_auto_sufficient_othdiscr,1.0941805514117351,1.2633475999999999,0,,,1.0941805514117351 -walk_ASC_no_auto_othdiscr,8.7710297682817657,3.2665945999999999,0,,,8.7710297682817657 -walk_transit_ASC_auto_deficient_othdiscr,13.266819655208037,0.95308839999999995,0,,,13.266819655208037 -walk_transit_ASC_auto_sufficient_othdiscr,11.302586771209716,-0.80636792999999996,0,,,11.302586771209716 -walk_transit_ASC_no_auto_othdiscr,20.427662059570103,2.2437784999999999,0,,,20.427662059570103 -bike_ASC_auto_deficient_othmaint,-1.5527604047004422,-1.5184648999999999,0,,,-1.5527604047004422 -bike_ASC_auto_sufficient_othmaint,-2.4841948233012818,-2.8083024000000001,0,,,-2.4841948233012818 -bike_ASC_no_auto_othmaint,7.0881917223708513,1.5394334000000001,0,,,7.0881917223708513 -drive_transit_ASC_auto_deficient_othmaint,-65.867616159128147,-0.29943228,0,,,-65.867616159128147 -drive_transit_ASC_auto_sufficient_othmaint,-32.152894844805871,-2.6249478000000002,0,,,-32.152894844805871 -sr2_ASC_auto_deficient_othmaint,-0.17432511879711185,0.26215270000000002,0,,,-0.17432511879711185 -sr2_ASC_auto_sufficient_othmaint,0.22153081726667476,0.25817883000000003,0,,,0.22153081726667476 -sr3p_ASC_auto_deficient_othmaint,-1.7678027401708742,-1.3493925,0,,,-1.7678027401708742 -sr3p_ASC_auto_sufficient_othmaint,-0.25110618149419051,-0.075498670000000004,0,,,-0.25110618149419051 -sr3p_ASC_no_auto_othmaint,4.5931064543486562,-0.80318540000000005,0,,,4.5931064543486562 -walk_ASC_auto_deficient_othmaint,1.8335810139202195,1.3690404,0,,,1.8335810139202195 -walk_ASC_auto_sufficient_othmaint,0.88973692144242589,0.79996339999999999,0,,,0.88973692144242589 -walk_ASC_no_auto_othmaint,6.2906587601839359,1.287299,0,,,6.2906587601839359 -walk_transit_ASC_auto_deficient_othmaint,9.407080733783447,-3.0597257999999998,0,,,9.407080733783447 -walk_transit_ASC_auto_sufficient_othmaint,10.958165434769871,-1.5471172,0,,,10.958165434769871 -walk_transit_ASC_no_auto_othmaint,20.617092448325504,2.5643455999999998,0,,,20.617092448325504 -bike_ASC_auto_deficient_school,-0.41778199451832254,-0.52806779999999998,0,,,-0.41778199451832254 -bike_ASC_auto_sufficient_school,-3.5078886893560863,-2.1134686,0,,,-3.5078886893560863 -bike_ASC_no_auto_school,-28.724176190313326,12.098735,0,,,-28.724176190313326 -coef_age010_trn_multiplier_school_univ,-1.1120244370243391,-1.5548,0,,,-1.1120244370243391 -coef_age1619_da_multiplier_school_univ,-1.5951711270563249,-1.3813,0,,,-1.5951711270563249 -coef_age16p_sr_multiplier_school_univ_work_atwork,-0.72100839095028546,0,0,,,-0.72100839095028546 -coef_hhsize2_sr_multiplier_school_univ,-0.53400766253899179,-0.63590000000000002,0,,,-0.53400766253899179 -coef_ivt_school_univ,-0.021192297603561172,-0.0224,0,,,-0.021192297603561172 -commuter_rail_ASC_school_univ,-32.353210620182892,1.0336205999999999,0,,,-32.353210620182892 -drive_ferry_ASC_school_univ,2.0202317000000001,2.0202317000000001,0,,,2.0202317000000001 -drive_light_rail_ASC_school_univ,-19.108400881329299,1.6814003,0,,,-19.108400881329299 -drive_transit_ASC_auto_deficient_school,-95.982095698903436,5.3252654000000001,0,,,-95.982095698903436 -drive_transit_ASC_auto_sufficient_school,-46.151623937860776,1.4013500000000001,0,,,-46.151623937860776 -drive_transit_CBD_ASC_school_univ,62.459413404223476,0.67200000000000004,0,,,62.459413404223476 -express_bus_ASC_school_univ,0.32496937999999997,0.32496937999999997,0,,,0.32496937999999997 -heavy_rail_ASC_school_univ,-12.380133019206522,0.96200377000000004,0,,,-12.380133019206522 -local_bus_ASC_school_univ,-13.872178494981991,-0.065086210000000005,0,,,-13.872178494981991 -sr2_ASC_auto_deficient_school,0.11627333557951013,0.12474365,0,,,0.11627333557951013 -sr2_ASC_auto_sufficient_school,-1.6466117937376035,-1.6062657,0,,,-1.6466117937376035 -sr3p_ASC_auto_deficient_school,0.72079329001052006,0.71495710000000001,0,,,0.72079329001052006 -sr3p_ASC_auto_sufficient_school,-1.1869716638057384,-1.0201935,0,,,-1.1869716638057384 -sr3p_ASC_no_auto_school,-6.0240829874137232,-6.0240827000000001,0,,,-6.0240829874137232 -taxi_ASC_auto_deficient_school,1.5929016972992514,-0.33379999999999999,0,,,1.5929016972992514 -taxi_ASC_auto_sufficient_school,-1.6320342977823235,-2.4293999999999998,0,,,-1.6320342977823235 -taxi_ASC_no_auto_school_univ,-7,-7,0,-7,-7,-7 -tnc_shared_ASC_auto_deficient_school,0.96832753972334895,-1.4745999999999999,0,,,0.96832753972334895 -tnc_shared_ASC_auto_sufficient_school,-2.7739120530297634,-3.7219000000000002,0,,,-2.7739120530297634 -tnc_shared_ASC_no_auto_school,-7,-7,0,-7,-7,-7 -tnc_single_ASC_auto_deficient_school,-3.3648846265737218,-0.5524,0,,,-3.3648846265737218 -tnc_single_ASC_auto_sufficient_school,-2.3704008497944398,-2.8374999999999999,0,,,-2.3704008497944398 -tnc_single_ASC_no_auto_school,-7,-7,0,-7,-7,-7 -walk_ASC_auto_deficient_school,3.2349172133905824,3.2573623999999999,0,,,3.2349172133905824 -walk_ASC_auto_sufficient_school,0.69222756273388997,0.64768559999999997,0,,,0.69222756273388997 -walk_ASC_no_auto_school,31.884868503149736,18.414556999999999,0,,,31.884868503149736 -walk_ferry_ASC_school_univ,2.0202317000000001,2.0202317000000001,0,,,2.0202317000000001 -walk_light_rail_ASC_school_univ,-12.140651343565191,1.6814003,0,,,-12.140651343565191 -walk_transit_ASC_auto_deficient_school,17.064091325381543,4.1207079999999996,0,,,17.064091325381543 -walk_transit_ASC_auto_sufficient_school,14.160601613148902,0.74590873999999996,0,,,14.160601613148902 -walk_transit_ASC_no_auto_school,48.738094718979411,21.383749000000002,0,,,48.738094718979411 -walk_transit_CBD_ASC_school_univ,0.78788966521195125,0.67200000000000004,0,,,0.78788966521195125 -bike_ASC_auto_deficient_shopping,-0.98208504158712495,-0.87584466000000005,0,,,-0.98208504158712495 -bike_ASC_auto_sufficient_shopping,-4.7656989395473435,-2.5662102999999998,0,,,-4.7656989395473435 -bike_ASC_no_auto_shopping,6.3473397917421011,0.83415550000000005,0,,,6.3473397917421011 -drive_transit_ASC_auto_deficient_shopping,-69.120302733575414,-0.41849177999999998,0,,,-69.120302733575414 -drive_transit_ASC_auto_sufficient_shopping,-74.360368326848842,-2.1718937999999999,0,,,-74.360368326848842 -sr2_ASC_auto_deficient_shopping,0.34099442656713952,0.24409755999999999,0,,,0.34099442656713952 -sr2_ASC_auto_sufficient_shopping,0.14451282933821491,0.19770707000000001,0,,,0.14451282933821491 -sr3p_ASC_auto_deficient_shopping,-0.26249087797911946,-0.073370166000000001,0,,,-0.26249087797911946 -sr3p_ASC_auto_sufficient_shopping,-0.2963226415957782,-0.077571294999999998,0,,,-0.2963226415957782 -sr3p_ASC_no_auto_shopping,5.6484952721990362,-0.27978947999999998,0,,,5.6484952721990362 -walk_ASC_auto_deficient_shopping,2.8036057394781277,2.2701733000000002,0,,,2.8036057394781277 -walk_ASC_auto_sufficient_shopping,0.47346256501524292,0.73126630000000004,0,,,0.47346256501524292 -walk_ASC_no_auto_shopping,8.2155350323455529,2.3768772999999999,0,,,8.2155350323455529 -walk_transit_ASC_auto_deficient_shopping,11.256552971319946,-0.84765690000000005,0,,,11.256552971319946 -walk_transit_ASC_auto_sufficient_shopping,9.7542972055490029,-2.2036798000000002,0,,,9.7542972055490029 -walk_transit_ASC_no_auto_shopping,19.703542063063956,2.1067475999999998,0,,,19.703542063063956 -bike_ASC_auto_deficient_social,-0.26949163972926454,0.63452140000000001,0,,,-0.26949163972926454 -bike_ASC_auto_sufficient_social,-0.85401921523485835,-1.368071,0,,,-0.85401921523485835 -bike_ASC_no_auto_social,5.5137426913975727,0.020583210000000001,0,,,5.5137426913975727 -drive_transit_ASC_auto_deficient_social,-52.758046290102875,1.5627195,0,,,-52.758046290102875 -drive_transit_ASC_auto_sufficient_social,-47.996801808437127,-0.61585575000000004,0,,,-47.996801808437127 -sr2_ASC_auto_deficient_social,1.429304838044295,1.8558528000000001,0,,,1.429304838044295 -sr2_ASC_auto_sufficient_social,0.97730089864256342,0.52360249999999997,0,,,0.97730089864256342 -sr3p_ASC_auto_deficient_social,0.67630143929989783,1.5007242999999999,0,,,0.67630143929989783 -sr3p_ASC_auto_sufficient_social,0.75744513577301464,0.50617886000000001,0,,,0.75744513577301464 -sr3p_ASC_no_auto_social,3.972071101285167,-1.4036902,0,,,3.972071101285167 -walk_ASC_auto_deficient_social,3.1688988708714376,2.8701840000000001,0,,,3.1688988708714376 -walk_ASC_auto_sufficient_social,2.6607837167356201,1.7072186,0,,,2.6607837167356201 -walk_ASC_no_auto_social,6.4445317299061999,1.8680915,0,,,6.4445317299061999 -walk_transit_ASC_auto_deficient_social,12.875988741851154,0.97444487000000002,0,,,12.875988741851154 -walk_transit_ASC_auto_sufficient_social,12.613259624057664,-0.34537590000000001,0,,,12.613259624057664 -walk_transit_ASC_no_auto_social,18.966818965194228,1.3814651,0,,,18.966818965194228 -bike_ASC_auto_deficient_univ,-0.66923500000000002,-0.66923500000000002,0,,,-0.66923500000000002 -bike_ASC_auto_sufficient_univ,-1.9397831999999999,-1.9397831999999999,0,,,-1.9397831999999999 -bike_ASC_no_auto_univ,4.2945156000000004,4.2945156000000004,0,,,4.2945156000000004 -drive_transit_ASC_auto_deficient_univ,1.8501175999999999,1.8501175999999999,0,,,1.8501175999999999 -drive_transit_ASC_auto_sufficient_univ,1.3587753,1.3587753,0,,,1.3587753 -sr2_ASC_auto_deficient_univ,-1.6922345999999999,-1.6922345999999999,0,,,-1.6922345999999999 -sr2_ASC_auto_sufficient_univ,-1.8594269999999999,-1.8594269999999999,0,,,-1.8594269999999999 -sr3p_ASC_auto_deficient_univ,-1.7277422,-1.7277422,0,,,-1.7277422 -sr3p_ASC_auto_sufficient_univ,-1.9047098,-1.9047098,0,,,-1.9047098 -sr3p_ASC_no_auto_univ,-6.0560010000000002,-6.0560010000000002,0,,,-6.0560010000000002 -taxi_ASC_auto_deficient_univ,4.2492000000000001,4.2492000000000001,0,,,4.2492000000000001 -taxi_ASC_auto_sufficient_univ,-0.31309999999999999,-0.31309999999999999,0,,,-0.31309999999999999 -tnc_shared_ASC_auto_deficient_univ,3.25,3.25,0,,,3.25 -tnc_shared_ASC_auto_sufficient_univ,-0.90680000000000005,-0.90680000000000005,0,,,-0.90680000000000005 -tnc_shared_ASC_no_auto_univ,-5.8116000000000003,-5.8116000000000003,0,,,-5.8116000000000003 -tnc_single_ASC_auto_deficient_univ,1.0221,1.0221,0,,,1.0221 -tnc_single_ASC_auto_sufficient_univ,0.20880000000000001,0.20880000000000001,0,,,0.20880000000000001 -tnc_single_ASC_no_auto_univ,-2.5190000000000001,-2.5190000000000001,0,,,-2.5190000000000001 -walk_ASC_auto_deficient_univ,4.5059100000000001,4.5059100000000001,0,,,4.5059100000000001 -walk_ASC_auto_sufficient_univ,1.0607664999999999,1.0607664999999999,0,,,1.0607664999999999 -walk_ASC_no_auto_univ,6.4089669999999996,6.4089669999999996,0,,,6.4089669999999996 -walk_transit_ASC_auto_deficient_univ,3.1362554999999999,3.1362554999999999,0,,,3.1362554999999999 -walk_transit_ASC_auto_sufficient_univ,0.47311629999999999,0.47311629999999999,0,,,0.47311629999999999 -walk_transit_ASC_no_auto_univ,8.7860370000000003,8.7860370000000003,0,,,8.7860370000000003 -bike_ASC_auto_deficient_work,0.1093970633711833,0.25318967999999997,0,,,0.1093970633711833 -bike_ASC_auto_sufficient_work,-1.7147321677779845,-1.5800232000000001,0,,,-1.7147321677779845 -bike_ASC_no_auto_work,7.916152782688358,3.1940088000000002,0,,,7.916152782688358 -coef_hhsize1_sr_multiplier_work,-0.6790273309383883,-0.73458800000000002,0,,,-0.6790273309383883 -coef_ivt_work,-0.013061382875350648,-0.0134,0,,,-0.013061382875350648 -commuter_rail_ASC_work,12.116488014803043,0.72550300000000001,0,,,12.116488014803043 -drive_ferry_ASC_work,0.93322605000000003,0.93322605000000003,0,,,0.93322605000000003 -drive_light_rail_ASC_work,-36.000808246088518,0.82555670000000003,0,,,-36.000808246088518 -drive_transit_ASC_auto_deficient_work,-10.817730116154191,0.10081567,0,,,-10.817730116154191 -drive_transit_ASC_auto_sufficient_work,-11.922033211338155,-1.0045459000000001,0,,,-11.922033211338155 -drive_transit_CBD_ASC_work,1.4326312016814422,1.1000000000000001,0,,,1.4326312016814422 -express_bus_ASC_work,-54.606930216243668,-0.51654739999999999,0,,,-54.606930216243668 -heavy_rail_ASC_work,11.025029288750547,0.64772974999999999,0,,,11.025029288750547 -local_bus_ASC_work,10.288307853536837,0.066895070000000001,0,,,10.288307853536837 -sr2_ASC_auto_deficient_work,0.46312369609634996,-0.33803123000000002,0,,,0.46312369609634996 -sr2_ASC_auto_sufficient_work,-0.39096777455191095,-1.0857458,0,,,-0.39096777455191095 -sr3p_ASC_auto_deficient_work,-0.050072021249821817,-0.85270420000000002,0,,,-0.050072021249821817 -sr3p_ASC_auto_sufficient_work,-0.71640219472524347,-1.4699701999999999,0,,,-0.71640219472524347 -sr3p_ASC_no_auto_work,5.2865327465387555,-0.5831269,0,,,5.2865327465387555 -taxi_ASC_auto_deficient_work,-1.3594600760328026,-1.4765999999999999,0,,,-1.3594600760328026 -taxi_ASC_auto_sufficient_work,-55.988330866418792,-4.8509000000000002,0,,,-55.988330866418792 -taxi_ASC_no_auto_work,9.43236827804283,4.7290999999999999,0,,,9.43236827804283 -tnc_shared_ASC_auto_deficient_work,-2.4348067005945464,-2.1435,0,,,-2.4348067005945464 -tnc_shared_ASC_auto_sufficient_work,-63.386791172965488,-5.3574999999999999,0,,,-63.386791172965488 -tnc_shared_ASC_no_auto_work,-47.309135186133922,3.2429000000000001,0,,,-47.309135186133922 -tnc_single_ASC_auto_deficient_work,-0.78812679103952732,-0.80130000000000001,0,,,-0.78812679103952732 -tnc_single_ASC_auto_sufficient_work,-4.8755977035592224,-4.1946000000000003,0,,,-4.8755977035592224 -tnc_single_ASC_no_auto_work,10.295672942342067,5.7854999999999999,0,,,10.295672942342067 -walk_ASC_auto_deficient_work,2.1275102930594469,2.4010416999999999,0,,,2.1275102930594469 -walk_ASC_auto_sufficient_work,0.17637095807617828,0.053265337000000003,0,,,0.17637095807617828 -walk_ASC_no_auto_work,10.356832861443557,5.7672157000000004,0,,,10.356832861443557 -walk_ferry_ASC_work,0.93322605000000003,0.93322605000000003,0,,,0.93322605000000003 -walk_light_rail_ASC_work,11.204407103182628,0.82555670000000003,0,,,11.204407103182628 -walk_transit_ASC_auto_deficient_work,-9.7699412444923333,0.65302855000000004,0,,,-9.7699412444923333 -walk_transit_ASC_auto_sufficient_work,-11.327002198633336,-0.89165070000000002,0,,,-11.327002198633336 -walk_transit_ASC_no_auto_work,-0.8184290314119107,5.0354165999999996,0,,,-0.8184290314119107 -walk_transit_CBD_ASC_work,0.97698021606324725,0.80400000000000005,0,,,0.97698021606324725 -bike_ASC_auto_deficient_atwork,-1.3755365229511889,-0.80740829999999997,0,,,-1.3755365229511889 -bike_ASC_auto_sufficient_atwork,15.727786619761421,15.72017,0,,,15.727786619761421 -bike_ASC_no_auto_atwork,-28.399708381108002,-0.90725845000000005,0,,,-28.399708381108002 -coef_age010_trn_multiplier_atwork,0.00072199999999999999,0.00072199999999999999,0,,,0.00072199999999999999 -coef_age1619_da_multiplier_atwork,-0.80694718452625747,0.0032336000000000001,0,,,-0.80694718452625747 -coef_ivt_atwork,-0.021019454866270101,-0.018800000000000001,0,,,-0.021019454866270101 -drive_transit_ASC_auto_deficient_atwork,-998.81960000000004,-998.81960000000004,0,,,-998.81960000000004 -drive_transit_ASC_auto_sufficient_atwork,-999.21465999999998,-999.21465999999998,0,,,-999.21465999999998 -drive_transit_CBD_ASC_atwork,0.56399999999999995,0.56399999999999995,0,,,0.56399999999999995 -sr2_ASC_auto_deficient_atwork,-1.892695657391221,-2.1102420999999998,0,,,-1.892695657391221 -sr2_ASC_auto_sufficient_atwork,-0.65249983963035285,-1.4450618,0,,,-0.65249983963035285 -sr3p_ASC_auto_deficient_atwork,-2.383158561544211,-2.5146579999999998,0,,,-2.383158561544211 -sr3p_ASC_auto_sufficient_atwork,-0.82204450780308591,-1.652174,0,,,-0.82204450780308591 -sr3p_ASC_no_auto_atwork,6.2362869423849405,0.58266260000000003,0,,,6.2362869423849405 -taxi_ASC_auto_deficient_atwork,-28.540908119718239,-4.4046000000000003,0,,,-28.540908119718239 -taxi_ASC_auto_sufficient_atwork,-28.643971281649424,-2.8803999999999998,0,,,-28.643971281649424 -taxi_ASC_no_auto_atwork,10.212879604829233,4.1021000000000001,0,,,10.212879604829233 -tnc_shared_ASC_auto_deficient_atwork,-3.912212918042727,-4.5088999999999997,0,,,-3.912212918042727 -tnc_shared_ASC_auto_sufficient_atwork,-2.6881377816112022,-3.5396999999999998,0,,,-2.6881377816112022 -tnc_shared_ASC_no_auto_atwork,9.0603158795129275,3.3672,0,,,9.0603158795129275 -tnc_single_ASC_auto_deficient_atwork,-3.1078735470600058,-3.7625999999999999,0,,,-3.1078735470600058 -tnc_single_ASC_auto_sufficient_atwork,-2.6270251391593975,-2.7988,0,,,-2.6270251391593975 -tnc_single_ASC_no_auto_atwork,10.48194785788473,4.4981999999999998,0,,,10.48194785788473 -walk_ASC_auto_deficient_atwork,1.82422508083581,0.92546092999999996,0,,,1.82422508083581 -walk_ASC_auto_sufficient_atwork,1.428722206355812,0.67721600000000004,0,,,1.428722206355812 -walk_ASC_no_auto_atwork,12.824108683156906,6.6692130000000001,0,,,12.824108683156906 -walk_transit_ASC_auto_deficient_atwork,8.9851772342267946,-2.9988291,0,,,8.9851772342267946 -walk_transit_ASC_auto_sufficient_atwork,9.1279962633935359,-3.401027,0,,,9.1279962633935359 -walk_transit_ASC_no_auto_atwork,21.234895822541418,2.7041876,0,,,21.234895822541418 -walk_transit_CBD_ASC_atwork,0.35194949771152162,0.56399999999999995,0,,,0.35194949771152162 +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +1,1,1,1,0 +bike_ASC_auto_deficient_atwork,-1.3785489288550536,-1.3785489288550536,-0.80740827322006226,0 +bike_ASC_auto_deficient_eatout,-13.478289059952681,-13.478289059952681,-1.569110631942749,0 +bike_ASC_auto_deficient_escort,-12.549532816371221,-12.549532816371221,-4.5279278755187988,0 +bike_ASC_auto_deficient_othdiscr,0.23084257669564343,0.23084257669564343,-0.092468343675136566,0 +bike_ASC_auto_deficient_othmaint,-1.5508409145945901,-1.5508409145945901,-1.5184649229049683,0 +bike_ASC_auto_deficient_school,-0.4215455293721031,-0.4215455293721031,-0.52806782722473145,0 +bike_ASC_auto_deficient_shopping,-0.98162820928675221,-0.98162820928675221,-0.87584465742111206,0 +bike_ASC_auto_deficient_social,-0.26248269451457257,-0.26248269451457257,0.63452142477035522,0 +bike_ASC_auto_deficient_univ,-0.6692349910736084,-0.6692349910736084,-0.6692349910736084,0 +bike_ASC_auto_deficient_work,0.10890208866785125,0.10890208866785125,0.25318968296051025,0 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a/activitysim/estimation/test/test_larch_estimation/test_workplace_location.csv b/activitysim/estimation/test/test_larch_estimation/test_workplace_location.csv index 4fbab98906..528d77a9ba 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_workplace_location.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_workplace_location.csv @@ -1,35 +1,35 @@ -,value,initvalue,nullvalue,minimum,maximum,best --999,-999,-999,-999,-999,-999,-999 -1,1,1,1,1,1,1 -coef_dist_0_1,-1.0822922946274103,-0.84279999999999999,0,-25,25,-1.0822922946274103 -coef_dist_0_5_high,0.1207879915621165,0.14999999999999999,0,-25,25,0.1207879915621165 -coef_dist_15_up,-0.091700000000000004,-0.091700000000000004,0,-25,25,-0.091700000000000004 -coef_dist_1_2,-0.24766620079389307,-0.31040000000000001,0,-25,25,-0.24766620079389307 -coef_dist_2_5,-0.3685512775196465,-0.37830000000000003,0,-25,25,-0.3685512775196465 -coef_dist_5_15,-0.15169975841932976,-0.1285,0,-25,25,-0.15169975841932976 -coef_dist_5_up_high,-0.015068815366553389,0.02,0,-25,25,-0.015068815366553389 -coef_mode_logsum,0.1608428973358158,0.29999999999999999,0,-25,25,0.1608428973358158 -work_high_AGREMPN,-5.414473039484391,-5.1159958097540823,0,-6,6,-5.414473039484391 -work_high_FPSEMPN,-2.0198354749074623,-1.575036485716768,0,-6,6,-2.0198354749074623 -work_high_HEREMPN,-1.5774962961301324,-1.258781040820931,0,-6,6,-1.5774962961301324 -work_high_MWTEMPN,-2.0728064576402221,-1.4312917270506265,0,-6,6,-2.0728064576402221 -work_high_OTHEMPN,-2.1440619487784449,-1.870802676568508,0,-6,6,-2.1440619487784449 -work_high_RETEMPN,-2.2072749131897207,-2.2072749131897207,0,-2.2072749131897207,-2.2072749131897207,-2.2072749131897207 -work_low_AGREMPN,-5.8479826351063204,-4.6051701859880909,0,-6,6,-5.8479826351063204 -work_low_FPSEMPN,-0.64550992870675994,-1.6450650900772514,0,-6,6,-0.64550992870675994 -work_low_HEREMPN,0.10934025159883133,-0.95972028980149104,0,-6,6,0.10934025159883133 -work_low_MWTEMPN,-0.35351399513998311,-1.8078888511579385,0,-6,6,-0.35351399513998311 -work_low_OTHEMPN,-0.68434316293298214,-2.120263536200091,0,-6,6,-0.68434316293298214 -work_low_RETEMPN,-2.0479428746204649,-2.0479428746204649,0,-2.0479428746204649,-2.0479428746204649,-2.0479428746204649 -work_med_AGREMPN,-6,-4.8283137373023015,0,-6,6,-6 -work_med_FPSEMPN,-1.9402118373687092,-1.6245515502441485,0,-6,6,-1.9402118373687092 -work_med_HEREMPN,-1.3812045016840873,-1.1239300966523995,0,-6,6,-1.3812045016840873 -work_med_MWTEMPN,-0.90824261771266779,-1.5606477482646683,0,-6,6,-0.90824261771266779 -work_med_OTHEMPN,-2.533158060495702,-1.9732813458514451,0,-6,6,-2.533158060495702 -work_med_RETEMPN,-2.120263536200091,-2.120263536200091,0,-2.120263536200091,-2.120263536200091,-2.120263536200091 -work_veryhigh_AGREMPN,-0.27766271475654764,-5.521460917862246,0,-6,6,-0.27766271475654764 -work_veryhigh_FPSEMPN,-1.7531684994723506,-1.3093333199837622,0,-6,6,-1.7531684994723506 -work_veryhigh_HEREMPN,-1.6190143529862893,-1.422958345491482,0,-6,6,-1.6190143529862893 -work_veryhigh_MWTEMPN,-1.7198536938187046,-1.4024237430497744,0,-6,6,-1.7198536938187046 -work_veryhigh_OTHEMPN,-2.4806660321461727,-1.9241486572738007,0,-6,6,-2.4806660321461727 -work_veryhigh_RETEMPN,-2.375155785828881,-2.375155785828881,0,-2.375155785828881,-2.375155785828881,-2.375155785828881 +param_name,value,best,initvalue,nullvalue +-999,-999,-999,-999,0 +1,1,1,1,0 +coef_dist_0_1,-0.30581956658755333,-0.30581956658755333,-0.84280002117156982,0 +coef_dist_0_5_high,-0.037591580411684179,-0.037591580411684179,0.15000000596046448,0 +coef_dist_15_up,-0.091700002551078796,-0.091700002551078796,-0.091700002551078796,0 +coef_dist_1_2,0.36403861650270469,0.36403861650270469,-0.31040000915527344,0 +coef_dist_2_5,0.074928140378863833,0.074928140378863833,-0.3783000111579895,0 +coef_dist_5_15,0.042013884570839009,0.042013884570839009,-0.12849999964237213,0 +coef_dist_5_up_high,-0.091028422362310263,-0.091028422362310263,0.019999999552965164,0 +coef_mode_logsum,0.30841772929564437,0.30841772929564437,0.30000001192092896,0 +work_high_AGREMPN,-5.1363934448871946,-5.1363934448871946,-5.1159958839416504,0 +work_high_FPSEMPN,-6,-6,-1.5750365257263184,0 +work_high_HEREMPN,-5.8758079453903402,-5.8758079453903402,-1.2587810754776001,0 +work_high_MWTEMPN,-6,-6,-1.4312916994094849,0 +work_high_OTHEMPN,-4.7871339627162968,-4.7871339627162968,-1.870802640914917,0 +work_high_RETEMPN,-2.2072749137878418,-2.2072749137878418,-2.2072749137878418,0 +work_low_AGREMPN,-4.62261674278023,-4.62261674278023,-4.6051702499389648,0 +work_low_FPSEMPN,-6,-6,-1.6450650691986084,0 +work_low_HEREMPN,-5.0606787642354085,-5.0606787642354085,-0.95972031354904175,0 +work_low_MWTEMPN,-5.9999999999999991,-5.9999999999999991,-1.8078888654708862,0 +work_low_OTHEMPN,-4.6880188560666634,-4.6880188560666634,-2.1202635765075684,0 +work_low_RETEMPN,-2.0479428768157959,-2.0479428768157959,-2.0479428768157959,0 +work_med_AGREMPN,-4.8408567797905402,-4.8408567797905402,-4.8283138275146484,0 +work_med_FPSEMPN,-6,-6,-1.62455153465271,0 +work_med_HEREMPN,-5.4208328700623296,-5.4208328700623296,-1.1239300966262817,0 +work_med_MWTEMPN,-5.8367726149021344,-5.8367726149021344,-1.56064772605896,0 +work_med_OTHEMPN,-4.8724459817438781,-4.8724459817438781,-1.9732813835144043,0 +work_med_RETEMPN,-2.1202635765075684,-2.1202635765075684,-2.1202635765075684,0 +work_veryhigh_AGREMPN,-5.543114854785494,-5.543114854785494,-5.521461009979248,0 +work_veryhigh_FPSEMPN,-6,-6,-1.309333324432373,0 +work_veryhigh_HEREMPN,-5.6530572756846489,-5.6530572756846489,-1.4229583740234375,0 +work_veryhigh_MWTEMPN,-6,-6,-1.4024237394332886,0 +work_veryhigh_OTHEMPN,-5.8240005358464035,-5.8240005358464035,-1.9241486787796021,0 +work_veryhigh_RETEMPN,-2.3751556873321533,-2.3751556873321533,-2.3751556873321533,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_workplace_location_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_workplace_location_loglike.csv index 71e9b13b18..dcd02282b7 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_workplace_location_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_workplace_location_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-13535.154991016063,-13520.930381371694 +0,-8694.16639312677943963,-7268.65904321087054996 diff --git a/activitysim/estimation/test/test_larch_estimation/test_workplace_location_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_workplace_location_size_spec.csv index b568bafc7b..f6d6b17462 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_workplace_location_size_spec.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_workplace_location_size_spec.csv @@ -1,8 +1,8 @@ ,segment,model_selector,TOTHH,RETEMPN,FPSEMPN,HEREMPN,OTHEMPN,AGREMPN,MWTEMPN,AGE0519,HSENROLL,COLLFTE,COLLPTE -0,work_low,workplace,0,0.04331096924066484,0.17606247084331519,0.37453642466033488,0.16935644669165648,0.000968861288590913,0.23576482727543777,0,0,0,0 -1,work_med,workplace,0,0.11999183383359351,0.14366373395357587,0.25125860903337882,0.079402445282216183,0.0024785834941433989,0.40320479440309209,0,0,0,0 -2,work_high,workplace,0,0.15790294154771911,0.19045576988955706,0.29641460514585227,0.1682066889662423,0.0063903077215986892,0.18062968672903063,0,0,0,0 -3,work_veryhigh,workplace,0,0.062641019242734242,0.11667678718376452,0.13342796655219047,0.056368476597385232,0.51025642529636983,0.12062932512755588,0,0,0,0 +0,work_low,workplace,0,0.8096367605074406,0.015557278192424053,0.039799319567405213,0.057772317445170702,0.06167704609513544,0.015557278192424065,0,0,0,0 +1,work_med,workplace,0,0.8254493658270311,0.017050704122867678,0.030427859824865577,0.052654174261774579,0.054344027646221538,0.020073868317239382,0,0,0,0 +2,work_high,workplace,0,0.83346467076784692,0.018781385164327268,0.02126490971714939,0.063163857701673223,0.044543791484676111,0.018781385164327268,0,0,0,0 +3,work_veryhigh,workplace,0,0.85845344910642152,0.022880571461814655,0.032369961125427262,0.027283649594894748,0.03613179724962709,0.022880571461814655,0,0,0,0 4,university,school,0,0,0,0,0,0,0,0,0,0.59199999999999997,0.40799999999999997 5,gradeschool,school,0,0,0,0,0,0,0,1,0,0,0 6,highschool,school,0,0,0,0,0,0,0,0,1,0,0 diff --git a/activitysim/examples/example_estimation/build_full_mtc_example.py b/activitysim/examples/example_estimation/build_full_mtc_example.py new file mode 100644 index 0000000000..1d92a35acd --- /dev/null +++ b/activitysim/examples/example_estimation/build_full_mtc_example.py @@ -0,0 +1,195 @@ +""" +This script builds estimation data bundles for the full MTC example for ActivitySim. + +It does so by running ActivitySim twice: once to create synthetic survey data and then +a second time to create the estimation data bundles. For "real" applications, the +synthetic survey data would not be generated by ActivitySim; it would be real survey data. + +It downloads the necessary example data, runs the ActivitySim model with specified configurations, +and processes the output data. The script accepts the working directory and household sample size +as command-line arguments. + +Functions: + download_example(download_dir: Path) -> Path: + Downloads the prototype MTC extended example data to the specified directory. + + main(working_dir: Path, household_sample_size: int): + Main function that sets up directories, runs the ActivitySim model, and processes the output data. + +Usage: + python build-full-mtc.py -d -s + +Arguments: + -d, --directory: Directory to use as the working directory. Defaults to '/tmp/edb-test'. + -s, --household_sample_size: Household sample size. Defaults to 2000. +""" + +from __future__ import annotations + +import argparse +import os +import shutil +import subprocess +import time +from pathlib import Path + +from activitysim.examples.external import download_external_example + + +def download_example(download_dir): + example_dir = download_external_example( + name="prototype_mtc_extended", + working_dir=download_dir, + url="https://github.com/ActivitySim/activitysim-prototype-mtc/archive/refs/heads/extended.tar.gz", + assets={ + "data_full.tar.zst": { + "url": "https://github.com/ActivitySim/activitysim-prototype-mtc/releases/download/v1.3.4/data_full.tar.zst", + "sha256": "b402506a61055e2d38621416dd9a5c7e3cf7517c0a9ae5869f6d760c03284ef3", + "unpack": "data_full", + }, + "test/prototype_mtc_reference_pipeline.zip": { + "url": "https://github.com/ActivitySim/activitysim-prototype-mtc/releases/download/v1.3.2/prototype_mtc_extended_reference_pipeline.zip", + "sha256": "4d94b6a8a83225dda17e9ca19c9110bc1df2df5b4b362effa153d1c8d31524f5", + }, + }, + ) + return example_dir + + +def main(working_dir: Path, household_sample_size: int, skip_to_edb: bool = False): + working_dir = Path(working_dir) + working_dir.mkdir(parents=True, exist_ok=True) + + script_dir = Path(__file__).resolve().parent + infer_py = script_dir / "scripts" / "infer.py" + + print(f'The current CONDA environment is {os.getenv("CONDA_DEFAULT_ENV")}') + + configs_dir = working_dir / "activitysim-prototype-mtc-extended" / "configs" + full_data_dir = working_dir / "activitysim-prototype-mtc-extended" / "data_full" + pseudosurvey_dir = working_dir / "activitysim-prototype-mtc-extended" / "output" + + if not skip_to_edb: + download_example(working_dir) + + subprocess.run( + [ + "python", + "-m", + "activitysim", + "run", + "-c", + str(configs_dir), + "-d", + str(full_data_dir), + "-o", + str(pseudosurvey_dir), + "--households_sample_size", + str(household_sample_size), + ], + check=True, + ) + + survey_data_dir = pseudosurvey_dir / "survey_data" + survey_data_dir.mkdir(parents=True, exist_ok=True) + + for file in pseudosurvey_dir.glob("final_*.csv"): + shutil.copy(str(file), str(survey_data_dir)) + + files_to_copy = [ + "final_households.csv", + "final_persons.csv", + "final_tours.csv", + "final_joint_tour_participants.csv", + "final_trips.csv", + ] + + for file_name in files_to_copy: + src = pseudosurvey_dir / file_name + dest = survey_data_dir / file_name.replace("final_", "survey_") + shutil.copy(src, dest) + + output_dir = working_dir / "infer-output" + output_dir.mkdir(parents=True, exist_ok=True) + output_dir.joinpath(".gitignore").write_text("**\n") + + subprocess.run( + [ + "python", + str(infer_py), + str(pseudosurvey_dir), + str(configs_dir), + str(output_dir), + ], + check=True, + ) + + for file in output_dir.glob("override_*.csv"): + shutil.copy(str(file), str(full_data_dir)) + + edb_dir = working_dir / "activitysim-prototype-mtc-extended" / "output-est-mode" + edb_dir.mkdir(parents=True, exist_ok=True) + + subprocess.run( + [ + "python", + "-m", + "activitysim", + "run", + "-c", + str(script_dir / "configs_estimation"), + "-c", + str(configs_dir), + "-d", + str(full_data_dir), + "-o", + str(edb_dir), + ], + check=True, + ) + + # mark the entire created directory as ignored for git + edb_dir.parent.joinpath(".gitignore").write_text("**\n") + + # create a success.txt file to indicate that the EDB was successfully built + completed_at = time.strftime("%Y-%m-%d %H:%M:%S") + edb_dir.joinpath("success.txt").write_text( + f"Successfully built the full MTC estimation data bundle example with {household_sample_size} households.\n" + f"Completed at {completed_at}" + ) + + +def as_needed(working_dir: Path, household_sample_size: int): + """Check if the EDB directory has already been built. If not, build it.""" + edb_dir = ( + Path(working_dir) / "activitysim-prototype-mtc-extended" / "output-est-mode" + ) + if not edb_dir.joinpath("success.txt").exists(): + main(working_dir, household_sample_size) + else: + print("EDB directory already populated.") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Build the full MTC example.") + parser.add_argument( + "-d", + "--directory", + type=str, + default="/tmp/edb-test", + help="Directory to use as the working directory. Defaults to '/tmp/edb-test'.", + ) + parser.add_argument( + "-s", + "--household_sample_size", + type=int, + default=2000, + help="Household sample size. Defaults to 2000.", + ) + parser.add_argument( + "--skip_to_edb", + action="store_true", + help="Skip to EDB step. Defaults to False.", + ) + args = parser.parse_args() + main(args.directory, args.household_sample_size, args.skip_to_edb) diff --git a/activitysim/examples/example_estimation/configs/estimation.yaml b/activitysim/examples/example_estimation/configs/estimation.yaml index 7e8112c0f0..b6bb5831ab 100644 --- a/activitysim/examples/example_estimation/configs/estimation.yaml +++ b/activitysim/examples/example_estimation/configs/estimation.yaml @@ -60,7 +60,7 @@ estimation_table_recipes: alternatives_combined: - interaction_sample_alternatives - interaction_expression_values - omnibus_tables_append_columns: [choosers_combined] + omnibus_tables_append_columns: [choosers_combined, alternatives_combined] interaction_simulate: omnibus_tables: @@ -97,7 +97,7 @@ estimation_table_recipes: omnibus_tables_append_columns: [values_combined] -model_estimation_table_types: +estimation_table_types: school_location: interaction_sample_simulate workplace_location: interaction_sample_simulate auto_ownership: simple_simulate diff --git a/activitysim/examples/example_estimation/configs_estimation/estimation.yaml b/activitysim/examples/example_estimation/configs_estimation/estimation.yaml new file mode 100644 index 0000000000..1f7bdfa6cd --- /dev/null +++ b/activitysim/examples/example_estimation/configs_estimation/estimation.yaml @@ -0,0 +1,129 @@ +EDB_ALTS_FILE_FORMAT: compact # options: compact, verbose +EDB_FILETYPE: parquet # options: csv, parquet, pkl + +enable: True + +bundles: + - school_location + - workplace_location + - auto_ownership + - vehicle_type_choice + - free_parking + - cdap + - mandatory_tour_frequency + - mandatory_tour_scheduling_work + - mandatory_tour_scheduling_school + - joint_tour_frequency + - joint_tour_composition + - joint_tour_participation + - joint_tour_destination + - joint_tour_scheduling + - non_mandatory_tour_frequency + - non_mandatory_tour_destination + - non_mandatory_tour_scheduling + - tour_mode_choice + - atwork_subtour_frequency + - atwork_subtour_destination + - atwork_subtour_scheduling + - atwork_subtour_mode_choice + - stop_frequency + - trip_purpose + - trip_destination + - trip_scheduling + - trip_mode_choice + +# - atwork_subtour_mode_choice subtours.tour_mode + +survey_tables: + households: + file_name: override_households.csv + index_col: household_id + persons: + file_name: override_persons.csv + index_col: person_id + tours: + file_name: override_tours.csv + index_col: tour_id + joint_tour_participants: + file_name: override_joint_tour_participants.csv + index_col: participant_id + trips: + file_name: override_trips.csv + index_col: trip_id + +estimation_table_recipes: + + interaction_sample_simulate: + omnibus_tables: + choosers_combined: + - choices + - override_choices + - choosers + alternatives_combined: + - interaction_sample_alternatives + - interaction_expression_values + omnibus_tables_append_columns: [choosers_combined, alternatives_combined] + + interaction_simulate: + omnibus_tables: + choosers_combined: + - choices + - override_choices + - choosers + omnibus_tables_append_columns: [choosers_combined] + + simple_simulate: + omnibus_tables: + values_combined: + - choices + - override_choices + - expression_values + - choosers + omnibus_tables_append_columns: [values_combined] + + cdap_simulate: + omnibus_tables: + values_combined: + - choices + - override_choices + - choosers + omnibus_tables_append_columns: [values_combined] + + simple_probabilistic: + omnibus_tables: + values_combined: + - choices + - override_choices + - choosers + - probs + omnibus_tables_append_columns: [values_combined] + + +estimation_table_types: + school_location: interaction_sample_simulate + workplace_location: interaction_sample_simulate + auto_ownership: simple_simulate + vehicle_type_choice: interaction_simulate + free_parking: simple_simulate + cdap: cdap_simulate + mandatory_tour_frequency: simple_simulate + mandatory_tour_scheduling_work: interaction_sample_simulate + mandatory_tour_scheduling_school: interaction_sample_simulate + joint_tour_frequency: simple_simulate + joint_tour_composition: simple_simulate + joint_tour_participation: simple_simulate + joint_tour_destination: interaction_sample_simulate + joint_tour_scheduling: interaction_sample_simulate + non_mandatory_tour_frequency: interaction_simulate + non_mandatory_tour_destination: interaction_sample_simulate + non_mandatory_tour_scheduling: interaction_sample_simulate + tour_mode_choice: simple_simulate + atwork_subtour_frequency: simple_simulate + atwork_subtour_destination: interaction_sample_simulate + atwork_subtour_scheduling: interaction_sample_simulate + atwork_subtour_mode_choice: simple_simulate + stop_frequency: simple_simulate + trip_purpose: simple_probabilistic + trip_destination: interaction_sample_simulate + trip_scheduling: simple_probabilistic + trip_mode_choice: simple_simulate diff --git a/activitysim/examples/example_estimation/configs_estimation/logging.yaml b/activitysim/examples/example_estimation/configs_estimation/logging.yaml new file mode 100644 index 0000000000..f4902943d6 --- /dev/null +++ b/activitysim/examples/example_estimation/configs_estimation/logging.yaml @@ -0,0 +1,67 @@ +# Config for logging +# ------------------ +# See http://docs.python.org/2.7/library/logging.config.html#configuration-dictionary-schema + +logging: + version: 1 + disable_existing_loggers: true + + + # Configuring the default (root) logger is highly recommended + root: + level: NOTSET + handlers: [console, logfile, elogfile] + + loggers: + + estimation: + level: DEBUG + handlers: [console, elogfile] + propagate: false + + activitysim: + level: INFO + handlers: [console, logfile] + propagate: false + + orca: + level: WARN + handlers: [console, logfile] + propagate: false + + handlers: + + elogfile: + class: logging.FileHandler + filename: + get_log_file_path: 'estimation.log' + mode: w + formatter: fileFormatter + level: NOTSET + + logfile: + class: logging.FileHandler + filename: + get_log_file_path: 'activitysim.log' + mode: w + formatter: fileFormatter + level: NOTSET + + console: + class: logging.StreamHandler + stream: ext://sys.stdout + formatter: simpleFormatter + level: NOTSET + + formatters: + + simpleFormatter: + class: logging.Formatter + # format: '%(levelname)s - %(name)s - %(message)s' + format: '%(levelname)s - %(message)s' + datefmt: '%d/%m/%Y %H:%M:%S' + + fileFormatter: + class: logging.Formatter + format: '%(asctime)s - %(levelname)s - %(name)s - %(message)s' + datefmt: '%d/%m/%Y %H:%M:%S' diff --git a/activitysim/examples/example_estimation/configs_estimation/settings.yaml b/activitysim/examples/example_estimation/configs_estimation/settings.yaml new file mode 100644 index 0000000000..1e96b0f1a5 --- /dev/null +++ b/activitysim/examples/example_estimation/configs_estimation/settings.yaml @@ -0,0 +1,165 @@ + +inherit_settings: True + +# assume enough RAM to not chunk +chunk_training_mode: disabled + +# input tables +input_table_list: + # + # households (table index 'household_id') + # + - tablename: households + filename: override_households.csv + index_col: household_id + keep_columns: + - home_zone_id + - income + - hhsize + - HHT + - auto_ownership + - num_workers + # + # persons (table index 'person_id') + # + - tablename: persons + filename: override_persons.csv + keep_columns: + - household_id + - age + - PNUM + - sex + - pemploy + - pstudent + - ptype + # + # land_use (table index 'zone_id') + # + - tablename: land_use + filename: land_use.csv + rename_columns: + # accept either TAZ or ZONE (but not both) + TAZ: zone_id + ZONE: zone_id + COUNTY: county_id + keep_columns: + - DISTRICT + - SD + - county_id + - TOTHH + - TOTPOP + - TOTACRE + - RESACRE + - CIACRE + - TOTEMP + - AGE0519 + - RETEMPN + - FPSEMPN + - HEREMPN + - OTHEMPN + - AGREMPN + - MWTEMPN + - PRKCST + - OPRKCST + - area_type + - HSENROLL + - COLLFTE + - COLLPTE + - TOPOLOGY + - TERMINAL + +write_raw_tables: False +rng_base_seed: 42 + +fail_fast: True + +use_shadow_pricing: False + +# turn writing of sample_tables on and off for all models +# (if True, tables will be written if DEST_CHOICE_SAMPLE_TABLE_NAME is specified in individual model settings) +want_dest_choice_sample_tables: False + +# number of households to simulate +households_sample_size: 0 + +# to resume after last successful checkpoint, specify resume_after: _ +#resume_after: initialize_households + +trace_hh_id: + +multiprocess: true +num_processes: 2 + + +output_tables: + h5_store: False + action: include + prefix: final_ + sort: True + tables: + - checkpoints + - accessibility + - land_use + - households + - persons + - tours + - trips + - joint_tour_participants + +resume_after: + +models: + - initialize_landuse + - initialize_households + - compute_accessibility + - school_location + - workplace_location + - auto_ownership_simulate + - free_parking + - cdap_simulate + - mandatory_tour_frequency + - mandatory_tour_scheduling + - joint_tour_frequency + - joint_tour_composition + - joint_tour_participation + - joint_tour_destination + - joint_tour_scheduling + - non_mandatory_tour_frequency + - non_mandatory_tour_destination + - non_mandatory_tour_scheduling + - tour_mode_choice_simulate + - atwork_subtour_frequency + - atwork_subtour_destination + - atwork_subtour_scheduling + - atwork_subtour_mode_choice + - stop_frequency + - trip_purpose + - trip_destination +# - trip_purpose_and_destination + - trip_scheduling + - trip_mode_choice +# - write_data_dictionary +# - track_skim_usage +# - write_trip_matrices + - write_tables + - coalesce_estimation_data_bundles + + +multiprocess_steps: + - name: mp_initialize + begin: initialize_landuse + - name: mp_accessibility + begin: compute_accessibility + slice: + tables: + - accessibility + # don't slice any tables not explicitly listed above in slice.tables + exclude: True + - name: mp_households + begin: school_location + slice: + tables: + - households + - persons + - name: mp_summarize + begin: write_tables diff --git a/activitysim/examples/example_estimation/notebooks/02_school_location.ipynb b/activitysim/examples/example_estimation/notebooks/02_school_location.ipynb index f838803020..8562928ae1 100644 --- a/activitysim/examples/example_estimation/notebooks/02_school_location.ipynb +++ b/activitysim/examples/example_estimation/notebooks/02_school_location.ipynb @@ -26,30 +26,73 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.31.dev37+gd94e3a6',\n", + " 'sharrow': '2.12.2.dev4+gea8174f',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import larch # !conda install larch #for estimation\n", + "import larch as lx\n", "import pandas as pd\n", - "import numpy as np\n", - "import yaml \n", - "import larch.util.excel\n", - "import os" + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "prepare()" ] }, { @@ -72,10 +115,27 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/school_location/school_location_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/school_location/school_location_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/school_location/school_location_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/school_location/school_location_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/school_location/school_location_landuse.csv\n", + "loading from output-est-mode/estimation_data_bundle/school_location/school_location_size_terms.csv\n" + ] + } + ], "source": [ "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname, return_data=True, \n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + ")" ] }, { @@ -266,148 +326,130 @@ " \n", " \n", " person_id\n", - " variable\n", - " 5\n", - " 9\n", - " 10\n", - " 12\n", - " 13\n", - " 14\n", - " 37\n", - " 39\n", - " ...\n", - " 178\n", - " 179\n", - " 180\n", - " 181\n", - " 182\n", - " 184\n", - " 186\n", - " 187\n", - " 189\n", - " 190\n", + " alt_dest\n", + " prob\n", + " pick_count\n", + " mode_choice_logsum\n", + " size_term\n", + " shadow_price_size_term_adjustment\n", + " shadow_price_utility_adjustment\n", + " util_dist_0_1\n", + " util_dist_1_2\n", + " util_dist_2_5\n", + " util_dist_5_15\n", + " util_dist_15_up\n", + " util_size_variable\n", + " util_utility_adjustment\n", + " util_no_attractions\n", + " util_mode_choice_logsum\n", + " util_sample_of_corrections_factor\n", " \n", " \n", " \n", " \n", " 0\n", - " 629\n", - " mode_choice_logsum\n", - " -1.2112310566711697\n", - " -0.932235390015777\n", - " -0.9960110406421955\n", - " -1.2780595287661722\n", - " -1.4547553701284834\n", - " -1.4573412829661365\n", - " -3.8602604963599583\n", - " -3.8673170163655084\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", + " 1918\n", + " 13\n", + " 0.006688\n", + " 1\n", + " -0.748611\n", + " 2578.276039\n", + " 1\n", + " 0\n", + " 1.0\n", + " 1.00\n", + " 3.00\n", + " 2.18\n", + " 0.000000\n", + " 7.855264\n", + " 0\n", + " False\n", + " -0.748611\n", + " 5.007436\n", " \n", " \n", " 1\n", - " 629\n", - " pick_count\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", + " 1918\n", + " 69\n", + " 0.034697\n", + " 2\n", + " -1.228993\n", + " 4541.220657\n", + " 1\n", + " 0\n", " 1.0\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", + " 1.00\n", + " 3.00\n", + " 0.02\n", + " 0.000000\n", + " 8.421171\n", + " 0\n", + " False\n", + " -1.228993\n", + " 4.054244\n", " \n", " \n", " 2\n", - " 629\n", - " prob\n", - " 3.964160543594042e-05\n", - " 0.0016781637363059928\n", - " 0.0006643895574387415\n", - " 0.00279311489869619\n", - " 0.0021809528368544094\n", - " 0.000462535262887269\n", - " 0.0001419935499379287\n", - " 0.00020956937572710045\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", + " 1918\n", + " 133\n", + " 0.249356\n", + " 5\n", + " -0.916451\n", + " 13419.153743\n", + " 1\n", + " 0\n", + " 1.0\n", + " 1.00\n", + " 1.46\n", + " 0.00\n", + " 0.000000\n", + " 9.504513\n", + " 0\n", + " False\n", + " -0.916451\n", + " 2.998311\n", " \n", " \n", " 3\n", - " 629\n", - " shadow_price_size_term_adjustment\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", + " 1918\n", + " 185\n", + " 0.073783\n", + " 6\n", + " 0.075435\n", + " 146.752243\n", + " 1\n", + " 0\n", " 1.0\n", - 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15744 rows × 192 columns

\n", + "

280374 rows × 18 columns

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NaN NaN NaN NaN NaN NaN NaN NaN \n", + " util_dist_2_5 util_dist_5_15 util_dist_15_up util_size_variable \\\n", + "0 3.00 2.18 0.000000 7.855264 \n", + "1 3.00 0.02 0.000000 8.421171 \n", + "2 1.46 0.00 0.000000 9.504513 \n", + "3 0.00 0.00 0.000000 4.995537 \n", + "4 0.21 0.00 0.000000 9.605815 \n", + "... ... ... ... ... \n", + "280369 3.00 10.00 12.840000 7.760123 \n", + "280370 3.00 10.00 15.450001 9.884101 \n", + "280371 3.00 10.00 10.639999 9.183034 \n", + "280372 3.00 10.00 19.779999 8.047318 \n", + "280373 0.32 0.00 0.000000 9.183034 \n", "\n", - " 189 190 \n", - "0 NaN NaN \n", - "1 NaN NaN \n", - "2 NaN NaN \n", - "3 NaN NaN \n", - "4 NaN NaN \n", - "... ... ... \n", - "15739 NaN NaN \n", - "15740 NaN NaN \n", - "15741 NaN NaN \n", - "15742 NaN NaN \n", - "15743 NaN NaN \n", + " util_utility_adjustment util_no_attractions util_mode_choice_logsum \\\n", + "0 0 False -0.748611 \n", + "1 0 False -1.228993 \n", + "2 0 False -0.916451 \n", + "3 0 False 0.075435 \n", + "4 0 False -0.494830 \n", + "... ... ... ... \n", + "280369 0 False -7.651546 \n", + "280370 0 False -8.962833 \n", + "280371 0 False -7.268993 \n", + "280372 0 False -10.470374 \n", + "280373 0 False 4.218881 \n", "\n", - "[15744 rows x 192 columns]" + " util_sample_of_corrections_factor \n", + "0 5.007436 \n", + "1 4.054244 \n", + "2 2.998311 \n", + "3 4.398386 \n", + "4 3.346785 \n", + "... ... \n", + "280369 5.340517 \n", + "280370 3.812534 \n", + "280371 3.757005 \n", + "280372 4.866794 \n", + "280373 3.452616 \n", + "\n", + "[280374 rows x 18 columns]" ] }, "execution_count": 6, @@ -680,48 +717,48 @@ " \n", " \n", " 0\n", - " 629\n", - " 13\n", - " 12\n", - " 131\n", + " 1918\n", + " 188\n", + " 188\n", + " 186\n", " 3\n", - " 629\n", + " 1918\n", " \n", " \n", " 1\n", - " 1274\n", - " 10\n", - " 10\n", - " 166\n", + " 2256\n", + " 133\n", + " 229\n", + " 208\n", " 3\n", - " 1274\n", + " 2256\n", " \n", " \n", " 2\n", - " 27266\n", - " 10\n", - " 12\n", - " 9\n", + " 3215\n", + " 291\n", + " 229\n", + " 252\n", " 3\n", - " 27266\n", + " 3215\n", " \n", " \n", " 3\n", - " 28012\n", - " 5\n", - " 5\n", - " 10\n", + " 4362\n", + " 300\n", + " 342\n", + " 313\n", " 3\n", - " 28012\n", + " 4362\n", " \n", " \n", " 4\n", - " 29368\n", - " 185\n", - " 185\n", - " 16\n", + " 5859\n", + " 490\n", + " 490\n", + " 400\n", " 3\n", - " 29368\n", + " 5859\n", " \n", " \n", " ...\n", @@ -733,83 +770,83 @@ " ...\n", " \n", " \n", - " 979\n", - " 7514214\n", - " 185\n", - " 185\n", - " 56\n", - " 3\n", - " 2822879\n", + " 14984\n", + " 7550994\n", + " 1091\n", + " 1091\n", + " 1124\n", + " 2\n", + " 2859659\n", " \n", " \n", - " 980\n", - " 7514777\n", - " 185\n", - " 185\n", - " 106\n", - " 3\n", - " 2823442\n", + " 14985\n", + " 7552418\n", + " 1270\n", + " 1263\n", + " 1268\n", + " 2\n", + " 2861083\n", " \n", " \n", - " 981\n", - " 7515185\n", - " 188\n", - " 188\n", - " 142\n", - " 3\n", - " 2823850\n", + " 14986\n", + " 7553232\n", + " 1324\n", + " 1324\n", + " 1320\n", + " 2\n", + " 2861897\n", " \n", " \n", - " 982\n", - " 7527597\n", - " 69\n", - " 13\n", - " 188\n", + " 14987\n", + " 7560173\n", + " 557\n", + " 811\n", + " 743\n", " 3\n", - " 2836262\n", + " 2868838\n", " \n", " \n", - " 983\n", - " 7541072\n", - " 112\n", - " 107\n", - " 117\n", + " 14988\n", + " 7561903\n", + " 1127\n", + " 1127\n", + " 1121\n", " 3\n", - " 2849737\n", + " 2870568\n", " \n", " \n", "\n", - "

984 rows × 6 columns

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14989 rows × 6 columns

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"979 2822879 \n", - "980 2823442 \n", - "981 2823850 \n", - "982 2836262 \n", - "983 2849737 \n", + " household_id \n", + "0 1918 \n", + "1 2256 \n", + "2 3215 \n", + "3 4362 \n", + "4 5859 \n", + "... ... \n", + "14984 2859659 \n", + "14985 2861083 \n", + "14986 2861897 \n", + "14987 2868838 \n", + "14988 2870568 \n", "\n", - "[984 rows x 6 columns]" + "[14989 rows x 6 columns]" ] }, "execution_count": 7, @@ -916,9 +953,9 @@ " 7\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 3\n", " 5.89564\n", " 2.875000\n", @@ -940,9 +977,9 @@ " 19\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.84871\n", " 5.195214\n", @@ -964,9 +1001,9 @@ " 38\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.53231\n", " 80.470405\n", @@ -988,9 +1025,9 @@ " 20\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 2\n", " 5.64330\n", " 7.947368\n", @@ -1012,9 +1049,9 @@ " 86\n", " ...\n", " 0\n", - " 0.00000\n", + " 0.0\n", " 72.14684\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.52555\n", " 38.187500\n", @@ -1047,188 +1084,188 @@ " ...\n", " \n", " \n", - " 186\n", - " 4\n", - " 4\n", - " 1\n", - " 2779\n", - " 8062\n", - " 376.0\n", - " 172.0\n", - " 15.00000\n", - " 1760\n", - " 1178\n", + " 1450\n", + " 34\n", + " 34\n", + " 9\n", + " 2724\n", + " 6493\n", + " 1320.0\n", + " 630.0\n", + " 69.00000\n", + " 1046\n", + " 1013\n", " ...\n", - " 3\n", - " 0.00000\n", - " 0.00000\n", + " 4\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - " 2.04173\n", - " 14.860963\n", - " 9.411765\n", - " 5.762347\n", + " 1.12116\n", + " 3.896996\n", + " 1.496423\n", + " 1.081235\n", " False\n", " \n", " \n", - " 187\n", - " 4\n", - " 4\n", - " 1\n", - " 1492\n", - " 4139\n", - " 214.0\n", - " 116.0\n", - " 10.00000\n", - " 808\n", - " 603\n", + " 1451\n", + " 34\n", + " 34\n", + " 9\n", + " 2016\n", + " 4835\n", + " 664.0\n", + " 379.0\n", + " 43.00000\n", + " 757\n", + " 757\n", " ...\n", - " 3\n", - 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" 2\n", - " 0.00000\n", - " 0.00000\n", + " 5\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - " 2.88773\n", - " 45.461538\n", - " 2.897436\n", - " 2.723836\n", + " 1.01972\n", + " 0.688222\n", + " 2.129330\n", + " 0.520115\n", " False\n", " \n", " \n", - " 190\n", - " 4\n", - " 4\n", - " 1\n", - " 968\n", - " 1647\n", - " 1381.0\n", - " 14.0\n", - " 28.00000\n", - " 1010\n", - " 114\n", + " 1454\n", + " 34\n", + " 34\n", + " 9\n", + " 1068\n", + " 2337\n", + " 10469.0\n", + " 1114.0\n", + " 27.00000\n", + " 607\n", + " 418\n", " ...\n", - " 3\n", - " 0.00000\n", - " 0.00000\n", + " 5\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - " 2.60309\n", - " 23.047619\n", - " 24.047619\n", - " 11.768501\n", + " 0.95542\n", + " 0.936021\n", + " 0.531989\n", + " 0.339203\n", " False\n", " \n", " \n", "\n", - "

190 rows × 28 columns

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1454 rows × 28 columns

\n", "" ], "text/plain": [ - " DISTRICT SD county_id TOTHH TOTPOP TOTACRE RESACRE CIACRE \\\n", - "zone_id \n", - "1 1 1 1 46 82 20.3 1.0 15.00000 \n", - "2 1 1 1 134 240 31.1 1.0 24.79297 \n", - "3 1 1 1 267 476 14.7 1.0 2.31799 \n", - "4 1 1 1 151 253 19.3 1.0 18.00000 \n", - "5 1 1 1 611 1069 52.7 1.0 15.00000 \n", - "... ... .. ... ... ... ... ... ... \n", - "186 4 4 1 2779 8062 376.0 172.0 15.00000 \n", - "187 4 4 1 1492 4139 214.0 116.0 10.00000 \n", - "188 4 4 1 753 4072 232.0 11.0 178.00000 \n", - "189 4 4 1 3546 8476 201.0 72.0 6.00000 \n", - "190 4 4 1 968 1647 1381.0 14.0 28.00000 \n", + " DISTRICT SD county_id TOTHH TOTPOP TOTACRE RESACRE CIACRE \\\n", + "zone_id \n", + "1 1 1 1 46 82 20.3 1.0 15.00000 \n", + "2 1 1 1 134 240 31.1 1.0 24.79297 \n", + "3 1 1 1 267 476 14.7 1.0 2.31799 \n", + "4 1 1 1 151 253 19.3 1.0 18.00000 \n", + "5 1 1 1 611 1069 52.7 1.0 15.00000 \n", + "... ... .. ... ... ... ... ... ... \n", + "1450 34 34 9 2724 6493 1320.0 630.0 69.00000 \n", + "1451 34 34 9 2016 4835 664.0 379.0 43.00000 \n", + "1452 34 34 9 2178 5055 1068.0 602.0 35.00000 \n", + "1453 34 34 9 298 779 14195.0 429.0 4.00000 \n", + "1454 34 34 9 1068 2337 10469.0 1114.0 27.00000 \n", "\n", - " TOTEMP AGE0519 ... area_type HSENROLL COLLFTE \\\n", - "zone_id ... \n", - "1 27318 7 ... 0 0.00000 0.00000 \n", - "2 42078 19 ... 0 0.00000 0.00000 \n", - "3 2445 38 ... 0 0.00000 0.00000 \n", - "4 22434 20 ... 0 0.00000 0.00000 \n", - "5 15662 86 ... 0 0.00000 72.14684 \n", - "... ... ... ... ... ... ... \n", - "186 1760 1178 ... 3 0.00000 0.00000 \n", - "187 808 603 ... 3 0.00000 0.00000 \n", - "188 4502 1117 ... 2 3961.04761 17397.79102 \n", - "189 226 1057 ... 2 0.00000 0.00000 \n", - "190 1010 114 ... 3 0.00000 0.00000 \n", + " TOTEMP AGE0519 ... area_type HSENROLL COLLFTE COLLPTE \\\n", + "zone_id ... \n", + "1 27318 7 ... 0 0.0 0.00000 0.0 \n", + "2 42078 19 ... 0 0.0 0.00000 0.0 \n", + "3 2445 38 ... 0 0.0 0.00000 0.0 \n", + "4 22434 20 ... 0 0.0 0.00000 0.0 \n", + "5 15662 86 ... 0 0.0 72.14684 0.0 \n", + "... ... ... ... ... ... ... ... \n", + "1450 1046 1013 ... 4 0.0 0.00000 0.0 \n", + "1451 757 757 ... 4 0.0 0.00000 0.0 \n", + "1452 2110 789 ... 4 0.0 0.00000 0.0 \n", + "1453 922 88 ... 5 0.0 0.00000 0.0 \n", + "1454 607 418 ... 5 0.0 0.00000 0.0 \n", "\n", - " COLLPTE TOPOLOGY TERMINAL household_density \\\n", - "zone_id \n", - "1 0.00000 3 5.89564 2.875000 \n", - "2 0.00000 1 5.84871 5.195214 \n", - "3 0.00000 1 5.53231 80.470405 \n", - "4 0.00000 2 5.64330 7.947368 \n", - "5 0.00000 1 5.52555 38.187500 \n", - "... ... ... ... ... \n", - "186 0.00000 1 2.04173 14.860963 \n", - "187 0.00000 2 1.73676 11.841270 \n", - "188 11152.93652 1 2.28992 3.984127 \n", - "189 0.00000 1 2.88773 45.461538 \n", - "190 0.00000 1 2.60309 23.047619 \n", + " TOPOLOGY TERMINAL household_density employment_density \\\n", + "zone_id \n", + "1 3 5.89564 2.875000 1707.375000 \n", + "2 1 5.84871 5.195214 1631.374751 \n", + "3 1 5.53231 80.470405 736.891913 \n", + "4 2 5.64330 7.947368 1180.736842 \n", + "5 1 5.52555 38.187500 978.875000 \n", + "... ... ... ... ... \n", + "1450 1 1.12116 3.896996 1.496423 \n", + "1451 1 1.17116 4.777251 1.793839 \n", + "1452 1 1.17587 3.419152 3.312402 \n", + "1453 1 1.01972 0.688222 2.129330 \n", + "1454 1 0.95542 0.936021 0.531989 \n", "\n", - " employment_density density_index is_cbd \n", - "zone_id \n", - "1 1707.375000 2.870167 False \n", - "2 1631.374751 5.178722 False \n", - "3 736.891913 72.547987 False \n", - "4 1180.736842 7.894233 False \n", - "5 978.875000 36.753679 False \n", - "... ... ... ... \n", - "186 9.411765 5.762347 False \n", - "187 6.412698 4.159890 False \n", - "188 23.820106 3.413233 False \n", - "189 2.897436 2.723836 False \n", - "190 24.047619 11.768501 False \n", + " density_index is_cbd \n", + "zone_id \n", + "1 2.870167 False \n", + "2 5.178722 False \n", + "3 72.547987 False \n", + "4 7.894233 False \n", + "5 36.753679 False \n", + "... ... ... \n", + "1450 1.081235 False \n", + "1451 1.304140 False \n", + "1452 1.682465 False \n", + "1453 0.520115 False \n", + "1454 0.339203 False \n", "\n", - "[190 rows x 28 columns]" + "[1454 rows x 28 columns]" ] }, "execution_count": 8, @@ -1498,31 +1535,129 @@ "data.size_spec" ] }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
keyvalue
ca
['AGE0519*(school_segment==1)',\n",
+       " 'COLLFTE*(school_segment==3)',\n",
+       " 'COLLPTE*(school_segment==3)',\n",
+       " 'HSENROLL*(school_segment==2)',\n",
+       " 'util_dist_0_1*(school_segment==1)',\n",
+       " 'util_dist_0_1*(school_segment==2)',\n",
+       " 'util_dist_0_1*(school_segment==3)',\n",
+       " 'util_dist_15_up*(school_segment==1)',\n",
+       " 'util_dist_15_up*(school_segment==2)',\n",
+       " 'util_dist_15_up*(school_segment==3)',\n",
+       " 'util_dist_1_2*(school_segment==1)',\n",
+       " 'util_dist_1_2*(school_segment==2)',\n",
+       " 'util_dist_1_2*(school_segment==3)',\n",
+       " 'util_dist_2_5*(school_segment==1)',\n",
+       " 'util_dist_2_5*(school_segment==2)',\n",
+       " 'util_dist_2_5*(school_segment==3)',\n",
+       " 'util_dist_5_15*(school_segment==1)',\n",
+       " 'util_dist_5_15*(school_segment==2)',\n",
+       " 'util_dist_5_15*(school_segment==3)',\n",
+       " 'util_mode_choice_logsum*(school_segment==1)',\n",
+       " 'util_mode_choice_logsum*(school_segment==2)',\n",
+       " 'util_mode_choice_logsum*(school_segment==3)',\n",
+       " 'util_no_attractions*(school_segment==1)',\n",
+       " 'util_no_attractions*(school_segment==2)',\n",
+       " 'util_no_attractions*(school_segment==3)',\n",
+       " 'util_sample_of_corrections_factor*(school_segment==1)',\n",
+       " 'util_sample_of_corrections_factor*(school_segment==2)',\n",
+       " 'util_sample_of_corrections_factor*(school_segment==3)']
choice_ca'override_choice == _original_zone_id'
avail_ca'_avail_'
" + ], + "text/plain": [ + "┣ ca: ['AGE0519*(school_segment==1)',\n", + "┃ 'COLLFTE*(school_segment==3)',\n", + "┃ 'COLLPTE*(school_segment==3)',\n", + "┃ 'HSENROLL*(school_segment==2)',\n", + "┃ 'util_dist_0_1*(school_segment==1)',\n", + "┃ 'util_dist_0_1*(school_segment==2)',\n", + "┃ 'util_dist_0_1*(school_segment==3)',\n", + "┃ 'util_dist_15_up*(school_segment==1)',\n", + "┃ 'util_dist_15_up*(school_segment==2)',\n", + "┃ 'util_dist_15_up*(school_segment==3)',\n", + "┃ 'util_dist_1_2*(school_segment==1)',\n", + "┃ 'util_dist_1_2*(school_segment==2)',\n", + "┃ 'util_dist_1_2*(school_segment==3)',\n", + "┃ 'util_dist_2_5*(school_segment==1)',\n", + "┃ 'util_dist_2_5*(school_segment==2)',\n", + "┃ 'util_dist_2_5*(school_segment==3)',\n", + "┃ 'util_dist_5_15*(school_segment==1)',\n", + "┃ 'util_dist_5_15*(school_segment==2)',\n", + "┃ 'util_dist_5_15*(school_segment==3)',\n", + "┃ 'util_mode_choice_logsum*(school_segment==1)',\n", + "┃ 'util_mode_choice_logsum*(school_segment==2)',\n", + "┃ 'util_mode_choice_logsum*(school_segment==3)',\n", + "┃ 'util_no_attractions*(school_segment==1)',\n", + "┃ 'util_no_attractions*(school_segment==2)',\n", + "┃ 'util_no_attractions*(school_segment==3)',\n", + "┃ 'util_sample_of_corrections_factor*(school_segment==1)',\n", + "┃ 'util_sample_of_corrections_factor*(school_segment==2)',\n", + "┃ 'util_sample_of_corrections_factor*(school_segment==3)']\n", + "┣ choice_ca: 'override_choice == _original_zone_id'\n", + "┣ avail_ca: '_avail_'" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.required_data()" + ] + }, { "cell_type": "markdown", "metadata": {}, "source": [ - "# Estimate\n", - "\n", - "With the model setup for estimation, the next step is to estimate the model coefficients. Make sure to use a sufficiently large enough household sample and set of zones to avoid an over-specified model, which does not have a numerically stable likelihood maximizing solution. Larch has a built-in estimation methods including BHHH, and also offers access to more advanced general purpose non-linear optimizers in the `scipy` package, including SLSQP, which allows for bounds and constraints on parameters. BHHH is the default and typically runs faster, but does not follow constraints on parameters." + "Running the `doctor` method will check the model specification for potential issues." ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "dictx()\n" ] - }, + } + ], + "source": [ + "model, problems = model.doctor()\n", + "\n", + "print(problems)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Estimate\n", + "\n", + "With the model setup for estimation, the next step is to estimate the model coefficients. Make sure to use a sufficiently large enough household sample and set of zones to avoid an over-specified model, which does not have a numerically stable likelihood maximizing solution. Larch has a built-in estimation methods including BHHH, and also offers access to more advanced general purpose non-linear optimizers in the `scipy` package, including SLSQP, which allows for bounds and constraints on parameters. BHHH is the default and typically runs faster, but does not follow constraints on parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ { "data": { "text/html": [ - "

Iteration 006 [Optimization terminated successfully.]

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Iteration 013 [Optimization terminated successfully]

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Best LL = -4058.719620832402

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tolerance4.213233078884777e-06stepsarray([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])message'Optimization terminated successfully'elapsed_time0:00:00.994749method'BHHH'n_cases14989iteration_number13
" ], "text/plain": [ - "┣ loglike: -4058.719620832402\n", + "┣ loglike: -30424.700914962996\n", "┣ x: -999 -999.000000\n", "┃ 1 1.000000\n", - "┃ coef_grade_dist_0_1 -1.824840\n", - "┃ coef_grade_dist_15_up -0.046000\n", - "┃ coef_grade_dist_5_15 -0.144663\n", - "┃ coef_high_dist_0_1 -2.106211\n", - "┃ coef_high_dist_15_up -0.188200\n", - "┃ coef_high_dist_5_15 -0.101747\n", - "┃ coef_high_grade_dist_1_2 -0.751852\n", - "┃ coef_high_grade_dist_2_5 -0.667119\n", - "┃ coef_mode_logsum 0.372245\n", - "┃ coef_univ_dist_0_1 -3.311744\n", - "┃ coef_univ_dist_15_up -0.073000\n", - "┃ coef_univ_dist_1_2 -2.878224\n", - "┃ coef_univ_dist_2_5 -0.456009\n", - "┃ coef_univ_dist_5_15 -0.572553\n", + "┃ coef_grade_dist_0_1 -1.886212\n", + "┃ coef_grade_dist_15_up -0.103616\n", + "┃ coef_grade_dist_5_15 -0.285452\n", + "┃ coef_high_dist_0_1 -0.869799\n", + "┃ coef_high_dist_15_up -0.233127\n", + "┃ coef_high_dist_5_15 -0.285690\n", + "┃ coef_high_grade_dist_1_2 -0.931692\n", + "┃ coef_high_grade_dist_2_5 -0.694687\n", + "┃ coef_mode_logsum 0.074994\n", + "┃ coef_univ_dist_0_1 -2.780799\n", + "┃ coef_univ_dist_15_up -0.145257\n", + "┃ coef_univ_dist_1_2 -3.082102\n", + "┃ coef_univ_dist_2_5 -0.668470\n", + "┃ coef_univ_dist_5_15 -0.563338\n", "┃ gradeschool_AGE0519 0.000000\n", "┃ highschool_HSENROLL 0.000000\n", "┃ university_COLLFTE -0.524249\n", - "┃ university_COLLPTE -1.208828\n", + "┃ university_COLLPTE -0.900765\n", "┃ dtype: float64\n", - "┣ tolerance: 7.272237631812952e-06\n", - "┣ steps: array([1., 1., 1., 1., 1., 1.])\n", - "┣ message: 'Optimization terminated successfully.'\n", - "┣ elapsed_time: datetime.timedelta(microseconds=218468)\n", + "┣ tolerance: 4.213233078884777e-06\n", + "┣ steps: array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])\n", + "┣ message: 'Optimization terminated successfully'\n", + "┣ elapsed_time: datetime.timedelta(microseconds=994749)\n", "┣ method: 'BHHH'\n", - "┣ n_cases: 984\n", - "┣ iteration_number: 6\n", - "┣ logloss: 4.124715061821547" + "┣ n_cases: 14989\n", + "┣ iteration_number: 13" ] }, - "execution_count": 11, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -2015,209 +2118,235 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Value Std Err t Stat Signif Null Value Constrained
-999-999. NA NA-999.00fixed value
1 1.00 NA NA 1.00fixed value
coef_grade_dist_0_1-1.82 0.435-4.19*** 0.00
coef_grade_dist_15_up-0.0460 4.66e-15-BIG*** 0.00
coef_grade_dist_5_15-0.145 0.0638-2.27* 0.00
coef_high_dist_0_1-2.11 0.801-2.63** 0.00
coef_high_dist_15_up-0.188 3.34e-15-BIG*** 0.00
coef_high_dist_5_15-0.102 0.143-0.71 0.00
coef_high_grade_dist_1_2-0.752 0.186-4.05*** 0.00
coef_high_grade_dist_2_5-0.667 0.0510-13.09*** 0.00
coef_mode_logsum 0.372 0.0461 8.08*** 0.00
coef_univ_dist_0_1-3.31 0.740-4.47*** 0.00
coef_univ_dist_15_up-0.0730 3.48e-16-BIG*** 0.00
coef_univ_dist_1_2-2.88 0.299-9.64*** 0.00
coef_univ_dist_2_5-0.456 0.0773-5.90*** 0.00
coef_univ_dist_5_15-0.573 0.0938-6.11*** 0.00
gradeschool_AGE0519 0.00 NA NA 0.00fixed value
highschool_HSENROLL 0.00 NA NA 0.00fixed value
university_COLLFTE-0.524 NA NA 0.00fixed value
university_COLLPTE-1.21 0.314-3.85*** 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
-999-999. 0.00 NA 0.00fixed value
1 1.00 0.00 NA 0.00fixed value
coef_grade_dist_0_1-1.89 0.0843-22.37*** 0.00
coef_grade_dist_15_up-0.104 0.00536-19.34*** 0.00
coef_grade_dist_5_15-0.285 0.00724-39.45*** 0.00
coef_high_dist_0_1-0.870 0.302-2.88** 0.00
coef_high_dist_15_up-0.233 0.0225-10.36*** 0.00
coef_high_dist_5_15-0.286 0.0124-23.10*** 0.00
coef_high_grade_dist_1_2-0.932 0.0424-22.00*** 0.00
coef_high_grade_dist_2_5-0.695 0.0138-50.31*** 0.00
coef_mode_logsum 0.0750 0.0118 6.35*** 0.00
coef_univ_dist_0_1-2.78 0.391-7.11*** 0.00
coef_univ_dist_15_up-0.145 0.0105-13.85*** 0.00
coef_univ_dist_1_2-3.08 0.168-18.34*** 0.00
coef_univ_dist_2_5-0.668 0.0383-17.46*** 0.00
coef_univ_dist_5_15-0.563 0.0167-33.63*** 0.00
gradeschool_AGE0519 0.00 0.00 NA 0.00fixed value
highschool_HSENROLL 0.00 0.00 NA 0.00fixed value
university_COLLFTE-0.524 0.00 NA 0.00fixed value
university_COLLPTE-0.901 0.0959-9.39*** 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 12, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -2226,6 +2355,29 @@ "model.parameter_summary()" ] }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
StatisticAggregatePer Case
Number of Cases14989
Log Likelihood at Convergence-30424.70-2.03
Log Likelihood at Null Parameters-71673.19-4.78
Rho Squared w.r.t. Null Parameters0.576
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.estimation_statistics()" + ] + }, { "cell_type": "markdown", "metadata": { @@ -2238,7 +2390,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -2255,7 +2407,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -2274,7 +2426,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -2391,8 +2543,8 @@ " 0.000000\n", " 0.000\n", " 0.000000\n", - " 0.664760\n", - " 0.335240\n", + " 0.593032\n", + " 0.406968\n", " \n", " \n", " 5\n", @@ -2700,7 +2852,7 @@ "1 0.139139 0.008008 0.210210 0.000 0.000000 0.000000 0.000000 \n", "2 0.154000 0.006000 0.239000 0.000 0.000000 0.000000 0.000000 \n", "3 0.146000 0.004000 0.246000 0.000 0.000000 0.000000 0.000000 \n", - "4 0.000000 0.000000 0.000000 0.000 0.000000 0.664760 0.335240 \n", + "4 0.000000 0.000000 0.000000 0.000 0.000000 0.593032 0.406968 \n", "5 0.000000 0.000000 0.000000 1.000 0.000000 0.000000 0.000000 \n", "6 0.000000 0.000000 0.000000 0.000 1.000000 0.000000 0.000000 \n", "7 0.000000 0.000000 0.000000 0.465 0.166000 0.000000 0.000000 \n", @@ -2720,7 +2872,7 @@ "21 0.000000 0.000000 0.000000 0.000 0.000000 0.591409 0.407592 " ] }, - "execution_count": 15, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -2741,7 +2893,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -2765,7 +2917,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -2798,85 +2950,85 @@ " \n", " 0\n", " coef_univ_dist_0_1\n", - " -3.311744\n", + " -2.780799\n", " F\n", " \n", " \n", " 1\n", " coef_univ_dist_1_2\n", - " -2.878224\n", + " -3.082102\n", " F\n", " \n", " \n", " 2\n", " coef_univ_dist_2_5\n", - " -0.456009\n", + " -0.668470\n", " F\n", " \n", " \n", " 3\n", " coef_univ_dist_5_15\n", - " -0.572553\n", + " -0.563338\n", " F\n", " \n", " \n", " 4\n", " coef_univ_dist_15_up\n", - " -0.073000\n", + " -0.145257\n", " F\n", " \n", " \n", " 5\n", " coef_high_dist_0_1\n", - " -2.106211\n", + " -0.869799\n", " F\n", " \n", " \n", " 6\n", " coef_high_grade_dist_1_2\n", - " -0.751852\n", + " -0.931692\n", " F\n", " \n", " \n", " 7\n", " coef_high_grade_dist_2_5\n", - " -0.667119\n", + " -0.694687\n", " F\n", " \n", " \n", " 8\n", " coef_high_dist_5_15\n", - " -0.101747\n", + " -0.285690\n", " F\n", " \n", " \n", " 9\n", " coef_high_dist_15_up\n", - " -0.188200\n", + " -0.233127\n", " F\n", " \n", " \n", " 10\n", " coef_grade_dist_0_1\n", - " -1.824840\n", + " -1.886212\n", " F\n", " \n", " \n", " 11\n", " coef_grade_dist_5_15\n", - " -0.144663\n", + " -0.285452\n", " F\n", " \n", " \n", " 12\n", " coef_grade_dist_15_up\n", - " -0.046000\n", + " -0.103616\n", " F\n", " \n", " \n", " 13\n", " coef_mode_logsum\n", - " 0.372245\n", + " 0.074994\n", " F\n", " \n", " \n", @@ -2885,23 +3037,23 @@ ], "text/plain": [ " coefficient_name value constrain\n", - "0 coef_univ_dist_0_1 -3.311744 F\n", - "1 coef_univ_dist_1_2 -2.878224 F\n", - "2 coef_univ_dist_2_5 -0.456009 F\n", - "3 coef_univ_dist_5_15 -0.572553 F\n", - "4 coef_univ_dist_15_up -0.073000 F\n", - "5 coef_high_dist_0_1 -2.106211 F\n", - "6 coef_high_grade_dist_1_2 -0.751852 F\n", - "7 coef_high_grade_dist_2_5 -0.667119 F\n", - "8 coef_high_dist_5_15 -0.101747 F\n", - "9 coef_high_dist_15_up -0.188200 F\n", - "10 coef_grade_dist_0_1 -1.824840 F\n", - "11 coef_grade_dist_5_15 -0.144663 F\n", - "12 coef_grade_dist_15_up -0.046000 F\n", - "13 coef_mode_logsum 0.372245 F" + "0 coef_univ_dist_0_1 -2.780799 F\n", + "1 coef_univ_dist_1_2 -3.082102 F\n", + "2 coef_univ_dist_2_5 -0.668470 F\n", + "3 coef_univ_dist_5_15 -0.563338 F\n", + "4 coef_univ_dist_15_up -0.145257 F\n", + "5 coef_high_dist_0_1 -0.869799 F\n", + "6 coef_high_grade_dist_1_2 -0.931692 F\n", + "7 coef_high_grade_dist_2_5 -0.694687 F\n", + "8 coef_high_dist_5_15 -0.285690 F\n", + "9 coef_high_dist_15_up -0.233127 F\n", + "10 coef_grade_dist_0_1 -1.886212 F\n", + "11 coef_grade_dist_5_15 -0.285452 F\n", + "12 coef_grade_dist_15_up -0.103616 F\n", + "13 coef_mode_logsum 0.074994 F" ] }, - "execution_count": 17, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -2912,7 +3064,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -3035,8 +3187,8 @@ " 0.000000\n", " 0.000\n", " 0.000000\n", - " 0.664760\n", - " 0.335240\n", + " 0.593032\n", + " 0.406968\n", " \n", " \n", " 5\n", @@ -3361,7 +3513,7 @@ "1 0.325325 0.139139 0.008008 0.210210 0.000 0.000000 0.000000 \n", "2 0.284000 0.154000 0.006000 0.239000 0.000 0.000000 0.000000 \n", "3 0.241000 0.146000 0.004000 0.246000 0.000 0.000000 0.000000 \n", - "4 0.000000 0.000000 0.000000 0.000000 0.000 0.000000 0.664760 \n", + "4 0.000000 0.000000 0.000000 0.000000 0.000 0.000000 0.593032 \n", "5 0.000000 0.000000 0.000000 0.000000 1.000 0.000000 0.000000 \n", "6 0.000000 0.000000 0.000000 0.000000 0.000 1.000000 0.000000 \n", "7 0.144000 0.000000 0.000000 0.000000 0.465 0.166000 0.000000 \n", @@ -3385,7 +3537,7 @@ "1 0.000000 \n", "2 0.000000 \n", "3 0.000000 \n", - "4 0.335240 \n", + "4 0.406968 \n", "5 0.000000 \n", "6 0.000000 \n", "7 0.000000 \n", @@ -3405,7 +3557,7 @@ "21 0.407592 " ] }, - "execution_count": 18, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -3422,7 +3574,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -3436,7 +3588,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/03_work_location.ipynb b/activitysim/examples/example_estimation/notebooks/03_work_location.ipynb index 2a9479023c..4fc0fbc480 100644 --- a/activitysim/examples/example_estimation/notebooks/03_work_location.ipynb +++ b/activitysim/examples/example_estimation/notebooks/03_work_location.ipynb @@ -25,38 +25,88 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, - "outputs": [], + "metadata": { + "jupyter": { + "is_executing": true + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.33',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import larch # !conda install larch #for estimation\n", + "import larch as lx # !conda install larch #for estimation\n", "import pandas as pd\n", - "import numpy as np\n", - "import yaml \n", - "import larch.util.excel\n", - "import os" + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare, backup\n", + "\n", + "prepare()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "# Load data and prep model for estimation" + "In this demo notebook, we will (later) edit the model spec file. But for demo purposes, we want to\n", + "make sure we are starting from the \"original\" spec file, so we'll check that now. For actual \n", + "applications, this step would not be necessary." ] }, { @@ -65,7 +115,14 @@ "metadata": {}, "outputs": [], "source": [ - "modelname=\"workplace_location\"" + "backup(\"output-est-mode/estimation_data_bundle/workplace_location/workplace_location_SPEC.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load data and prep model for estimation" ] }, { @@ -73,9 +130,36 @@ "execution_count": 4, "metadata": {}, "outputs": [], + "source": [ + "modelname = \"workplace_location\"" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_landuse.csv\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_size_terms.csv\n" + ] + } + ], "source": [ "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -96,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -187,7 +271,7 @@ "coef_mode_logsum 0.3000 F" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -205,7 +289,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -230,148 +314,142 @@ " \n", " \n", " person_id\n", - " variable\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", - " 8\n", - " ...\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", - " 190\n", + " alt_dest\n", + " prob\n", + " pick_count\n", + " mode_choice_logsum\n", + " size_term\n", + " shadow_price_size_term_adjustment\n", + " shadow_price_utility_adjustment\n", + " util_dist_0_1\n", + " util_dist_1_2\n", + " util_dist_2_5\n", + " util_dist_5_15\n", + " util_dist_15_up\n", + " util_dist_0_5_high\n", + " util_dist_15_up_high\n", + " util_size_variable\n", + " util_utility_adjustment\n", + " util_no_attractions\n", + " util_mode_logsum\n", + " util_sample_of_corrections_factor\n", " \n", " \n", " \n", " \n", " 0\n", - " 72241\n", - " mode_choice_logsum\n", - " -0.6000073826104492\n", - " -0.4656491845430101\n", - " -0.41794791684660004\n", - " -0.4545880924383482\n", - " -0.3870339464573669\n", - " -0.713189384898449\n", - " -0.6002723120707204\n", - " -0.7303789868909905\n", - " ...\n", - " -1.2551998198820722\n", - " -1.444611856370077\n", - " -1.309689434695158\n", - " -1.2118895631639268\n", - " -1.116133290115392\n", - " -1.1401586021041086\n", - " -1.268242046936546\n", - " -1.1992258811031282\n", - " -1.332212687016352\n", - " -1.4322381548918224\n", + " 72355\n", + " 2\n", + " 0.033018\n", + " 4\n", + " -1.930058\n", + " 8679.220\n", + " 1\n", + " 0\n", + " 1.0\n", + " 1.0\n", + " 3.0\n", + " 1.01\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", + " 9.068802\n", + " 0\n", + " False\n", + " -1.930058\n", + " 4.796986\n", " \n", " \n", " 1\n", - " 72241\n", - " pick_count\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " ...\n", - " 1.0\n", - " 1.0\n", - 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46476 rows × 192 columns

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766224 rows × 20 columns

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2582 rows × 5 columns

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28281 rows × 5 columns

\n", "" ], "text/plain": [ - " person_id model_choice override_choice income_segment home_zone_id\n", - "0 72241 13 9 1 17\n", - "1 72441 100 100 1 60\n", - "2 72528 139 126 1 69\n", - "3 73144 77 77 1 125\n", - "4 73493 117 117 1 133\n", - "... ... ... ... ... ...\n", - "2577 7514214 80 71 1 56\n", - "2578 7514284 187 186 1 72\n", - "2579 7514404 105 106 1 81\n", - "2580 7514777 87 87 1 106\n", - "2581 7515185 16 16 1 142\n", + " person_id model_choice override_choice income_segment home_zone_id\n", + "0 72355 14 17 1 55\n", + "1 72384 1 16 1 59\n", + "2 72407 70 70 1 59\n", + "3 72459 193 30 1 61\n", + "4 72529 16 57 1 69\n", + "... ... ... ... ... ...\n", + "28276 7539071 1006 1019 1 1006\n", + "28277 7539203 1059 1152 1 1159\n", + "28278 7539217 940 991 1 1159\n", + "28279 7539270 1162 1145 1 1161\n", + "28280 7539317 1390 1381 1 1390\n", "\n", - "[2582 rows x 5 columns]" + "[28281 rows x 5 columns]" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -795,7 +867,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -881,9 +953,9 @@ " 7\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 3\n", " 5.89564\n", " 2.875000\n", @@ -905,9 +977,9 @@ " 19\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.84871\n", " 5.195214\n", @@ -929,9 +1001,9 @@ " 38\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.53231\n", " 80.470405\n", @@ -953,9 +1025,9 @@ " 20\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 2\n", " 5.64330\n", " 7.947368\n", @@ -977,9 +1049,9 @@ " 86\n", " ...\n", " 0\n", - " 0.00000\n", + " 0.0\n", " 72.14684\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.52555\n", " 38.187500\n", @@ -1012,191 +1084,191 @@ " ...\n", " \n", " \n", - " 186\n", - " 4\n", - " 4\n", - " 1\n", - " 2779\n", - " 8062\n", - " 376.0\n", - " 172.0\n", - " 15.00000\n", - " 1760\n", - " 1178\n", + " 1450\n", + " 34\n", + " 34\n", + " 9\n", + " 2724\n", + " 6493\n", + " 1320.0\n", + " 630.0\n", + " 69.00000\n", + " 1046\n", + " 1013\n", " ...\n", - " 3\n", - " 0.00000\n", - " 0.00000\n", + " 4\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - " 2.04173\n", - " 14.860963\n", - " 9.411765\n", - " 5.762347\n", + " 1.12116\n", + " 3.896996\n", + " 1.496423\n", + " 1.081235\n", " False\n", " \n", " \n", - " 187\n", - " 4\n", - " 4\n", - " 1\n", - " 1492\n", - " 4139\n", - " 214.0\n", - " 116.0\n", - " 10.00000\n", - " 808\n", - " 603\n", + " 1451\n", + " 34\n", + " 34\n", + " 9\n", + " 2016\n", + " 4835\n", + " 664.0\n", + " 379.0\n", + " 43.00000\n", + " 757\n", + " 757\n", " ...\n", - " 3\n", - " 0.00000\n", - " 0.00000\n", + " 4\n", + " 0.0\n", " 0.00000\n", - " 2\n", - " 1.73676\n", - " 11.841270\n", - " 6.412698\n", - " 4.159890\n", + " 0.0\n", + " 1\n", + " 1.17116\n", + " 4.777251\n", + " 1.793839\n", + " 1.304140\n", " False\n", " \n", " \n", - " 188\n", - " 4\n", - " 4\n", - " 1\n", - " 753\n", - " 4072\n", - " 232.0\n", - " 11.0\n", - " 178.00000\n", - " 4502\n", - " 1117\n", + " 1452\n", + " 34\n", + " 34\n", + " 9\n", + " 2178\n", + " 5055\n", + " 1068.0\n", + " 602.0\n", + " 35.00000\n", + " 2110\n", + " 789\n", " ...\n", - " 2\n", - " 3961.04761\n", - " 17397.79102\n", - " 11152.93652\n", + " 4\n", + " 0.0\n", + " 0.00000\n", + " 0.0\n", " 1\n", - " 2.28992\n", - " 3.984127\n", - " 23.820106\n", - " 3.413233\n", + " 1.17587\n", + " 3.419152\n", + " 3.312402\n", + " 1.682465\n", " False\n", " \n", " \n", - " 189\n", - " 4\n", - " 4\n", - " 1\n", - " 3546\n", - " 8476\n", - " 201.0\n", - " 72.0\n", - " 6.00000\n", - " 226\n", - " 1057\n", + " 1453\n", + " 34\n", + " 34\n", + " 9\n", + " 298\n", + " 779\n", + " 14195.0\n", + " 429.0\n", + " 4.00000\n", + " 922\n", + " 88\n", " ...\n", - " 2\n", - " 0.00000\n", - " 0.00000\n", + " 5\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - " 2.88773\n", - " 45.461538\n", - " 2.897436\n", - " 2.723836\n", + " 1.01972\n", + " 0.688222\n", + " 2.129330\n", + " 0.520115\n", " False\n", " \n", " \n", - " 190\n", - " 4\n", - " 4\n", - " 1\n", - " 968\n", - " 1647\n", - " 1381.0\n", - " 14.0\n", - " 28.00000\n", - " 1010\n", - " 114\n", + " 1454\n", + " 34\n", + " 34\n", + " 9\n", + " 1068\n", + " 2337\n", + " 10469.0\n", + " 1114.0\n", + " 27.00000\n", + " 607\n", + " 418\n", " ...\n", - " 3\n", - " 0.00000\n", - " 0.00000\n", + " 5\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - " 2.60309\n", - " 23.047619\n", - " 24.047619\n", - " 11.768501\n", + " 0.95542\n", + " 0.936021\n", + " 0.531989\n", + " 0.339203\n", " False\n", " \n", " \n", "\n", - "

190 rows × 28 columns

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1454 rows × 28 columns

\n", "" ], "text/plain": [ - " DISTRICT SD county_id TOTHH TOTPOP TOTACRE RESACRE CIACRE \\\n", - "zone_id \n", - "1 1 1 1 46 82 20.3 1.0 15.00000 \n", - "2 1 1 1 134 240 31.1 1.0 24.79297 \n", - "3 1 1 1 267 476 14.7 1.0 2.31799 \n", - "4 1 1 1 151 253 19.3 1.0 18.00000 \n", - "5 1 1 1 611 1069 52.7 1.0 15.00000 \n", - "... ... .. ... ... ... ... ... ... \n", - "186 4 4 1 2779 8062 376.0 172.0 15.00000 \n", - "187 4 4 1 1492 4139 214.0 116.0 10.00000 \n", - "188 4 4 1 753 4072 232.0 11.0 178.00000 \n", - "189 4 4 1 3546 8476 201.0 72.0 6.00000 \n", - "190 4 4 1 968 1647 1381.0 14.0 28.00000 \n", + " DISTRICT SD county_id TOTHH TOTPOP TOTACRE RESACRE CIACRE \\\n", + "zone_id \n", + "1 1 1 1 46 82 20.3 1.0 15.00000 \n", + "2 1 1 1 134 240 31.1 1.0 24.79297 \n", + "3 1 1 1 267 476 14.7 1.0 2.31799 \n", + "4 1 1 1 151 253 19.3 1.0 18.00000 \n", + "5 1 1 1 611 1069 52.7 1.0 15.00000 \n", + "... ... .. ... ... ... ... ... ... \n", + "1450 34 34 9 2724 6493 1320.0 630.0 69.00000 \n", + "1451 34 34 9 2016 4835 664.0 379.0 43.00000 \n", + "1452 34 34 9 2178 5055 1068.0 602.0 35.00000 \n", + "1453 34 34 9 298 779 14195.0 429.0 4.00000 \n", + "1454 34 34 9 1068 2337 10469.0 1114.0 27.00000 \n", "\n", - " TOTEMP AGE0519 ... area_type HSENROLL COLLFTE \\\n", - "zone_id ... \n", - "1 27318 7 ... 0 0.00000 0.00000 \n", - "2 42078 19 ... 0 0.00000 0.00000 \n", - "3 2445 38 ... 0 0.00000 0.00000 \n", - "4 22434 20 ... 0 0.00000 0.00000 \n", - "5 15662 86 ... 0 0.00000 72.14684 \n", - "... ... ... ... ... ... ... \n", - "186 1760 1178 ... 3 0.00000 0.00000 \n", - "187 808 603 ... 3 0.00000 0.00000 \n", - "188 4502 1117 ... 2 3961.04761 17397.79102 \n", - "189 226 1057 ... 2 0.00000 0.00000 \n", - "190 1010 114 ... 3 0.00000 0.00000 \n", + " TOTEMP AGE0519 ... area_type HSENROLL COLLFTE COLLPTE \\\n", + "zone_id ... \n", + "1 27318 7 ... 0 0.0 0.00000 0.0 \n", + "2 42078 19 ... 0 0.0 0.00000 0.0 \n", + "3 2445 38 ... 0 0.0 0.00000 0.0 \n", + "4 22434 20 ... 0 0.0 0.00000 0.0 \n", + "5 15662 86 ... 0 0.0 72.14684 0.0 \n", + "... ... ... ... ... ... ... ... \n", + "1450 1046 1013 ... 4 0.0 0.00000 0.0 \n", + "1451 757 757 ... 4 0.0 0.00000 0.0 \n", + "1452 2110 789 ... 4 0.0 0.00000 0.0 \n", + "1453 922 88 ... 5 0.0 0.00000 0.0 \n", + "1454 607 418 ... 5 0.0 0.00000 0.0 \n", "\n", - " COLLPTE TOPOLOGY TERMINAL household_density \\\n", - "zone_id \n", - "1 0.00000 3 5.89564 2.875000 \n", - "2 0.00000 1 5.84871 5.195214 \n", - "3 0.00000 1 5.53231 80.470405 \n", - "4 0.00000 2 5.64330 7.947368 \n", - "5 0.00000 1 5.52555 38.187500 \n", - "... ... ... ... ... \n", - "186 0.00000 1 2.04173 14.860963 \n", - "187 0.00000 2 1.73676 11.841270 \n", - "188 11152.93652 1 2.28992 3.984127 \n", - "189 0.00000 1 2.88773 45.461538 \n", - "190 0.00000 1 2.60309 23.047619 \n", + " TOPOLOGY TERMINAL household_density employment_density \\\n", + "zone_id \n", + "1 3 5.89564 2.875000 1707.375000 \n", + "2 1 5.84871 5.195214 1631.374751 \n", + "3 1 5.53231 80.470405 736.891913 \n", + "4 2 5.64330 7.947368 1180.736842 \n", + "5 1 5.52555 38.187500 978.875000 \n", + "... ... ... ... ... \n", + "1450 1 1.12116 3.896996 1.496423 \n", + "1451 1 1.17116 4.777251 1.793839 \n", + "1452 1 1.17587 3.419152 3.312402 \n", + "1453 1 1.01972 0.688222 2.129330 \n", + "1454 1 0.95542 0.936021 0.531989 \n", "\n", - " employment_density density_index is_cbd \n", - "zone_id \n", - "1 1707.375000 2.870167 False \n", - "2 1631.374751 5.178722 False \n", - "3 736.891913 72.547987 False \n", - "4 1180.736842 7.894233 False \n", - "5 978.875000 36.753679 False \n", - "... ... ... ... \n", - "186 9.411765 5.762347 False \n", - "187 6.412698 4.159890 False \n", - "188 23.820106 3.413233 False \n", - "189 2.897436 2.723836 False \n", - "190 24.047619 11.768501 False \n", + " density_index is_cbd \n", + "zone_id \n", + "1 2.870167 False \n", + "2 5.178722 False \n", + "3 72.547987 False \n", + "4 7.894233 False \n", + "5 36.753679 False \n", + "... ... ... \n", + "1450 1.081235 False \n", + "1451 1.304140 False \n", + "1452 1.682465 False \n", + "1453 0.520115 False \n", + "1454 0.339203 False \n", "\n", - "[190 rows x 28 columns]" + "[1454 rows x 28 columns]" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -1214,7 +1286,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -1357,7 +1429,7 @@ "9 @np.minimum(np.log(df.pick_count/df.prob), 60) 1 " ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -1375,7 +1447,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -1466,7 +1538,7 @@ "work_veryhigh 0.093 0.270 0.241 0.146 0.004 0.246" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -1486,20 +1558,13 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

Iteration 475 [Optimization terminated successfully.]

" + "

Iteration 009 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1511,7 +1576,7 @@ { "data": { "text/html": [ - "

Best LL = -13521.35475538419

" + "

Best LL = -88683.85038605405

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"work_veryhigh_RETEMPN -2.375156 -2.375156 0.0 -6.0 6.0 \n", + " value best initvalue minimum \\\n", + "param_name \n", + "-999 -9.990000e+02 -9.990000e+02 -999.000000 -999.000000 \n", + "1 1.000000e+00 1.000000e+00 1.000000 1.000000 \n", + "coef_dist_0_1 -1.035381e+00 -1.035381e+00 -0.842800 -25.000000 \n", + "coef_dist_0_5_high 1.469662e-01 1.469662e-01 0.150000 -25.000000 \n", + "coef_dist_15_up -1.170512e-01 -1.170512e-01 -0.091700 -25.000000 \n", + "coef_dist_1_2 -4.652491e-01 -4.652491e-01 -0.310400 -25.000000 \n", + "coef_dist_2_5 -4.177477e-01 -4.177477e-01 -0.378300 -25.000000 \n", + "coef_dist_5_15 -1.558734e-01 -1.558734e-01 -0.128500 -25.000000 \n", + "coef_dist_5_up_high 2.506728e-02 2.506728e-02 0.020000 -25.000000 \n", + "coef_mode_logsum 7.423654e-02 7.423654e-02 0.300000 -25.000000 \n", + "work_high_AGREMPN -1.856268e+00 -1.856268e+00 -5.115996 -6.000000 \n", + "work_high_FPSEMPN -1.895722e+00 -1.895722e+00 -1.575037 -6.000000 \n", + "work_high_HEREMPN -1.698263e+00 -1.698263e+00 -1.258781 -6.000000 \n", + "work_high_MWTEMPN -1.815687e+00 -1.815687e+00 -1.431292 -6.000000 \n", + "work_high_OTHEMPN -2.187482e+00 -2.187482e+00 -1.870803 -6.000000 \n", + "work_high_RETEMPN -2.207275e+00 -2.207275e+00 -2.207275 -2.207275 \n", + "work_low_AGREMPN -7.178467e+01 -7.178467e+01 -4.605170 -6.000000 \n", + "work_low_FPSEMPN -1.507959e+00 -1.507959e+00 -1.645065 -6.000000 \n", + "work_low_HEREMPN -8.190703e-01 -8.190703e-01 -0.959720 -6.000000 \n", + "work_low_MWTEMPN -1.980587e+00 -1.980587e+00 -1.807889 -6.000000 \n", + "work_low_OTHEMPN -2.021455e+00 -2.021455e+00 -2.120264 -6.000000 \n", + "work_low_RETEMPN -2.047943e+00 -2.047943e+00 -2.047943 -2.047943 \n", + "work_med_AGREMPN -8.087999e+64 -8.087999e+64 -4.828314 -6.000000 \n", + "work_med_FPSEMPN -2.151306e+00 -2.151306e+00 -1.624552 -6.000000 \n", + "work_med_HEREMPN -1.606036e+00 -1.606036e+00 -1.123930 -6.000000 \n", + "work_med_MWTEMPN -2.043992e+00 -2.043992e+00 -1.560648 -6.000000 \n", + "work_med_OTHEMPN -2.172089e+00 -2.172089e+00 -1.973281 -6.000000 \n", + "work_med_RETEMPN -2.120264e+00 -2.120264e+00 -2.120264 -2.120264 \n", + "work_veryhigh_AGREMPN -6.042012e+00 -6.042012e+00 -5.521461 -6.000000 \n", + "work_veryhigh_FPSEMPN -1.838134e+00 -1.838134e+00 -1.309333 -6.000000 \n", + "work_veryhigh_HEREMPN -1.992130e+00 -1.992130e+00 -1.422958 -6.000000 \n", + "work_veryhigh_MWTEMPN -1.763131e+00 -1.763131e+00 -1.402424 -6.000000 \n", + "work_veryhigh_OTHEMPN -2.509024e+00 -2.509024e+00 -1.924149 -6.000000 \n", + "work_veryhigh_RETEMPN -2.375156e+00 -2.375156e+00 -2.375156 -2.375156 \n", "\n", - " holdfast note best \n", - "-999 1 -999.000000 \n", - "1 1 1.000000 \n", - "coef_dist_0_1 0 -1.084778 \n", - "coef_dist_0_5_high 0 0.120981 \n", - "coef_dist_15_up 0 -0.091700 \n", - "coef_dist_1_2 0 -0.252580 \n", - "coef_dist_2_5 0 -0.369689 \n", - "coef_dist_5_15 0 -0.152259 \n", - "coef_dist_5_up_high 0 -0.015225 \n", - "coef_mode_logsum 0 0.155426 \n", - "work_high_AGREMPN 0 -14.042031 \n", - "work_high_FPSEMPN 0 -2.021234 \n", - "work_high_HEREMPN 0 -1.578781 \n", - "work_high_MWTEMPN 0 -2.074250 \n", - "work_high_OTHEMPN 0 -2.145558 \n", - "work_high_RETEMPN 1 -2.207275 \n", - "work_low_AGREMPN 0 -40.734929 \n", - "work_low_FPSEMPN 0 -0.670108 \n", - "work_low_HEREMPN 0 0.087905 \n", - "work_low_MWTEMPN 0 -0.373028 \n", - "work_low_OTHEMPN 0 -0.705270 \n", - "work_low_RETEMPN 1 -2.047943 \n", - "work_med_AGREMPN 0 -14.886841 \n", - "work_med_FPSEMPN 0 -1.942050 \n", - "work_med_HEREMPN 0 -1.382809 \n", - "work_med_MWTEMPN 0 -0.910436 \n", - "work_med_OTHEMPN 0 -2.535326 \n", - "work_med_RETEMPN 1 -2.120264 \n", - "work_veryhigh_AGREMPN 0 -0.277725 \n", - "work_veryhigh_FPSEMPN 0 -1.757306 \n", - "work_veryhigh_HEREMPN 0 -1.621894 \n", - "work_veryhigh_MWTEMPN 0 -1.722069 \n", - "work_veryhigh_OTHEMPN 0 -2.483268 \n", - "work_veryhigh_RETEMPN 1 -2.375156 " + " maximum nullvalue holdfast \n", + "param_name \n", + "-999 -999.000000 0.0 1 \n", + "1 1.000000 0.0 1 \n", + "coef_dist_0_1 25.000000 0.0 0 \n", + "coef_dist_0_5_high 25.000000 0.0 0 \n", + "coef_dist_15_up 25.000000 0.0 0 \n", + "coef_dist_1_2 25.000000 0.0 0 \n", + "coef_dist_2_5 25.000000 0.0 0 \n", + "coef_dist_5_15 25.000000 0.0 0 \n", + "coef_dist_5_up_high 25.000000 0.0 0 \n", + "coef_mode_logsum 25.000000 0.0 0 \n", + "work_high_AGREMPN 6.000000 0.0 0 \n", + "work_high_FPSEMPN 6.000000 0.0 0 \n", + "work_high_HEREMPN 6.000000 0.0 0 \n", + "work_high_MWTEMPN 6.000000 0.0 0 \n", + "work_high_OTHEMPN 6.000000 0.0 0 \n", + "work_high_RETEMPN -2.207275 0.0 1 \n", + "work_low_AGREMPN 6.000000 0.0 0 \n", + "work_low_FPSEMPN 6.000000 0.0 0 \n", + "work_low_HEREMPN 6.000000 0.0 0 \n", + "work_low_MWTEMPN 6.000000 0.0 0 \n", + "work_low_OTHEMPN 6.000000 0.0 0 \n", + "work_low_RETEMPN -2.047943 0.0 1 \n", + "work_med_AGREMPN 6.000000 0.0 0 \n", + "work_med_FPSEMPN 6.000000 0.0 0 \n", + "work_med_HEREMPN 6.000000 0.0 0 \n", + "work_med_MWTEMPN 6.000000 0.0 0 \n", + "work_med_OTHEMPN 6.000000 0.0 0 \n", + "work_med_RETEMPN -2.120264 0.0 1 \n", + "work_veryhigh_AGREMPN 6.000000 0.0 0 \n", + "work_veryhigh_FPSEMPN 6.000000 0.0 0 \n", + "work_veryhigh_HEREMPN 6.000000 0.0 0 \n", + "work_veryhigh_MWTEMPN 6.000000 0.0 0 \n", + "work_veryhigh_OTHEMPN 6.000000 0.0 0 \n", + "work_veryhigh_RETEMPN -2.375156 0.0 1 " ] }, "metadata": {}, @@ -2011,1040 +2053,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 6.58075738982826e-14 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 8.609108514589023e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 4.858994087802833e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 4.590724503258719e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.764703716398322e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 7.95965356556717e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.818442093095742e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 5.03392554043634e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.5381467152499962e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - 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" warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.1462882066859337e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.2236450588660233e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 8.957773169475355e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.403629593864148e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - 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" warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.8356027731239294e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.1421351948148873e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.2122137179899207e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.361811071723201e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 7.424246392034423e-17 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 9.833431869070201e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.3560892176329117e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.3002356046314505e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 8.14760641170999e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.5893755977713855e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.2242791423085704e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 7.840228498303649e-17 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.821310614405388e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - 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" warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.874082949306298e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 7.371793040685402e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.938572491694241e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.246124180526511e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.141265756002516e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.100401477984635e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.5378782864186965e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.9313922953760897e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.1977191783387483e-15 in general_inverse\n", - 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"/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.4275891045055421e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.4393823211036024e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 4.186384064873585e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 4.824617816113209e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.85880587925525e-15 in general_inverse\n", - 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"/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.4897864931953783e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.0509512337158769e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.1377543116819802e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.800744497149333e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.761798985494412e-15 in general_inverse\n", - 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" warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.8734374809662115e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.232343583659919e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.0482842256784803e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.467379347282302e-18 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.5759888124606325e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.225617744485029e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 7.703772751192879e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 6.883109514984853e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.455312980236373e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 6.23895606701099e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.0603077714105237e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate(method='BHHH', options={'maxiter':1000})\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 8.886410808092305e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { "data": { "text/html": [ - 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work_veryhigh_OTHEMPN-2.483268-2.509024e+00
work_veryhigh_RETEMPN-2.375156-2.375156e+00
tolerance9.957944723905177e-06
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message'Optimization terminated successfully.'
elapsed_time0:00:22.109298
method'BHHH'
n_cases2582
iteration_number475
logloss5.2367756604896165
" + "
tolerance8.618081038971004e-07stepsarray([0.125, 0.25 , 0.375, 0.5 , 0.625, 0.75 , 1. , 1. , 1. ])message'Optimization terminated successfully'elapsed_time0:00:02.528580method'BHHH'n_cases28281iteration_number9
" ], "text/plain": [ - "┣ loglike: -13521.35475538419\n", - "┣ x: -999 -999.000000\n", - "┃ 1 1.000000\n", - "┃ coef_dist_0_1 -1.084778\n", - "┃ coef_dist_0_5_high 0.120981\n", - "┃ coef_dist_15_up -0.091700\n", - "┃ coef_dist_1_2 -0.252580\n", - "┃ coef_dist_2_5 -0.369689\n", - "┃ coef_dist_5_15 -0.152259\n", - "┃ coef_dist_5_up_high -0.015225\n", - "┃ coef_mode_logsum 0.155426\n", - "┃ work_high_AGREMPN -14.042031\n", - "┃ work_high_FPSEMPN -2.021234\n", - "┃ work_high_HEREMPN -1.578781\n", - "┃ work_high_MWTEMPN -2.074250\n", - "┃ work_high_OTHEMPN -2.145558\n", - "┃ work_high_RETEMPN -2.207275\n", - "┃ work_low_AGREMPN -40.734929\n", - "┃ work_low_FPSEMPN -0.670108\n", - "┃ work_low_HEREMPN 0.087905\n", - "┃ work_low_MWTEMPN -0.373028\n", - "┃ work_low_OTHEMPN -0.705270\n", - "┃ work_low_RETEMPN -2.047943\n", - "┃ work_med_AGREMPN -14.886841\n", - "┃ work_med_FPSEMPN -1.942050\n", - "┃ work_med_HEREMPN -1.382809\n", - "┃ work_med_MWTEMPN -0.910436\n", - "┃ work_med_OTHEMPN -2.535326\n", - "┃ work_med_RETEMPN -2.120264\n", - "┃ work_veryhigh_AGREMPN -0.277725\n", - "┃ work_veryhigh_FPSEMPN -1.757306\n", - "┃ work_veryhigh_HEREMPN -1.621894\n", - "┃ work_veryhigh_MWTEMPN -1.722069\n", - "┃ work_veryhigh_OTHEMPN -2.483268\n", - "┃ work_veryhigh_RETEMPN -2.375156\n", + "┣ loglike: -88683.85038605405\n", + "┣ x: -999 -9.990000e+02\n", + "┃ 1 1.000000e+00\n", + "┃ coef_dist_0_1 -1.035381e+00\n", + "┃ coef_dist_0_5_high 1.469662e-01\n", + "┃ coef_dist_15_up -1.170512e-01\n", + "┃ coef_dist_1_2 -4.652491e-01\n", + "┃ coef_dist_2_5 -4.177477e-01\n", + "┃ coef_dist_5_15 -1.558734e-01\n", + "┃ coef_dist_5_up_high 2.506728e-02\n", + "┃ coef_mode_logsum 7.423654e-02\n", + "┃ work_high_AGREMPN -1.856268e+00\n", + "┃ work_high_FPSEMPN -1.895722e+00\n", + "┃ work_high_HEREMPN -1.698263e+00\n", + "┃ work_high_MWTEMPN -1.815687e+00\n", + "┃ work_high_OTHEMPN -2.187482e+00\n", + "┃ work_high_RETEMPN -2.207275e+00\n", + "┃ work_low_AGREMPN -7.178467e+01\n", + "┃ work_low_FPSEMPN -1.507959e+00\n", + "┃ work_low_HEREMPN -8.190703e-01\n", + "┃ work_low_MWTEMPN -1.980587e+00\n", + "┃ work_low_OTHEMPN -2.021455e+00\n", + "┃ work_low_RETEMPN -2.047943e+00\n", + "┃ work_med_AGREMPN -8.087999e+64\n", + "┃ work_med_FPSEMPN -2.151306e+00\n", + "┃ work_med_HEREMPN -1.606036e+00\n", + "┃ work_med_MWTEMPN -2.043992e+00\n", + "┃ work_med_OTHEMPN -2.172089e+00\n", + "┃ work_med_RETEMPN -2.120264e+00\n", + "┃ work_veryhigh_AGREMPN -6.042012e+00\n", + "┃ work_veryhigh_FPSEMPN -1.838134e+00\n", + "┃ work_veryhigh_HEREMPN -1.992130e+00\n", + "┃ work_veryhigh_MWTEMPN -1.763131e+00\n", + "┃ work_veryhigh_OTHEMPN -2.509024e+00\n", + "┃ work_veryhigh_RETEMPN -2.375156e+00\n", "┃ dtype: float64\n", - "┣ tolerance: 9.957944723905177e-06\n", - "┣ steps: array([0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625, 0.015625, 0.015625, 0.015625, 0.015625, 0.015625,\n", - "┃ 0.015625])\n", - "┣ message: 'Optimization terminated successfully.'\n", - "┣ elapsed_time: datetime.timedelta(seconds=22, microseconds=109298)\n", + "┣ tolerance: 8.618081038971004e-07\n", + "┣ steps: array([0.125, 0.25 , 0.375, 0.5 , 0.625, 0.75 , 1. , 1. , 1. ])\n", + "┣ message: 'Optimization terminated successfully'\n", + "┣ elapsed_time: datetime.timedelta(seconds=2, microseconds=528580)\n", "┣ method: 'BHHH'\n", - "┣ n_cases: 2582\n", - "┣ iteration_number: 475\n", - "┣ logloss: 5.2367756604896165" + "┣ n_cases: 28281\n", + "┣ iteration_number: 9" ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.estimate(method='BHHH', options={'maxiter':1000})" + "model.estimate(method=\"BHHH\", options={\"maxiter\": 1000})" ] }, { @@ -3414,335 +2271,361 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Null Value Constrained
-999-999. NA NA-999.00fixed value
1 1.00 NA NA 1.00fixed value
coef_dist_0_1-1.08 0.270-4.02*** 0.00
coef_dist_0_5_high 0.121 0.0339 3.57*** 0.00
coef_dist_15_up-0.0917 0.000603-152.16*** 0.00
coef_dist_1_2-0.253 0.115-2.20* 0.00
coef_dist_2_5-0.370 0.0329-11.23*** 0.00
coef_dist_5_15-0.152 0.0419-3.63*** 0.00
coef_dist_5_up_high-0.0152 0.0576-0.26 0.00
coef_mode_logsum 0.155 0.0455 3.41*** 0.00
work_high_AGREMPN-14.0 9.45e+03-0.00 0.00
work_high_FPSEMPN-2.02 0.419-4.83*** 0.00
work_high_HEREMPN-1.58 0.398-3.97*** 0.00
work_high_MWTEMPN-2.07 1.07-1.94 0.00
work_high_OTHEMPN-2.15 0.463-4.64*** 0.00
work_high_RETEMPN-2.21 NA NA 0.00fixed value
work_low_AGREMPN-40.7 3.95e-06-BIG*** 0.00
work_low_FPSEMPN-0.670 1.46-0.46 0.00
work_low_HEREMPN 0.0879 1.47 0.06 0.00
work_low_MWTEMPN-0.373 1.66-0.22 0.00
work_low_OTHEMPN-0.705 1.49-0.47 0.00
work_low_RETEMPN-2.05 NA NA 0.00fixed value
work_med_AGREMPN-14.9 2.37e+03-0.01 0.00
work_med_FPSEMPN-1.94 0.484-4.01*** 0.00
work_med_HEREMPN-1.38 0.448-3.09** 0.00
work_med_MWTEMPN-0.910 0.564-1.61 0.00
work_med_OTHEMPN-2.54 0.640-3.96*** 0.00
work_med_RETEMPN-2.12 NA NA 0.00fixed value
work_veryhigh_AGREMPN-0.278 2.35-0.12 0.00
work_veryhigh_FPSEMPN-1.76 0.410-4.29*** 0.00
work_veryhigh_HEREMPN-1.62 0.414-3.92*** 0.00
work_veryhigh_MWTEMPN-1.72 0.739-2.33* 0.00
work_veryhigh_OTHEMPN-2.48 0.493-5.03*** 0.00
work_veryhigh_RETEMPN-2.38 NA NA 0.00fixed value
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
-999-999. 0.00 NA 0.00fixed value
1 1.00 0.00 NA 0.00fixed value
coef_dist_0_1-1.04 0.105-9.89*** 0.00
coef_dist_0_5_high 0.147 0.0114 12.86*** 0.00
coef_dist_15_up-0.117 0.00211-55.56*** 0.00
coef_dist_1_2-0.465 0.0428-10.86*** 0.00
coef_dist_2_5-0.418 0.0116-36.15*** 0.00
coef_dist_5_15-0.156 0.00276-56.40*** 0.00
coef_dist_5_up_high 0.0251 0.00176 14.22*** 0.00
coef_mode_logsum 0.0742 0.00837 8.87*** 0.00
work_high_AGREMPN-1.86 0.596-3.11** 0.00
work_high_FPSEMPN-1.90 0.178-10.67*** 0.00
work_high_HEREMPN-1.70 0.193-8.81*** 0.00
work_high_MWTEMPN-1.82 0.188-9.68*** 0.00
work_high_OTHEMPN-2.19 0.207-10.56*** 0.00
work_high_RETEMPN-2.21 0.00 NA 0.00fixed value
work_low_AGREMPN-71.8 7.07e-12-BIG*** 0.00
work_low_FPSEMPN-1.51 0.346-4.36*** 0.00
work_low_HEREMPN-0.819 0.360-2.27* 0.00
work_low_MWTEMPN-1.98 0.387-5.12*** 0.00
work_low_OTHEMPN-2.02 0.407-4.97*** 0.00
work_low_RETEMPN-2.05 0.00 NA 0.00fixed value
work_med_AGREMPN-8.09e+64 NA NA 0.00
work_med_FPSEMPN-2.15 0.194-11.06*** 0.00
work_med_HEREMPN-1.61 0.205-7.85*** 0.00
work_med_MWTEMPN-2.04 0.210-9.74*** 0.00
work_med_OTHEMPN-2.17 0.222-9.77*** 0.00
work_med_RETEMPN-2.12 0.00 NA 0.00fixed value
work_veryhigh_AGREMPN-6.04 24.2-0.25 0.00
work_veryhigh_FPSEMPN-1.84 0.152-12.10*** 0.00
work_veryhigh_HEREMPN-1.99 0.170-11.71*** 0.00
work_veryhigh_MWTEMPN-1.76 0.159-11.08*** 0.00
work_veryhigh_OTHEMPN-2.51 0.189-13.24*** 0.00
work_veryhigh_RETEMPN-2.38 0.00 NA 0.00fixed value
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -3763,12 +2646,13 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "from activitysim.estimation.larch import update_coefficients, update_size_spec\n", - "result_dir = data.edb_directory/\"estimated\"" + "\n", + "result_dir = data.edb_directory / \"estimated\"" ] }, { @@ -3780,12 +2664,14 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "update_coefficients(\n", - " model, data, result_dir,\n", + " model,\n", + " data,\n", + " result_dir,\n", " output_file=f\"{modelname}_coefficients_revised.csv\",\n", ");" ] @@ -3799,7 +2685,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -3844,12 +2730,12 @@ " work_low\n", " workplace\n", " 0.000000\n", - " 0.044251\n", - " 0.175515\n", - " 0.374554\n", - " 0.169451\n", - " 6.988481e-19\n", - " 0.236229\n", + " 0.121509\n", + " 0.208506\n", + " 0.415240\n", + " 0.124770\n", + " 6.285395e-32\n", + " 0.129975\n", " 0.000\n", " 0.000000\n", " 0.000000\n", @@ -3860,12 +2746,12 @@ " work_med\n", " workplace\n", " 0.000000\n", - " 0.120498\n", - " 0.144005\n", - " 0.251914\n", - " 0.079565\n", - " 3.439740e-07\n", - " 0.404018\n", + " 0.176350\n", + " 0.170960\n", + " 0.294919\n", + " 0.167444\n", + " 0.000000e+00\n", + " 0.190327\n", " 0.000\n", " 0.000000\n", " 0.000000\n", @@ -3876,12 +2762,12 @@ " work_high\n", " workplace\n", " 0.000000\n", - " 0.159104\n", - " 0.191636\n", - " 0.298286\n", - " 0.169233\n", - " 1.153217e-06\n", - " 0.181741\n", + " 0.125802\n", + " 0.171788\n", + " 0.209290\n", + " 0.128317\n", + " 1.787012e-01\n", + " 0.186102\n", " 0.000\n", " 0.000000\n", " 0.000000\n", @@ -3892,12 +2778,12 @@ " work_veryhigh\n", " workplace\n", " 0.000000\n", - " 0.062723\n", - " 0.116348\n", - " 0.133219\n", - " 0.056296\n", - " 5.108942e-01\n", - " 0.120520\n", + " 0.144466\n", + " 0.247167\n", + " 0.211891\n", + " 0.126365\n", + " 3.692074e-03\n", + " 0.266419\n", " 0.000\n", " 0.000000\n", " 0.000000\n", @@ -4197,10 +3083,10 @@ ], "text/plain": [ " segment model_selector TOTHH RETEMPN FPSEMPN HEREMPN \\\n", - "0 work_low workplace 0.000000 0.044251 0.175515 0.374554 \n", - "1 work_med workplace 0.000000 0.120498 0.144005 0.251914 \n", - "2 work_high workplace 0.000000 0.159104 0.191636 0.298286 \n", - "3 work_veryhigh workplace 0.000000 0.062723 0.116348 0.133219 \n", + "0 work_low workplace 0.000000 0.121509 0.208506 0.415240 \n", + "1 work_med workplace 0.000000 0.176350 0.170960 0.294919 \n", + "2 work_high workplace 0.000000 0.125802 0.171788 0.209290 \n", + "3 work_veryhigh workplace 0.000000 0.144466 0.247167 0.211891 \n", "4 university school 0.000000 0.000000 0.000000 0.000000 \n", "5 gradeschool school 0.000000 0.000000 0.000000 0.000000 \n", "6 highschool school 0.000000 0.000000 0.000000 0.000000 \n", @@ -4221,10 +3107,10 @@ "21 univ trip 0.000999 0.000000 0.000000 0.000000 \n", "\n", " OTHEMPN AGREMPN MWTEMPN AGE0519 HSENROLL COLLFTE COLLPTE \n", - "0 0.169451 6.988481e-19 0.236229 0.000 0.000000 0.000000 0.000000 \n", - "1 0.079565 3.439740e-07 0.404018 0.000 0.000000 0.000000 0.000000 \n", - "2 0.169233 1.153217e-06 0.181741 0.000 0.000000 0.000000 0.000000 \n", - "3 0.056296 5.108942e-01 0.120520 0.000 0.000000 0.000000 0.000000 \n", + "0 0.124770 6.285395e-32 0.129975 0.000 0.000000 0.000000 0.000000 \n", + "1 0.167444 0.000000e+00 0.190327 0.000 0.000000 0.000000 0.000000 \n", + "2 0.128317 1.787012e-01 0.186102 0.000 0.000000 0.000000 0.000000 \n", + "3 0.126365 3.692074e-03 0.266419 0.000 0.000000 0.000000 0.000000 \n", "4 0.000000 0.000000e+00 0.000000 0.000 0.000000 0.592000 0.408000 \n", "5 0.000000 0.000000e+00 0.000000 1.000 0.000000 0.000000 0.000000 \n", "6 0.000000 0.000000e+00 0.000000 0.000 1.000000 0.000000 0.000000 \n", @@ -4245,14 +3131,16 @@ "21 0.000000 0.000000e+00 0.000000 0.000 0.000000 0.591409 0.407592 " ] }, - "execution_count": 15, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "update_size_spec(\n", - " model, data, result_dir, \n", + " model,\n", + " data,\n", + " result_dir,\n", " output_file=f\"{modelname}_size_terms.csv\",\n", ")" ] @@ -4266,12 +3154,12 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "model.to_xlsx(\n", - " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", + " result_dir / f\"{modelname}_model_estimation.xlsx\",\n", " data_statistics=False,\n", ");" ] @@ -4290,7 +3178,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -4323,49 +3211,49 @@ " \n", " 0\n", " coef_dist_0_1\n", - " -1.084778\n", + " -1.035381\n", " F\n", " \n", " \n", " 1\n", " coef_dist_1_2\n", - " -0.252580\n", + " -0.465249\n", " F\n", " \n", " \n", " 2\n", " coef_dist_2_5\n", - " -0.369689\n", + " -0.417748\n", " F\n", " \n", " \n", " 3\n", " coef_dist_5_15\n", - " -0.152259\n", + " -0.155873\n", " F\n", " \n", " \n", " 4\n", " coef_dist_15_up\n", - " -0.091700\n", + " -0.117051\n", " F\n", " \n", " \n", " 5\n", " coef_dist_0_5_high\n", - " 0.120981\n", + " 0.146966\n", " F\n", " \n", " \n", " 6\n", " coef_dist_5_up_high\n", - " -0.015225\n", + " 0.025067\n", " F\n", " \n", " \n", " 7\n", " coef_mode_logsum\n", - " 0.155426\n", + " 0.074237\n", " F\n", " \n", " \n", @@ -4374,28 +3262,28 @@ ], "text/plain": [ " coefficient_name value constrain\n", - "0 coef_dist_0_1 -1.084778 F\n", - "1 coef_dist_1_2 -0.252580 F\n", - "2 coef_dist_2_5 -0.369689 F\n", - "3 coef_dist_5_15 -0.152259 F\n", - "4 coef_dist_15_up -0.091700 F\n", - "5 coef_dist_0_5_high 0.120981 F\n", - "6 coef_dist_5_up_high -0.015225 F\n", - "7 coef_mode_logsum 0.155426 F" + "0 coef_dist_0_1 -1.035381 F\n", + "1 coef_dist_1_2 -0.465249 F\n", + "2 coef_dist_2_5 -0.417748 F\n", + "3 coef_dist_5_15 -0.155873 F\n", + "4 coef_dist_15_up -0.117051 F\n", + "5 coef_dist_0_5_high 0.146966 F\n", + "6 coef_dist_5_up_high 0.025067 F\n", + "7 coef_mode_logsum 0.074237 F" ] }, - "execution_count": 17, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.read_csv(result_dir/f\"{modelname}_coefficients_revised.csv\")" + "pd.read_csv(result_dir / f\"{modelname}_coefficients_revised.csv\")" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -4442,12 +3330,12 @@ " work_low\n", " workplace\n", " 0.000000\n", - " 0.044251\n", - " 0.175515\n", - " 0.374554\n", - " 0.169451\n", - " 6.988481e-19\n", - " 0.236229\n", + " 0.121509\n", + " 0.208506\n", + " 0.415240\n", + " 0.124770\n", + " 6.285395e-32\n", + " 0.129975\n", " 0.000\n", " 0.000000\n", " 0.000000\n", @@ -4459,12 +3347,12 @@ " work_med\n", " workplace\n", " 0.000000\n", - " 0.120498\n", - " 0.144005\n", - " 0.251914\n", - " 0.079565\n", - " 3.439740e-07\n", - " 0.404018\n", + " 0.176350\n", + " 0.170960\n", + " 0.294919\n", + " 0.167444\n", + " 0.000000e+00\n", + " 0.190327\n", " 0.000\n", " 0.000000\n", " 0.000000\n", @@ -4476,12 +3364,12 @@ " work_high\n", " workplace\n", " 0.000000\n", - " 0.159104\n", - " 0.191636\n", - " 0.298286\n", - " 0.169233\n", - " 1.153217e-06\n", - " 0.181741\n", + " 0.125802\n", + " 0.171788\n", + " 0.209290\n", + " 0.128317\n", + " 1.787012e-01\n", + " 0.186102\n", " 0.000\n", " 0.000000\n", " 0.000000\n", @@ -4493,12 +3381,12 @@ " work_veryhigh\n", " workplace\n", " 0.000000\n", - " 0.062723\n", - " 0.116348\n", - " 0.133219\n", - " 0.056296\n", - " 5.108942e-01\n", - " 0.120520\n", + " 0.144466\n", + " 0.247167\n", + " 0.211891\n", + " 0.126365\n", + " 3.692074e-03\n", + " 0.266419\n", " 0.000\n", " 0.000000\n", " 0.000000\n", @@ -4816,10 +3704,10 @@ ], "text/plain": [ " index segment model_selector TOTHH RETEMPN FPSEMPN \\\n", - "0 0 work_low workplace 0.000000 0.044251 0.175515 \n", - "1 1 work_med workplace 0.000000 0.120498 0.144005 \n", - "2 2 work_high workplace 0.000000 0.159104 0.191636 \n", - "3 3 work_veryhigh workplace 0.000000 0.062723 0.116348 \n", + "0 0 work_low workplace 0.000000 0.121509 0.208506 \n", + "1 1 work_med workplace 0.000000 0.176350 0.170960 \n", + "2 2 work_high workplace 0.000000 0.125802 0.171788 \n", + "3 3 work_veryhigh workplace 0.000000 0.144466 0.247167 \n", "4 4 university school 0.000000 0.000000 0.000000 \n", "5 5 gradeschool school 0.000000 0.000000 0.000000 \n", "6 6 highschool school 0.000000 0.000000 0.000000 \n", @@ -4840,10 +3728,10 @@ "21 21 univ trip 0.000999 0.000000 0.000000 \n", "\n", " HEREMPN OTHEMPN AGREMPN MWTEMPN AGE0519 HSENROLL COLLFTE \\\n", - "0 0.374554 0.169451 6.988481e-19 0.236229 0.000 0.000000 0.000000 \n", - "1 0.251914 0.079565 3.439740e-07 0.404018 0.000 0.000000 0.000000 \n", - "2 0.298286 0.169233 1.153217e-06 0.181741 0.000 0.000000 0.000000 \n", - "3 0.133219 0.056296 5.108942e-01 0.120520 0.000 0.000000 0.000000 \n", + "0 0.415240 0.124770 6.285395e-32 0.129975 0.000 0.000000 0.000000 \n", + "1 0.294919 0.167444 0.000000e+00 0.190327 0.000 0.000000 0.000000 \n", + "2 0.209290 0.128317 1.787012e-01 0.186102 0.000 0.000000 0.000000 \n", + "3 0.211891 0.126365 3.692074e-03 0.266419 0.000 0.000000 0.000000 \n", "4 0.000000 0.000000 0.000000e+00 0.000000 0.000 0.000000 0.592000 \n", "5 0.000000 0.000000 0.000000e+00 0.000000 1.000 0.000000 0.000000 \n", "6 0.000000 0.000000 0.000000e+00 0.000000 0.000 1.000000 0.000000 \n", @@ -4888,13 +3776,1784 @@ "21 0.407592 " ] }, - "execution_count": 18, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pd.read_csv(result_dir / f\"{modelname}_size_terms.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Modify Spec\n", + "\n", + "Here, we will demonstrate the process of re-estimating the model with a modified\n", + "SPEC file. This does *not* require re-running ActivitySim, it just requires\n", + "changing the SPEC file and re-running the Larch estimation only.\n", + "\n", + "The `backup` command we ran earlier made a backup copy of the \n", + "original spec file in the EDB directory.\n", + "This was not strictly necessary, but since we're about to modify it and\n", + "we may want undo our changes, it can be handy to keep a copy of the\n", + "original spec file around. Since we already have a backup copy, we'll make some \n", + "changes directly in the SPEC file. As an example here, we're going\n", + "to change one of the breakpoints on the piecewise distance function in the\n", + "utility calculation. For this demo we are editing \n", + "the SPEC file using Python code to make the changes, but a user does not need\n", + "to change the file using Python; any CSV editor (e.g. Excel) can be used. \n", + "\n", + "The raw contents of the SPEC file can be loaded and viewed in Python like this:" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Label,Description,Expression,coefficient\n", + "local_dist,,_DIST@skims['DIST'],1\n", + "util_dist_0_1,\"Distance, piecewise linear from 0 to 1 miles\",\"@_DIST.clip(0,1)\",coef_dist_0_1\n", + "util_dist_1_2,\"Distance, piecewise linear from 1 to 2 miles\",\"@(_DIST-1).clip(0,1)\",coef_dist_1_2\n", + "util_dist_2_5,\"Distance, piecewise linear from 2 to 5 miles\",\"@(_DIST-2).clip(0,3)\",coef_dist_2_5\n", + "util_dist_5_15,\"Distance, piecewise linear from 5 to 15 miles\",\"@(_DIST-5).clip(0,10)\",coef_dist_5_15\n", + "util_dist_15_up,\"Distance, piecewise linear for 15+ miles\",@(_DIST-15.0).clip(0),coef_dist_15_up\n", + "util_dist_0_5_high,\"Distance 0 to 5 mi, high and very high income\",@(df['income_segment']>=WORK_HIGH_SEGMENT_ID) * _DIST.clip(upper=5),coef_dist_0_5_high\n", + "util_dist_15_up_high,\"Distance 5+ mi, high and very high income\",@(df['income_segment']>=WORK_HIGH_SEGMENT_ID) * (_DIST-5).clip(0),coef_dist_5_up_high\n", + "util_size_variable,Size variable,@(df['size_term'] * df['shadow_price_size_term_adjustment']).apply(np.log1p),1\n", + "util_utility_adjustment,utility adjustment,@df['shadow_price_utility_adjustment'],1\n", + "util_no_attractions,No attractions,@df['size_term']==0,-999\n", + "util_mode_logsum,Mode choice logsum,mode_choice_logsum,coef_mode_logsum\n", + "util_sample_of_corrections_factor,Sample of alternatives correction factor,\"@np.minimum(np.log(df.pick_count/df.prob), 60)\",1\n" + ] + } + ], + "source": [ + "with open(data.edb_directory / \"workplace_location_SPEC.csv\") as f:\n", + " raw_spec = f.read()\n", + "\n", + "print(raw_spec)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's move the 2 mile breakpoint to 3 miles. To do so, we will need to change two lines\n", + "of the SPEC file. As we change the file, we will edit all four columns: label, description, \n", + "expression, and coefficient. \n", + "\n", + "## WARNING\n", + "\n", + "**It is particularly important to make changes to the label when \n", + "changing the expression.** The estimation tools will prefer the pre-calculated variables computed\n", + "and stored with the given label, so if the label is not changed the expression changes will be ignored.\n", + "\n", + "After we make the changes, we'll write the modified SPEC file back to disk, overwriting the original." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "orig_lines = \"\"\"util_dist_1_2,\"Distance, piecewise linear from 1 to 2 miles\",\"@(_DIST-1).clip(0,1)\",coef_dist_1_2\n", + "util_dist_2_5,\"Distance, piecewise linear from 2 to 5 miles\",\"@(_DIST-2).clip(0,3)\",coef_dist_2_5\"\"\"\n", + "\n", + "repl_lines = \"\"\"util_dist_1_3,\"Distance, piecewise linear from 1 to 3 miles\",\"@(_DIST-1).clip(0,2)\",coef_dist_1_3\n", + "util_dist_3_5,\"Distance, piecewise linear from 3 to 5 miles\",\"@(_DIST-3).clip(0,2)\",coef_dist_3_5\"\"\"\n", + "\n", + "raw_spec = raw_spec.replace(orig_lines, repl_lines)\n", + "\n", + "with open(data.edb_directory / \"workplace_location_SPEC.csv\", mode=\"w\") as f:\n", + " f.write(raw_spec)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Reloading the model and getting set for re-estimation can be done using the same commands as above." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_landuse.csv\n", + "loading from output-est-mode/estimation_data_bundle/workplace_location/workplace_location_size_terms.csv\n" + ] + } + ], + "source": [ + "model2, data2 = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You may notice in the utility functions shown below, all of the unadulterated lines of the \n", + "spec file correlate with utility terms that are simple `X.label` data items, which are \n", + "stored as pre-computed data variables in the EDB. Our modified lines, however, are now\n", + "showing the complete expression that will be freshly evaluated by Larch using Sharrow." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
P.coef_dist_0_1 * X.util_dist_0_1
+ P.coef_dist_1_3 * X('(_DIST-1).clip(0,2)')
+ P.coef_dist_3_5 * X('(_DIST-3).clip(0,2)')
+ P.coef_dist_5_15 * X.util_dist_5_15
+ P.coef_dist_15_up * X.util_dist_15_up
+ P.coef_dist_0_5_high * X.util_dist_0_5_high
+ P.coef_dist_5_up_high * X.util_dist_15_up_high
+ P('-999') * X.util_no_attractions
+ P.coef_mode_logsum * X.util_mode_logsum
+ P('1') * X.util_sample_of_corrections_factor
" + ], + "text/plain": [ + " P.coef_dist_0_1 * X.util_dist_0_1\n", + "+ P.coef_dist_1_3 * X('(_DIST-1).clip(0,2)')\n", + "+ P.coef_dist_3_5 * X('(_DIST-3).clip(0,2)')\n", + "+ P.coef_dist_5_15 * X.util_dist_5_15\n", + "+ P.coef_dist_15_up * X.util_dist_15_up\n", + "+ P.coef_dist_0_5_high * X.util_dist_0_5_high\n", + "+ P.coef_dist_5_up_high * X.util_dist_15_up_high\n", + "+ P('-999') * X.util_no_attractions\n", + "+ P.coef_mode_logsum * X.util_mode_logsum\n", + "+ P('1') * X.util_sample_of_corrections_factor" + ] + }, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.read_csv(result_dir/f\"{modelname}_size_terms.csv\")" + "model2.utility_ca" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We are almost ready to go with this model. But if we attempt to estimate the model now, we will get an error:" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "NameError(\"name '_DIST' is not defined\")\n" + ] + } + ], + "source": [ + "from larch.util.shush import shush\n", + "\n", + "with shush(stderr=True):\n", + " try:\n", + " model2.estimate()\n", + " except NameError as e:\n", + " print(repr(e))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The error arises because the model SPEC includes a temporary `_DIST` variable, which was not stored in the EDB data files.\n", + "There are several ways to solve this problem. The most robust way would be to return to ActivitySim and edit the model specification\n", + "and configurations so that this variable is not a temporary value (i.e. add it to a preprocessor or annotator). This process \n", + "may take some time and effort, but it should be able to allow the user to access any variable from ActivitySim.\n", + "\n", + "Alternatively, it may be possible to reconstruct the value of the temporary variable, or a suitable proxy, by processing \n", + "values that did get stored in the EDB. We can do so here, by reconstituting the distance value as the sum of the piecewise\n", + "parts that did get stored in the EDB. Rather than returning to ActivitySim, we can simply compute the temporary variable\n", + "directly in the model's data object, giving it the same name as from the specification file, and otherwise proceed as normal." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "model2.data[\"_DIST\"] = (\n", + " model2.data.util_dist_0_1\n", + " + model2.data.util_dist_1_2\n", + " + model2.data.util_dist_2_5\n", + " + model2.data.util_dist_5_15\n", + " + model2.data.util_dist_15_up\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

Iteration 008 [Optimization terminated successfully]

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

Best LL = -88684.18177107332

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0
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coef_dist_0_5_high0.147163
coef_dist_15_up-0.117017
coef_dist_1_3-0.433865
coef_dist_3_5-0.417069
coef_dist_5_15-0.155760
coef_dist_5_up_high0.025050
coef_mode_logsum0.074530
work_high_AGREMPN-1.857041
work_high_FPSEMPN-1.895566
work_high_HEREMPN-1.698595
work_high_MWTEMPN-1.816036
work_high_OTHEMPN-2.187730
work_high_RETEMPN-2.207275
work_low_AGREMPN-286.802086
work_low_FPSEMPN-1.507131
work_low_HEREMPN-0.818251
work_low_MWTEMPN-1.979965
work_low_OTHEMPN-2.020885
work_low_RETEMPN-2.047943
work_med_AGREMPN-1490.624349
work_med_FPSEMPN-2.150429
work_med_HEREMPN-1.605331
work_med_MWTEMPN-2.043346
work_med_OTHEMPN-2.171601
work_med_RETEMPN-2.120264
work_veryhigh_AGREMPN-6.028955
work_veryhigh_FPSEMPN-1.838036
work_veryhigh_HEREMPN-1.992113
work_veryhigh_MWTEMPN-1.763204
work_veryhigh_OTHEMPN-2.509234
work_veryhigh_RETEMPN-2.375156
tolerance2.5082874166498626e-07
stepsarray([0.25, 0.5 , 0.75, 1. , 1. , 1. , 1. , 1. ])
message'Optimization terminated successfully'
elapsed_time0:00:02.337866
method'BHHH'
n_cases28281
iteration_number8
" + ], + "text/plain": [ + "┣ loglike: -88684.18177107332\n", + "┣ x: -999 -999.000000\n", + "┃ 1 1.000000\n", + "┃ coef_dist_0_1 -1.072002\n", + "┃ coef_dist_0_5_high 0.147163\n", + "┃ coef_dist_15_up -0.117017\n", + "┃ coef_dist_1_3 -0.433865\n", + "┃ coef_dist_3_5 -0.417069\n", + "┃ coef_dist_5_15 -0.155760\n", + "┃ coef_dist_5_up_high 0.025050\n", + "┃ coef_mode_logsum 0.074530\n", + "┃ work_high_AGREMPN -1.857041\n", + "┃ work_high_FPSEMPN -1.895566\n", + "┃ work_high_HEREMPN -1.698595\n", + "┃ work_high_MWTEMPN -1.816036\n", + "┃ work_high_OTHEMPN -2.187730\n", + "┃ work_high_RETEMPN -2.207275\n", + "┃ work_low_AGREMPN -286.802086\n", + "┃ work_low_FPSEMPN -1.507131\n", + "┃ work_low_HEREMPN -0.818251\n", + "┃ work_low_MWTEMPN -1.979965\n", + "┃ work_low_OTHEMPN -2.020885\n", + "┃ work_low_RETEMPN -2.047943\n", + "┃ work_med_AGREMPN -1490.624349\n", + "┃ work_med_FPSEMPN -2.150429\n", + "┃ work_med_HEREMPN -1.605331\n", + "┃ work_med_MWTEMPN -2.043346\n", + "┃ work_med_OTHEMPN -2.171601\n", + "┃ work_med_RETEMPN -2.120264\n", + "┃ work_veryhigh_AGREMPN -6.028955\n", + "┃ work_veryhigh_FPSEMPN -1.838036\n", + "┃ work_veryhigh_HEREMPN -1.992113\n", + "┃ work_veryhigh_MWTEMPN -1.763204\n", + "┃ work_veryhigh_OTHEMPN -2.509234\n", + "┃ work_veryhigh_RETEMPN -2.375156\n", + "┃ dtype: float64\n", + "┣ tolerance: 2.5082874166498626e-07\n", + "┣ steps: array([0.25, 0.5 , 0.75, 1. , 1. , 1. , 1. , 1. ])\n", + "┣ message: 'Optimization terminated successfully'\n", + "┣ elapsed_time: datetime.timedelta(seconds=2, microseconds=337866)\n", + "┣ method: 'BHHH'\n", + "┣ n_cases: 28281\n", + "┣ iteration_number: 8" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "with shush(stderr=True):\n", + " # swallow a bunch of error logging related to recovery from our previous estimation failure\n", + " result2 = model2.estimate(method=\"BHHH\", options={\"maxiter\": 1000})\n", + "\n", + "result2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can then review the original and revised models side-by-side to see the differences." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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modelmodel2
Number of CasesAggregate28281.00000028281.000000
Log Likelihood at ConvergenceAggregate-88683.850386-88684.181771
Per Case-3.135810-3.135822
Log Likelihood at Null ParametersAggregate-124263.519724-124263.519724
Per Case-4.393887-4.393887
Rho Squared w.r.t. Null ParametersAggregate0.2863240.286322
\n", + "
" + ], + "text/plain": [ + " model model2\n", + "Number of Cases Aggregate 28281.000000 28281.000000\n", + "Log Likelihood at Convergence Aggregate -88683.850386 -88684.181771\n", + " Per Case -3.135810 -3.135822\n", + "Log Likelihood at Null Parameters Aggregate -124263.519724 -124263.519724\n", + " Per Case -4.393887 -4.393887\n", + "Rho Squared w.r.t. Null Parameters Aggregate 0.286324 0.286322" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with pd.option_context('display.max_rows', 999):\n", + " display(pd.concat({\n", + " \"model\": model.estimation_statistics_raw(),\n", + " \"model2\": model2.estimation_statistics_raw(),\n", + " }, axis=1).fillna(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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modelmodel2
ValueStd Errt StatSignifNull ValueConstrainedValueStd Errt StatSignifNull ValueConstrained
Parameter
-999-999.0.00NA0.0fixed value-999.0.00NA0.0fixed value
11.000.00NA0.0fixed value1.000.00NA0.0fixed value
coef_dist_0_1-1.040.105-9.89***0.0-1.070.0946-11.33***0.0
coef_dist_0_5_high0.1470.011412.86***0.00.1470.011412.86***0.0
coef_dist_15_up-0.1170.00211-55.56***0.0-0.1170.00211-55.55***0.0
coef_dist_1_2-0.4650.0428-10.86***0.0
coef_dist_2_5-0.4180.0116-36.15***0.0
coef_dist_5_15-0.1560.00276-56.40***0.0-0.1560.00283-55.09***0.0
coef_dist_5_up_high0.02510.0017614.22***0.00.02500.0017614.20***0.0
coef_mode_logsum0.07420.008378.87***0.00.07450.008368.91***0.0
work_high_AGREMPN-1.860.596-3.11**0.0-1.860.597-3.11**0.0
work_high_FPSEMPN-1.900.178-10.67***0.0-1.900.178-10.67***0.0
work_high_HEREMPN-1.700.193-8.81***0.0-1.700.193-8.81***0.0
work_high_MWTEMPN-1.820.188-9.68***0.0-1.820.188-9.68***0.0
work_high_OTHEMPN-2.190.207-10.56***0.0-2.190.207-10.56***0.0
work_high_RETEMPN-2.210.00NA0.0fixed value-2.210.00NA0.0fixed value
work_low_AGREMPN-71.87.07e-12-BIG***0.0-287.NANA0.0
work_low_FPSEMPN-1.510.346-4.36***0.0-1.510.346-4.36***0.0
work_low_HEREMPN-0.8190.360-2.27*0.0-0.8180.361-2.27*0.0
work_low_MWTEMPN-1.980.387-5.12***0.0-1.980.387-5.11***0.0
work_low_OTHEMPN-2.020.407-4.97***0.0-2.020.407-4.96***0.0
work_low_RETEMPN-2.050.00NA0.0fixed value-2.050.00NA0.0fixed value
work_med_AGREMPN-8.09e+64NANA0.0-1.49e+03NANA0.0
work_med_FPSEMPN-2.150.194-11.06***0.0-2.150.195-11.05***0.0
work_med_HEREMPN-1.610.205-7.85***0.0-1.610.205-7.84***0.0
work_med_MWTEMPN-2.040.210-9.74***0.0-2.040.210-9.73***0.0
work_med_OTHEMPN-2.170.222-9.77***0.0-2.170.222-9.77***0.0
work_med_RETEMPN-2.120.00NA0.0fixed value-2.120.00NA0.0fixed value
work_veryhigh_AGREMPN-6.0424.2-0.250.0-6.0323.7-0.250.0
work_veryhigh_FPSEMPN-1.840.152-12.10***0.0-1.840.152-12.10***0.0
work_veryhigh_HEREMPN-1.990.170-11.71***0.0-1.990.170-11.71***0.0
work_veryhigh_MWTEMPN-1.760.159-11.08***0.0-1.760.159-11.08***0.0
work_veryhigh_OTHEMPN-2.510.189-13.24***0.0-2.510.189-13.24***0.0
work_veryhigh_RETEMPN-2.380.00NA0.0fixed value-2.380.00NA0.0fixed value
coef_dist_1_3-0.4340.0202-21.48***0.0
coef_dist_3_5-0.4170.0156-26.81***0.0
\n", + "
" + ], + "text/plain": [ + " model \\\n", + " Value Std Err t Stat Signif Null Value \n", + "Parameter \n", + "-999 -999.  0.00  NA 0.0 \n", + "1  1.00  0.00  NA 0.0 \n", + "coef_dist_0_1 -1.04  0.105 -9.89 *** 0.0 \n", + "coef_dist_0_5_high  0.147  0.0114  12.86 *** 0.0 \n", + "coef_dist_15_up -0.117  0.00211 -55.56 *** 0.0 \n", + "coef_dist_1_2 -0.465  0.0428 -10.86 *** 0.0 \n", + "coef_dist_2_5 -0.418  0.0116 -36.15 *** 0.0 \n", + "coef_dist_5_15 -0.156  0.00276 -56.40 *** 0.0 \n", + "coef_dist_5_up_high  0.0251  0.00176  14.22 *** 0.0 \n", + "coef_mode_logsum  0.0742  0.00837  8.87 *** 0.0 \n", + "work_high_AGREMPN -1.86  0.596 -3.11 ** 0.0 \n", + "work_high_FPSEMPN -1.90  0.178 -10.67 *** 0.0 \n", + "work_high_HEREMPN -1.70  0.193 -8.81 *** 0.0 \n", + "work_high_MWTEMPN -1.82  0.188 -9.68 *** 0.0 \n", + "work_high_OTHEMPN -2.19  0.207 -10.56 *** 0.0 \n", + "work_high_RETEMPN -2.21  0.00  NA 0.0 \n", + "work_low_AGREMPN -71.8  7.07e-12 -BIG *** 0.0 \n", + "work_low_FPSEMPN -1.51  0.346 -4.36 *** 0.0 \n", + "work_low_HEREMPN -0.819  0.360 -2.27 * 0.0 \n", + "work_low_MWTEMPN -1.98  0.387 -5.12 *** 0.0 \n", + "work_low_OTHEMPN -2.02  0.407 -4.97 *** 0.0 \n", + "work_low_RETEMPN -2.05  0.00  NA 0.0 \n", + "work_med_AGREMPN -8.09e+64  NA  NA 0.0 \n", + "work_med_FPSEMPN -2.15  0.194 -11.06 *** 0.0 \n", + "work_med_HEREMPN -1.61  0.205 -7.85 *** 0.0 \n", + "work_med_MWTEMPN -2.04  0.210 -9.74 *** 0.0 \n", + "work_med_OTHEMPN -2.17  0.222 -9.77 *** 0.0 \n", + "work_med_RETEMPN -2.12  0.00  NA 0.0 \n", + "work_veryhigh_AGREMPN -6.04  24.2 -0.25 0.0 \n", + "work_veryhigh_FPSEMPN -1.84  0.152 -12.10 *** 0.0 \n", + "work_veryhigh_HEREMPN -1.99  0.170 -11.71 *** 0.0 \n", + "work_veryhigh_MWTEMPN -1.76  0.159 -11.08 *** 0.0 \n", + "work_veryhigh_OTHEMPN -2.51  0.189 -13.24 *** 0.0 \n", + "work_veryhigh_RETEMPN -2.38  0.00  NA 0.0 \n", + "coef_dist_1_3 \n", + "coef_dist_3_5 \n", + "\n", + " model2 \\\n", + " Constrained Value Std Err t Stat Signif \n", + "Parameter \n", + "-999 fixed value -999.  0.00  NA \n", + "1 fixed value  1.00  0.00  NA \n", + "coef_dist_0_1 -1.07  0.0946 -11.33 *** \n", + "coef_dist_0_5_high  0.147  0.0114  12.86 *** \n", + "coef_dist_15_up -0.117  0.00211 -55.55 *** \n", + "coef_dist_1_2 \n", + "coef_dist_2_5 \n", + "coef_dist_5_15 -0.156  0.00283 -55.09 *** \n", + "coef_dist_5_up_high  0.0250  0.00176  14.20 *** \n", + "coef_mode_logsum  0.0745  0.00836  8.91 *** \n", + "work_high_AGREMPN -1.86  0.597 -3.11 ** \n", + "work_high_FPSEMPN -1.90  0.178 -10.67 *** \n", + "work_high_HEREMPN -1.70  0.193 -8.81 *** \n", + "work_high_MWTEMPN -1.82  0.188 -9.68 *** \n", + "work_high_OTHEMPN -2.19  0.207 -10.56 *** \n", + "work_high_RETEMPN fixed value -2.21  0.00  NA \n", + "work_low_AGREMPN -287.  NA  NA \n", + "work_low_FPSEMPN -1.51  0.346 -4.36 *** \n", + "work_low_HEREMPN -0.818  0.361 -2.27 * \n", + "work_low_MWTEMPN -1.98  0.387 -5.11 *** \n", + "work_low_OTHEMPN -2.02  0.407 -4.96 *** \n", + "work_low_RETEMPN fixed value -2.05  0.00  NA \n", + "work_med_AGREMPN -1.49e+03  NA  NA \n", + "work_med_FPSEMPN -2.15  0.195 -11.05 *** \n", + "work_med_HEREMPN -1.61  0.205 -7.84 *** \n", + "work_med_MWTEMPN -2.04  0.210 -9.73 *** \n", + "work_med_OTHEMPN -2.17  0.222 -9.77 *** \n", + "work_med_RETEMPN fixed value -2.12  0.00  NA \n", + "work_veryhigh_AGREMPN -6.03  23.7 -0.25 \n", + "work_veryhigh_FPSEMPN -1.84  0.152 -12.10 *** \n", + "work_veryhigh_HEREMPN -1.99  0.170 -11.71 *** \n", + "work_veryhigh_MWTEMPN -1.76  0.159 -11.08 *** \n", + "work_veryhigh_OTHEMPN -2.51  0.189 -13.24 *** \n", + "work_veryhigh_RETEMPN fixed value -2.38  0.00  NA \n", + "coef_dist_1_3 -0.434  0.0202 -21.48 *** \n", + "coef_dist_3_5 -0.417  0.0156 -26.81 *** \n", + "\n", + " \n", + " Null Value Constrained \n", + "Parameter \n", + "-999 0.0 fixed value \n", + "1 0.0 fixed value \n", + "coef_dist_0_1 0.0 \n", + "coef_dist_0_5_high 0.0 \n", + "coef_dist_15_up 0.0 \n", + "coef_dist_1_2 \n", + "coef_dist_2_5 \n", + "coef_dist_5_15 0.0 \n", + "coef_dist_5_up_high 0.0 \n", + "coef_mode_logsum 0.0 \n", + "work_high_AGREMPN 0.0 \n", + "work_high_FPSEMPN 0.0 \n", + "work_high_HEREMPN 0.0 \n", + "work_high_MWTEMPN 0.0 \n", + "work_high_OTHEMPN 0.0 \n", + "work_high_RETEMPN 0.0 fixed value \n", + "work_low_AGREMPN 0.0 \n", + "work_low_FPSEMPN 0.0 \n", + "work_low_HEREMPN 0.0 \n", + "work_low_MWTEMPN 0.0 \n", + "work_low_OTHEMPN 0.0 \n", + "work_low_RETEMPN 0.0 fixed value \n", + "work_med_AGREMPN 0.0 \n", + "work_med_FPSEMPN 0.0 \n", + "work_med_HEREMPN 0.0 \n", + "work_med_MWTEMPN 0.0 \n", + "work_med_OTHEMPN 0.0 \n", + "work_med_RETEMPN 0.0 fixed value \n", + "work_veryhigh_AGREMPN 0.0 \n", + "work_veryhigh_FPSEMPN 0.0 \n", + "work_veryhigh_HEREMPN 0.0 \n", + "work_veryhigh_MWTEMPN 0.0 \n", + "work_veryhigh_OTHEMPN 0.0 \n", + "work_veryhigh_RETEMPN 0.0 fixed value \n", + "coef_dist_1_3 0.0 \n", + "coef_dist_3_5 0.0 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with pd.option_context('display.max_rows', 999):\n", + " display(pd.concat({\n", + " \"model\": model.parameter_summary().data,\n", + " \"model2\": model2.parameter_summary().data,\n", + " }, axis=1).fillna(\"\"))" ] } ], @@ -4905,7 +5564,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -4919,7 +5578,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/04_auto_ownership.ipynb b/activitysim/examples/example_estimation/notebooks/04_auto_ownership.ipynb index 8a4206918f..c637ed5407 100644 --- a/activitysim/examples/example_estimation/notebooks/04_auto_ownership.ipynb +++ b/activitysim/examples/example_estimation/notebooks/04_auto_ownership.ipynb @@ -34,34 +34,82 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare, backup\n", + "prepare()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "# Load data and prep model for estimation" + "In this demo notebook, we will (later) edit the model spec file. But for demo purposes, we want to\n", + "make sure we are starting from the \"original\" spec file, so we'll check that now. For actual \n", + "applications, this step would not be necessary." ] }, { @@ -69,11 +117,41 @@ "execution_count": 3, "metadata": {}, "outputs": [], + "source": [ + "backup(\"output-est-mode/estimation_data_bundle/auto_ownership/auto_ownership_SPEC.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load data and prep model for estimation" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/auto_ownership/auto_ownership_coefficients.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/auto_ownership/auto_ownership_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/auto_ownership/auto_ownership_values_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"auto_ownership\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "model, data = component_model(\n", + " modelname, \n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -94,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -206,7 +284,7 @@ "[67 rows x 2 columns]" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -224,7 +302,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -801,7 +879,7 @@ "28 coef_cars4_auto_time_saving_per_worker " ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -819,7 +897,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -854,15 +932,15 @@ " util_presence_children_0_4\n", " util_presence_children_5_17\n", " ...\n", - " HSENROLL\n", - " COLLFTE\n", - " COLLPTE\n", - " TOPOLOGY\n", - " TERMINAL\n", - " household_density\n", - " employment_density\n", - " density_index\n", - " is_cbd\n", + " auPkTotal\n", + " auOpRetail\n", + " auOpTotal\n", + " trPkRetail\n", + " trPkTotal\n", + " trOpRetail\n", + " trOpTotal\n", + " nmRetail\n", + " nmTotal\n", " override_choice_code\n", " \n", " \n", @@ -892,9 +970,9 @@ " \n", " \n", " \n", - " 166\n", - " 0\n", - " 0\n", + " 45\n", + " 1\n", + " 1\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -904,21 +982,21 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.21263\n", - " 24.783133\n", - " 31.566265\n", - " 13.883217\n", - " False\n", - " 1\n", + " 12.513805\n", + " 9.924660\n", + " 12.562639\n", + " 4.193237\n", + " 6.875144\n", + " 3.952128\n", + " 6.590585\n", + " 2.194792\n", + " 6.359507\n", + " 2\n", " \n", " \n", - " 197\n", - " 0\n", - " 0\n", + " 499\n", + " 1\n", + " 1\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -928,19 +1006,19 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.68156\n", - " 56.783784\n", - " 10.459459\n", - " 8.832526\n", - " False\n", - " 1\n", + " 12.823009\n", + " 10.284673\n", + " 12.868645\n", + " 6.639963\n", + " 9.364105\n", + " 6.531079\n", + " 9.259002\n", + " 5.955868\n", + " 7.795004\n", + " 2\n", " \n", " \n", - " 268\n", + " 659\n", " 1\n", " 1\n", " 0.0\n", @@ -952,19 +1030,19 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 3598.08521\n", - " 0.00000\n", - " 1\n", - " 3.29100\n", - " 11.947644\n", - " 45.167539\n", - " 9.448375\n", - " True\n", + " 12.663406\n", + " 10.247505\n", + " 12.762286\n", + " 6.001466\n", + " 8.409169\n", + " 5.786652\n", + " 8.279842\n", + " 5.798886\n", + " 7.900061\n", " 2\n", " \n", " \n", - " 375\n", + " 948\n", " 1\n", " 1\n", " 0.0\n", @@ -976,20 +1054,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 4.11499\n", - " 73.040169\n", - " 28.028350\n", - " 20.255520\n", - " True\n", + " 12.710919\n", + " 10.150335\n", + " 12.777635\n", + " 5.172974\n", + " 7.850360\n", + " 4.893929\n", + " 7.571579\n", + " 4.895220\n", + " 7.409345\n", " 2\n", " \n", " \n", - " 387\n", - " 1\n", + " 1276\n", + " 0\n", " 1\n", " 0.0\n", " 0.0\n", @@ -1000,15 +1078,15 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 227.78223\n", - " 41.22827\n", - " 1\n", - " 3.83527\n", - " 26.631579\n", - " 45.868421\n", - " 16.848945\n", - " False\n", + " 12.661307\n", + " 10.258471\n", + " 12.759529\n", + " 6.039019\n", + " 8.348963\n", + " 5.778785\n", + " 8.070525\n", + " 6.073537\n", + " 7.851667\n", " 2\n", " \n", " \n", @@ -1036,7 +1114,7 @@ " ...\n", " \n", " \n", - " 2863464\n", + " 2874468\n", " 1\n", " 1\n", " 0.0\n", @@ -1048,21 +1126,21 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 72.14684\n", - " 0.00000\n", - " 1\n", - " 5.52555\n", - " 38.187500\n", - " 978.875000\n", - " 36.753679\n", - " False\n", + " 10.036845\n", + " 8.113608\n", + " 10.265845\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " 2\n", " \n", " \n", - " 2863483\n", - " 1\n", + " 2874567\n", " 1\n", + " 0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -1072,20 +1150,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 0.00000\n", - " 0.00000\n", - " 3\n", - " 3.99027\n", - " 39.838272\n", - " 71.693001\n", - " 25.608291\n", - " True\n", - " 2\n", + " 8.811126\n", + " 6.560015\n", + " 8.886403\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 1\n", " \n", " \n", - " 2863806\n", - " 1\n", + " 2874576\n", + " 0\n", " 1\n", " 0.0\n", " 0.0\n", @@ -1096,19 +1174,19 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 4.27539\n", - " 51.675676\n", - " 47.216216\n", - " 24.672699\n", - " False\n", + " 8.811126\n", + " 6.560015\n", + " 8.886403\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " 2\n", " \n", " \n", - " 2864518\n", + " 2874826\n", " 1\n", " 1\n", " 0.0\n", @@ -1120,20 +1198,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 25.52083\n", - " 15.938148\n", - " 551.353820\n", - " 15.490363\n", - " True\n", + " 11.356335\n", + " 9.298380\n", + " 11.721935\n", + " 1.052528\n", + " 2.925968\n", + " 0.494776\n", + " 2.006432\n", + " 3.782008\n", + " 6.208875\n", " 2\n", " \n", " \n", - " 2864688\n", - " 1\n", + " 2875013\n", + " 0\n", " 1\n", " 0.0\n", " 0.0\n", @@ -1144,111 +1222,111 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.29134\n", - " 16.000000\n", - " 31.644068\n", - " 10.626823\n", - " False\n", + " 11.663277\n", + " 9.588527\n", + " 12.019407\n", + " 3.053361\n", + " 5.871246\n", + " 0.141304\n", + " 0.776133\n", + " 4.090554\n", + " 6.388513\n", " 2\n", " \n", " \n", "\n", - "

2000 rows × 95 columns

\n", + "

20000 rows × 95 columns

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Iteration 015 [Optimization terminated successfully.]

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Iteration 067 [Optimization terminated successfully]

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Best LL = -1732.441809546802

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66 rows × 8 columns

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66 rows × 7 columns

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"coef_retail_non_motor NaN NaN 1 \n", - "coef_retail_transit_no_workers NaN NaN 0 \n", - "coef_retail_transit_workers NaN NaN 0 \n", + " value best initvalue \\\n", + "param_name \n", + "coef_cars1_asc 1.337433 1.337433 1.1865 \n", + "coef_cars1_asc_county -0.655949 -0.655949 -0.5660 \n", + "coef_cars1_asc_marin -0.168475 -0.168475 -0.2434 \n", + "coef_cars1_asc_san_francisco 0.324519 0.324519 0.4259 \n", + "coef_cars1_auto_time_saving_per_worker 0.394451 0.394451 0.4707 \n", + "... ... ... ... \n", + "coef_retail_auto_no_workers 0.039844 0.039844 0.0626 \n", + "coef_retail_auto_workers 0.155792 0.155792 0.1646 \n", + "coef_retail_non_motor -0.030000 -0.030000 -0.0300 \n", + "coef_retail_transit_no_workers -0.307701 -0.307701 -0.3053 \n", + "coef_retail_transit_workers -0.524658 -0.524658 -0.5117 \n", "\n", - " best \n", - "coef_cars1_asc 4.744711 \n", - "coef_cars1_asc_county -0.566000 \n", - "coef_cars1_asc_marin -0.243396 \n", - "coef_cars1_asc_san_francisco 3.984111 \n", - "coef_cars1_auto_time_saving_per_worker -0.039384 \n", - 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"text": [ - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 9.359944885353407e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 8.107476782860855e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 7.627843595130013e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.990378290025734e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.0563705701904108e-16 in general_inverse\n", - 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x\n", + "
keyvalue
x\n", " \n", " \n", " \n", @@ -1563,23 +1577,23 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1587,11 +1601,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1603,11 +1617,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1623,7 +1637,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1631,11 +1645,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1643,175 +1657,175 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1819,816 +1833,3969 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - "
coef_cars1_asc4.7447111.337433
coef_cars1_asc_county-0.566000-0.655949
coef_cars1_asc_marin-0.243396-0.168475
coef_cars1_asc_san_francisco3.9841110.324519
coef_cars1_auto_time_saving_per_worker-0.0393840.394451
coef_cars1_density_0_10_no_workers
coef_cars1_density_10_up_no_workers-0.006930-0.014457
coef_cars1_density_10_up_workers-0.016448-0.018280
coef_cars1_drivers_2
coef_cars1_drivers_4_up2.0455452.010834
coef_cars1_hh_income_0_30k0.0285640.045617
coef_cars1_hh_income_30_up
coef_cars1_persons_18_24-0.448145-0.475768
coef_cars1_persons_25_34
coef_cars1_presence_children_0_40.4863210.486627
coef_cars1_presence_children_5_17-0.2342660.038980
coef_cars234_asc_marin
coef_cars234_presence_children_0_40.5901130.834181
coef_cars2_asc2.466763-0.816912
coef_cars2_asc_county-0.442900-0.534108
coef_cars2_asc_san_francisco4.0196630.395165
coef_cars2_auto_time_saving_per_worker0.0106060.625959
coef_cars2_density_0_10_no_workers-0.189423-0.188961
coef_cars2_density_10_up_no_workers-0.121021-0.118760
coef_cars2_drivers_22.9451532.883946
coef_cars2_drivers_33.5950543.464192
coef_cars2_drivers_4_up6.8564056.182053
coef_cars2_hh_income_0_30k0.0622690.055723
coef_cars2_hh_income_30_up0.0072880.007093
coef_cars2_num_workers_clip_3-0.0282580.316983
coef_cars2_persons_16_17-1.439330-0.845210
coef_cars2_persons_18_24-0.942633-0.990269
coef_cars2_persons_25_34-0.471640-0.379371
coef_cars2_presence_children_5_170.1645260.327420
coef_cars34_asc_county-0.237200-0.260727
coef_cars34_asc_san_francisco-180.6108020.055894
coef_cars34_density_0_10_no_workers-0.377292-0.342857
coef_cars34_density_10_up_no_workers-0.211272-0.255253
coef_cars34_persons_16_17-1.955221-1.816227
coef_cars34_persons_18_24-0.988280-1.014724
coef_cars34_persons_25_34-0.914993-0.745197
coef_cars34_presence_children_5_170.4654180.541541
coef_cars3_asc185.820626-3.427743
coef_cars3_auto_time_saving_per_worker0.0094180.538213
coef_cars3_drivers_22.3528283.329318
coef_cars3_drivers_35.0484885.702014
coef_cars3_drivers_4_up8.3179508.643466
coef_cars3_hh_income_0_30k0.0519870.064430
coef_cars3_hh_income_30_up0.0047160.009129
coef_cars3_num_workers_clip_30.3741280.650136
coef_cars4_asc-375.140428-5.526492
coef_cars4_auto_time_saving_per_worker-0.1472990.834093
coef_cars4_drivers_2561.0150572.649806
coef_cars4_drivers_3564.4901585.329905
coef_cars4_drivers_4_up568.2725149.423154
coef_cars4_hh_income_0_30k0.0358320.071838
coef_cars4_hh_income_30_up0.0130760.013164
coef_cars4_num_workers_clip_30.6996560.948575
coef_retail_auto_no_workers-0.6377040.039844
coef_retail_auto_workers-0.5311120.155792
coef_retail_non_motor
coef_retail_transit_no_workers-0.333447-0.307701
coef_retail_transit_workers-0.464382-0.524658
tolerance4.356665489100602e-06
steps
array([1. , 1. , 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,\n",
-       "       0.5, 0.5])
message'Optimization terminated successfully.'
elapsed_time0:00:00.484879
method'bhhh'
n_cases2000
iteration_number15
logloss0.866220904773401
" - ], - "text/plain": [ - "┣ loglike: -1732.441809546802\n", - "┣ x: coef_cars1_asc 4.744711\n", - "┃ coef_cars1_asc_county -0.566000\n", - "┃ coef_cars1_asc_marin -0.243396\n", - "┃ coef_cars1_asc_san_francisco 3.984111\n", - "┃ coef_cars1_auto_time_saving_per_worker -0.039384\n", - "┃ ... \n", - "┃ coef_retail_auto_no_workers -0.637704\n", - "┃ coef_retail_auto_workers -0.531112\n", - "┃ coef_retail_non_motor -0.030000\n", - "┃ coef_retail_transit_no_workers -0.333447\n", - "┃ coef_retail_transit_workers -0.464382\n", - "┃ Length: 66, dtype: float64\n", - "┣ tolerance: 4.356665489100602e-06\n", - "┣ steps: array([1. , 1. , 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,\n", - "┃ 0.5, 0.5])\n", - "┣ message: 'Optimization terminated successfully.'\n", - "┣ elapsed_time: datetime.timedelta(microseconds=484879)\n", - "┣ method: 'bhhh'\n", - "┣ n_cases: 2000\n", - "┣ iteration_number: 15\n", - "┣ logloss: 0.866220904773401" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.estimate()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Estimated coefficients" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
coef_cars1_asc 4.74 2.66 1.78 NA 0.00
coef_cars1_asc_county-0.566 NA NA[] 0.00 0.00
coef_cars1_asc_marin-0.243 0.0141-17.28*** NA 0.00
coef_cars1_asc_san_francisco 3.98 2.66 1.50 NA 0.00
coef_cars1_auto_time_saving_per_worker-0.0394 0.561-0.07 NA 0.00
coef_cars1_density_0_10_no_workers 0.00 NA NA NA 0.00fixed value
coef_cars1_density_10_up_no_workers-0.00693 0.00514-1.35 NA 0.00
coef_cars1_density_10_up_workers-0.0164 0.00390-4.21*** NA 0.00
coef_cars1_drivers_2 0.00 NA NA NA 0.00fixed value
coef_cars1_drivers_3 0.00 NA NA NA 0.00fixed value
coef_cars1_drivers_4_up 2.05 0.504 4.06*** NA 0.00
coef_cars1_hh_income_0_30k 0.0286 0.00628 4.55*** NA 0.00
coef_cars1_hh_income_30_up 0.00 NA NA NA 0.00fixed value
coef_cars1_num_workers_clip_3 0.00 NA NA NA 0.00fixed value
coef_cars1_persons_16_17 0.00 NA NA NA 0.00fixed value
coef_cars1_persons_18_24-0.448 0.125-3.59*** NA 0.00
coef_cars1_persons_25_34 0.00 NA NA NA 0.00fixed value
coef_cars1_presence_children_0_4 0.486 0.262 1.85 NA 0.00
coef_cars1_presence_children_5_17-0.234 0.196-1.19 NA 0.00
coef_cars234_asc_marin 0.00 NA NA NA 0.00fixed value
coef_cars234_presence_children_0_4 0.590 0.323 1.83 NA 0.00
coef_cars2_asc 2.47 2.66 0.93 NA 0.00
coef_cars2_asc_county-0.443 0.000441-BIG*** NA 0.00
coef_cars2_asc_san_francisco 4.02 2.66 1.51 NA 0.00
coef_cars2_auto_time_saving_per_worker 0.0106 0.709 0.01 NA 0.00
coef_cars2_density_0_10_no_workers-0.189 0.0342-5.54*** NA 0.00
coef_cars2_density_10_up_no_workers-0.121 0.0176-6.87*** NA 0.00
coef_cars2_drivers_2 2.95 0.265 11.12*** NA 0.00
coef_cars2_drivers_3 3.60 0.354 10.14*** NA 0.00
coef_cars2_drivers_4_up 6.86 0.647 10.60*** NA 0.00
coef_cars2_hh_income_0_30k 0.0623 0.0149 4.17*** NA 0.00
coef_cars2_hh_income_30_up 0.00729 0.00256 2.85** NA 0.00
coef_cars2_num_workers_clip_3-0.0283 0.144-0.20 NA 0.00
coef_cars2_persons_16_17-1.44 0.381-3.78*** NA 0.00
coef_cars2_persons_18_24-0.943 0.176-5.36*** NA 0.00
coef_cars2_persons_25_34-0.472 0.0988-4.78*** NA 0.00
coef_cars2_presence_children_5_17 0.165 0.260 0.63 NA 0.00
coef_cars34_asc_county-0.237 8.28e-05-BIG*** NA 0.00
coef_cars34_asc_san_francisco-181. NA NA[***] BIG 0.00
coef_cars34_density_0_10_no_workers-0.377 0.0616-6.12*** NA 0.00
coef_cars34_density_10_up_no_workers-0.211 0.0736-2.87** NA 0.00
coef_cars34_persons_16_17-1.96 0.507-3.86*** NA 0.00
coef_cars34_persons_18_24-0.988 0.215-4.61*** NA 0.00
coef_cars34_persons_25_34-0.915 0.168-5.46*** NA 0.00
coef_cars34_presence_children_5_17 0.465 0.364 1.28 NA 0.00
coef_cars3_asc 186. NA NA[***] BIG 0.00
coef_cars3_auto_time_saving_per_worker 0.00942 1.06 0.01 NA 0.00
coef_cars3_drivers_2 2.35 0.790 2.98** NA 0.00
coef_cars3_drivers_3 5.05 0.811 6.23*** NA 0.00
coef_cars3_drivers_4_up 8.32 1.01 8.25*** NA 0.00
coef_cars3_hh_income_0_30k 0.0520 0.0286 1.82 NA 0.00
coef_cars3_hh_income_30_up 0.00472 0.00485 0.97 NA 0.00
coef_cars3_num_workers_clip_3 0.374 0.234 1.60 NA 0.00
coef_cars4_asc-375. 2.15e+03-0.17 NA 0.00
coef_cars4_auto_time_saving_per_worker-0.147 1.49-0.10 NA 0.00
coef_cars4_drivers_2 561. 2.30e+03 0.24 NA 0.00
coef_cars4_drivers_3 564. 2.30e+03 0.25 NA 0.00
coef_cars4_drivers_4_up 568. 2.30e+03 0.25 NA 0.00
coef_cars4_hh_income_0_30k 0.0358 0.0460 0.78 NA 0.00
coef_cars4_hh_income_30_up 0.0131 0.00635 2.06* NA 0.00
coef_cars4_num_workers_clip_3 0.700 0.321 2.18* NA 0.00
coef_retail_auto_no_workers-0.638 0.595-1.07 NA 0.00
coef_retail_auto_workers-0.531 0.589-0.90 NA 0.00
coef_retail_non_motor-0.0300 NA NA NA 0.00fixed value
coef_retail_transit_no_workers-0.333 0.193-1.73 NA 0.00
coef_retail_transit_workers-0.464 0.162-2.86** NA 0.00
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.parameter_summary()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "colab_type": "text", - "id": "TojXWivZsx7M" - }, - "source": [ - "# Output Estimation Results" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "from activitysim.estimation.larch import update_coefficients\n", - "result_dir = data.edb_directory/\"estimated\"\n", - "update_coefficients(\n", - " model, data, result_dir,\n", - " output_file=f\"{modelname}_coefficients_revised.csv\",\n", - ");" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, + "
logloss0.924274751334728d_logloss\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
0
coef_cars1_asc5.272591e-05
coef_cars1_asc_county-8.675234e-06
coef_cars1_asc_marin-6.400057e-05
coef_cars1_asc_san_francisco-1.587832e-04
coef_cars1_auto_time_saving_per_worker1.403290e-04
coef_cars1_density_0_10_no_workers0.000000e+00
coef_cars1_density_10_up_no_workers6.620783e-06
coef_cars1_density_10_up_workers-2.503582e-06
coef_cars1_drivers_20.000000e+00
coef_cars1_drivers_30.000000e+00
coef_cars1_drivers_4_up-7.541270e-05
coef_cars1_hh_income_0_30k1.049198e-05
coef_cars1_hh_income_30_up0.000000e+00
coef_cars1_num_workers_clip_30.000000e+00
coef_cars1_persons_16_170.000000e+00
coef_cars1_persons_18_241.878411e-05
coef_cars1_persons_25_340.000000e+00
coef_cars1_presence_children_0_4-2.694541e-05
coef_cars1_presence_children_5_171.274960e-04
coef_cars234_asc_marin0.000000e+00
coef_cars234_presence_children_0_4-3.830304e-05
coef_cars2_asc-1.829182e-05
coef_cars2_asc_county-3.904999e-05
coef_cars2_asc_san_francisco1.268645e-04
coef_cars2_auto_time_saving_per_worker-3.296868e-05
coef_cars2_density_0_10_no_workers-4.356619e-06
coef_cars2_density_10_up_no_workers-1.094392e-05
coef_cars2_drivers_2-4.226757e-05
coef_cars2_drivers_36.818523e-05
coef_cars2_drivers_4_up3.745028e-05
coef_cars2_hh_income_0_30k3.076831e-05
coef_cars2_hh_income_30_up4.120039e-07
coef_cars2_num_workers_clip_3-9.781070e-05
coef_cars2_persons_16_171.620926e-04
coef_cars2_persons_18_24-1.615064e-04
coef_cars2_persons_25_34-1.420584e-05
coef_cars2_presence_children_5_176.079833e-05
coef_cars34_asc_county2.795941e-05
coef_cars34_asc_san_francisco2.027922e-05
coef_cars34_density_0_10_no_workers5.432376e-06
coef_cars34_density_10_up_no_workers4.880993e-05
coef_cars34_persons_16_17-1.804202e-04
coef_cars34_persons_18_247.896584e-05
coef_cars34_persons_25_34-3.944173e-06
coef_cars34_presence_children_5_17-2.364296e-04
coef_cars3_asc4.510100e-05
coef_cars3_auto_time_saving_per_worker-6.354019e-05
coef_cars3_drivers_21.322705e-04
coef_cars3_drivers_37.346112e-05
coef_cars3_drivers_4_up-1.013529e-04
coef_cars3_hh_income_0_30k5.005154e-06
coef_cars3_hh_income_30_up-1.522397e-05
coef_cars3_num_workers_clip_3-2.420821e-04
coef_cars4_asc-4.863863e-05
coef_cars4_auto_time_saving_per_worker-3.102682e-05
coef_cars4_drivers_21.784363e-05
coef_cars4_drivers_32.136643e-05
coef_cars4_drivers_4_up1.397419e-06
coef_cars4_hh_income_0_30k7.719776e-07
coef_cars4_hh_income_30_up-1.121368e-05
coef_cars4_num_workers_clip_3-7.913124e-05
coef_retail_auto_no_workers1.803616e-05
coef_retail_auto_workers-1.355341e-06
coef_retail_non_motor0.000000e+00
coef_retail_transit_no_workers-6.122156e-05
coef_retail_transit_workers-7.132030e-06
nit67nfev84njev67status0message'Optimization terminated successfully'successTrueelapsed_time0:00:01.497985method'slsqp'n_cases20000iteration_number67loglike-18485.49502669456
" + ], + "text/plain": [ + "┣ x: coef_cars1_asc 1.337433\n", + "┃ coef_cars1_asc_county -0.655949\n", + "┃ coef_cars1_asc_marin -0.168475\n", + "┃ coef_cars1_asc_san_francisco 0.324519\n", + "┃ coef_cars1_auto_time_saving_per_worker 0.394451\n", + "┃ ... \n", + "┃ coef_retail_auto_no_workers 0.039844\n", + "┃ coef_retail_auto_workers 0.155792\n", + "┃ coef_retail_non_motor -0.030000\n", + "┃ coef_retail_transit_no_workers -0.307701\n", + "┃ coef_retail_transit_workers -0.524658\n", + "┃ Length: 66, dtype: float64\n", + "┣ logloss: 0.924274751334728\n", + "┣ d_logloss: coef_cars1_asc 0.000053\n", + "┃ coef_cars1_asc_county -0.000009\n", + "┃ coef_cars1_asc_marin -0.000064\n", + "┃ coef_cars1_asc_san_francisco -0.000159\n", + "┃ coef_cars1_auto_time_saving_per_worker 0.000140\n", + "┃ ... \n", + "┃ coef_retail_auto_no_workers 0.000018\n", + "┃ coef_retail_auto_workers -0.000001\n", + "┃ coef_retail_non_motor 0.000000\n", + "┃ coef_retail_transit_no_workers -0.000061\n", + "┃ coef_retail_transit_workers -0.000007\n", + "┃ Length: 66, dtype: float64\n", + "┣ nit: 67\n", + "┣ nfev: 84\n", + "┣ njev: 67\n", + "┣ status: 0\n", + "┣ message: 'Optimization terminated successfully'\n", + "┣ success: True\n", + "┣ elapsed_time: datetime.timedelta(seconds=1, microseconds=497985)\n", + "┣ method: 'slsqp'\n", + "┣ n_cases: 20000\n", + "┣ iteration_number: 67\n", + "┣ loglike: -18485.49502669456" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "### Write the model estimation report, including coefficient t-statistic and log likelihood" + "model.estimate()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Estimated coefficients" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_cars1_asc 1.34 0.941 1.42 0.00
coef_cars1_asc_county-0.656 0.158-4.14*** 0.00
coef_cars1_asc_marin-0.168 0.106-1.58 0.00
coef_cars1_asc_san_francisco 0.325 0.0979 3.31*** 0.00
coef_cars1_auto_time_saving_per_worker 0.394 0.188 2.10* 0.00
coef_cars1_density_0_10_no_workers 0.00 0.00 NA 0.00fixed value
coef_cars1_density_10_up_no_workers-0.0145 0.00339-4.27*** 0.00
coef_cars1_density_10_up_workers-0.0183 0.00271-6.75*** 0.00
coef_cars1_drivers_2 0.00 0.00 NA 0.00fixed value
coef_cars1_drivers_3 0.00 0.00 NA 0.00fixed value
coef_cars1_drivers_4_up 2.01 0.317 6.35*** 0.00
coef_cars1_hh_income_0_30k 0.0456 0.00298 15.29*** 0.00
coef_cars1_hh_income_30_up 0.00 0.00 NA 0.00fixed value
coef_cars1_num_workers_clip_3 0.00 0.00 NA 0.00fixed value
coef_cars1_persons_16_17 0.00 0.00 NA 0.00fixed value
coef_cars1_persons_18_24-0.476 0.0586-8.11*** 0.00
coef_cars1_persons_25_34 0.00 0.00 NA 0.00fixed value
coef_cars1_presence_children_0_4 0.487 0.130 3.75*** 0.00
coef_cars1_presence_children_5_17 0.0390 0.0934 0.42 0.00
coef_cars234_asc_marin 0.00 0.00 NA 0.00fixed value
coef_cars234_presence_children_0_4 0.834 0.137 6.10*** 0.00
coef_cars2_asc-0.817 0.944-0.87 0.00
coef_cars2_asc_county-0.534 0.166-3.22** 0.00
coef_cars2_asc_san_francisco 0.395 0.123 3.22** 0.00
coef_cars2_auto_time_saving_per_worker 0.626 0.197 3.18** 0.00
coef_cars2_density_0_10_no_workers-0.189 0.0118-16.03*** 0.00
coef_cars2_density_10_up_no_workers-0.119 0.0117-10.12*** 0.00
coef_cars2_drivers_2 2.88 0.0602 47.87*** 0.00
coef_cars2_drivers_3 3.46 0.0971 35.68*** 0.00
coef_cars2_drivers_4_up 6.18 0.332 18.61*** 0.00
coef_cars2_hh_income_0_30k 0.0557 0.00419 13.31*** 0.00
coef_cars2_hh_income_30_up 0.00709 0.000782 9.07*** 0.00
coef_cars2_num_workers_clip_3 0.317 0.0420 7.55*** 0.00
coef_cars2_persons_16_17-0.845 0.0976-8.66*** 0.00
coef_cars2_persons_18_24-0.990 0.0659-15.04*** 0.00
coef_cars2_persons_25_34-0.379 0.0322-11.77*** 0.00
coef_cars2_presence_children_5_17 0.327 0.104 3.16** 0.00
coef_cars34_asc_county-0.261 0.173-1.50 0.00
coef_cars34_asc_san_francisco 0.0559 0.161 0.35 0.00
coef_cars34_density_0_10_no_workers-0.343 0.0182-18.81*** 0.00
coef_cars34_density_10_up_no_workers-0.255 0.0544-4.69*** 0.00
coef_cars34_persons_16_17-1.82 0.113-16.13*** 0.00
coef_cars34_persons_18_24-1.01 0.0695-14.60*** 0.00
coef_cars34_persons_25_34-0.745 0.0402-18.56*** 0.00
coef_cars34_presence_children_5_17 0.542 0.112 4.83*** 0.00
coef_cars3_asc-3.43 0.962-3.56*** 0.00
coef_cars3_auto_time_saving_per_worker 0.538 0.215 2.50* 0.00
coef_cars3_drivers_2 3.33 0.151 21.99*** 0.00
coef_cars3_drivers_3 5.70 0.170 33.48*** 0.00
coef_cars3_drivers_4_up 8.64 0.364 23.72*** 0.00
coef_cars3_hh_income_0_30k 0.0644 0.00668 9.65*** 0.00
coef_cars3_hh_income_30_up 0.00913 0.00103 8.88*** 0.00
coef_cars3_num_workers_clip_3 0.650 0.0519 12.53*** 0.00
coef_cars4_asc-5.53 1.02-5.42*** 0.00
coef_cars4_auto_time_saving_per_worker 0.834 0.249 3.35*** 0.00
coef_cars4_drivers_2 2.65 0.287 9.23*** 0.00
coef_cars4_drivers_3 5.33 0.297 17.95*** 0.00
coef_cars4_drivers_4_up 9.42 0.436 21.59*** 0.00
coef_cars4_hh_income_0_30k 0.0718 0.0111 6.46*** 0.00
coef_cars4_hh_income_30_up 0.0132 0.00132 10.00*** 0.00
coef_cars4_num_workers_clip_3 0.949 0.0646 14.69*** 0.00
coef_retail_auto_no_workers 0.0398 0.101 0.39 0.00
coef_retail_auto_workers 0.156 0.102 1.52 0.00
coef_retail_non_motor-0.0300 0.00 NA 0.00fixed value
coef_retail_transit_no_workers-0.308 0.0295-10.44*** 0.00
coef_retail_transit_workers-0.525 0.0396-13.24*** 0.00
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.parameter_summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "TojXWivZsx7M" + }, + "source": [ + "# Output Estimation Results" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "from activitysim.estimation.larch import update_coefficients\n", + "result_dir = data.edb_directory/\"estimated\"\n", + "update_coefficients(\n", + " model, data, result_dir,\n", + " output_file=f\"{modelname}_coefficients_revised.csv\",\n", + ");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Write the model estimation report, including coefficient t-statistic and log likelihood" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "model.to_xlsx(\n", + " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", + " data_statistics=False,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Next Steps\n", + "\n", + "The final step is to either manually or automatically copy the `*_coefficients_revised.csv` file to the configs folder, rename it to `*_coefficients.csv`, and run ActivitySim in simulation mode." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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coefficient_namevalueconstrain
0coef_cars1_drivers_20.000000T
1coef_cars1_drivers_30.000000T
2coef_cars1_persons_16_170.000000T
3coef_cars234_asc_marin0.000000T
4coef_cars1_persons_25_340.000000T
............
62coef_cars4_drivers_35.329905F
63coef_cars3_drivers_35.702014F
64coef_cars2_drivers_4_up6.182053F
65coef_cars3_drivers_4_up8.643466F
66coef_cars4_drivers_4_up9.423154F
\n", + "

67 rows × 3 columns

\n", + "
" + ], + "text/plain": [ + " coefficient_name value constrain\n", + "0 coef_cars1_drivers_2 0.000000 T\n", + "1 coef_cars1_drivers_3 0.000000 T\n", + "2 coef_cars1_persons_16_17 0.000000 T\n", + "3 coef_cars234_asc_marin 0.000000 T\n", + "4 coef_cars1_persons_25_34 0.000000 T\n", + ".. ... ... ...\n", + "62 coef_cars4_drivers_3 5.329905 F\n", + "63 coef_cars3_drivers_3 5.702014 F\n", + "64 coef_cars2_drivers_4_up 6.182053 F\n", + "65 coef_cars3_drivers_4_up 8.643466 F\n", + "66 coef_cars4_drivers_4_up 9.423154 F\n", + "\n", + "[67 rows x 3 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pd.read_csv(result_dir/f\"{modelname}_coefficients_revised.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Modify Spec\n", + "\n", + "Here, we will demonstrate the process of re-estimating the model with a modified\n", + "SPEC file. This does *not* require re-running ActivitySim, it just requires\n", + "changing the SPEC file and re-running the Larch estimation only.\n", + "\n", + "The `backup` command we ran earlier made a backup copy of the\n", + "original spec file in the EDB directory.\n", + "This was not strictly necessary, but since we're about to modify it and\n", + "we may want undo our changes, it can be handy to keep a copy of the\n", + "original spec file around. Since we already have a backup copy, we'll make some \n", + "changes directly in the SPEC file. As an example here, we're going\n", + "to re-write the household income section of the file, to change the piecewise \n", + "linear utility from 3 segments to 4. We'll move the breakpoints and rename some\n", + "coefficients to accomodate the change. As above, for this demo we are editing \n", + "the SPEC file using Python code to make the changes, but a user does not need\n", + "to change the file using Python; any CSV editor (e.g. Excel) can be used. " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "with open(data.edb_directory / \"auto_ownership_SPEC.csv\") as f:\n", + " raw_spec = f.read()\n", + "\n", + "orig_lines = \"\"\"util_hh_income_0_30k,\"Piecewise Linear household income, $0-30k\",\"@df.income_in_thousands.clip(0, 30)\",,coef_cars1_hh_income_0_30k,coef_cars2_hh_income_0_30k,coef_cars3_hh_income_0_30k,coef_cars4_hh_income_0_30k\n", + "util_hh_income_30_75k,\"Piecewise Linear household income, $30-75k\",\"@(df.income_in_thousands-30).clip(0, 45)\",,coef_cars1_hh_income_30_up,coef_cars2_hh_income_30_up,coef_cars3_hh_income_30_up,coef_cars4_hh_income_30_up\n", + "util_hh_income_75k_up,\"Piecewise Linear household income, $75k+, capped at $125k\",\"@(df.income_in_thousands-75).clip(0, 50)\",,coef_cars1_hh_income_30_up,coef_cars2_hh_income_30_up,coef_cars3_hh_income_30_up,coef_cars4_hh_income_30_up\"\"\"\n", + "\n", + "repl_lines = \"\"\"util_hh_income_0_25k,\"Piecewise Linear household income, $0-25k\",\"@df.income_in_thousands.clip(0, 25)\",,coef_cars1_hh_income_0_25k,coef_cars2_hh_income_0_25k,coef_cars3_hh_income_0_25k,coef_cars4_hh_income_0_25k\n", + "util_hh_income_25_50k,\"Piecewise Linear household income, $25-50k\",\"@(df.income_in_thousands-25).clip(0, 25)\",,coef_cars1_hh_income_25_50,coef_cars2_hh_income_25_50,coef_cars3_hh_income_25_50,coef_cars4_hh_income_25_50\n", + "util_hh_income_50_75k,\"Piecewise Linear household income, $50-75k\",\"@(df.income_in_thousands-50).clip(0, 25)\",,coef_cars1_hh_income_50_75,coef_cars2_hh_income_50_75,coef_cars3_hh_income_50_75,coef_cars4_hh_income_50_75\n", + "util_hh_income_75k_150k,\"Piecewise Linear household income, $75k+, capped at $150k\",\"@(df.income_in_thousands-75).clip(0, 75)\",,coef_cars1_hh_income_75_up,coef_cars2_hh_income_75_up,coef_cars3_hh_income_75_up,coef_cars4_hh_income_75_up\"\"\"\n", + "\n", + "raw_spec = raw_spec.replace(orig_lines, repl_lines)\n", + "\n", + "with open(data.edb_directory / \"auto_ownership_SPEC.csv\", mode=\"w\") as f:\n", + " f.write(raw_spec)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### WARNING\n", + "\n", + "The re-estimation process will use the variable in the estimation data bundle (EDB) given by the \"Label\" \n", + "column of the SPEC, if a variable with that exact name exists in the EDB. Otherwise, it will attempt to\n", + "re-evaluate the contents of the \"Expression\" column using Sharrow, and the other data in the EDB. Thus,\n", + "the expression must only reference other data that is available explicitly in the EDB; to use \n", + "variables that ActivitySim could access but which have not been written to the EDB, it will be necessary\n", + "to go back to ActivitySim and re-run in estimation mode.\n", + "\n", + "Also, the estimation functions do not inherently know what the \"original\" spec file contained, and rely\n", + "entirely on the presence or absence of an exact match on the \"Label\" column to find pre-evaluated expressions.\n", + "It is imcumbent on the user to ensure that any material changes the Expression column are also reflected\n", + "by a new unique name in the \"Label\" column." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now to re-estimate the model, we just re-run the same steps as the original estimation above." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/auto_ownership/auto_ownership_coefficients.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/auto_ownership/auto_ownership_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/auto_ownership/auto_ownership_values_combined.parquet\n" + ] + } + ], + "source": [ + "model2, data2 = component_model(modelname, edb_directory=data.edb_directory, return_data=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You may notice in the utility functions shown below, all of the unadulterated lines of the \n", + "spec file correlate with utility terms that are simple `X.label` data items, which are \n", + "stored as pre-computed data variables in the EDB. Our modified lines, however, are now\n", + "showing the complete expression that will be freshly evaluated by Larch using Sharrow." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
<larch.DictOfLinearFunction>
altformula
1
<Empty LinearFunction>
2
P.coef_cars1_drivers_2 * X.util_drivers_2
+ P.coef_cars1_drivers_3 * X.util_drivers_3
+ P.coef_cars1_drivers_4_up * X.util_drivers_4_up
+ P.coef_cars1_persons_16_17 * X.util_persons_16_17
+ P.coef_cars1_persons_18_24 * X.util_persons_18_24
+ P.coef_cars1_persons_25_34 * X.util_persons_25_34
+ P.coef_cars1_presence_children_0_4 * X.util_presence_children_0_4
+ P.coef_cars1_presence_children_5_17 * X.util_presence_children_5_17
+ P.coef_cars1_num_workers_clip_3 * X.util_num_workers_clip_3
+ P.coef_cars1_hh_income_0_25k * X('df.income_in_thousands.clip(0, 25)')
+ P.coef_cars1_hh_income_25_50 * X('(df.income_in_thousands-25).clip(0, 25)')
+ P.coef_cars1_hh_income_50_75 * X('(df.income_in_thousands-50).clip(0, 25)')
+ P.coef_cars1_hh_income_75_up * X('(df.income_in_thousands-75).clip(0, 75)')
+ P.coef_cars1_density_0_10_no_workers * X.util_density_0_10_no_workers
+ P.coef_cars1_density_10_up_no_workers * X.util_density_10_up_no_workers
+ P.coef_cars1_density_0_10_no_workers * X.util_density_0_10_workers
+ P.coef_cars1_density_10_up_workers * X.util_density_10_up_workers
+ P.coef_cars1_asc * X.util_asc
+ P.coef_cars1_asc_san_francisco * X.util_asc_san_francisco
+ P.coef_cars1_asc_county * X.util_asc_solano
+ P.coef_cars1_asc_county * X.util_asc_napa
+ P.coef_cars1_asc_county * X.util_asc_sonoma
+ P.coef_cars1_asc_marin * X.util_asc_marin
+ P.coef_retail_auto_no_workers * X.util_retail_auto_no_workers
+ P.coef_retail_auto_workers * X.util_retail_auto_workers
+ P.coef_retail_transit_no_workers * X.util_retail_transit_no_workers
+ P.coef_retail_transit_workers * X.util_retail_transit_workers
+ P.coef_retail_non_motor * X.util_retail_non_motor_no_workers
+ P.coef_retail_non_motor * X.util_retail_non_motor_workers
+ P.coef_cars1_auto_time_saving_per_worker * X.util_auto_time_saving_per_worker
3
P.coef_cars2_drivers_2 * X.util_drivers_2
+ P.coef_cars2_drivers_3 * X.util_drivers_3
+ P.coef_cars2_drivers_4_up * X.util_drivers_4_up
+ P.coef_cars2_persons_16_17 * X.util_persons_16_17
+ P.coef_cars2_persons_18_24 * X.util_persons_18_24
+ P.coef_cars2_persons_25_34 * X.util_persons_25_34
+ P.coef_cars234_presence_children_0_4 * X.util_presence_children_0_4
+ P.coef_cars2_presence_children_5_17 * X.util_presence_children_5_17
+ P.coef_cars2_num_workers_clip_3 * X.util_num_workers_clip_3
+ P.coef_cars2_hh_income_0_25k * X('df.income_in_thousands.clip(0, 25)')
+ P.coef_cars2_hh_income_25_50 * X('(df.income_in_thousands-25).clip(0, 25)')
+ P.coef_cars2_hh_income_50_75 * X('(df.income_in_thousands-50).clip(0, 25)')
+ P.coef_cars2_hh_income_75_up * X('(df.income_in_thousands-75).clip(0, 75)')
+ P.coef_cars2_density_0_10_no_workers * X.util_density_0_10_no_workers
+ P.coef_cars2_density_10_up_no_workers * X.util_density_10_up_no_workers
+ P.coef_cars2_density_0_10_no_workers * X.util_density_0_10_workers
+ P.coef_cars2_density_10_up_no_workers * X.util_density_10_up_workers
+ P.coef_cars2_asc * X.util_asc
+ P.coef_cars2_asc_san_francisco * X.util_asc_san_francisco
+ P.coef_cars2_asc_county * X.util_asc_solano
+ P.coef_cars2_asc_county * X.util_asc_napa
+ P.coef_cars2_asc_county * X.util_asc_sonoma
+ P.coef_cars234_asc_marin * X.util_asc_marin
+ P.coef_retail_auto_no_workers * X.util_retail_auto_no_workers
+ P.coef_retail_auto_workers * X.util_retail_auto_workers
+ P.coef_retail_transit_no_workers * X.util_retail_transit_no_workers
+ P.coef_retail_transit_workers * X.util_retail_transit_workers
+ P.coef_retail_non_motor * X.util_retail_non_motor_no_workers
+ P.coef_retail_non_motor * X.util_retail_non_motor_workers
+ P.coef_cars2_auto_time_saving_per_worker * X.util_auto_time_saving_per_worker
4
P.coef_cars3_drivers_2 * X.util_drivers_2
+ P.coef_cars3_drivers_3 * X.util_drivers_3
+ P.coef_cars3_drivers_4_up * X.util_drivers_4_up
+ P.coef_cars34_persons_16_17 * X.util_persons_16_17
+ P.coef_cars34_persons_18_24 * X.util_persons_18_24
+ P.coef_cars34_persons_25_34 * X.util_persons_25_34
+ P.coef_cars234_presence_children_0_4 * X.util_presence_children_0_4
+ P.coef_cars34_presence_children_5_17 * X.util_presence_children_5_17
+ P.coef_cars3_num_workers_clip_3 * X.util_num_workers_clip_3
+ P.coef_cars3_hh_income_0_25k * X('df.income_in_thousands.clip(0, 25)')
+ P.coef_cars3_hh_income_25_50 * X('(df.income_in_thousands-25).clip(0, 25)')
+ P.coef_cars3_hh_income_50_75 * X('(df.income_in_thousands-50).clip(0, 25)')
+ P.coef_cars3_hh_income_75_up * X('(df.income_in_thousands-75).clip(0, 75)')
+ P.coef_cars34_density_0_10_no_workers * X.util_density_0_10_no_workers
+ P.coef_cars34_density_10_up_no_workers * X.util_density_10_up_no_workers
+ P.coef_cars34_density_0_10_no_workers * X.util_density_0_10_workers
+ P.coef_cars34_density_10_up_no_workers * X.util_density_10_up_workers
+ P.coef_cars3_asc * X.util_asc
+ P.coef_cars34_asc_san_francisco * X.util_asc_san_francisco
+ P.coef_cars34_asc_county * X.util_asc_solano
+ P.coef_cars34_asc_county * X.util_asc_napa
+ P.coef_cars34_asc_county * X.util_asc_sonoma
+ P.coef_cars234_asc_marin * X.util_asc_marin
+ P.coef_retail_auto_no_workers * X.util_retail_auto_no_workers
+ P.coef_retail_auto_workers * X.util_retail_auto_workers
+ P.coef_retail_transit_no_workers * X.util_retail_transit_no_workers
+ P.coef_retail_transit_workers * X.util_retail_transit_workers
+ P.coef_retail_non_motor * X.util_retail_non_motor_no_workers
+ P.coef_retail_non_motor * X.util_retail_non_motor_workers
+ P.coef_cars3_auto_time_saving_per_worker * X.util_auto_time_saving_per_worker
5
P.coef_cars4_drivers_2 * X.util_drivers_2
+ P.coef_cars4_drivers_3 * X.util_drivers_3
+ P.coef_cars4_drivers_4_up * X.util_drivers_4_up
+ P.coef_cars34_persons_16_17 * X.util_persons_16_17
+ P.coef_cars34_persons_18_24 * X.util_persons_18_24
+ P.coef_cars34_persons_25_34 * X.util_persons_25_34
+ P.coef_cars234_presence_children_0_4 * X.util_presence_children_0_4
+ P.coef_cars34_presence_children_5_17 * X.util_presence_children_5_17
+ P.coef_cars4_num_workers_clip_3 * X.util_num_workers_clip_3
+ P.coef_cars4_hh_income_0_25k * X('df.income_in_thousands.clip(0, 25)')
+ P.coef_cars4_hh_income_25_50 * X('(df.income_in_thousands-25).clip(0, 25)')
+ P.coef_cars4_hh_income_50_75 * X('(df.income_in_thousands-50).clip(0, 25)')
+ P.coef_cars4_hh_income_75_up * X('(df.income_in_thousands-75).clip(0, 75)')
+ P.coef_cars34_density_0_10_no_workers * X.util_density_0_10_no_workers
+ P.coef_cars34_density_10_up_no_workers * X.util_density_10_up_no_workers
+ P.coef_cars34_density_0_10_no_workers * X.util_density_0_10_workers
+ P.coef_cars34_density_10_up_no_workers * X.util_density_10_up_workers
+ P.coef_cars4_asc * X.util_asc
+ P.coef_cars34_asc_san_francisco * X.util_asc_san_francisco
+ P.coef_cars34_asc_county * X.util_asc_solano
+ P.coef_cars34_asc_county * X.util_asc_napa
+ P.coef_cars34_asc_county * X.util_asc_sonoma
+ P.coef_cars234_asc_marin * X.util_asc_marin
+ P.coef_retail_auto_no_workers * X.util_retail_auto_no_workers
+ P.coef_retail_auto_workers * X.util_retail_auto_workers
+ P.coef_retail_transit_no_workers * X.util_retail_transit_no_workers
+ P.coef_retail_transit_workers * X.util_retail_transit_workers
+ P.coef_retail_non_motor * X.util_retail_non_motor_no_workers
+ P.coef_retail_non_motor * X.util_retail_non_motor_workers
+ P.coef_cars4_auto_time_saving_per_worker * X.util_auto_time_saving_per_worker
" + ], + "text/plain": [ + "DictOfLinearFunction({1: , 2: P.coef_cars1_drivers_2 * X.util_drivers_2\n", + "+ P.coef_cars1_drivers_3 * X.util_drivers_3\n", + "+ P.coef_cars1_drivers_4_up * X.util_drivers_4_up\n", + "+ P.coef_cars1_persons_16_17 * X.util_persons_16_17\n", + "+ P.coef_cars1_persons_18_24 * X.util_persons_18_24\n", + "+ P.coef_cars1_persons_25_34 * X.util_persons_25_34\n", + "+ P.coef_cars1_presence_children_0_4 * X.util_presence_children_0_4\n", + "+ P.coef_cars1_presence_children_5_17 * X.util_presence_children_5_17\n", + "+ P.coef_cars1_num_workers_clip_3 * X.util_num_workers_clip_3\n", + "+ P.coef_cars1_hh_income_0_25k * X('df.income_in_thousands.clip(0, 25)')\n", + "+ P.coef_cars1_hh_income_25_50 * X('(df.income_in_thousands-25).clip(0, 25)')\n", + "+ P.coef_cars1_hh_income_50_75 * X('(df.income_in_thousands-50).clip(0, 25)')\n", + "+ P.coef_cars1_hh_income_75_up * X('(df.income_in_thousands-75).clip(0, 75)')\n", + "+ P.coef_cars1_density_0_10_no_workers * X.util_density_0_10_no_workers\n", + "+ P.coef_cars1_density_10_up_no_workers * X.util_density_10_up_no_workers\n", + "+ P.coef_cars1_density_0_10_no_workers * X.util_density_0_10_workers\n", + "+ P.coef_cars1_density_10_up_workers * X.util_density_10_up_workers\n", + "+ P.coef_cars1_asc * X.util_asc\n", + "+ P.coef_cars1_asc_san_francisco * X.util_asc_san_francisco\n", + "+ P.coef_cars1_asc_county * X.util_asc_solano\n", + "+ P.coef_cars1_asc_county * X.util_asc_napa\n", + "+ P.coef_cars1_asc_county * X.util_asc_sonoma\n", + "+ P.coef_cars1_asc_marin * X.util_asc_marin\n", + "+ P.coef_retail_auto_no_workers * X.util_retail_auto_no_workers\n", + "+ P.coef_retail_auto_workers * X.util_retail_auto_workers\n", + "+ P.coef_retail_transit_no_workers * X.util_retail_transit_no_workers\n", + "+ P.coef_retail_transit_workers * X.util_retail_transit_workers\n", + "+ P.coef_retail_non_motor * X.util_retail_non_motor_no_workers\n", + "+ P.coef_retail_non_motor * X.util_retail_non_motor_workers\n", + "+ P.coef_cars1_auto_time_saving_per_worker * X.util_auto_time_saving_per_worker, 3: P.coef_cars2_drivers_2 * X.util_drivers_2\n", + "+ P.coef_cars2_drivers_3 * X.util_drivers_3\n", + "+ P.coef_cars2_drivers_4_up * X.util_drivers_4_up\n", + "+ P.coef_cars2_persons_16_17 * X.util_persons_16_17\n", + "+ P.coef_cars2_persons_18_24 * X.util_persons_18_24\n", + "+ P.coef_cars2_persons_25_34 * X.util_persons_25_34\n", + "+ P.coef_cars234_presence_children_0_4 * X.util_presence_children_0_4\n", + "+ P.coef_cars2_presence_children_5_17 * X.util_presence_children_5_17\n", + "+ P.coef_cars2_num_workers_clip_3 * X.util_num_workers_clip_3\n", + "+ P.coef_cars2_hh_income_0_25k * X('df.income_in_thousands.clip(0, 25)')\n", + "+ P.coef_cars2_hh_income_25_50 * X('(df.income_in_thousands-25).clip(0, 25)')\n", + "+ P.coef_cars2_hh_income_50_75 * X('(df.income_in_thousands-50).clip(0, 25)')\n", + "+ P.coef_cars2_hh_income_75_up * X('(df.income_in_thousands-75).clip(0, 75)')\n", + "+ P.coef_cars2_density_0_10_no_workers * X.util_density_0_10_no_workers\n", + "+ P.coef_cars2_density_10_up_no_workers * X.util_density_10_up_no_workers\n", + "+ P.coef_cars2_density_0_10_no_workers * X.util_density_0_10_workers\n", + "+ P.coef_cars2_density_10_up_no_workers * X.util_density_10_up_workers\n", + "+ P.coef_cars2_asc * X.util_asc\n", + "+ P.coef_cars2_asc_san_francisco * X.util_asc_san_francisco\n", + "+ P.coef_cars2_asc_county * X.util_asc_solano\n", + "+ P.coef_cars2_asc_county * X.util_asc_napa\n", + "+ P.coef_cars2_asc_county * X.util_asc_sonoma\n", + "+ P.coef_cars234_asc_marin * X.util_asc_marin\n", + "+ P.coef_retail_auto_no_workers * X.util_retail_auto_no_workers\n", + "+ P.coef_retail_auto_workers * X.util_retail_auto_workers\n", + "+ P.coef_retail_transit_no_workers * X.util_retail_transit_no_workers\n", + "+ P.coef_retail_transit_workers * X.util_retail_transit_workers\n", + "+ P.coef_retail_non_motor * X.util_retail_non_motor_no_workers\n", + "+ P.coef_retail_non_motor * X.util_retail_non_motor_workers\n", + "+ P.coef_cars2_auto_time_saving_per_worker * X.util_auto_time_saving_per_worker, 4: P.coef_cars3_drivers_2 * X.util_drivers_2\n", + "+ P.coef_cars3_drivers_3 * X.util_drivers_3\n", + "+ P.coef_cars3_drivers_4_up * X.util_drivers_4_up\n", + "+ P.coef_cars34_persons_16_17 * X.util_persons_16_17\n", + "+ P.coef_cars34_persons_18_24 * X.util_persons_18_24\n", + "+ P.coef_cars34_persons_25_34 * X.util_persons_25_34\n", + "+ P.coef_cars234_presence_children_0_4 * X.util_presence_children_0_4\n", + "+ P.coef_cars34_presence_children_5_17 * X.util_presence_children_5_17\n", + "+ P.coef_cars3_num_workers_clip_3 * X.util_num_workers_clip_3\n", + "+ P.coef_cars3_hh_income_0_25k * X('df.income_in_thousands.clip(0, 25)')\n", + "+ P.coef_cars3_hh_income_25_50 * X('(df.income_in_thousands-25).clip(0, 25)')\n", + "+ P.coef_cars3_hh_income_50_75 * X('(df.income_in_thousands-50).clip(0, 25)')\n", + "+ P.coef_cars3_hh_income_75_up * X('(df.income_in_thousands-75).clip(0, 75)')\n", + "+ P.coef_cars34_density_0_10_no_workers * X.util_density_0_10_no_workers\n", + "+ P.coef_cars34_density_10_up_no_workers * X.util_density_10_up_no_workers\n", + "+ P.coef_cars34_density_0_10_no_workers * X.util_density_0_10_workers\n", + "+ P.coef_cars34_density_10_up_no_workers * X.util_density_10_up_workers\n", + "+ P.coef_cars3_asc * X.util_asc\n", + "+ P.coef_cars34_asc_san_francisco * X.util_asc_san_francisco\n", + "+ P.coef_cars34_asc_county * X.util_asc_solano\n", + "+ P.coef_cars34_asc_county * X.util_asc_napa\n", + "+ P.coef_cars34_asc_county * X.util_asc_sonoma\n", + "+ P.coef_cars234_asc_marin * X.util_asc_marin\n", + "+ P.coef_retail_auto_no_workers * X.util_retail_auto_no_workers\n", + "+ P.coef_retail_auto_workers * X.util_retail_auto_workers\n", + "+ P.coef_retail_transit_no_workers * X.util_retail_transit_no_workers\n", + "+ P.coef_retail_transit_workers * X.util_retail_transit_workers\n", + "+ P.coef_retail_non_motor * X.util_retail_non_motor_no_workers\n", + "+ P.coef_retail_non_motor * X.util_retail_non_motor_workers\n", + "+ P.coef_cars3_auto_time_saving_per_worker * X.util_auto_time_saving_per_worker, 5: P.coef_cars4_drivers_2 * X.util_drivers_2\n", + "+ P.coef_cars4_drivers_3 * X.util_drivers_3\n", + "+ P.coef_cars4_drivers_4_up * X.util_drivers_4_up\n", + "+ P.coef_cars34_persons_16_17 * X.util_persons_16_17\n", + "+ P.coef_cars34_persons_18_24 * X.util_persons_18_24\n", + "+ P.coef_cars34_persons_25_34 * X.util_persons_25_34\n", + "+ P.coef_cars234_presence_children_0_4 * X.util_presence_children_0_4\n", + "+ P.coef_cars34_presence_children_5_17 * X.util_presence_children_5_17\n", + "+ P.coef_cars4_num_workers_clip_3 * X.util_num_workers_clip_3\n", + "+ P.coef_cars4_hh_income_0_25k * X('df.income_in_thousands.clip(0, 25)')\n", + "+ P.coef_cars4_hh_income_25_50 * X('(df.income_in_thousands-25).clip(0, 25)')\n", + "+ P.coef_cars4_hh_income_50_75 * X('(df.income_in_thousands-50).clip(0, 25)')\n", + "+ P.coef_cars4_hh_income_75_up * X('(df.income_in_thousands-75).clip(0, 75)')\n", + "+ P.coef_cars34_density_0_10_no_workers * X.util_density_0_10_no_workers\n", + "+ P.coef_cars34_density_10_up_no_workers * X.util_density_10_up_no_workers\n", + "+ P.coef_cars34_density_0_10_no_workers * X.util_density_0_10_workers\n", + "+ P.coef_cars34_density_10_up_no_workers * X.util_density_10_up_workers\n", + "+ P.coef_cars4_asc * X.util_asc\n", + "+ P.coef_cars34_asc_san_francisco * X.util_asc_san_francisco\n", + "+ P.coef_cars34_asc_county * X.util_asc_solano\n", + "+ P.coef_cars34_asc_county * X.util_asc_napa\n", + "+ P.coef_cars34_asc_county * X.util_asc_sonoma\n", + "+ P.coef_cars234_asc_marin * X.util_asc_marin\n", + "+ P.coef_retail_auto_no_workers * X.util_retail_auto_no_workers\n", + "+ P.coef_retail_auto_workers * X.util_retail_auto_workers\n", + "+ P.coef_retail_transit_no_workers * X.util_retail_transit_no_workers\n", + "+ P.coef_retail_transit_workers * X.util_retail_transit_workers\n", + "+ P.coef_retail_non_motor * X.util_retail_non_motor_no_workers\n", + "+ P.coef_retail_non_motor * X.util_retail_non_motor_workers\n", + "+ P.coef_cars4_auto_time_saving_per_worker * X.util_auto_time_saving_per_worker})" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model2.utility_co" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

Iteration 077 [Optimization terminated successfully]

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

Best LL = -18480.69200834759

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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valuebestinitvalueminimummaximumnullvalueholdfast
param_name
coef_cars1_asc1.4519301.4519301.1865-50.0050.000.00
coef_cars1_asc_county-0.669928-0.669928-0.5660-50.0050.000.00
coef_cars1_asc_marin-0.170886-0.170886-0.2434-50.0050.000.00
coef_cars1_asc_san_francisco0.3172280.3172280.4259-50.0050.000.00
coef_cars1_auto_time_saving_per_worker0.3802890.3802890.4707-50.0050.000.00
........................
coef_retail_auto_no_workers0.0278530.0278530.0626-50.0050.000.00
coef_retail_auto_workers0.1430320.1430320.1646-50.0050.000.00
coef_retail_non_motor-0.030000-0.030000-0.0300-0.03-0.030.01
coef_retail_transit_no_workers-0.307531-0.307531-0.3053-50.0050.000.00
coef_retail_transit_workers-0.522486-0.522486-0.5117-50.0050.000.00
\n", + "

74 rows × 7 columns

\n", + "
" + ], + "text/plain": [ + " value best initvalue \\\n", + "param_name \n", + "coef_cars1_asc 1.451930 1.451930 1.1865 \n", + "coef_cars1_asc_county -0.669928 -0.669928 -0.5660 \n", + "coef_cars1_asc_marin -0.170886 -0.170886 -0.2434 \n", + "coef_cars1_asc_san_francisco 0.317228 0.317228 0.4259 \n", + "coef_cars1_auto_time_saving_per_worker 0.380289 0.380289 0.4707 \n", + "... ... ... ... \n", + "coef_retail_auto_no_workers 0.027853 0.027853 0.0626 \n", + "coef_retail_auto_workers 0.143032 0.143032 0.1646 \n", + "coef_retail_non_motor -0.030000 -0.030000 -0.0300 \n", + "coef_retail_transit_no_workers -0.307531 -0.307531 -0.3053 \n", + "coef_retail_transit_workers -0.522486 -0.522486 -0.5117 \n", + "\n", + " minimum maximum nullvalue holdfast \n", + "param_name \n", + "coef_cars1_asc -50.00 50.00 0.0 0 \n", + "coef_cars1_asc_county -50.00 50.00 0.0 0 \n", + "coef_cars1_asc_marin -50.00 50.00 0.0 0 \n", + "coef_cars1_asc_san_francisco -50.00 50.00 0.0 0 \n", + "coef_cars1_auto_time_saving_per_worker -50.00 50.00 0.0 0 \n", + "... ... ... ... ... \n", + "coef_retail_auto_no_workers -50.00 50.00 0.0 0 \n", + "coef_retail_auto_workers -50.00 50.00 0.0 0 \n", + "coef_retail_non_motor -0.03 -0.03 0.0 1 \n", + "coef_retail_transit_no_workers -50.00 50.00 0.0 0 \n", + "coef_retail_transit_workers -50.00 50.00 0.0 0 \n", + "\n", + "[74 rows x 7 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
keyvalue
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0
coef_cars1_asc1.451930
coef_cars1_asc_county-0.669928
coef_cars1_asc_marin-0.170886
coef_cars1_asc_san_francisco0.317228
coef_cars1_auto_time_saving_per_worker0.380289
coef_cars1_density_0_10_no_workers0.000000
coef_cars1_density_10_up_no_workers-0.014252
coef_cars1_density_10_up_workers-0.018450
coef_cars1_drivers_20.000000
coef_cars1_drivers_30.000000
coef_cars1_drivers_4_up1.993329
coef_cars1_hh_income_0_25k0.047122
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coef_cars1_hh_income_75_up-0.002331
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coef_cars1_persons_16_170.000000
coef_cars1_persons_18_24-0.473008
coef_cars1_persons_25_340.000000
coef_cars1_presence_children_0_40.494212
coef_cars1_presence_children_5_170.044213
coef_cars234_asc_marin0.000000
coef_cars234_presence_children_0_40.839737
coef_cars2_asc-0.751717
coef_cars2_asc_county-0.552884
coef_cars2_asc_san_francisco0.394107
coef_cars2_auto_time_saving_per_worker0.608005
coef_cars2_density_0_10_no_workers-0.190732
coef_cars2_density_10_up_no_workers-0.118593
coef_cars2_drivers_22.883229
coef_cars2_drivers_33.462629
coef_cars2_drivers_4_up6.177691
coef_cars2_hh_income_0_25k0.062963
coef_cars2_hh_income_25_500.007705
coef_cars2_hh_income_50_750.019152
coef_cars2_hh_income_75_up0.002677
coef_cars2_num_workers_clip_30.316577
coef_cars2_persons_16_17-0.851694
coef_cars2_persons_18_24-0.988962
coef_cars2_persons_25_34-0.375153
coef_cars2_presence_children_5_170.333678
coef_cars34_asc_county-0.272462
coef_cars34_asc_san_francisco0.042635
coef_cars34_density_0_10_no_workers-0.343379
coef_cars34_density_10_up_no_workers-0.254388
coef_cars34_persons_16_17-1.828782
coef_cars34_persons_18_24-1.015850
coef_cars34_persons_25_34-0.741201
coef_cars34_presence_children_5_170.545134
coef_cars3_asc-3.502778
coef_cars3_auto_time_saving_per_worker0.528275
coef_cars3_drivers_23.337821
coef_cars3_drivers_35.712040
coef_cars3_drivers_4_up8.649770
coef_cars3_hh_income_0_25k0.081492
coef_cars3_hh_income_25_500.001622
coef_cars3_hh_income_50_750.026796
coef_cars3_hh_income_75_up0.003811
coef_cars3_num_workers_clip_30.651693
coef_cars4_asc-5.633922
coef_cars4_auto_time_saving_per_worker0.825818
coef_cars4_drivers_22.636133
coef_cars4_drivers_35.304881
coef_cars4_drivers_4_up9.400424
coef_cars4_hh_income_0_25k0.095108
coef_cars4_hh_income_25_500.002764
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coef_retail_auto_no_workers0.027853
coef_retail_auto_workers0.143032
coef_retail_non_motor-0.030000
coef_retail_transit_no_workers-0.307531
coef_retail_transit_workers-0.522486
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coef_cars1_asc0.000104
coef_cars1_asc_county-0.000032
coef_cars1_asc_marin-0.000051
coef_cars1_asc_san_francisco-0.000097
coef_cars1_auto_time_saving_per_worker0.000056
coef_cars1_density_0_10_no_workers0.000000
coef_cars1_density_10_up_no_workers-0.000020
coef_cars1_density_10_up_workers0.000007
coef_cars1_drivers_20.000000
coef_cars1_drivers_30.000000
coef_cars1_drivers_4_up-0.000038
coef_cars1_hh_income_0_25k0.000119
coef_cars1_hh_income_25_500.000125
coef_cars1_hh_income_50_750.000092
coef_cars1_hh_income_75_up0.000120
coef_cars1_num_workers_clip_30.000000
coef_cars1_persons_16_170.000000
coef_cars1_persons_18_240.000042
coef_cars1_persons_25_340.000000
coef_cars1_presence_children_0_40.000002
coef_cars1_presence_children_5_170.000109
coef_cars234_asc_marin0.000000
coef_cars234_presence_children_0_4-0.000091
coef_cars2_asc-0.000074
coef_cars2_asc_county0.000006
coef_cars2_asc_san_francisco0.000069
coef_cars2_auto_time_saving_per_worker0.000086
coef_cars2_density_0_10_no_workers0.000073
coef_cars2_density_10_up_no_workers-0.000101
coef_cars2_drivers_2-0.000008
coef_cars2_drivers_30.000049
coef_cars2_drivers_4_up-0.000019
coef_cars2_hh_income_0_25k0.000382
coef_cars2_hh_income_25_500.000289
coef_cars2_hh_income_50_750.000444
coef_cars2_hh_income_75_up0.000750
coef_cars2_num_workers_clip_30.000106
coef_cars2_persons_16_170.000130
coef_cars2_persons_18_24-0.000274
coef_cars2_persons_25_34-0.000109
coef_cars2_presence_children_5_17-0.000037
coef_cars34_asc_county0.000005
coef_cars34_asc_san_francisco0.000055
coef_cars34_density_0_10_no_workers0.000004
coef_cars34_density_10_up_no_workers0.000024
coef_cars34_persons_16_17-0.000129
coef_cars34_persons_18_240.000166
coef_cars34_persons_25_34-0.000067
coef_cars34_presence_children_5_17-0.000139
coef_cars3_asc0.000107
coef_cars3_auto_time_saving_per_worker-0.000071
coef_cars3_drivers_20.000149
coef_cars3_drivers_30.000024
coef_cars3_drivers_4_up-0.000038
coef_cars3_hh_income_0_25k0.000005
coef_cars3_hh_income_25_500.000096
coef_cars3_hh_income_50_750.000072
coef_cars3_hh_income_75_up0.000185
coef_cars3_num_workers_clip_3-0.000169
coef_cars4_asc-0.000103
coef_cars4_auto_time_saving_per_worker-0.000058
coef_cars4_drivers_2-0.000040
coef_cars4_drivers_30.000093
coef_cars4_drivers_4_up-0.000046
coef_cars4_hh_income_0_25k-0.000523
coef_cars4_hh_income_25_50-0.000691
coef_cars4_hh_income_50_75-0.000513
coef_cars4_hh_income_75_up-0.001026
coef_cars4_num_workers_clip_3-0.000170
coef_retail_auto_no_workers0.000014
coef_retail_auto_workers0.000098
coef_retail_non_motor0.000000
coef_retail_transit_no_workers0.000133
coef_retail_transit_workers-0.000083
nit77
nfev102
njev77
status0
message'Optimization terminated successfully'
successTrue
elapsed_time0:00:01.723675
method'slsqp'
n_cases20000
iteration_number77
loglike-18480.69200834759
" + ], + "text/plain": [ + "┣ x: coef_cars1_asc 1.451930\n", + "┃ coef_cars1_asc_county -0.669928\n", + "┃ coef_cars1_asc_marin -0.170886\n", + "┃ coef_cars1_asc_san_francisco 0.317228\n", + "┃ coef_cars1_auto_time_saving_per_worker 0.380289\n", + "┃ ... \n", + "┃ coef_retail_auto_no_workers 0.027853\n", + "┃ coef_retail_auto_workers 0.143032\n", + "┃ coef_retail_non_motor -0.030000\n", + "┃ coef_retail_transit_no_workers -0.307531\n", + "┃ coef_retail_transit_workers -0.522486\n", + "┃ Length: 74, dtype: float64\n", + "┣ logloss: 0.9240346004173794\n", + "┣ d_logloss: coef_cars1_asc 0.000104\n", + "┃ coef_cars1_asc_county -0.000032\n", + "┃ coef_cars1_asc_marin -0.000051\n", + "┃ coef_cars1_asc_san_francisco -0.000097\n", + "┃ coef_cars1_auto_time_saving_per_worker 0.000056\n", + "┃ ... \n", + "┃ coef_retail_auto_no_workers 0.000014\n", + "┃ coef_retail_auto_workers 0.000098\n", + "┃ coef_retail_non_motor 0.000000\n", + "┃ coef_retail_transit_no_workers 0.000133\n", + "┃ coef_retail_transit_workers -0.000083\n", + "┃ Length: 74, dtype: float64\n", + "┣ nit: 77\n", + "┣ nfev: 102\n", + "┣ njev: 77\n", + "┣ status: 0\n", + "┣ message: 'Optimization terminated successfully'\n", + "┣ success: True\n", + "┣ elapsed_time: datetime.timedelta(seconds=1, microseconds=723675)\n", + "┣ method: 'slsqp'\n", + "┣ n_cases: 20000\n", + "┣ iteration_number: 77\n", + "┣ loglike: -18480.69200834759" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model2.estimate(maxiter=200)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can easily review the parameter estimates from the original and\n", + "revised models side by side to see what changed." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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modelmodel2
ValueStd Errt StatSignifNull ValueConstrainedValueStd Errt StatSignifNull ValueConstrained
Parameter
coef_cars1_asc1.340.9411.420.01.450.9461.540.0
coef_cars1_asc_county-0.6560.158-4.14***0.0-0.6700.159-4.22***0.0
coef_cars1_asc_marin-0.1680.106-1.580.0-0.1710.106-1.610.0
coef_cars1_asc_san_francisco0.3250.09793.31***0.00.3170.09823.23**0.0
coef_cars1_auto_time_saving_per_worker0.3940.1882.10*0.00.3800.1892.01*0.0
coef_cars1_density_0_10_no_workers0.000.00NA0.0fixed value0.000.00NA0.0fixed value
coef_cars1_density_10_up_no_workers-0.01450.00339-4.27***0.0-0.01430.00339-4.21***0.0
coef_cars1_density_10_up_workers-0.01830.00271-6.75***0.0-0.01840.00271-6.80***0.0
coef_cars1_drivers_20.000.00NA0.0fixed value0.000.00NA0.0fixed value
coef_cars1_drivers_30.000.00NA0.0fixed value0.000.00NA0.0fixed value
coef_cars1_drivers_4_up2.010.3176.35***0.01.990.3186.27***0.0
coef_cars1_hh_income_0_30k0.04560.0029815.29***0.0
coef_cars1_hh_income_30_up0.000.00NA0.0fixed value
coef_cars1_num_workers_clip_30.000.00NA0.0fixed value0.000.00NA0.0fixed value
coef_cars1_persons_16_170.000.00NA0.0fixed value0.000.00NA0.0fixed value
coef_cars1_persons_18_24-0.4760.0586-8.11***0.0-0.4730.0586-8.07***0.0
coef_cars1_persons_25_340.000.00NA0.0fixed value0.000.00NA0.0fixed value
coef_cars1_presence_children_0_40.4870.1303.75***0.00.4940.1303.80***0.0
coef_cars1_presence_children_5_170.03900.09340.420.00.04420.09350.470.0
coef_cars234_asc_marin0.000.00NA0.0fixed value0.000.00NA0.0fixed value
coef_cars234_presence_children_0_40.8340.1376.10***0.00.8400.1376.13***0.0
coef_cars2_asc-0.8170.944-0.870.0-0.7520.949-0.790.0
coef_cars2_asc_county-0.5340.166-3.22**0.0-0.5530.166-3.33***0.0
coef_cars2_asc_san_francisco0.3950.1233.22**0.00.3940.1233.20**0.0
coef_cars2_auto_time_saving_per_worker0.6260.1973.18**0.00.6080.1983.07**0.0
coef_cars2_density_0_10_no_workers-0.1890.0118-16.03***0.0-0.1910.0118-16.16***0.0
coef_cars2_density_10_up_no_workers-0.1190.0117-10.12***0.0-0.1190.0117-10.13***0.0
coef_cars2_drivers_22.880.060247.87***0.02.880.060347.83***0.0
coef_cars2_drivers_33.460.097135.68***0.03.460.097135.66***0.0
coef_cars2_drivers_4_up6.180.33218.61***0.06.180.33318.53***0.0
coef_cars2_hh_income_0_30k0.05570.0041913.31***0.0
coef_cars2_hh_income_30_up0.007090.0007829.07***0.0
coef_cars2_num_workers_clip_30.3170.04207.55***0.00.3170.04207.54***0.0
coef_cars2_persons_16_17-0.8450.0976-8.66***0.0-0.8520.0977-8.72***0.0
coef_cars2_persons_18_24-0.9900.0659-15.04***0.0-0.9890.0659-15.01***0.0
coef_cars2_persons_25_34-0.3790.0322-11.77***0.0-0.3750.0322-11.64***0.0
coef_cars2_presence_children_5_170.3270.1043.16**0.00.3340.1043.21**0.0
coef_cars34_asc_county-0.2610.173-1.500.0-0.2720.174-1.570.0
coef_cars34_asc_san_francisco0.05590.1610.350.00.04260.1610.260.0
coef_cars34_density_0_10_no_workers-0.3430.0182-18.81***0.0-0.3430.0182-18.84***0.0
coef_cars34_density_10_up_no_workers-0.2550.0544-4.69***0.0-0.2540.0542-4.70***0.0
coef_cars34_persons_16_17-1.820.113-16.13***0.0-1.830.113-16.23***0.0
coef_cars34_persons_18_24-1.010.0695-14.60***0.0-1.020.0696-14.60***0.0
coef_cars34_persons_25_34-0.7450.0402-18.56***0.0-0.7410.0402-18.44***0.0
coef_cars34_presence_children_5_170.5420.1124.83***0.00.5450.1124.86***0.0
coef_cars3_asc-3.430.962-3.56***0.0-3.500.972-3.60***0.0
coef_cars3_auto_time_saving_per_worker0.5380.2152.50*0.00.5280.2162.45*0.0
coef_cars3_drivers_23.330.15121.99***0.03.340.15221.93***0.0
coef_cars3_drivers_35.700.17033.48***0.05.710.17133.40***0.0
coef_cars3_drivers_4_up8.640.36423.72***0.08.650.36623.64***0.0
coef_cars3_hh_income_0_30k0.06440.006689.65***0.0
coef_cars3_hh_income_30_up0.009130.001038.88***0.0
coef_cars3_num_workers_clip_30.6500.051912.53***0.00.6520.051912.55***0.0
coef_cars4_asc-5.531.02-5.42***0.0-5.631.04-5.40***0.0
coef_cars4_auto_time_saving_per_worker0.8340.2493.35***0.00.8260.2503.30***0.0
coef_cars4_drivers_22.650.2879.23***0.02.640.2839.30***0.0
coef_cars4_drivers_35.330.29717.95***0.05.300.29318.07***0.0
coef_cars4_drivers_4_up9.420.43621.59***0.09.400.43521.61***0.0
coef_cars4_hh_income_0_30k0.07180.01116.46***0.0
coef_cars4_hh_income_30_up0.01320.0013210.00***0.0
coef_cars4_num_workers_clip_30.9490.064614.69***0.00.9580.064614.82***0.0
coef_retail_auto_no_workers0.03980.1010.390.00.02790.1020.270.0
coef_retail_auto_workers0.1560.1021.520.00.1430.1031.390.0
coef_retail_non_motor-0.03000.00NA0.0fixed value-0.03000.00NA0.0fixed value
coef_retail_transit_no_workers-0.3080.0295-10.44***0.0-0.3080.0295-10.42***0.0
coef_retail_transit_workers-0.5250.0396-13.24***0.0-0.5220.0397-13.15***0.0
coef_cars1_hh_income_0_25k0.04710.0043610.81***0.0
coef_cars1_hh_income_25_500.006620.005371.230.0
coef_cars1_hh_income_50_750.007920.006661.190.0
coef_cars1_hh_income_75_up-0.002330.00246-0.950.0
coef_cars2_hh_income_0_25k0.06300.0060710.37***0.0
coef_cars2_hh_income_25_500.007700.006081.270.0
coef_cars2_hh_income_50_750.01920.007142.68**0.0
coef_cars2_hh_income_75_up0.002680.002591.030.0
coef_cars3_hh_income_0_25k0.08150.01018.05***0.0
coef_cars3_hh_income_25_500.001620.007460.220.0
coef_cars3_hh_income_50_750.02680.007933.38***0.0
coef_cars3_hh_income_75_up0.003810.002751.390.0
coef_cars4_hh_income_0_25k0.09510.01755.45***0.0
coef_cars4_hh_income_25_500.002760.009820.280.0
coef_cars4_hh_income_50_750.02740.009073.02**0.0
coef_cars4_hh_income_75_up0.008110.002922.78**0.0
\n", + "
" + ], "text/plain": [ - "" + " model \\\n", + " Value Std Err t Stat Signif \n", + "Parameter \n", + "coef_cars1_asc  1.34  0.941  1.42 \n", + "coef_cars1_asc_county -0.656  0.158 -4.14 *** \n", + "coef_cars1_asc_marin -0.168  0.106 -1.58 \n", + "coef_cars1_asc_san_francisco  0.325  0.0979  3.31 *** \n", + "coef_cars1_auto_time_saving_per_worker  0.394  0.188  2.10 * \n", + "coef_cars1_density_0_10_no_workers  0.00  0.00  NA \n", + "coef_cars1_density_10_up_no_workers -0.0145  0.00339 -4.27 *** \n", + "coef_cars1_density_10_up_workers -0.0183  0.00271 -6.75 *** \n", + "coef_cars1_drivers_2  0.00  0.00  NA \n", + "coef_cars1_drivers_3  0.00  0.00  NA \n", + "coef_cars1_drivers_4_up  2.01  0.317  6.35 *** \n", + "coef_cars1_hh_income_0_30k  0.0456  0.00298  15.29 *** \n", + "coef_cars1_hh_income_30_up  0.00  0.00  NA \n", + "coef_cars1_num_workers_clip_3  0.00  0.00  NA \n", + "coef_cars1_persons_16_17  0.00  0.00  NA \n", + "coef_cars1_persons_18_24 -0.476  0.0586 -8.11 *** \n", + "coef_cars1_persons_25_34  0.00  0.00  NA \n", + "coef_cars1_presence_children_0_4  0.487  0.130  3.75 *** \n", + "coef_cars1_presence_children_5_17  0.0390  0.0934  0.42 \n", + "coef_cars234_asc_marin  0.00  0.00  NA \n", + "coef_cars234_presence_children_0_4  0.834  0.137  6.10 *** \n", + "coef_cars2_asc -0.817  0.944 -0.87 \n", + "coef_cars2_asc_county -0.534  0.166 -3.22 ** \n", + "coef_cars2_asc_san_francisco  0.395  0.123  3.22 ** \n", + "coef_cars2_auto_time_saving_per_worker  0.626  0.197  3.18 ** \n", + "coef_cars2_density_0_10_no_workers -0.189  0.0118 -16.03 *** \n", + "coef_cars2_density_10_up_no_workers -0.119  0.0117 -10.12 *** \n", + "coef_cars2_drivers_2  2.88  0.0602  47.87 *** \n", + "coef_cars2_drivers_3  3.46  0.0971  35.68 *** \n", + "coef_cars2_drivers_4_up  6.18  0.332  18.61 *** \n", + "coef_cars2_hh_income_0_30k  0.0557  0.00419  13.31 *** \n", + "coef_cars2_hh_income_30_up  0.00709  0.000782  9.07 *** \n", + "coef_cars2_num_workers_clip_3  0.317  0.0420  7.55 *** \n", + "coef_cars2_persons_16_17 -0.845  0.0976 -8.66 *** \n", + "coef_cars2_persons_18_24 -0.990  0.0659 -15.04 *** \n", + "coef_cars2_persons_25_34 -0.379  0.0322 -11.77 *** \n", + "coef_cars2_presence_children_5_17  0.327  0.104  3.16 ** \n", + "coef_cars34_asc_county -0.261  0.173 -1.50 \n", + "coef_cars34_asc_san_francisco  0.0559  0.161  0.35 \n", + "coef_cars34_density_0_10_no_workers -0.343  0.0182 -18.81 *** \n", + "coef_cars34_density_10_up_no_workers -0.255  0.0544 -4.69 *** \n", + "coef_cars34_persons_16_17 -1.82  0.113 -16.13 *** \n", + "coef_cars34_persons_18_24 -1.01  0.0695 -14.60 *** \n", + "coef_cars34_persons_25_34 -0.745  0.0402 -18.56 *** \n", + "coef_cars34_presence_children_5_17  0.542  0.112  4.83 *** \n", + "coef_cars3_asc -3.43  0.962 -3.56 *** \n", + "coef_cars3_auto_time_saving_per_worker  0.538  0.215  2.50 * \n", + "coef_cars3_drivers_2  3.33  0.151  21.99 *** \n", + "coef_cars3_drivers_3  5.70  0.170  33.48 *** \n", + "coef_cars3_drivers_4_up  8.64  0.364  23.72 *** \n", + "coef_cars3_hh_income_0_30k  0.0644  0.00668  9.65 *** \n", + "coef_cars3_hh_income_30_up  0.00913  0.00103  8.88 *** \n", + "coef_cars3_num_workers_clip_3  0.650  0.0519  12.53 *** \n", + "coef_cars4_asc -5.53  1.02 -5.42 *** \n", + "coef_cars4_auto_time_saving_per_worker  0.834  0.249  3.35 *** \n", + "coef_cars4_drivers_2  2.65  0.287  9.23 *** \n", + "coef_cars4_drivers_3  5.33  0.297  17.95 *** \n", + "coef_cars4_drivers_4_up  9.42  0.436  21.59 *** \n", + "coef_cars4_hh_income_0_30k  0.0718  0.0111  6.46 *** \n", + "coef_cars4_hh_income_30_up  0.0132  0.00132  10.00 *** \n", + "coef_cars4_num_workers_clip_3  0.949  0.0646  14.69 *** \n", + "coef_retail_auto_no_workers  0.0398  0.101  0.39 \n", + "coef_retail_auto_workers  0.156  0.102  1.52 \n", + "coef_retail_non_motor -0.0300  0.00  NA \n", + "coef_retail_transit_no_workers -0.308  0.0295 -10.44 *** \n", + "coef_retail_transit_workers -0.525  0.0396 -13.24 *** \n", + "coef_cars1_hh_income_0_25k \n", + "coef_cars1_hh_income_25_50 \n", + "coef_cars1_hh_income_50_75 \n", + "coef_cars1_hh_income_75_up \n", + "coef_cars2_hh_income_0_25k \n", + "coef_cars2_hh_income_25_50 \n", + "coef_cars2_hh_income_50_75 \n", + "coef_cars2_hh_income_75_up \n", + "coef_cars3_hh_income_0_25k \n", + "coef_cars3_hh_income_25_50 \n", + "coef_cars3_hh_income_50_75 \n", + "coef_cars3_hh_income_75_up \n", + "coef_cars4_hh_income_0_25k \n", + "coef_cars4_hh_income_25_50 \n", + "coef_cars4_hh_income_50_75 \n", + "coef_cars4_hh_income_75_up \n", + "\n", + " model2 \\\n", + " Null Value Constrained Value \n", + "Parameter \n", + "coef_cars1_asc 0.0  1.45 \n", + "coef_cars1_asc_county 0.0 -0.670 \n", + "coef_cars1_asc_marin 0.0 -0.171 \n", + "coef_cars1_asc_san_francisco 0.0  0.317 \n", + "coef_cars1_auto_time_saving_per_worker 0.0  0.380 \n", + "coef_cars1_density_0_10_no_workers 0.0 fixed value  0.00 \n", + "coef_cars1_density_10_up_no_workers 0.0 -0.0143 \n", + "coef_cars1_density_10_up_workers 0.0 -0.0184 \n", + "coef_cars1_drivers_2 0.0 fixed value  0.00 \n", + "coef_cars1_drivers_3 0.0 fixed value  0.00 \n", + "coef_cars1_drivers_4_up 0.0  1.99 \n", + "coef_cars1_hh_income_0_30k 0.0 \n", + "coef_cars1_hh_income_30_up 0.0 fixed value \n", + "coef_cars1_num_workers_clip_3 0.0 fixed value  0.00 \n", + "coef_cars1_persons_16_17 0.0 fixed value  0.00 \n", + "coef_cars1_persons_18_24 0.0 -0.473 \n", + "coef_cars1_persons_25_34 0.0 fixed value  0.00 \n", + "coef_cars1_presence_children_0_4 0.0  0.494 \n", + "coef_cars1_presence_children_5_17 0.0  0.0442 \n", + "coef_cars234_asc_marin 0.0 fixed value  0.00 \n", + "coef_cars234_presence_children_0_4 0.0  0.840 \n", + "coef_cars2_asc 0.0 -0.752 \n", + "coef_cars2_asc_county 0.0 -0.553 \n", + "coef_cars2_asc_san_francisco 0.0  0.394 \n", + "coef_cars2_auto_time_saving_per_worker 0.0  0.608 \n", + "coef_cars2_density_0_10_no_workers 0.0 -0.191 \n", + "coef_cars2_density_10_up_no_workers 0.0 -0.119 \n", + "coef_cars2_drivers_2 0.0  2.88 \n", + "coef_cars2_drivers_3 0.0  3.46 \n", + "coef_cars2_drivers_4_up 0.0  6.18 \n", + "coef_cars2_hh_income_0_30k 0.0 \n", + "coef_cars2_hh_income_30_up 0.0 \n", + "coef_cars2_num_workers_clip_3 0.0  0.317 \n", + "coef_cars2_persons_16_17 0.0 -0.852 \n", + "coef_cars2_persons_18_24 0.0 -0.989 \n", + "coef_cars2_persons_25_34 0.0 -0.375 \n", + "coef_cars2_presence_children_5_17 0.0  0.334 \n", + "coef_cars34_asc_county 0.0 -0.272 \n", + "coef_cars34_asc_san_francisco 0.0  0.0426 \n", + "coef_cars34_density_0_10_no_workers 0.0 -0.343 \n", + "coef_cars34_density_10_up_no_workers 0.0 -0.254 \n", + "coef_cars34_persons_16_17 0.0 -1.83 \n", + "coef_cars34_persons_18_24 0.0 -1.02 \n", + "coef_cars34_persons_25_34 0.0 -0.741 \n", + "coef_cars34_presence_children_5_17 0.0  0.545 \n", + "coef_cars3_asc 0.0 -3.50 \n", + "coef_cars3_auto_time_saving_per_worker 0.0  0.528 \n", + "coef_cars3_drivers_2 0.0  3.34 \n", + "coef_cars3_drivers_3 0.0  5.71 \n", + "coef_cars3_drivers_4_up 0.0  8.65 \n", + "coef_cars3_hh_income_0_30k 0.0 \n", + "coef_cars3_hh_income_30_up 0.0 \n", + "coef_cars3_num_workers_clip_3 0.0  0.652 \n", + "coef_cars4_asc 0.0 -5.63 \n", + "coef_cars4_auto_time_saving_per_worker 0.0  0.826 \n", + "coef_cars4_drivers_2 0.0  2.64 \n", + "coef_cars4_drivers_3 0.0  5.30 \n", + "coef_cars4_drivers_4_up 0.0  9.40 \n", + "coef_cars4_hh_income_0_30k 0.0 \n", + "coef_cars4_hh_income_30_up 0.0 \n", + "coef_cars4_num_workers_clip_3 0.0  0.958 \n", + "coef_retail_auto_no_workers 0.0  0.0279 \n", + "coef_retail_auto_workers 0.0  0.143 \n", + "coef_retail_non_motor 0.0 fixed value -0.0300 \n", + "coef_retail_transit_no_workers 0.0 -0.308 \n", + "coef_retail_transit_workers 0.0 -0.522 \n", + "coef_cars1_hh_income_0_25k  0.0471 \n", + "coef_cars1_hh_income_25_50  0.00662 \n", + "coef_cars1_hh_income_50_75  0.00792 \n", + "coef_cars1_hh_income_75_up -0.00233 \n", + "coef_cars2_hh_income_0_25k  0.0630 \n", + "coef_cars2_hh_income_25_50  0.00770 \n", + "coef_cars2_hh_income_50_75  0.0192 \n", + "coef_cars2_hh_income_75_up  0.00268 \n", + "coef_cars3_hh_income_0_25k  0.0815 \n", + "coef_cars3_hh_income_25_50  0.00162 \n", + "coef_cars3_hh_income_50_75  0.0268 \n", + "coef_cars3_hh_income_75_up  0.00381 \n", + "coef_cars4_hh_income_0_25k  0.0951 \n", + "coef_cars4_hh_income_25_50  0.00276 \n", + "coef_cars4_hh_income_50_75  0.0274 \n", + "coef_cars4_hh_income_75_up  0.00811 \n", + "\n", + " \\\n", + " Std Err t Stat Signif Null Value \n", + "Parameter \n", + "coef_cars1_asc  0.946  1.54 0.0 \n", + "coef_cars1_asc_county  0.159 -4.22 *** 0.0 \n", + "coef_cars1_asc_marin  0.106 -1.61 0.0 \n", + "coef_cars1_asc_san_francisco  0.0982  3.23 ** 0.0 \n", + "coef_cars1_auto_time_saving_per_worker  0.189  2.01 * 0.0 \n", + "coef_cars1_density_0_10_no_workers  0.00  NA 0.0 \n", + "coef_cars1_density_10_up_no_workers  0.00339 -4.21 *** 0.0 \n", + "coef_cars1_density_10_up_workers  0.00271 -6.80 *** 0.0 \n", + "coef_cars1_drivers_2  0.00  NA 0.0 \n", + "coef_cars1_drivers_3  0.00  NA 0.0 \n", + "coef_cars1_drivers_4_up  0.318  6.27 *** 0.0 \n", + "coef_cars1_hh_income_0_30k \n", + "coef_cars1_hh_income_30_up \n", + "coef_cars1_num_workers_clip_3  0.00  NA 0.0 \n", + "coef_cars1_persons_16_17  0.00  NA 0.0 \n", + "coef_cars1_persons_18_24  0.0586 -8.07 *** 0.0 \n", + "coef_cars1_persons_25_34  0.00  NA 0.0 \n", + "coef_cars1_presence_children_0_4  0.130  3.80 *** 0.0 \n", + "coef_cars1_presence_children_5_17  0.0935  0.47 0.0 \n", + "coef_cars234_asc_marin  0.00  NA 0.0 \n", + "coef_cars234_presence_children_0_4  0.137  6.13 *** 0.0 \n", + "coef_cars2_asc  0.949 -0.79 0.0 \n", + "coef_cars2_asc_county  0.166 -3.33 *** 0.0 \n", + "coef_cars2_asc_san_francisco  0.123  3.20 ** 0.0 \n", + "coef_cars2_auto_time_saving_per_worker  0.198  3.07 ** 0.0 \n", + "coef_cars2_density_0_10_no_workers  0.0118 -16.16 *** 0.0 \n", + "coef_cars2_density_10_up_no_workers  0.0117 -10.13 *** 0.0 \n", + "coef_cars2_drivers_2  0.0603  47.83 *** 0.0 \n", + "coef_cars2_drivers_3  0.0971  35.66 *** 0.0 \n", + "coef_cars2_drivers_4_up  0.333  18.53 *** 0.0 \n", + "coef_cars2_hh_income_0_30k \n", + "coef_cars2_hh_income_30_up \n", + "coef_cars2_num_workers_clip_3  0.0420  7.54 *** 0.0 \n", + "coef_cars2_persons_16_17  0.0977 -8.72 *** 0.0 \n", + "coef_cars2_persons_18_24  0.0659 -15.01 *** 0.0 \n", + "coef_cars2_persons_25_34  0.0322 -11.64 *** 0.0 \n", + "coef_cars2_presence_children_5_17  0.104  3.21 ** 0.0 \n", + "coef_cars34_asc_county  0.174 -1.57 0.0 \n", + "coef_cars34_asc_san_francisco  0.161  0.26 0.0 \n", + "coef_cars34_density_0_10_no_workers  0.0182 -18.84 *** 0.0 \n", + "coef_cars34_density_10_up_no_workers  0.0542 -4.70 *** 0.0 \n", + "coef_cars34_persons_16_17  0.113 -16.23 *** 0.0 \n", + "coef_cars34_persons_18_24  0.0696 -14.60 *** 0.0 \n", + "coef_cars34_persons_25_34  0.0402 -18.44 *** 0.0 \n", + "coef_cars34_presence_children_5_17  0.112  4.86 *** 0.0 \n", + "coef_cars3_asc  0.972 -3.60 *** 0.0 \n", + "coef_cars3_auto_time_saving_per_worker  0.216  2.45 * 0.0 \n", + "coef_cars3_drivers_2  0.152  21.93 *** 0.0 \n", + "coef_cars3_drivers_3  0.171  33.40 *** 0.0 \n", + "coef_cars3_drivers_4_up  0.366  23.64 *** 0.0 \n", + "coef_cars3_hh_income_0_30k \n", + "coef_cars3_hh_income_30_up \n", + "coef_cars3_num_workers_clip_3  0.0519  12.55 *** 0.0 \n", + "coef_cars4_asc  1.04 -5.40 *** 0.0 \n", + "coef_cars4_auto_time_saving_per_worker  0.250  3.30 *** 0.0 \n", + "coef_cars4_drivers_2  0.283  9.30 *** 0.0 \n", + "coef_cars4_drivers_3  0.293  18.07 *** 0.0 \n", + "coef_cars4_drivers_4_up  0.435  21.61 *** 0.0 \n", + "coef_cars4_hh_income_0_30k \n", + "coef_cars4_hh_income_30_up \n", + "coef_cars4_num_workers_clip_3  0.0646  14.82 *** 0.0 \n", + "coef_retail_auto_no_workers  0.102  0.27 0.0 \n", + "coef_retail_auto_workers  0.103  1.39 0.0 \n", + "coef_retail_non_motor  0.00  NA 0.0 \n", + "coef_retail_transit_no_workers  0.0295 -10.42 *** 0.0 \n", + "coef_retail_transit_workers  0.0397 -13.15 *** 0.0 \n", + "coef_cars1_hh_income_0_25k  0.00436  10.81 *** 0.0 \n", + "coef_cars1_hh_income_25_50  0.00537  1.23 0.0 \n", + "coef_cars1_hh_income_50_75  0.00666  1.19 0.0 \n", + "coef_cars1_hh_income_75_up  0.00246 -0.95 0.0 \n", + "coef_cars2_hh_income_0_25k  0.00607  10.37 *** 0.0 \n", + "coef_cars2_hh_income_25_50  0.00608  1.27 0.0 \n", + "coef_cars2_hh_income_50_75  0.00714  2.68 ** 0.0 \n", + "coef_cars2_hh_income_75_up  0.00259  1.03 0.0 \n", + "coef_cars3_hh_income_0_25k  0.0101  8.05 *** 0.0 \n", + "coef_cars3_hh_income_25_50  0.00746  0.22 0.0 \n", + "coef_cars3_hh_income_50_75  0.00793  3.38 *** 0.0 \n", + "coef_cars3_hh_income_75_up  0.00275  1.39 0.0 \n", + "coef_cars4_hh_income_0_25k  0.0175  5.45 *** 0.0 \n", + "coef_cars4_hh_income_25_50  0.00982  0.28 0.0 \n", + "coef_cars4_hh_income_50_75  0.00907  3.02 ** 0.0 \n", + "coef_cars4_hh_income_75_up  0.00292  2.78 ** 0.0 \n", + "\n", + " \n", + " Constrained \n", + "Parameter \n", + "coef_cars1_asc \n", + "coef_cars1_asc_county \n", + "coef_cars1_asc_marin \n", + "coef_cars1_asc_san_francisco \n", + "coef_cars1_auto_time_saving_per_worker \n", + "coef_cars1_density_0_10_no_workers fixed value \n", + "coef_cars1_density_10_up_no_workers \n", + "coef_cars1_density_10_up_workers \n", + "coef_cars1_drivers_2 fixed value \n", + "coef_cars1_drivers_3 fixed value \n", + "coef_cars1_drivers_4_up \n", + "coef_cars1_hh_income_0_30k \n", + "coef_cars1_hh_income_30_up \n", + "coef_cars1_num_workers_clip_3 fixed value \n", + "coef_cars1_persons_16_17 fixed value \n", + "coef_cars1_persons_18_24 \n", + "coef_cars1_persons_25_34 fixed value \n", + "coef_cars1_presence_children_0_4 \n", + "coef_cars1_presence_children_5_17 \n", + "coef_cars234_asc_marin fixed value \n", + "coef_cars234_presence_children_0_4 \n", + "coef_cars2_asc \n", + "coef_cars2_asc_county \n", + "coef_cars2_asc_san_francisco \n", + "coef_cars2_auto_time_saving_per_worker \n", + "coef_cars2_density_0_10_no_workers \n", + "coef_cars2_density_10_up_no_workers \n", + "coef_cars2_drivers_2 \n", + "coef_cars2_drivers_3 \n", + "coef_cars2_drivers_4_up \n", + "coef_cars2_hh_income_0_30k \n", + "coef_cars2_hh_income_30_up \n", + "coef_cars2_num_workers_clip_3 \n", + "coef_cars2_persons_16_17 \n", + "coef_cars2_persons_18_24 \n", + "coef_cars2_persons_25_34 \n", + "coef_cars2_presence_children_5_17 \n", + "coef_cars34_asc_county \n", + "coef_cars34_asc_san_francisco \n", + "coef_cars34_density_0_10_no_workers \n", + "coef_cars34_density_10_up_no_workers \n", + "coef_cars34_persons_16_17 \n", + "coef_cars34_persons_18_24 \n", + "coef_cars34_persons_25_34 \n", + "coef_cars34_presence_children_5_17 \n", + "coef_cars3_asc \n", + "coef_cars3_auto_time_saving_per_worker \n", + "coef_cars3_drivers_2 \n", + "coef_cars3_drivers_3 \n", + "coef_cars3_drivers_4_up \n", + "coef_cars3_hh_income_0_30k \n", + "coef_cars3_hh_income_30_up \n", + "coef_cars3_num_workers_clip_3 \n", + "coef_cars4_asc \n", + "coef_cars4_auto_time_saving_per_worker \n", + "coef_cars4_drivers_2 \n", + "coef_cars4_drivers_3 \n", + "coef_cars4_drivers_4_up \n", + "coef_cars4_hh_income_0_30k \n", + "coef_cars4_hh_income_30_up \n", + "coef_cars4_num_workers_clip_3 \n", + "coef_retail_auto_no_workers \n", + "coef_retail_auto_workers \n", + "coef_retail_non_motor fixed value \n", + "coef_retail_transit_no_workers \n", + "coef_retail_transit_workers \n", + "coef_cars1_hh_income_0_25k \n", + "coef_cars1_hh_income_25_50 \n", + "coef_cars1_hh_income_50_75 \n", + "coef_cars1_hh_income_75_up \n", + "coef_cars2_hh_income_0_25k \n", + "coef_cars2_hh_income_25_50 \n", + "coef_cars2_hh_income_50_75 \n", + "coef_cars2_hh_income_75_up \n", + "coef_cars3_hh_income_0_25k \n", + "coef_cars3_hh_income_25_50 \n", + "coef_cars3_hh_income_50_75 \n", + "coef_cars3_hh_income_75_up \n", + "coef_cars4_hh_income_0_25k \n", + "coef_cars4_hh_income_25_50 \n", + "coef_cars4_hh_income_50_75 \n", + "coef_cars4_hh_income_75_up " ] }, - "execution_count": 10, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "model.to_xlsx(\n", - " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", - " data_statistics=False,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Next Steps\n", - "\n", - "The final step is to either manually or automatically copy the `*_coefficients_revised.csv` file to the configs folder, rename it to `*_coefficients.csv`, and run ActivitySim in simulation mode." + "with pd.option_context('display.max_rows', 999):\n", + " display(pd.concat({\n", + " \"model\": model.parameter_summary().data,\n", + " \"model2\": model2.parameter_summary().data,\n", + " }, axis=1).fillna(\"\"))" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -2652,107 +5819,70 @@ " \n", " \n", " \n", - " coefficient_name\n", - " value\n", - " constrain\n", + " \n", + " model\n", + " model2\n", " \n", " \n", " \n", " \n", - " 0\n", - " coef_cars1_drivers_2\n", - " 0.000000\n", - " T\n", - " \n", - " \n", - " 1\n", - " coef_cars1_drivers_3\n", - " 0.000000\n", - " T\n", - " \n", - " \n", - " 2\n", - " coef_cars1_persons_16_17\n", - " 0.000000\n", - " T\n", - " \n", - " \n", - " 3\n", - " coef_cars234_asc_marin\n", - " 0.000000\n", - " T\n", - " \n", - " \n", - " 4\n", - " coef_cars1_persons_25_34\n", - " 0.000000\n", - " T\n", - " \n", - " \n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", + " Number of Cases\n", + " Aggregate\n", + " 20000.000000\n", + " 20000.000000\n", " \n", " \n", - " 62\n", - " coef_cars4_drivers_3\n", - " 564.490158\n", - " F\n", + " Log Likelihood at Convergence\n", + " Aggregate\n", + " -18485.495027\n", + " -18480.692008\n", " \n", " \n", - " 63\n", - " coef_cars3_drivers_3\n", - " 5.048488\n", - " F\n", + " Per Case\n", + " -0.924275\n", + " -0.924035\n", " \n", " \n", - " 64\n", - " coef_cars2_drivers_4_up\n", - " 6.856405\n", - " F\n", + " Log Likelihood at Null Parameters\n", + " Aggregate\n", + " -32431.882743\n", + " -32431.882743\n", " \n", " \n", - " 65\n", - " coef_cars3_drivers_4_up\n", - " 8.317950\n", - " F\n", + " Per Case\n", + " -1.621594\n", + " -1.621594\n", " \n", " \n", - " 66\n", - " coef_cars4_drivers_4_up\n", - " 568.272514\n", - " F\n", + " Rho Squared w.r.t. Null Parameters\n", + " Aggregate\n", + " 0.430021\n", + " 0.430169\n", " \n", " \n", "\n", - "

67 rows × 3 columns

\n", "" ], "text/plain": [ - " coefficient_name value constrain\n", - "0 coef_cars1_drivers_2 0.000000 T\n", - "1 coef_cars1_drivers_3 0.000000 T\n", - "2 coef_cars1_persons_16_17 0.000000 T\n", - "3 coef_cars234_asc_marin 0.000000 T\n", - "4 coef_cars1_persons_25_34 0.000000 T\n", - ".. ... ... ...\n", - "62 coef_cars4_drivers_3 564.490158 F\n", - "63 coef_cars3_drivers_3 5.048488 F\n", - "64 coef_cars2_drivers_4_up 6.856405 F\n", - "65 coef_cars3_drivers_4_up 8.317950 F\n", - "66 coef_cars4_drivers_4_up 568.272514 F\n", - "\n", - "[67 rows x 3 columns]" + " model model2\n", + "Number of Cases Aggregate 20000.000000 20000.000000\n", + "Log Likelihood at Convergence Aggregate -18485.495027 -18480.692008\n", + " Per Case -0.924275 -0.924035\n", + "Log Likelihood at Null Parameters Aggregate -32431.882743 -32431.882743\n", + " Per Case -1.621594 -1.621594\n", + "Rho Squared w.r.t. Null Parameters Aggregate 0.430021 0.430169" ] }, - "execution_count": 11, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "pd.read_csv(result_dir/f\"{modelname}_coefficients_revised.csv\")" + "with pd.option_context('display.max_rows', 999):\n", + " display(pd.concat({\n", + " \"model\": model.estimation_statistics_raw(),\n", + " \"model2\": model2.estimation_statistics_raw(),\n", + " }, axis=1).fillna(\"\"))" ] } ], @@ -2763,7 +5893,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -2777,7 +5907,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/05_free_parking.ipynb b/activitysim/examples/example_estimation/notebooks/05_free_parking.ipynb index fd0fe5714f..464f32106c 100644 --- a/activitysim/examples/example_estimation/notebooks/05_free_parking.ipynb +++ b/activitysim/examples/example_estimation/notebooks/05_free_parking.ipynb @@ -34,27 +34,75 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +116,27 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/free_parking/free_parking_coefficients.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/free_parking/free_parking_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/free_parking/free_parking_values_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"free_parking\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -388,14 +451,14 @@ " util_hh_size_4_up\n", " util_more_autos_than_workers\n", " ...\n", - " COLLFTE\n", - " COLLPTE\n", - " TOPOLOGY\n", - " TERMINAL\n", - " household_density\n", - " employment_density\n", - " density_index\n", - " is_cbd\n", + " auOpRetail\n", + " auOpTotal\n", + " trPkRetail\n", + " trPkTotal\n", + " trOpRetail\n", + " trOpTotal\n", + " nmRetail\n", + " nmTotal\n", " workplace_county_id\n", " override_choice_code\n", " \n", @@ -426,8 +489,8 @@ " \n", " \n", " \n", - " 72241\n", - " 72241\n", + " 72355\n", + " 72355\n", " False\n", " False\n", " 1.0\n", @@ -436,22 +499,22 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 4.58156\n", - " 68.092368\n", - " 151.674705\n", - " 46.994710\n", - " True\n", + " 9.915345\n", + " 12.430580\n", + " 6.550726\n", + " 9.119016\n", + " 6.446184\n", + " 9.035333\n", + " 5.256966\n", + " 6.831275\n", " 1\n", " 2\n", " \n", " \n", - " 72441\n", - " 72441\n", + " 72384\n", + " 72384\n", " False\n", " False\n", " 1.0\n", @@ -462,20 +525,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 2.28482\n", - " 28.491228\n", - " 4.052632\n", - " 3.547964\n", - " False\n", + " 9.971763\n", + " 12.488100\n", + " 6.384615\n", + " 8.910521\n", + " 6.292135\n", + " 8.845287\n", + " 5.447277\n", + " 7.062559\n", " 1\n", " 2\n", " \n", " \n", - " 72528\n", - " 72528\n", + " 72407\n", + " 72407\n", " False\n", " False\n", " 1.0\n", @@ -486,20 +549,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 6861.20508\n", - " 1174.96875\n", - " 1\n", - " 3.49553\n", - " 19.033424\n", - " 37.235052\n", - " 12.595161\n", - " False\n", + " 9.971763\n", + " 12.488100\n", + " 6.384615\n", + " 8.910521\n", + " 6.292135\n", + " 8.845287\n", + " 5.447277\n", + " 7.062559\n", " 1\n", " 2\n", " \n", " \n", - " 73144\n", - " 73144\n", + " 72459\n", + " 72459\n", " False\n", " False\n", " 1.0\n", @@ -510,20 +573,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 2.48345\n", - " 26.073171\n", - " 8.048780\n", - " 6.150212\n", - " False\n", + " 10.086939\n", + " 12.619691\n", + " 6.787018\n", + " 9.400117\n", + " 6.687820\n", + " 9.307625\n", + " 5.877288\n", + " 7.691985\n", " 1\n", " 2\n", " \n", " \n", - " 73493\n", - " 73493\n", + " 72529\n", + " 72529\n", " False\n", " False\n", " 1.0\n", @@ -534,14 +597,14 @@ " 0.0\n", " 0.0\n", " ...\n", - " 7144.64307\n", - " 22523.34570\n", - " 1\n", - " 3.20356\n", - " 13.672131\n", - " 39.852459\n", - " 10.179771\n", - " False\n", + " 10.263491\n", + " 12.913804\n", + " 6.830450\n", + " 9.558905\n", + " 6.611336\n", + " 9.308290\n", + " 6.696709\n", + " 8.925142\n", " 1\n", " 2\n", " \n", @@ -570,35 +633,35 @@ " ...\n", " \n", " \n", - " 2822879\n", - " 7514214\n", - " False\n", + " 2847736\n", + " 7539071\n", " False\n", - " 1.0\n", - " 0.0\n", + " True\n", " 0.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", + " 1.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 1.08765\n", - " 0.415094\n", - " 3.578616\n", - " 0.371951\n", - " False\n", + " 9.875413\n", + " 12.586445\n", + " 4.800090\n", + " 8.088658\n", + " 4.581187\n", + " 7.858361\n", + " 5.697172\n", + " 9.212853\n", + " 4\n", " 1\n", - " 2\n", " \n", " \n", - " 2822949\n", - " 7514284\n", + " 2847868\n", + " 7539203\n", " False\n", " False\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -606,47 +669,47 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.86254\n", - " 33.841404\n", - " 40.299687\n", - " 18.394631\n", - " True\n", - " 1\n", + " 9.121001\n", + " 11.606573\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 1.324505\n", + " 4.959246\n", + " 5\n", " 2\n", " \n", " \n", - " 2823069\n", - " 7514404\n", - " False\n", - " False\n", - " 1.0\n", + " 2847882\n", + " 7539217\n", + " True\n", + " True\n", " 0.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.95752\n", - " 65.596535\n", - " 32.655666\n", - " 21.802041\n", - " True\n", + " 9.121001\n", + " 11.606573\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 1.324505\n", + " 4.959246\n", + " 4\n", " 1\n", - " 2\n", " \n", " \n", - " 2823442\n", - " 7514777\n", + " 2847935\n", + " 7539270\n", " False\n", " False\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -654,23 +717,23 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 2\n", - " 4.51942\n", - " 56.706023\n", - " 144.861886\n", - " 40.753220\n", - " True\n", - " 1\n", + " 9.653875\n", + " 12.007751\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 5.523983\n", + " 7.598532\n", + " 5\n", " 2\n", " \n", " \n", - " 2823850\n", - " 7515185\n", - " False\n", + " 2847982\n", + " 7539317\n", + " True\n", " False\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -678,108 +741,108 @@ " 0.0\n", " 0.0\n", " ...\n", - 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2582 rows × 116 columns

\n", + "

28281 rows × 116 columns

\n", "" ], "text/plain": [ " person_id model_choice override_choice \\\n", "household_id \n", - "72241 72241 False False \n", - "72441 72441 False False \n", - "72528 72528 False False \n", - "73144 73144 False False \n", - "73493 73493 False False \n", + "72355 72355 False False \n", + "72384 72384 False False \n", + "72407 72407 False False \n", + "72459 72459 False False \n", + "72529 72529 False False \n", "... ... ... ... \n", - "2822879 7514214 False False \n", - "2822949 7514284 False False \n", - "2823069 7514404 False False \n", - "2823442 7514777 False False \n", - "2823850 7515185 False False \n", + "2847736 7539071 False True \n", + "2847868 7539203 False False \n", + "2847882 7539217 True True \n", + "2847935 7539270 False False \n", + "2847982 7539317 True False \n", "\n", " util_asc_san_francisco util_asc_santa_clara util_asc_alameda \\\n", "household_id \n", - "72241 1.0 0.0 0.0 \n", - "72441 1.0 0.0 0.0 \n", - "72528 1.0 0.0 0.0 \n", - "73144 1.0 0.0 0.0 \n", - "73493 1.0 0.0 0.0 \n", + "72355 1.0 0.0 0.0 \n", + "72384 1.0 0.0 0.0 \n", + "72407 1.0 0.0 0.0 \n", + "72459 1.0 0.0 0.0 \n", + "72529 1.0 0.0 0.0 \n", "... ... ... ... \n", - "2822879 1.0 0.0 0.0 \n", - "2822949 1.0 0.0 0.0 \n", - "2823069 1.0 0.0 0.0 \n", - "2823442 1.0 0.0 0.0 \n", - "2823850 1.0 0.0 0.0 \n", + "2847736 0.0 0.0 1.0 \n", + "2847868 0.0 0.0 0.0 \n", + "2847882 0.0 0.0 1.0 \n", + "2847935 0.0 0.0 0.0 \n", + "2847982 0.0 0.0 0.0 \n", "\n", " util_income_very_high util_income_high util_hh_size_4_up \\\n", "household_id \n", - "72241 0.0 0.0 0.0 \n", - "72441 0.0 0.0 0.0 \n", - "72528 0.0 0.0 0.0 \n", - "73144 0.0 0.0 0.0 \n", - "73493 0.0 0.0 0.0 \n", + "72355 0.0 0.0 0.0 \n", + "72384 0.0 0.0 0.0 \n", + "72407 0.0 0.0 0.0 \n", + "72459 0.0 0.0 0.0 \n", + "72529 0.0 0.0 0.0 \n", "... ... ... ... \n", - "2822879 0.0 0.0 0.0 \n", - "2822949 0.0 0.0 0.0 \n", - "2823069 0.0 0.0 0.0 \n", - "2823442 0.0 0.0 0.0 \n", - "2823850 0.0 0.0 0.0 \n", + "2847736 0.0 0.0 0.0 \n", + "2847868 0.0 0.0 0.0 \n", + "2847882 0.0 0.0 0.0 \n", + "2847935 0.0 0.0 0.0 \n", + "2847982 0.0 0.0 0.0 \n", "\n", - " util_more_autos_than_workers ... COLLFTE COLLPTE \\\n", - "household_id ... \n", - "72241 0.0 ... 0.00000 0.00000 \n", - "72441 0.0 ... 0.00000 0.00000 \n", - "72528 0.0 ... 6861.20508 1174.96875 \n", - "73144 0.0 ... 0.00000 0.00000 \n", - "73493 0.0 ... 7144.64307 22523.34570 \n", - "... ... ... ... ... \n", - "2822879 0.0 ... 0.00000 0.00000 \n", - "2822949 0.0 ... 0.00000 0.00000 \n", - "2823069 0.0 ... 0.00000 0.00000 \n", - "2823442 0.0 ... 0.00000 0.00000 \n", - "2823850 0.0 ... 0.00000 0.00000 \n", + " util_more_autos_than_workers ... auOpRetail auOpTotal \\\n", + "household_id ... \n", + "72355 1.0 ... 9.915345 12.430580 \n", + "72384 0.0 ... 9.971763 12.488100 \n", + "72407 0.0 ... 9.971763 12.488100 \n", + "72459 0.0 ... 10.086939 12.619691 \n", + "72529 0.0 ... 10.263491 12.913804 \n", + "... ... ... ... ... \n", + "2847736 1.0 ... 9.875413 12.586445 \n", + "2847868 0.0 ... 9.121001 11.606573 \n", + "2847882 0.0 ... 9.121001 11.606573 \n", + "2847935 0.0 ... 9.653875 12.007751 \n", + "2847982 0.0 ... 6.494711 8.713819 \n", "\n", - " TOPOLOGY TERMINAL household_density employment_density \\\n", - "household_id \n", - "72241 1 4.58156 68.092368 151.674705 \n", - "72441 1 2.28482 28.491228 4.052632 \n", - "72528 1 3.49553 19.033424 37.235052 \n", - "73144 1 2.48345 26.073171 8.048780 \n", - "73493 1 3.20356 13.672131 39.852459 \n", - "... ... ... ... ... \n", - "2822879 1 1.08765 0.415094 3.578616 \n", - "2822949 1 3.86254 33.841404 40.299687 \n", - "2823069 1 3.95752 65.596535 32.655666 \n", - "2823442 2 4.51942 56.706023 144.861886 \n", - "2823850 3 2.46800 0.296858 36.296472 \n", + " trPkRetail trPkTotal trOpRetail trOpTotal nmRetail \\\n", + "household_id \n", + "72355 6.550726 9.119016 6.446184 9.035333 5.256966 \n", + "72384 6.384615 8.910521 6.292135 8.845287 5.447277 \n", + "72407 6.384615 8.910521 6.292135 8.845287 5.447277 \n", + "72459 6.787018 9.400117 6.687820 9.307625 5.877288 \n", + "72529 6.830450 9.558905 6.611336 9.308290 6.696709 \n", + "... ... ... ... ... ... \n", + "2847736 4.800090 8.088658 4.581187 7.858361 5.697172 \n", + "2847868 0.000000 0.000000 0.000000 0.000000 1.324505 \n", + "2847882 0.000000 0.000000 0.000000 0.000000 1.324505 \n", + "2847935 0.000000 0.000000 0.000000 0.000000 5.523983 \n", + "2847982 0.019735 0.222696 0.016077 0.153189 0.000000 \n", "\n", - " density_index is_cbd workplace_county_id override_choice_code \n", - "household_id \n", - "72241 46.994710 True 1 2 \n", - "72441 3.547964 False 1 2 \n", - "72528 12.595161 False 1 2 \n", - "73144 6.150212 False 1 2 \n", - "73493 10.179771 False 1 2 \n", - "... ... ... ... ... \n", - "2822879 0.371951 False 1 2 \n", - "2822949 18.394631 True 1 2 \n", - "2823069 21.802041 True 1 2 \n", - "2823442 40.753220 True 1 2 \n", - "2823850 0.294449 True 1 2 \n", + " nmTotal workplace_county_id override_choice_code \n", + "household_id \n", + "72355 6.831275 1 2 \n", + "72384 7.062559 1 2 \n", + "72407 7.062559 1 2 \n", + "72459 7.691985 1 2 \n", + "72529 8.925142 1 2 \n", + "... ... ... ... \n", + "2847736 9.212853 4 1 \n", + "2847868 4.959246 5 2 \n", + "2847882 4.959246 4 1 \n", + "2847935 7.598532 5 2 \n", + "2847982 0.000000 8 2 \n", "\n", - "[2582 rows x 116 columns]" + "[28281 rows x 116 columns]" ] }, "execution_count": 6, @@ -802,20 +865,13 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

Iteration 010 [Optimization terminated successfully]

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Iteration 007 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -827,7 +883,7 @@ { "data": { "text/html": [ - "

Best LL = -484.0908426547178

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Best LL = -15941.804810325377

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coef_asc_san_francisco0.0003990.000074
coef_asc_santa_clara0.0000000.000008
coef_fewer_autos_than_workers0.0001830.000150
coef_hh_size_4_up0.000210-0.000075
coef_income_high0.0003640.000317
coef_income_very_high-0.000061-0.000092
coef_more_autos_than_workers0.0001070.000781
nit10nfev19njev10status0message'Optimization terminated successfully'successTrueelapsed_time0:00:00.810470method'slsqp'n_cases2582iteration_number10logloss0.1874867709739418" + "nit7nfev7njev7status0message'Optimization terminated successfully'successTrueelapsed_time0:00:00.092472method'slsqp'n_cases28281iteration_number7loglike-15941.804810325377" ], "text/plain": [ "┣ x: 0.0 0.000000\n", - "┃ coef_asc_alameda -0.109200\n", - "┃ coef_asc_san_francisco -2.456059\n", - "┃ coef_asc_santa_clara 0.211800\n", - "┃ coef_fewer_autos_than_workers -1.619489\n", - "┃ coef_hh_size_4_up 0.279145\n", - "┃ coef_income_high -0.053120\n", - "┃ coef_income_very_high 0.296661\n", - "┃ coef_more_autos_than_workers 0.223434\n", + "┃ coef_asc_alameda -0.141547\n", + "┃ coef_asc_san_francisco -2.630212\n", + "┃ coef_asc_santa_clara 0.188205\n", + "┃ coef_fewer_autos_than_workers -1.407827\n", + "┃ coef_hh_size_4_up 0.264779\n", + "┃ coef_income_high 0.217818\n", + "┃ coef_income_very_high 0.235389\n", + "┃ coef_more_autos_than_workers 0.225131\n", "┃ dtype: float64\n", - "┣ loglike: -484.0908426547178\n", - "┣ d_loglike: 0.0 0.000000\n", - "┃ coef_asc_alameda 0.000000\n", - "┃ coef_asc_san_francisco 0.000399\n", - "┃ coef_asc_santa_clara 0.000000\n", - "┃ coef_fewer_autos_than_workers 0.000183\n", - "┃ coef_hh_size_4_up 0.000210\n", - "┃ coef_income_high 0.000364\n", - "┃ coef_income_very_high -0.000061\n", - "┃ coef_more_autos_than_workers 0.000107\n", + "┣ logloss: 0.5636931088124669\n", + "┣ d_logloss: 0.0 0.000000\n", + "┃ coef_asc_alameda 0.000061\n", + "┃ coef_asc_san_francisco 0.000074\n", + "┃ coef_asc_santa_clara 0.000008\n", + "┃ coef_fewer_autos_than_workers 0.000150\n", + "┃ coef_hh_size_4_up -0.000075\n", + "┃ coef_income_high 0.000317\n", + "┃ coef_income_very_high -0.000092\n", + "┃ coef_more_autos_than_workers 0.000781\n", "┃ dtype: float64\n", - "┣ nit: 10\n", - "┣ nfev: 19\n", - "┣ njev: 10\n", + "┣ nit: 7\n", + "┣ nfev: 7\n", + "┣ njev: 7\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(microseconds=810470)\n", + "┣ elapsed_time: datetime.timedelta(microseconds=92472)\n", "┣ method: 'slsqp'\n", - "┣ n_cases: 2582\n", - "┣ iteration_number: 10\n", - "┣ logloss: 0.1874867709739418" + "┣ n_cases: 28281\n", + "┣ iteration_number: 7\n", + "┣ loglike: -15941.804810325377" ] }, - "execution_count": 9, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -1154,119 +1204,136 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Value Std Err t Stat Signif Like Ratio Null Value Constrained
0.0 0.00 NA NA NA 0.00fixed value
coef_asc_alameda-0.109 0.00 NA[] 0.00 0.00
coef_asc_san_francisco-2.46 0.168-14.65*** NA 0.00
coef_asc_santa_clara 0.212 1.43e-16 BIG*** NA 0.00
coef_fewer_autos_than_workers-1.62 0.220-7.37*** NA 0.00
coef_hh_size_4_up 0.279 0.196 1.43 NA 0.00
coef_income_high-0.0531 0.242-0.22 NA 0.00
coef_income_very_high 0.297 0.208 1.43 NA 0.00
coef_more_autos_than_workers 0.223 0.241 0.93 NA 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
0.0 0.00 0.00 NA 0.00fixed value
coef_asc_alameda-0.142 0.0310-4.56*** 0.00
coef_asc_san_francisco-2.63 0.0591-44.52*** 0.00
coef_asc_santa_clara 0.188 0.0294 6.40*** 0.00
coef_fewer_autos_than_workers-1.41 0.0366-38.48*** 0.00
coef_hh_size_4_up 0.265 0.0278 9.51*** 0.00
coef_income_high 0.218 0.0307 7.09*** 0.00
coef_income_very_high 0.235 0.0282 8.35*** 0.00
coef_more_autos_than_workers 0.225 0.0294 7.65*** 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 10, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1287,14 +1354,17 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "from activitysim.estimation.larch import update_coefficients\n", - "result_dir = data.edb_directory/\"estimated\"\n", + "\n", + "result_dir = data.edb_directory / \"estimated\"\n", "update_coefficients(\n", - " model, data, result_dir,\n", + " model,\n", + " data,\n", + " result_dir,\n", " output_file=f\"{modelname}_coefficients_revised.csv\",\n", ");" ] @@ -1308,23 +1378,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", - " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", + " result_dir / f\"{modelname}_model_estimation.xlsx\",\n", " data_statistics=False,\n", ")" ] @@ -1340,7 +1399,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -1373,49 +1432,49 @@ " \n", " 0\n", " coef_asc_san_francisco\n", - " -2.456059\n", + " -2.630212\n", " F\n", " \n", " \n", " 1\n", " coef_asc_santa_clara\n", - " 0.211800\n", + " 0.188205\n", " F\n", " \n", " \n", " 2\n", " coef_asc_alameda\n", - " -0.109200\n", + " -0.141547\n", " F\n", " \n", " \n", " 3\n", " coef_income_very_high\n", - " 0.296661\n", + " 0.235389\n", " F\n", " \n", " \n", " 4\n", " coef_income_high\n", - " -0.053120\n", + " 0.217818\n", " F\n", " \n", " \n", " 5\n", " coef_hh_size_4_up\n", - " 0.279145\n", + " 0.264779\n", " F\n", " \n", " \n", " 6\n", " coef_more_autos_than_workers\n", - " 0.223434\n", + " 0.225131\n", " F\n", " \n", " \n", " 7\n", " coef_fewer_autos_than_workers\n", - " -1.619489\n", + " -1.407827\n", " F\n", " \n", " \n", @@ -1424,23 +1483,23 @@ ], "text/plain": [ " coefficient_name value constrain\n", - "0 coef_asc_san_francisco -2.456059 F\n", - "1 coef_asc_santa_clara 0.211800 F\n", - "2 coef_asc_alameda -0.109200 F\n", - "3 coef_income_very_high 0.296661 F\n", - "4 coef_income_high -0.053120 F\n", - "5 coef_hh_size_4_up 0.279145 F\n", - "6 coef_more_autos_than_workers 0.223434 F\n", - "7 coef_fewer_autos_than_workers -1.619489 F" + "0 coef_asc_san_francisco -2.630212 F\n", + "1 coef_asc_santa_clara 0.188205 F\n", + "2 coef_asc_alameda -0.141547 F\n", + "3 coef_income_very_high 0.235389 F\n", + "4 coef_income_high 0.217818 F\n", + "5 coef_hh_size_4_up 0.264779 F\n", + "6 coef_more_autos_than_workers 0.225131 F\n", + "7 coef_fewer_autos_than_workers -1.407827 F" ] }, - "execution_count": 13, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.read_csv(result_dir/f\"{modelname}_coefficients_revised.csv\")" + "pd.read_csv(result_dir / f\"{modelname}_coefficients_revised.csv\")" ] } ], @@ -1451,7 +1510,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -1465,7 +1524,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/06_cdap.ipynb b/activitysim/examples/example_estimation/notebooks/06_cdap.ipynb index 72169b9e3d..a29ea0a7b1 100644 --- a/activitysim/examples/example_estimation/notebooks/06_cdap.ipynb +++ b/activitysim/examples/example_estimation/notebooks/06_cdap.ipynb @@ -23,21 +23,84 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import numpy as np\n", "import pandas as pd\n", - "import larch\n", - "import os" + "import larch as lx\n", + "import os\n", + "\n", + "lx.versions()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from est_mode_setup import prepare, backup\n", + "\n", + "prepare()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ - "os.chdir('test')" + "backup(\"output-est-mode/estimation_data_bundle/cdap/cdap_INDIV_AND_HHSIZE1_SPEC.csv\")\n" ] }, { @@ -49,31 +112,35 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "one-hot encoding choice array\n", - "converting data_ch to \n", - "one-hot encoding choice array\n", - "converting data_ch to \n", - "one-hot encoding choice array\n", - "converting data_ch to \n", - "one-hot encoding choice array\n", - "converting data_ch to \n", - "one-hot encoding choice array\n", - "converting data_ch to \n" + "Reading output-est-mode/estimation_data_bundle/cdap/cdap_model_settings.yaml\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/final_households.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/final_persons.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_coefficients.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_interaction_coefficients.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_joint_tour_coefficients.csv\n", + "Including joint tour utility?: False\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_INDIV_AND_HHSIZE1_SPEC.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_values_combined.parquet\n" ] } ], "source": [ + "from activitysim.estimation.larch import component_model\n", + "\n", "modelname = \"cdap\"\n", "\n", - "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -92,34 +159,51 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "┣ INDIV_AND_HHSIZE1_SPEC: 'cdap_indiv_and_hhsize1.csv'\n", + "┣ ADD_JOINT_TOUR_UTILITY: False\n", "┣ COEFFICIENTS: 'cdap_coefficients.csv'\n", - "┣ INTERACTION_COEFFICIENTS: 'cdap_interaction_coefficients.csv'\n", - "┣ FIXED_RELATIVE_PROPORTIONS_SPEC: 'cdap_fixed_relative_proportions.csv'\n", - "┣ CONSTANTS: ┣ FULL: 1\n", - "┃ ┣ PART: 2\n", - "┃ ┣ UNIVERSITY: 3\n", + "┣ CONSTANTS: ┣ DRIVING: 6\n", + "┃ ┣ FULL: 1\n", "┃ ┣ NONWORK: 4\n", + "┃ ┣ PART: 2\n", + "┃ ┣ PRESCHOOL: 8\n", "┃ ┣ RETIRED: 5\n", - "┃ ┣ DRIVING: 6\n", "┃ ┣ SCHOOL: 7\n", - "┃ ┣ PRESCHOOL: 8\n", - "┣ PERSON_TYPE_MAP: ┣ WORKER: [1, 2]\n", - "┃ ┣ CHILD: [6, 7, 8]\n", - "┣ annotate_persons: ┣ SPEC: 'annotate_persons_cdap'\n", - "┃ ┣ DF: 'persons'\n", - "┣ annotate_households: ┣ SPEC: 'annotate_households_cdap'\n", - "┃ ┣ DF: 'households'\n", - "┃ ┣ TABLES: ['persons']" + "┃ ┣ UNIVERSITY: 3\n", + "┣ FIXED_RELATIVE_PROPORTIONS_SPEC: 'cdap_fixed_relative_proportions.csv'\n", + "┣ INDIV_AND_HHSIZE1_SPEC: 'cdap_indiv_and_hhsize1.csv'\n", + "┣ INTERACTION_COEFFICIENTS: 'cdap_interaction_coefficients.csv'\n", + "┣ JOINT_TOUR_COEFFICIENTS: 'cdap_joint_tour_coefficients.csv'\n", + "┣ JOINT_TOUR_USEFUL_COLUMNS: None\n", + "┣ PERSON_TYPE_MAP: ┣ CHILD: ---\n", + "┃ ┃ - 6\n", + "┃ ┃ - 7\n", + "┃ ┃ - 8\n", + "┃ ┃ ...\n", + "┃ ┣ WORKER: ---\n", + "┃ ┃ - 1\n", + "┃ ┃ - 2\n", + "┃ ┃ ...\n", + "┣ annotate_households: ┣ DF: 'households'\n", + "┃ ┣ SPEC: 'annotate_households_cdap'\n", + "┃ ┣ TABLES: ---\n", + "┃ ┃ - persons\n", + "┃ ┃ ...\n", + "┣ annotate_persons: ┣ DF: 'persons'\n", + "┃ ┣ SPEC: 'annotate_persons_cdap'\n", + "┃ ┣ TABLES: None\n", + "┣ compute_settings: None\n", + "┣ source_file_paths: ---\n", + "┃ - /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/test-estimation-data/activitysim-prototype-mtc-extended/configs/cdap.yaml\n", + "┃ ..." ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -137,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -161,7 +245,6 @@ " \n", " \n", " \n", - " household_id\n", " home_zone_id\n", " income\n", " hhsize\n", @@ -171,8 +254,8 @@ " sample_rate\n", " income_in_thousands\n", " income_segment\n", + " median_value_of_time\n", " ...\n", - " hh_work_auto_savings_ratio\n", " num_under16_not_at_school\n", " num_travel_active\n", " num_travel_active_adults\n", @@ -182,23 +265,23 @@ " participates_in_jtf_model\n", " joint_tour_frequency\n", " num_hh_joint_tours\n", + " household_id\n", " \n", " \n", " \n", " \n", " 0\n", - " 166\n", - " 71\n", - " 9000\n", - " 1\n", - " 6\n", + " 52\n", " 0\n", + " 1\n", + " 4\n", + " 1\n", " 0\n", " 1\n", - " 9.00\n", + " 0.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -208,21 +291,21 @@ " False\n", " 0_tours\n", " 0\n", + " 45\n", " \n", " \n", " 1\n", - " 197\n", - " 80\n", - " 4400\n", + " 124\n", + " 14000\n", + " 1\n", + " 4\n", " 1\n", - " 6\n", - " 0\n", " 0\n", " 1\n", - " 4.40\n", + " 14.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -232,21 +315,21 @@ " False\n", " 0_tours\n", " 0\n", + " 499\n", " \n", " \n", " 2\n", - " 268\n", - " 91\n", - " 1200\n", + " 132\n", + " 9600\n", " 1\n", " 4\n", " 1\n", " 0\n", " 1\n", - " 1.20\n", + " 9.6\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -256,21 +339,21 @@ " False\n", " 0_tours\n", " 0\n", + " 659\n", " \n", " \n", " 3\n", - " 375\n", - " 105\n", - " 0\n", + " 148\n", + " 18000\n", " 1\n", " 6\n", " 1\n", " 0\n", " 1\n", - " 0.00\n", + " 18.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -280,21 +363,21 @@ " False\n", " 0_tours\n", " 0\n", + " 948\n", " \n", " \n", " 4\n", - " 387\n", - " 112\n", - " 15770\n", + " 166\n", + " 14000\n", " 1\n", - " 6\n", + " 4\n", " 1\n", " 0\n", " 1\n", - " 15.77\n", + " 14.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -304,6 +387,7 @@ " False\n", " 0_tours\n", " 0\n", + " 1276\n", " \n", " \n", " ...\n", @@ -330,19 +414,18 @@ " ...\n", " \n", " \n", - " 1995\n", - " 2863464\n", - " 5\n", + " 19995\n", + " 1386\n", " 0\n", " 1\n", " 0\n", " 1\n", " 0\n", " 1\n", - " 0.00\n", + " 0.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -352,45 +435,45 @@ " False\n", " 0_tours\n", " 0\n", + " 2874468\n", " \n", " \n", - " 1996\n", - " 2863483\n", - " 20\n", + " 19996\n", + " 1402\n", " 0\n", " 1\n", " 0\n", - " 1\n", + " 0\n", " 0\n", " 1\n", - " 0.00\n", + " 0.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", - " 1\n", - " 1\n", " 0\n", " 0\n", - " 1\n", + " 0\n", + " 0\n", + " 0\n", " False\n", " 0_tours\n", " 0\n", + " 2874567\n", " \n", " \n", - " 1997\n", - " 2863806\n", - " 85\n", + " 19997\n", + " 1402\n", " 0\n", " 1\n", " 0\n", " 1\n", " 0\n", " 1\n", - " 0.00\n", + " 0.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -400,21 +483,21 @@ " False\n", " 0_tours\n", " 0\n", + " 2874576\n", " \n", " \n", - " 1998\n", - " 2864518\n", - " 115\n", + " 19998\n", + " 1421\n", " 0\n", " 1\n", " 0\n", " 1\n", " 0\n", " 1\n", - " 0.00\n", + " 0.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -424,21 +507,21 @@ " False\n", " 0_tours\n", " 0\n", + " 2874826\n", " \n", " \n", - " 1999\n", - " 2864688\n", - " 136\n", + " 19999\n", + " 1437\n", " 0\n", " 1\n", " 0\n", " 1\n", " 0\n", " 1\n", - " 0.00\n", + " 0.0\n", " 1\n", + " 6.01\n", " ...\n", - " 0.0\n", " 0\n", " 1\n", " 1\n", @@ -448,108 +531,109 @@ " False\n", " 0_tours\n", " 0\n", + " 2875013\n", " \n", " \n", "\n", - "

2000 rows × 35 columns

\n", + "

20000 rows × 35 columns

\n", "" ], "text/plain": [ - " household_id home_zone_id income hhsize HHT auto_ownership \\\n", - "0 166 71 9000 1 6 0 \n", - "1 197 80 4400 1 6 0 \n", - "2 268 91 1200 1 4 1 \n", - "3 375 105 0 1 6 1 \n", - "4 387 112 15770 1 6 1 \n", - "... ... ... ... ... ... ... \n", - "1995 2863464 5 0 1 0 1 \n", - "1996 2863483 20 0 1 0 1 \n", - "1997 2863806 85 0 1 0 1 \n", - "1998 2864518 115 0 1 0 1 \n", - "1999 2864688 136 0 1 0 1 \n", + " home_zone_id income hhsize HHT auto_ownership num_workers \\\n", + "0 52 0 1 4 1 0 \n", + "1 124 14000 1 4 1 0 \n", + "2 132 9600 1 4 1 0 \n", + "3 148 18000 1 6 1 0 \n", + "4 166 14000 1 4 1 0 \n", + "... ... ... ... ... ... ... \n", + "19995 1386 0 1 0 1 0 \n", + "19996 1402 0 1 0 0 0 \n", + "19997 1402 0 1 0 1 0 \n", + "19998 1421 0 1 0 1 0 \n", + "19999 1437 0 1 0 1 0 \n", "\n", - " num_workers sample_rate income_in_thousands income_segment ... \\\n", - "0 0 1 9.00 1 ... \n", - "1 0 1 4.40 1 ... \n", - "2 0 1 1.20 1 ... \n", - "3 0 1 0.00 1 ... \n", - "4 0 1 15.77 1 ... \n", - "... ... ... ... ... ... \n", - "1995 0 1 0.00 1 ... \n", - "1996 0 1 0.00 1 ... \n", - "1997 0 1 0.00 1 ... \n", - "1998 0 1 0.00 1 ... \n", - "1999 0 1 0.00 1 ... \n", + " sample_rate income_in_thousands income_segment median_value_of_time \\\n", + "0 1 0.0 1 6.01 \n", + "1 1 14.0 1 6.01 \n", + "2 1 9.6 1 6.01 \n", + "3 1 18.0 1 6.01 \n", + "4 1 14.0 1 6.01 \n", + "... ... ... ... ... \n", + "19995 1 0.0 1 6.01 \n", + "19996 1 0.0 1 6.01 \n", + "19997 1 0.0 1 6.01 \n", + "19998 1 0.0 1 6.01 \n", + "19999 1 0.0 1 6.01 \n", "\n", - " hh_work_auto_savings_ratio num_under16_not_at_school \\\n", - "0 0.0 0 \n", - "1 0.0 0 \n", - "2 0.0 0 \n", - "3 0.0 0 \n", - "4 0.0 0 \n", - "... ... ... \n", - "1995 0.0 0 \n", - "1996 0.0 0 \n", - "1997 0.0 0 \n", - "1998 0.0 0 \n", - "1999 0.0 0 \n", + " ... num_under16_not_at_school num_travel_active \\\n", + "0 ... 0 1 \n", + "1 ... 0 1 \n", + "2 ... 0 1 \n", + "3 ... 0 1 \n", + "4 ... 0 1 \n", + "... ... ... ... \n", + "19995 ... 0 1 \n", + "19996 ... 0 0 \n", + "19997 ... 0 1 \n", + "19998 ... 0 1 \n", + "19999 ... 0 1 \n", "\n", - " num_travel_active num_travel_active_adults \\\n", - "0 1 1 \n", - "1 1 1 \n", - "2 1 1 \n", - "3 1 1 \n", - "4 1 1 \n", - "... ... ... \n", - "1995 1 1 \n", - "1996 1 1 \n", - "1997 1 1 \n", - "1998 1 1 \n", - "1999 1 1 \n", + " num_travel_active_adults num_travel_active_preschoolers \\\n", + "0 1 0 \n", + "1 1 0 \n", + "2 1 0 \n", + "3 1 0 \n", + "4 1 0 \n", + "... ... ... \n", + "19995 1 0 \n", + "19996 0 0 \n", + "19997 1 0 \n", + "19998 1 0 \n", + "19999 1 0 \n", "\n", - " num_travel_active_preschoolers num_travel_active_children \\\n", - "0 0 0 \n", - "1 0 0 \n", - "2 0 0 \n", - "3 0 0 \n", - "4 0 0 \n", - "... ... ... \n", - "1995 0 0 \n", - "1996 0 0 \n", - "1997 0 0 \n", - "1998 0 0 \n", - "1999 0 0 \n", + " num_travel_active_children num_travel_active_non_preschoolers \\\n", + "0 0 1 \n", + "1 0 1 \n", + "2 0 1 \n", + "3 0 1 \n", + "4 0 1 \n", + "... ... ... \n", + "19995 0 1 \n", + "19996 0 0 \n", + "19997 0 1 \n", + "19998 0 1 \n", + "19999 0 1 \n", "\n", - " num_travel_active_non_preschoolers participates_in_jtf_model \\\n", - "0 1 False \n", - "1 1 False \n", - "2 1 False \n", - "3 1 False \n", - "4 1 False \n", - "... ... ... \n", - "1995 1 False \n", - "1996 1 False \n", - "1997 1 False \n", - "1998 1 False \n", - "1999 1 False \n", + " participates_in_jtf_model joint_tour_frequency num_hh_joint_tours \\\n", + "0 False 0_tours 0 \n", + "1 False 0_tours 0 \n", + "2 False 0_tours 0 \n", + "3 False 0_tours 0 \n", + "4 False 0_tours 0 \n", + "... ... ... ... \n", + "19995 False 0_tours 0 \n", + "19996 False 0_tours 0 \n", + "19997 False 0_tours 0 \n", + "19998 False 0_tours 0 \n", + "19999 False 0_tours 0 \n", "\n", - " joint_tour_frequency num_hh_joint_tours \n", - "0 0_tours 0 \n", - "1 0_tours 0 \n", - "2 0_tours 0 \n", - "3 0_tours 0 \n", - "4 0_tours 0 \n", - "... ... ... \n", - "1995 0_tours 0 \n", - "1996 0_tours 0 \n", - "1997 0_tours 0 \n", - "1998 0_tours 0 \n", - "1999 0_tours 0 \n", + " household_id \n", + "0 45 \n", + "1 499 \n", + "2 659 \n", + "3 948 \n", + "4 1276 \n", + "... ... \n", + "19995 2874468 \n", + "19996 2874567 \n", + "19997 2874576 \n", + "19998 2874826 \n", + "19999 2875013 \n", "\n", - "[2000 rows x 35 columns]" + "[20000 rows x 35 columns]" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -567,7 +651,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -602,14 +686,14 @@ " pstudent\n", " ptype\n", " ...\n", - " COLLFTE\n", - " COLLPTE\n", - " TOPOLOGY\n", - " TERMINAL\n", - " household_density\n", - " employment_density\n", - " density_index\n", - " is_cbd\n", + " auOpRetail\n", + " auOpTotal\n", + " trPkRetail\n", + " trPkTotal\n", + " trOpRetail\n", + " trOpTotal\n", + " nmRetail\n", + " nmTotal\n", " chunk_id\n", " cdap_rank\n", " \n", @@ -617,122 +701,122 @@ " \n", " \n", " 0\n", - " 166\n", + " 45\n", " N\n", " N\n", - " 166\n", - " 54\n", + " 45\n", + " 48\n", + " 1\n", " 1\n", - " 2\n", " 3\n", " 3\n", " 4\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.21263\n", - " 24.783133\n", - " 31.566265\n", - " 13.883217\n", - " False\n", + " 9.924660\n", + " 12.562639\n", + " 4.193237\n", + " 6.875144\n", + " 3.952128\n", + " 6.590585\n", + " 2.194792\n", + " 6.359507\n", " 0\n", " 1\n", " \n", " \n", " 1\n", - " 197\n", + " 499\n", " N\n", " N\n", - " 197\n", - " 46\n", + " 499\n", + " 50\n", + " 1\n", " 1\n", - " 2\n", " 3\n", " 3\n", " 4\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.68156\n", - " 56.783784\n", - " 10.459459\n", - " 8.832526\n", - " False\n", + " 10.284673\n", + " 12.868645\n", + " 6.639963\n", + " 9.364105\n", + " 6.531079\n", + " 9.259002\n", + " 5.955868\n", + " 7.795004\n", " 1\n", " 1\n", " \n", " \n", " 2\n", - " 268\n", + " 659\n", " N\n", " N\n", - " 268\n", - " 46\n", + " 659\n", + " 52\n", " 1\n", " 1\n", " 3\n", " 3\n", " 4\n", " ...\n", - " 3598.08521\n", - " 0.00000\n", - " 1\n", - " 3.29100\n", - " 11.947644\n", - " 45.167539\n", - " 9.448375\n", - " True\n", - " 2\n", + " 10.247505\n", + " 12.762286\n", + " 6.001466\n", + " 8.409169\n", + " 5.786652\n", + " 8.279842\n", + " 5.798886\n", + " 7.900061\n", + " 0\n", " 1\n", " \n", " \n", " 3\n", - " 375\n", + " 948\n", " N\n", " N\n", - " 375\n", - " 54\n", + " 948\n", + " 61\n", " 1\n", " 2\n", " 3\n", " 3\n", " 4\n", " ...\n", - " 0.00000\n", - " 0.00000\n", + " 10.150335\n", + " 12.777635\n", + " 5.172974\n", + " 7.850360\n", + " 4.893929\n", + " 7.571579\n", + " 4.895220\n", + " 7.409345\n", " 1\n", - " 4.11499\n", - " 73.040169\n", - " 28.028350\n", - " 20.255520\n", - " True\n", - " 3\n", " 1\n", " \n", " \n", " 4\n", - " 387\n", - " N\n", + " 1276\n", + " H\n", " N\n", - " 387\n", - " 44\n", + " 1276\n", + " 46\n", + " 1\n", " 1\n", - " 2\n", " 3\n", " 3\n", " 4\n", " ...\n", - " 227.78223\n", - " 41.22827\n", - " 1\n", - " 3.83527\n", - " 26.631579\n", - " 45.868421\n", - " 16.848945\n", - " False\n", - " 4\n", + " 10.258471\n", + " 12.759529\n", + " 6.039019\n", + " 8.348963\n", + " 5.778785\n", + " 8.070525\n", + " 6.073537\n", + " 7.851667\n", + " 2\n", " 1\n", " \n", " \n", @@ -760,187 +844,187 @@ " ...\n", " \n", " \n", - " 4400\n", - " 7554799\n", + " 53069\n", + " 7565803\n", " N\n", " N\n", - " 2863464\n", - " 93\n", + " 2874468\n", + " 85\n", " 1\n", " 2\n", " 3\n", " 3\n", " 5\n", " ...\n", - " 72.14684\n", - " 0.00000\n", - " 1\n", - " 5.52555\n", - " 38.187500\n", - " 978.875000\n", - " 36.753679\n", - " False\n", - " 1995\n", + " 8.113608\n", + " 10.265845\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 9998\n", " 1\n", " \n", " \n", - " 4401\n", - " 7554818\n", - " N\n", - " N\n", - " 2863483\n", - " 68\n", - " 1\n", + " 53070\n", + " 7565902\n", + " H\n", + " H\n", + " 2874567\n", + " 87\n", " 1\n", + " 2\n", " 3\n", " 3\n", " 5\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 3\n", - " 3.99027\n", - " 39.838272\n", - " 71.693001\n", - " 25.608291\n", - " True\n", - " 1996\n", + " 6.560015\n", + " 8.886403\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 9997\n", " 1\n", " \n", " \n", - " 4402\n", - " 7555141\n", + " 53071\n", + " 7565911\n", " N\n", " N\n", - " 2863806\n", - " 93\n", + " 2874576\n", + " 85\n", " 1\n", " 2\n", " 3\n", " 3\n", " 5\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 4.27539\n", - " 51.675676\n", - " 47.216216\n", - " 24.672699\n", - " False\n", - " 1997\n", + " 6.560015\n", + " 8.886403\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 9999\n", " 1\n", " \n", " \n", - " 4403\n", - " 7555853\n", + " 53072\n", + " 7566161\n", " N\n", " N\n", - " 2864518\n", - " 71\n", + " 2874826\n", + " 79\n", " 1\n", " 1\n", " 3\n", " 3\n", " 5\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 25.52083\n", - " 15.938148\n", - " 551.353820\n", - " 15.490363\n", - " True\n", - " 1998\n", + " 9.298380\n", + " 11.721935\n", + " 1.052528\n", + " 2.925968\n", + " 0.494776\n", + " 2.006432\n", + " 3.782008\n", + " 6.208875\n", + " 9998\n", " 1\n", " \n", " \n", - " 4404\n", - " 7556023\n", + " 53073\n", + " 7566348\n", " N\n", " N\n", - " 2864688\n", + " 2875013\n", " 93\n", " 1\n", - " 1\n", + " 2\n", " 3\n", " 3\n", " 5\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.29134\n", - " 16.000000\n", - " 31.644068\n", - " 10.626823\n", - " False\n", - " 1999\n", + " 9.588527\n", + " 12.019407\n", + " 3.053361\n", + " 5.871246\n", + " 0.141304\n", + " 0.776133\n", + " 4.090554\n", + " 6.388513\n", + " 9999\n", " 1\n", " \n", " \n", "\n", - "

4405 rows × 110 columns

\n", + "

53074 rows × 110 columns

\n", "" ], "text/plain": [ - " person_id model_choice override_choice household_id age PNUM sex \\\n", - "0 166 N N 166 54 1 2 \n", - "1 197 N N 197 46 1 2 \n", - "2 268 N N 268 46 1 1 \n", - "3 375 N N 375 54 1 2 \n", - "4 387 N N 387 44 1 2 \n", - "... ... ... ... ... ... ... ... \n", - "4400 7554799 N N 2863464 93 1 2 \n", - "4401 7554818 N N 2863483 68 1 1 \n", - "4402 7555141 N N 2863806 93 1 2 \n", - "4403 7555853 N N 2864518 71 1 1 \n", - "4404 7556023 N N 2864688 93 1 1 \n", + " person_id model_choice override_choice household_id age PNUM sex \\\n", + "0 45 N N 45 48 1 1 \n", + "1 499 N N 499 50 1 1 \n", + "2 659 N N 659 52 1 1 \n", + "3 948 N N 948 61 1 2 \n", + "4 1276 H N 1276 46 1 1 \n", + "... ... ... ... ... ... ... ... \n", + "53069 7565803 N N 2874468 85 1 2 \n", + "53070 7565902 H H 2874567 87 1 2 \n", + "53071 7565911 N N 2874576 85 1 2 \n", + "53072 7566161 N N 2874826 79 1 1 \n", + "53073 7566348 N N 2875013 93 1 2 \n", "\n", - " pemploy pstudent ptype ... COLLFTE COLLPTE TOPOLOGY TERMINAL \\\n", - "0 3 3 4 ... 0.00000 0.00000 1 3.21263 \n", - "1 3 3 4 ... 0.00000 0.00000 1 3.68156 \n", - "2 3 3 4 ... 3598.08521 0.00000 1 3.29100 \n", - "3 3 3 4 ... 0.00000 0.00000 1 4.11499 \n", - "4 3 3 4 ... 227.78223 41.22827 1 3.83527 \n", - "... ... ... ... ... ... ... ... ... \n", - "4400 3 3 5 ... 72.14684 0.00000 1 5.52555 \n", - "4401 3 3 5 ... 0.00000 0.00000 3 3.99027 \n", - "4402 3 3 5 ... 0.00000 0.00000 1 4.27539 \n", - "4403 3 3 5 ... 0.00000 0.00000 1 25.52083 \n", - "4404 3 3 5 ... 0.00000 0.00000 1 3.29134 \n", + " pemploy pstudent ptype ... auOpRetail auOpTotal trPkRetail \\\n", + "0 3 3 4 ... 9.924660 12.562639 4.193237 \n", + "1 3 3 4 ... 10.284673 12.868645 6.639963 \n", + "2 3 3 4 ... 10.247505 12.762286 6.001466 \n", + "3 3 3 4 ... 10.150335 12.777635 5.172974 \n", + "4 3 3 4 ... 10.258471 12.759529 6.039019 \n", + "... ... ... ... ... ... ... ... \n", + "53069 3 3 5 ... 8.113608 10.265845 0.000000 \n", + "53070 3 3 5 ... 6.560015 8.886403 0.000000 \n", + "53071 3 3 5 ... 6.560015 8.886403 0.000000 \n", + "53072 3 3 5 ... 9.298380 11.721935 1.052528 \n", + "53073 3 3 5 ... 9.588527 12.019407 3.053361 \n", "\n", - " household_density employment_density density_index is_cbd chunk_id \\\n", - "0 24.783133 31.566265 13.883217 False 0 \n", - "1 56.783784 10.459459 8.832526 False 1 \n", - "2 11.947644 45.167539 9.448375 True 2 \n", - "3 73.040169 28.028350 20.255520 True 3 \n", - "4 26.631579 45.868421 16.848945 False 4 \n", - "... ... ... ... ... ... \n", - "4400 38.187500 978.875000 36.753679 False 1995 \n", - "4401 39.838272 71.693001 25.608291 True 1996 \n", - "4402 51.675676 47.216216 24.672699 False 1997 \n", - "4403 15.938148 551.353820 15.490363 True 1998 \n", - "4404 16.000000 31.644068 10.626823 False 1999 \n", + " trPkTotal trOpRetail trOpTotal nmRetail nmTotal chunk_id \\\n", + "0 6.875144 3.952128 6.590585 2.194792 6.359507 0 \n", + "1 9.364105 6.531079 9.259002 5.955868 7.795004 1 \n", + "2 8.409169 5.786652 8.279842 5.798886 7.900061 0 \n", + "3 7.850360 4.893929 7.571579 4.895220 7.409345 1 \n", + "4 8.348963 5.778785 8.070525 6.073537 7.851667 2 \n", + "... ... ... ... ... ... ... \n", + "53069 0.000000 0.000000 0.000000 0.000000 0.000000 9998 \n", + "53070 0.000000 0.000000 0.000000 0.000000 0.000000 9997 \n", + "53071 0.000000 0.000000 0.000000 0.000000 0.000000 9999 \n", + "53072 2.925968 0.494776 2.006432 3.782008 6.208875 9998 \n", + "53073 5.871246 0.141304 0.776133 4.090554 6.388513 9999 \n", "\n", - " cdap_rank \n", - "0 1 \n", - "1 1 \n", - "2 1 \n", - "3 1 \n", - "4 1 \n", - "... ... \n", - "4400 1 \n", - "4401 1 \n", - "4402 1 \n", - "4403 1 \n", - "4404 1 \n", + " cdap_rank \n", + "0 1 \n", + "1 1 \n", + "2 1 \n", + "3 1 \n", + "4 1 \n", + "... ... \n", + "53069 1 \n", + "53070 1 \n", + "53071 1 \n", + "53072 1 \n", + "53073 1 \n", "\n", - "[4405 rows x 110 columns]" + "[53074 rows x 110 columns]" ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -958,7 +1042,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -1100,7 +1184,7 @@ "[133 rows x 5 columns]" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1118,7 +1202,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -1210,7 +1294,7 @@ "4 coef_UNAVAILABLE coef_retired_asc_N NaN " ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -1219,6 +1303,26 @@ "data.spec1.head()" ] }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['edb_directory', 'person_data', 'spec1', 'interaction_coef', 'coefficients', 'households', 'settings', 'joint_coef', 'add_joint'])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.keys()" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1303,7 +1407,7 @@ { "data": { "text/html": [ - "

Iteration 124 [Optimization terminated successfully]

" + "

Iteration 138 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1315,7 +1419,7 @@ { "data": { "text/html": [ - "

Best LL = -2354.458830163564

" + "

Best LL = -28223.515541250054

" ], "text/plain": [ "" @@ -1346,70 +1450,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " coef_UNAVAILABLE\n", + " -999.0\n", " -999.000000\n", " -999.000000\n", - " 0.0\n", - " NaN\n", - " NaN\n", - " True\n", - " \n", " -999.000000\n", + " -999.0\n", + " -999.0\n", + " 0.0\n", + " 1\n", " \n", " \n", - " coef_child_who_is_in_school_or_too_young_for_school_interaction_with_off_peak_accessibility_to_retail_N\n", - " 0.856930\n", - " 0.082330\n", + " coef_H_11\n", + " 1.446554\n", + " 1.446554\n", + " 1.626000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " 0.856930\n", + " 0\n", " \n", " \n", - " coef_driving_age_child_who_is_in_school_asc_M\n", - " 0.738480\n", - " 2.330919\n", + " coef_H_12\n", + " 0.954554\n", + " 0.954554\n", + " 0.740700\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " 0.738480\n", + " 0\n", " \n", " \n", - " coef_driving_age_child_who_is_in_school_asc_N\n", - " -8.930886\n", - " -0.599119\n", + " coef_H_124_122_144\n", + " 0.353981\n", + " 0.353981\n", + " 0.957300\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " -8.930886\n", + " 0\n", " \n", " \n", - " coef_driving_age_child_who_is_in_school_interaction_income_between_50k_and_100k_H\n", - " -0.938531\n", - " -0.503100\n", + " coef_H_126_146\n", + " -0.013374\n", + " -0.013374\n", + " 0.293900\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " -0.938531\n", + " 0\n", " \n", " \n", " ...\n", @@ -1420,122 +1528,120 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", - " coef_N_124_122_144\n", - " 0.996710\n", - " 0.349100\n", + " coef_retired_interaction_with_more_cars_than_workers_M\n", + " 2.992000\n", + " 2.992000\n", + " 2.992000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " 0.996710\n", + " 0\n", " \n", " \n", - " coef_N_166\n", - " -1.976101\n", - " 0.355300\n", + " coef_retired_interaction_with_more_cars_than_workers_N\n", + " 1.015905\n", + " 1.015905\n", + " 1.056000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " -1.976101\n", + " 0\n", " \n", " \n", - " coef_N_222_224_444\n", - " -2.046233\n", - " -1.386000\n", + " coef_retired_interaction_with_peak_accessibility_to_all_employment_M\n", + " 0.279200\n", + " 0.279200\n", + " 0.279200\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " -2.046233\n", + " 0\n", " \n", " \n", - " coef_N_246_226_446\n", - " -0.859376\n", - " -0.857100\n", + " coef_university_student_asc_M\n", + " 2.169416\n", + " 2.169416\n", + " 2.353595\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " -0.859376\n", + " 0\n", " \n", " \n", - " coef_N_xxxxx\n", - " -0.825691\n", - " -3.453000\n", + " coef_university_student_asc_N\n", + " 0.489431\n", + " 0.489431\n", + " 0.609710\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", - " False\n", - " \n", - " -0.825691\n", + " 0\n", " \n", " \n", "\n", - "

161 rows × 8 columns

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161 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_UNAVAILABLE -999.000000 -999.000000 \n", - "coef_child_who_is_in_school_or_too_young_for_sc... 0.856930 0.082330 \n", - "coef_driving_age_child_who_is_in_school_asc_M 0.738480 2.330919 \n", - "coef_driving_age_child_who_is_in_school_asc_N -8.930886 -0.599119 \n", - "coef_driving_age_child_who_is_in_school_interac... -0.938531 -0.503100 \n", + " value best \\\n", + "param_name \n", + "-999.0 -999.000000 -999.000000 \n", + "coef_H_11 1.446554 1.446554 \n", + "coef_H_12 0.954554 0.954554 \n", + "coef_H_124_122_144 0.353981 0.353981 \n", + "coef_H_126_146 -0.013374 -0.013374 \n", "... ... ... \n", - "coef_N_124_122_144 0.996710 0.349100 \n", - "coef_N_166 -1.976101 0.355300 \n", - "coef_N_222_224_444 -2.046233 -1.386000 \n", - "coef_N_246_226_446 -0.859376 -0.857100 \n", - "coef_N_xxxxx -0.825691 -3.453000 \n", + "coef_retired_interaction_with_more_cars_than_wo... 2.992000 2.992000 \n", + "coef_retired_interaction_with_more_cars_than_wo... 1.015905 1.015905 \n", + "coef_retired_interaction_with_peak_accessibilit... 0.279200 0.279200 \n", + "coef_university_student_asc_M 2.169416 2.169416 \n", + "coef_university_student_asc_N 0.489431 0.489431 \n", "\n", - " nullvalue minimum \\\n", - "coef_UNAVAILABLE 0.0 NaN \n", - "coef_child_who_is_in_school_or_too_young_for_sc... 0.0 NaN \n", - "coef_driving_age_child_who_is_in_school_asc_M 0.0 NaN \n", - "coef_driving_age_child_who_is_in_school_asc_N 0.0 NaN \n", - "coef_driving_age_child_who_is_in_school_interac... 0.0 NaN \n", - "... ... ... \n", - "coef_N_124_122_144 0.0 NaN \n", - "coef_N_166 0.0 NaN \n", - "coef_N_222_224_444 0.0 NaN \n", - "coef_N_246_226_446 0.0 NaN \n", - "coef_N_xxxxx 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "-999.0 -999.000000 -999.0 \n", + "coef_H_11 1.626000 -inf \n", + "coef_H_12 0.740700 -inf \n", + "coef_H_124_122_144 0.957300 -inf \n", + "coef_H_126_146 0.293900 -inf \n", + "... ... ... \n", + "coef_retired_interaction_with_more_cars_than_wo... 2.992000 -inf \n", + "coef_retired_interaction_with_more_cars_than_wo... 1.056000 -inf \n", + "coef_retired_interaction_with_peak_accessibilit... 0.279200 -inf \n", + "coef_university_student_asc_M 2.353595 -inf \n", + "coef_university_student_asc_N 0.609710 -inf \n", "\n", - " maximum holdfast note \\\n", - "coef_UNAVAILABLE NaN True \n", - "coef_child_who_is_in_school_or_too_young_for_sc... NaN False \n", - "coef_driving_age_child_who_is_in_school_asc_M NaN False \n", - "coef_driving_age_child_who_is_in_school_asc_N NaN False \n", - "coef_driving_age_child_who_is_in_school_interac... NaN False \n", - "... ... ... ... \n", - "coef_N_124_122_144 NaN False \n", - "coef_N_166 NaN False \n", - "coef_N_222_224_444 NaN False \n", - "coef_N_246_226_446 NaN False \n", - "coef_N_xxxxx NaN False \n", + " maximum nullvalue \\\n", + "param_name \n", + "-999.0 -999.0 0.0 \n", + "coef_H_11 inf 0.0 \n", + "coef_H_12 inf 0.0 \n", + "coef_H_124_122_144 inf 0.0 \n", + "coef_H_126_146 inf 0.0 \n", + "... ... ... \n", + "coef_retired_interaction_with_more_cars_than_wo... inf 0.0 \n", + "coef_retired_interaction_with_more_cars_than_wo... inf 0.0 \n", + "coef_retired_interaction_with_peak_accessibilit... inf 0.0 \n", + "coef_university_student_asc_M inf 0.0 \n", + "coef_university_student_asc_N inf 0.0 \n", "\n", - " best \n", - "coef_UNAVAILABLE -999.000000 \n", - "coef_child_who_is_in_school_or_too_young_for_sc... 0.856930 \n", - "coef_driving_age_child_who_is_in_school_asc_M 0.738480 \n", - "coef_driving_age_child_who_is_in_school_asc_N -8.930886 \n", - "coef_driving_age_child_who_is_in_school_interac... -0.938531 \n", - "... ... \n", - "coef_N_124_122_144 0.996710 \n", - "coef_N_166 -1.976101 \n", - "coef_N_222_224_444 -2.046233 \n", - "coef_N_246_226_446 -0.859376 \n", - "coef_N_xxxxx -0.825691 \n", + " holdfast \n", + "param_name \n", + "-999.0 1 \n", + "coef_H_11 0 \n", + "coef_H_12 0 \n", + "coef_H_124_122_144 0 \n", + "coef_H_126_146 0 \n", + "... ... \n", + "coef_retired_interaction_with_more_cars_than_wo... 0 \n", + "coef_retired_interaction_with_more_cars_than_wo... 0 \n", + "coef_retired_interaction_with_peak_accessibilit... 0 \n", + "coef_university_student_asc_M 0 \n", + "coef_university_student_asc_N 0 \n", "\n", - "[161 rows x 8 columns]" + "[161 rows x 7 columns]" ] }, "metadata": {}, @@ -1545,12 +1651,9 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " r = model.estimate(method='SLSQP', options={'maxiter':1000})\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.7787895067513534e-43 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - ":1: RuntimeWarning: invalid value encountered in sqrt\n", - " r = model.estimate(method='SLSQP', options={'maxiter':1000})\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/optimization.py:338: UserWarning: SLSQP may not play nicely with unbounded parameters\n", + "if you get poor results, consider setting global bounds with model.set_cap()\n", + " warnings.warn( # infinite bounds # )\n" ] } ], @@ -1566,1704 +1669,4882 @@ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value
coef_UNAVAILABLE-999. 0.00 NA NA 0.00
coef_child_who_is_in_school_or_too_young_for_school_interaction_with_off_peak_accessibility_to_retail_N 0.857 0.618 1.39 NA 0.00
coef_driving_age_child_who_is_in_school_asc_M 0.738 0.649 1.14 NA 0.00
coef_driving_age_child_who_is_in_school_asc_N-8.93 6.17-1.45 NA 0.00
coef_driving_age_child_who_is_in_school_interaction_income_between_50k_and_100k_H-0.939 0.760-1.23 NA 0.00
coef_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H 0.409 0.669 0.61 NA 0.00
coef_driving_age_child_who_is_in_school_interaction_with_income_more_than_100k_H-1.75 0.887-1.97* NA 0.00
coef_driving_age_child_who_is_in_school_interaction_with_less_than_20k_H 0.456 0.807 0.57 NA 0.00
coef_full_time_worker_asc_M 1.03 2.64 0.39 NA 0.00
coef_full_time_worker_asc_N 0.742 0.188 3.95*** NA 0.00
coef_full_time_worker_interaction_with_age_less_than_40_M 0.439 0.131 3.35*** NA 0.00
coef_full_time_worker_interaction_with_female_gender_M 0.0529 0.130 0.41 NA 0.00
coef_full_time_worker_interaction_with_fewer_cars_than_workers_H 0.418 0.192 2.18* NA 0.00
coef_full_time_worker_interaction_with_income_less_than_20k_H 0.359 0.326 1.10 NA 0.00
coef_full_time_worker_intraction_with_peak_accessibility_to_all_employment_M 0.147 0.209 0.70 NA 0.00
coef_non_working_adult_asc_N 0.874 3.96 0.22 NA 0.00
coef_non_working_adult_interaction_with_female_gender_M-0.743 0.0120-62.04*** NA 0.00
coef_non_working_adult_interaction_with_fewer_cars_than_workers_H 0.797 0.336 2.37* NA 0.00
coef_non_working_adult_interaction_with_income_between_50k_and_100k_H-1.23 0.374-3.28** NA 0.00
coef_non_working_adult_interaction_with_income_more_than_100k_H-0.683 0.344-1.98* NA 0.00
coef_non_working_adult_interaction_with_more_cars_than_workers_M 0.651 0.0188 34.73*** NA 0.00
coef_non_working_adult_interaction_with_more_cars_than_workers_N 1.33 0.300 4.42*** NA 0.00
coef_non_working_adult_interaction_with_peak_accessibility_to_all_employment_M 0.231 0.00933 24.80*** NA 0.00
coef_non_working_adult_retired_or_univ_student_interaction_with_off_peak_accessibility_to_all_employment_N 0.0176 0.396 0.04 NA 0.00
coef_part_time_worker_asc_M 4.90 4.19 1.17 NA 0.00
coef_part_time_worker_asc_N 0.659 0.316 2.09* NA 0.00
coef_part_time_worker_interaction_with_income_between_50k_and_100k_H 0.172 0.421 0.41 NA 0.00
coef_part_time_worker_interaction_with_income_less_than_20k_H 0.380 0.411 0.93 NA 0.00
coef_part_time_worker_interaction_with_income_more_than_100k_H-1.36 0.780-1.75 NA 0.00
coef_part_time_worker_interaction_with_income_more_than_100k_N 0.493 0.272 1.81 NA 0.00
coef_part_time_worker_interaction_with_peak_accessibility_to_all_employment_M-0.247 0.330-0.75 NA 0.00
coef_pre_driving_age_child_who_is_in_school_asc_M 3.95 0.527 7.49*** NA 0.00
coef_pre_driving_age_child_who_is_in_school_asc_N-6.81 6.14-1.11 NA 0.00
coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_M-1.55 0.475-3.26** NA 0.00
coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_N-1.15 0.513-2.25* NA 0.00
coef_pre_driving_age_child_who_is_in_school_interaction_with_age_6_to_9_M-0.670 0.371-1.81 NA 0.00
coef_pre_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H 1.10 0.381 2.89** NA 0.00
coef_pre_driving_age_child_who_is_too_young_for_school_asc_M 0.938 0.408 2.30* NA 0.00
coef_pre_driving_age_child_who_is_too_young_for_school_asc_N-8.47 6.15-1.38 NA 0.00
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_0_to_1_M-0.944 0.359-2.63** NA 0.00
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_4_to_5_M 0.239 0.412 0.58 NA 0.00
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_fewer_cars_than_workers_H-0.0626 0.407-0.15 NA 0.00
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_between_50k_and_100k_H-0.723 0.506-1.43 NA 0.00
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_more_than_100k_H-0.783 0.465-1.68 NA 0.00
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_more_cars_than_workers_N 0.772 0.420 1.84 NA 0.00
coef_retired_asc_N 1.54 3.97 0.39 NA 0.00
coef_retired_interaction_with_age_more_than_80_H 1.17 0.248 4.71*** NA 0.00
coef_retired_interaction_with_female_M 0.477 0.00219 218.04*** NA 0.00
coef_retired_interaction_with_fewer_cars_than_workers_H 0.849 0.444 1.91 NA 0.00
coef_retired_interaction_with_income_less_than_20k_H 0.635 0.259 2.45* NA 0.00
coef_retired_interaction_with_more_cars_than_workers_M 2.99 0.00983 304.22*** NA 0.00
coef_retired_interaction_with_more_cars_than_workers_N 0.713 0.256 2.79** NA 0.00
coef_retired_interaction_with_peak_accessibility_to_all_employment_M 0.279 0.0173 16.15*** NA 0.00
coef_university_student_asc_M 2.12 0.255 8.29*** NA 0.00
coef_university_student_asc_N 0.810 3.94 0.21 NA 0.00
-999.0-999. 0.00 NA NA-999.00
coef_H_11 1.48 0.210 7.04*** NA 0.00
coef_H_12-0.0642 0.955-0.07 NA 0.00
coef_H_13 1.49 0.327 4.56*** NA 0.00
coef_H_14 1.21 0.276 4.37*** NA 0.00
coef_H_15 0.966 0.369 2.62** NA 0.00
coef_H_16 1.54 0.345 4.47*** NA 0.00
coef_H_17 1.46 0.227 6.46*** NA 0.00
coef_H_18 1.21 0.309 3.92*** NA 0.00
coef_H_22-20.0 1.16e+03-0.02 NA 0.00
coef_H_23 0.761 1.06 0.72 NA 0.00
coef_H_24 0.966 0.806 1.20 NA 0.00
coef_H_25-18.4 1.22e+04-0.00 NA 0.00
coef_H_26 4.14 1.29 3.20** NA 0.00
coef_H_27 0.402 1.00 0.40 NA 0.00
coef_H_28-17.8 9.45e+03-0.00 NA 0.00
coef_H_33 0.955 0.848 1.13 NA 0.00
coef_H_34 1.56 0.392 3.97*** NA 0.00
coef_H_35-18.3 1.34e+04-0.00 NA 0.00
coef_H_36 1.55 0.0159 97.45*** NA 0.00
coef_H_37 1.55 0.00264 587.28*** NA 0.00
coef_H_38 1.34 0.0149 90.11*** NA 0.00
coef_H_44 1.52 0.412 3.69*** NA 0.00
coef_H_45 2.05 0.499 4.11*** NA 0.00
coef_H_46 0.524 0.00131 399.66*** NA 0.00
coef_H_47 0.811 0.00179 453.41*** NA 0.00
coef_H_48 1.17 0.0131 89.09*** NA 0.00
coef_H_55 1.01 0.517 1.96 NA 0.00
coef_H_56_57_58 0.863 0.0203 42.43*** NA 0.00
coef_H_66 20.8 NA NA[***] 55.85 0.00
coef_H_67-22.2 0.00635-BIG*** NA 0.00
coef_H_68 1.47 0.00299 490.95*** NA 0.00
coef_H_77 2.42 0.504 4.81*** NA 0.00
coef_H_78 18.7 NA NA[***] 7.25 0.00
coef_H_88 1.18 0.582 2.03* NA 0.00
coef_M_11-0.103 0.147-0.70 NA 0.00
coef_M_12 0.243 0.225 1.08 NA 0.00
coef_M_13 0.235 0.156 1.51 NA 0.00
coef_M_16 0.374 0.290 1.29 NA 0.00
coef_M_17-0.124 0.116-1.06 NA 0.00
coef_M_18 0.262 0.167 1.57 NA 0.00
coef_M_22 0.888 0.287 3.10** NA 0.00
coef_M_23 0.170 0.330 0.51 NA 0.00
coef_M_26 1.90 1.13 1.68 NA 0.00
coef_M_27 0.0987 0.189 0.52 NA 0.00
coef_M_28 0.378 0.294 1.28 NA 0.00
coef_M_33 0.470 0.212 2.21* NA 0.00
coef_M_36-0.00210 NA NA[] 0.00 0.00
coef_M_37 0.297 0.000362 822.44*** NA 0.00
coef_M_38 0.225 NA NA[] 0.00 0.00
coef_M_66 19.2 NA NA[***] 35.09 0.00
coef_M_67-21.0 2.08-10.10*** NA 0.00
coef_M_68 0.552 0.000386 BIG*** NA 0.00
coef_M_77 1.17 0.316 3.71*** NA 0.00
coef_M_78-1.62 0.000121-BIG*** NA 0.00
coef_M_88 1.14 0.349 3.28** NA 0.00
coef_N_11 0.776 0.323 2.41* NA 0.00
coef_N_12 0.488 0.429 1.14 NA 0.00
coef_N_13 0.497 0.436 1.14 NA 0.00
coef_N_14-0.360 0.326-1.11 NA 0.00
coef_N_15 0.366 0.242 1.51 NA 0.00
coef_N_16 0.864 0.738 1.17 NA 0.00
coef_N_17-0.155 0.514-0.30 NA 0.00
coef_N_18 0.0616 0.502 0.12 NA 0.00
coef_N_22 0.782 0.611 1.28 NA 0.00
coef_N_23 0.518 0.622 0.83 NA 0.00
coef_N_24 1.21 0.329 3.66*** NA 0.00
coef_N_25-0.304 0.471-0.65 NA 0.00
coef_N_26-17.9 0.143-125.60*** NA 0.00
coef_N_27 0.291 0.521 0.56 NA 0.00
coef_N_28 0.932 0.453 2.06* NA 0.00
coef_N_33 0.976 0.277 3.52*** NA 0.00
coef_N_34-0.197 0.399-0.49 NA 0.00
coef_N_35 0.0721 0.504 0.14 NA 0.00
coef_N_36 1.62 0.00 NA[] 0.00 0.00
coef_N_37 0.516 0.00 NA[] 0.00 0.00
coef_N_38 0.897 0.00 NA[] 0.00 0.00
coef_N_44 0.492 0.450 1.09 NA 0.00
coef_N_45 0.0795 0.354 0.22 NA 0.00
coef_N_46 0.680 0.00 NA[] 0.00 0.00
coef_N_47 0.565 0.00 NA[] 0.00 0.00
coef_N_48 1.16 0.00 NA[] 0.00 0.00
coef_N_55 0.712 0.348 2.04* NA 0.00
coef_N_56_57_58 0.292 0.00 NA[] 0.00 0.00
coef_N_66-3.08 0.00112-BIG*** NA 0.00
coef_N_67-17.1 2.19e+04-0.00 NA 0.00
coef_N_68 1.27 0.00 NA[] 0.00 0.00
coef_N_77 2.27 0.413 5.49*** NA 0.00
coef_N_78-0.396 1.75e-15-BIG*** NA 0.00
coef_N_88-0.184 0.811-0.23 NA 0.00
coef_H_124_122_144 0.693 0.513 1.35 NA 0.00
coef_H_126_146 1.70 1.76 0.97 NA 0.00
coef_H_222_224_244-9.07 1.44e+03-0.01 NA 0.00
coef_H_226_246_446 39.5 1.16e+03 0.03 NA 0.00
coef_H_266_466 0.475 0.00 NA[] 0.00 0.00
coef_H_xxxxx-4.45 1.19-3.74*** NA 0.00
coef_M_111 0.265 0.175 1.51 NA 0.00
coef_M_112_114-0.133 0.365-0.37 NA 0.00
coef_M_666-0.391 0.00 NA[] 0.00 0.00
coef_M_xxxxx-0.0402 0.190-0.21 NA 0.00
coef_N_112_114-0.452 0.881-0.51 NA 0.00
coef_N_124_122_144 0.997 0.535 1.86 NA 0.00
coef_N_166-1.98 1.09e-05-BIG*** NA 0.00
coef_N_222_224_444-2.05 0.981-2.09* NA 0.00
coef_N_246_226_446-0.859 2.50e-18-BIG*** NA 0.00
coef_N_xxxxx-0.826 0.514-1.61 NA 0.00
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.parameter_summary()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "colab_type": "text", - "id": "TojXWivZsx7M" - }, - "source": [ - "# Output Estimation Results" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "from larch.util.activitysim import update_coefficients\n", - "coefficients = update_coefficients(model, data)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "result_dir = data.edb_directory/'estimated'" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "os.makedirs(result_dir, exist_ok=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Write the re-estimated coefficients file" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "coefficients.reset_index().to_csv(\n", - " result_dir/\"cdap_coefficients_revised.csv\", \n", - " index=False,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Write the model estimation report, including coefficient t-statistic and log likelihood" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "for hh_size, submodel in enumerate(model, 1):\n", - " if hh_size > 3: \n", - " break \n", - " # the largest HH sizes have massive model reports that \n", - " # Excel doesn't handle well; review them in Jupyter \n", - " # instead if you are interested\n", - " submodel.to_xlsx(\n", - " result_dir/f\"cdap_model_estimation_hhsize{hh_size}.xlsx\", \n", - " data_statistics=False,\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Next Steps\n", - "\n", - "The final step is to either manually or automatically copy the `cdap_coefficients.csv_revised.csv` file to the configs folder, rename it to `cdap_coefficients.csv.csv`, and run ActivitySim in simulation mode." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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coefficient_namevalueconstrain
 ValueStd Errt StatSignifNull Value
Parameter     
0coef_UNAVAILABLE-999.000000T-999.0-999. 0.00 NA 0.00
1coef_full_time_worker_asc_M1.034987Fcoef_H_11 1.45 0.0614 23.55*** 0.00
2coef_full_time_worker_asc_N0.742053Fcoef_H_12 0.955 0.132 7.21*** 0.00
3coef_part_time_worker_asc_M4.900043Fcoef_H_124_122_144 0.354 0.153 2.31* 0.00
4coef_part_time_worker_asc_N0.659214Fcoef_H_126_146-0.0134 0.336-0.04 0.00
............coef_H_13 1.20 0.130 9.21*** 0.00
161coef_N_xxxx-1.346000Fcoef_H_14 0.998 0.0903 11.05*** 0.00
162coef_H_xxxx-3.733000Fcoef_H_15 1.18 0.0922 12.76*** 0.00
163coef_M_xxxxx-0.040214Fcoef_H_16 1.85 0.102 18.08*** 0.00
164coef_N_xxxxx-0.825691Fcoef_H_17 1.34 0.0557 24.07*** 0.00
165coef_H_xxxxx-4.449197Fcoef_H_18 0.803 0.109 7.36*** 0.00
\n", - "

166 rows × 3 columns

\n", - "
" - ], - "text/plain": [ - " coefficient_name value constrain\n", - "0 coef_UNAVAILABLE -999.000000 T\n", - "1 coef_full_time_worker_asc_M 1.034987 F\n", - "2 coef_full_time_worker_asc_N 0.742053 F\n", - "3 coef_part_time_worker_asc_M 4.900043 F\n", - "4 coef_part_time_worker_asc_N 0.659214 F\n", - ".. ... ... ...\n", - "161 coef_N_xxxx -1.346000 F\n", - "162 coef_H_xxxx -3.733000 F\n", - "163 coef_M_xxxxx -0.040214 F\n", - "164 coef_N_xxxxx -0.825691 F\n", - "165 coef_H_xxxxx -4.449197 F\n", - "\n", - "[166 rows x 3 columns]" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "pd.read_csv(result_dir/\"cdap_coefficients_revised.csv\")" + " \n", + " coef_H_22\n", + "  1.66\n", + "  0.215\n", + "  7.76\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_222_224_244\n", + "  0.0747\n", + "  0.225\n", + "  0.33\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_226_246_446\n", + "  0.0745\n", + "  0.683\n", + "  0.11\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_23\n", + "  1.68\n", + "  0.209\n", + "  8.02\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_24\n", + "  1.20\n", + "  0.165\n", + "  7.27\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_25\n", + " -0.0811\n", + "  0.278\n", + " -0.29\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_26\n", + "  2.83\n", + "  0.239\n", + "  11.83\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_266_466\n", + "  1.24\n", + "  0.650\n", + "  1.91\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_27\n", + "  0.803\n", + "  0.158\n", + "  5.08\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_28\n", + "  0.941\n", + "  0.187\n", + "  5.05\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_33\n", + "  0.359\n", + "  0.448\n", + "  0.80\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_34\n", + "  1.54\n", + "  0.131\n", + "  11.80\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_35\n", + "  0.211\n", + "  0.389\n", + "  0.54\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_36\n", + "  1.55\n", + "  2.55e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_37\n", + "  1.55\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_38\n", + "  1.34\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_44\n", + "  1.09\n", + "  0.0884\n", + "  12.29\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_45\n", + "  1.13\n", + "  0.139\n", + "  8.18\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_46\n", + "  0.524\n", + "  9.04e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_47\n", + "  0.811\n", + "  4.46e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_48\n", + "  1.17\n", + "  2.26e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_55\n", + "  1.22\n", + "  0.166\n", + "  7.37\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_56_57_58\n", + "  0.863\n", + "  1.52e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_66\n", + "  1.36\n", + "  0.299\n", + "  4.56\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_67\n", + "  1.29\n", + "  0.385\n", + "  3.35\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_68\n", + "  1.39\n", + "  0.755\n", + "  1.85\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_H_77\n", + "  2.43\n", + "  0.0802\n", + "  30.27\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_78\n", + "  1.21\n", + "  0.157\n", + "  7.72\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_88\n", + "  0.944\n", + "  0.218\n", + "  4.33\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_H_xxxxx\n", + " -3.46\n", + "  0.269\n", + " -12.86\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_11\n", + "  0.00775\n", + "  0.0439\n", + "  0.18\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_111\n", + "  0.158\n", + "  0.0551\n", + "  2.87\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_M_112_114\n", + "  0.297\n", + "  0.0900\n", + "  3.30\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_12\n", + " -0.109\n", + "  0.0595\n", + " -1.83\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_13\n", + "  0.195\n", + "  0.0448\n", + "  4.36\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_16\n", + "  0.158\n", + "  0.0607\n", + "  2.61\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_M_17\n", + "  0.0366\n", + "  0.0286\n", + "  1.28\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_18\n", + "  0.373\n", + "  0.0438\n", + "  8.53\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_22\n", + "  0.964\n", + "  0.0932\n", + "  10.34\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_23\n", + "  0.107\n", + "  0.0905\n", + "  1.18\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_26\n", + "  0.775\n", + "  0.129\n", + "  5.99\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_27\n", + "  0.0971\n", + "  0.0483\n", + "  2.01\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " coef_M_28\n", + "  0.515\n", + "  0.0771\n", + "  6.68\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_33\n", + "  0.671\n", + "  0.0861\n", + "  7.79\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_36\n", + " -0.00210\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_37\n", + "  0.297\n", + "  3.78e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_38\n", + "  0.225\n", + "  9.09e-14\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_66\n", + "  0.0385\n", + "  0.239\n", + "  0.16\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_666\n", + " -0.673\n", + "  1.46\n", + " -0.46\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_67\n", + "  0.274\n", + "  0.359\n", + "  0.76\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_68\n", + "  0.691\n", + "  0.457\n", + "  1.51\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_77\n", + "  0.700\n", + "  0.0584\n", + "  11.99\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_78\n", + "  0.141\n", + "  0.0957\n", + "  1.48\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_M_88\n", + "  1.33\n", + "  0.0903\n", + "  14.70\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_M_xxxxx\n", + "  0.103\n", + "  0.0498\n", + "  2.07\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " coef_N_11\n", + "  0.914\n", + "  0.0818\n", + "  11.17\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_112_114\n", + "  0.103\n", + "  0.173\n", + "  0.60\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_12\n", + "  0.465\n", + "  0.111\n", + "  4.21\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_124_122_144\n", + "  0.132\n", + "  0.142\n", + "  0.93\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_13\n", + "  0.216\n", + "  0.135\n", + "  1.60\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_14\n", + "  0.0331\n", + "  0.0719\n", + "  0.46\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_15\n", + "  0.0871\n", + "  0.0882\n", + "  0.99\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_16\n", + "  0.308\n", + "  0.222\n", + "  1.38\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_166\n", + "  0.434\n", + "  0.521\n", + "  0.83\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_17\n", + "  0.277\n", + "  0.0921\n", + "  3.01\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_N_18\n", + "  0.297\n", + "  0.0989\n", + "  3.01\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_N_22\n", + "  0.867\n", + "  0.169\n", + "  5.14\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_222_224_444\n", + " -1.34\n", + "  0.194\n", + " -6.91\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_23\n", + "  0.160\n", + "  0.200\n", + "  0.80\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_24\n", + "  0.596\n", + "  0.0737\n", + "  8.09\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_246_226_446\n", + " -0.872\n", + "  5.63\n", + " -0.15\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_25\n", + " -0.0263\n", + "  0.107\n", + " -0.25\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_26\n", + "  0.125\n", + "  0.436\n", + "  0.29\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_27\n", + "  0.733\n", + "  0.0964\n", + "  7.60\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_28\n", + "  1.05\n", + "  0.107\n", + "  9.85\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_33\n", + "  0.781\n", + "  0.165\n", + "  4.72\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_34\n", + " -0.0522\n", + "  0.0980\n", + " -0.53\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_35\n", + "  0.390\n", + "  0.151\n", + "  2.59\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_N_36\n", + "  1.62\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_37\n", + "  0.516\n", + "  1.11e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_38\n", + "  0.897\n", + "  8.33e-14\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_44\n", + "  0.302\n", + "  0.0996\n", + "  3.03\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_N_45\n", + " -0.0876\n", + "  0.0854\n", + " -1.03\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_46\n", + "  0.680\n", + "  3.06e-14\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_47\n", + "  0.565\n", + "  1.01e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_48\n", + "  1.16\n", + "  2.00e-13\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_55\n", + "  0.731\n", + "  0.114\n", + "  6.42\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_56_57_58\n", + "  0.292\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_66\n", + "  1.60\n", + "  0.492\n", + "  3.25\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_N_67\n", + "  1.29\n", + "  0.666\n", + "  1.93\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_68\n", + "  1.14\n", + "  0.897\n", + "  1.27\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_77\n", + "  1.27\n", + "  0.109\n", + "  11.65\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_78\n", + " -0.429\n", + "  0.549\n", + " -0.78\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_N_88\n", + "  0.645\n", + "  0.151\n", + "  4.26\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_N_xxxxx\n", + " -0.0469\n", + "  0.100\n", + " -0.47\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_UNAVAILABLE\n", + " -999.\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_child_who_is_in_school_or_too_young_for_school_interaction_with_off_peak_accessibility_to_retail_N\n", + "  0.138\n", + "  0.0415\n", + "  3.32\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_driving_age_child_who_is_in_school_asc_M\n", + "  2.27\n", + "  0.177\n", + "  12.78\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_driving_age_child_who_is_in_school_asc_N\n", + " -1.09\n", + "  0.445\n", + " -2.45\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " coef_driving_age_child_who_is_in_school_interaction_income_between_50k_and_100k_H\n", + " -0.159\n", + "  0.188\n", + " -0.85\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H\n", + "  0.839\n", + "  0.168\n", + "  4.98\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_driving_age_child_who_is_in_school_interaction_with_income_more_than_100k_H\n", + " -1.57\n", + "  0.241\n", + " -6.53\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_driving_age_child_who_is_in_school_interaction_with_less_than_20k_H\n", + "  1.46\n", + "  0.217\n", + "  6.75\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_full_time_worker_asc_M\n", + "  2.13\n", + "  0.243\n", + "  8.76\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_full_time_worker_asc_N\n", + "  0.651\n", + "  0.0476\n", + "  13.66\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_full_time_worker_interaction_with_age_less_than_40_M\n", + "  0.210\n", + "  0.0388\n", + "  5.41\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_full_time_worker_interaction_with_female_gender_M\n", + " -0.128\n", + "  0.0394\n", + " -3.24\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_full_time_worker_interaction_with_fewer_cars_than_workers_H\n", + "  0.520\n", + "  0.0567\n", + "  9.16\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_full_time_worker_interaction_with_income_less_than_20k_H\n", + "  0.406\n", + "  0.109\n", + "  3.72\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_full_time_worker_intraction_with_peak_accessibility_to_all_employment_M\n", + "  0.0656\n", + "  0.0203\n", + "  3.23\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_asc_N\n", + "  0.697\n", + "  0.354\n", + "  1.97\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_interaction_with_female_gender_M\n", + " -0.743\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_interaction_with_fewer_cars_than_workers_H\n", + "  0.977\n", + "  0.136\n", + "  7.19\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_interaction_with_income_between_50k_and_100k_H\n", + " -0.422\n", + "  0.0839\n", + " -5.03\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_interaction_with_income_more_than_100k_H\n", + " -0.721\n", + "  0.104\n", + " -6.94\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_interaction_with_more_cars_than_workers_M\n", + "  0.651\n", + "  7.21e-15\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_interaction_with_more_cars_than_workers_N\n", + "  0.783\n", + "  0.0828\n", + "  9.45\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_interaction_with_peak_accessibility_to_all_employment_M\n", + "  0.231\n", + "  1.73e-14\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_non_working_adult_retired_or_univ_student_interaction_with_off_peak_accessibility_to_all_employment_N\n", + "  0.0628\n", + "  0.0353\n", + "  1.78\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_part_time_worker_asc_M\n", + " -0.903\n", + "  0.394\n", + " -2.29\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " coef_part_time_worker_asc_N\n", + "  0.677\n", + "  0.0943\n", + "  7.18\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_part_time_worker_interaction_with_income_between_50k_and_100k_H\n", + " -0.470\n", + "  0.120\n", + " -3.93\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_part_time_worker_interaction_with_income_less_than_20k_H\n", + "  0.274\n", + "  0.126\n", + "  2.18\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " coef_part_time_worker_interaction_with_income_more_than_100k_H\n", + " -0.492\n", + "  0.135\n", + " -3.64\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_part_time_worker_interaction_with_income_more_than_100k_N\n", + "  0.334\n", + "  0.0733\n", + "  4.56\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_part_time_worker_interaction_with_peak_accessibility_to_all_employment_M\n", + "  0.218\n", + "  0.0323\n", + "  6.76\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_in_school_asc_M\n", + "  3.24\n", + "  0.104\n", + "  31.22\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_in_school_asc_N\n", + " -0.0676\n", + "  0.411\n", + " -0.16\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_M\n", + " -0.694\n", + "  0.112\n", + " -6.17\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_N\n", + " -0.607\n", + "  0.129\n", + " -4.70\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_in_school_interaction_with_age_6_to_9_M\n", + " -0.400\n", + "  0.0833\n", + " -4.80\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H\n", + "  0.674\n", + "  0.0861\n", + "  7.83\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_too_young_for_school_asc_M\n", + "  0.583\n", + "  0.107\n", + "  5.43\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_too_young_for_school_asc_N\n", + " -1.39\n", + "  0.416\n", + " -3.34\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_0_to_1_M\n", + " -0.393\n", + "  0.0920\n", + " -4.27\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_4_to_5_M\n", + "  0.669\n", + "  0.0978\n", + "  6.84\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_fewer_cars_than_workers_H\n", + "  0.243\n", + "  0.134\n", + "  1.81\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_between_50k_and_100k_H\n", + " -0.707\n", + "  0.128\n", + " -5.51\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_more_than_100k_H\n", + " -0.695\n", + "  0.131\n", + " -5.31\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_more_cars_than_workers_N\n", + "  0.685\n", + "  0.0858\n", + "  7.99\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_retired_asc_N\n", + "  0.434\n", + "  0.359\n", + "  1.21\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_retired_interaction_with_age_more_than_80_H\n", + "  0.730\n", + "  0.0826\n", + "  8.84\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_retired_interaction_with_female_M\n", + "  0.477\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_retired_interaction_with_fewer_cars_than_workers_H\n", + "  0.650\n", + "  0.218\n", + "  2.98\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " coef_retired_interaction_with_income_less_than_20k_H\n", + "  0.476\n", + "  0.0845\n", + "  5.63\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_retired_interaction_with_more_cars_than_workers_M\n", + "  2.99\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_retired_interaction_with_more_cars_than_workers_N\n", + "  1.02\n", + "  0.0885\n", + "  11.48\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_retired_interaction_with_peak_accessibility_to_all_employment_M\n", + "  0.279\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_university_student_asc_M\n", + "  2.17\n", + "  0.0864\n", + "  25.12\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_university_student_asc_N\n", + "  0.489\n", + "  0.356\n", + "  1.38\n", + " \n", + " 0.00\n", + " \n", + " \n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.parameter_summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "TojXWivZsx7M" + }, + "source": [ + "# Output Estimation Results" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "from activitysim.estimation.larch import update_coefficients\n", + "coefficients = update_coefficients(model, data)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "result_dir = data.edb_directory/'estimated'" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "os.makedirs(result_dir, exist_ok=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Write the re-estimated coefficients file" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "coefficients.reset_index().to_csv(\n", + " result_dir/\"cdap_coefficients_revised.csv\", \n", + " index=False,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Write the model estimation report, including coefficient t-statistic and log likelihood" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "for hh_size, submodel in enumerate(model, 1):\n", + " if hh_size > 3: \n", + " break \n", + " # the largest HH sizes have massive model reports that \n", + " # Excel doesn't handle well; review them in Jupyter \n", + " # instead if you are interested\n", + " submodel.to_xlsx(\n", + " result_dir/f\"cdap_model_estimation_hhsize{hh_size}.xlsx\", \n", + " data_statistics=False,\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Next Steps\n", + "\n", + "The final step is to either manually or automatically copy the `cdap_coefficients.csv_revised.csv` file to the configs folder, rename it to `cdap_coefficients.csv.csv`, and run ActivitySim in simulation mode." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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coefficient_namevalueconstrain
0coef_UNAVAILABLE-999.000000T
1coef_full_time_worker_asc_M2.126748F
2coef_full_time_worker_asc_N0.650847F
3coef_part_time_worker_asc_M-0.902594F
4coef_part_time_worker_asc_N0.677144F
............
161coef_N_xxxx-1.346000F
162coef_H_xxxx-3.733000F
163coef_M_xxxxx0.103269F
164coef_N_xxxxx-0.046852F
165coef_H_xxxxx-3.460857F
\n", + "

166 rows × 3 columns

\n", + "
" + ], + "text/plain": [ + " coefficient_name value constrain\n", + "0 coef_UNAVAILABLE -999.000000 T\n", + "1 coef_full_time_worker_asc_M 2.126748 F\n", + "2 coef_full_time_worker_asc_N 0.650847 F\n", + "3 coef_part_time_worker_asc_M -0.902594 F\n", + "4 coef_part_time_worker_asc_N 0.677144 F\n", + ".. ... ... ...\n", + "161 coef_N_xxxx -1.346000 F\n", + "162 coef_H_xxxx -3.733000 F\n", + "163 coef_M_xxxxx 0.103269 F\n", + "164 coef_N_xxxxx -0.046852 F\n", + "165 coef_H_xxxxx -3.460857 F\n", + "\n", + "[166 rows x 3 columns]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pd.read_csv(result_dir/\"cdap_coefficients_revised.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Modify Spec\n", + "\n", + "Here, we will demonstrate the process of re-estimating the CDAP model with a modified\n", + "SPEC file. This does *not* require re-running ActivitySim, it just requires\n", + "changing the SPEC file and re-running the Larch estimation only.\n", + "\n", + "The `backup` command we ran earlier made a backup copy of the\n", + "original spec file in the EDB directory.\n", + "This was not strictly necessary, but since we're about to modify it and\n", + "we may want undo our changes, it can be handy to keep a copy of the\n", + "original spec file around. Since we already have a backup copy, we'll make some \n", + "changes directly in the SPEC file. As an example here, we're going\n", + "to re-write the household income section of the file, to change the piecewise \n", + "linear utility from 3 segments to 4. We'll move the breakpoints and rename some\n", + "coefficients to accomodate the change. As above, for this demo we are editing \n", + "the SPEC file using Python code to make the changes, but a user does not need\n", + "to change the file using Python; any CSV editor (e.g. Excel) can be used. " + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "with open(data.edb_directory / \"cdap_INDIV_AND_HHSIZE1_SPEC.csv\") as f:\n", + " raw_spec = f.read()\n", + "\n", + "repl_lines = \"\"\"Full-time worker interaction with income less than $20k,(ptype == 1) & (income_in_thousands < 20),,,coef_full_time_worker_interaction_with_income_less_than_20k_H\n", + "\"\"\"\n", + "\n", + "new_lines = \"\"\"Full-time worker interaction with income less than $35k,(ptype == 1) & (income_in_thousands < 35),,,coef_full_time_worker_interaction_with_income_less_than_35k_H\n", + "Full-time worker interaction with income between $35k and $100k,(ptype == 1) & (income_in_thousands >= 35) & (income_in_thousands <= 100),,,coef_full_time_worker_interaction_with_income_between_35k_and_100k_H\n", + "\"\"\"\n", + "\n", + "raw_spec = raw_spec.replace(repl_lines, new_lines)\n", + "\n", + "with open(data.edb_directory / \"cdap_INDIV_AND_HHSIZE1_SPEC.csv\", \"w\") as f:\n", + " f.write(raw_spec)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Unlike other components, the CDAP estimation process is built fundamentally against \n", + "a re-evaluation of utility functions, instead of using pre-computed values in the\n", + "EDB. Thus, the user does not need to worry about the \"Label\" column of the utility\n", + "specification file (which in this example does not even exist.) \n", + "\n", + "Estimation of the revised model can be completed using the same process as the \n", + "original estimation." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Reading output-est-mode/estimation_data_bundle/cdap/cdap_model_settings.yaml\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/final_households.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/final_persons.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_coefficients.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_interaction_coefficients.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_joint_tour_coefficients.csv\n", + "Including joint tour utility?: False\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_INDIV_AND_HHSIZE1_SPEC.csv\n", + "Reading /Users/jpn/Git/est-mode/activitysim/activitysim/examples/example_estimation/notebooks/test-estimation-data/activitysim-prototype-mtc-extended/output-est-mode/estimation_data_bundle/cdap/cdap_values_combined.parquet\n" + ] + } + ], + "source": [ + "model2, data2 = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

Iteration 138 [Optimization terminated successfully]

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Best LL = -28225.10715069874

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valuebestinitvalueminimummaximumnullvalueholdfast
param_name
-999.0-999.000000-999.000000-999.000000-999.0-999.00.01
coef_H_111.4550121.4550121.626000-infinf0.00
coef_H_120.9496080.9496080.740700-infinf0.00
coef_H_124_122_1440.3674960.3674960.957300-infinf0.00
coef_H_126_146-0.009021-0.0090210.293900-infinf0.00
........................
coef_retired_interaction_with_more_cars_than_workers_M2.9920002.9920002.992000-infinf0.00
coef_retired_interaction_with_more_cars_than_workers_N1.0128061.0128061.056000-infinf0.00
coef_retired_interaction_with_peak_accessibility_to_all_employment_M0.2792000.2792000.279200-infinf0.00
coef_university_student_asc_M2.1683682.1683682.353595-infinf0.00
coef_university_student_asc_N0.4898480.4898480.609710-infinf0.00
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162 rows × 7 columns

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modelmodel2
Number of CasesAggregate20000.00000020000.000000
Log Likelihood at ConvergenceAggregate-28223.515541-28225.107151
Per Case-1.411176-1.411255
Log Likelihood at Null ParametersAggregate-51107.531825-51107.531825
Per Case-2.555377-2.555377
Rho Squared w.r.t. Null ParametersAggregate0.4477620.447731
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" + ], + "text/plain": [ + " model model2\n", + "Number of Cases Aggregate 20000.000000 20000.000000\n", + "Log Likelihood at Convergence Aggregate -28223.515541 -28225.107151\n", + " Per Case -1.411176 -1.411255\n", + "Log Likelihood at Null Parameters Aggregate -51107.531825 -51107.531825\n", + " Per Case -2.555377 -2.555377\n", + "Rho Squared w.r.t. Null Parameters Aggregate 0.447762 0.447731" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with pd.option_context('display.max_rows', 999):\n", + " display(pd.concat({\n", + " \"model\": model.estimation_statistics_raw(),\n", + " \"model2\": model2.estimation_statistics_raw(),\n", + " }, axis=1).fillna(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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modelmodel2
ValueStd Errt StatSignifNull ValueValueStd Errt StatSignifNull Value
Parameter
-999.0-999.0.00NA0.0-999.0.00NA0.0
coef_H_111.450.061423.55***0.01.460.062223.40***0.0
coef_H_120.9550.1327.21***0.00.9500.1327.18***0.0
coef_H_124_122_1440.3540.1532.31*0.00.3670.1532.40*0.0
coef_H_126_146-0.01340.336-0.040.0-0.009020.336-0.030.0
coef_H_131.200.1309.21***0.01.200.1319.17***0.0
coef_H_140.9980.090311.05***0.00.9910.090410.96***0.0
coef_H_151.180.092212.76***0.01.180.092112.86***0.0
coef_H_161.850.10218.08***0.01.850.10317.98***0.0
coef_H_171.340.055724.07***0.01.340.055824.04***0.0
coef_H_180.8030.1097.36***0.00.8080.1097.42***0.0
coef_H_221.660.2157.76***0.01.660.2157.73***0.0
coef_H_222_224_2440.07470.2250.330.00.08040.2250.360.0
coef_H_226_246_4460.07450.6830.110.00.07260.6870.110.0
coef_H_231.680.2098.02***0.01.680.2098.03***0.0
coef_H_241.200.1657.27***0.01.200.1657.24***0.0
coef_H_25-0.08110.278-0.290.0-0.07370.277-0.270.0
coef_H_262.830.23911.83***0.02.840.23911.86***0.0
coef_H_266_4661.240.6501.910.01.250.6521.910.0
coef_H_270.8030.1585.08***0.00.8040.1585.07***0.0
coef_H_280.9410.1875.05***0.00.9460.1865.08***0.0
coef_H_330.3590.4480.800.00.3660.4480.820.0
coef_H_341.540.13111.80***0.01.540.13111.75***0.0
coef_H_350.2110.3890.540.00.2130.3890.550.0
coef_H_361.552.55e-13BIG***0.01.55NANA0.0
coef_H_371.55NANA0.01.55NANA0.0
coef_H_381.34NANA0.01.344.18e-13BIG***0.0
coef_H_441.090.088412.29***0.01.090.088312.30***0.0
coef_H_451.130.1398.18***0.01.130.1398.16***0.0
coef_H_460.5249.04e-13BIG***0.00.5243.12e-13BIG***0.0
coef_H_470.8114.46e-13BIG***0.00.811NANA0.0
coef_H_481.172.26e-13BIG***0.01.176.30e-13BIG***0.0
coef_H_551.220.1667.37***0.01.220.1657.39***0.0
coef_H_56_57_580.8631.52e-13BIG***0.00.863NANA0.0
coef_H_661.360.2994.56***0.01.370.2984.60***0.0
coef_H_671.290.3853.35***0.01.280.3863.32***0.0
coef_H_681.390.7551.850.01.390.7561.830.0
coef_H_772.430.080230.27***0.02.420.080430.16***0.0
coef_H_781.210.1577.72***0.01.210.1577.69***0.0
coef_H_880.9440.2184.33***0.00.9560.2174.40***0.0
coef_H_xxxxx-3.460.269-12.86***0.0-3.470.269-12.88***0.0
coef_M_110.007750.04390.180.09.36e-050.04430.000.0
coef_M_1110.1580.05512.87**0.00.1640.05522.96**0.0
coef_M_112_1140.2970.09003.30***0.00.2950.09003.28**0.0
coef_M_12-0.1090.0595-1.830.0-0.1090.0595-1.830.0
coef_M_130.1950.04484.36***0.00.1970.04484.39***0.0
coef_M_160.1580.06072.61**0.00.1590.06072.63**0.0
coef_M_170.03660.02861.280.00.03720.02861.300.0
coef_M_180.3730.04388.53***0.00.3720.04388.49***0.0
coef_M_220.9640.093210.34***0.00.9660.093310.36***0.0
coef_M_230.1070.09051.180.00.1070.09051.180.0
coef_M_260.7750.1295.99***0.00.7760.1296.00***0.0
coef_M_270.09710.04832.01*0.00.09430.04821.950.0
coef_M_280.5150.07716.68***0.00.5150.07716.68***0.0
coef_M_330.6710.08617.79***0.00.6730.08627.81***0.0
coef_M_36-0.00210NANA0.0-0.00210NANA0.0
coef_M_370.2973.78e-13BIG***0.00.2973.67e-13BIG***0.0
coef_M_380.2259.09e-14BIG***0.00.2254.32e-13BIG***0.0
coef_M_660.03850.2390.160.00.04220.2400.180.0
coef_M_666-0.6731.46-0.460.0-0.6711.46-0.460.0
coef_M_670.2740.3590.760.00.2880.3600.800.0
coef_M_680.6910.4571.510.00.6950.4571.520.0
coef_M_770.7000.058411.99***0.00.7030.058412.03***0.0
coef_M_780.1410.09571.480.00.1410.09571.480.0
coef_M_881.330.090314.70***0.01.330.090314.70***0.0
coef_M_xxxxx0.1030.04982.07*0.00.1050.04982.10*0.0
coef_N_110.9140.081811.17***0.00.9150.081611.21***0.0
coef_N_112_1140.1030.1730.600.00.1040.1740.600.0
coef_N_120.4650.1114.21***0.00.4670.1114.22***0.0
coef_N_124_122_1440.1320.1420.930.00.1280.1430.900.0
coef_N_130.2160.1351.600.00.2110.1351.570.0
coef_N_140.03310.07190.460.00.02710.07200.380.0
coef_N_150.08710.08820.990.00.08940.08811.010.0
coef_N_160.3080.2221.380.00.3090.2231.390.0
coef_N_1660.4340.5210.830.00.4330.5250.820.0
coef_N_170.2770.09213.01**0.00.2800.09193.04**0.0
coef_N_180.2970.09893.01**0.00.2990.09893.02**0.0
coef_N_220.8670.1695.14***0.00.8670.1695.14***0.0
coef_N_222_224_444-1.340.194-6.91***0.0-1.350.195-6.91***0.0
coef_N_230.1600.2000.800.00.1650.2000.830.0
coef_N_240.5960.07378.09***0.00.5950.07378.07***0.0
coef_N_246_226_446-0.8725.63-0.150.0-0.8725.62-0.160.0
coef_N_25-0.02630.107-0.250.0-0.02750.107-0.260.0
coef_N_260.1250.4360.290.00.1260.4360.290.0
coef_N_270.7330.09647.60***0.00.7340.09617.64***0.0
coef_N_281.050.1079.85***0.01.050.1079.85***0.0
coef_N_330.7810.1654.72***0.00.7860.1654.77***0.0
coef_N_34-0.05220.0980-0.530.0-0.05110.0979-0.520.0
coef_N_350.3900.1512.59**0.00.3900.1502.59**0.0
coef_N_361.62NANA0.01.62NANA0.0
coef_N_370.5161.11e-13BIG***0.00.516NANA0.0
coef_N_380.8978.33e-14BIG***0.00.8972.96e-13BIG***0.0
coef_N_440.3020.09963.03**0.00.3000.09963.01**0.0
coef_N_45-0.08760.0854-1.030.0-0.09020.0854-1.060.0
coef_N_460.6803.06e-14BIG***0.00.6802.86e-13BIG***0.0
coef_N_470.5651.01e-13BIG***0.00.5652.67e-13BIG***0.0
coef_N_481.162.00e-13BIG***0.01.162.34e-13BIG***0.0
coef_N_550.7310.1146.42***0.00.7290.1146.41***0.0
coef_N_56_57_580.292NANA0.00.292NANA0.0
coef_N_661.600.4923.25**0.01.600.4953.23**0.0
coef_N_671.290.6661.930.01.290.6731.920.0
coef_N_681.140.8971.270.01.140.8991.270.0
coef_N_771.270.10911.65***0.01.280.10911.68***0.0
coef_N_78-0.4290.549-0.780.0-0.4210.546-0.770.0
coef_N_880.6450.1514.26***0.00.6450.1514.26***0.0
coef_N_xxxxx-0.04690.100-0.470.0-0.04460.100-0.440.0
coef_UNAVAILABLE-999.0.00NA0.0-999.0.00NA0.0
coef_child_who_is_in_school_or_too_young_for_school_interaction_with_off_peak_accessibility_to_retail_N0.1380.04153.32***0.00.1390.04163.35***0.0
coef_driving_age_child_who_is_in_school_asc_M2.270.17712.78***0.02.300.17812.94***0.0
coef_driving_age_child_who_is_in_school_asc_N-1.090.445-2.45*0.0-1.060.445-2.39*0.0
coef_driving_age_child_who_is_in_school_interaction_income_between_50k_and_100k_H-0.1590.188-0.850.0-0.1320.188-0.700.0
coef_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H0.8390.1684.98***0.00.8360.1684.96***0.0
coef_driving_age_child_who_is_in_school_interaction_with_income_more_than_100k_H-1.570.241-6.53***0.0-1.510.242-6.24***0.0
coef_driving_age_child_who_is_in_school_interaction_with_less_than_20k_H1.460.2176.75***0.01.530.2167.05***0.0
coef_full_time_worker_asc_M2.130.2438.76***0.02.180.2468.88***0.0
coef_full_time_worker_asc_N0.6510.047613.66***0.00.6930.057412.07***0.0
coef_full_time_worker_interaction_with_age_less_than_40_M0.2100.03885.41***0.00.2160.03895.54***0.0
coef_full_time_worker_interaction_with_female_gender_M-0.1280.0394-3.24**0.0-0.1240.0394-3.15**0.0
coef_full_time_worker_interaction_with_fewer_cars_than_workers_H0.5200.05679.16***0.00.5280.05689.29***0.0
coef_full_time_worker_interaction_with_income_less_than_20k_H0.4060.1093.72***0.0
coef_full_time_worker_intraction_with_peak_accessibility_to_all_employment_M0.06560.02033.23**0.00.06420.02033.16**0.0
coef_non_working_adult_asc_N0.6970.3541.97*0.00.6980.3541.97*0.0
coef_non_working_adult_interaction_with_female_gender_M-0.743NANA0.0-0.7433.86e-14-BIG***0.0
coef_non_working_adult_interaction_with_fewer_cars_than_workers_H0.9770.1367.19***0.00.9780.1367.19***0.0
coef_non_working_adult_interaction_with_income_between_50k_and_100k_H-0.4220.0839-5.03***0.0-0.4240.0839-5.05***0.0
coef_non_working_adult_interaction_with_income_more_than_100k_H-0.7210.104-6.94***0.0-0.7160.104-6.89***0.0
coef_non_working_adult_interaction_with_more_cars_than_workers_M0.6517.21e-15BIG***0.00.651NANA0.0
coef_non_working_adult_interaction_with_more_cars_than_workers_N0.7830.08289.45***0.00.7810.08289.43***0.0
coef_non_working_adult_interaction_with_peak_accessibility_to_all_employment_M0.2311.73e-14BIG***0.00.2318.76e-15BIG***0.0
coef_non_working_adult_retired_or_univ_student_interaction_with_off_peak_accessibility_to_all_employment_N0.06280.03531.780.00.06290.03521.790.0
coef_part_time_worker_asc_M-0.9030.394-2.29*0.0-0.9000.394-2.29*0.0
coef_part_time_worker_asc_N0.6770.09437.18***0.00.6790.09447.19***0.0
coef_part_time_worker_interaction_with_income_between_50k_and_100k_H-0.4700.120-3.93***0.0-0.4710.120-3.93***0.0
coef_part_time_worker_interaction_with_income_less_than_20k_H0.2740.1262.18*0.00.2780.1262.21*0.0
coef_part_time_worker_interaction_with_income_more_than_100k_H-0.4920.135-3.64***0.0-0.4880.135-3.61***0.0
coef_part_time_worker_interaction_with_income_more_than_100k_N0.3340.07334.56***0.00.3340.07344.55***0.0
coef_part_time_worker_interaction_with_peak_accessibility_to_all_employment_M0.2180.03236.76***0.00.2180.03236.75***0.0
coef_pre_driving_age_child_who_is_in_school_asc_M3.240.10431.22***0.03.240.10431.19***0.0
coef_pre_driving_age_child_who_is_in_school_asc_N-0.06760.411-0.160.0-0.07780.412-0.190.0
coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_M-0.6940.112-6.17***0.0-0.6970.112-6.19***0.0
coef_pre_driving_age_child_who_is_in_school_interaction_with_age_13_to_15_N-0.6070.129-4.70***0.0-0.6050.129-4.69***0.0
coef_pre_driving_age_child_who_is_in_school_interaction_with_age_6_to_9_M-0.4000.0833-4.80***0.0-0.3980.0834-4.77***0.0
coef_pre_driving_age_child_who_is_in_school_interaction_with_fewer_cars_than_workers_H0.6740.08617.83***0.00.6760.08627.84***0.0
coef_pre_driving_age_child_who_is_too_young_for_school_asc_M0.5830.1075.43***0.00.5870.1075.47***0.0
coef_pre_driving_age_child_who_is_too_young_for_school_asc_N-1.390.416-3.34***0.0-1.400.417-3.36***0.0
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_0_to_1_M-0.3930.0920-4.27***0.0-0.3920.0920-4.27***0.0
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_age_4_to_5_M0.6690.09786.84***0.00.6700.09786.85***0.0
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_fewer_cars_than_workers_H0.2430.1341.810.00.2430.1341.820.0
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_between_50k_and_100k_H-0.7070.128-5.51***0.0-0.7080.128-5.52***0.0
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_income_more_than_100k_H-0.6950.131-5.31***0.0-0.6880.131-5.26***0.0
coef_pre_driving_age_child_who_is_too_young_for_school_interaction_with_more_cars_than_workers_N0.6850.08587.99***0.00.6860.08587.99***0.0
coef_retired_asc_N0.4340.3591.210.00.4390.3591.220.0
coef_retired_interaction_with_age_more_than_80_H0.7300.08268.84***0.00.7320.08258.87***0.0
coef_retired_interaction_with_female_M0.4770.00NA0.00.4770.00NA0.0
coef_retired_interaction_with_fewer_cars_than_workers_H0.6500.2182.98**0.00.6490.2182.97**0.0
coef_retired_interaction_with_income_less_than_20k_H0.4760.08455.63***0.00.4830.08445.72***0.0
coef_retired_interaction_with_more_cars_than_workers_M2.990.00NA0.02.990.00NA0.0
coef_retired_interaction_with_more_cars_than_workers_N1.020.088511.48***0.01.010.088411.45***0.0
coef_retired_interaction_with_peak_accessibility_to_all_employment_M0.2790.00NA0.00.2790.00NA0.0
coef_university_student_asc_M2.170.086425.12***0.02.170.086425.10***0.0
coef_university_student_asc_N0.4890.3561.380.00.4900.3561.380.0
coef_full_time_worker_interaction_with_income_between_35k_and_100k_H0.05410.05421.000.0
coef_full_time_worker_interaction_with_income_less_than_35k_H0.2450.07953.08**0.0
\n", + "
" + ], + "text/plain": [ + " model \\\n", + " Value Std Err \n", + "Parameter \n", + "-999.0 -999.  0.00 \n", + "coef_H_11  1.45  0.0614 \n", + "coef_H_12  0.955  0.132 \n", + "coef_H_124_122_144  0.354  0.153 \n", + "coef_H_126_146 -0.0134  0.336 \n", + "coef_H_13  1.20  0.130 \n", + "coef_H_14  0.998  0.0903 \n", + "coef_H_15  1.18  0.0922 \n", + "coef_H_16  1.85  0.102 \n", + "coef_H_17  1.34  0.0557 \n", + "coef_H_18  0.803  0.109 \n", + "coef_H_22  1.66  0.215 \n", + "coef_H_222_224_244  0.0747  0.225 \n", + "coef_H_226_246_446  0.0745  0.683 \n", + "coef_H_23  1.68  0.209 \n", + "coef_H_24  1.20  0.165 \n", + "coef_H_25 -0.0811  0.278 \n", + "coef_H_26  2.83  0.239 \n", + "coef_H_266_466  1.24  0.650 \n", + "coef_H_27  0.803  0.158 \n", + "coef_H_28  0.941  0.187 \n", + "coef_H_33  0.359  0.448 \n", + "coef_H_34  1.54  0.131 \n", + "coef_H_35  0.211  0.389 \n", + "coef_H_36  1.55  2.55e-13 \n", + "coef_H_37  1.55  NA \n", + "coef_H_38  1.34  NA \n", + "coef_H_44  1.09  0.0884 \n", + "coef_H_45  1.13  0.139 \n", + "coef_H_46  0.524  9.04e-13 \n", + "coef_H_47  0.811  4.46e-13 \n", + "coef_H_48  1.17  2.26e-13 \n", + "coef_H_55  1.22  0.166 \n", + "coef_H_56_57_58  0.863  1.52e-13 \n", + "coef_H_66  1.36  0.299 \n", + "coef_H_67  1.29  0.385 \n", + "coef_H_68  1.39  0.755 \n", + "coef_H_77  2.43  0.0802 \n", + "coef_H_78  1.21  0.157 \n", + "coef_H_88  0.944  0.218 \n", + "coef_H_xxxxx -3.46  0.269 \n", + "coef_M_11  0.00775  0.0439 \n", + "coef_M_111  0.158  0.0551 \n", + "coef_M_112_114  0.297  0.0900 \n", + "coef_M_12 -0.109  0.0595 \n", + "coef_M_13  0.195  0.0448 \n", + "coef_M_16  0.158  0.0607 \n", + "coef_M_17  0.0366  0.0286 \n", + "coef_M_18  0.373  0.0438 \n", + "coef_M_22  0.964  0.0932 \n", + "coef_M_23  0.107  0.0905 \n", + "coef_M_26  0.775  0.129 \n", + "coef_M_27  0.0971  0.0483 \n", + "coef_M_28  0.515  0.0771 \n", + "coef_M_33  0.671  0.0861 \n", + "coef_M_36 -0.00210  NA \n", + "coef_M_37  0.297  3.78e-13 \n", + "coef_M_38  0.225  9.09e-14 \n", + "coef_M_66  0.0385  0.239 \n", + "coef_M_666 -0.673  1.46 \n", + "coef_M_67  0.274  0.359 \n", + "coef_M_68  0.691  0.457 \n", + "coef_M_77  0.700  0.0584 \n", + "coef_M_78  0.141  0.0957 \n", + "coef_M_88  1.33  0.0903 \n", + "coef_M_xxxxx  0.103  0.0498 \n", + "coef_N_11  0.914  0.0818 \n", + "coef_N_112_114  0.103  0.173 \n", + "coef_N_12  0.465  0.111 \n", + "coef_N_124_122_144  0.132  0.142 \n", + "coef_N_13  0.216  0.135 \n", + "coef_N_14  0.0331  0.0719 \n", + "coef_N_15  0.0871  0.0882 \n", + "coef_N_16  0.308  0.222 \n", + "coef_N_166  0.434  0.521 \n", + "coef_N_17  0.277  0.0921 \n", + "coef_N_18  0.297  0.0989 \n", + "coef_N_22  0.867  0.169 \n", + "coef_N_222_224_444 -1.34  0.194 \n", + "coef_N_23  0.160  0.200 \n", + "coef_N_24  0.596  0.0737 \n", + "coef_N_246_226_446 -0.872  5.63 \n", + "coef_N_25 -0.0263  0.107 \n", + "coef_N_26  0.125  0.436 \n", + "coef_N_27  0.733  0.0964 \n", + "coef_N_28  1.05  0.107 \n", + "coef_N_33  0.781  0.165 \n", + "coef_N_34 -0.0522  0.0980 \n", + "coef_N_35  0.390  0.151 \n", + "coef_N_36  1.62  NA \n", + "coef_N_37  0.516  1.11e-13 \n", + "coef_N_38  0.897  8.33e-14 \n", + "coef_N_44  0.302  0.0996 \n", + "coef_N_45 -0.0876  0.0854 \n", + "coef_N_46  0.680  3.06e-14 \n", + "coef_N_47  0.565  1.01e-13 \n", + "coef_N_48  1.16  2.00e-13 \n", + "coef_N_55  0.731  0.114 \n", + "coef_N_56_57_58  0.292  NA \n", + "coef_N_66  1.60  0.492 \n", + "coef_N_67  1.29  0.666 \n", + "coef_N_68  1.14  0.897 \n", + "coef_N_77  1.27  0.109 \n", + "coef_N_78 -0.429  0.549 \n", + "coef_N_88  0.645  0.151 \n", + "coef_N_xxxxx -0.0469  0.100 \n", + "coef_UNAVAILABLE -999.  0.00 \n", + "coef_child_who_is_in_school_or_too_young_for_sc...  0.138  0.0415 \n", + "coef_driving_age_child_who_is_in_school_asc_M  2.27  0.177 \n", + "coef_driving_age_child_who_is_in_school_asc_N -1.09  0.445 \n", + "coef_driving_age_child_who_is_in_school_interac... -0.159  0.188 \n", + "coef_driving_age_child_who_is_in_school_interac...  0.839  0.168 \n", + "coef_driving_age_child_who_is_in_school_interac... -1.57  0.241 \n", + "coef_driving_age_child_who_is_in_school_interac...  1.46  0.217 \n", + "coef_full_time_worker_asc_M  2.13  0.243 \n", + "coef_full_time_worker_asc_N  0.651  0.0476 \n", + "coef_full_time_worker_interaction_with_age_less...  0.210  0.0388 \n", + "coef_full_time_worker_interaction_with_female_g... -0.128  0.0394 \n", + "coef_full_time_worker_interaction_with_fewer_ca...  0.520  0.0567 \n", + "coef_full_time_worker_interaction_with_income_l...  0.406  0.109 \n", + "coef_full_time_worker_intraction_with_peak_acce...  0.0656  0.0203 \n", + "coef_non_working_adult_asc_N  0.697  0.354 \n", + "coef_non_working_adult_interaction_with_female_... -0.743  NA \n", + "coef_non_working_adult_interaction_with_fewer_c...  0.977  0.136 \n", + "coef_non_working_adult_interaction_with_income_... -0.422  0.0839 \n", + "coef_non_working_adult_interaction_with_income_... -0.721  0.104 \n", + "coef_non_working_adult_interaction_with_more_ca...  0.651  7.21e-15 \n", + "coef_non_working_adult_interaction_with_more_ca...  0.783  0.0828 \n", + "coef_non_working_adult_interaction_with_peak_ac...  0.231  1.73e-14 \n", + "coef_non_working_adult_retired_or_univ_student_...  0.0628  0.0353 \n", + "coef_part_time_worker_asc_M -0.903  0.394 \n", + "coef_part_time_worker_asc_N  0.677  0.0943 \n", + "coef_part_time_worker_interaction_with_income_b... -0.470  0.120 \n", + "coef_part_time_worker_interaction_with_income_l...  0.274  0.126 \n", + "coef_part_time_worker_interaction_with_income_m... -0.492  0.135 \n", + "coef_part_time_worker_interaction_with_income_m...  0.334  0.0733 \n", + "coef_part_time_worker_interaction_with_peak_acc...  0.218  0.0323 \n", + "coef_pre_driving_age_child_who_is_in_school_asc_M  3.24  0.104 \n", + "coef_pre_driving_age_child_who_is_in_school_asc_N -0.0676  0.411 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -0.694  0.112 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -0.607  0.129 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -0.400  0.0833 \n", + "coef_pre_driving_age_child_who_is_in_school_int...  0.674  0.0861 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  0.583  0.107 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -1.39  0.416 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -0.393  0.0920 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  0.669  0.0978 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  0.243  0.134 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -0.707  0.128 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -0.695  0.131 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  0.685  0.0858 \n", + "coef_retired_asc_N  0.434  0.359 \n", + "coef_retired_interaction_with_age_more_than_80_H  0.730  0.0826 \n", + "coef_retired_interaction_with_female_M  0.477  0.00 \n", + "coef_retired_interaction_with_fewer_cars_than_w...  0.650  0.218 \n", + "coef_retired_interaction_with_income_less_than_...  0.476  0.0845 \n", + "coef_retired_interaction_with_more_cars_than_wo...  2.99  0.00 \n", + "coef_retired_interaction_with_more_cars_than_wo...  1.02  0.0885 \n", + "coef_retired_interaction_with_peak_accessibilit...  0.279  0.00 \n", + "coef_university_student_asc_M  2.17  0.0864 \n", + "coef_university_student_asc_N  0.489  0.356 \n", + "coef_full_time_worker_interaction_with_income_b... \n", + "coef_full_time_worker_interaction_with_income_l... \n", + "\n", + " \\\n", + " t Stat Signif Null Value \n", + "Parameter \n", + "-999.0  NA 0.0 \n", + "coef_H_11  23.55 *** 0.0 \n", + "coef_H_12  7.21 *** 0.0 \n", + "coef_H_124_122_144  2.31 * 0.0 \n", + "coef_H_126_146 -0.04 0.0 \n", + "coef_H_13  9.21 *** 0.0 \n", + "coef_H_14  11.05 *** 0.0 \n", + "coef_H_15  12.76 *** 0.0 \n", + "coef_H_16  18.08 *** 0.0 \n", + "coef_H_17  24.07 *** 0.0 \n", + "coef_H_18  7.36 *** 0.0 \n", + "coef_H_22  7.76 *** 0.0 \n", + "coef_H_222_224_244  0.33 0.0 \n", + "coef_H_226_246_446  0.11 0.0 \n", + "coef_H_23  8.02 *** 0.0 \n", + "coef_H_24  7.27 *** 0.0 \n", + "coef_H_25 -0.29 0.0 \n", + "coef_H_26  11.83 *** 0.0 \n", + "coef_H_266_466  1.91 0.0 \n", + "coef_H_27  5.08 *** 0.0 \n", + "coef_H_28  5.05 *** 0.0 \n", + "coef_H_33  0.80 0.0 \n", + "coef_H_34  11.80 *** 0.0 \n", + "coef_H_35  0.54 0.0 \n", + "coef_H_36  BIG *** 0.0 \n", + "coef_H_37  NA 0.0 \n", + "coef_H_38  NA 0.0 \n", + "coef_H_44  12.29 *** 0.0 \n", + "coef_H_45  8.18 *** 0.0 \n", + "coef_H_46  BIG *** 0.0 \n", + "coef_H_47  BIG *** 0.0 \n", + "coef_H_48  BIG *** 0.0 \n", + "coef_H_55  7.37 *** 0.0 \n", + "coef_H_56_57_58  BIG *** 0.0 \n", + "coef_H_66  4.56 *** 0.0 \n", + "coef_H_67  3.35 *** 0.0 \n", + "coef_H_68  1.85 0.0 \n", + "coef_H_77  30.27 *** 0.0 \n", + "coef_H_78  7.72 *** 0.0 \n", + "coef_H_88  4.33 *** 0.0 \n", + "coef_H_xxxxx -12.86 *** 0.0 \n", + "coef_M_11  0.18 0.0 \n", + "coef_M_111  2.87 ** 0.0 \n", + "coef_M_112_114  3.30 *** 0.0 \n", + "coef_M_12 -1.83 0.0 \n", + "coef_M_13  4.36 *** 0.0 \n", + "coef_M_16  2.61 ** 0.0 \n", + "coef_M_17  1.28 0.0 \n", + "coef_M_18  8.53 *** 0.0 \n", + "coef_M_22  10.34 *** 0.0 \n", + "coef_M_23  1.18 0.0 \n", + "coef_M_26  5.99 *** 0.0 \n", + "coef_M_27  2.01 * 0.0 \n", + "coef_M_28  6.68 *** 0.0 \n", + "coef_M_33  7.79 *** 0.0 \n", + "coef_M_36  NA 0.0 \n", + "coef_M_37  BIG *** 0.0 \n", + "coef_M_38  BIG *** 0.0 \n", + "coef_M_66  0.16 0.0 \n", + "coef_M_666 -0.46 0.0 \n", + "coef_M_67  0.76 0.0 \n", + "coef_M_68  1.51 0.0 \n", + "coef_M_77  11.99 *** 0.0 \n", + "coef_M_78  1.48 0.0 \n", + "coef_M_88  14.70 *** 0.0 \n", + "coef_M_xxxxx  2.07 * 0.0 \n", + "coef_N_11  11.17 *** 0.0 \n", + "coef_N_112_114  0.60 0.0 \n", + "coef_N_12  4.21 *** 0.0 \n", + "coef_N_124_122_144  0.93 0.0 \n", + "coef_N_13  1.60 0.0 \n", + "coef_N_14  0.46 0.0 \n", + "coef_N_15  0.99 0.0 \n", + "coef_N_16  1.38 0.0 \n", + "coef_N_166  0.83 0.0 \n", + "coef_N_17  3.01 ** 0.0 \n", + "coef_N_18  3.01 ** 0.0 \n", + "coef_N_22  5.14 *** 0.0 \n", + "coef_N_222_224_444 -6.91 *** 0.0 \n", + "coef_N_23  0.80 0.0 \n", + "coef_N_24  8.09 *** 0.0 \n", + "coef_N_246_226_446 -0.15 0.0 \n", + "coef_N_25 -0.25 0.0 \n", + "coef_N_26  0.29 0.0 \n", + "coef_N_27  7.60 *** 0.0 \n", + "coef_N_28  9.85 *** 0.0 \n", + "coef_N_33  4.72 *** 0.0 \n", + "coef_N_34 -0.53 0.0 \n", + "coef_N_35  2.59 ** 0.0 \n", + "coef_N_36  NA 0.0 \n", + "coef_N_37  BIG *** 0.0 \n", + "coef_N_38  BIG *** 0.0 \n", + "coef_N_44  3.03 ** 0.0 \n", + "coef_N_45 -1.03 0.0 \n", + "coef_N_46  BIG *** 0.0 \n", + "coef_N_47  BIG *** 0.0 \n", + "coef_N_48  BIG *** 0.0 \n", + "coef_N_55  6.42 *** 0.0 \n", + "coef_N_56_57_58  NA 0.0 \n", + "coef_N_66  3.25 ** 0.0 \n", + "coef_N_67  1.93 0.0 \n", + "coef_N_68  1.27 0.0 \n", + "coef_N_77  11.65 *** 0.0 \n", + "coef_N_78 -0.78 0.0 \n", + "coef_N_88  4.26 *** 0.0 \n", + "coef_N_xxxxx -0.47 0.0 \n", + "coef_UNAVAILABLE  NA 0.0 \n", + "coef_child_who_is_in_school_or_too_young_for_sc...  3.32 *** 0.0 \n", + "coef_driving_age_child_who_is_in_school_asc_M  12.78 *** 0.0 \n", + "coef_driving_age_child_who_is_in_school_asc_N -2.45 * 0.0 \n", + "coef_driving_age_child_who_is_in_school_interac... -0.85 0.0 \n", + "coef_driving_age_child_who_is_in_school_interac...  4.98 *** 0.0 \n", + "coef_driving_age_child_who_is_in_school_interac... -6.53 *** 0.0 \n", + "coef_driving_age_child_who_is_in_school_interac...  6.75 *** 0.0 \n", + "coef_full_time_worker_asc_M  8.76 *** 0.0 \n", + "coef_full_time_worker_asc_N  13.66 *** 0.0 \n", + "coef_full_time_worker_interaction_with_age_less...  5.41 *** 0.0 \n", + "coef_full_time_worker_interaction_with_female_g... -3.24 ** 0.0 \n", + "coef_full_time_worker_interaction_with_fewer_ca...  9.16 *** 0.0 \n", + "coef_full_time_worker_interaction_with_income_l...  3.72 *** 0.0 \n", + "coef_full_time_worker_intraction_with_peak_acce...  3.23 ** 0.0 \n", + "coef_non_working_adult_asc_N  1.97 * 0.0 \n", + "coef_non_working_adult_interaction_with_female_...  NA 0.0 \n", + "coef_non_working_adult_interaction_with_fewer_c...  7.19 *** 0.0 \n", + "coef_non_working_adult_interaction_with_income_... -5.03 *** 0.0 \n", + "coef_non_working_adult_interaction_with_income_... -6.94 *** 0.0 \n", + "coef_non_working_adult_interaction_with_more_ca...  BIG *** 0.0 \n", + "coef_non_working_adult_interaction_with_more_ca...  9.45 *** 0.0 \n", + "coef_non_working_adult_interaction_with_peak_ac...  BIG *** 0.0 \n", + "coef_non_working_adult_retired_or_univ_student_...  1.78 0.0 \n", + "coef_part_time_worker_asc_M -2.29 * 0.0 \n", + "coef_part_time_worker_asc_N  7.18 *** 0.0 \n", + "coef_part_time_worker_interaction_with_income_b... -3.93 *** 0.0 \n", + "coef_part_time_worker_interaction_with_income_l...  2.18 * 0.0 \n", + "coef_part_time_worker_interaction_with_income_m... -3.64 *** 0.0 \n", + "coef_part_time_worker_interaction_with_income_m...  4.56 *** 0.0 \n", + "coef_part_time_worker_interaction_with_peak_acc...  6.76 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_asc_M  31.22 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_asc_N -0.16 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -6.17 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -4.70 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -4.80 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_int...  7.83 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  5.43 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -3.34 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -4.27 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  6.84 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  1.81 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -5.51 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -5.31 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  7.99 *** 0.0 \n", + "coef_retired_asc_N  1.21 0.0 \n", + "coef_retired_interaction_with_age_more_than_80_H  8.84 *** 0.0 \n", + "coef_retired_interaction_with_female_M  NA 0.0 \n", + "coef_retired_interaction_with_fewer_cars_than_w...  2.98 ** 0.0 \n", + "coef_retired_interaction_with_income_less_than_...  5.63 *** 0.0 \n", + "coef_retired_interaction_with_more_cars_than_wo...  NA 0.0 \n", + "coef_retired_interaction_with_more_cars_than_wo...  11.48 *** 0.0 \n", + "coef_retired_interaction_with_peak_accessibilit...  NA 0.0 \n", + "coef_university_student_asc_M  25.12 *** 0.0 \n", + "coef_university_student_asc_N  1.38 0.0 \n", + "coef_full_time_worker_interaction_with_income_b... \n", + "coef_full_time_worker_interaction_with_income_l... \n", + "\n", + " model2 \\\n", + " Value Std Err \n", + "Parameter \n", + "-999.0 -999.  0.00 \n", + "coef_H_11  1.46  0.0622 \n", + "coef_H_12  0.950  0.132 \n", + "coef_H_124_122_144  0.367  0.153 \n", + "coef_H_126_146 -0.00902  0.336 \n", + "coef_H_13  1.20  0.131 \n", + "coef_H_14  0.991  0.0904 \n", + "coef_H_15  1.18  0.0921 \n", + "coef_H_16  1.85  0.103 \n", + "coef_H_17  1.34  0.0558 \n", + "coef_H_18  0.808  0.109 \n", + "coef_H_22  1.66  0.215 \n", + "coef_H_222_224_244  0.0804  0.225 \n", + "coef_H_226_246_446  0.0726  0.687 \n", + "coef_H_23  1.68  0.209 \n", + "coef_H_24  1.20  0.165 \n", + "coef_H_25 -0.0737  0.277 \n", + "coef_H_26  2.84  0.239 \n", + "coef_H_266_466  1.25  0.652 \n", + "coef_H_27  0.804  0.158 \n", + "coef_H_28  0.946  0.186 \n", + "coef_H_33  0.366  0.448 \n", + "coef_H_34  1.54  0.131 \n", + "coef_H_35  0.213  0.389 \n", + "coef_H_36  1.55  NA \n", + "coef_H_37  1.55  NA \n", + "coef_H_38  1.34  4.18e-13 \n", + "coef_H_44  1.09  0.0883 \n", + "coef_H_45  1.13  0.139 \n", + "coef_H_46  0.524  3.12e-13 \n", + "coef_H_47  0.811  NA \n", + "coef_H_48  1.17  6.30e-13 \n", + "coef_H_55  1.22  0.165 \n", + "coef_H_56_57_58  0.863  NA \n", + "coef_H_66  1.37  0.298 \n", + "coef_H_67  1.28  0.386 \n", + "coef_H_68  1.39  0.756 \n", + "coef_H_77  2.42  0.0804 \n", + "coef_H_78  1.21  0.157 \n", + "coef_H_88  0.956  0.217 \n", + "coef_H_xxxxx -3.47  0.269 \n", + "coef_M_11  9.36e-05  0.0443 \n", + "coef_M_111  0.164  0.0552 \n", + "coef_M_112_114  0.295  0.0900 \n", + "coef_M_12 -0.109  0.0595 \n", + "coef_M_13  0.197  0.0448 \n", + "coef_M_16  0.159  0.0607 \n", + "coef_M_17  0.0372  0.0286 \n", + "coef_M_18  0.372  0.0438 \n", + "coef_M_22  0.966  0.0933 \n", + "coef_M_23  0.107  0.0905 \n", + "coef_M_26  0.776  0.129 \n", + "coef_M_27  0.0943  0.0482 \n", + "coef_M_28  0.515  0.0771 \n", + "coef_M_33  0.673  0.0862 \n", + "coef_M_36 -0.00210  NA \n", + "coef_M_37  0.297  3.67e-13 \n", + "coef_M_38  0.225  4.32e-13 \n", + "coef_M_66  0.0422  0.240 \n", + "coef_M_666 -0.671  1.46 \n", + "coef_M_67  0.288  0.360 \n", + "coef_M_68  0.695  0.457 \n", + "coef_M_77  0.703  0.0584 \n", + "coef_M_78  0.141  0.0957 \n", + "coef_M_88  1.33  0.0903 \n", + "coef_M_xxxxx  0.105  0.0498 \n", + "coef_N_11  0.915  0.0816 \n", + "coef_N_112_114  0.104  0.174 \n", + "coef_N_12  0.467  0.111 \n", + "coef_N_124_122_144  0.128  0.143 \n", + "coef_N_13  0.211  0.135 \n", + "coef_N_14  0.0271  0.0720 \n", + "coef_N_15  0.0894  0.0881 \n", + "coef_N_16  0.309  0.223 \n", + "coef_N_166  0.433  0.525 \n", + "coef_N_17  0.280  0.0919 \n", + "coef_N_18  0.299  0.0989 \n", + "coef_N_22  0.867  0.169 \n", + "coef_N_222_224_444 -1.35  0.195 \n", + "coef_N_23  0.165  0.200 \n", + "coef_N_24  0.595  0.0737 \n", + "coef_N_246_226_446 -0.872  5.62 \n", + "coef_N_25 -0.0275  0.107 \n", + "coef_N_26  0.126  0.436 \n", + "coef_N_27  0.734  0.0961 \n", + "coef_N_28  1.05  0.107 \n", + "coef_N_33  0.786  0.165 \n", + "coef_N_34 -0.0511  0.0979 \n", + "coef_N_35  0.390  0.150 \n", + "coef_N_36  1.62  NA \n", + "coef_N_37  0.516  NA \n", + "coef_N_38  0.897  2.96e-13 \n", + "coef_N_44  0.300  0.0996 \n", + "coef_N_45 -0.0902  0.0854 \n", + "coef_N_46  0.680  2.86e-13 \n", + "coef_N_47  0.565  2.67e-13 \n", + "coef_N_48  1.16  2.34e-13 \n", + "coef_N_55  0.729  0.114 \n", + "coef_N_56_57_58  0.292  NA \n", + "coef_N_66  1.60  0.495 \n", + "coef_N_67  1.29  0.673 \n", + "coef_N_68  1.14  0.899 \n", + "coef_N_77  1.28  0.109 \n", + "coef_N_78 -0.421  0.546 \n", + "coef_N_88  0.645  0.151 \n", + "coef_N_xxxxx -0.0446  0.100 \n", + "coef_UNAVAILABLE -999.  0.00 \n", + "coef_child_who_is_in_school_or_too_young_for_sc...  0.139  0.0416 \n", + "coef_driving_age_child_who_is_in_school_asc_M  2.30  0.178 \n", + "coef_driving_age_child_who_is_in_school_asc_N -1.06  0.445 \n", + "coef_driving_age_child_who_is_in_school_interac... -0.132  0.188 \n", + "coef_driving_age_child_who_is_in_school_interac...  0.836  0.168 \n", + "coef_driving_age_child_who_is_in_school_interac... -1.51  0.242 \n", + "coef_driving_age_child_who_is_in_school_interac...  1.53  0.216 \n", + "coef_full_time_worker_asc_M  2.18  0.246 \n", + "coef_full_time_worker_asc_N  0.693  0.0574 \n", + "coef_full_time_worker_interaction_with_age_less...  0.216  0.0389 \n", + "coef_full_time_worker_interaction_with_female_g... -0.124  0.0394 \n", + "coef_full_time_worker_interaction_with_fewer_ca...  0.528  0.0568 \n", + "coef_full_time_worker_interaction_with_income_l... \n", + "coef_full_time_worker_intraction_with_peak_acce...  0.0642  0.0203 \n", + "coef_non_working_adult_asc_N  0.698  0.354 \n", + "coef_non_working_adult_interaction_with_female_... -0.743  3.86e-14 \n", + "coef_non_working_adult_interaction_with_fewer_c...  0.978  0.136 \n", + "coef_non_working_adult_interaction_with_income_... -0.424  0.0839 \n", + "coef_non_working_adult_interaction_with_income_... -0.716  0.104 \n", + "coef_non_working_adult_interaction_with_more_ca...  0.651  NA \n", + "coef_non_working_adult_interaction_with_more_ca...  0.781  0.0828 \n", + "coef_non_working_adult_interaction_with_peak_ac...  0.231  8.76e-15 \n", + "coef_non_working_adult_retired_or_univ_student_...  0.0629  0.0352 \n", + "coef_part_time_worker_asc_M -0.900  0.394 \n", + "coef_part_time_worker_asc_N  0.679  0.0944 \n", + "coef_part_time_worker_interaction_with_income_b... -0.471  0.120 \n", + "coef_part_time_worker_interaction_with_income_l...  0.278  0.126 \n", + "coef_part_time_worker_interaction_with_income_m... -0.488  0.135 \n", + "coef_part_time_worker_interaction_with_income_m...  0.334  0.0734 \n", + "coef_part_time_worker_interaction_with_peak_acc...  0.218  0.0323 \n", + "coef_pre_driving_age_child_who_is_in_school_asc_M  3.24  0.104 \n", + "coef_pre_driving_age_child_who_is_in_school_asc_N -0.0778  0.412 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -0.697  0.112 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -0.605  0.129 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -0.398  0.0834 \n", + "coef_pre_driving_age_child_who_is_in_school_int...  0.676  0.0862 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  0.587  0.107 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -1.40  0.417 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -0.392  0.0920 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  0.670  0.0978 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  0.243  0.134 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -0.708  0.128 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -0.688  0.131 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  0.686  0.0858 \n", + "coef_retired_asc_N  0.439  0.359 \n", + "coef_retired_interaction_with_age_more_than_80_H  0.732  0.0825 \n", + "coef_retired_interaction_with_female_M  0.477  0.00 \n", + "coef_retired_interaction_with_fewer_cars_than_w...  0.649  0.218 \n", + "coef_retired_interaction_with_income_less_than_...  0.483  0.0844 \n", + "coef_retired_interaction_with_more_cars_than_wo...  2.99  0.00 \n", + "coef_retired_interaction_with_more_cars_than_wo...  1.01  0.0884 \n", + "coef_retired_interaction_with_peak_accessibilit...  0.279  0.00 \n", + "coef_university_student_asc_M  2.17  0.0864 \n", + "coef_university_student_asc_N  0.490  0.356 \n", + "coef_full_time_worker_interaction_with_income_b...  0.0541  0.0542 \n", + "coef_full_time_worker_interaction_with_income_l...  0.245  0.0795 \n", + "\n", + " \n", + " t Stat Signif Null Value \n", + "Parameter \n", + "-999.0  NA 0.0 \n", + "coef_H_11  23.40 *** 0.0 \n", + "coef_H_12  7.18 *** 0.0 \n", + "coef_H_124_122_144  2.40 * 0.0 \n", + "coef_H_126_146 -0.03 0.0 \n", + "coef_H_13  9.17 *** 0.0 \n", + "coef_H_14  10.96 *** 0.0 \n", + "coef_H_15  12.86 *** 0.0 \n", + "coef_H_16  17.98 *** 0.0 \n", + "coef_H_17  24.04 *** 0.0 \n", + "coef_H_18  7.42 *** 0.0 \n", + "coef_H_22  7.73 *** 0.0 \n", + "coef_H_222_224_244  0.36 0.0 \n", + "coef_H_226_246_446  0.11 0.0 \n", + "coef_H_23  8.03 *** 0.0 \n", + "coef_H_24  7.24 *** 0.0 \n", + "coef_H_25 -0.27 0.0 \n", + "coef_H_26  11.86 *** 0.0 \n", + "coef_H_266_466  1.91 0.0 \n", + "coef_H_27  5.07 *** 0.0 \n", + "coef_H_28  5.08 *** 0.0 \n", + "coef_H_33  0.82 0.0 \n", + "coef_H_34  11.75 *** 0.0 \n", + "coef_H_35  0.55 0.0 \n", + "coef_H_36  NA 0.0 \n", + "coef_H_37  NA 0.0 \n", + "coef_H_38  BIG *** 0.0 \n", + "coef_H_44  12.30 *** 0.0 \n", + "coef_H_45  8.16 *** 0.0 \n", + "coef_H_46  BIG *** 0.0 \n", + "coef_H_47  NA 0.0 \n", + "coef_H_48  BIG *** 0.0 \n", + "coef_H_55  7.39 *** 0.0 \n", + "coef_H_56_57_58  NA 0.0 \n", + "coef_H_66  4.60 *** 0.0 \n", + "coef_H_67  3.32 *** 0.0 \n", + "coef_H_68  1.83 0.0 \n", + "coef_H_77  30.16 *** 0.0 \n", + "coef_H_78  7.69 *** 0.0 \n", + "coef_H_88  4.40 *** 0.0 \n", + "coef_H_xxxxx -12.88 *** 0.0 \n", + "coef_M_11  0.00 0.0 \n", + "coef_M_111  2.96 ** 0.0 \n", + "coef_M_112_114  3.28 ** 0.0 \n", + "coef_M_12 -1.83 0.0 \n", + "coef_M_13  4.39 *** 0.0 \n", + "coef_M_16  2.63 ** 0.0 \n", + "coef_M_17  1.30 0.0 \n", + "coef_M_18  8.49 *** 0.0 \n", + "coef_M_22  10.36 *** 0.0 \n", + "coef_M_23  1.18 0.0 \n", + "coef_M_26  6.00 *** 0.0 \n", + "coef_M_27  1.95 0.0 \n", + "coef_M_28  6.68 *** 0.0 \n", + "coef_M_33  7.81 *** 0.0 \n", + "coef_M_36  NA 0.0 \n", + "coef_M_37  BIG *** 0.0 \n", + "coef_M_38  BIG *** 0.0 \n", + "coef_M_66  0.18 0.0 \n", + "coef_M_666 -0.46 0.0 \n", + "coef_M_67  0.80 0.0 \n", + "coef_M_68  1.52 0.0 \n", + "coef_M_77  12.03 *** 0.0 \n", + "coef_M_78  1.48 0.0 \n", + "coef_M_88  14.70 *** 0.0 \n", + "coef_M_xxxxx  2.10 * 0.0 \n", + "coef_N_11  11.21 *** 0.0 \n", + "coef_N_112_114  0.60 0.0 \n", + "coef_N_12  4.22 *** 0.0 \n", + "coef_N_124_122_144  0.90 0.0 \n", + "coef_N_13  1.57 0.0 \n", + "coef_N_14  0.38 0.0 \n", + "coef_N_15  1.01 0.0 \n", + "coef_N_16  1.39 0.0 \n", + "coef_N_166  0.82 0.0 \n", + "coef_N_17  3.04 ** 0.0 \n", + "coef_N_18  3.02 ** 0.0 \n", + "coef_N_22  5.14 *** 0.0 \n", + "coef_N_222_224_444 -6.91 *** 0.0 \n", + "coef_N_23  0.83 0.0 \n", + "coef_N_24  8.07 *** 0.0 \n", + "coef_N_246_226_446 -0.16 0.0 \n", + "coef_N_25 -0.26 0.0 \n", + "coef_N_26  0.29 0.0 \n", + "coef_N_27  7.64 *** 0.0 \n", + "coef_N_28  9.85 *** 0.0 \n", + "coef_N_33  4.77 *** 0.0 \n", + "coef_N_34 -0.52 0.0 \n", + "coef_N_35  2.59 ** 0.0 \n", + "coef_N_36  NA 0.0 \n", + "coef_N_37  NA 0.0 \n", + "coef_N_38  BIG *** 0.0 \n", + "coef_N_44  3.01 ** 0.0 \n", + "coef_N_45 -1.06 0.0 \n", + "coef_N_46  BIG *** 0.0 \n", + "coef_N_47  BIG *** 0.0 \n", + "coef_N_48  BIG *** 0.0 \n", + "coef_N_55  6.41 *** 0.0 \n", + "coef_N_56_57_58  NA 0.0 \n", + "coef_N_66  3.23 ** 0.0 \n", + "coef_N_67  1.92 0.0 \n", + "coef_N_68  1.27 0.0 \n", + "coef_N_77  11.68 *** 0.0 \n", + "coef_N_78 -0.77 0.0 \n", + "coef_N_88  4.26 *** 0.0 \n", + "coef_N_xxxxx -0.44 0.0 \n", + "coef_UNAVAILABLE  NA 0.0 \n", + "coef_child_who_is_in_school_or_too_young_for_sc...  3.35 *** 0.0 \n", + "coef_driving_age_child_who_is_in_school_asc_M  12.94 *** 0.0 \n", + "coef_driving_age_child_who_is_in_school_asc_N -2.39 * 0.0 \n", + "coef_driving_age_child_who_is_in_school_interac... -0.70 0.0 \n", + "coef_driving_age_child_who_is_in_school_interac...  4.96 *** 0.0 \n", + "coef_driving_age_child_who_is_in_school_interac... -6.24 *** 0.0 \n", + "coef_driving_age_child_who_is_in_school_interac...  7.05 *** 0.0 \n", + "coef_full_time_worker_asc_M  8.88 *** 0.0 \n", + "coef_full_time_worker_asc_N  12.07 *** 0.0 \n", + "coef_full_time_worker_interaction_with_age_less...  5.54 *** 0.0 \n", + "coef_full_time_worker_interaction_with_female_g... -3.15 ** 0.0 \n", + "coef_full_time_worker_interaction_with_fewer_ca...  9.29 *** 0.0 \n", + "coef_full_time_worker_interaction_with_income_l... \n", + "coef_full_time_worker_intraction_with_peak_acce...  3.16 ** 0.0 \n", + "coef_non_working_adult_asc_N  1.97 * 0.0 \n", + "coef_non_working_adult_interaction_with_female_... -BIG *** 0.0 \n", + "coef_non_working_adult_interaction_with_fewer_c...  7.19 *** 0.0 \n", + "coef_non_working_adult_interaction_with_income_... -5.05 *** 0.0 \n", + "coef_non_working_adult_interaction_with_income_... -6.89 *** 0.0 \n", + "coef_non_working_adult_interaction_with_more_ca...  NA 0.0 \n", + "coef_non_working_adult_interaction_with_more_ca...  9.43 *** 0.0 \n", + "coef_non_working_adult_interaction_with_peak_ac...  BIG *** 0.0 \n", + "coef_non_working_adult_retired_or_univ_student_...  1.79 0.0 \n", + "coef_part_time_worker_asc_M -2.29 * 0.0 \n", + "coef_part_time_worker_asc_N  7.19 *** 0.0 \n", + "coef_part_time_worker_interaction_with_income_b... -3.93 *** 0.0 \n", + "coef_part_time_worker_interaction_with_income_l...  2.21 * 0.0 \n", + "coef_part_time_worker_interaction_with_income_m... -3.61 *** 0.0 \n", + "coef_part_time_worker_interaction_with_income_m...  4.55 *** 0.0 \n", + "coef_part_time_worker_interaction_with_peak_acc...  6.75 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_asc_M  31.19 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_asc_N -0.19 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -6.19 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -4.69 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_int... -4.77 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_in_school_int...  7.84 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  5.47 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -3.36 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -4.27 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  6.85 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  1.82 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -5.52 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for... -5.26 *** 0.0 \n", + "coef_pre_driving_age_child_who_is_too_young_for...  7.99 *** 0.0 \n", + "coef_retired_asc_N  1.22 0.0 \n", + "coef_retired_interaction_with_age_more_than_80_H  8.87 *** 0.0 \n", + "coef_retired_interaction_with_female_M  NA 0.0 \n", + "coef_retired_interaction_with_fewer_cars_than_w...  2.97 ** 0.0 \n", + "coef_retired_interaction_with_income_less_than_...  5.72 *** 0.0 \n", + "coef_retired_interaction_with_more_cars_than_wo...  NA 0.0 \n", + "coef_retired_interaction_with_more_cars_than_wo...  11.45 *** 0.0 \n", + "coef_retired_interaction_with_peak_accessibilit...  NA 0.0 \n", + "coef_university_student_asc_M  25.10 *** 0.0 \n", + "coef_university_student_asc_N  1.38 0.0 \n", + "coef_full_time_worker_interaction_with_income_b...  1.00 0.0 \n", + "coef_full_time_worker_interaction_with_income_l...  3.08 ** 0.0 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with pd.option_context('display.max_rows', 999):\n", + " display(pd.concat({\n", + " \"model\": model.parameter_summary().data,\n", + " \"model2\": model2.parameter_summary().data,\n", + " }, axis=1).fillna(\"\"))" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -3277,7 +6558,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.8" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/07_mand_tour_freq.ipynb b/activitysim/examples/example_estimation/notebooks/07_mand_tour_freq.ipynb index 12091fc166..5e444a544c 100644 --- a/activitysim/examples/example_estimation/notebooks/07_mand_tour_freq.ipynb +++ b/activitysim/examples/example_estimation/notebooks/07_mand_tour_freq.ipynb @@ -24,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +115,27 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_frequency/mandatory_tour_frequency_coefficients.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/mandatory_tour_frequency/mandatory_tour_frequency_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_frequency/mandatory_tour_frequency_values_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"mandatory_tour_frequency\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -743,15 +805,15 @@ " util_driving_age_child\n", " util_pre_driving_age_child\n", " ...\n", - " HSENROLL\n", - " COLLFTE\n", - " COLLPTE\n", - " TOPOLOGY\n", - " TERMINAL\n", - " household_density\n", - " employment_density\n", - " density_index\n", - " is_cbd\n", + " auPkTotal\n", + " auOpRetail\n", + " auOpTotal\n", + " trPkRetail\n", + " trPkTotal\n", + " trOpRetail\n", + " trOpTotal\n", + " nmRetail\n", + " nmTotal\n", " override_choice_code\n", " \n", " \n", @@ -781,8 +843,8 @@ " \n", " \n", " \n", - " 629\n", - " 629\n", + " 1918\n", + " 1918\n", " school1\n", " school1\n", " 0.0\n", @@ -793,20 +855,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 1.64217\n", - " 13.280000\n", - " 4.535000\n", - " 3.380567\n", - " False\n", + " 12.295952\n", + " 10.006297\n", + " 12.411522\n", + " 5.033643\n", + " 7.242282\n", + " 4.864150\n", + " 7.063680\n", + " 5.626389\n", + " 7.133756\n", " 3\n", " \n", " \n", - " 1274\n", - " 1274\n", + " 3215\n", + " 3215\n", " school1\n", " school1\n", " 0.0\n", @@ -817,20 +879,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 506.23721\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 2.44180\n", - " 19.776119\n", - " 7.179104\n", - " 5.267062\n", - " False\n", + " 12.036005\n", + " 9.698240\n", + " 12.156041\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 1.360774\n", + " 5.139792\n", " 3\n", " \n", " \n", - " 27266\n", - " 27266\n", + " 4362\n", + " 4362\n", " school1\n", " school1\n", " 0.0\n", @@ -841,20 +903,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 26.92893\n", - " 2035.58118\n", - " 20.60887\n", - " 2\n", - " 5.22542\n", - " 97.634722\n", - " 550.205552\n", - " 82.920387\n", - " False\n", + " 11.954228\n", + " 9.566058\n", + " 12.139587\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 3.086628\n", + " 5.647842\n", " 3\n", " \n", " \n", - " 28012\n", - " 28012\n", + " 5859\n", + " 5859\n", " school1\n", " school1\n", " 0.0\n", @@ -865,20 +927,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 690.54974\n", - " 0.00000\n", - " 3\n", - " 4.73802\n", - " 117.769796\n", - " 246.205869\n", - " 79.663609\n", - " False\n", + " 12.484185\n", + " 9.994051\n", + " 12.608786\n", + " 2.273060\n", + " 4.760981\n", + " 2.104966\n", + " 4.545843\n", + " 4.254230\n", + " 6.941860\n", " 3\n", " \n", " \n", - " 29476\n", - " 29476\n", + " 6100\n", + " 6100\n", " school1\n", " school1\n", " 0.0\n", @@ -889,15 +951,15 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 0.00000\n", - " 2\n", - " 4.75017\n", - " 71.898080\n", - " 273.023745\n", - " 56.911108\n", - " False\n", + " 12.718182\n", + " 10.233345\n", + " 12.809847\n", + " 3.534863\n", + " 6.375527\n", + " 3.401762\n", + " 6.258096\n", + " 5.240538\n", + " 7.175776\n", " 3\n", " \n", " \n", @@ -925,106 +987,106 @@ " ...\n", " \n", " \n", - " 2823069\n", - " 7514404\n", - " work1\n", - " work1\n", - " 1.0\n", + " 2857869\n", + " 7549204\n", + " school1\n", + " school1\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 3.95752\n", - " 65.596535\n", - " 32.655666\n", - " 21.802041\n", - " True\n", - " 1\n", + " 12.307902\n", + " 10.005144\n", + " 12.585021\n", + " 3.812385\n", + " 6.519807\n", + " 3.632087\n", + " 6.178083\n", + " 3.718425\n", + " 5.556368\n", + " 3\n", " \n", " \n", - " 2823442\n", - " 7514777\n", - " work1\n", - " work1\n", + " 2857903\n", + " 7549238\n", + " school1\n", + " school1\n", " 0.0\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 0.00000\n", - " 2\n", - " 4.51942\n", - " 56.706023\n", - " 144.861886\n", - " 40.753220\n", - " True\n", - " 1\n", + " 12.309276\n", + " 9.986443\n", + " 12.582868\n", + " 3.319335\n", + " 6.046532\n", + " 3.207581\n", + " 5.829832\n", + " 4.139571\n", + " 6.510036\n", + " 3\n", " \n", " \n", - " 2823850\n", - " 7515185\n", - " work_and_school\n", - " work_and_school\n", + " 2859659\n", + " 7550994\n", + " school1\n", + " school1\n", " 0.0\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 11.638333\n", + " 9.598840\n", + " 11.963516\n", + " 0.916326\n", + " 3.279901\n", + " 0.315332\n", + " 2.429541\n", + " 3.824743\n", + " 6.768218\n", " 3\n", - " 2.46800\n", - " 0.296858\n", - " 36.296472\n", - " 0.294449\n", - " True\n", - " 5\n", " \n", " \n", - " 2836262\n", - " 7527597\n", + " 2861083\n", + " 7552418\n", " school1\n", " school1\n", " 0.0\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", + " 1.0\n", " ...\n", - " 3961.04761\n", - " 17397.79102\n", - " 11152.93652\n", - " 1\n", - " 2.28992\n", - " 3.984127\n", - " 23.820106\n", - " 3.413233\n", - " False\n", + " 10.447823\n", + " 8.697696\n", + " 10.794293\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 3.679297\n", + " 5.376192\n", " 3\n", " \n", " \n", - " 2849737\n", - " 7541072\n", - " school2\n", - " school2\n", + " 2870568\n", + " 7561903\n", + " school1\n", + " school1\n", " 0.0\n", " 0.0\n", " 1.0\n", @@ -1033,108 +1095,94 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 11.802080\n", + " 9.800589\n", + " 12.206363\n", + " 1.183362\n", + " 3.611805\n", + " 0.897289\n", + " 3.179071\n", + " 5.769691\n", + " 8.087817\n", " 3\n", - " 3.35329\n", - " 34.477273\n", - " 15.454545\n", - " 10.671163\n", - " True\n", - " 4\n", " \n", " \n", "\n", - "

2620 rows × 220 columns

\n", + "

31768 rows × 220 columns

\n", "" ], "text/plain": [ - " person_id model_choice override_choice util_ft_worker \\\n", - "household_id \n", - "629 629 school1 school1 0.0 \n", - "1274 1274 school1 school1 0.0 \n", - "27266 27266 school1 school1 0.0 \n", - "28012 28012 school1 school1 0.0 \n", - "29476 29476 school1 school1 0.0 \n", - "... ... ... ... ... \n", - "2823069 7514404 work1 work1 1.0 \n", - "2823442 7514777 work1 work1 0.0 \n", - "2823850 7515185 work_and_school work_and_school 0.0 \n", - "2836262 7527597 school1 school1 0.0 \n", - "2849737 7541072 school2 school2 0.0 \n", + " person_id model_choice override_choice util_ft_worker \\\n", + "household_id \n", + "1918 1918 school1 school1 0.0 \n", + "3215 3215 school1 school1 0.0 \n", + "4362 4362 school1 school1 0.0 \n", + "5859 5859 school1 school1 0.0 \n", + "6100 6100 school1 school1 0.0 \n", + "... ... ... ... ... \n", + "2857869 7549204 school1 school1 0.0 \n", + "2857903 7549238 school1 school1 0.0 \n", + "2859659 7550994 school1 school1 0.0 \n", + "2861083 7552418 school1 school1 0.0 \n", + "2870568 7561903 school1 school1 0.0 \n", "\n", " util_pt_worker util_univ util_non_working_adult util_retired \\\n", "household_id \n", - "629 0.0 1.0 0.0 0.0 \n", - "1274 0.0 1.0 0.0 0.0 \n", - "27266 0.0 1.0 0.0 0.0 \n", - "28012 0.0 1.0 0.0 0.0 \n", - "29476 0.0 1.0 0.0 0.0 \n", + "1918 0.0 1.0 0.0 0.0 \n", + "3215 0.0 1.0 0.0 0.0 \n", + "4362 0.0 1.0 0.0 0.0 \n", + "5859 0.0 1.0 0.0 0.0 \n", + "6100 0.0 1.0 0.0 0.0 \n", "... ... ... ... ... \n", - "2823069 0.0 0.0 0.0 0.0 \n", - "2823442 0.0 1.0 0.0 0.0 \n", - "2823850 0.0 1.0 0.0 0.0 \n", - "2836262 0.0 1.0 0.0 0.0 \n", - "2849737 0.0 1.0 0.0 0.0 \n", + "2857869 0.0 0.0 0.0 0.0 \n", + "2857903 0.0 0.0 0.0 0.0 \n", + "2859659 0.0 0.0 0.0 0.0 \n", + "2861083 0.0 0.0 0.0 0.0 \n", + "2870568 0.0 1.0 0.0 0.0 \n", "\n", " util_driving_age_child util_pre_driving_age_child ... \\\n", "household_id ... \n", - "629 0.0 0.0 ... \n", - "1274 0.0 0.0 ... \n", - "27266 0.0 0.0 ... \n", - "28012 0.0 0.0 ... \n", - "29476 0.0 0.0 ... \n", + "1918 0.0 0.0 ... \n", + "3215 0.0 0.0 ... \n", + "4362 0.0 0.0 ... \n", + "5859 0.0 0.0 ... \n", + "6100 0.0 0.0 ... \n", "... ... ... ... \n", - "2823069 0.0 0.0 ... \n", - "2823442 0.0 0.0 ... \n", - "2823850 0.0 0.0 ... \n", - "2836262 0.0 0.0 ... \n", - "2849737 0.0 0.0 ... \n", + "2857869 1.0 0.0 ... \n", + "2857903 1.0 0.0 ... \n", + "2859659 1.0 0.0 ... \n", + "2861083 0.0 1.0 ... \n", + "2870568 0.0 0.0 ... \n", "\n", - " HSENROLL COLLFTE COLLPTE TOPOLOGY TERMINAL \\\n", - "household_id \n", - "629 0.00000 0.00000 0.00000 1 1.64217 \n", - "1274 506.23721 0.00000 0.00000 1 2.44180 \n", - "27266 26.92893 2035.58118 20.60887 2 5.22542 \n", - "28012 0.00000 690.54974 0.00000 3 4.73802 \n", - "29476 0.00000 0.00000 0.00000 2 4.75017 \n", - "... ... ... ... ... ... \n", - "2823069 0.00000 0.00000 0.00000 1 3.95752 \n", - "2823442 0.00000 0.00000 0.00000 2 4.51942 \n", - "2823850 0.00000 0.00000 0.00000 3 2.46800 \n", - "2836262 3961.04761 17397.79102 11152.93652 1 2.28992 \n", - "2849737 0.00000 0.00000 0.00000 3 3.35329 \n", + " auPkTotal auOpRetail auOpTotal trPkRetail trPkTotal \\\n", + "household_id \n", + "1918 12.295952 10.006297 12.411522 5.033643 7.242282 \n", + "3215 12.036005 9.698240 12.156041 0.000000 0.000000 \n", + "4362 11.954228 9.566058 12.139587 0.000000 0.000000 \n", + "5859 12.484185 9.994051 12.608786 2.273060 4.760981 \n", + "6100 12.718182 10.233345 12.809847 3.534863 6.375527 \n", + "... ... ... ... ... ... \n", + "2857869 12.307902 10.005144 12.585021 3.812385 6.519807 \n", + "2857903 12.309276 9.986443 12.582868 3.319335 6.046532 \n", + "2859659 11.638333 9.598840 11.963516 0.916326 3.279901 \n", + "2861083 10.447823 8.697696 10.794293 0.000000 0.000000 \n", + "2870568 11.802080 9.800589 12.206363 1.183362 3.611805 \n", "\n", - " household_density employment_density density_index is_cbd \\\n", - "household_id \n", - "629 13.280000 4.535000 3.380567 False \n", - "1274 19.776119 7.179104 5.267062 False \n", - "27266 97.634722 550.205552 82.920387 False \n", - "28012 117.769796 246.205869 79.663609 False \n", - "29476 71.898080 273.023745 56.911108 False \n", - "... ... ... ... ... \n", - "2823069 65.596535 32.655666 21.802041 True \n", - "2823442 56.706023 144.861886 40.753220 True \n", - "2823850 0.296858 36.296472 0.294449 True \n", - "2836262 3.984127 23.820106 3.413233 False \n", - "2849737 34.477273 15.454545 10.671163 True \n", + " trOpRetail trOpTotal nmRetail nmTotal override_choice_code \n", + "household_id \n", + "1918 4.864150 7.063680 5.626389 7.133756 3 \n", + "3215 0.000000 0.000000 1.360774 5.139792 3 \n", + "4362 0.000000 0.000000 3.086628 5.647842 3 \n", + "5859 2.104966 4.545843 4.254230 6.941860 3 \n", + "6100 3.401762 6.258096 5.240538 7.175776 3 \n", + "... ... ... ... ... ... \n", + "2857869 3.632087 6.178083 3.718425 5.556368 3 \n", + "2857903 3.207581 5.829832 4.139571 6.510036 3 \n", + "2859659 0.315332 2.429541 3.824743 6.768218 3 \n", + "2861083 0.000000 0.000000 3.679297 5.376192 3 \n", + "2870568 0.897289 3.179071 5.769691 8.087817 3 \n", "\n", - " override_choice_code \n", - "household_id \n", - "629 3 \n", - "1274 3 \n", - "27266 3 \n", - "28012 3 \n", - "29476 3 \n", - "... ... \n", - "2823069 1 \n", - "2823442 1 \n", - "2823850 5 \n", - "2836262 3 \n", - "2849737 4 \n", - "\n", - "[2620 rows x 220 columns]" + "[31768 rows x 220 columns]" ] }, "execution_count": 6, @@ -1160,17 +1208,10 @@ "execution_count": 7, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

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Best LL = -410.2201502048449

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Best LL = -4677.236180934496

" ], "text/plain": [ "" @@ -1213,823 +1254,783 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " 0\n", " 0.000000\n", + " 0.000000\n", " 0.0000\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_can_walk_to_work_and_school\n", - " 0.071630\n", + " 0.284832\n", + " 0.284832\n", " 0.1391\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.071630\n", " \n", " \n", " coef_can_walk_to_work_school2\n", - " 1.368092\n", + " 0.811379\n", + " 0.811379\n", " 0.7114\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.368092\n", " \n", " \n", " coef_can_walk_to_work_work2\n", - " 0.651120\n", + " 0.600928\n", + " 0.600928\n", " 0.5268\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.651120\n", " \n", " \n", " coef_driving_age_child_school2_asc\n", - " -13.067731\n", + " -3.209418\n", + " -3.209418\n", " -3.1360\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -13.067731\n", " \n", " \n", " coef_driving_age_child_work_and_school_asc\n", - " -12.605997\n", + " -4.565091\n", + " -4.565091\n", " -4.4362\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -12.605997\n", " \n", " \n", " coef_female_school1\n", - " 0.247086\n", + " 0.000463\n", + " 0.000463\n", " 0.1592\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.247086\n", " \n", " \n", " coef_female_school2\n", - " -0.301339\n", + " -0.016856\n", + " -0.016856\n", " 0.1140\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.301339\n", " \n", " \n", " coef_female_work1\n", - " -2.242748\n", + " 0.333342\n", + " 0.333342\n", " 0.1737\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.242748\n", " \n", " \n", " coef_female_work2\n", - " -0.387411\n", + " -0.219862\n", + " -0.219862\n", " -0.2255\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.387411\n", " \n", " \n", " coef_female_work_and_school\n", - " -3.218280\n", + " -0.265847\n", + " -0.265847\n", " -0.3442\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -3.218280\n", " \n", " \n", " coef_few_cars_than_drivers_school2\n", - " -0.862451\n", + " -0.297623\n", + " -0.297623\n", " -0.5759\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.862451\n", " \n", " \n", " coef_ft_worker_work2_asc\n", - " -5.517933\n", + " -3.494595\n", + " -3.494595\n", " -3.3781\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -5.517933\n", " \n", " \n", " coef_hh_income_gt_50k_school1\n", " 0.034700\n", + " 0.034700\n", " 0.0347\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.034700\n", " \n", " \n", " coef_hh_income_gt_50k_student_work_and_school\n", - " -0.921175\n", + " -0.128428\n", + " -0.128428\n", " -0.0528\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.921175\n", " \n", " \n", " coef_hh_income_gt_50k_work\n", - " -1.418551\n", + " -0.286159\n", + " -0.286159\n", " -0.0528\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.418551\n", " \n", " \n", " coef_hh_income_gt_50k_worker_work_and_school\n", " 0.034700\n", + " 0.034700\n", " 0.0347\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.034700\n", " \n", " \n", " coef_home_urban_school1\n", " -0.136100\n", + " -0.136100\n", " -0.1361\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.136100\n", " \n", " \n", " coef_home_urban_school2\n", - " -8.455615\n", + " 0.161745\n", + " 0.161745\n", " 0.3170\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -8.455615\n", " \n", " \n", " coef_home_urban_work1\n", - " 4.026796\n", + " -0.122770\n", + " -0.122770\n", " -0.2831\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4.026796\n", " \n", " \n", " coef_home_urban_work2\n", - " 2.624854\n", + " 0.142218\n", + " 0.142218\n", " 0.2308\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2.624854\n", " \n", " \n", " coef_home_urban_work_and_school\n", - " -0.447070\n", + " -0.436835\n", + " -0.436835\n", " -0.3509\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.447070\n", " \n", " \n", " coef_no_cars_in_hh_school2\n", - " -0.620465\n", + " -1.479517\n", + " -1.479517\n", " -1.4130\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.620465\n", " \n", " \n", " coef_no_cars_in_hh_work2\n", - " -0.725967\n", + " -1.524960\n", + " -1.524960\n", " -1.3060\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.725967\n", " \n", " \n", " coef_no_cars_in_hh_work_and_school\n", - " -0.775934\n", + " -1.244512\n", + " -1.244512\n", " -1.3020\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.775934\n", " \n", " \n", " coef_non_family_hh_category1\n", " -0.250000\n", + " -0.250000\n", " -0.2500\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.250000\n", " \n", " \n", " coef_non_family_hh_category2\n", - " 5.000771\n", + " -0.091298\n", + " -0.091298\n", " -0.1792\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 5.000771\n", " \n", " \n", " coef_non_student_goes_to_school\n", " 3.883000\n", + " 3.883000\n", " 3.8830\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 3.883000\n", " \n", " \n", " coef_num_non_workers_in_hh_school1\n", " 0.257400\n", + " 0.257400\n", " 0.2574\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.257400\n", " \n", " \n", " coef_num_preschool_in_hh_school1\n", " -0.133500\n", + " -0.133500\n", " -0.1335\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.133500\n", " \n", " \n", " coef_num_preschool_in_hh_school2\n", - " 0.356660\n", + " -0.796350\n", + " -0.796350\n", " -0.5577\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.356660\n", " \n", " \n", " coef_num_preschool_in_hh_work1\n", - " -2.930501\n", + " 0.125045\n", + " 0.125045\n", " 0.2191\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.930501\n", " \n", " \n", " coef_num_preschool_in_hh_work2\n", - " 0.225173\n", + " -0.126183\n", + " -0.126183\n", " -0.1478\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.225173\n", " \n", " \n", " coef_num_preschool_in_hh_work_and_school\n", - " -29.197569\n", + " -0.070125\n", + " -0.070125\n", " -0.1251\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -29.197569\n", " \n", " \n", " coef_num_under_16_not_at_school_school2\n", - " -0.638293\n", + " -0.015345\n", + " -0.015345\n", " 0.0866\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.638293\n", " \n", " \n", " coef_num_under_16_not_at_school_work2\n", - " -0.118991\n", + " 0.168260\n", + " 0.168260\n", " 0.1804\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.118991\n", " \n", " \n", " coef_num_under_16_not_at_school_work_and_school\n", - " -15.357907\n", + " -0.192330\n", + " -0.192330\n", " -0.1955\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -15.357907\n", " \n", " \n", " coef_pre_driving_age_child_school2_asc\n", - " 3.679726\n", + " -4.210709\n", + " -4.210709\n", " -3.9703\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 3.679726\n", " \n", " \n", " coef_pt_worker_work2_asc\n", - " -4.743242\n", + " -3.079547\n", + " -3.079547\n", " -3.0476\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.743242\n", " \n", " \n", " coef_round_trip_auto_time_to_work_school2\n", - " 0.064411\n", + " -0.005959\n", + " -0.005959\n", " -0.0034\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.064411\n", " \n", " \n", " coef_round_trip_auto_time_to_work_work2\n", - " -0.025905\n", + " -0.001855\n", + " -0.001855\n", " -0.0035\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.025905\n", " \n", " \n", " coef_round_trip_auto_time_to_work_work_and_school\n", - " -0.021804\n", + " -0.002208\n", + " -0.002208\n", " -0.0031\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.021804\n", " \n", " \n", " coef_student_employed\n", - " 13.457255\n", + " 2.918973\n", + " 2.918973\n", " 3.0140\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 13.457255\n", " \n", " \n", " coef_unavailable\n", " -999.000000\n", + " -999.000000\n", " -999.0000\n", + " -999.0\n", + " -999.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_under_35_school1\n", " 0.721800\n", + " 0.721800\n", " 0.7218\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.721800\n", " \n", " \n", " coef_under_35_school2\n", - " 15.011164\n", + " 1.230550\n", + " 1.230550\n", " 1.2750\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 15.011164\n", " \n", " \n", " coef_under_35_work1\n", - " 1.038242\n", + " -0.458863\n", + " -0.458863\n", " -0.4629\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.038242\n", " \n", " \n", " coef_under_35_work2\n", - " -0.253875\n", + " 0.005614\n", + " 0.005614\n", " -0.1375\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.253875\n", " \n", " \n", " coef_under_35_work_and_school\n", - " 2.257035\n", + " 1.149726\n", + " 1.149726\n", " 0.9761\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2.257035\n", " \n", " \n", " coef_univ_school2_asc\n", - " -10.233810\n", + " -3.640737\n", + " -3.640737\n", " -3.7429\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -10.233810\n", " \n", " \n", " coef_univ_work1_asc\n", - " 6.475896\n", + " 2.209708\n", + " 2.209708\n", " 2.1660\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 6.475896\n", " \n", " \n", " coef_univ_work2_asc\n", - " 4.833029\n", + " -1.472430\n", + " -1.472430\n", " -1.3965\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4.833029\n", " \n", " \n", " coef_univ_work_and_school_asc\n", - " 8.180927\n", + " 0.173386\n", + " 0.173386\n", " 0.1073\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 8.180927\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "0 0.000000 0.0000 \n", - "coef_can_walk_to_work_and_school 0.071630 0.1391 \n", - "coef_can_walk_to_work_school2 1.368092 0.7114 \n", - "coef_can_walk_to_work_work2 0.651120 0.5268 \n", - "coef_driving_age_child_school2_asc -13.067731 -3.1360 \n", - "coef_driving_age_child_work_and_school_asc -12.605997 -4.4362 \n", - "coef_female_school1 0.247086 0.1592 \n", - "coef_female_school2 -0.301339 0.1140 \n", - "coef_female_work1 -2.242748 0.1737 \n", - "coef_female_work2 -0.387411 -0.2255 \n", - "coef_female_work_and_school -3.218280 -0.3442 \n", - "coef_few_cars_than_drivers_school2 -0.862451 -0.5759 \n", - "coef_ft_worker_work2_asc -5.517933 -3.3781 \n", - "coef_hh_income_gt_50k_school1 0.034700 0.0347 \n", - "coef_hh_income_gt_50k_student_work_and_school -0.921175 -0.0528 \n", - "coef_hh_income_gt_50k_work -1.418551 -0.0528 \n", - "coef_hh_income_gt_50k_worker_work_and_school 0.034700 0.0347 \n", - "coef_home_urban_school1 -0.136100 -0.1361 \n", - "coef_home_urban_school2 -8.455615 0.3170 \n", - "coef_home_urban_work1 4.026796 -0.2831 \n", - "coef_home_urban_work2 2.624854 0.2308 \n", - "coef_home_urban_work_and_school -0.447070 -0.3509 \n", - "coef_no_cars_in_hh_school2 -0.620465 -1.4130 \n", - "coef_no_cars_in_hh_work2 -0.725967 -1.3060 \n", - "coef_no_cars_in_hh_work_and_school -0.775934 -1.3020 \n", - "coef_non_family_hh_category1 -0.250000 -0.2500 \n", - "coef_non_family_hh_category2 5.000771 -0.1792 \n", - "coef_non_student_goes_to_school 3.883000 3.8830 \n", - "coef_num_non_workers_in_hh_school1 0.257400 0.2574 \n", - "coef_num_preschool_in_hh_school1 -0.133500 -0.1335 \n", - "coef_num_preschool_in_hh_school2 0.356660 -0.5577 \n", - "coef_num_preschool_in_hh_work1 -2.930501 0.2191 \n", - "coef_num_preschool_in_hh_work2 0.225173 -0.1478 \n", - "coef_num_preschool_in_hh_work_and_school -29.197569 -0.1251 \n", - "coef_num_under_16_not_at_school_school2 -0.638293 0.0866 \n", - "coef_num_under_16_not_at_school_work2 -0.118991 0.1804 \n", - "coef_num_under_16_not_at_school_work_and_school -15.357907 -0.1955 \n", - "coef_pre_driving_age_child_school2_asc 3.679726 -3.9703 \n", - "coef_pt_worker_work2_asc -4.743242 -3.0476 \n", - "coef_round_trip_auto_time_to_work_school2 0.064411 -0.0034 \n", - "coef_round_trip_auto_time_to_work_work2 -0.025905 -0.0035 \n", - "coef_round_trip_auto_time_to_work_work_and_school -0.021804 -0.0031 \n", - "coef_student_employed 13.457255 3.0140 \n", - "coef_unavailable -999.000000 -999.0000 \n", - "coef_under_35_school1 0.721800 0.7218 \n", - "coef_under_35_school2 15.011164 1.2750 \n", - "coef_under_35_work1 1.038242 -0.4629 \n", - "coef_under_35_work2 -0.253875 -0.1375 \n", - "coef_under_35_work_and_school 2.257035 0.9761 \n", - "coef_univ_school2_asc -10.233810 -3.7429 \n", - "coef_univ_work1_asc 6.475896 2.1660 \n", - "coef_univ_work2_asc 4.833029 -1.3965 \n", - "coef_univ_work_and_school_asc 8.180927 0.1073 \n", + " value best \\\n", + "param_name \n", + "0 0.000000 0.000000 \n", + "coef_can_walk_to_work_and_school 0.284832 0.284832 \n", + "coef_can_walk_to_work_school2 0.811379 0.811379 \n", + "coef_can_walk_to_work_work2 0.600928 0.600928 \n", + "coef_driving_age_child_school2_asc -3.209418 -3.209418 \n", + "coef_driving_age_child_work_and_school_asc -4.565091 -4.565091 \n", + "coef_female_school1 0.000463 0.000463 \n", + "coef_female_school2 -0.016856 -0.016856 \n", + "coef_female_work1 0.333342 0.333342 \n", + "coef_female_work2 -0.219862 -0.219862 \n", + "coef_female_work_and_school -0.265847 -0.265847 \n", + "coef_few_cars_than_drivers_school2 -0.297623 -0.297623 \n", + "coef_ft_worker_work2_asc -3.494595 -3.494595 \n", + "coef_hh_income_gt_50k_school1 0.034700 0.034700 \n", + "coef_hh_income_gt_50k_student_work_and_school -0.128428 -0.128428 \n", + "coef_hh_income_gt_50k_work -0.286159 -0.286159 \n", + "coef_hh_income_gt_50k_worker_work_and_school 0.034700 0.034700 \n", + "coef_home_urban_school1 -0.136100 -0.136100 \n", + "coef_home_urban_school2 0.161745 0.161745 \n", + "coef_home_urban_work1 -0.122770 -0.122770 \n", + "coef_home_urban_work2 0.142218 0.142218 \n", + "coef_home_urban_work_and_school -0.436835 -0.436835 \n", + "coef_no_cars_in_hh_school2 -1.479517 -1.479517 \n", + "coef_no_cars_in_hh_work2 -1.524960 -1.524960 \n", + "coef_no_cars_in_hh_work_and_school -1.244512 -1.244512 \n", + "coef_non_family_hh_category1 -0.250000 -0.250000 \n", + "coef_non_family_hh_category2 -0.091298 -0.091298 \n", + "coef_non_student_goes_to_school 3.883000 3.883000 \n", + "coef_num_non_workers_in_hh_school1 0.257400 0.257400 \n", + "coef_num_preschool_in_hh_school1 -0.133500 -0.133500 \n", + "coef_num_preschool_in_hh_school2 -0.796350 -0.796350 \n", + "coef_num_preschool_in_hh_work1 0.125045 0.125045 \n", + "coef_num_preschool_in_hh_work2 -0.126183 -0.126183 \n", + "coef_num_preschool_in_hh_work_and_school -0.070125 -0.070125 \n", + "coef_num_under_16_not_at_school_school2 -0.015345 -0.015345 \n", + "coef_num_under_16_not_at_school_work2 0.168260 0.168260 \n", + "coef_num_under_16_not_at_school_work_and_school -0.192330 -0.192330 \n", + "coef_pre_driving_age_child_school2_asc -4.210709 -4.210709 \n", + "coef_pt_worker_work2_asc -3.079547 -3.079547 \n", + "coef_round_trip_auto_time_to_work_school2 -0.005959 -0.005959 \n", + "coef_round_trip_auto_time_to_work_work2 -0.001855 -0.001855 \n", + "coef_round_trip_auto_time_to_work_work_and_school -0.002208 -0.002208 \n", + "coef_student_employed 2.918973 2.918973 \n", + "coef_unavailable -999.000000 -999.000000 \n", + "coef_under_35_school1 0.721800 0.721800 \n", + "coef_under_35_school2 1.230550 1.230550 \n", + "coef_under_35_work1 -0.458863 -0.458863 \n", + "coef_under_35_work2 0.005614 0.005614 \n", + "coef_under_35_work_and_school 1.149726 1.149726 \n", + "coef_univ_school2_asc -3.640737 -3.640737 \n", + "coef_univ_work1_asc 2.209708 2.209708 \n", + "coef_univ_work2_asc -1.472430 -1.472430 \n", + "coef_univ_work_and_school_asc 0.173386 0.173386 \n", "\n", - " nullvalue minimum \\\n", - "0 0.0 0.0 \n", - "coef_can_walk_to_work_and_school 0.0 NaN \n", - "coef_can_walk_to_work_school2 0.0 NaN \n", - "coef_can_walk_to_work_work2 0.0 NaN \n", - "coef_driving_age_child_school2_asc 0.0 NaN \n", - "coef_driving_age_child_work_and_school_asc 0.0 NaN \n", - "coef_female_school1 0.0 NaN \n", - "coef_female_school2 0.0 NaN \n", - "coef_female_work1 0.0 NaN \n", - "coef_female_work2 0.0 NaN \n", - "coef_female_work_and_school 0.0 NaN \n", - "coef_few_cars_than_drivers_school2 0.0 NaN \n", - "coef_ft_worker_work2_asc 0.0 NaN \n", - "coef_hh_income_gt_50k_school1 0.0 NaN \n", - "coef_hh_income_gt_50k_student_work_and_school 0.0 NaN \n", - "coef_hh_income_gt_50k_work 0.0 NaN \n", - "coef_hh_income_gt_50k_worker_work_and_school 0.0 NaN \n", - "coef_home_urban_school1 0.0 NaN \n", - "coef_home_urban_school2 0.0 NaN \n", - "coef_home_urban_work1 0.0 NaN \n", - "coef_home_urban_work2 0.0 NaN \n", - "coef_home_urban_work_and_school 0.0 NaN \n", - "coef_no_cars_in_hh_school2 0.0 NaN \n", - "coef_no_cars_in_hh_work2 0.0 NaN \n", - "coef_no_cars_in_hh_work_and_school 0.0 NaN \n", - "coef_non_family_hh_category1 0.0 NaN \n", - "coef_non_family_hh_category2 0.0 NaN \n", - "coef_non_student_goes_to_school 0.0 NaN \n", - "coef_num_non_workers_in_hh_school1 0.0 NaN \n", - "coef_num_preschool_in_hh_school1 0.0 NaN \n", - "coef_num_preschool_in_hh_school2 0.0 NaN \n", - "coef_num_preschool_in_hh_work1 0.0 NaN \n", - "coef_num_preschool_in_hh_work2 0.0 NaN \n", - "coef_num_preschool_in_hh_work_and_school 0.0 NaN \n", - "coef_num_under_16_not_at_school_school2 0.0 NaN \n", - "coef_num_under_16_not_at_school_work2 0.0 NaN \n", - "coef_num_under_16_not_at_school_work_and_school 0.0 NaN \n", - "coef_pre_driving_age_child_school2_asc 0.0 NaN \n", - "coef_pt_worker_work2_asc 0.0 NaN \n", - "coef_round_trip_auto_time_to_work_school2 0.0 NaN \n", - "coef_round_trip_auto_time_to_work_work2 0.0 NaN \n", - "coef_round_trip_auto_time_to_work_work_and_school 0.0 NaN \n", - "coef_student_employed 0.0 NaN \n", - "coef_unavailable 0.0 NaN \n", - "coef_under_35_school1 0.0 NaN \n", - "coef_under_35_school2 0.0 NaN \n", - "coef_under_35_work1 0.0 NaN \n", - "coef_under_35_work2 0.0 NaN \n", - "coef_under_35_work_and_school 0.0 NaN \n", - "coef_univ_school2_asc 0.0 NaN \n", - "coef_univ_work1_asc 0.0 NaN \n", - "coef_univ_work2_asc 0.0 NaN \n", - "coef_univ_work_and_school_asc 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "0 0.0000 0.0 \n", + "coef_can_walk_to_work_and_school 0.1391 -50.0 \n", + "coef_can_walk_to_work_school2 0.7114 -50.0 \n", + "coef_can_walk_to_work_work2 0.5268 -50.0 \n", + "coef_driving_age_child_school2_asc -3.1360 -50.0 \n", + "coef_driving_age_child_work_and_school_asc -4.4362 -50.0 \n", + "coef_female_school1 0.1592 -50.0 \n", + "coef_female_school2 0.1140 -50.0 \n", + "coef_female_work1 0.1737 -50.0 \n", + "coef_female_work2 -0.2255 -50.0 \n", + "coef_female_work_and_school -0.3442 -50.0 \n", + "coef_few_cars_than_drivers_school2 -0.5759 -50.0 \n", + "coef_ft_worker_work2_asc -3.3781 -50.0 \n", + "coef_hh_income_gt_50k_school1 0.0347 -50.0 \n", + "coef_hh_income_gt_50k_student_work_and_school -0.0528 -50.0 \n", + "coef_hh_income_gt_50k_work -0.0528 -50.0 \n", + "coef_hh_income_gt_50k_worker_work_and_school 0.0347 -50.0 \n", + "coef_home_urban_school1 -0.1361 -50.0 \n", + "coef_home_urban_school2 0.3170 -50.0 \n", + "coef_home_urban_work1 -0.2831 -50.0 \n", + "coef_home_urban_work2 0.2308 -50.0 \n", + "coef_home_urban_work_and_school -0.3509 -50.0 \n", + "coef_no_cars_in_hh_school2 -1.4130 -50.0 \n", + "coef_no_cars_in_hh_work2 -1.3060 -50.0 \n", + "coef_no_cars_in_hh_work_and_school -1.3020 -50.0 \n", + "coef_non_family_hh_category1 -0.2500 -50.0 \n", + "coef_non_family_hh_category2 -0.1792 -50.0 \n", + "coef_non_student_goes_to_school 3.8830 -50.0 \n", + "coef_num_non_workers_in_hh_school1 0.2574 -50.0 \n", + "coef_num_preschool_in_hh_school1 -0.1335 -50.0 \n", + "coef_num_preschool_in_hh_school2 -0.5577 -50.0 \n", + "coef_num_preschool_in_hh_work1 0.2191 -50.0 \n", + "coef_num_preschool_in_hh_work2 -0.1478 -50.0 \n", + "coef_num_preschool_in_hh_work_and_school -0.1251 -50.0 \n", + "coef_num_under_16_not_at_school_school2 0.0866 -50.0 \n", + "coef_num_under_16_not_at_school_work2 0.1804 -50.0 \n", + "coef_num_under_16_not_at_school_work_and_school -0.1955 -50.0 \n", + "coef_pre_driving_age_child_school2_asc -3.9703 -50.0 \n", + "coef_pt_worker_work2_asc -3.0476 -50.0 \n", + "coef_round_trip_auto_time_to_work_school2 -0.0034 -50.0 \n", + "coef_round_trip_auto_time_to_work_work2 -0.0035 -50.0 \n", + "coef_round_trip_auto_time_to_work_work_and_school -0.0031 -50.0 \n", + "coef_student_employed 3.0140 -50.0 \n", + "coef_unavailable -999.0000 -999.0 \n", + "coef_under_35_school1 0.7218 -50.0 \n", + "coef_under_35_school2 1.2750 -50.0 \n", + "coef_under_35_work1 -0.4629 -50.0 \n", + "coef_under_35_work2 -0.1375 -50.0 \n", + "coef_under_35_work_and_school 0.9761 -50.0 \n", + "coef_univ_school2_asc -3.7429 -50.0 \n", + "coef_univ_work1_asc 2.1660 -50.0 \n", + "coef_univ_work2_asc -1.3965 -50.0 \n", + "coef_univ_work_and_school_asc 0.1073 -50.0 \n", "\n", - " maximum holdfast note \\\n", - "0 0.0 1 \n", - "coef_can_walk_to_work_and_school NaN 0 \n", - "coef_can_walk_to_work_school2 NaN 0 \n", - "coef_can_walk_to_work_work2 NaN 0 \n", - "coef_driving_age_child_school2_asc NaN 0 \n", - "coef_driving_age_child_work_and_school_asc NaN 0 \n", - "coef_female_school1 NaN 0 \n", - "coef_female_school2 NaN 0 \n", - "coef_female_work1 NaN 0 \n", - "coef_female_work2 NaN 0 \n", - "coef_female_work_and_school NaN 0 \n", - "coef_few_cars_than_drivers_school2 NaN 0 \n", - "coef_ft_worker_work2_asc NaN 0 \n", - "coef_hh_income_gt_50k_school1 NaN 0 \n", - "coef_hh_income_gt_50k_student_work_and_school NaN 0 \n", - "coef_hh_income_gt_50k_work NaN 0 \n", - "coef_hh_income_gt_50k_worker_work_and_school NaN 0 \n", - "coef_home_urban_school1 NaN 0 \n", - "coef_home_urban_school2 NaN 0 \n", - "coef_home_urban_work1 NaN 0 \n", - "coef_home_urban_work2 NaN 0 \n", - "coef_home_urban_work_and_school NaN 0 \n", - "coef_no_cars_in_hh_school2 NaN 0 \n", - "coef_no_cars_in_hh_work2 NaN 0 \n", - "coef_no_cars_in_hh_work_and_school NaN 0 \n", - "coef_non_family_hh_category1 NaN 0 \n", - "coef_non_family_hh_category2 NaN 0 \n", - "coef_non_student_goes_to_school NaN 0 \n", - "coef_num_non_workers_in_hh_school1 NaN 0 \n", - "coef_num_preschool_in_hh_school1 NaN 0 \n", - "coef_num_preschool_in_hh_school2 NaN 0 \n", - "coef_num_preschool_in_hh_work1 NaN 0 \n", - "coef_num_preschool_in_hh_work2 NaN 0 \n", - "coef_num_preschool_in_hh_work_and_school NaN 0 \n", - "coef_num_under_16_not_at_school_school2 NaN 0 \n", - "coef_num_under_16_not_at_school_work2 NaN 0 \n", - "coef_num_under_16_not_at_school_work_and_school NaN 0 \n", - "coef_pre_driving_age_child_school2_asc NaN 0 \n", - "coef_pt_worker_work2_asc NaN 0 \n", - "coef_round_trip_auto_time_to_work_school2 NaN 0 \n", - "coef_round_trip_auto_time_to_work_work2 NaN 0 \n", - "coef_round_trip_auto_time_to_work_work_and_school NaN 0 \n", - "coef_student_employed NaN 0 \n", - "coef_unavailable NaN 1 \n", - "coef_under_35_school1 NaN 0 \n", - "coef_under_35_school2 NaN 0 \n", - "coef_under_35_work1 NaN 0 \n", - "coef_under_35_work2 NaN 0 \n", - "coef_under_35_work_and_school NaN 0 \n", - "coef_univ_school2_asc NaN 0 \n", - "coef_univ_work1_asc NaN 0 \n", - "coef_univ_work2_asc NaN 0 \n", - "coef_univ_work_and_school_asc NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "0 0.0 0.0 \n", + "coef_can_walk_to_work_and_school 50.0 0.0 \n", + "coef_can_walk_to_work_school2 50.0 0.0 \n", + "coef_can_walk_to_work_work2 50.0 0.0 \n", + "coef_driving_age_child_school2_asc 50.0 0.0 \n", + "coef_driving_age_child_work_and_school_asc 50.0 0.0 \n", + "coef_female_school1 50.0 0.0 \n", + "coef_female_school2 50.0 0.0 \n", + "coef_female_work1 50.0 0.0 \n", + "coef_female_work2 50.0 0.0 \n", + "coef_female_work_and_school 50.0 0.0 \n", + "coef_few_cars_than_drivers_school2 50.0 0.0 \n", + "coef_ft_worker_work2_asc 50.0 0.0 \n", + "coef_hh_income_gt_50k_school1 50.0 0.0 \n", + "coef_hh_income_gt_50k_student_work_and_school 50.0 0.0 \n", + "coef_hh_income_gt_50k_work 50.0 0.0 \n", + "coef_hh_income_gt_50k_worker_work_and_school 50.0 0.0 \n", + "coef_home_urban_school1 50.0 0.0 \n", + "coef_home_urban_school2 50.0 0.0 \n", + "coef_home_urban_work1 50.0 0.0 \n", + "coef_home_urban_work2 50.0 0.0 \n", + "coef_home_urban_work_and_school 50.0 0.0 \n", + "coef_no_cars_in_hh_school2 50.0 0.0 \n", + "coef_no_cars_in_hh_work2 50.0 0.0 \n", + "coef_no_cars_in_hh_work_and_school 50.0 0.0 \n", + "coef_non_family_hh_category1 50.0 0.0 \n", + "coef_non_family_hh_category2 50.0 0.0 \n", + "coef_non_student_goes_to_school 50.0 0.0 \n", + "coef_num_non_workers_in_hh_school1 50.0 0.0 \n", + "coef_num_preschool_in_hh_school1 50.0 0.0 \n", + "coef_num_preschool_in_hh_school2 50.0 0.0 \n", + "coef_num_preschool_in_hh_work1 50.0 0.0 \n", + "coef_num_preschool_in_hh_work2 50.0 0.0 \n", + "coef_num_preschool_in_hh_work_and_school 50.0 0.0 \n", + "coef_num_under_16_not_at_school_school2 50.0 0.0 \n", + "coef_num_under_16_not_at_school_work2 50.0 0.0 \n", + "coef_num_under_16_not_at_school_work_and_school 50.0 0.0 \n", + "coef_pre_driving_age_child_school2_asc 50.0 0.0 \n", + "coef_pt_worker_work2_asc 50.0 0.0 \n", + "coef_round_trip_auto_time_to_work_school2 50.0 0.0 \n", + "coef_round_trip_auto_time_to_work_work2 50.0 0.0 \n", + "coef_round_trip_auto_time_to_work_work_and_school 50.0 0.0 \n", + "coef_student_employed 50.0 0.0 \n", + "coef_unavailable -999.0 0.0 \n", + "coef_under_35_school1 50.0 0.0 \n", + "coef_under_35_school2 50.0 0.0 \n", + "coef_under_35_work1 50.0 0.0 \n", + "coef_under_35_work2 50.0 0.0 \n", + "coef_under_35_work_and_school 50.0 0.0 \n", + "coef_univ_school2_asc 50.0 0.0 \n", + "coef_univ_work1_asc 50.0 0.0 \n", + "coef_univ_work2_asc 50.0 0.0 \n", + "coef_univ_work_and_school_asc 50.0 0.0 \n", "\n", - " best \n", - "0 0.000000 \n", - "coef_can_walk_to_work_and_school 0.071630 \n", - "coef_can_walk_to_work_school2 1.368092 \n", - "coef_can_walk_to_work_work2 0.651120 \n", - "coef_driving_age_child_school2_asc -13.067731 \n", - "coef_driving_age_child_work_and_school_asc -12.605997 \n", - "coef_female_school1 0.247086 \n", - "coef_female_school2 -0.301339 \n", - "coef_female_work1 -2.242748 \n", - "coef_female_work2 -0.387411 \n", - "coef_female_work_and_school -3.218280 \n", - "coef_few_cars_than_drivers_school2 -0.862451 \n", - "coef_ft_worker_work2_asc -5.517933 \n", - "coef_hh_income_gt_50k_school1 0.034700 \n", - "coef_hh_income_gt_50k_student_work_and_school -0.921175 \n", - "coef_hh_income_gt_50k_work -1.418551 \n", - "coef_hh_income_gt_50k_worker_work_and_school 0.034700 \n", - "coef_home_urban_school1 -0.136100 \n", - "coef_home_urban_school2 -8.455615 \n", - "coef_home_urban_work1 4.026796 \n", - "coef_home_urban_work2 2.624854 \n", - "coef_home_urban_work_and_school -0.447070 \n", - "coef_no_cars_in_hh_school2 -0.620465 \n", - "coef_no_cars_in_hh_work2 -0.725967 \n", - "coef_no_cars_in_hh_work_and_school -0.775934 \n", - "coef_non_family_hh_category1 -0.250000 \n", - "coef_non_family_hh_category2 5.000771 \n", - "coef_non_student_goes_to_school 3.883000 \n", - "coef_num_non_workers_in_hh_school1 0.257400 \n", - "coef_num_preschool_in_hh_school1 -0.133500 \n", - "coef_num_preschool_in_hh_school2 0.356660 \n", - "coef_num_preschool_in_hh_work1 -2.930501 \n", - "coef_num_preschool_in_hh_work2 0.225173 \n", - "coef_num_preschool_in_hh_work_and_school -29.197569 \n", - "coef_num_under_16_not_at_school_school2 -0.638293 \n", - "coef_num_under_16_not_at_school_work2 -0.118991 \n", - "coef_num_under_16_not_at_school_work_and_school -15.357907 \n", - "coef_pre_driving_age_child_school2_asc 3.679726 \n", - "coef_pt_worker_work2_asc -4.743242 \n", - "coef_round_trip_auto_time_to_work_school2 0.064411 \n", - "coef_round_trip_auto_time_to_work_work2 -0.025905 \n", - "coef_round_trip_auto_time_to_work_work_and_school -0.021804 \n", - "coef_student_employed 13.457255 \n", - "coef_unavailable -999.000000 \n", - "coef_under_35_school1 0.721800 \n", - "coef_under_35_school2 15.011164 \n", - "coef_under_35_work1 1.038242 \n", - "coef_under_35_work2 -0.253875 \n", - "coef_under_35_work_and_school 2.257035 \n", - "coef_univ_school2_asc -10.233810 \n", - "coef_univ_work1_asc 6.475896 \n", - "coef_univ_work2_asc 4.833029 \n", - "coef_univ_work_and_school_asc 8.180927 " + " holdfast \n", + "param_name \n", + "0 1 \n", + "coef_can_walk_to_work_and_school 0 \n", + "coef_can_walk_to_work_school2 0 \n", + "coef_can_walk_to_work_work2 0 \n", + "coef_driving_age_child_school2_asc 0 \n", + "coef_driving_age_child_work_and_school_asc 0 \n", + "coef_female_school1 0 \n", + "coef_female_school2 0 \n", + "coef_female_work1 0 \n", + "coef_female_work2 0 \n", + "coef_female_work_and_school 0 \n", + "coef_few_cars_than_drivers_school2 0 \n", + "coef_ft_worker_work2_asc 0 \n", + "coef_hh_income_gt_50k_school1 0 \n", + "coef_hh_income_gt_50k_student_work_and_school 0 \n", + "coef_hh_income_gt_50k_work 0 \n", + "coef_hh_income_gt_50k_worker_work_and_school 0 \n", + "coef_home_urban_school1 0 \n", + "coef_home_urban_school2 0 \n", + "coef_home_urban_work1 0 \n", + "coef_home_urban_work2 0 \n", + "coef_home_urban_work_and_school 0 \n", + "coef_no_cars_in_hh_school2 0 \n", + "coef_no_cars_in_hh_work2 0 \n", + "coef_no_cars_in_hh_work_and_school 0 \n", + "coef_non_family_hh_category1 0 \n", + "coef_non_family_hh_category2 0 \n", + "coef_non_student_goes_to_school 0 \n", + "coef_num_non_workers_in_hh_school1 0 \n", + "coef_num_preschool_in_hh_school1 0 \n", + "coef_num_preschool_in_hh_school2 0 \n", + "coef_num_preschool_in_hh_work1 0 \n", + "coef_num_preschool_in_hh_work2 0 \n", + "coef_num_preschool_in_hh_work_and_school 0 \n", + "coef_num_under_16_not_at_school_school2 0 \n", + "coef_num_under_16_not_at_school_work2 0 \n", + "coef_num_under_16_not_at_school_work_and_school 0 \n", + "coef_pre_driving_age_child_school2_asc 0 \n", + "coef_pt_worker_work2_asc 0 \n", + "coef_round_trip_auto_time_to_work_school2 0 \n", + "coef_round_trip_auto_time_to_work_work2 0 \n", + "coef_round_trip_auto_time_to_work_work_and_school 0 \n", + "coef_student_employed 0 \n", + "coef_unavailable 1 \n", + "coef_under_35_school1 0 \n", + "coef_under_35_school2 0 \n", + "coef_under_35_work1 0 \n", + "coef_under_35_work2 0 \n", + "coef_under_35_work_and_school 0 \n", + "coef_univ_school2_asc 0 \n", + "coef_univ_work1_asc 0 \n", + "coef_univ_work2_asc 0 \n", + "coef_univ_work_and_school_asc 0 " ] }, "metadata": {}, @@ -2039,12 +2040,8 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate()\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.771611294971759e-29 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - ":1: RuntimeWarning: invalid value encountered in sqrt\n", - " model.estimate()\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { @@ -2064,51 +2061,51 @@ " \n", " \n", " coef_can_walk_to_work_and_school\n", - " 0.071630\n", + " 0.284832\n", " \n", " \n", " coef_can_walk_to_work_school2\n", - " 1.368092\n", + " 0.811379\n", " \n", " \n", " coef_can_walk_to_work_work2\n", - " 0.651120\n", + " 0.600928\n", " \n", " \n", " coef_driving_age_child_school2_asc\n", - " -13.067731\n", + " -3.209418\n", " \n", " \n", " coef_driving_age_child_work_and_school_asc\n", - " -12.605997\n", + " -4.565091\n", " \n", " \n", " coef_female_school1\n", - " 0.247086\n", + " 0.000463\n", " \n", " \n", " coef_female_school2\n", - " -0.301339\n", + " -0.016856\n", " \n", " \n", " coef_female_work1\n", - " -2.242748\n", + " 0.333342\n", " \n", " \n", " coef_female_work2\n", - " -0.387411\n", + " -0.219862\n", " \n", " \n", " coef_female_work_and_school\n", - " -3.218280\n", + " -0.265847\n", " \n", " \n", " coef_few_cars_than_drivers_school2\n", - " -0.862451\n", + " -0.297623\n", " \n", " \n", " coef_ft_worker_work2_asc\n", - " -5.517933\n", + " -3.494595\n", " \n", " \n", " coef_hh_income_gt_50k_school1\n", @@ -2116,11 +2113,11 @@ " \n", " \n", " coef_hh_income_gt_50k_student_work_and_school\n", - " -0.921175\n", + " -0.128428\n", " \n", " \n", " coef_hh_income_gt_50k_work\n", - " -1.418551\n", + " -0.286159\n", " \n", " \n", " coef_hh_income_gt_50k_worker_work_and_school\n", @@ -2132,31 +2129,31 @@ " \n", " \n", " coef_home_urban_school2\n", - " -8.455615\n", + " 0.161745\n", " \n", " \n", " coef_home_urban_work1\n", - " 4.026796\n", + " -0.122770\n", " \n", " \n", " coef_home_urban_work2\n", - " 2.624854\n", + " 0.142218\n", " \n", " \n", " coef_home_urban_work_and_school\n", - " -0.447070\n", + " -0.436835\n", " \n", " \n", " coef_no_cars_in_hh_school2\n", - " -0.620465\n", + " -1.479517\n", " \n", " \n", " coef_no_cars_in_hh_work2\n", - " -0.725967\n", + " -1.524960\n", " \n", " \n", " coef_no_cars_in_hh_work_and_school\n", - " -0.775934\n", + " -1.244512\n", " \n", " \n", " coef_non_family_hh_category1\n", @@ -2164,7 +2161,7 @@ " \n", " \n", " coef_non_family_hh_category2\n", - " 5.000771\n", + " -0.091298\n", " \n", " \n", " coef_non_student_goes_to_school\n", @@ -2180,55 +2177,55 @@ " \n", " \n", " coef_num_preschool_in_hh_school2\n", - " 0.356660\n", + " -0.796350\n", " \n", " \n", " coef_num_preschool_in_hh_work1\n", - " -2.930501\n", + " 0.125045\n", " \n", " \n", " coef_num_preschool_in_hh_work2\n", - " 0.225173\n", + " -0.126183\n", " \n", " \n", " coef_num_preschool_in_hh_work_and_school\n", - " -29.197569\n", + " -0.070125\n", " \n", " \n", " coef_num_under_16_not_at_school_school2\n", - " -0.638293\n", + " -0.015345\n", " \n", " \n", " coef_num_under_16_not_at_school_work2\n", - " -0.118991\n", + " 0.168260\n", " \n", " \n", " coef_num_under_16_not_at_school_work_and_school\n", - " -15.357907\n", + " -0.192330\n", " \n", " \n", " coef_pre_driving_age_child_school2_asc\n", - " 3.679726\n", + " -4.210709\n", " \n", " \n", " coef_pt_worker_work2_asc\n", - " -4.743242\n", + " -3.079547\n", " \n", " \n", " coef_round_trip_auto_time_to_work_school2\n", - " 0.064411\n", + " -0.005959\n", " \n", " \n", " coef_round_trip_auto_time_to_work_work2\n", - " -0.025905\n", + " -0.001855\n", " \n", " \n", " coef_round_trip_auto_time_to_work_work_and_school\n", - " -0.021804\n", + " -0.002208\n", " \n", " \n", " coef_student_employed\n", - " 13.457255\n", + " 2.918973\n", " \n", " \n", " coef_unavailable\n", @@ -2240,38 +2237,38 @@ " \n", " \n", " coef_under_35_school2\n", - " 15.011164\n", + " 1.230550\n", " \n", " \n", " coef_under_35_work1\n", - " 1.038242\n", + " -0.458863\n", " \n", " \n", " coef_under_35_work2\n", - " -0.253875\n", + " 0.005614\n", " \n", " \n", " coef_under_35_work_and_school\n", - " 2.257035\n", + " 1.149726\n", " \n", " \n", " coef_univ_school2_asc\n", - " -10.233810\n", + " -3.640737\n", " \n", " \n", " coef_univ_work1_asc\n", - " 6.475896\n", + " 2.209708\n", " \n", " \n", " coef_univ_work2_asc\n", - " 4.833029\n", + " -1.472430\n", " \n", " \n", " coef_univ_work_and_school_asc\n", - " 8.180927\n", + " 0.173386\n", " \n", " \n", - "loglike-410.2201502048449d_loglike\n", + "
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00.000000e+000.000000
coef_can_walk_to_work_and_school-2.159761e-05-0.000048
coef_can_walk_to_work_school2-7.694778e-050.000193
coef_can_walk_to_work_work24.202731e-05-0.000216
coef_driving_age_child_school2_asc-4.255256e-08-0.000081
coef_driving_age_child_work_and_school_asc2.167724e-050.000044
coef_female_school1-6.957308e-05-0.000091
coef_female_school2-2.554309e-040.000133
coef_female_work1-7.357671e-050.000084
coef_female_work28.686757e-05-0.000073
coef_female_work_and_school1.188196e-050.000059
coef_few_cars_than_drivers_school2-2.286678e-040.000044
coef_ft_worker_work2_asc5.501466e-05-0.000349
coef_hh_income_gt_50k_school10.000000e+000.000000
coef_hh_income_gt_50k_student_work_and_school6.367109e-06-0.000180
coef_hh_income_gt_50k_work-1.223654e-050.000049
coef_hh_income_gt_50k_worker_work_and_school0.000000e+000.000000
coef_home_urban_school10.000000e+000.000000
coef_home_urban_school2-1.028755e-040.000081
coef_home_urban_work1-4.465713e-05-0.000036
coef_home_urban_work21.557017e-04-0.000060
coef_home_urban_work_and_school1.077213e-040.000041
coef_no_cars_in_hh_school28.945645e-05-0.000061
coef_no_cars_in_hh_work23.899664e-05-0.000129
coef_no_cars_in_hh_work_and_school-3.695621e-050.000036
coef_non_family_hh_category10.000000e+000.000000
coef_non_family_hh_category21.251878e-100.000057
coef_non_student_goes_to_school0.000000e+000.000000
coef_num_non_workers_in_hh_school10.000000e+000.000000
coef_num_preschool_in_hh_school10.000000e+000.000000
coef_num_preschool_in_hh_school23.508996e-050.000013
coef_num_preschool_in_hh_work1-2.217197e-050.000012
coef_num_preschool_in_hh_work28.498540e-050.000204
coef_num_preschool_in_hh_work_and_school-3.475886e-12-0.000049
coef_num_under_16_not_at_school_school2-8.486532e-050.000086
coef_num_under_16_not_at_school_work2-3.959448e-050.000236
coef_num_under_16_not_at_school_work_and_school-2.351049e-07-0.000025
coef_pre_driving_age_child_school2_asc6.171829e-060.000137
coef_pt_worker_work2_asc1.420463e-04-0.000007
coef_round_trip_auto_time_to_work_school2-4.638296e-030.000126
coef_round_trip_auto_time_to_work_work23.215960e-030.000199
coef_round_trip_auto_time_to_work_work_and_school1.679772e-030.000093
coef_student_employed2.170492e-050.000041
coef_unavailable0.000000e+000.000000
coef_under_35_school10.000000e+000.000000
coef_under_35_school2-1.082319e-04-0.000063
coef_under_35_work1-9.399930e-050.000101
coef_under_35_work27.788570e-05-0.000136
coef_under_35_work_and_school-1.237585e-04-0.000093
coef_univ_school2_asc-1.090048e-040.000045
coef_univ_work1_asc-4.465713e-050.000111
coef_univ_work2_asc-4.135926e-050.000065
coef_univ_work_and_school_asc8.604407e-05-0.000179
nit50nfev84njev50status0message'Optimization terminated successfully'successTrueelapsed_time0:00:03.886165method'slsqp'n_cases2620iteration_number50logloss0.15657257641406294" + "nit34nfev39njev34status0message'Optimization terminated successfully'successTrueelapsed_time0:00:01.181912method'slsqp'n_cases31768iteration_number34loglike-4677.236180934496" ], "text/plain": [ "┣ x: 0 0.000000\n", - "┃ coef_can_walk_to_work_and_school 0.071630\n", - "┃ coef_can_walk_to_work_school2 1.368092\n", - "┃ coef_can_walk_to_work_work2 0.651120\n", - "┃ coef_driving_age_child_school2_asc -13.067731\n", - "┃ coef_driving_age_child_work_and_school_asc -12.605997\n", - "┃ coef_female_school1 0.247086\n", - "┃ coef_female_school2 -0.301339\n", - "┃ coef_female_work1 -2.242748\n", - "┃ coef_female_work2 -0.387411\n", - "┃ coef_female_work_and_school -3.218280\n", - "┃ coef_few_cars_than_drivers_school2 -0.862451\n", - "┃ coef_ft_worker_work2_asc -5.517933\n", + "┃ coef_can_walk_to_work_and_school 0.284832\n", + "┃ coef_can_walk_to_work_school2 0.811379\n", + "┃ coef_can_walk_to_work_work2 0.600928\n", + "┃ coef_driving_age_child_school2_asc -3.209418\n", + "┃ coef_driving_age_child_work_and_school_asc -4.565091\n", + "┃ coef_female_school1 0.000463\n", + "┃ coef_female_school2 -0.016856\n", + "┃ coef_female_work1 0.333342\n", + "┃ coef_female_work2 -0.219862\n", + "┃ coef_female_work_and_school -0.265847\n", + "┃ coef_few_cars_than_drivers_school2 -0.297623\n", + "┃ coef_ft_worker_work2_asc -3.494595\n", "┃ coef_hh_income_gt_50k_school1 0.034700\n", - "┃ coef_hh_income_gt_50k_student_work_and_school -0.921175\n", - "┃ coef_hh_income_gt_50k_work -1.418551\n", + "┃ coef_hh_income_gt_50k_student_work_and_school -0.128428\n", + "┃ coef_hh_income_gt_50k_work -0.286159\n", "┃ coef_hh_income_gt_50k_worker_work_and_school 0.034700\n", "┃ coef_home_urban_school1 -0.136100\n", - "┃ coef_home_urban_school2 -8.455615\n", - "┃ coef_home_urban_work1 4.026796\n", - "┃ coef_home_urban_work2 2.624854\n", - "┃ coef_home_urban_work_and_school -0.447070\n", - "┃ coef_no_cars_in_hh_school2 -0.620465\n", - "┃ coef_no_cars_in_hh_work2 -0.725967\n", - "┃ coef_no_cars_in_hh_work_and_school -0.775934\n", + "┃ coef_home_urban_school2 0.161745\n", + "┃ coef_home_urban_work1 -0.122770\n", + "┃ coef_home_urban_work2 0.142218\n", + "┃ coef_home_urban_work_and_school -0.436835\n", + "┃ coef_no_cars_in_hh_school2 -1.479517\n", + "┃ coef_no_cars_in_hh_work2 -1.524960\n", + "┃ coef_no_cars_in_hh_work_and_school -1.244512\n", "┃ coef_non_family_hh_category1 -0.250000\n", - "┃ coef_non_family_hh_category2 5.000771\n", + "┃ coef_non_family_hh_category2 -0.091298\n", "┃ coef_non_student_goes_to_school 3.883000\n", "┃ coef_num_non_workers_in_hh_school1 0.257400\n", "┃ coef_num_preschool_in_hh_school1 -0.133500\n", - "┃ coef_num_preschool_in_hh_school2 0.356660\n", - "┃ coef_num_preschool_in_hh_work1 -2.930501\n", - "┃ coef_num_preschool_in_hh_work2 0.225173\n", - "┃ coef_num_preschool_in_hh_work_and_school -29.197569\n", - "┃ coef_num_under_16_not_at_school_school2 -0.638293\n", - "┃ coef_num_under_16_not_at_school_work2 -0.118991\n", - "┃ coef_num_under_16_not_at_school_work_and_school -15.357907\n", - "┃ coef_pre_driving_age_child_school2_asc 3.679726\n", - "┃ coef_pt_worker_work2_asc -4.743242\n", - "┃ coef_round_trip_auto_time_to_work_school2 0.064411\n", - "┃ coef_round_trip_auto_time_to_work_work2 -0.025905\n", - "┃ coef_round_trip_auto_time_to_work_work_and_school -0.021804\n", - "┃ coef_student_employed 13.457255\n", + "┃ coef_num_preschool_in_hh_school2 -0.796350\n", + "┃ coef_num_preschool_in_hh_work1 0.125045\n", + "┃ coef_num_preschool_in_hh_work2 -0.126183\n", + "┃ coef_num_preschool_in_hh_work_and_school -0.070125\n", + "┃ coef_num_under_16_not_at_school_school2 -0.015345\n", + "┃ coef_num_under_16_not_at_school_work2 0.168260\n", + "┃ coef_num_under_16_not_at_school_work_and_school -0.192330\n", + "┃ coef_pre_driving_age_child_school2_asc -4.210709\n", + "┃ coef_pt_worker_work2_asc -3.079547\n", + "┃ coef_round_trip_auto_time_to_work_school2 -0.005959\n", + "┃ coef_round_trip_auto_time_to_work_work2 -0.001855\n", + "┃ coef_round_trip_auto_time_to_work_work_and_school -0.002208\n", + "┃ coef_student_employed 2.918973\n", "┃ coef_unavailable -999.000000\n", "┃ coef_under_35_school1 0.721800\n", - "┃ coef_under_35_school2 15.011164\n", - "┃ coef_under_35_work1 1.038242\n", - "┃ coef_under_35_work2 -0.253875\n", - "┃ coef_under_35_work_and_school 2.257035\n", - "┃ coef_univ_school2_asc -10.233810\n", - "┃ coef_univ_work1_asc 6.475896\n", - "┃ coef_univ_work2_asc 4.833029\n", - "┃ coef_univ_work_and_school_asc 8.180927\n", + "┃ coef_under_35_school2 1.230550\n", + "┃ coef_under_35_work1 -0.458863\n", + "┃ coef_under_35_work2 0.005614\n", + "┃ coef_under_35_work_and_school 1.149726\n", + "┃ coef_univ_school2_asc -3.640737\n", + "┃ coef_univ_work1_asc 2.209708\n", + "┃ coef_univ_work2_asc -1.472430\n", + "┃ coef_univ_work_and_school_asc 0.173386\n", "┃ dtype: float64\n", - "┣ loglike: -410.2201502048449\n", - "┣ d_loglike: 0 0.000000e+00\n", - "┃ coef_can_walk_to_work_and_school -2.159761e-05\n", - "┃ coef_can_walk_to_work_school2 -7.694778e-05\n", - "┃ coef_can_walk_to_work_work2 4.202731e-05\n", - "┃ coef_driving_age_child_school2_asc -4.255256e-08\n", - "┃ coef_driving_age_child_work_and_school_asc 2.167724e-05\n", - "┃ coef_female_school1 -6.957308e-05\n", - "┃ coef_female_school2 -2.554309e-04\n", - "┃ coef_female_work1 -7.357671e-05\n", - "┃ coef_female_work2 8.686757e-05\n", - "┃ coef_female_work_and_school 1.188196e-05\n", - "┃ coef_few_cars_than_drivers_school2 -2.286678e-04\n", - "┃ coef_ft_worker_work2_asc 5.501466e-05\n", - "┃ coef_hh_income_gt_50k_school1 0.000000e+00\n", - "┃ coef_hh_income_gt_50k_student_work_and_school 6.367109e-06\n", - "┃ coef_hh_income_gt_50k_work -1.223654e-05\n", - "┃ coef_hh_income_gt_50k_worker_work_and_school 0.000000e+00\n", - "┃ coef_home_urban_school1 0.000000e+00\n", - "┃ coef_home_urban_school2 -1.028755e-04\n", - "┃ coef_home_urban_work1 -4.465713e-05\n", - "┃ coef_home_urban_work2 1.557017e-04\n", - "┃ coef_home_urban_work_and_school 1.077213e-04\n", - "┃ coef_no_cars_in_hh_school2 8.945645e-05\n", - "┃ coef_no_cars_in_hh_work2 3.899664e-05\n", - "┃ coef_no_cars_in_hh_work_and_school -3.695621e-05\n", - "┃ coef_non_family_hh_category1 0.000000e+00\n", - "┃ coef_non_family_hh_category2 1.251878e-10\n", - "┃ coef_non_student_goes_to_school 0.000000e+00\n", - "┃ coef_num_non_workers_in_hh_school1 0.000000e+00\n", - "┃ coef_num_preschool_in_hh_school1 0.000000e+00\n", - "┃ coef_num_preschool_in_hh_school2 3.508996e-05\n", - "┃ coef_num_preschool_in_hh_work1 -2.217197e-05\n", - "┃ coef_num_preschool_in_hh_work2 8.498540e-05\n", - "┃ coef_num_preschool_in_hh_work_and_school -3.475886e-12\n", - "┃ coef_num_under_16_not_at_school_school2 -8.486532e-05\n", - "┃ coef_num_under_16_not_at_school_work2 -3.959448e-05\n", - "┃ coef_num_under_16_not_at_school_work_and_school -2.351049e-07\n", - "┃ coef_pre_driving_age_child_school2_asc 6.171829e-06\n", - "┃ coef_pt_worker_work2_asc 1.420463e-04\n", - "┃ coef_round_trip_auto_time_to_work_school2 -4.638296e-03\n", - "┃ coef_round_trip_auto_time_to_work_work2 3.215960e-03\n", - "┃ coef_round_trip_auto_time_to_work_work_and_school 1.679772e-03\n", - "┃ coef_student_employed 2.170492e-05\n", - "┃ coef_unavailable 0.000000e+00\n", - "┃ coef_under_35_school1 0.000000e+00\n", - "┃ coef_under_35_school2 -1.082319e-04\n", - "┃ coef_under_35_work1 -9.399930e-05\n", - "┃ coef_under_35_work2 7.788570e-05\n", - "┃ coef_under_35_work_and_school -1.237585e-04\n", - "┃ coef_univ_school2_asc -1.090048e-04\n", - "┃ coef_univ_work1_asc -4.465713e-05\n", - "┃ coef_univ_work2_asc -4.135926e-05\n", - "┃ coef_univ_work_and_school_asc 8.604407e-05\n", + "┣ logloss: 0.1472310558088169\n", + "┣ d_logloss: 0 0.000000\n", + "┃ coef_can_walk_to_work_and_school -0.000048\n", + "┃ coef_can_walk_to_work_school2 0.000193\n", + "┃ coef_can_walk_to_work_work2 -0.000216\n", + "┃ coef_driving_age_child_school2_asc -0.000081\n", + "┃ coef_driving_age_child_work_and_school_asc 0.000044\n", + "┃ coef_female_school1 -0.000091\n", + "┃ coef_female_school2 0.000133\n", + "┃ coef_female_work1 0.000084\n", + "┃ coef_female_work2 -0.000073\n", + "┃ coef_female_work_and_school 0.000059\n", + "┃ coef_few_cars_than_drivers_school2 0.000044\n", + "┃ coef_ft_worker_work2_asc -0.000349\n", + "┃ coef_hh_income_gt_50k_school1 0.000000\n", + "┃ coef_hh_income_gt_50k_student_work_and_school -0.000180\n", + "┃ coef_hh_income_gt_50k_work 0.000049\n", + "┃ coef_hh_income_gt_50k_worker_work_and_school 0.000000\n", + "┃ coef_home_urban_school1 0.000000\n", + "┃ coef_home_urban_school2 0.000081\n", + "┃ coef_home_urban_work1 -0.000036\n", + "┃ coef_home_urban_work2 -0.000060\n", + "┃ coef_home_urban_work_and_school 0.000041\n", + "┃ coef_no_cars_in_hh_school2 -0.000061\n", + "┃ coef_no_cars_in_hh_work2 -0.000129\n", + "┃ coef_no_cars_in_hh_work_and_school 0.000036\n", + "┃ coef_non_family_hh_category1 0.000000\n", + "┃ coef_non_family_hh_category2 0.000057\n", + "┃ coef_non_student_goes_to_school 0.000000\n", + "┃ coef_num_non_workers_in_hh_school1 0.000000\n", + "┃ coef_num_preschool_in_hh_school1 0.000000\n", + "┃ coef_num_preschool_in_hh_school2 0.000013\n", + "┃ coef_num_preschool_in_hh_work1 0.000012\n", + "┃ coef_num_preschool_in_hh_work2 0.000204\n", + "┃ coef_num_preschool_in_hh_work_and_school -0.000049\n", + "┃ coef_num_under_16_not_at_school_school2 0.000086\n", + "┃ coef_num_under_16_not_at_school_work2 0.000236\n", + "┃ coef_num_under_16_not_at_school_work_and_school -0.000025\n", + "┃ coef_pre_driving_age_child_school2_asc 0.000137\n", + "┃ coef_pt_worker_work2_asc -0.000007\n", + "┃ coef_round_trip_auto_time_to_work_school2 0.000126\n", + "┃ coef_round_trip_auto_time_to_work_work2 0.000199\n", + "┃ coef_round_trip_auto_time_to_work_work_and_school 0.000093\n", + "┃ coef_student_employed 0.000041\n", + "┃ coef_unavailable 0.000000\n", + "┃ coef_under_35_school1 0.000000\n", + "┃ coef_under_35_school2 -0.000063\n", + "┃ coef_under_35_work1 0.000101\n", + "┃ coef_under_35_work2 -0.000136\n", + "┃ coef_under_35_work_and_school -0.000093\n", + "┃ coef_univ_school2_asc 0.000045\n", + "┃ coef_univ_work1_asc 0.000111\n", + "┃ coef_univ_work2_asc 0.000065\n", + "┃ coef_univ_work_and_school_asc -0.000179\n", "┃ dtype: float64\n", - "┣ nit: 50\n", - "┣ nfev: 84\n", - "┣ njev: 50\n", + "┣ nit: 34\n", + "┣ nfev: 39\n", + "┣ njev: 34\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=3, microseconds=886165)\n", + "┣ elapsed_time: datetime.timedelta(seconds=1, microseconds=181912)\n", "┣ method: 'slsqp'\n", - "┣ n_cases: 2620\n", - "┣ iteration_number: 50\n", - "┣ logloss: 0.15657257641406294" + "┣ n_cases: 31768\n", + "┣ iteration_number: 34\n", + "┣ loglike: -4677.236180934496" ] }, "execution_count": 7, @@ -2641,550 +2638,523 @@ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
0 0.00 NA NA NA 0.00fixed value
coef_can_walk_to_work_and_school 0.0716 0.710 0.10 NA 0.00
coef_can_walk_to_work_school2 1.37 0.878 1.56 NA 0.00
coef_can_walk_to_work_work2 0.651 0.397 1.64 NA 0.00
coef_driving_age_child_school2_asc-13.1 4.56e+03-0.00 NA 0.00
coef_driving_age_child_work_and_school_asc-12.6 NA NA[***] 68.07 0.00
coef_female_school1 0.247 1.35 0.18 NA 0.00
coef_female_school2-0.301 0.785-0.38 NA 0.00
coef_female_work1-2.24 1.34-1.68 NA 0.00
coef_female_work2-0.387 0.246-1.57 NA 0.00
coef_female_work_and_school-3.22 1.40-2.30* NA 0.00
coef_few_cars_than_drivers_school2-0.862 0.715-1.21 NA 0.00
coef_ft_worker_work2_asc-5.52 NA NA[***] BIG 0.00
coef_hh_income_gt_50k_school1 0.0347 NA NA[] 0.00 0.00
coef_hh_income_gt_50k_student_work_and_school-0.921 1.85-0.50 NA 0.00
coef_hh_income_gt_50k_work-1.42 1.92-0.74 NA 0.00
coef_hh_income_gt_50k_worker_work_and_school 0.0347 NA NA[] 0.00 0.00
coef_home_urban_school1-0.136 NA NA[] 0.00 0.00
coef_home_urban_school2-8.46 NA NA[***] BIG 0.00
coef_home_urban_work1 4.03 NA NA[***] 165.42 0.00
coef_home_urban_work2 2.62 NA NA[***] 134.83 0.00
coef_home_urban_work_and_school-0.447 NA NA[] 1.59 0.00
coef_no_cars_in_hh_school2-0.620 1.18-0.52 NA 0.00
coef_no_cars_in_hh_work2-0.726 0.336-2.16* NA 0.00
coef_no_cars_in_hh_work_and_school-0.776 0.703-1.10 NA 0.00
coef_non_family_hh_category1-0.250 NA NA[] 0.00 0.00
coef_non_family_hh_category2 5.00 NA NA[] 0.00 0.00
coef_non_student_goes_to_school 3.88 NA NA[] 0.00 0.00
coef_num_non_workers_in_hh_school1 0.257 NA NA[] 0.00 0.00
coef_num_preschool_in_hh_school1-0.134 NA NA[] 0.00 0.00
coef_num_preschool_in_hh_school2 0.357 0.576 0.62 NA 0.00
coef_num_preschool_in_hh_work1-2.93 1.55-1.89 NA 0.00
coef_num_preschool_in_hh_work2 0.225 0.192 1.17 NA 0.00
coef_num_preschool_in_hh_work_and_school-29.2 NA NA[**] 4.26 0.00
coef_num_under_16_not_at_school_school2-0.638 1.02-0.63 NA 0.00
coef_num_under_16_not_at_school_work2-0.119 0.306-0.39 NA 0.00
coef_num_under_16_not_at_school_work_and_school-15.4 2.03e+03-0.01 NA 0.00
coef_pre_driving_age_child_school2_asc 3.68 NA NA[***] 18.81 0.00
coef_pt_worker_work2_asc-4.74 NA NA[***] 562.79 0.00
coef_round_trip_auto_time_to_work_school2 0.0644 0.0331 1.95 NA 0.00
coef_round_trip_auto_time_to_work_work2-0.0259 0.0249-1.04 NA 0.00
coef_round_trip_auto_time_to_work_work_and_school-0.0218 0.0402-0.54 NA 0.00
coef_student_employed 13.5 1.31e+03 0.01 NA 0.00
coef_unavailable-999. NA NA NA 0.00fixed value
coef_under_35_school1 0.722 0.00 NA[] 0.00 0.00
coef_under_35_school2 15.0 1.14e+03 0.01 NA 0.00
coef_under_35_work1 1.04 0.886 1.17 NA 0.00
coef_under_35_work2-0.254 0.245-1.03 NA 0.00
coef_under_35_work_and_school 2.26 1.21 1.87 NA 0.00
coef_univ_school2_asc-10.2 NA NA[***] 556.91 0.00
coef_univ_work1_asc 6.48 NA NA[***] 349.23 0.00
coef_univ_work2_asc 4.83 NA NA[***] 26.10 0.00
coef_univ_work_and_school_asc 8.18 NA NA[***] 132.81 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
0 0.00 0.00 NA 0.00fixed value
coef_can_walk_to_work_and_school 0.285 0.165 1.73 0.00
coef_can_walk_to_work_school2 0.811 0.163 4.97*** 0.00
coef_can_walk_to_work_work2 0.601 0.103 5.81*** 0.00
coef_driving_age_child_school2_asc-3.21 0.230-13.96*** 0.00
coef_driving_age_child_work_and_school_asc-4.57 889.-0.01 0.00
coef_female_school1 0.000463 0.265 0.00 0.00
coef_female_school2-0.0169 0.166-0.10 0.00
coef_female_work1 0.333 0.257 1.30 0.00
coef_female_work2-0.220 0.0801-2.75** 0.00
coef_female_work_and_school-0.266 0.240-1.11 0.00
coef_few_cars_than_drivers_school2-0.298 0.146-2.04* 0.00
coef_ft_worker_work2_asc-3.49 0.110-31.78*** 0.00
coef_hh_income_gt_50k_school1 0.0347 1.34e-05 BIG*** 0.00
coef_hh_income_gt_50k_student_work_and_school-0.128 0.325-0.39 0.00
coef_hh_income_gt_50k_work-0.286 0.351-0.81 0.00
coef_hh_income_gt_50k_worker_work_and_school 0.0347 NA NA 0.00
coef_home_urban_school1-0.136 NA NA 0.00
coef_home_urban_school2 0.162 0.147 1.10 0.00
coef_home_urban_work1-0.123 0.280-0.44 0.00
coef_home_urban_work2 0.142 0.0850 1.67 0.00
coef_home_urban_work_and_school-0.437 0.269-1.62 0.00
coef_no_cars_in_hh_school2-1.48 0.438-3.37*** 0.00
coef_no_cars_in_hh_work2-1.52 0.310-4.92*** 0.00
coef_no_cars_in_hh_work_and_school-1.24 0.334-3.72*** 0.00
coef_non_family_hh_category1-0.250 NA NA 0.00
coef_non_family_hh_category2-0.0913 0.741-0.12 0.00
coef_non_student_goes_to_school 3.88 7.74e-06 BIG*** 0.00
coef_num_non_workers_in_hh_school1 0.257 2.54e-06 BIG*** 0.00
coef_num_preschool_in_hh_school1-0.133 1.09e-06-BIG*** 0.00
coef_num_preschool_in_hh_school2-0.796 0.214-3.72*** 0.00
coef_num_preschool_in_hh_work1 0.125 0.323 0.39 0.00
coef_num_preschool_in_hh_work2-0.126 0.0781-1.62 0.00
coef_num_preschool_in_hh_work_and_school-0.0701 0.322-0.22 0.00
coef_num_under_16_not_at_school_school2-0.0153 0.176-0.09 0.00
coef_num_under_16_not_at_school_work2 0.168 0.0783 2.15* 0.00
coef_num_under_16_not_at_school_work_and_school-0.192 0.210-0.92 0.00
coef_pre_driving_age_child_school2_asc-4.21 0.204-20.62*** 0.00
coef_pt_worker_work2_asc-3.08 0.135-22.84*** 0.00
coef_round_trip_auto_time_to_work_school2-0.00596 0.00317-1.88 0.00
coef_round_trip_auto_time_to_work_work2-0.00185 0.00188-0.99 0.00
coef_round_trip_auto_time_to_work_work_and_school-0.00221 0.00565-0.39 0.00
coef_student_employed 2.92 889. 0.00 0.00
coef_unavailable-999. 0.00 NA 0.00fixed value
coef_under_35_school1 0.722 0.00 NA 0.00
coef_under_35_school2 1.23 0.389 3.16** 0.00
coef_under_35_work1-0.459 0.574-0.80 0.00
coef_under_35_work2 0.00561 0.0823 0.07 0.00
coef_under_35_work_and_school 1.15 0.646 1.78 0.00
coef_univ_school2_asc-3.64 0.415-8.77*** 0.00
coef_univ_work1_asc 2.21 889. 0.00 0.00
coef_univ_work2_asc-1.47 889.-0.00 0.00
coef_univ_work_and_school_asc 0.173 889. 0.00 0.00
\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 8, @@ -3231,18 +3201,7 @@ "cell_type": "code", "execution_count": 10, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -3300,85 +3259,85 @@ " \n", " 1\n", " coef_ft_worker_work2_asc\n", - " -5.517933\n", + " -3.494595\n", " F\n", " \n", " \n", " 2\n", " coef_pt_worker_work2_asc\n", - " -4.743242\n", + " -3.079547\n", " F\n", " \n", " \n", " 3\n", " coef_univ_work1_asc\n", - " 6.475896\n", + " 2.209708\n", " F\n", " \n", " \n", " 4\n", " coef_univ_work2_asc\n", - " 4.833029\n", + " -1.472430\n", " F\n", " \n", " \n", " 5\n", " coef_univ_school2_asc\n", - " -10.233810\n", + " -3.640737\n", " F\n", " \n", " \n", " 6\n", " coef_univ_work_and_school_asc\n", - " 8.180927\n", + " 0.173386\n", " F\n", " \n", " \n", " 7\n", " coef_driving_age_child_school2_asc\n", - " -13.067731\n", + " -3.209418\n", " F\n", " \n", " \n", " 8\n", " coef_driving_age_child_work_and_school_asc\n", - " -12.605997\n", + " -4.565091\n", " F\n", " \n", " \n", " 9\n", " coef_pre_driving_age_child_school2_asc\n", - " 3.679726\n", + " -4.210709\n", " F\n", " \n", " \n", " 10\n", " coef_female_work1\n", - " -2.242748\n", + " 0.333342\n", " F\n", " \n", " \n", " 11\n", " coef_female_work2\n", - " -0.387411\n", + " -0.219862\n", " F\n", " \n", " \n", " 12\n", " coef_female_school1\n", - " 0.247086\n", + " 0.000463\n", " F\n", " \n", " \n", " 13\n", " coef_female_school2\n", - " -0.301339\n", + " -0.016856\n", " F\n", " \n", " \n", " 14\n", " coef_female_work_and_school\n", - " -3.218280\n", + " -0.265847\n", " F\n", " \n", " \n", @@ -3390,13 +3349,13 @@ " \n", " 16\n", " coef_under_35_work1\n", - " 1.038242\n", + " -0.458863\n", " F\n", " \n", " \n", " 17\n", " coef_under_35_work2\n", - " -0.253875\n", + " 0.005614\n", " F\n", " \n", " \n", @@ -3408,55 +3367,55 @@ " \n", " 19\n", " coef_under_35_school2\n", - " 15.011164\n", + " 1.230550\n", " F\n", " \n", " \n", " 20\n", " coef_under_35_work_and_school\n", - " 2.257035\n", + " 1.149726\n", " F\n", " \n", " \n", " 21\n", " coef_can_walk_to_work_work2\n", - " 0.651120\n", + " 0.600928\n", " F\n", " \n", " \n", " 22\n", " coef_can_walk_to_work_school2\n", - " 1.368092\n", + " 0.811379\n", " F\n", " \n", " \n", " 23\n", " coef_can_walk_to_work_and_school\n", - " 0.071630\n", + " 0.284832\n", " F\n", " \n", " \n", " 24\n", " coef_round_trip_auto_time_to_work_work2\n", - " -0.025905\n", + " -0.001855\n", " F\n", " \n", " \n", " 25\n", " coef_round_trip_auto_time_to_work_school2\n", - " 0.064411\n", + " -0.005959\n", " F\n", " \n", " \n", " 26\n", " coef_round_trip_auto_time_to_work_work_and_school\n", - " -0.021804\n", + " -0.002208\n", " F\n", " \n", " \n", " 27\n", " coef_student_employed\n", - " 13.457255\n", + " 2.918973\n", " F\n", " \n", " \n", @@ -3468,37 +3427,37 @@ " \n", " 29\n", " coef_no_cars_in_hh_work2\n", - " -0.725967\n", + " -1.524960\n", " F\n", " \n", " \n", " 30\n", " coef_no_cars_in_hh_school2\n", - " -0.620465\n", + " -1.479517\n", " F\n", " \n", " \n", " 31\n", " coef_no_cars_in_hh_work_and_school\n", - " -0.775934\n", + " -1.244512\n", " F\n", " \n", " \n", " 32\n", " coef_few_cars_than_drivers_school2\n", - " -0.862451\n", + " -0.297623\n", " F\n", " \n", " \n", " 33\n", " coef_num_preschool_in_hh_work1\n", - " -2.930501\n", + " 0.125045\n", " F\n", " \n", " \n", " 34\n", " coef_num_preschool_in_hh_work2\n", - " 0.225173\n", + " -0.126183\n", " F\n", " \n", " \n", @@ -3510,13 +3469,13 @@ " \n", " 36\n", " coef_num_preschool_in_hh_school2\n", - " 0.356660\n", + " -0.796350\n", " F\n", " \n", " \n", " 37\n", " coef_num_preschool_in_hh_work_and_school\n", - " -29.197569\n", + " -0.070125\n", " F\n", " \n", " \n", @@ -3528,7 +3487,7 @@ " \n", " 39\n", " coef_hh_income_gt_50k_work\n", - " -1.418551\n", + " -0.286159\n", " F\n", " \n", " \n", @@ -3546,7 +3505,7 @@ " \n", " 42\n", " coef_hh_income_gt_50k_student_work_and_school\n", - " -0.921175\n", + " -0.128428\n", " F\n", " \n", " \n", @@ -3558,37 +3517,37 @@ " \n", " 44\n", " coef_non_family_hh_category2\n", - " 5.000771\n", + " -0.091298\n", " F\n", " \n", " \n", " 45\n", " coef_num_under_16_not_at_school_work2\n", - " -0.118991\n", + " 0.168260\n", " NaN\n", " \n", " \n", " 46\n", " coef_num_under_16_not_at_school_school2\n", - " -0.638293\n", + " -0.015345\n", " NaN\n", " \n", " \n", " 47\n", " coef_num_under_16_not_at_school_work_and_school\n", - " -15.357907\n", + " -0.192330\n", " NaN\n", " \n", " \n", " 48\n", " coef_home_urban_work1\n", - " 4.026796\n", + " -0.122770\n", " NaN\n", " \n", " \n", " 49\n", " coef_home_urban_work2\n", - " 2.624854\n", + " 0.142218\n", " NaN\n", " \n", " \n", @@ -3600,13 +3559,13 @@ " \n", " 51\n", " coef_home_urban_school2\n", - " -8.455615\n", + " 0.161745\n", " NaN\n", " \n", " \n", " 52\n", " coef_home_urban_work_and_school\n", - " -0.447070\n", + " -0.436835\n", " NaN\n", " \n", " \n", @@ -3616,58 +3575,58 @@ "text/plain": [ " coefficient_name value constrain\n", "0 coef_unavailable -999.000000 T\n", - "1 coef_ft_worker_work2_asc -5.517933 F\n", - "2 coef_pt_worker_work2_asc -4.743242 F\n", - "3 coef_univ_work1_asc 6.475896 F\n", - "4 coef_univ_work2_asc 4.833029 F\n", - "5 coef_univ_school2_asc -10.233810 F\n", - "6 coef_univ_work_and_school_asc 8.180927 F\n", - "7 coef_driving_age_child_school2_asc -13.067731 F\n", - "8 coef_driving_age_child_work_and_school_asc -12.605997 F\n", - "9 coef_pre_driving_age_child_school2_asc 3.679726 F\n", - "10 coef_female_work1 -2.242748 F\n", - "11 coef_female_work2 -0.387411 F\n", - "12 coef_female_school1 0.247086 F\n", - "13 coef_female_school2 -0.301339 F\n", - "14 coef_female_work_and_school -3.218280 F\n", + "1 coef_ft_worker_work2_asc -3.494595 F\n", + "2 coef_pt_worker_work2_asc -3.079547 F\n", + "3 coef_univ_work1_asc 2.209708 F\n", + "4 coef_univ_work2_asc -1.472430 F\n", + "5 coef_univ_school2_asc -3.640737 F\n", + "6 coef_univ_work_and_school_asc 0.173386 F\n", + "7 coef_driving_age_child_school2_asc -3.209418 F\n", + "8 coef_driving_age_child_work_and_school_asc -4.565091 F\n", + "9 coef_pre_driving_age_child_school2_asc -4.210709 F\n", + "10 coef_female_work1 0.333342 F\n", + "11 coef_female_work2 -0.219862 F\n", + "12 coef_female_school1 0.000463 F\n", + "13 coef_female_school2 -0.016856 F\n", + "14 coef_female_work_and_school -0.265847 F\n", "15 coef_female_univ_work1 0.173700 F\n", - "16 coef_under_35_work1 1.038242 F\n", - "17 coef_under_35_work2 -0.253875 F\n", + "16 coef_under_35_work1 -0.458863 F\n", + "17 coef_under_35_work2 0.005614 F\n", "18 coef_under_35_school1 0.721800 F\n", - "19 coef_under_35_school2 15.011164 F\n", - "20 coef_under_35_work_and_school 2.257035 F\n", - "21 coef_can_walk_to_work_work2 0.651120 F\n", - "22 coef_can_walk_to_work_school2 1.368092 F\n", - "23 coef_can_walk_to_work_and_school 0.071630 F\n", - "24 coef_round_trip_auto_time_to_work_work2 -0.025905 F\n", - "25 coef_round_trip_auto_time_to_work_school2 0.064411 F\n", - "26 coef_round_trip_auto_time_to_work_work_and_school -0.021804 F\n", - "27 coef_student_employed 13.457255 F\n", + "19 coef_under_35_school2 1.230550 F\n", + "20 coef_under_35_work_and_school 1.149726 F\n", + "21 coef_can_walk_to_work_work2 0.600928 F\n", + "22 coef_can_walk_to_work_school2 0.811379 F\n", + "23 coef_can_walk_to_work_and_school 0.284832 F\n", + "24 coef_round_trip_auto_time_to_work_work2 -0.001855 F\n", + "25 coef_round_trip_auto_time_to_work_school2 -0.005959 F\n", + "26 coef_round_trip_auto_time_to_work_work_and_school -0.002208 F\n", + "27 coef_student_employed 2.918973 F\n", "28 coef_non_student_goes_to_school 3.883000 F\n", - "29 coef_no_cars_in_hh_work2 -0.725967 F\n", - "30 coef_no_cars_in_hh_school2 -0.620465 F\n", - "31 coef_no_cars_in_hh_work_and_school -0.775934 F\n", - "32 coef_few_cars_than_drivers_school2 -0.862451 F\n", - "33 coef_num_preschool_in_hh_work1 -2.930501 F\n", - "34 coef_num_preschool_in_hh_work2 0.225173 F\n", + "29 coef_no_cars_in_hh_work2 -1.524960 F\n", + "30 coef_no_cars_in_hh_school2 -1.479517 F\n", + "31 coef_no_cars_in_hh_work_and_school -1.244512 F\n", + "32 coef_few_cars_than_drivers_school2 -0.297623 F\n", + "33 coef_num_preschool_in_hh_work1 0.125045 F\n", + "34 coef_num_preschool_in_hh_work2 -0.126183 F\n", "35 coef_num_preschool_in_hh_school1 -0.133500 F\n", - "36 coef_num_preschool_in_hh_school2 0.356660 F\n", - "37 coef_num_preschool_in_hh_work_and_school -29.197569 F\n", + "36 coef_num_preschool_in_hh_school2 -0.796350 F\n", + "37 coef_num_preschool_in_hh_work_and_school -0.070125 F\n", "38 coef_num_non_workers_in_hh_school1 0.257400 F\n", - "39 coef_hh_income_gt_50k_work -1.418551 F\n", + "39 coef_hh_income_gt_50k_work -0.286159 F\n", "40 coef_hh_income_gt_50k_school1 0.034700 F\n", "41 coef_hh_income_gt_50k_worker_work_and_school 0.034700 F\n", - "42 coef_hh_income_gt_50k_student_work_and_school -0.921175 F\n", + "42 coef_hh_income_gt_50k_student_work_and_school -0.128428 F\n", "43 coef_non_family_hh_category1 -0.250000 F\n", - "44 coef_non_family_hh_category2 5.000771 F\n", - "45 coef_num_under_16_not_at_school_work2 -0.118991 NaN\n", - "46 coef_num_under_16_not_at_school_school2 -0.638293 NaN\n", - "47 coef_num_under_16_not_at_school_work_and_school -15.357907 NaN\n", - "48 coef_home_urban_work1 4.026796 NaN\n", - "49 coef_home_urban_work2 2.624854 NaN\n", + "44 coef_non_family_hh_category2 -0.091298 F\n", + "45 coef_num_under_16_not_at_school_work2 0.168260 NaN\n", + "46 coef_num_under_16_not_at_school_school2 -0.015345 NaN\n", + "47 coef_num_under_16_not_at_school_work_and_school -0.192330 NaN\n", + "48 coef_home_urban_work1 -0.122770 NaN\n", + "49 coef_home_urban_work2 0.142218 NaN\n", "50 coef_home_urban_school1 -0.136100 NaN\n", - "51 coef_home_urban_school2 -8.455615 NaN\n", - "52 coef_home_urban_work_and_school -0.447070 NaN" + "51 coef_home_urban_school2 0.161745 NaN\n", + "52 coef_home_urban_work_and_school -0.436835 NaN" ] }, "execution_count": 11, @@ -3687,7 +3646,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -3701,7 +3660,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/08_work_tour_scheduling.ipynb b/activitysim/examples/example_estimation/notebooks/08_work_tour_scheduling.ipynb index 3cd81e8a23..b592a29746 100644 --- a/activitysim/examples/example_estimation/notebooks/08_work_tour_scheduling.ipynb +++ b/activitysim/examples/example_estimation/notebooks/08_work_tour_scheduling.ipynb @@ -34,27 +34,75 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +116,28 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_scheduling_work/tour_scheduling_work_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_scheduling_work/mandatory_tour_scheduling_work_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_scheduling_work/mandatory_tour_scheduling_work_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_scheduling_work/mandatory_tour_scheduling_work_choosers_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"mandatory_tour_scheduling_work\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -461,10 +525,10 @@ " \n", " \n", " 0\n", - " 2961920\n", - " 32\n", - " 35\n", - " 72241\n", + " 2966594\n", + " 7\n", + " 96\n", + " 72355\n", " work\n", " 1\n", " 1\n", @@ -477,18 +541,18 @@ " True\n", " False\n", " False\n", - " 9\n", - " -1\n", " 17\n", + " -1\n", + " 55\n", " 5\n", " 5\n", " \n", " \n", " 1\n", - " 2970120\n", - " 51\n", - " 51\n", - " 72441\n", + " 2967783\n", + " 50\n", + " 30\n", + " 72384\n", " work\n", " 1\n", " 1\n", @@ -501,18 +565,18 @@ " True\n", " False\n", " False\n", - " 100\n", + " 16\n", " -1\n", - " 60\n", + " 59\n", " 5\n", " 5\n", " \n", " \n", " 2\n", - " 2998943\n", + " 2968726\n", + " 64\n", " 29\n", - " 28\n", - " 73144\n", + " 72407\n", " work\n", " 1\n", " 1\n", @@ -525,18 +589,18 @@ " True\n", " False\n", " False\n", - " 77\n", + " 70\n", " -1\n", - " 125\n", + " 59\n", " 5\n", " 5\n", " \n", " \n", " 3\n", - " 3013252\n", - " 47\n", - " 47\n", - " 73493\n", + " 2970858\n", + " 31\n", + " 80\n", + " 72459\n", " work\n", " 1\n", " 1\n", @@ -549,18 +613,18 @@ " True\n", " False\n", " False\n", - " 117\n", + " 30\n", " -1\n", - " 133\n", + " 61\n", " 5\n", " 5\n", " \n", " \n", " 4\n", - " 3015794\n", - " 59\n", - " 59\n", - " 73555\n", + " 2973728\n", + " 61\n", + " 115\n", + " 72529\n", " work\n", " 1\n", " 1\n", @@ -573,9 +637,9 @@ " True\n", " False\n", " False\n", - " 167\n", + " 57\n", " -1\n", - " 136\n", + " 69\n", " 5\n", " 5\n", " \n", @@ -604,35 +668,35 @@ " ...\n", " \n", " \n", - " 2119\n", - " 308070309\n", - " 184\n", - " 184\n", - " 7513909\n", + " 22632\n", + " 309081532\n", + " 32\n", + " 10\n", + " 7538573\n", " work\n", - " 2\n", - " 2\n", - " 2\n", - " 2\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " mandatory\n", " ...\n", " False\n", - " work2\n", + " work1\n", " True\n", " False\n", " False\n", - " 11\n", + " 135\n", " -1\n", - " 21\n", - " 17\n", - " 21\n", + " 200\n", + " 5\n", + " 5\n", " \n", " \n", - " 2120\n", - " 308073875\n", - " 41\n", - " 38\n", - " 7513996\n", + " 22633\n", + " 309090634\n", + " 48\n", + " 79\n", + " 7538795\n", " work\n", " 1\n", " 1\n", @@ -645,18 +709,18 @@ " True\n", " False\n", " False\n", - " 67\n", + " 1018\n", " -1\n", - " 21\n", + " 1006\n", " 5\n", " 5\n", " \n", " \n", - " 2121\n", - " 308090603\n", - " 27\n", - " 27\n", - " 7514404\n", + " 22634\n", + " 309101950\n", + " 69\n", + " 78\n", + " 7539071\n", " work\n", " 1\n", " 1\n", @@ -669,18 +733,18 @@ " True\n", " False\n", " False\n", - " 106\n", + " 1019\n", " -1\n", - " 81\n", + " 1006\n", " 5\n", " 5\n", " \n", " \n", - " 2122\n", - " 308105896\n", - " 6\n", - " 6\n", - " 7514777\n", + " 22635\n", + " 309107362\n", + " 139\n", + " 53\n", + " 7539203\n", " work\n", " 1\n", " 1\n", @@ -691,110 +755,110 @@ " False\n", " work1\n", " True\n", - " True\n", - " True\n", - " 87\n", - " 185\n", - " 106\n", + " False\n", + " False\n", + " 1152\n", + " -1\n", + " 1159\n", " 5\n", " 5\n", " \n", " \n", - " 2123\n", - " 308122624\n", - " 44\n", - " 44\n", - " 7515185\n", + " 22636\n", + " 309112036\n", + " 64\n", + " 36\n", + " 7539317\n", " work\n", " 1\n", " 1\n", " 1\n", - " 2\n", + " 1\n", " mandatory\n", " ...\n", " False\n", - " work_and_school\n", - " True\n", - " True\n", + " work1\n", " True\n", - " 16\n", - " 188\n", - " 142\n", + " False\n", + " False\n", + " 1381\n", + " -1\n", + " 1390\n", " 5\n", " 5\n", " \n", " \n", "\n", - "

2124 rows × 40 columns

\n", + "

22637 rows × 40 columns

\n", "" ], "text/plain": [ - " tour_id model_choice override_choice person_id tour_type \\\n", - "0 2961920 32 35 72241 work \n", - "1 2970120 51 51 72441 work \n", - "2 2998943 29 28 73144 work \n", - "3 3013252 47 47 73493 work \n", - "4 3015794 59 59 73555 work \n", - "... ... ... ... ... ... \n", - "2119 308070309 184 184 7513909 work \n", - "2120 308073875 41 38 7513996 work \n", - "2121 308090603 27 27 7514404 work \n", - "2122 308105896 6 6 7514777 work \n", - "2123 308122624 44 44 7515185 work \n", + " tour_id model_choice override_choice person_id tour_type \\\n", + "0 2966594 7 96 72355 work \n", + "1 2967783 50 30 72384 work \n", + "2 2968726 64 29 72407 work \n", + "3 2970858 31 80 72459 work \n", + "4 2973728 61 115 72529 work \n", + "... ... ... ... ... ... \n", + "22632 309081532 32 10 7538573 work \n", + "22633 309090634 48 79 7538795 work \n", + "22634 309101950 69 78 7539071 work \n", + "22635 309107362 139 53 7539203 work \n", + "22636 309112036 64 36 7539317 work \n", "\n", - " tour_type_count tour_type_num tour_num tour_count tour_category ... \\\n", - "0 1 1 1 1 mandatory ... \n", - "1 1 1 1 1 mandatory ... \n", - "2 1 1 1 1 mandatory ... \n", - "3 1 1 1 1 mandatory ... \n", - "4 1 1 1 1 mandatory ... \n", - "... ... ... ... ... ... ... \n", - "2119 2 2 2 2 mandatory ... \n", - "2120 1 1 1 1 mandatory ... \n", - "2121 1 1 1 1 mandatory ... \n", - "2122 1 1 1 1 mandatory ... \n", - "2123 1 1 1 2 mandatory ... \n", + " tour_type_count tour_type_num tour_num tour_count tour_category \\\n", + "0 1 1 1 1 mandatory \n", + "1 1 1 1 1 mandatory \n", + "2 1 1 1 1 mandatory \n", + "3 1 1 1 1 mandatory \n", + "4 1 1 1 1 mandatory \n", + "... ... ... ... ... ... \n", + "22632 1 1 1 1 mandatory \n", + "22633 1 1 1 1 mandatory \n", + "22634 1 1 1 1 mandatory \n", + "22635 1 1 1 1 mandatory \n", + "22636 1 1 1 1 mandatory \n", "\n", - " home_is_rural mandatory_tour_frequency is_worker is_student \\\n", - "0 False work1 True False \n", - "1 False work1 True False \n", - "2 False work1 True False \n", - "3 False work1 True False \n", - "4 False work1 True False \n", - "... ... ... ... ... \n", - "2119 False work2 True False \n", - "2120 False work1 True False \n", - "2121 False work1 True False \n", - "2122 False work1 True True \n", - "2123 False work_and_school True True \n", + " ... home_is_rural mandatory_tour_frequency is_worker is_student \\\n", + "0 ... False work1 True False \n", + "1 ... False work1 True False \n", + "2 ... False work1 True False \n", + "3 ... False work1 True False \n", + "4 ... False work1 True False \n", + "... ... ... ... ... ... \n", + "22632 ... False work1 True False \n", + "22633 ... False work1 True False \n", + "22634 ... False work1 True False \n", + "22635 ... False work1 True False \n", + "22636 ... False work1 True False \n", "\n", - " is_university workplace_zone_id school_zone_id home_zone_id \\\n", - "0 False 9 -1 17 \n", - "1 False 100 -1 60 \n", - "2 False 77 -1 125 \n", - "3 False 117 -1 133 \n", - "4 False 167 -1 136 \n", - "... ... ... ... ... \n", - "2119 False 11 -1 21 \n", - "2120 False 67 -1 21 \n", - "2121 False 106 -1 81 \n", - "2122 True 87 185 106 \n", - "2123 True 16 188 142 \n", + " is_university workplace_zone_id school_zone_id home_zone_id \\\n", + "0 False 17 -1 55 \n", + "1 False 16 -1 59 \n", + "2 False 70 -1 59 \n", + "3 False 30 -1 61 \n", + "4 False 57 -1 69 \n", + "... ... ... ... ... \n", + "22632 False 135 -1 200 \n", + "22633 False 1018 -1 1006 \n", + "22634 False 1019 -1 1006 \n", + "22635 False 1152 -1 1159 \n", + "22636 False 1381 -1 1390 \n", "\n", - " start_previous end_previous \n", - "0 5 5 \n", - "1 5 5 \n", - "2 5 5 \n", - "3 5 5 \n", - "4 5 5 \n", - "... ... ... \n", - "2119 17 21 \n", - "2120 5 5 \n", - "2121 5 5 \n", - "2122 5 5 \n", - "2123 5 5 \n", + " start_previous end_previous \n", + "0 5 5 \n", + "1 5 5 \n", + "2 5 5 \n", + "3 5 5 \n", + "4 5 5 \n", + "... ... ... \n", + "22632 5 5 \n", + "22633 5 5 \n", + "22634 5 5 \n", + "22635 5 5 \n", + "22636 5 5 \n", "\n", - "[2124 rows x 40 columns]" + "[22637 rows x 40 columns]" ] }, "execution_count": 6, @@ -840,148 +904,148 @@ " \n", " \n", " tour_id\n", - " variable\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", + " start\n", + " end\n", + " duration\n", + " tdd\n", + " out_period\n", + " in_period\n", + " mode_choice_logsum\n", + " util_free_flow_round_trip_auto_time_shift_effects_departure\n", + " util_free_flow_round_trip_auto_time_shift_effects_duration\n", " ...\n", - " 180\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", + " util_arrival_constants_late\n", + " util_duration_constants_0_to_2_hours\n", + " util_duration_constants_3_to_4_hours\n", + " util_duration_constants_5_to_6_hours\n", + " util_duration_constants_7_to_8_hours\n", + " util_duration_constants_9_hours\n", + " util_duration_constants_10_hours\n", + " util_duration_constants_11_hours\n", + " util_duration_constants_12_to_13_hours\n", + " util_duration_constants_14_to_18_hours\n", " \n", " \n", " \n", " \n", " 0\n", - " 2961920\n", - " duration\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", + " 2966594\n", + " 5\n", " 5\n", - " 6\n", - " 7\n", - " ...\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", " 0\n", - " 1\n", - " 2\n", - " 0\n", - " 1\n", " 0\n", + " EA\n", + " EA\n", + " -0.897101\n", + " 163.399994\n", + " 0.000000\n", + " ...\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 1\n", - " 2961920\n", - " end\n", + " 2966594\n", " 5\n", " 6\n", - " 7\n", - " 8\n", - " 9\n", - " 10\n", - " 11\n", - " 12\n", + " 1\n", + " 1\n", + " EA\n", + " AM\n", + " -1.333629\n", + " 163.399994\n", + " 32.680000\n", " ...\n", - " 20\n", - " 21\n", - " 22\n", - " 23\n", - " 21\n", - " 22\n", - " 23\n", - " 22\n", - " 23\n", - " 23\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 2\n", - " 2961920\n", - " in_period\n", + " 2966594\n", + " 5\n", + " 7\n", + " 2\n", + " 2\n", " EA\n", " AM\n", - " AM\n", - " AM\n", - " AM\n", - " MD\n", - " MD\n", - " MD\n", + " -1.333629\n", + " 163.399994\n", + " 65.360001\n", " ...\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 3\n", - " 2961920\n", - " mode_choice_logsum\n", - " -0.6808670711507444\n", - " -0.9609052826735235\n", - " -0.9609052826735235\n", - " -0.9609052826735235\n", - " -0.9609052826735235\n", - " -1.1106688167107288\n", - " -1.1106688167107288\n", - " -1.1106688167107288\n", - " ...\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", - " -0.8117834942924501\n", + " 2966594\n", + " 5\n", + " 8\n", + " 3\n", + " 3\n", + " EA\n", + " AM\n", + " -1.333629\n", + " 163.399994\n", + " 98.040001\n", + " ...\n", + " False\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 4\n", - " 2961920\n", - " out_period\n", - " EA\n", - " EA\n", - " EA\n", - " EA\n", - " EA\n", - " EA\n", - " EA\n", + " 2966594\n", + " 5\n", + " 9\n", + " 4\n", + " 4\n", " EA\n", + " AM\n", + " -1.333629\n", + " 163.399994\n", + " 130.720001\n", " ...\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", + " False\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " ...\n", @@ -1008,9 +1072,20 @@ " ...\n", " \n", " \n", - " 146551\n", - " 308122624\n", - " util_subsequent_tour_must_start_after_previous...\n", + " 4222354\n", + " 309112036\n", + " 21\n", + " 22\n", + " 1\n", + " 185\n", + " EV\n", + " EV\n", + " -2.780379\n", + " 1388.099976\n", + " 66.099998\n", + " ...\n", + " True\n", + " True\n", " False\n", " False\n", " False\n", @@ -1019,9 +1094,22 @@ " False\n", " False\n", " False\n", + " \n", + " \n", + " 4222355\n", + " 309112036\n", + " 21\n", + " 23\n", + " 2\n", + " 186\n", + " EV\n", + " EV\n", + " -2.780379\n", + " 1388.099976\n", + " 132.199997\n", " ...\n", - " False\n", - " False\n", + " True\n", + " True\n", " False\n", " False\n", " False\n", @@ -1032,81 +1120,44 @@ " False\n", " \n", " \n", - " 146552\n", - " 308122624\n", - " util_tours_by_student_duration_lt_8_hrs\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", + " 4222356\n", + " 309112036\n", + " 22\n", + " 22\n", + " 0\n", + " 187\n", + " EV\n", + " EV\n", + " -2.780379\n", + " 1454.199951\n", + " 0.000000\n", " ...\n", " True\n", " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", - " 146553\n", - " 308122624\n", - " util_tours_by_worker_duration_lt_8_hrs\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", + " 4222357\n", + " 309112036\n", + " 22\n", + " 23\n", + " 1\n", + " 188\n", + " EV\n", + " EV\n", + " -2.780379\n", + " 1454.199951\n", + " 66.099998\n", " ...\n", " True\n", " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " \n", - " \n", - " 146554\n", - " 308122624\n", - " util_university_student_departure_shift_effects\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " ...\n", - " 20\n", - " 20\n", - " 20\n", - " 20\n", - " 21\n", - " 21\n", - " 21\n", - " 22\n", - " 22\n", - " 23\n", - " \n", - " \n", - " 146555\n", - " 308122624\n", - " util_worker_13_to_15_arrival_interaction\n", " False\n", " False\n", " False\n", @@ -1115,9 +1166,22 @@ " False\n", " False\n", " False\n", + " \n", + " \n", + " 4222358\n", + " 309112036\n", + " 23\n", + " 23\n", + " 0\n", + " 189\n", + " EV\n", + " EV\n", + " -2.780379\n", + " 1520.299927\n", + " 0.000000\n", " ...\n", - " False\n", - " False\n", + " True\n", + " True\n", " False\n", " False\n", " False\n", @@ -1129,102 +1193,167 @@ " \n", " \n", "\n", - "

146556 rows × 192 columns

\n", + "

4222359 rows × 71 columns

\n", "" ], "text/plain": [ - " tour_id variable \\\n", - "0 2961920 duration \n", - "1 2961920 end \n", - "2 2961920 in_period \n", - "3 2961920 mode_choice_logsum \n", - "4 2961920 out_period \n", - "... ... ... \n", - "146551 308122624 util_subsequent_tour_must_start_after_previous... \n", - "146552 308122624 util_tours_by_student_duration_lt_8_hrs \n", - "146553 308122624 util_tours_by_worker_duration_lt_8_hrs \n", - "146554 308122624 util_university_student_departure_shift_effects \n", - "146555 308122624 util_worker_13_to_15_arrival_interaction \n", + " tour_id start end duration tdd out_period in_period \\\n", + "0 2966594 5 5 0 0 EA EA \n", + "1 2966594 5 6 1 1 EA AM \n", + "2 2966594 5 7 2 2 EA AM \n", + "3 2966594 5 8 3 3 EA AM \n", + "4 2966594 5 9 4 4 EA AM \n", + "... ... ... ... ... ... ... ... \n", + "4222354 309112036 21 22 1 185 EV EV \n", + "4222355 309112036 21 23 2 186 EV EV \n", + "4222356 309112036 22 22 0 187 EV EV \n", + "4222357 309112036 22 23 1 188 EV EV \n", + "4222358 309112036 23 23 0 189 EV EV \n", "\n", - " 0 1 2 \\\n", - "0 0 1 2 \n", - "1 5 6 7 \n", - "2 EA AM AM \n", - "3 -0.6808670711507444 -0.9609052826735235 -0.9609052826735235 \n", - "4 EA EA EA \n", - "... ... ... ... \n", - "146551 False False False \n", - "146552 True True True \n", - "146553 True True True \n", - "146554 5 5 5 \n", - "146555 False False False \n", + " mode_choice_logsum \\\n", + "0 -0.897101 \n", + "1 -1.333629 \n", + "2 -1.333629 \n", + "3 -1.333629 \n", + "4 -1.333629 \n", + "... ... \n", + "4222354 -2.780379 \n", + "4222355 -2.780379 \n", + "4222356 -2.780379 \n", + "4222357 -2.780379 \n", + "4222358 -2.780379 \n", "\n", - " 3 4 5 \\\n", - "0 3 4 5 \n", - "1 8 9 10 \n", - "2 AM AM MD \n", - "3 -0.9609052826735235 -0.9609052826735235 -1.1106688167107288 \n", - "4 EA EA EA \n", - "... ... ... ... \n", - "146551 False False False \n", - "146552 True True True \n", - "146553 True True True \n", - "146554 5 5 5 \n", - "146555 False False False \n", + " util_free_flow_round_trip_auto_time_shift_effects_departure \\\n", + "0 163.399994 \n", + "1 163.399994 \n", + "2 163.399994 \n", + "3 163.399994 \n", + "4 163.399994 \n", + "... ... \n", + "4222354 1388.099976 \n", + "4222355 1388.099976 \n", + "4222356 1454.199951 \n", + "4222357 1454.199951 \n", + "4222358 1520.299927 \n", "\n", - " 6 7 ... 180 \\\n", - "0 6 7 ... 0 \n", - "1 11 12 ... 20 \n", - "2 MD MD ... EV \n", - "3 -1.1106688167107288 -1.1106688167107288 ... -0.8117834942924501 \n", - "4 EA EA ... EV \n", - "... ... ... ... ... \n", - "146551 False False ... False \n", - "146552 True True ... True \n", - "146553 True True ... True \n", - "146554 5 5 ... 20 \n", - "146555 False False ... False \n", + " util_free_flow_round_trip_auto_time_shift_effects_duration ... \\\n", + "0 0.000000 ... \n", + "1 32.680000 ... \n", + "2 65.360001 ... \n", + "3 98.040001 ... \n", + "4 130.720001 ... \n", + "... ... ... \n", + "4222354 66.099998 ... \n", + "4222355 132.199997 ... \n", + "4222356 0.000000 ... \n", + "4222357 66.099998 ... \n", + "4222358 0.000000 ... \n", "\n", - " 181 182 183 \\\n", - "0 1 2 3 \n", - "1 21 22 23 \n", - "2 EV EV EV \n", - "3 -0.8117834942924501 -0.8117834942924501 -0.8117834942924501 \n", - "4 EV EV EV \n", - "... ... ... ... \n", - "146551 False False False \n", - "146552 True True True \n", - "146553 True True True \n", - "146554 20 20 20 \n", - "146555 False False False \n", + " util_arrival_constants_late util_duration_constants_0_to_2_hours \\\n", + "0 False True \n", + "1 False True \n", + "2 False True \n", + "3 False False \n", + "4 False False \n", + "... ... ... \n", + "4222354 True True \n", + "4222355 True True \n", + "4222356 True True \n", + "4222357 True True \n", + "4222358 True True \n", "\n", - " 184 185 186 \\\n", - "0 0 1 2 \n", - "1 21 22 23 \n", - "2 EV EV EV \n", - "3 -0.8117834942924501 -0.8117834942924501 -0.8117834942924501 \n", - "4 EV EV EV \n", - "... ... ... ... \n", - "146551 False False False \n", - "146552 True True True \n", - "146553 True True True \n", - "146554 21 21 21 \n", - "146555 False False False \n", + " util_duration_constants_3_to_4_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 True \n", + "4 True \n", + "... ... \n", + "4222354 False \n", + "4222355 False \n", + "4222356 False \n", + "4222357 False \n", + "4222358 False \n", "\n", - " 187 188 189 \n", - "0 0 1 0 \n", - "1 22 23 23 \n", - "2 EV EV EV \n", - "3 -0.8117834942924501 -0.8117834942924501 -0.8117834942924501 \n", - "4 EV EV EV \n", - "... ... ... ... \n", - "146551 False False False \n", - "146552 True True True \n", - "146553 True True True \n", - "146554 22 22 23 \n", - "146555 False False False \n", + " util_duration_constants_5_to_6_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "4222354 False \n", + "4222355 False \n", + "4222356 False \n", + "4222357 False \n", + "4222358 False \n", "\n", - "[146556 rows x 192 columns]" + " util_duration_constants_7_to_8_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "4222354 False \n", + "4222355 False \n", + "4222356 False \n", + "4222357 False \n", + "4222358 False \n", + "\n", + " util_duration_constants_9_hours util_duration_constants_10_hours \\\n", + "0 False False \n", + "1 False False \n", + "2 False False \n", + "3 False False \n", + "4 False False \n", + "... ... ... \n", + "4222354 False False \n", + "4222355 False False \n", + "4222356 False False \n", + "4222357 False False \n", + "4222358 False False \n", + "\n", + " util_duration_constants_11_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "4222354 False \n", + "4222355 False \n", + "4222356 False \n", + "4222357 False \n", + "4222358 False \n", + "\n", + " util_duration_constants_12_to_13_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "4222354 False \n", + "4222355 False \n", + "4222356 False \n", + "4222357 False \n", + "4222358 False \n", + "\n", + " util_duration_constants_14_to_18_hours \n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "4222354 False \n", + "4222355 False \n", + "4222356 False \n", + "4222357 False \n", + "4222358 False \n", + "\n", + "[4222359 rows x 71 columns]" ] }, "execution_count": 7, @@ -1254,13 +1383,47 @@ "name": "stderr", "output_type": "stream", "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "problem: chosen_but_not_available has (83 issues)\n" ] }, + { + "data": { + "text/plain": [ + "(,\n", + " ┣ chosen_but_not_available: altid n example rows\n", + " ┃ 0 23 1 7136\n", + " ┃ 1 40 1 7611\n", + " ┃ 2 41 2 2673, 3979\n", + " ┃ 3 42 1 15549\n", + " ┃ 4 44 2 10390, 17539\n", + " ┃ .. ... .. ...\n", + " ┃ 78 175 1 15501\n", + " ┃ 79 177 1 16777\n", + " ┃ 80 178 1 1665\n", + " ┃ 81 180 1 6817\n", + " ┃ 82 184 1 10510\n", + " ┃ \n", + " ┃ [83 rows x 3 columns])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.doctor(repair_ch_av=\"-\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ { "data": { "text/html": [ - "

Iteration 064 [Optimization terminated successfully]

" + "

Iteration 055 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1272,7 +1435,7 @@ { "data": { "text/html": [ - "

Best LL = -8399.82196783851

" + "

Best LL = -89082.99255547294

" ], "text/plain": [ "" @@ -1303,70 +1466,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction\n", - " 0.326676\n", + " 0.346120\n", + " 0.346120\n", " 0.362700\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.326676\n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction\n", - " 0.298901\n", + " -0.097167\n", + " -0.097167\n", " -0.101200\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.298901\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction\n", - " -0.038388\n", + " 0.103758\n", + " 0.103758\n", " 0.177100\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.038388\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction\n", - " -0.012605\n", + " -0.534895\n", + " -0.534895\n", " -0.212300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.012605\n", " \n", " \n", " coef_arrival_constants_am_peak\n", - " -2.527138\n", + " -1.859817\n", + " -1.859817\n", " -1.854521\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.527138\n", " \n", " \n", " ...\n", @@ -1377,122 +1544,120 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", " coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs\n", - " 5.443390\n", + " 2.609918\n", + " 2.609918\n", " 2.582000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 5.443390\n", " \n", " \n", " coef_subsequent_tour_must_start_after_previous_tour_ends\n", " -100.000000\n", " -100.000000\n", + " -100.000000\n", + " -100.0\n", + " -100.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " -100.000000\n", " \n", " \n", " coef_tours_by_student_duration_lt_8_hrs\n", - " 20.927636\n", + " 2.619822\n", + " 2.619822\n", " 2.582000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 20.927636\n", " \n", " \n", " coef_tours_by_worker_duration_lt_8_hrs\n", - " 19.258236\n", + " 0.950422\n", + " 0.950422\n", " 0.912600\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 19.258236\n", " \n", " \n", " coef_university_student_departure_shift_effects\n", - " 0.076480\n", + " 0.045387\n", + " 0.045387\n", " 0.057470\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.076480\n", " \n", " \n", "\n", - "

63 rows × 8 columns

\n", + "

63 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_adjacent_window_exists_after_this_arrival_... 0.326676 0.362700 \n", - "coef_adjacent_window_exists_after_this_arrival_... 0.298901 -0.101200 \n", - "coef_adjacent_window_exists_before_this_departu... -0.038388 0.177100 \n", - "coef_adjacent_window_exists_before_this_departu... -0.012605 -0.212300 \n", - "coef_arrival_constants_am_peak -2.527138 -1.854521 \n", + " value best \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 0.346120 0.346120 \n", + "coef_adjacent_window_exists_after_this_arrival_... -0.097167 -0.097167 \n", + "coef_adjacent_window_exists_before_this_departu... 0.103758 0.103758 \n", + "coef_adjacent_window_exists_before_this_departu... -0.534895 -0.534895 \n", + "coef_arrival_constants_am_peak -1.859817 -1.859817 \n", "... ... ... \n", - "coef_subsequent_of_2plus_work_tours_duration_lt... 5.443390 2.582000 \n", + "coef_subsequent_of_2plus_work_tours_duration_lt... 2.609918 2.609918 \n", "coef_subsequent_tour_must_start_after_previous_... -100.000000 -100.000000 \n", - "coef_tours_by_student_duration_lt_8_hrs 20.927636 2.582000 \n", - "coef_tours_by_worker_duration_lt_8_hrs 19.258236 0.912600 \n", - "coef_university_student_departure_shift_effects 0.076480 0.057470 \n", + "coef_tours_by_student_duration_lt_8_hrs 2.619822 2.619822 \n", + "coef_tours_by_worker_duration_lt_8_hrs 0.950422 0.950422 \n", + "coef_university_student_departure_shift_effects 0.045387 0.045387 \n", "\n", - " nullvalue minimum \\\n", - "coef_adjacent_window_exists_after_this_arrival_... 0.0 -25.0 \n", - "coef_adjacent_window_exists_after_this_arrival_... 0.0 -25.0 \n", - "coef_adjacent_window_exists_before_this_departu... 0.0 -25.0 \n", - "coef_adjacent_window_exists_before_this_departu... 0.0 -25.0 \n", - "coef_arrival_constants_am_peak 0.0 -25.0 \n", - "... ... ... \n", - "coef_subsequent_of_2plus_work_tours_duration_lt... 0.0 -25.0 \n", - "coef_subsequent_tour_must_start_after_previous_... 0.0 -25.0 \n", - "coef_tours_by_student_duration_lt_8_hrs 0.0 -25.0 \n", - "coef_tours_by_worker_duration_lt_8_hrs 0.0 -25.0 \n", - "coef_university_student_departure_shift_effects 0.0 -25.0 \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 0.362700 -25.0 \n", + "coef_adjacent_window_exists_after_this_arrival_... -0.101200 -25.0 \n", + "coef_adjacent_window_exists_before_this_departu... 0.177100 -25.0 \n", + "coef_adjacent_window_exists_before_this_departu... -0.212300 -25.0 \n", + "coef_arrival_constants_am_peak -1.854521 -25.0 \n", + "... ... ... \n", + "coef_subsequent_of_2plus_work_tours_duration_lt... 2.582000 -25.0 \n", + "coef_subsequent_tour_must_start_after_previous_... -100.000000 -100.0 \n", + "coef_tours_by_student_duration_lt_8_hrs 2.582000 -25.0 \n", + "coef_tours_by_worker_duration_lt_8_hrs 0.912600 -25.0 \n", + "coef_university_student_departure_shift_effects 0.057470 -25.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_adjacent_window_exists_after_this_arrival_... 25.0 0 \n", - "coef_adjacent_window_exists_after_this_arrival_... 25.0 0 \n", - "coef_adjacent_window_exists_before_this_departu... 25.0 0 \n", - "coef_adjacent_window_exists_before_this_departu... 25.0 0 \n", - "coef_arrival_constants_am_peak 25.0 0 \n", - "... ... ... ... \n", - "coef_subsequent_of_2plus_work_tours_duration_lt... 25.0 0 \n", - "coef_subsequent_tour_must_start_after_previous_... 25.0 1 \n", - "coef_tours_by_student_duration_lt_8_hrs 25.0 0 \n", - "coef_tours_by_worker_duration_lt_8_hrs 25.0 0 \n", - "coef_university_student_departure_shift_effects 25.0 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 25.0 0.0 \n", + "coef_adjacent_window_exists_after_this_arrival_... 25.0 0.0 \n", + "coef_adjacent_window_exists_before_this_departu... 25.0 0.0 \n", + "coef_adjacent_window_exists_before_this_departu... 25.0 0.0 \n", + "coef_arrival_constants_am_peak 25.0 0.0 \n", + "... ... ... \n", + "coef_subsequent_of_2plus_work_tours_duration_lt... 25.0 0.0 \n", + "coef_subsequent_tour_must_start_after_previous_... -100.0 0.0 \n", + "coef_tours_by_student_duration_lt_8_hrs 25.0 0.0 \n", + "coef_tours_by_worker_duration_lt_8_hrs 25.0 0.0 \n", + "coef_university_student_departure_shift_effects 25.0 0.0 \n", "\n", - " best \n", - "coef_adjacent_window_exists_after_this_arrival_... 0.326676 \n", - "coef_adjacent_window_exists_after_this_arrival_... 0.298901 \n", - "coef_adjacent_window_exists_before_this_departu... -0.038388 \n", - "coef_adjacent_window_exists_before_this_departu... -0.012605 \n", - "coef_arrival_constants_am_peak -2.527138 \n", - "... ... \n", - "coef_subsequent_of_2plus_work_tours_duration_lt... 5.443390 \n", - "coef_subsequent_tour_must_start_after_previous_... -100.000000 \n", - "coef_tours_by_student_duration_lt_8_hrs 20.927636 \n", - "coef_tours_by_worker_duration_lt_8_hrs 19.258236 \n", - "coef_university_student_departure_shift_effects 0.076480 \n", + " holdfast \n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 0 \n", + "coef_adjacent_window_exists_after_this_arrival_... 0 \n", + "coef_adjacent_window_exists_before_this_departu... 0 \n", + "coef_adjacent_window_exists_before_this_departu... 0 \n", + "coef_arrival_constants_am_peak 0 \n", + "... ... \n", + "coef_subsequent_of_2plus_work_tours_duration_lt... 0 \n", + "coef_subsequent_tour_must_start_after_previous_... 1 \n", + "coef_tours_by_student_duration_lt_8_hrs 0 \n", + "coef_tours_by_worker_duration_lt_8_hrs 0 \n", + "coef_university_student_departure_shift_effects 0 \n", "\n", - "[63 rows x 8 columns]" + "[63 rows x 7 columns]" ] }, "metadata": {}, @@ -1502,10 +1667,8 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate()\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.580800976238575e-22 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { @@ -1521,23 +1684,23 @@ " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction\n", - " 0.326676\n", + " 0.346120\n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction\n", - " 0.298901\n", + " -0.097167\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction\n", - " -0.038388\n", + " 0.103758\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction\n", - " -0.012605\n", + " -0.534895\n", " \n", " \n", " coef_arrival_constants_am_peak\n", - " -2.527138\n", + " -1.859817\n", " \n", " \n", " coef_arrival_constants_early\n", @@ -1545,19 +1708,19 @@ " \n", " \n", " coef_arrival_constants_evening\n", - " -0.085796\n", + " 0.108541\n", " \n", " \n", " coef_arrival_constants_late\n", - " -1.221408\n", + " -0.888178\n", " \n", " \n", " coef_arrival_constants_midday_1\n", - " -0.489736\n", + " -0.478024\n", " \n", " \n", " coef_arrival_constants_midday_2\n", - " -0.383260\n", + " -0.405187\n", " \n", " \n", " coef_arrival_constants_pm_peak_1\n", @@ -1565,19 +1728,19 @@ " \n", " \n", " coef_arrival_constants_pm_peak_2\n", - " 0.202005\n", + " 0.320157\n", " \n", " \n", " coef_arrival_constants_pm_peak_3\n", - " 0.572524\n", + " 0.736762\n", " \n", " \n", " coef_arrival_constants_pm_peak_4\n", - " 0.705592\n", + " 0.834430\n", " \n", " \n", " coef_departure_constants_am_peak_1\n", - " -0.641898\n", + " -0.600877\n", " \n", " \n", " coef_departure_constants_am_peak_2\n", @@ -1585,55 +1748,55 @@ " \n", " \n", " coef_departure_constants_am_peak_3\n", - " -0.323006\n", + " -0.221080\n", " \n", " \n", " coef_departure_constants_am_peak_4\n", - " -1.220042\n", + " -1.207929\n", " \n", " \n", " coef_departure_constants_early\n", - " -0.889376\n", + " -0.930812\n", " \n", " \n", " coef_departure_constants_evening\n", - " -1.989402\n", + " -1.498679\n", " \n", " \n", " coef_departure_constants_late\n", - " -2.936685\n", + " -2.893575\n", " \n", " \n", " coef_departure_constants_midday_1\n", - " -1.826700\n", + " -1.684758\n", " \n", " \n", " coef_departure_constants_midday_2\n", - " -1.878783\n", + " -1.708659\n", " \n", " \n", " coef_departure_constants_pm_peak\n", - " -1.691847\n", + " -1.375804\n", " \n", " \n", " coef_destination_in_cbd_departure_shift_effects\n", - " 0.028678\n", + " 0.057883\n", " \n", " \n", " coef_destination_in_cbd_duration_shift_effects\n", - " 0.096673\n", + " 0.070217\n", " \n", " \n", " coef_destination_in_cbd_early_departure_interaction\n", - " -0.419959\n", + " -0.365371\n", " \n", " \n", " coef_destination_in_cbd_late_arrival_interaction\n", - " -0.266935\n", + " -0.156618\n", " \n", " \n", " coef_duration_constants_0_to_2_hours\n", - " -2.062403\n", + " -2.598564\n", " \n", " \n", " coef_duration_constants_10_hours\n", @@ -1641,75 +1804,75 @@ " \n", " \n", " coef_duration_constants_11_hours\n", - " -0.358479\n", + " -0.316543\n", " \n", " \n", " coef_duration_constants_12_to_13_hours\n", - " -1.132000\n", + " -0.998700\n", " \n", " \n", " coef_duration_constants_14_to_18_hours\n", - " -1.854875\n", + " -1.641305\n", " \n", " \n", " coef_duration_constants_3_to_4_hours\n", - " -0.600278\n", + " -0.976620\n", " \n", " \n", " coef_duration_constants_5_to_6_hours\n", - " -0.343562\n", + " -0.786160\n", " \n", " \n", " coef_duration_constants_7_to_8_hours\n", - " -0.033981\n", + " -0.191835\n", " \n", " \n", " coef_duration_constants_9_hours\n", - " 0.137251\n", + " 0.041325\n", " \n", " \n", " coef_first_of_2plus_work_tours_departure_shift_effects\n", - " -0.289684\n", + " -0.286911\n", " \n", " \n", " coef_first_of_2plus_work_tours_duration_lt_8_hrs\n", - " 1.916784\n", + " 2.160421\n", " \n", " \n", " coef_first_of_2plus_work_tours_duration_shift_effects\n", - " -0.286185\n", + " -0.159326\n", " \n", " \n", " coef_free_flow_round_trip_auto_time_shift_effects_departure\n", - " 0.000599\n", + " -0.001158\n", " \n", " \n", " coef_free_flow_round_trip_auto_time_shift_effects_duration\n", - " 0.004216\n", + " 0.002097\n", " \n", " \n", " coef_full_time_worker_10_to_12_departure_interaction\n", - " -0.678250\n", + " -0.474411\n", " \n", " \n", " coef_full_time_worker_duration_lt_9_hours_interaction\n", - " -1.357293\n", + " -1.190464\n", " \n", " \n", " coef_household_income_departure_shift_effects\n", - " 0.000111\n", + " 0.000219\n", " \n", " \n", " coef_household_income_early_departure_interaction\n", - " -0.582774\n", + " -0.462242\n", " \n", " \n", " coef_household_income_late_arrival_interaction\n", - " 0.029954\n", + " -0.560334\n", " \n", " \n", " coef_mode_choice_logsum\n", - " 0.247114\n", + " 0.666366\n", " \n", " \n", " coef_non_working_adult_duration_shift_effects\n", @@ -1717,23 +1880,23 @@ " \n", " \n", " coef_part_time_worker_13_to_15_arrival_interaction\n", - " 0.375322\n", + " 0.687690\n", " \n", " \n", " coef_part_time_worker_departure_shift_effects\n", - " 0.095094\n", + " 0.058805\n", " \n", " \n", " coef_previously_scheduled_tour_begins_in_this_arrival_hour\n", - " -6.724955\n", + " -1.250685\n", " \n", " \n", " coef_previously_scheduled_tour_ends_in_this_departure_hour\n", - " 0.258853\n", + " -0.563627\n", " \n", " \n", " coef_remaining_tours_to_be_scheduled_div_number_of_unscheduled_hours\n", - " -6.865187\n", + " -18.677135\n", " \n", " \n", " coef_rural_household_early_departure_interaction\n", @@ -1745,34 +1908,34 @@ " \n", " \n", " coef_subsequent_2plus_work_departure_tours_shift_effects\n", - " 0.060824\n", + " 0.059853\n", " \n", " \n", " coef_subsequent_2plus_work_duration_tours_shift_effects\n", - " -0.080957\n", + " -0.352513\n", " \n", " \n", " coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs\n", - " 5.443390\n", + " 2.609918\n", " \n", " \n", " coef_subsequent_tour_must_start_after_previous_tour_ends\n", - " -25.000000\n", + " -100.000000\n", " \n", " \n", " coef_tours_by_student_duration_lt_8_hrs\n", - " 20.927636\n", + " 2.619822\n", " \n", " \n", " coef_tours_by_worker_duration_lt_8_hrs\n", - " 19.258236\n", + " 0.950422\n", " \n", " \n", " coef_university_student_departure_shift_effects\n", - " 0.076480\n", + " 0.045387\n", " \n", " \n", - "loglike-8399.82196783851d_loglike\n", + "
logloss3.971246101795334d_logloss\n", " \n", " \n", " \n", @@ -1782,23 +1945,23 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1806,19 +1969,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1826,19 +1989,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1846,55 +2009,55 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1902,75 +2065,75 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1978,23 +2141,23 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2006,15 +2169,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2022,65 +2185,65 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - "
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction6.227709e-05-2.476569e-05
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction-3.094051e-042.401362e-05
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction2.047044e-04-3.242733e-07
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction1.044967e-041.721606e-05
coef_arrival_constants_am_peak-2.094941e-056.908123e-05
coef_arrival_constants_early
coef_arrival_constants_evening-2.523831e-047.288184e-05
coef_arrival_constants_late-1.447395e-03-9.483020e-05
coef_arrival_constants_midday_12.766105e-04-4.017493e-05
coef_arrival_constants_midday_27.345342e-04-6.167975e-05
coef_arrival_constants_pm_peak_1
coef_arrival_constants_pm_peak_27.327399e-04-3.095877e-05
coef_arrival_constants_pm_peak_34.196985e-04-1.941954e-04
coef_arrival_constants_pm_peak_4-6.906812e-049.466248e-05
coef_departure_constants_am_peak_11.225866e-035.666160e-05
coef_departure_constants_am_peak_2
coef_departure_constants_am_peak_31.473105e-03-1.055621e-04
coef_departure_constants_am_peak_4-1.160737e-031.197416e-05
coef_departure_constants_early1.279229e-03-4.303027e-05
coef_departure_constants_evening-7.494769e-044.847181e-05
coef_departure_constants_late-3.382858e-04-1.550132e-05
coef_departure_constants_midday_13.335414e-054.834936e-05
coef_departure_constants_midday_2-2.645412e-03-1.698437e-04
coef_departure_constants_pm_peak-1.917919e-031.852010e-04
coef_destination_in_cbd_departure_shift_effects-4.480046e-022.109060e-04
coef_destination_in_cbd_duration_shift_effects2.390663e-025.183584e-04
coef_destination_in_cbd_early_departure_interaction1.038321e-038.561721e-05
coef_destination_in_cbd_late_arrival_interaction-7.345503e-043.056000e-06
coef_duration_constants_0_to_2_hours-1.367149e-037.551894e-05
coef_duration_constants_10_hours
coef_duration_constants_11_hours7.690066e-04-5.843846e-05
coef_duration_constants_12_to_13_hours1.653562e-036.715821e-05
coef_duration_constants_14_to_18_hours1.225821e-031.601895e-04
coef_duration_constants_3_to_4_hours-1.640102e-03-3.312036e-05
coef_duration_constants_5_to_6_hours-5.618970e-04-1.248871e-04
coef_duration_constants_7_to_8_hours4.597377e-041.212099e-05
coef_duration_constants_9_hours-7.212915e-04-1.193587e-04
coef_first_of_2plus_work_tours_departure_shift_effects-6.512833e-036.406568e-05
coef_first_of_2plus_work_tours_duration_lt_8_hrs-2.321194e-041.190483e-05
coef_first_of_2plus_work_tours_duration_shift_effects3.977570e-03-9.017286e-05
coef_free_flow_round_trip_auto_time_shift_effects_departure-9.773028e-01-1.930899e-03
coef_free_flow_round_trip_auto_time_shift_effects_duration6.851835e-013.916590e-04
coef_full_time_worker_10_to_12_departure_interaction-1.959177e-042.789068e-05
coef_full_time_worker_duration_lt_9_hours_interaction-2.085279e-03-5.147377e-05
coef_household_income_departure_shift_effects-6.023402e+00-8.126657e-03
coef_household_income_early_departure_interaction9.200981e-05-4.696739e-05
coef_household_income_late_arrival_interaction-2.749490e-045.039132e-05
coef_mode_choice_logsum-1.198356e-031.368051e-05
coef_non_working_adult_duration_shift_effects
coef_part_time_worker_13_to_15_arrival_interaction3.494690e-042.401302e-05
coef_part_time_worker_departure_shift_effects-7.745591e-031.505693e-04
coef_previously_scheduled_tour_begins_in_this_arrival_hour-4.665139e-051.307335e-04
coef_previously_scheduled_tour_ends_in_this_departure_hour-2.485873e-05-6.743726e-06
coef_remaining_tours_to_be_scheduled_div_number_of_unscheduled_hours2.255476e-066.820090e-06
coef_rural_household_early_departure_interaction
coef_subsequent_2plus_work_departure_tours_shift_effects-8.338787e-03-3.661524e-05
coef_subsequent_2plus_work_duration_tours_shift_effects7.065869e-042.967934e-05
coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs-2.124468e-043.755607e-05
coef_subsequent_tour_must_start_after_previous_tour_ends
coef_tours_by_student_duration_lt_8_hrs-7.862668e-165.453713e-05
coef_tours_by_worker_duration_lt_8_hrs-7.862668e-165.453713e-05
coef_university_student_departure_shift_effects-1.306805e-025.979971e-05
nit64nfev177njev64status0message'Optimization terminated successfully'successTrueelapsed_time0:00:08.813504method'slsqp'n_cases2124iteration_number64logloss3.954718440601935" + "nit55nfev69njev55status0message'Optimization terminated successfully'successTrueelapsed_time0:00:40.125911method'slsqp'n_cases22637iteration_number55loglike-89082.99255547294" ], "text/plain": [ - "┣ x: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.326676\n", - "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction 0.298901\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction -0.038388\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction -0.012605\n", - "┃ coef_arrival_constants_am_peak -2.527138\n", - "┃ ... \n", - "┃ coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs 5.443390\n", - "┃ coef_subsequent_tour_must_start_after_previous_tour_ends -25.000000\n", - "┃ coef_tours_by_student_duration_lt_8_hrs 20.927636\n", - "┃ coef_tours_by_worker_duration_lt_8_hrs 19.258236\n", - "┃ coef_university_student_departure_shift_effects 0.076480\n", + "┣ x: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.346120\n", + "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction -0.097167\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.103758\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction -0.534895\n", + "┃ coef_arrival_constants_am_peak -1.859817\n", + "┃ ... \n", + "┃ coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs 2.609918\n", + "┃ coef_subsequent_tour_must_start_after_previous_tour_ends -100.000000\n", + "┃ coef_tours_by_student_duration_lt_8_hrs 2.619822\n", + "┃ coef_tours_by_worker_duration_lt_8_hrs 0.950422\n", + "┃ coef_university_student_departure_shift_effects 0.045387\n", "┃ Length: 63, dtype: float64\n", - "┣ loglike: -8399.82196783851\n", - "┣ d_loglike: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 6.227709e-05\n", - "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction -3.094051e-04\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 2.047044e-04\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction 1.044967e-04\n", - "┃ coef_arrival_constants_am_peak -2.094941e-05\n", + "┣ logloss: 3.971246101795334\n", + "┣ d_logloss: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction -2.476569e-05\n", + "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction 2.401362e-05\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction -3.242733e-07\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction 1.721606e-05\n", + "┃ coef_arrival_constants_am_peak 6.908123e-05\n", "┃ ... \n", - "┃ coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs -2.124468e-04\n", + "┃ coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs 3.755607e-05\n", "┃ coef_subsequent_tour_must_start_after_previous_tour_ends 0.000000e+00\n", - "┃ coef_tours_by_student_duration_lt_8_hrs -7.862668e-16\n", - "┃ coef_tours_by_worker_duration_lt_8_hrs -7.862668e-16\n", - "┃ coef_university_student_departure_shift_effects -1.306805e-02\n", + "┃ coef_tours_by_student_duration_lt_8_hrs 5.453713e-05\n", + "┃ coef_tours_by_worker_duration_lt_8_hrs 5.453713e-05\n", + "┃ coef_university_student_departure_shift_effects 5.979971e-05\n", "┃ Length: 63, dtype: float64\n", - "┣ nit: 64\n", - "┣ nfev: 177\n", - "┣ njev: 64\n", + "┣ nit: 55\n", + "┣ nfev: 69\n", + "┣ njev: 55\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=8, microseconds=813504)\n", + "┣ elapsed_time: datetime.timedelta(seconds=40, microseconds=125911)\n", "┣ method: 'slsqp'\n", - "┣ n_cases: 2124\n", - "┣ iteration_number: 64\n", - "┣ logloss: 3.954718440601935" + "┣ n_cases: 22637\n", + "┣ iteration_number: 55\n", + "┣ loglike: -89082.99255547294" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - 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Value Std Err t Stat Signif Null Value Constrained
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.327 0.208 1.57 0.00
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction 0.299 0.244 1.23 0.00
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction-0.0384 0.207-0.19 0.00
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction-0.0126 0.274-0.05 0.00
coef_arrival_constants_am_peak-2.53 0.539-4.68*** 0.00
coef_arrival_constants_early 0.00 NA NA 0.00fixed value
coef_arrival_constants_evening-0.0858 0.208-0.41 0.00
coef_arrival_constants_late-1.22 0.282-4.33*** 0.00
coef_arrival_constants_midday_1-0.490 0.186-2.64** 0.00
coef_arrival_constants_midday_2-0.383 0.132-2.90** 0.00
coef_arrival_constants_pm_peak_1 0.00 NA NA 0.00fixed value
coef_arrival_constants_pm_peak_2 0.202 0.120 1.69 0.00
coef_arrival_constants_pm_peak_3 0.573 0.133 4.30*** 0.00
coef_arrival_constants_pm_peak_4 0.706 0.159 4.44*** 0.00
coef_departure_constants_am_peak_1-0.642 0.0804-7.99*** 0.00
coef_departure_constants_am_peak_2 0.00 NA NA 0.00fixed value
coef_departure_constants_am_peak_3-0.323 0.0737-4.38*** 0.00
coef_departure_constants_am_peak_4-1.22 0.117-10.45*** 0.00
coef_departure_constants_early-0.889 0.134-6.62*** 0.00
coef_departure_constants_evening-1.99 0.528-3.77*** 0.00
coef_departure_constants_late-2.94 1.18-2.49* 0.00
coef_departure_constants_midday_1-1.83 0.208-8.78*** 0.00
coef_departure_constants_midday_2-1.88 0.266-7.06*** 0.00
coef_departure_constants_pm_peak-1.69 0.371-4.56*** 0.00
coef_destination_in_cbd_departure_shift_effects 0.0287 0.0226 1.27 0.00
coef_destination_in_cbd_duration_shift_effects 0.0967 0.0220 4.39*** 0.00
coef_destination_in_cbd_early_departure_interaction-0.420 0.196-2.14* 0.00
coef_destination_in_cbd_late_arrival_interaction-0.267 0.283-0.94 0.00
coef_duration_constants_0_to_2_hours-2.06 0.351-5.88*** 0.00
coef_duration_constants_10_hours 0.00 NA NA 0.00fixed value
coef_duration_constants_11_hours-0.358 0.0855-4.19*** 0.00
coef_duration_constants_12_to_13_hours-1.13 0.126-9.00*** 0.00
coef_duration_constants_14_to_18_hours-1.85 0.206-9.00*** 0.00
coef_duration_constants_3_to_4_hours-0.600 0.269-2.23* 0.00
coef_duration_constants_5_to_6_hours-0.344 0.216-1.59 0.00
coef_duration_constants_7_to_8_hours-0.0340 0.168-0.20 0.00
coef_duration_constants_9_hours 0.137 0.0802 1.71 0.00
coef_first_of_2plus_work_tours_departure_shift_effects-0.290 0.0438-6.61*** 0.00
coef_first_of_2plus_work_tours_duration_lt_8_hrs 1.92 0.473 4.05*** 0.00
coef_first_of_2plus_work_tours_duration_shift_effects-0.286 0.117-2.44* 0.00
coef_free_flow_round_trip_auto_time_shift_effects_departure 0.000599 0.00113 0.53 0.00
coef_free_flow_round_trip_auto_time_shift_effects_duration 0.00422 0.00113 3.74*** 0.00
coef_full_time_worker_10_to_12_departure_interaction-0.678 0.188-3.61*** 0.00
coef_full_time_worker_duration_lt_9_hours_interaction-1.36 0.151-8.96*** 0.00
coef_household_income_departure_shift_effects 0.000111 5.14e-05 2.17* 0.00
coef_household_income_early_departure_interaction-0.583 0.190-3.06** 0.00
coef_household_income_late_arrival_interaction 0.0300 0.261 0.11 0.00
coef_mode_choice_logsum 0.247 0.208 1.19 0.00
coef_non_working_adult_duration_shift_effects-0.121 7.38e-09-BIG*** 0.00
coef_part_time_worker_13_to_15_arrival_interaction 0.375 0.175 2.15* 0.00
coef_part_time_worker_departure_shift_effects 0.0951 0.0253 3.76*** 0.00
coef_previously_scheduled_tour_begins_in_this_arrival_hour-6.72 146.-0.05 0.00
coef_previously_scheduled_tour_ends_in_this_departure_hour 0.259 0.357 0.72 0.00
coef_remaining_tours_to_be_scheduled_div_number_of_unscheduled_hours-6.87 21.4-0.32 0.00
coef_rural_household_early_departure_interaction 0.404 1.82e-10 BIG*** 0.00
coef_rural_household_late_arrival_interaction-0.345 1.13e-10-BIG*** 0.00
coef_subsequent_2plus_work_departure_tours_shift_effects 0.0608 0.0688 0.88 0.00
coef_subsequent_2plus_work_duration_tours_shift_effects-0.0810 0.0775-1.05 0.00
coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs 5.44 1.37 3.97*** 0.00
coef_subsequent_tour_must_start_after_previous_tour_ends-100. NA NA 0.00fixed value
coef_tours_by_student_duration_lt_8_hrs 20.9 8.74e-05 BIG*** 0.00
coef_tours_by_worker_duration_lt_8_hrs 19.3 8.74e-05 BIG*** 0.00
coef_university_student_departure_shift_effects 0.0765 0.0340 2.25* 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.346 0.844 0.41 0.00
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction-0.0972 0.215-0.45 0.00
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.104 0.118 0.88 0.00
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction-0.535 0.816-0.66 0.00
coef_arrival_constants_am_peak-1.86 0.145-12.84*** 0.00
coef_arrival_constants_early 0.00 0.00 NA 0.00fixed value
coef_arrival_constants_evening 0.109 0.0645 1.68 0.00
coef_arrival_constants_late-0.888 0.0858-10.35*** 0.00
coef_arrival_constants_midday_1-0.478 0.0618-7.73*** 0.00
coef_arrival_constants_midday_2-0.405 0.0420-9.64*** 0.00
coef_arrival_constants_pm_peak_1 0.00 0.00 NA 0.00fixed value
coef_arrival_constants_pm_peak_2 0.320 0.0376 8.52*** 0.00
coef_arrival_constants_pm_peak_3 0.737 0.0414 17.81*** 0.00
coef_arrival_constants_pm_peak_4 0.834 0.0492 16.97*** 0.00
coef_departure_constants_am_peak_1-0.601 0.0240-25.03*** 0.00
coef_departure_constants_am_peak_2 0.00 0.00 NA 0.00fixed value
coef_departure_constants_am_peak_3-0.221 0.0223-9.89*** 0.00
coef_departure_constants_am_peak_4-1.21 0.0368-32.83*** 0.00
coef_departure_constants_early-0.931 0.0394-23.64*** 0.00
coef_departure_constants_evening-1.50 0.169-8.89*** 0.00
coef_departure_constants_late-2.89 0.523-5.53*** 0.00
coef_departure_constants_midday_1-1.68 0.0667-25.25*** 0.00
coef_departure_constants_midday_2-1.71 0.0823-20.76*** 0.00
coef_departure_constants_pm_peak-1.38 0.115-11.93*** 0.00
coef_destination_in_cbd_departure_shift_effects 0.0579 0.00940 6.16*** 0.00
coef_destination_in_cbd_duration_shift_effects 0.0702 0.00841 8.35*** 0.00
coef_destination_in_cbd_early_departure_interaction-0.365 0.0703-5.19*** 0.00
coef_destination_in_cbd_late_arrival_interaction-0.157 0.102-1.54 0.00
coef_duration_constants_0_to_2_hours-2.60 0.110-23.52*** 0.00
coef_duration_constants_10_hours 0.00 0.00 NA 0.00fixed value
coef_duration_constants_11_hours-0.317 0.0255-12.41*** 0.00
coef_duration_constants_12_to_13_hours-0.999 0.0368-27.14*** 0.00
coef_duration_constants_14_to_18_hours-1.64 0.0595-27.58*** 0.00
coef_duration_constants_3_to_4_hours-0.977 0.0830-11.76*** 0.00
coef_duration_constants_5_to_6_hours-0.786 0.0678-11.60*** 0.00
coef_duration_constants_7_to_8_hours-0.192 0.0520-3.69*** 0.00
coef_duration_constants_9_hours 0.0413 0.0245 1.69 0.00
coef_first_of_2plus_work_tours_departure_shift_effects-0.287 0.0162-17.76*** 0.00
coef_first_of_2plus_work_tours_duration_lt_8_hrs 2.16 0.150 14.40*** 0.00
coef_first_of_2plus_work_tours_duration_shift_effects-0.159 0.0411-3.88*** 0.00
coef_free_flow_round_trip_auto_time_shift_effects_departure-0.00116 0.000147-7.89*** 0.00
coef_free_flow_round_trip_auto_time_shift_effects_duration 0.00210 0.000113 18.52*** 0.00
coef_full_time_worker_10_to_12_departure_interaction-0.474 0.0596-7.95*** 0.00
coef_full_time_worker_duration_lt_9_hours_interaction-1.19 0.0487-24.43*** 0.00
coef_household_income_departure_shift_effects 0.000219 3.32e-05 6.61*** 0.00
coef_household_income_early_departure_interaction-0.462 0.0533-8.67*** 0.00
coef_household_income_late_arrival_interaction-0.560 0.0878-6.38*** 0.00
coef_mode_choice_logsum 0.666 0.0752 8.86*** 0.00
coef_non_working_adult_duration_shift_effects-0.121 NA NA 0.00
coef_part_time_worker_13_to_15_arrival_interaction 0.688 0.0550 12.51*** 0.00
coef_part_time_worker_departure_shift_effects 0.0588 0.00877 6.70*** 0.00
coef_previously_scheduled_tour_begins_in_this_arrival_hour-1.25 3.92-0.32 0.00
coef_previously_scheduled_tour_ends_in_this_departure_hour-0.564 0.810-0.70 0.00
coef_remaining_tours_to_be_scheduled_div_number_of_unscheduled_hours-18.7 7.36-2.54* 0.00
coef_rural_household_early_departure_interaction 0.404 NA NA 0.00
coef_rural_household_late_arrival_interaction-0.345 2.80e-14-BIG*** 0.00
coef_subsequent_2plus_work_departure_tours_shift_effects 0.0599 0.0282 2.12* 0.00
coef_subsequent_2plus_work_duration_tours_shift_effects-0.353 0.0325-10.85*** 0.00
coef_subsequent_of_2plus_work_tours_duration_lt_8_hrs 2.61 0.544 4.80*** 0.00
coef_subsequent_tour_must_start_after_previous_tour_ends-100. 0.00 NA 0.00fixed value
coef_tours_by_student_duration_lt_8_hrs 2.62 0.456 5.75*** 0.00
coef_tours_by_worker_duration_lt_8_hrs 0.950 0.456 2.08* 0.00
coef_university_student_departure_shift_effects 0.0454 0.0124 3.66*** 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -2702,7 +2891,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -2723,20 +2912,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -2755,7 +2933,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -2794,19 +2972,19 @@ " \n", " 1\n", " coef_free_flow_round_trip_auto_time_shift_effe...\n", - " 0.000599\n", + " -0.001158\n", " F\n", " \n", " \n", " 2\n", " coef_free_flow_round_trip_auto_time_shift_effe...\n", - " 0.004216\n", + " 0.002097\n", " F\n", " \n", " \n", " 3\n", " coef_part_time_worker_departure_shift_effects\n", - " 0.095094\n", + " 0.058805\n", " F\n", " \n", " \n", @@ -2824,7 +3002,7 @@ " \n", " 59\n", " coef_duration_constants_9_hours\n", - " 0.137251\n", + " 0.041325\n", " F\n", " \n", " \n", @@ -2836,19 +3014,19 @@ " \n", " 61\n", " coef_duration_constants_11_hours\n", - " -0.358479\n", + " -0.316543\n", " F\n", " \n", " \n", " 62\n", " coef_duration_constants_12_to_13_hours\n", - " -1.132000\n", + " -0.998700\n", " F\n", " \n", " \n", " 63\n", " coef_duration_constants_14_to_18_hours\n", - " -1.854875\n", + " -1.641305\n", " F\n", " \n", " \n", @@ -2859,21 +3037,21 @@ "text/plain": [ " coefficient_name value constrain\n", "0 coef_dummy 1.000000 T\n", - "1 coef_free_flow_round_trip_auto_time_shift_effe... 0.000599 F\n", - "2 coef_free_flow_round_trip_auto_time_shift_effe... 0.004216 F\n", - "3 coef_part_time_worker_departure_shift_effects 0.095094 F\n", + "1 coef_free_flow_round_trip_auto_time_shift_effe... -0.001158 F\n", + "2 coef_free_flow_round_trip_auto_time_shift_effe... 0.002097 F\n", + "3 coef_part_time_worker_departure_shift_effects 0.058805 F\n", "4 coef_non_working_adult_duration_shift_effects -0.120700 F\n", ".. ... ... ...\n", - "59 coef_duration_constants_9_hours 0.137251 F\n", + "59 coef_duration_constants_9_hours 0.041325 F\n", "60 coef_duration_constants_10_hours 0.000000 T\n", - "61 coef_duration_constants_11_hours -0.358479 F\n", - "62 coef_duration_constants_12_to_13_hours -1.132000 F\n", - "63 coef_duration_constants_14_to_18_hours -1.854875 F\n", + "61 coef_duration_constants_11_hours -0.316543 F\n", + "62 coef_duration_constants_12_to_13_hours -0.998700 F\n", + "63 coef_duration_constants_14_to_18_hours -1.641305 F\n", "\n", "[64 rows x 3 columns]" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -2890,7 +3068,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -2904,7 +3082,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/09_school_tour_scheduling.ipynb b/activitysim/examples/example_estimation/notebooks/09_school_tour_scheduling.ipynb index 397fe34962..d05cc6e6f9 100644 --- a/activitysim/examples/example_estimation/notebooks/09_school_tour_scheduling.ipynb +++ b/activitysim/examples/example_estimation/notebooks/09_school_tour_scheduling.ipynb @@ -34,27 +34,75 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +116,28 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_scheduling_school/tour_scheduling_school_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_scheduling_school/mandatory_tour_scheduling_school_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_scheduling_school/mandatory_tour_scheduling_school_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/mandatory_tour_scheduling_school/mandatory_tour_scheduling_school_choosers_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"mandatory_tour_scheduling_school\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -673,28 +737,28 @@ " 23\n", " coef_adjacent_window_exists_before_this_depart...\n", " Adjacent window exists before this departure h...\n", - " @(df.tour_count>1) & (df.tour_num == 1) & _adj...\n", + " @(df.tour_count>1) * (df.tour_num == 1) * _adj...\n", " coef_adjacent_window_exists_before_this_depart...\n", " \n", " \n", " 24\n", " coef_adjacent_window_exists_after_this_arrival...\n", " Adjacent window exists after this arrival hour...\n", - " @(df.tour_count>1) & (df.tour_num == 1) & _adj...\n", + " @(df.tour_count>1) * (df.tour_num == 1) * _adj...\n", " coef_adjacent_window_exists_after_this_arrival...\n", " \n", " \n", " 25\n", " util_adjacent_window_exists_before_this_depart...\n", " Adjacent window exists before this departure h...\n", - " @(df.tour_num > 1) & _adjacent_window_before\n", + " @(df.tour_num > 1) * _adjacent_window_before\n", " coef_adjacent_window_exists_before_this_depart...\n", " \n", " \n", " 26\n", " util_adjacent_window_exists_after_this_arrival...\n", " Adjacent window exists after this arrival hour...\n", - " @(df.tour_num > 1) & _adjacent_window_after\n", + " @(df.tour_num > 1) * _adjacent_window_after\n", " coef_adjacent_window_exists_after_this_arrival...\n", " \n", " \n", @@ -713,7 +777,7 @@ " \n", " \n", " 29\n", - " util_departure_constants_am_peak_1 _6\n", + " util_departure_constants_am_peak_1_6\n", " Departure Constants -- AM peak 1 (6)\n", " start == 6\n", " coef_departure_constants_am_peak_1\n", @@ -940,7 +1004,7 @@ "26 util_adjacent_window_exists_after_this_arrival... \n", "27 util_remaining_work_school_tours_to_be_schedul... \n", "28 util_departure_constants_early_up_to_5 \n", - "29 util_departure_constants_am_peak_1 _6 \n", + "29 util_departure_constants_am_peak_1_6 \n", "30 util_departure_constants_am_peak_2_7 \n", "31 util_departure_constants_am_peak_3_8 \n", "32 util_departure_constants_am_peak_4_9 \n", @@ -1048,10 +1112,10 @@ "18 mode_choice_logsum \n", "21 @tt.previous_tour_ends(df.person_id, df.start) \n", "22 @tt.previous_tour_begins(df.person_id, df.end) \n", - "23 @(df.tour_count>1) & (df.tour_num == 1) & _adj... \n", - "24 @(df.tour_count>1) & (df.tour_num == 1) & _adj... \n", - "25 @(df.tour_num > 1) & _adjacent_window_before \n", - "26 @(df.tour_num > 1) & _adjacent_window_after \n", + "23 @(df.tour_count>1) * (df.tour_num == 1) * _adj... \n", + "24 @(df.tour_count>1) * (df.tour_num == 1) * _adj... \n", + "25 @(df.tour_num > 1) * _adjacent_window_before \n", + "26 @(df.tour_num > 1) * _adjacent_window_after \n", "27 @((df.tour_count>1) & (df.tour_num == 1)) * 1.... \n", "28 start < 6 \n", "29 start == 6 \n", @@ -1209,10 +1273,10 @@ " \n", " \n", " 0\n", - " 25820\n", - " 106\n", - " 121\n", - " 629\n", + " 78669\n", + " 136\n", + " 59\n", + " 1918\n", " school\n", " 1\n", " 1\n", @@ -1226,17 +1290,17 @@ " True\n", " True\n", " -1\n", - " 12\n", - " 131\n", + " 188\n", + " 186\n", " 5\n", " 5\n", " \n", " \n", " 1\n", - " 52265\n", - " 88\n", - " 86\n", - " 1274\n", + " 131846\n", + " 175\n", + " 59\n", + " 3215\n", " school\n", " 1\n", " 1\n", @@ -1250,17 +1314,17 @@ " True\n", " True\n", " -1\n", - " 10\n", - " 166\n", + " 229\n", + " 252\n", " 5\n", " 5\n", " \n", " \n", " 2\n", - " 1117937\n", - " 163\n", - " 163\n", - " 27266\n", + " 178873\n", + " 166\n", + " 45\n", + " 4362\n", " school\n", " 1\n", " 1\n", @@ -1274,17 +1338,17 @@ " True\n", " True\n", " -1\n", - " 12\n", - " 9\n", + " 342\n", + " 313\n", " 5\n", " 5\n", " \n", " \n", " 3\n", - " 1148523\n", - " 126\n", - " 56\n", - " 28012\n", + " 240250\n", + " 154\n", + " 64\n", + " 5859\n", " school\n", " 1\n", " 1\n", @@ -1298,17 +1362,17 @@ " True\n", " True\n", " -1\n", - " 5\n", - " 10\n", + " 490\n", + " 400\n", " 5\n", " 5\n", " \n", " \n", " 4\n", - " 1208547\n", - " 61\n", - " 61\n", - " 29476\n", + " 250131\n", + " 164\n", + " 74\n", + " 6100\n", " school\n", " 1\n", " 1\n", @@ -1322,8 +1386,8 @@ " True\n", " True\n", " -1\n", - " 13\n", - " 16\n", + " 545\n", + " 437\n", " 5\n", " 5\n", " \n", @@ -1352,59 +1416,59 @@ " ...\n", " \n", " \n", - " 604\n", - " 307969317\n", - " 170\n", - " 170\n", - " 7511446\n", + " 10347\n", + " 309517395\n", + " 78\n", + " 60\n", + " 7549204\n", " school\n", " 1\n", " 1\n", - " 2\n", - " 2\n", + " 1\n", + " 1\n", " mandatory\n", " ...\n", " False\n", - " work_and_school\n", - " True\n", - " True\n", + " school1\n", + " False\n", " True\n", - " 92\n", - " 91\n", - " 8\n", - " 7\n", - " 12\n", + " False\n", + " -1\n", + " 885\n", + " 907\n", + " 5\n", + " 5\n", " \n", " \n", - " 605\n", - " 308122616\n", - " 163\n", - " 164\n", - " 7515185\n", + " 10348\n", + " 309518789\n", + " 45\n", + " 64\n", + " 7549238\n", " school\n", " 1\n", " 1\n", - " 2\n", - " 2\n", + " 1\n", + " 1\n", " mandatory\n", " ...\n", " False\n", - " work_and_school\n", - " True\n", - " True\n", + " school1\n", + " False\n", " True\n", - " 16\n", - " 188\n", - " 142\n", - " 7\n", - " 14\n", + " False\n", + " -1\n", + " 1018\n", + " 910\n", + " 5\n", + " 5\n", " \n", " \n", - " 606\n", - " 308631508\n", - " 169\n", - " 169\n", - " 7527597\n", + " 10349\n", + " 309590785\n", + " 126\n", + " 46\n", + " 7550994\n", " school\n", " 1\n", " 1\n", @@ -1416,133 +1480,133 @@ " school1\n", " False\n", " True\n", - " True\n", + " False\n", " -1\n", - " 13\n", - " 188\n", + " 1091\n", + " 1124\n", " 5\n", " 5\n", " \n", " \n", - " 607\n", - " 309183983\n", - " 22\n", - " 20\n", - " 7541072\n", + " 10350\n", + " 309649169\n", + " 62\n", + " 28\n", + " 7552418\n", " school\n", - " 2\n", " 1\n", " 1\n", - " 2\n", + " 1\n", + " 1\n", " mandatory\n", " ...\n", " False\n", - " school2\n", + " school1\n", " False\n", " True\n", - " True\n", + " False\n", " -1\n", - " 107\n", - " 117\n", + " 1263\n", + " 1268\n", " 5\n", " 5\n", " \n", " \n", - " 608\n", - " 309183984\n", - " 180\n", - " 175\n", - " 7541072\n", + " 10351\n", + " 310038054\n", + " 38\n", + " 148\n", + " 7561903\n", " school\n", - " 2\n", - " 2\n", - " 2\n", - " 2\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " mandatory\n", " ...\n", " False\n", - " school2\n", + " school1\n", " False\n", " True\n", " True\n", " -1\n", - " 107\n", - " 117\n", - " 6\n", - " 9\n", + " 1127\n", + " 1121\n", + " 5\n", + " 5\n", " \n", " \n", "\n", - "

609 rows × 40 columns

\n", + "

10352 rows × 40 columns

\n", "" ], "text/plain": [ - " tour_id model_choice override_choice person_id tour_type \\\n", - "0 25820 106 121 629 school \n", - "1 52265 88 86 1274 school \n", - "2 1117937 163 163 27266 school \n", - "3 1148523 126 56 28012 school \n", - "4 1208547 61 61 29476 school \n", - ".. ... ... ... ... ... \n", - "604 307969317 170 170 7511446 school \n", - "605 308122616 163 164 7515185 school \n", - "606 308631508 169 169 7527597 school \n", - "607 309183983 22 20 7541072 school \n", - "608 309183984 180 175 7541072 school \n", + " tour_id model_choice override_choice person_id tour_type \\\n", + "0 78669 136 59 1918 school \n", + "1 131846 175 59 3215 school \n", + "2 178873 166 45 4362 school \n", + "3 240250 154 64 5859 school \n", + "4 250131 164 74 6100 school \n", + "... ... ... ... ... ... \n", + "10347 309517395 78 60 7549204 school \n", + "10348 309518789 45 64 7549238 school \n", + "10349 309590785 126 46 7550994 school \n", + "10350 309649169 62 28 7552418 school \n", + "10351 310038054 38 148 7561903 school \n", "\n", - " tour_type_count tour_type_num tour_num tour_count tour_category ... \\\n", - "0 1 1 1 1 mandatory ... \n", - "1 1 1 1 1 mandatory ... \n", - "2 1 1 1 1 mandatory ... \n", - "3 1 1 1 1 mandatory ... \n", - "4 1 1 1 1 mandatory ... \n", - ".. ... ... ... ... ... ... \n", - "604 1 1 2 2 mandatory ... \n", - "605 1 1 2 2 mandatory ... \n", - "606 1 1 1 1 mandatory ... \n", - "607 2 1 1 2 mandatory ... \n", - "608 2 2 2 2 mandatory ... \n", + " tour_type_count tour_type_num tour_num tour_count tour_category \\\n", + "0 1 1 1 1 mandatory \n", + "1 1 1 1 1 mandatory \n", + "2 1 1 1 1 mandatory \n", + "3 1 1 1 1 mandatory \n", + "4 1 1 1 1 mandatory \n", + "... ... ... ... ... ... \n", + "10347 1 1 1 1 mandatory \n", + "10348 1 1 1 1 mandatory \n", + "10349 1 1 1 1 mandatory \n", + "10350 1 1 1 1 mandatory \n", + "10351 1 1 1 1 mandatory \n", "\n", - " home_is_rural mandatory_tour_frequency is_worker is_student \\\n", - "0 False school1 False True \n", - "1 False school1 False True \n", - "2 False school1 False True \n", - "3 False school1 False True \n", - "4 False school1 False True \n", - ".. ... ... ... ... \n", - "604 False work_and_school True True \n", - "605 False work_and_school True True \n", - "606 False school1 False True \n", - "607 False school2 False True \n", - "608 False school2 False True \n", + " ... home_is_rural mandatory_tour_frequency is_worker is_student \\\n", + "0 ... False school1 False True \n", + "1 ... False school1 False True \n", + "2 ... False school1 False True \n", + "3 ... False school1 False True \n", + "4 ... False school1 False True \n", + "... ... ... ... ... ... \n", + "10347 ... False school1 False True \n", + "10348 ... False school1 False True \n", + "10349 ... False school1 False True \n", + "10350 ... False school1 False True \n", + "10351 ... False school1 False True \n", "\n", - " is_university workplace_zone_id school_zone_id home_zone_id \\\n", - "0 True -1 12 131 \n", - "1 True -1 10 166 \n", - "2 True -1 12 9 \n", - "3 True -1 5 10 \n", - "4 True -1 13 16 \n", - ".. ... ... ... ... \n", - "604 True 92 91 8 \n", - "605 True 16 188 142 \n", - "606 True -1 13 188 \n", - "607 True -1 107 117 \n", - "608 True -1 107 117 \n", + " is_university workplace_zone_id school_zone_id home_zone_id \\\n", + "0 True -1 188 186 \n", + "1 True -1 229 252 \n", + "2 True -1 342 313 \n", + "3 True -1 490 400 \n", + "4 True -1 545 437 \n", + "... ... ... ... ... \n", + "10347 False -1 885 907 \n", + "10348 False -1 1018 910 \n", + "10349 False -1 1091 1124 \n", + "10350 False -1 1263 1268 \n", + "10351 True -1 1127 1121 \n", "\n", - " start_previous end_previous \n", - "0 5 5 \n", - "1 5 5 \n", - "2 5 5 \n", - "3 5 5 \n", - "4 5 5 \n", - ".. ... ... \n", - "604 7 12 \n", - "605 7 14 \n", - "606 5 5 \n", - "607 5 5 \n", - "608 6 9 \n", + " start_previous end_previous \n", + "0 5 5 \n", + "1 5 5 \n", + "2 5 5 \n", + "3 5 5 \n", + "4 5 5 \n", + "... ... ... \n", + "10347 5 5 \n", + "10348 5 5 \n", + "10349 5 5 \n", + "10350 5 5 \n", + "10351 5 5 \n", "\n", - "[609 rows x 40 columns]" + "[10352 rows x 40 columns]" ] }, "execution_count": 6, @@ -1588,148 +1652,148 @@ " \n", " \n", " tour_id\n", - " variable\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", + " start\n", + " end\n", + " duration\n", + " tdd\n", + " out_period\n", + " in_period\n", + " mode_choice_logsum\n", + " util_roundtrip_auto_time_to_work\n", + " util_ft_worker_departure\n", " ...\n", - " 180\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", + " util_arrival_constants_late_22_and_later\n", + " util_duration_constants_0_to_2_hours\n", + " util_duration_constants_3_to_4_hours\n", + " util_duration_constants_5_to_6_hours\n", + " util_duration_constants_7_to_8_hours\n", + " util_duration_constants_9_hours\n", + " util_duration_constants_10_hours\n", + " util_duration_constants_11_hours\n", + " util_duration_constants_12_to_13_hours\n", + " util_duration_constants_14_to_18_hours\n", " \n", " \n", " \n", " \n", " 0\n", - " 25820\n", - " duration\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", + " 78669\n", + " 5\n", " 5\n", - " 6\n", - " 7\n", - " ...\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", " 0\n", - " 1\n", - " 2\n", " 0\n", - " 1\n", + " EA\n", + " EA\n", + " -0.558633\n", + " 0.0\n", " 0\n", + " ...\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 1\n", - " 25820\n", - " end\n", + " 78669\n", " 5\n", " 6\n", - " 7\n", - " 8\n", - " 9\n", - " 10\n", - " 11\n", - " 12\n", + " 1\n", + " 1\n", + " EA\n", + " AM\n", + " -0.452321\n", + " 0.0\n", + " 0\n", " ...\n", - " 20\n", - " 21\n", - " 22\n", - " 23\n", - " 21\n", - " 22\n", - " 23\n", - " 22\n", - " 23\n", - " 23\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 2\n", - " 25820\n", - " in_period\n", + " 78669\n", + " 5\n", + " 7\n", + " 2\n", + " 2\n", " EA\n", " AM\n", - " AM\n", - " AM\n", - " AM\n", - " MD\n", - " MD\n", - " MD\n", + " -0.452321\n", + " 0.0\n", + " 0\n", " ...\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 3\n", - " 25820\n", - " mode_choice_logsum\n", - " -1.296359741907684\n", - " -1.3037984712857993\n", - " -1.3037984712857993\n", - " -1.3037984712857993\n", - " -1.3037984712857993\n", - " -1.3201068063134296\n", - " -1.3201068063134296\n", - " -1.3201068063134296\n", + " 78669\n", + " 5\n", + " 8\n", + " 3\n", + " 3\n", + " EA\n", + " AM\n", + " -0.452321\n", + " 0.0\n", + " 0\n", " ...\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", - " -1.5517476709880444\n", + " False\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 4\n", - " 25820\n", - " out_period\n", - " EA\n", - " EA\n", - " EA\n", - " EA\n", - " EA\n", - " EA\n", - " EA\n", + " 78669\n", + " 5\n", + " 9\n", + " 4\n", + " 4\n", " EA\n", + " AM\n", + " -0.452321\n", + " 0.0\n", + " 0\n", " ...\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", - " EV\n", + " False\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " ...\n", @@ -1756,68 +1820,68 @@ " ...\n", " \n", " \n", - " 37144\n", - " 309183984\n", - " util_subsequent_2plus_school_tours_duration\n", - " 0\n", + " 1912825\n", + " 310038054\n", + " 21\n", + " 22\n", " 1\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 185\n", + " EV\n", + " EV\n", + " 1.881379\n", + " 0.0\n", " 0\n", " ...\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 0\n", - " 1\n", - " 2\n", - " 0\n", - " 1\n", - " 0\n", - " \n", - " \n", - " 37145\n", - " 309183984\n", - " util_subsequent_of_2plus_school_lt_6_hours\n", " True\n", " True\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " \n", + " \n", + " 1912826\n", + " 310038054\n", + " 21\n", + " 23\n", + " 2\n", + " 186\n", + " EV\n", + " EV\n", + " 1.881379\n", + " 0.0\n", " 0\n", " ...\n", " True\n", " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", - " 37146\n", - " 309183984\n", - " util_subsequent_tour_must_start_after_previous...\n", - " True\n", - " True\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 1912827\n", + " 310038054\n", + " 22\n", + " 22\n", " 0\n", + " 187\n", + " EV\n", + " EV\n", + " 1.881379\n", + " 0.0\n", " 0\n", " ...\n", - " False\n", - " False\n", + " True\n", + " True\n", " False\n", " False\n", " False\n", @@ -1828,151 +1892,216 @@ " False\n", " \n", " \n", - " 37147\n", - " 309183984\n", - " util_univ_departure\n", - " 5\n", - " 5\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " ...\n", - " 20\n", - " 20\n", - " 20\n", - " 20\n", - " 21\n", - " 21\n", - " 21\n", - " 22\n", + " 1912828\n", + " 310038054\n", " 22\n", " 23\n", - " \n", - " \n", - " 37148\n", - " 309183984\n", - " util_univ_duration\n", - " 0\n", " 1\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 188\n", + " EV\n", + " EV\n", + " 1.881379\n", + " 0.0\n", " 0\n", " ...\n", + " True\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " \n", + " \n", + " 1912829\n", + " 310038054\n", + " 23\n", + " 23\n", " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 0\n", - " 1\n", - " 2\n", - " 0\n", - " 1\n", + " 189\n", + " EV\n", + " EV\n", + " 1.881379\n", + " 0.0\n", " 0\n", + " ...\n", + " True\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", "\n", - "

37149 rows × 192 columns

\n", + "

1912830 rows × 63 columns

\n", "" ], "text/plain": [ - " tour_id variable \\\n", - "0 25820 duration \n", - "1 25820 end \n", - "2 25820 in_period \n", - "3 25820 mode_choice_logsum \n", - "4 25820 out_period \n", - "... ... ... \n", - "37144 309183984 util_subsequent_2plus_school_tours_duration \n", - "37145 309183984 util_subsequent_of_2plus_school_lt_6_hours \n", - "37146 309183984 util_subsequent_tour_must_start_after_previous... \n", - "37147 309183984 util_univ_departure \n", - "37148 309183984 util_univ_duration \n", + " tour_id start end duration tdd out_period in_period \\\n", + "0 78669 5 5 0 0 EA EA \n", + "1 78669 5 6 1 1 EA AM \n", + "2 78669 5 7 2 2 EA AM \n", + "3 78669 5 8 3 3 EA AM \n", + "4 78669 5 9 4 4 EA AM \n", + "... ... ... ... ... ... ... ... \n", + "1912825 310038054 21 22 1 185 EV EV \n", + "1912826 310038054 21 23 2 186 EV EV \n", + "1912827 310038054 22 22 0 187 EV EV \n", + "1912828 310038054 22 23 1 188 EV EV \n", + "1912829 310038054 23 23 0 189 EV EV \n", + "\n", + " mode_choice_logsum util_roundtrip_auto_time_to_work \\\n", + "0 -0.558633 0.0 \n", + "1 -0.452321 0.0 \n", + "2 -0.452321 0.0 \n", + "3 -0.452321 0.0 \n", + "4 -0.452321 0.0 \n", + "... ... ... \n", + "1912825 1.881379 0.0 \n", + "1912826 1.881379 0.0 \n", + "1912827 1.881379 0.0 \n", + "1912828 1.881379 0.0 \n", + "1912829 1.881379 0.0 \n", + "\n", + " util_ft_worker_departure ... \\\n", + "0 0 ... \n", + "1 0 ... \n", + "2 0 ... \n", + "3 0 ... \n", + "4 0 ... \n", + "... ... ... \n", + "1912825 0 ... \n", + "1912826 0 ... \n", + "1912827 0 ... \n", + "1912828 0 ... \n", + "1912829 0 ... \n", + "\n", + " util_arrival_constants_late_22_and_later \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "1912825 True \n", + "1912826 True \n", + "1912827 True \n", + "1912828 True \n", + "1912829 True \n", + "\n", + " util_duration_constants_0_to_2_hours \\\n", + "0 True \n", + "1 True \n", + "2 True \n", + "3 False \n", + "4 False \n", + "... ... \n", + "1912825 True \n", + "1912826 True \n", + "1912827 True \n", + "1912828 True \n", + "1912829 True \n", "\n", - " 0 1 2 \\\n", - "0 0 1 2 \n", - "1 5 6 7 \n", - "2 EA AM AM \n", - "3 -1.296359741907684 -1.3037984712857993 -1.3037984712857993 \n", - "4 EA EA EA \n", - "... ... ... ... \n", - "37144 0 1 0 \n", - "37145 True True 0 \n", - "37146 True True 0 \n", - "37147 5 5 0 \n", - "37148 0 1 0 \n", + " util_duration_constants_3_to_4_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 True \n", + "4 True \n", + "... ... \n", + "1912825 False \n", + "1912826 False \n", + "1912827 False \n", + "1912828 False \n", + "1912829 False \n", "\n", - " 3 4 5 \\\n", - "0 3 4 5 \n", - "1 8 9 10 \n", - "2 AM AM MD \n", - "3 -1.3037984712857993 -1.3037984712857993 -1.3201068063134296 \n", - "4 EA EA EA \n", - "... ... ... ... \n", - "37144 0 0 0 \n", - "37145 0 0 0 \n", - "37146 0 0 0 \n", - "37147 0 0 0 \n", - "37148 0 0 0 \n", + " util_duration_constants_5_to_6_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "1912825 False \n", + "1912826 False \n", + "1912827 False \n", + "1912828 False \n", + "1912829 False \n", "\n", - " 6 7 ... 180 \\\n", - "0 6 7 ... 0 \n", - "1 11 12 ... 20 \n", - "2 MD MD ... EV \n", - "3 -1.3201068063134296 -1.3201068063134296 ... -1.5517476709880444 \n", - "4 EA EA ... EV \n", - "... ... ... ... ... \n", - "37144 0 0 ... 0 \n", - "37145 0 0 ... True \n", - "37146 0 0 ... False \n", - "37147 0 0 ... 20 \n", - "37148 0 0 ... 0 \n", + " util_duration_constants_7_to_8_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "1912825 False \n", + "1912826 False \n", + "1912827 False \n", + "1912828 False \n", + "1912829 False \n", "\n", - " 181 182 183 \\\n", - "0 1 2 3 \n", - "1 21 22 23 \n", - "2 EV EV EV \n", - "3 -1.5517476709880444 -1.5517476709880444 -1.5517476709880444 \n", - "4 EV EV EV \n", - "... ... ... ... \n", - "37144 1 2 3 \n", - "37145 True True True \n", - "37146 False False False \n", - "37147 20 20 20 \n", - "37148 1 2 3 \n", + " util_duration_constants_9_hours util_duration_constants_10_hours \\\n", + "0 False False \n", + "1 False False \n", + "2 False False \n", + "3 False False \n", + "4 False False \n", + "... ... ... \n", + "1912825 False False \n", + "1912826 False False \n", + "1912827 False False \n", + "1912828 False False \n", + "1912829 False False \n", "\n", - " 184 185 186 \\\n", - "0 0 1 2 \n", - "1 21 22 23 \n", - "2 EV EV EV \n", - "3 -1.5517476709880444 -1.5517476709880444 -1.5517476709880444 \n", - "4 EV EV EV \n", - "... ... ... ... \n", - "37144 0 1 2 \n", - "37145 True True True \n", - "37146 False False False \n", - "37147 21 21 21 \n", - "37148 0 1 2 \n", + " util_duration_constants_11_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "1912825 False \n", + "1912826 False \n", + "1912827 False \n", + "1912828 False \n", + "1912829 False \n", "\n", - " 187 188 189 \n", - "0 0 1 0 \n", - "1 22 23 23 \n", - "2 EV EV EV \n", - "3 -1.5517476709880444 -1.5517476709880444 -1.5517476709880444 \n", - "4 EV EV EV \n", - "... ... ... ... \n", - "37144 0 1 0 \n", - "37145 True True True \n", - "37146 False False False \n", - "37147 22 22 23 \n", - "37148 0 1 0 \n", + " util_duration_constants_12_to_13_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "1912825 False \n", + "1912826 False \n", + "1912827 False \n", + "1912828 False \n", + "1912829 False \n", "\n", - "[37149 rows x 192 columns]" + " util_duration_constants_14_to_18_hours \n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "1912825 False \n", + "1912826 False \n", + "1912827 False \n", + "1912828 False \n", + "1912829 False \n", + "\n", + "[1912830 rows x 63 columns]" ] }, "execution_count": 7, @@ -2002,13 +2131,80 @@ "name": "stderr", "output_type": "stream", "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "problem: chosen_but_not_available has (46 issues)\n" ] }, + { + "data": { + "text/plain": [ + "(,\n", + " ┣ chosen_but_not_available: altid n example rows\n", + " ┃ 0 42 1 3775\n", + " ┃ 1 43 1 3607\n", + " ┃ 2 56 1 2492\n", + " ┃ 3 57 1 9754\n", + " ┃ 4 58 1 3045\n", + " ┃ 5 60 1 4646\n", + " ┃ 6 72 2 2490, 5457\n", + " ┃ 7 76 2 2863, 7566\n", + " ┃ 8 89 1 178\n", + " ┃ 9 90 2 8286, 9903\n", + " ┃ 10 100 1 4456\n", + " ┃ 11 102 3 15, 4847, 7101\n", + " ┃ 12 103 1 4586\n", + " ┃ 13 104 2 1063, 3558\n", + " ┃ 14 105 2 3258, 4140\n", + " ┃ 15 113 2 117, 499\n", + " ┃ 16 114 3 4784, 6830, 7852\n", + " ┃ 17 115 1 604\n", + " ┃ 18 116 5 588, 3916, 7212\n", + " ┃ 19 117 1 145\n", + " ┃ 20 118 4 5150, 5158, 6843\n", + " ┃ 21 120 1 5714\n", + " ┃ 22 125 2 2341, 6819\n", + " ┃ 23 127 2 3989, 5454\n", + " ┃ 24 128 4 1505, 2340, 4408\n", + " ┃ 25 129 1 8024\n", + " ┃ 26 130 2 5146, 9537\n", + " ┃ 27 136 2 932, 1303\n", + " ┃ 28 138 1 8854\n", + " ┃ 29 139 2 4901, 5428\n", + " ┃ 30 140 1 2116\n", + " ┃ 31 141 2 2305, 5424\n", + " ┃ 32 146 4 54, 2193, 2350\n", + " ┃ 33 147 2 7792, 9568\n", + " ┃ 34 156 2 7158, 7229\n", + " ┃ 35 157 1 9717\n", + " ┃ 36 158 1 7840\n", + " ┃ 37 159 2 111, 7231\n", + " ┃ 38 163 2 540, 7847\n", + " ┃ 39 164 2 188, 1819\n", + " ┃ 40 166 1 2035\n", + " ┃ 41 167 1 2976\n", + " ┃ 42 168 1 2143\n", + " ┃ 43 170 2 5247, 7868\n", + " ┃ 44 171 1 64\n", + " ┃ 45 183 1 9440)" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.doctor(repair_ch_av=\"-\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ { "data": { "text/html": [ - "

Iteration 077 [Optimization terminated successfully]

" + "

Iteration 139 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -2020,7 +2216,7 @@ { "data": { "text/html": [ - "

Best LL = -2331.7420221780226

" + "

Best LL = -39483.50824582766

" ], "text/plain": [ "" @@ -2051,853 +2247,811 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction\n", - " -0.414229\n", + " 0.232285\n", + " 0.232285\n", " -0.003049\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.414229\n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction\n", - " -0.640186\n", + " -1.201676\n", + " -1.201676\n", " -0.527100\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.640186\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction\n", - " 1.656920\n", + " -0.419250\n", + " -0.419250\n", " 0.089750\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 1.656920\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction\n", - " 0.225722\n", + " -0.760747\n", + " -0.760747\n", " -0.440000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.225722\n", " \n", " \n", " coef_all_adults_ft_worker_duration\n", - " 0.052336\n", + " 0.079713\n", + " 0.079713\n", " 0.109300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.052336\n", " \n", " \n", " coef_arrival_constants_am_peak\n", - " -2.239162\n", + " -2.595385\n", + " -2.595385\n", " -2.428718\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.239162\n", " \n", " \n", " coef_arrival_constants_early\n", - " -1.065980\n", + " -2.446580\n", + " -2.446580\n", " -2.428718\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.065980\n", " \n", " \n", " coef_arrival_constants_evening\n", - " -1.033329\n", + " -0.707272\n", + " -0.707272\n", " -0.870147\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.033329\n", " \n", " \n", " coef_arrival_constants_late\n", - " -1.315910\n", + " -1.639520\n", + " -1.639520\n", " -1.752000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.315910\n", " \n", " \n", " coef_arrival_constants_midday_1\n", - " -1.302330\n", + " -1.267988\n", + " -1.267988\n", " -1.237909\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.302330\n", " \n", " \n", " coef_arrival_constants_midday_2\n", - " -0.554673\n", + " -0.523484\n", + " -0.523484\n", " -0.539769\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.554673\n", " \n", " \n", " coef_arrival_constants_pm_peak_1\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_arrival_constants_pm_peak_2\n", - " -0.441387\n", + " -0.360268\n", + " -0.360268\n", " -0.389169\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.441387\n", " \n", " \n", " coef_arrival_constants_pm_peak_3\n", - " -0.281247\n", + " -0.096426\n", + " -0.096426\n", " -0.198120\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.281247\n", " \n", " \n", " coef_arrival_constants_pm_peak_4\n", - " -0.370368\n", + " -0.127905\n", + " -0.127905\n", " -0.253625\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.370368\n", " \n", " \n", " coef_departure_constants_am_peak_1\n", - " -1.882694\n", + " -1.606835\n", + " -1.606835\n", " -1.617644\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.882694\n", " \n", " \n", " coef_departure_constants_am_peak_2\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_departure_constants_am_peak_3\n", - " -0.183985\n", + " -0.100582\n", + " -0.100582\n", " -0.073827\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.183985\n", " \n", " \n", " coef_departure_constants_am_peak_4\n", - " -2.016403\n", + " -2.142432\n", + " -2.142432\n", " -2.080571\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.016403\n", " \n", " \n", " coef_departure_constants_early\n", - " -3.636770\n", + " -3.850945\n", + " -3.850945\n", " -3.820662\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -3.636770\n", " \n", " \n", " coef_departure_constants_evening\n", - " -5.258795\n", + " -5.546826\n", + " -5.546826\n", " -5.230288\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -5.258795\n", " \n", " \n", " coef_departure_constants_late\n", - " -21.447622\n", + " -10.890722\n", + " -10.890722\n", " -11.886047\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -21.447622\n", " \n", " \n", " coef_departure_constants_midday_1\n", - " -3.279864\n", + " -3.124481\n", + " -3.124481\n", " -2.985739\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -3.279864\n", " \n", " \n", " coef_departure_constants_midday_2\n", - " -3.750548\n", + " -3.861525\n", + " -3.861525\n", " -3.628435\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -3.750548\n", " \n", " \n", " coef_departure_constants_pm_peak\n", - " -3.093167\n", + " -3.281532\n", + " -3.281532\n", " -3.102505\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -3.093167\n", " \n", " \n", " coef_duration_constants_0_to_2_hours\n", - " -1.372110\n", + " -1.318085\n", + " -1.318085\n", " -1.409956\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.372110\n", " \n", " \n", " coef_duration_constants_10_hours\n", - " -0.876448\n", + " -0.914359\n", + " -0.914359\n", " -0.904789\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.876448\n", " \n", " \n", " coef_duration_constants_11_hours\n", - " -1.127264\n", + " -1.643692\n", + " -1.643692\n", " -1.521163\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.127264\n", " \n", " \n", " coef_duration_constants_12_to_13_hours\n", - " -2.668346\n", + " -2.528269\n", + " -2.528269\n", " -2.418489\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.668346\n", " \n", " \n", " coef_duration_constants_14_to_18_hours\n", - " -2.675974\n", + " -2.541672\n", + " -2.541672\n", " -2.503137\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.675974\n", " \n", " \n", " coef_duration_constants_3_to_4_hours\n", - " -0.552200\n", + " -0.680239\n", + " -0.680239\n", " -0.745893\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.552200\n", " \n", " \n", " coef_duration_constants_5_to_6_hours\n", - " -0.532627\n", + " -0.551126\n", + " -0.551126\n", " -0.567637\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.532627\n", " \n", " \n", " coef_duration_constants_7_to_8_hours\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_duration_constants_9_hours\n", - " -0.487609\n", + " -0.664353\n", + " -0.664353\n", " -0.650807\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.487609\n", " \n", " \n", " coef_first_of_2plus_school_lt_6_hours\n", - " 0.169055\n", + " 1.768123\n", + " 1.768123\n", " 1.487000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.169055\n", " \n", " \n", " coef_first_of_2plus_school_tours_departure\n", - " -0.333830\n", + " -0.277161\n", + " -0.277161\n", " -0.300200\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.333830\n", " \n", " \n", " coef_first_of_2plus_school_tours_duration\n", - " -0.042558\n", + " -0.077846\n", + " -0.077846\n", " -0.159300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.042558\n", " \n", " \n", " coef_ft_worker_departure\n", " 0.397100\n", " 0.397100\n", - " 0.0\n", + " 0.397100\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.397100\n", " \n", " \n", " coef_ft_worker_duration\n", " -0.190800\n", " -0.190800\n", - " 0.0\n", + " -0.190800\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.190800\n", " \n", " \n", " coef_hh_income_early_departure\n", - " -13.757852\n", + " -0.643531\n", + " -0.643531\n", " -0.883700\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -13.757852\n", " \n", " \n", " coef_hh_income_late_arrival\n", - " 0.101726\n", + " -0.123912\n", + " -0.123912\n", " -0.353300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.101726\n", " \n", " \n", " coef_mode_choice_logsum\n", - " 0.056410\n", + " 1.403530\n", + " 1.403530\n", " 2.127000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.056410\n", " \n", " \n", " coef_non_worker_departure\n", " 0.553900\n", " 0.553900\n", - " 0.0\n", + " 0.553900\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.553900\n", " \n", " \n", " coef_previous_tour_begins_this_arrival_hour\n", - " -10.370632\n", + " 1.748525\n", + " 1.748525\n", " -1.102000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -10.370632\n", " \n", " \n", " coef_previous_tour_ends_this_departure_hour\n", - " 0.298551\n", + " -1.454921\n", + " -1.454921\n", " -0.599500\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.298551\n", " \n", " \n", " coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours\n", - " -25.000000\n", + " -16.666935\n", + " -16.666935\n", " -16.670000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -25.000000\n", " \n", " \n", " coef_roundtrip_auto_time_to_work\n", - " 0.005137\n", + " 0.002946\n", + " 0.002946\n", " 0.003195\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.005137\n", " \n", " \n", " coef_school_plus_work_tours_by_student_lt_6_hours\n", - " -2.483313\n", + " 1.805060\n", + " 1.805060\n", " 1.730000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.483313\n", " \n", " \n", " coef_school_plus_work_tours_by_worker_lt_6_hours\n", - " -2.071313\n", + " 2.217060\n", + " 2.217060\n", " 2.142000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.071313\n", " \n", " \n", " coef_student_driver_duration\n", - " -0.003958\n", + " 0.021414\n", + " 0.021414\n", " 0.034640\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.003958\n", " \n", " \n", " coef_subsequent_2plus_school_tours_duration\n", - " -0.188299\n", + " -0.309377\n", + " -0.309377\n", " -0.233800\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.188299\n", " \n", " \n", " coef_subsequent_of_2plus_school_lt_6_hours\n", - " 25.000000\n", + " 1.522961\n", + " 1.522961\n", " 2.142000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 25.000000\n", " \n", " \n", " coef_subsequent_tour_must_start_after_previous_tour_ends\n", " -100.000000\n", " -100.000000\n", + " -100.000000\n", + " -100.0\n", + " -100.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " -100.000000\n", " \n", " \n", " coef_univ_departure\n", - " 0.234367\n", + " 0.281763\n", + " 0.281763\n", " 0.280000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.234367\n", " \n", " \n", " coef_univ_duration\n", - " -0.409132\n", + " -0.287541\n", + " -0.287541\n", " -0.290700\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.409132\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_adjacent_window_exists_after_this_arrival_... -0.414229 -0.003049 \n", - "coef_adjacent_window_exists_after_this_arrival_... -0.640186 -0.527100 \n", - "coef_adjacent_window_exists_before_this_departu... 1.656920 0.089750 \n", - "coef_adjacent_window_exists_before_this_departu... 0.225722 -0.440000 \n", - "coef_all_adults_ft_worker_duration 0.052336 0.109300 \n", - "coef_arrival_constants_am_peak -2.239162 -2.428718 \n", - "coef_arrival_constants_early -1.065980 -2.428718 \n", - "coef_arrival_constants_evening -1.033329 -0.870147 \n", - "coef_arrival_constants_late -1.315910 -1.752000 \n", - "coef_arrival_constants_midday_1 -1.302330 -1.237909 \n", - "coef_arrival_constants_midday_2 -0.554673 -0.539769 \n", + " value best \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 0.232285 0.232285 \n", + "coef_adjacent_window_exists_after_this_arrival_... -1.201676 -1.201676 \n", + "coef_adjacent_window_exists_before_this_departu... -0.419250 -0.419250 \n", + "coef_adjacent_window_exists_before_this_departu... -0.760747 -0.760747 \n", + "coef_all_adults_ft_worker_duration 0.079713 0.079713 \n", + "coef_arrival_constants_am_peak -2.595385 -2.595385 \n", + "coef_arrival_constants_early -2.446580 -2.446580 \n", + "coef_arrival_constants_evening -0.707272 -0.707272 \n", + "coef_arrival_constants_late -1.639520 -1.639520 \n", + "coef_arrival_constants_midday_1 -1.267988 -1.267988 \n", + "coef_arrival_constants_midday_2 -0.523484 -0.523484 \n", "coef_arrival_constants_pm_peak_1 0.000000 0.000000 \n", - "coef_arrival_constants_pm_peak_2 -0.441387 -0.389169 \n", - "coef_arrival_constants_pm_peak_3 -0.281247 -0.198120 \n", - "coef_arrival_constants_pm_peak_4 -0.370368 -0.253625 \n", - "coef_departure_constants_am_peak_1 -1.882694 -1.617644 \n", + "coef_arrival_constants_pm_peak_2 -0.360268 -0.360268 \n", + "coef_arrival_constants_pm_peak_3 -0.096426 -0.096426 \n", + "coef_arrival_constants_pm_peak_4 -0.127905 -0.127905 \n", + "coef_departure_constants_am_peak_1 -1.606835 -1.606835 \n", "coef_departure_constants_am_peak_2 0.000000 0.000000 \n", - "coef_departure_constants_am_peak_3 -0.183985 -0.073827 \n", - "coef_departure_constants_am_peak_4 -2.016403 -2.080571 \n", - "coef_departure_constants_early -3.636770 -3.820662 \n", - "coef_departure_constants_evening -5.258795 -5.230288 \n", - "coef_departure_constants_late -21.447622 -11.886047 \n", - "coef_departure_constants_midday_1 -3.279864 -2.985739 \n", - "coef_departure_constants_midday_2 -3.750548 -3.628435 \n", - "coef_departure_constants_pm_peak -3.093167 -3.102505 \n", - "coef_duration_constants_0_to_2_hours -1.372110 -1.409956 \n", - "coef_duration_constants_10_hours -0.876448 -0.904789 \n", - "coef_duration_constants_11_hours -1.127264 -1.521163 \n", - "coef_duration_constants_12_to_13_hours -2.668346 -2.418489 \n", - "coef_duration_constants_14_to_18_hours -2.675974 -2.503137 \n", - "coef_duration_constants_3_to_4_hours -0.552200 -0.745893 \n", - "coef_duration_constants_5_to_6_hours -0.532627 -0.567637 \n", + "coef_departure_constants_am_peak_3 -0.100582 -0.100582 \n", + "coef_departure_constants_am_peak_4 -2.142432 -2.142432 \n", + "coef_departure_constants_early -3.850945 -3.850945 \n", + "coef_departure_constants_evening -5.546826 -5.546826 \n", + "coef_departure_constants_late -10.890722 -10.890722 \n", + "coef_departure_constants_midday_1 -3.124481 -3.124481 \n", + "coef_departure_constants_midday_2 -3.861525 -3.861525 \n", + "coef_departure_constants_pm_peak -3.281532 -3.281532 \n", + "coef_duration_constants_0_to_2_hours -1.318085 -1.318085 \n", + "coef_duration_constants_10_hours -0.914359 -0.914359 \n", + "coef_duration_constants_11_hours -1.643692 -1.643692 \n", + "coef_duration_constants_12_to_13_hours -2.528269 -2.528269 \n", + "coef_duration_constants_14_to_18_hours -2.541672 -2.541672 \n", + "coef_duration_constants_3_to_4_hours -0.680239 -0.680239 \n", + "coef_duration_constants_5_to_6_hours -0.551126 -0.551126 \n", "coef_duration_constants_7_to_8_hours 0.000000 0.000000 \n", - "coef_duration_constants_9_hours -0.487609 -0.650807 \n", - "coef_first_of_2plus_school_lt_6_hours 0.169055 1.487000 \n", - "coef_first_of_2plus_school_tours_departure -0.333830 -0.300200 \n", - "coef_first_of_2plus_school_tours_duration -0.042558 -0.159300 \n", + "coef_duration_constants_9_hours -0.664353 -0.664353 \n", + "coef_first_of_2plus_school_lt_6_hours 1.768123 1.768123 \n", + "coef_first_of_2plus_school_tours_departure -0.277161 -0.277161 \n", + "coef_first_of_2plus_school_tours_duration -0.077846 -0.077846 \n", "coef_ft_worker_departure 0.397100 0.397100 \n", "coef_ft_worker_duration -0.190800 -0.190800 \n", - "coef_hh_income_early_departure -13.757852 -0.883700 \n", - "coef_hh_income_late_arrival 0.101726 -0.353300 \n", - "coef_mode_choice_logsum 0.056410 2.127000 \n", + "coef_hh_income_early_departure -0.643531 -0.643531 \n", + "coef_hh_income_late_arrival -0.123912 -0.123912 \n", + "coef_mode_choice_logsum 1.403530 1.403530 \n", "coef_non_worker_departure 0.553900 0.553900 \n", - "coef_previous_tour_begins_this_arrival_hour -10.370632 -1.102000 \n", - "coef_previous_tour_ends_this_departure_hour 0.298551 -0.599500 \n", - "coef_remaining_work_school_tours_to_be_schedule... -25.000000 -16.670000 \n", - "coef_roundtrip_auto_time_to_work 0.005137 0.003195 \n", - "coef_school_plus_work_tours_by_student_lt_6_hours -2.483313 1.730000 \n", - "coef_school_plus_work_tours_by_worker_lt_6_hours -2.071313 2.142000 \n", - "coef_student_driver_duration -0.003958 0.034640 \n", - "coef_subsequent_2plus_school_tours_duration -0.188299 -0.233800 \n", - "coef_subsequent_of_2plus_school_lt_6_hours 25.000000 2.142000 \n", + "coef_previous_tour_begins_this_arrival_hour 1.748525 1.748525 \n", + "coef_previous_tour_ends_this_departure_hour -1.454921 -1.454921 \n", + "coef_remaining_work_school_tours_to_be_schedule... -16.666935 -16.666935 \n", + "coef_roundtrip_auto_time_to_work 0.002946 0.002946 \n", + "coef_school_plus_work_tours_by_student_lt_6_hours 1.805060 1.805060 \n", + "coef_school_plus_work_tours_by_worker_lt_6_hours 2.217060 2.217060 \n", + "coef_student_driver_duration 0.021414 0.021414 \n", + "coef_subsequent_2plus_school_tours_duration -0.309377 -0.309377 \n", + "coef_subsequent_of_2plus_school_lt_6_hours 1.522961 1.522961 \n", "coef_subsequent_tour_must_start_after_previous_... -100.000000 -100.000000 \n", - "coef_univ_departure 0.234367 0.280000 \n", - "coef_univ_duration -0.409132 -0.290700 \n", + "coef_univ_departure 0.281763 0.281763 \n", + "coef_univ_duration -0.287541 -0.287541 \n", "\n", - " nullvalue minimum \\\n", - "coef_adjacent_window_exists_after_this_arrival_... 0.0 -25.0 \n", - "coef_adjacent_window_exists_after_this_arrival_... 0.0 -25.0 \n", - "coef_adjacent_window_exists_before_this_departu... 0.0 -25.0 \n", - "coef_adjacent_window_exists_before_this_departu... 0.0 -25.0 \n", - "coef_all_adults_ft_worker_duration 0.0 -25.0 \n", - "coef_arrival_constants_am_peak 0.0 -25.0 \n", - "coef_arrival_constants_early 0.0 -25.0 \n", - "coef_arrival_constants_evening 0.0 -25.0 \n", - "coef_arrival_constants_late 0.0 -25.0 \n", - "coef_arrival_constants_midday_1 0.0 -25.0 \n", - "coef_arrival_constants_midday_2 0.0 -25.0 \n", - "coef_arrival_constants_pm_peak_1 0.0 -25.0 \n", - "coef_arrival_constants_pm_peak_2 0.0 -25.0 \n", - "coef_arrival_constants_pm_peak_3 0.0 -25.0 \n", - "coef_arrival_constants_pm_peak_4 0.0 -25.0 \n", - "coef_departure_constants_am_peak_1 0.0 -25.0 \n", - "coef_departure_constants_am_peak_2 0.0 -25.0 \n", - "coef_departure_constants_am_peak_3 0.0 -25.0 \n", - "coef_departure_constants_am_peak_4 0.0 -25.0 \n", - "coef_departure_constants_early 0.0 -25.0 \n", - "coef_departure_constants_evening 0.0 -25.0 \n", - "coef_departure_constants_late 0.0 -25.0 \n", - "coef_departure_constants_midday_1 0.0 -25.0 \n", - "coef_departure_constants_midday_2 0.0 -25.0 \n", - "coef_departure_constants_pm_peak 0.0 -25.0 \n", - "coef_duration_constants_0_to_2_hours 0.0 -25.0 \n", - "coef_duration_constants_10_hours 0.0 -25.0 \n", - "coef_duration_constants_11_hours 0.0 -25.0 \n", - "coef_duration_constants_12_to_13_hours 0.0 -25.0 \n", - "coef_duration_constants_14_to_18_hours 0.0 -25.0 \n", - "coef_duration_constants_3_to_4_hours 0.0 -25.0 \n", - "coef_duration_constants_5_to_6_hours 0.0 -25.0 \n", - "coef_duration_constants_7_to_8_hours 0.0 -25.0 \n", - "coef_duration_constants_9_hours 0.0 -25.0 \n", - "coef_first_of_2plus_school_lt_6_hours 0.0 -25.0 \n", - "coef_first_of_2plus_school_tours_departure 0.0 -25.0 \n", - "coef_first_of_2plus_school_tours_duration 0.0 -25.0 \n", - "coef_ft_worker_departure 0.0 -25.0 \n", - "coef_ft_worker_duration 0.0 -25.0 \n", - "coef_hh_income_early_departure 0.0 -25.0 \n", - "coef_hh_income_late_arrival 0.0 -25.0 \n", - "coef_mode_choice_logsum 0.0 -25.0 \n", - "coef_non_worker_departure 0.0 -25.0 \n", - "coef_previous_tour_begins_this_arrival_hour 0.0 -25.0 \n", - "coef_previous_tour_ends_this_departure_hour 0.0 -25.0 \n", - "coef_remaining_work_school_tours_to_be_schedule... 0.0 -25.0 \n", - "coef_roundtrip_auto_time_to_work 0.0 -25.0 \n", - "coef_school_plus_work_tours_by_student_lt_6_hours 0.0 -25.0 \n", - "coef_school_plus_work_tours_by_worker_lt_6_hours 0.0 -25.0 \n", - "coef_student_driver_duration 0.0 -25.0 \n", - "coef_subsequent_2plus_school_tours_duration 0.0 -25.0 \n", - "coef_subsequent_of_2plus_school_lt_6_hours 0.0 -25.0 \n", - "coef_subsequent_tour_must_start_after_previous_... 0.0 -25.0 \n", - "coef_univ_departure 0.0 -25.0 \n", - "coef_univ_duration 0.0 -25.0 \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... -0.003049 -25.0 \n", + "coef_adjacent_window_exists_after_this_arrival_... -0.527100 -25.0 \n", + "coef_adjacent_window_exists_before_this_departu... 0.089750 -25.0 \n", + "coef_adjacent_window_exists_before_this_departu... -0.440000 -25.0 \n", + "coef_all_adults_ft_worker_duration 0.109300 -25.0 \n", + "coef_arrival_constants_am_peak -2.428718 -25.0 \n", + "coef_arrival_constants_early -2.428718 -25.0 \n", + "coef_arrival_constants_evening -0.870147 -25.0 \n", + "coef_arrival_constants_late -1.752000 -25.0 \n", + "coef_arrival_constants_midday_1 -1.237909 -25.0 \n", + "coef_arrival_constants_midday_2 -0.539769 -25.0 \n", + "coef_arrival_constants_pm_peak_1 0.000000 0.0 \n", + "coef_arrival_constants_pm_peak_2 -0.389169 -25.0 \n", + "coef_arrival_constants_pm_peak_3 -0.198120 -25.0 \n", + "coef_arrival_constants_pm_peak_4 -0.253625 -25.0 \n", + "coef_departure_constants_am_peak_1 -1.617644 -25.0 \n", + "coef_departure_constants_am_peak_2 0.000000 0.0 \n", + "coef_departure_constants_am_peak_3 -0.073827 -25.0 \n", + "coef_departure_constants_am_peak_4 -2.080571 -25.0 \n", + "coef_departure_constants_early -3.820662 -25.0 \n", + "coef_departure_constants_evening -5.230288 -25.0 \n", + "coef_departure_constants_late -11.886047 -25.0 \n", + "coef_departure_constants_midday_1 -2.985739 -25.0 \n", + "coef_departure_constants_midday_2 -3.628435 -25.0 \n", + "coef_departure_constants_pm_peak -3.102505 -25.0 \n", + "coef_duration_constants_0_to_2_hours -1.409956 -25.0 \n", + "coef_duration_constants_10_hours -0.904789 -25.0 \n", + "coef_duration_constants_11_hours -1.521163 -25.0 \n", + "coef_duration_constants_12_to_13_hours -2.418489 -25.0 \n", + "coef_duration_constants_14_to_18_hours -2.503137 -25.0 \n", + "coef_duration_constants_3_to_4_hours -0.745893 -25.0 \n", + "coef_duration_constants_5_to_6_hours -0.567637 -25.0 \n", + "coef_duration_constants_7_to_8_hours 0.000000 0.0 \n", + "coef_duration_constants_9_hours -0.650807 -25.0 \n", + "coef_first_of_2plus_school_lt_6_hours 1.487000 -25.0 \n", + "coef_first_of_2plus_school_tours_departure -0.300200 -25.0 \n", + "coef_first_of_2plus_school_tours_duration -0.159300 -25.0 \n", + "coef_ft_worker_departure 0.397100 -25.0 \n", + "coef_ft_worker_duration -0.190800 -25.0 \n", + "coef_hh_income_early_departure -0.883700 -25.0 \n", + "coef_hh_income_late_arrival -0.353300 -25.0 \n", + "coef_mode_choice_logsum 2.127000 -25.0 \n", + "coef_non_worker_departure 0.553900 -25.0 \n", + "coef_previous_tour_begins_this_arrival_hour -1.102000 -25.0 \n", + "coef_previous_tour_ends_this_departure_hour -0.599500 -25.0 \n", + "coef_remaining_work_school_tours_to_be_schedule... -16.670000 -25.0 \n", + "coef_roundtrip_auto_time_to_work 0.003195 -25.0 \n", + "coef_school_plus_work_tours_by_student_lt_6_hours 1.730000 -25.0 \n", + "coef_school_plus_work_tours_by_worker_lt_6_hours 2.142000 -25.0 \n", + "coef_student_driver_duration 0.034640 -25.0 \n", + "coef_subsequent_2plus_school_tours_duration -0.233800 -25.0 \n", + "coef_subsequent_of_2plus_school_lt_6_hours 2.142000 -25.0 \n", + "coef_subsequent_tour_must_start_after_previous_... -100.000000 -100.0 \n", + "coef_univ_departure 0.280000 -25.0 \n", + "coef_univ_duration -0.290700 -25.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_adjacent_window_exists_after_this_arrival_... 25.0 0 \n", - "coef_adjacent_window_exists_after_this_arrival_... 25.0 0 \n", - "coef_adjacent_window_exists_before_this_departu... 25.0 0 \n", - "coef_adjacent_window_exists_before_this_departu... 25.0 0 \n", - "coef_all_adults_ft_worker_duration 25.0 0 \n", - "coef_arrival_constants_am_peak 25.0 0 \n", - "coef_arrival_constants_early 25.0 0 \n", - "coef_arrival_constants_evening 25.0 0 \n", - "coef_arrival_constants_late 25.0 0 \n", - "coef_arrival_constants_midday_1 25.0 0 \n", - "coef_arrival_constants_midday_2 25.0 0 \n", - "coef_arrival_constants_pm_peak_1 25.0 1 \n", - "coef_arrival_constants_pm_peak_2 25.0 0 \n", - "coef_arrival_constants_pm_peak_3 25.0 0 \n", - "coef_arrival_constants_pm_peak_4 25.0 0 \n", - "coef_departure_constants_am_peak_1 25.0 0 \n", - "coef_departure_constants_am_peak_2 25.0 1 \n", - "coef_departure_constants_am_peak_3 25.0 0 \n", - "coef_departure_constants_am_peak_4 25.0 0 \n", - "coef_departure_constants_early 25.0 0 \n", - "coef_departure_constants_evening 25.0 0 \n", - "coef_departure_constants_late 25.0 0 \n", - "coef_departure_constants_midday_1 25.0 0 \n", - "coef_departure_constants_midday_2 25.0 0 \n", - "coef_departure_constants_pm_peak 25.0 0 \n", - "coef_duration_constants_0_to_2_hours 25.0 0 \n", - "coef_duration_constants_10_hours 25.0 0 \n", - "coef_duration_constants_11_hours 25.0 0 \n", - "coef_duration_constants_12_to_13_hours 25.0 0 \n", - "coef_duration_constants_14_to_18_hours 25.0 0 \n", - "coef_duration_constants_3_to_4_hours 25.0 0 \n", - "coef_duration_constants_5_to_6_hours 25.0 0 \n", - "coef_duration_constants_7_to_8_hours 25.0 1 \n", - "coef_duration_constants_9_hours 25.0 0 \n", - "coef_first_of_2plus_school_lt_6_hours 25.0 0 \n", - "coef_first_of_2plus_school_tours_departure 25.0 0 \n", - "coef_first_of_2plus_school_tours_duration 25.0 0 \n", - "coef_ft_worker_departure 25.0 0 \n", - "coef_ft_worker_duration 25.0 0 \n", - "coef_hh_income_early_departure 25.0 0 \n", - "coef_hh_income_late_arrival 25.0 0 \n", - "coef_mode_choice_logsum 25.0 0 \n", - "coef_non_worker_departure 25.0 0 \n", - "coef_previous_tour_begins_this_arrival_hour 25.0 0 \n", - "coef_previous_tour_ends_this_departure_hour 25.0 0 \n", - "coef_remaining_work_school_tours_to_be_schedule... 25.0 0 \n", - "coef_roundtrip_auto_time_to_work 25.0 0 \n", - "coef_school_plus_work_tours_by_student_lt_6_hours 25.0 0 \n", - "coef_school_plus_work_tours_by_worker_lt_6_hours 25.0 0 \n", - "coef_student_driver_duration 25.0 0 \n", - "coef_subsequent_2plus_school_tours_duration 25.0 0 \n", - "coef_subsequent_of_2plus_school_lt_6_hours 25.0 0 \n", - "coef_subsequent_tour_must_start_after_previous_... 25.0 1 \n", - "coef_univ_departure 25.0 0 \n", - "coef_univ_duration 25.0 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 25.0 0.0 \n", + "coef_adjacent_window_exists_after_this_arrival_... 25.0 0.0 \n", + "coef_adjacent_window_exists_before_this_departu... 25.0 0.0 \n", + "coef_adjacent_window_exists_before_this_departu... 25.0 0.0 \n", + "coef_all_adults_ft_worker_duration 25.0 0.0 \n", + "coef_arrival_constants_am_peak 25.0 0.0 \n", + "coef_arrival_constants_early 25.0 0.0 \n", + "coef_arrival_constants_evening 25.0 0.0 \n", + "coef_arrival_constants_late 25.0 0.0 \n", + "coef_arrival_constants_midday_1 25.0 0.0 \n", + "coef_arrival_constants_midday_2 25.0 0.0 \n", + "coef_arrival_constants_pm_peak_1 0.0 0.0 \n", + "coef_arrival_constants_pm_peak_2 25.0 0.0 \n", + "coef_arrival_constants_pm_peak_3 25.0 0.0 \n", + "coef_arrival_constants_pm_peak_4 25.0 0.0 \n", + "coef_departure_constants_am_peak_1 25.0 0.0 \n", + "coef_departure_constants_am_peak_2 0.0 0.0 \n", + "coef_departure_constants_am_peak_3 25.0 0.0 \n", + "coef_departure_constants_am_peak_4 25.0 0.0 \n", + "coef_departure_constants_early 25.0 0.0 \n", + "coef_departure_constants_evening 25.0 0.0 \n", + "coef_departure_constants_late 25.0 0.0 \n", + "coef_departure_constants_midday_1 25.0 0.0 \n", + "coef_departure_constants_midday_2 25.0 0.0 \n", + "coef_departure_constants_pm_peak 25.0 0.0 \n", + "coef_duration_constants_0_to_2_hours 25.0 0.0 \n", + "coef_duration_constants_10_hours 25.0 0.0 \n", + "coef_duration_constants_11_hours 25.0 0.0 \n", + "coef_duration_constants_12_to_13_hours 25.0 0.0 \n", + "coef_duration_constants_14_to_18_hours 25.0 0.0 \n", + "coef_duration_constants_3_to_4_hours 25.0 0.0 \n", + "coef_duration_constants_5_to_6_hours 25.0 0.0 \n", + "coef_duration_constants_7_to_8_hours 0.0 0.0 \n", + "coef_duration_constants_9_hours 25.0 0.0 \n", + "coef_first_of_2plus_school_lt_6_hours 25.0 0.0 \n", + "coef_first_of_2plus_school_tours_departure 25.0 0.0 \n", + "coef_first_of_2plus_school_tours_duration 25.0 0.0 \n", + "coef_ft_worker_departure 25.0 0.0 \n", + "coef_ft_worker_duration 25.0 0.0 \n", + "coef_hh_income_early_departure 25.0 0.0 \n", + "coef_hh_income_late_arrival 25.0 0.0 \n", + "coef_mode_choice_logsum 25.0 0.0 \n", + "coef_non_worker_departure 25.0 0.0 \n", + "coef_previous_tour_begins_this_arrival_hour 25.0 0.0 \n", + "coef_previous_tour_ends_this_departure_hour 25.0 0.0 \n", + "coef_remaining_work_school_tours_to_be_schedule... 25.0 0.0 \n", + "coef_roundtrip_auto_time_to_work 25.0 0.0 \n", + "coef_school_plus_work_tours_by_student_lt_6_hours 25.0 0.0 \n", + "coef_school_plus_work_tours_by_worker_lt_6_hours 25.0 0.0 \n", + "coef_student_driver_duration 25.0 0.0 \n", + "coef_subsequent_2plus_school_tours_duration 25.0 0.0 \n", + "coef_subsequent_of_2plus_school_lt_6_hours 25.0 0.0 \n", + "coef_subsequent_tour_must_start_after_previous_... -100.0 0.0 \n", + "coef_univ_departure 25.0 0.0 \n", + "coef_univ_duration 25.0 0.0 \n", "\n", - " best \n", - "coef_adjacent_window_exists_after_this_arrival_... -0.414229 \n", - "coef_adjacent_window_exists_after_this_arrival_... -0.640186 \n", - "coef_adjacent_window_exists_before_this_departu... 1.656920 \n", - "coef_adjacent_window_exists_before_this_departu... 0.225722 \n", - "coef_all_adults_ft_worker_duration 0.052336 \n", - "coef_arrival_constants_am_peak -2.239162 \n", - "coef_arrival_constants_early -1.065980 \n", - "coef_arrival_constants_evening -1.033329 \n", - "coef_arrival_constants_late -1.315910 \n", - "coef_arrival_constants_midday_1 -1.302330 \n", - "coef_arrival_constants_midday_2 -0.554673 \n", - "coef_arrival_constants_pm_peak_1 0.000000 \n", - "coef_arrival_constants_pm_peak_2 -0.441387 \n", - "coef_arrival_constants_pm_peak_3 -0.281247 \n", - "coef_arrival_constants_pm_peak_4 -0.370368 \n", - "coef_departure_constants_am_peak_1 -1.882694 \n", - "coef_departure_constants_am_peak_2 0.000000 \n", - "coef_departure_constants_am_peak_3 -0.183985 \n", - "coef_departure_constants_am_peak_4 -2.016403 \n", - "coef_departure_constants_early -3.636770 \n", - "coef_departure_constants_evening -5.258795 \n", - "coef_departure_constants_late -21.447622 \n", - "coef_departure_constants_midday_1 -3.279864 \n", - "coef_departure_constants_midday_2 -3.750548 \n", - "coef_departure_constants_pm_peak -3.093167 \n", - "coef_duration_constants_0_to_2_hours -1.372110 \n", - "coef_duration_constants_10_hours -0.876448 \n", - "coef_duration_constants_11_hours -1.127264 \n", - "coef_duration_constants_12_to_13_hours -2.668346 \n", - "coef_duration_constants_14_to_18_hours -2.675974 \n", - "coef_duration_constants_3_to_4_hours -0.552200 \n", - "coef_duration_constants_5_to_6_hours -0.532627 \n", - "coef_duration_constants_7_to_8_hours 0.000000 \n", - "coef_duration_constants_9_hours -0.487609 \n", - "coef_first_of_2plus_school_lt_6_hours 0.169055 \n", - "coef_first_of_2plus_school_tours_departure -0.333830 \n", - "coef_first_of_2plus_school_tours_duration -0.042558 \n", - "coef_ft_worker_departure 0.397100 \n", - "coef_ft_worker_duration -0.190800 \n", - "coef_hh_income_early_departure -13.757852 \n", - "coef_hh_income_late_arrival 0.101726 \n", - "coef_mode_choice_logsum 0.056410 \n", - "coef_non_worker_departure 0.553900 \n", - "coef_previous_tour_begins_this_arrival_hour -10.370632 \n", - "coef_previous_tour_ends_this_departure_hour 0.298551 \n", - "coef_remaining_work_school_tours_to_be_schedule... -25.000000 \n", - "coef_roundtrip_auto_time_to_work 0.005137 \n", - "coef_school_plus_work_tours_by_student_lt_6_hours -2.483313 \n", - "coef_school_plus_work_tours_by_worker_lt_6_hours -2.071313 \n", - "coef_student_driver_duration -0.003958 \n", - "coef_subsequent_2plus_school_tours_duration -0.188299 \n", - "coef_subsequent_of_2plus_school_lt_6_hours 25.000000 \n", - "coef_subsequent_tour_must_start_after_previous_... -100.000000 \n", - "coef_univ_departure 0.234367 \n", - "coef_univ_duration -0.409132 " + " holdfast \n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 0 \n", + "coef_adjacent_window_exists_after_this_arrival_... 0 \n", + "coef_adjacent_window_exists_before_this_departu... 0 \n", + "coef_adjacent_window_exists_before_this_departu... 0 \n", + "coef_all_adults_ft_worker_duration 0 \n", + "coef_arrival_constants_am_peak 0 \n", + "coef_arrival_constants_early 0 \n", + "coef_arrival_constants_evening 0 \n", + "coef_arrival_constants_late 0 \n", + "coef_arrival_constants_midday_1 0 \n", + "coef_arrival_constants_midday_2 0 \n", + "coef_arrival_constants_pm_peak_1 1 \n", + "coef_arrival_constants_pm_peak_2 0 \n", + "coef_arrival_constants_pm_peak_3 0 \n", + "coef_arrival_constants_pm_peak_4 0 \n", + "coef_departure_constants_am_peak_1 0 \n", + "coef_departure_constants_am_peak_2 1 \n", + "coef_departure_constants_am_peak_3 0 \n", + "coef_departure_constants_am_peak_4 0 \n", + "coef_departure_constants_early 0 \n", + "coef_departure_constants_evening 0 \n", + "coef_departure_constants_late 0 \n", + "coef_departure_constants_midday_1 0 \n", + "coef_departure_constants_midday_2 0 \n", + "coef_departure_constants_pm_peak 0 \n", + "coef_duration_constants_0_to_2_hours 0 \n", + "coef_duration_constants_10_hours 0 \n", + "coef_duration_constants_11_hours 0 \n", + "coef_duration_constants_12_to_13_hours 0 \n", + "coef_duration_constants_14_to_18_hours 0 \n", + "coef_duration_constants_3_to_4_hours 0 \n", + "coef_duration_constants_5_to_6_hours 0 \n", + "coef_duration_constants_7_to_8_hours 1 \n", + "coef_duration_constants_9_hours 0 \n", + "coef_first_of_2plus_school_lt_6_hours 0 \n", + "coef_first_of_2plus_school_tours_departure 0 \n", + "coef_first_of_2plus_school_tours_duration 0 \n", + "coef_ft_worker_departure 0 \n", + "coef_ft_worker_duration 0 \n", + "coef_hh_income_early_departure 0 \n", + "coef_hh_income_late_arrival 0 \n", + "coef_mode_choice_logsum 0 \n", + "coef_non_worker_departure 0 \n", + "coef_previous_tour_begins_this_arrival_hour 0 \n", + "coef_previous_tour_ends_this_departure_hour 0 \n", + "coef_remaining_work_school_tours_to_be_schedule... 0 \n", + "coef_roundtrip_auto_time_to_work 0 \n", + "coef_school_plus_work_tours_by_student_lt_6_hours 0 \n", + "coef_school_plus_work_tours_by_worker_lt_6_hours 0 \n", + "coef_student_driver_duration 0 \n", + "coef_subsequent_2plus_school_tours_duration 0 \n", + "coef_subsequent_of_2plus_school_lt_6_hours 0 \n", + "coef_subsequent_tour_must_start_after_previous_... 1 \n", + "coef_univ_departure 0 \n", + "coef_univ_duration 0 " ] }, "metadata": {}, @@ -2907,10 +3061,8 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate()\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.3990405079720497e-24 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { @@ -2926,47 +3078,47 @@ " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction\n", - " -0.414229\n", + " 0.232285\n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction\n", - " -0.640186\n", + " -1.201676\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction\n", - " 1.656920\n", + " -0.419250\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction\n", - " 0.225722\n", + " -0.760747\n", " \n", " \n", " coef_all_adults_ft_worker_duration\n", - " 0.052336\n", + " 0.079713\n", " \n", " \n", " coef_arrival_constants_am_peak\n", - " -2.239162\n", + " -2.595385\n", " \n", " \n", " coef_arrival_constants_early\n", - " -1.065980\n", + " -2.446580\n", " \n", " \n", " coef_arrival_constants_evening\n", - " -1.033329\n", + " -0.707272\n", " \n", " \n", " coef_arrival_constants_late\n", - " -1.315910\n", + " -1.639520\n", " \n", " \n", " coef_arrival_constants_midday_1\n", - " -1.302330\n", + " -1.267988\n", " \n", " \n", " coef_arrival_constants_midday_2\n", - " -0.554673\n", + " -0.523484\n", " \n", " \n", " coef_arrival_constants_pm_peak_1\n", @@ -2974,19 +3126,19 @@ " \n", " \n", " coef_arrival_constants_pm_peak_2\n", - " -0.441387\n", + " -0.360268\n", " \n", " \n", " coef_arrival_constants_pm_peak_3\n", - " -0.281247\n", + " -0.096426\n", " \n", " \n", " coef_arrival_constants_pm_peak_4\n", - " -0.370368\n", + " -0.127905\n", " \n", " \n", " coef_departure_constants_am_peak_1\n", - " -1.882694\n", + " -1.606835\n", " \n", " \n", " coef_departure_constants_am_peak_2\n", @@ -2994,63 +3146,63 @@ " \n", " \n", " coef_departure_constants_am_peak_3\n", - " -0.183985\n", + " -0.100582\n", " \n", " \n", " coef_departure_constants_am_peak_4\n", - " -2.016403\n", + " -2.142432\n", " \n", " \n", " coef_departure_constants_early\n", - " -3.636770\n", + " -3.850945\n", " \n", " \n", " coef_departure_constants_evening\n", - " -5.258795\n", + " -5.546826\n", " \n", " \n", " coef_departure_constants_late\n", - " -21.447622\n", + " -10.890722\n", " \n", " \n", " coef_departure_constants_midday_1\n", - " -3.279864\n", + " -3.124481\n", " \n", " \n", " coef_departure_constants_midday_2\n", - " -3.750548\n", + " -3.861525\n", " \n", " \n", " coef_departure_constants_pm_peak\n", - " -3.093167\n", + " -3.281532\n", " \n", " \n", " coef_duration_constants_0_to_2_hours\n", - " -1.372110\n", + " -1.318085\n", " \n", " \n", " coef_duration_constants_10_hours\n", - " -0.876448\n", + " -0.914359\n", " \n", " \n", " coef_duration_constants_11_hours\n", - " -1.127264\n", + " -1.643692\n", " \n", " \n", " coef_duration_constants_12_to_13_hours\n", - " -2.668346\n", + " -2.528269\n", " \n", " \n", " coef_duration_constants_14_to_18_hours\n", - " -2.675974\n", + " -2.541672\n", " \n", " \n", " coef_duration_constants_3_to_4_hours\n", - " -0.552200\n", + " -0.680239\n", " \n", " \n", " coef_duration_constants_5_to_6_hours\n", - " -0.532627\n", + " -0.551126\n", " \n", " \n", " coef_duration_constants_7_to_8_hours\n", @@ -3058,19 +3210,19 @@ " \n", " \n", " coef_duration_constants_9_hours\n", - " -0.487609\n", + " -0.664353\n", " \n", " \n", " coef_first_of_2plus_school_lt_6_hours\n", - " 0.169055\n", + " 1.768123\n", " \n", " \n", " coef_first_of_2plus_school_tours_departure\n", - " -0.333830\n", + " -0.277161\n", " \n", " \n", " coef_first_of_2plus_school_tours_duration\n", - " -0.042558\n", + " -0.077846\n", " \n", " \n", " coef_ft_worker_departure\n", @@ -3082,15 +3234,15 @@ " \n", " \n", " coef_hh_income_early_departure\n", - " -13.757852\n", + " -0.643531\n", " \n", " \n", " coef_hh_income_late_arrival\n", - " 0.101726\n", + " -0.123912\n", " \n", " \n", " coef_mode_choice_logsum\n", - " 0.056410\n", + " 1.403530\n", " \n", " \n", " coef_non_worker_departure\n", @@ -3098,54 +3250,54 @@ " \n", " \n", " coef_previous_tour_begins_this_arrival_hour\n", - " -10.370632\n", + " 1.748525\n", " \n", " \n", " coef_previous_tour_ends_this_departure_hour\n", - " 0.298551\n", + " -1.454921\n", " \n", " \n", " coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours\n", - " -25.000000\n", + " -16.666935\n", " \n", " \n", " coef_roundtrip_auto_time_to_work\n", - " 0.005137\n", + " 0.002946\n", " \n", " \n", " coef_school_plus_work_tours_by_student_lt_6_hours\n", - " -2.483313\n", + " 1.805060\n", " \n", " \n", " coef_school_plus_work_tours_by_worker_lt_6_hours\n", - " -2.071313\n", + " 2.217060\n", " \n", " \n", " coef_student_driver_duration\n", - " -0.003958\n", + " 0.021414\n", " \n", " \n", " coef_subsequent_2plus_school_tours_duration\n", - " -0.188299\n", + " -0.309377\n", " \n", " \n", " coef_subsequent_of_2plus_school_lt_6_hours\n", - " 25.000000\n", + " 1.522961\n", " \n", " \n", " coef_subsequent_tour_must_start_after_previous_tour_ends\n", - " -25.000000\n", + " -100.000000\n", " \n", " \n", " coef_univ_departure\n", - " 0.234367\n", + " 0.281763\n", " \n", " \n", " coef_univ_duration\n", - " -0.409132\n", + " -0.287541\n", " \n", " \n", - "loglike-2331.7420221780226d_loglike\n", + "
logloss3.8441737168559693d_logloss\n", " \n", " \n", " \n", @@ -3155,47 +3307,47 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3203,19 +3355,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3223,63 +3375,63 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3287,19 +3439,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3311,15 +3463,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3327,39 +3479,39 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3367,149 +3519,149 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - "
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction-1.569000e-041.678936e-05
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction2.469873e-05-4.551660e-05
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction-1.376329e-041.846962e-05
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction-1.199309e-04-1.145647e-04
coef_all_adults_ft_worker_duration-2.382589e-04-8.371558e-05
coef_arrival_constants_am_peak1.105861e-042.196925e-04
coef_arrival_constants_early-7.161434e-05-5.719292e-06
coef_arrival_constants_evening-3.213301e-04-8.835678e-05
coef_arrival_constants_late-3.685726e-051.013090e-04
coef_arrival_constants_midday_12.405910e-047.833025e-05
coef_arrival_constants_midday_23.974766e-04-1.965074e-04
coef_arrival_constants_pm_peak_1
coef_arrival_constants_pm_peak_2-3.784033e-04-9.685367e-05
coef_arrival_constants_pm_peak_3-2.802883e-04-9.087295e-05
coef_arrival_constants_pm_peak_41.590313e-042.740145e-05
coef_departure_constants_am_peak_13.893384e-051.513237e-04
coef_departure_constants_am_peak_2
coef_departure_constants_am_peak_3-1.076955e-04-8.937296e-06
coef_departure_constants_am_peak_4-1.023082e-04-8.822207e-05
coef_departure_constants_early-1.964617e-056.575707e-05
coef_departure_constants_evening9.016158e-05-4.373200e-05
coef_departure_constants_late-6.465407e-077.294452e-05
coef_departure_constants_midday_1-1.539484e-05-7.045255e-05
coef_departure_constants_midday_27.340411e-059.783210e-05
coef_departure_constants_pm_peak-3.023675e-041.854008e-04
coef_duration_constants_0_to_2_hours-1.095813e-04-1.017742e-05
coef_duration_constants_10_hours-4.107214e-05-1.010013e-04
coef_duration_constants_11_hours1.853670e-043.540305e-05
coef_duration_constants_12_to_13_hours4.561763e-053.622247e-06
coef_duration_constants_14_to_18_hours1.362278e-041.457916e-04
coef_duration_constants_3_to_4_hours3.779389e-06-1.500782e-04
coef_duration_constants_5_to_6_hours1.389604e-042.054373e-04
coef_duration_constants_7_to_8_hours
coef_duration_constants_9_hours-4.131255e-041.173908e-04
coef_first_of_2plus_school_lt_6_hours2.433801e-056.625071e-05
coef_first_of_2plus_school_tours_departure-1.088730e-044.904242e-05
coef_first_of_2plus_school_tours_duration-1.351925e-045.848347e-05
coef_ft_worker_departure
coef_hh_income_early_departure-1.184539e-06-5.079513e-05
coef_hh_income_late_arrival8.674395e-05-7.624692e-05
coef_mode_choice_logsum7.755139e-04-2.256830e-05
coef_non_worker_departure
coef_previous_tour_begins_this_arrival_hour-7.619359e-07-8.260618e-06
coef_previous_tour_ends_this_departure_hour-2.114195e-05-4.098700e-05
coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours-1.863986e-023.894311e-07
coef_roundtrip_auto_time_to_work-2.056667e-035.433902e-05
coef_school_plus_work_tours_by_student_lt_6_hours2.636310e-068.778429e-06
coef_school_plus_work_tours_by_worker_lt_6_hours2.636310e-068.778429e-06
coef_student_driver_duration4.065449e-04-5.008566e-05
coef_subsequent_2plus_school_tours_duration6.239050e-055.111004e-05
coef_subsequent_of_2plus_school_lt_6_hours2.696315e-069.902870e-05
coef_subsequent_tour_must_start_after_previous_tour_ends
coef_univ_departure-2.420842e-03-7.874285e-05
coef_univ_duration7.174716e-04-1.251813e-05
nit77nfev141njev77status0message'Optimization terminated successfully'successTrueelapsed_time0:00:02.917567method'slsqp'n_cases609iteration_number77logloss3.8288046341182636" + "nit139nfev142njev139status0message'Optimization terminated successfully'successTrueelapsed_time0:00:41.638335method'slsqp'n_cases10352iteration_number139loglike-39483.50824582766" ], "text/plain": [ - "┣ x: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction -0.414229\n", - "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction -0.640186\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 1.656920\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction 0.225722\n", - "┃ coef_all_adults_ft_worker_duration 0.052336\n", - "┃ coef_arrival_constants_am_peak -2.239162\n", - "┃ coef_arrival_constants_early -1.065980\n", - "┃ coef_arrival_constants_evening -1.033329\n", - "┃ coef_arrival_constants_late -1.315910\n", - "┃ coef_arrival_constants_midday_1 -1.302330\n", - "┃ coef_arrival_constants_midday_2 -0.554673\n", - "┃ coef_arrival_constants_pm_peak_1 0.000000\n", - "┃ coef_arrival_constants_pm_peak_2 -0.441387\n", - "┃ coef_arrival_constants_pm_peak_3 -0.281247\n", - "┃ coef_arrival_constants_pm_peak_4 -0.370368\n", - "┃ coef_departure_constants_am_peak_1 -1.882694\n", - "┃ coef_departure_constants_am_peak_2 0.000000\n", - "┃ coef_departure_constants_am_peak_3 -0.183985\n", - "┃ coef_departure_constants_am_peak_4 -2.016403\n", - "┃ coef_departure_constants_early -3.636770\n", - "┃ coef_departure_constants_evening -5.258795\n", - "┃ coef_departure_constants_late -21.447622\n", - "┃ coef_departure_constants_midday_1 -3.279864\n", - "┃ coef_departure_constants_midday_2 -3.750548\n", - "┃ coef_departure_constants_pm_peak -3.093167\n", - "┃ coef_duration_constants_0_to_2_hours -1.372110\n", - "┃ coef_duration_constants_10_hours -0.876448\n", - "┃ coef_duration_constants_11_hours -1.127264\n", - "┃ coef_duration_constants_12_to_13_hours -2.668346\n", - "┃ coef_duration_constants_14_to_18_hours -2.675974\n", - "┃ coef_duration_constants_3_to_4_hours -0.552200\n", - "┃ coef_duration_constants_5_to_6_hours -0.532627\n", - "┃ coef_duration_constants_7_to_8_hours 0.000000\n", - "┃ coef_duration_constants_9_hours -0.487609\n", - "┃ coef_first_of_2plus_school_lt_6_hours 0.169055\n", - "┃ coef_first_of_2plus_school_tours_departure -0.333830\n", - "┃ coef_first_of_2plus_school_tours_duration -0.042558\n", - "┃ coef_ft_worker_departure 0.397100\n", - "┃ coef_ft_worker_duration -0.190800\n", - "┃ coef_hh_income_early_departure -13.757852\n", - "┃ coef_hh_income_late_arrival 0.101726\n", - "┃ coef_mode_choice_logsum 0.056410\n", - "┃ coef_non_worker_departure 0.553900\n", - "┃ coef_previous_tour_begins_this_arrival_hour -10.370632\n", - "┃ coef_previous_tour_ends_this_departure_hour 0.298551\n", - "┃ coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours -25.000000\n", - "┃ coef_roundtrip_auto_time_to_work 0.005137\n", - "┃ coef_school_plus_work_tours_by_student_lt_6_hours -2.483313\n", - "┃ coef_school_plus_work_tours_by_worker_lt_6_hours -2.071313\n", - "┃ coef_student_driver_duration -0.003958\n", - "┃ coef_subsequent_2plus_school_tours_duration -0.188299\n", - "┃ coef_subsequent_of_2plus_school_lt_6_hours 25.000000\n", - "┃ coef_subsequent_tour_must_start_after_previous_tour_ends -25.000000\n", - "┃ coef_univ_departure 0.234367\n", - "┃ coef_univ_duration -0.409132\n", + "┣ x: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.232285\n", + "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction -1.201676\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction -0.419250\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction -0.760747\n", + "┃ coef_all_adults_ft_worker_duration 0.079713\n", + "┃ coef_arrival_constants_am_peak -2.595385\n", + "┃ coef_arrival_constants_early -2.446580\n", + "┃ coef_arrival_constants_evening -0.707272\n", + "┃ coef_arrival_constants_late -1.639520\n", + "┃ coef_arrival_constants_midday_1 -1.267988\n", + "┃ coef_arrival_constants_midday_2 -0.523484\n", + "┃ coef_arrival_constants_pm_peak_1 0.000000\n", + "┃ coef_arrival_constants_pm_peak_2 -0.360268\n", + "┃ coef_arrival_constants_pm_peak_3 -0.096426\n", + "┃ coef_arrival_constants_pm_peak_4 -0.127905\n", + "┃ coef_departure_constants_am_peak_1 -1.606835\n", + "┃ coef_departure_constants_am_peak_2 0.000000\n", + "┃ coef_departure_constants_am_peak_3 -0.100582\n", + "┃ coef_departure_constants_am_peak_4 -2.142432\n", + "┃ coef_departure_constants_early -3.850945\n", + "┃ coef_departure_constants_evening -5.546826\n", + "┃ coef_departure_constants_late -10.890722\n", + "┃ coef_departure_constants_midday_1 -3.124481\n", + "┃ coef_departure_constants_midday_2 -3.861525\n", + "┃ coef_departure_constants_pm_peak -3.281532\n", + "┃ coef_duration_constants_0_to_2_hours -1.318085\n", + "┃ coef_duration_constants_10_hours -0.914359\n", + "┃ coef_duration_constants_11_hours -1.643692\n", + "┃ coef_duration_constants_12_to_13_hours -2.528269\n", + "┃ coef_duration_constants_14_to_18_hours -2.541672\n", + "┃ coef_duration_constants_3_to_4_hours -0.680239\n", + "┃ coef_duration_constants_5_to_6_hours -0.551126\n", + "┃ coef_duration_constants_7_to_8_hours 0.000000\n", + "┃ coef_duration_constants_9_hours -0.664353\n", + "┃ coef_first_of_2plus_school_lt_6_hours 1.768123\n", + "┃ coef_first_of_2plus_school_tours_departure -0.277161\n", + "┃ coef_first_of_2plus_school_tours_duration -0.077846\n", + "┃ coef_ft_worker_departure 0.397100\n", + "┃ coef_ft_worker_duration -0.190800\n", + "┃ coef_hh_income_early_departure -0.643531\n", + "┃ coef_hh_income_late_arrival -0.123912\n", + "┃ coef_mode_choice_logsum 1.403530\n", + "┃ coef_non_worker_departure 0.553900\n", + "┃ coef_previous_tour_begins_this_arrival_hour 1.748525\n", + "┃ coef_previous_tour_ends_this_departure_hour -1.454921\n", + "┃ coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours -16.666935\n", + "┃ coef_roundtrip_auto_time_to_work 0.002946\n", + "┃ coef_school_plus_work_tours_by_student_lt_6_hours 1.805060\n", + "┃ coef_school_plus_work_tours_by_worker_lt_6_hours 2.217060\n", + "┃ coef_student_driver_duration 0.021414\n", + "┃ coef_subsequent_2plus_school_tours_duration -0.309377\n", + "┃ coef_subsequent_of_2plus_school_lt_6_hours 1.522961\n", + "┃ coef_subsequent_tour_must_start_after_previous_tour_ends -100.000000\n", + "┃ coef_univ_departure 0.281763\n", + "┃ coef_univ_duration -0.287541\n", "┃ dtype: float64\n", - "┣ loglike: -2331.7420221780226\n", - "┣ d_loglike: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction -1.569000e-04\n", - "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction 2.469873e-05\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction -1.376329e-04\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction -1.199309e-04\n", - "┃ coef_all_adults_ft_worker_duration -2.382589e-04\n", - "┃ coef_arrival_constants_am_peak 1.105861e-04\n", - "┃ coef_arrival_constants_early -7.161434e-05\n", - "┃ coef_arrival_constants_evening -3.213301e-04\n", - "┃ coef_arrival_constants_late -3.685726e-05\n", - "┃ coef_arrival_constants_midday_1 2.405910e-04\n", - "┃ coef_arrival_constants_midday_2 3.974766e-04\n", + "┣ logloss: 3.8441737168559693\n", + "┣ d_logloss: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 1.678936e-05\n", + "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction -4.551660e-05\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 1.846962e-05\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction -1.145647e-04\n", + "┃ coef_all_adults_ft_worker_duration -8.371558e-05\n", + "┃ coef_arrival_constants_am_peak 2.196925e-04\n", + "┃ coef_arrival_constants_early -5.719292e-06\n", + "┃ coef_arrival_constants_evening -8.835678e-05\n", + "┃ coef_arrival_constants_late 1.013090e-04\n", + "┃ coef_arrival_constants_midday_1 7.833025e-05\n", + "┃ coef_arrival_constants_midday_2 -1.965074e-04\n", "┃ coef_arrival_constants_pm_peak_1 0.000000e+00\n", - "┃ coef_arrival_constants_pm_peak_2 -3.784033e-04\n", - "┃ coef_arrival_constants_pm_peak_3 -2.802883e-04\n", - "┃ coef_arrival_constants_pm_peak_4 1.590313e-04\n", - "┃ coef_departure_constants_am_peak_1 3.893384e-05\n", + "┃ coef_arrival_constants_pm_peak_2 -9.685367e-05\n", + "┃ coef_arrival_constants_pm_peak_3 -9.087295e-05\n", + "┃ coef_arrival_constants_pm_peak_4 2.740145e-05\n", + "┃ coef_departure_constants_am_peak_1 1.513237e-04\n", "┃ coef_departure_constants_am_peak_2 0.000000e+00\n", - "┃ coef_departure_constants_am_peak_3 -1.076955e-04\n", - "┃ coef_departure_constants_am_peak_4 -1.023082e-04\n", - "┃ coef_departure_constants_early -1.964617e-05\n", - "┃ coef_departure_constants_evening 9.016158e-05\n", - "┃ coef_departure_constants_late -6.465407e-07\n", - "┃ coef_departure_constants_midday_1 -1.539484e-05\n", - "┃ coef_departure_constants_midday_2 7.340411e-05\n", - "┃ coef_departure_constants_pm_peak -3.023675e-04\n", - "┃ coef_duration_constants_0_to_2_hours -1.095813e-04\n", - "┃ coef_duration_constants_10_hours -4.107214e-05\n", - "┃ coef_duration_constants_11_hours 1.853670e-04\n", - "┃ coef_duration_constants_12_to_13_hours 4.561763e-05\n", - "┃ coef_duration_constants_14_to_18_hours 1.362278e-04\n", - "┃ coef_duration_constants_3_to_4_hours 3.779389e-06\n", - "┃ coef_duration_constants_5_to_6_hours 1.389604e-04\n", + "┃ coef_departure_constants_am_peak_3 -8.937296e-06\n", + "┃ coef_departure_constants_am_peak_4 -8.822207e-05\n", + "┃ coef_departure_constants_early 6.575707e-05\n", + "┃ coef_departure_constants_evening -4.373200e-05\n", + "┃ coef_departure_constants_late 7.294452e-05\n", + "┃ coef_departure_constants_midday_1 -7.045255e-05\n", + "┃ coef_departure_constants_midday_2 9.783210e-05\n", + "┃ coef_departure_constants_pm_peak 1.854008e-04\n", + "┃ coef_duration_constants_0_to_2_hours -1.017742e-05\n", + "┃ coef_duration_constants_10_hours -1.010013e-04\n", + "┃ coef_duration_constants_11_hours 3.540305e-05\n", + "┃ coef_duration_constants_12_to_13_hours 3.622247e-06\n", + "┃ coef_duration_constants_14_to_18_hours 1.457916e-04\n", + "┃ coef_duration_constants_3_to_4_hours -1.500782e-04\n", + "┃ coef_duration_constants_5_to_6_hours 2.054373e-04\n", "┃ coef_duration_constants_7_to_8_hours 0.000000e+00\n", - "┃ coef_duration_constants_9_hours -4.131255e-04\n", - "┃ coef_first_of_2plus_school_lt_6_hours 2.433801e-05\n", - "┃ coef_first_of_2plus_school_tours_departure -1.088730e-04\n", - "┃ coef_first_of_2plus_school_tours_duration -1.351925e-04\n", + "┃ coef_duration_constants_9_hours 1.173908e-04\n", + "┃ coef_first_of_2plus_school_lt_6_hours 6.625071e-05\n", + "┃ coef_first_of_2plus_school_tours_departure 4.904242e-05\n", + "┃ coef_first_of_2plus_school_tours_duration 5.848347e-05\n", "┃ coef_ft_worker_departure 0.000000e+00\n", "┃ coef_ft_worker_duration 0.000000e+00\n", - "┃ coef_hh_income_early_departure -1.184539e-06\n", - "┃ coef_hh_income_late_arrival 8.674395e-05\n", - "┃ coef_mode_choice_logsum 7.755139e-04\n", + "┃ coef_hh_income_early_departure -5.079513e-05\n", + "┃ coef_hh_income_late_arrival -7.624692e-05\n", + "┃ coef_mode_choice_logsum -2.256830e-05\n", "┃ coef_non_worker_departure 0.000000e+00\n", - "┃ coef_previous_tour_begins_this_arrival_hour -7.619359e-07\n", - "┃ coef_previous_tour_ends_this_departure_hour -2.114195e-05\n", - "┃ coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours -1.863986e-02\n", - "┃ coef_roundtrip_auto_time_to_work -2.056667e-03\n", - "┃ coef_school_plus_work_tours_by_student_lt_6_hours 2.636310e-06\n", - "┃ coef_school_plus_work_tours_by_worker_lt_6_hours 2.636310e-06\n", - "┃ coef_student_driver_duration 4.065449e-04\n", - "┃ coef_subsequent_2plus_school_tours_duration 6.239050e-05\n", - "┃ coef_subsequent_of_2plus_school_lt_6_hours 2.696315e-06\n", + "┃ coef_previous_tour_begins_this_arrival_hour -8.260618e-06\n", + "┃ coef_previous_tour_ends_this_departure_hour -4.098700e-05\n", + "┃ coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours 3.894311e-07\n", + "┃ coef_roundtrip_auto_time_to_work 5.433902e-05\n", + "┃ coef_school_plus_work_tours_by_student_lt_6_hours 8.778429e-06\n", + "┃ coef_school_plus_work_tours_by_worker_lt_6_hours 8.778429e-06\n", + "┃ coef_student_driver_duration -5.008566e-05\n", + "┃ coef_subsequent_2plus_school_tours_duration 5.111004e-05\n", + "┃ coef_subsequent_of_2plus_school_lt_6_hours 9.902870e-05\n", "┃ coef_subsequent_tour_must_start_after_previous_tour_ends 0.000000e+00\n", - "┃ coef_univ_departure -2.420842e-03\n", - "┃ coef_univ_duration 7.174716e-04\n", + "┃ coef_univ_departure -7.874285e-05\n", + "┃ coef_univ_duration -1.251813e-05\n", "┃ dtype: float64\n", - "┣ nit: 77\n", - "┣ nfev: 141\n", - "┣ njev: 77\n", + "┣ nit: 139\n", + "┣ nfev: 142\n", + "┣ njev: 139\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=2, microseconds=917567)\n", + "┣ elapsed_time: datetime.timedelta(seconds=41, microseconds=638335)\n", "┣ method: 'slsqp'\n", - "┣ n_cases: 609\n", - "┣ iteration_number: 77\n", - "┣ logloss: 3.8288046341182636" + "┣ n_cases: 10352\n", + "┣ iteration_number: 139\n", + "┣ loglike: -39483.50824582766" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.estimate()" + "model.estimate(maxiter=999)" ] }, { @@ -3521,579 +3673,550 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction-0.414 0.645-0.64 NA 0.00
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction-0.640 0.383-1.67 NA 0.00
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 1.66 0.794 2.09* NA 0.00
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction 0.226 0.377 0.60 NA 0.00
coef_all_adults_ft_worker_duration 0.0523 0.179 0.29 NA 0.00
coef_arrival_constants_am_peak-2.24 0.467-4.79*** NA 0.00
coef_arrival_constants_early-1.07 0.889-1.20 NA 0.00
coef_arrival_constants_evening-1.03 0.346-2.99** NA 0.00
coef_arrival_constants_late-1.32 0.510-2.58** NA 0.00
coef_arrival_constants_midday_1-1.30 0.285-4.57*** NA 0.00
coef_arrival_constants_midday_2-0.555 0.161-3.45*** NA 0.00
coef_arrival_constants_pm_peak_1 0.00 NA NA NA 0.00fixed value
coef_arrival_constants_pm_peak_2-0.441 0.167-2.64** NA 0.00
coef_arrival_constants_pm_peak_3-0.281 0.223-1.26 NA 0.00
coef_arrival_constants_pm_peak_4-0.370 0.274-1.35 NA 0.00
coef_departure_constants_am_peak_1-1.88 0.214-8.81*** NA 0.00
coef_departure_constants_am_peak_2 0.00 NA NA NA 0.00fixed value
coef_departure_constants_am_peak_3-0.184 0.114-1.61 NA 0.00
coef_departure_constants_am_peak_4-2.02 0.224-9.01*** NA 0.00
coef_departure_constants_early-3.64 0.600-6.07*** NA 0.00
coef_departure_constants_evening-5.26 0.830-6.34*** NA 0.00
coef_departure_constants_late-21.4 1.78e+03-0.01 NA 0.00
coef_departure_constants_midday_1-3.28 0.291-11.28*** NA 0.00
coef_departure_constants_midday_2-3.75 0.433-8.67*** NA 0.00
coef_departure_constants_pm_peak-3.09 0.579-5.34*** NA 0.00
coef_duration_constants_0_to_2_hours-1.37 0.393-3.49*** NA 0.00
coef_duration_constants_10_hours-0.876 0.271-3.24** NA 0.00
coef_duration_constants_11_hours-1.13 0.347-3.24** NA 0.00
coef_duration_constants_12_to_13_hours-2.67 0.530-5.04*** NA 0.00
coef_duration_constants_14_to_18_hours-2.68 0.614-4.36*** NA 0.00
coef_duration_constants_3_to_4_hours-0.552 0.277-2.00* NA 0.00
coef_duration_constants_5_to_6_hours-0.533 0.179-2.97** NA 0.00
coef_duration_constants_7_to_8_hours 0.00 NA NA NA 0.00fixed value
coef_duration_constants_9_hours-0.488 0.199-2.45* NA 0.00
coef_first_of_2plus_school_lt_6_hours 0.169 1.14 0.15 NA 0.00
coef_first_of_2plus_school_tours_departure-0.334 0.170-1.96* NA 0.00
coef_first_of_2plus_school_tours_duration-0.0426 0.214-0.20 NA 0.00
coef_ft_worker_departure 0.397 0.0143 27.72*** NA 0.00
coef_ft_worker_duration-0.191 0.00454-42.02*** NA 0.00
coef_hh_income_early_departure-13.8 934.-0.01 NA 0.00
coef_hh_income_late_arrival 0.102 0.762 0.13 NA 0.00
coef_mode_choice_logsum 0.0564 0.267 0.21 NA 0.00
coef_non_worker_departure 0.554 0.000124 BIG*** NA 0.00
coef_previous_tour_begins_this_arrival_hour-10.4 1.62e+03-0.01 NA 0.00
coef_previous_tour_ends_this_departure_hour 0.299 0.613 0.49 NA 0.00
coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours-25.0 NA NA[] 1.05 0.00coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours ≥ -25.0
coef_roundtrip_auto_time_to_work 0.00514 0.00516 1.00 NA 0.00
coef_school_plus_work_tours_by_student_lt_6_hours-2.48 314.-0.01 NA 0.00
coef_school_plus_work_tours_by_worker_lt_6_hours-2.07 314.-0.01 NA 0.00
coef_student_driver_duration-0.00396 0.0373-0.11 NA 0.00
coef_subsequent_2plus_school_tours_duration-0.188 0.149-1.27 NA 0.00
coef_subsequent_of_2plus_school_lt_6_hours 25.0 NA NA[***] 220.75 0.00coef_subsequent_of_2plus_school_lt_6_hours ≤ 25.0
coef_subsequent_tour_must_start_after_previous_tour_ends-100. NA NA NA 0.00fixed value
coef_univ_departure 0.234 0.0383 6.13*** NA 0.00
coef_univ_duration-0.409 0.0544-7.52*** NA 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.232 2.43 0.10 0.00
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction-1.20 0.265-4.54*** 0.00
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction-0.419 0.705-0.59 0.00
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction-0.761 0.722-1.05 0.00
coef_all_adults_ft_worker_duration 0.0797 0.0336 2.37* 0.00
coef_arrival_constants_am_peak-2.60 0.128-20.35*** 0.00
coef_arrival_constants_early-2.45 0.378-6.47*** 0.00
coef_arrival_constants_evening-0.707 0.0872-8.11*** 0.00
coef_arrival_constants_late-1.64 0.137-11.98*** 0.00
coef_arrival_constants_midday_1-1.27 0.0711-17.84*** 0.00
coef_arrival_constants_midday_2-0.523 0.0391-13.41*** 0.00
coef_arrival_constants_pm_peak_1 0.00 0.00 NA 0.00fixed value
coef_arrival_constants_pm_peak_2-0.360 0.0391-9.21*** 0.00
coef_arrival_constants_pm_peak_3-0.0964 0.0543-1.78 0.00
coef_arrival_constants_pm_peak_4-0.128 0.0672-1.90 0.00
coef_departure_constants_am_peak_1-1.61 0.0470-34.22*** 0.00
coef_departure_constants_am_peak_2 0.00 0.00 NA 0.00fixed value
coef_departure_constants_am_peak_3-0.101 0.0275-3.66*** 0.00
coef_departure_constants_am_peak_4-2.14 0.0570-37.57*** 0.00
coef_departure_constants_early-3.85 0.173-22.28*** 0.00
coef_departure_constants_evening-5.55 0.220-25.26*** 0.00
coef_departure_constants_late-10.9 2.02-5.39*** 0.00
coef_departure_constants_midday_1-3.12 0.0717-43.56*** 0.00
coef_departure_constants_midday_2-3.86 0.112-34.58*** 0.00
coef_departure_constants_pm_peak-3.28 0.148-22.16*** 0.00
coef_duration_constants_0_to_2_hours-1.32 0.0986-13.37*** 0.00
coef_duration_constants_10_hours-0.914 0.0627-14.59*** 0.00
coef_duration_constants_11_hours-1.64 0.0876-18.76*** 0.00
coef_duration_constants_12_to_13_hours-2.53 0.112-22.51*** 0.00
coef_duration_constants_14_to_18_hours-2.54 0.143-17.80*** 0.00
coef_duration_constants_3_to_4_hours-0.680 0.0695-9.79*** 0.00
coef_duration_constants_5_to_6_hours-0.551 0.0434-12.71*** 0.00
coef_duration_constants_7_to_8_hours 0.00 0.00 NA 0.00fixed value
coef_duration_constants_9_hours-0.664 0.0471-14.10*** 0.00
coef_first_of_2plus_school_lt_6_hours 1.77 0.267 6.63*** 0.00
coef_first_of_2plus_school_tours_departure-0.277 0.0289-9.59*** 0.00
coef_first_of_2plus_school_tours_duration-0.0778 0.0892-0.87 0.00
coef_ft_worker_departure 0.397 NA NA 0.00
coef_ft_worker_duration-0.191 NA NA 0.00
coef_hh_income_early_departure-0.644 0.381-1.69 0.00
coef_hh_income_late_arrival-0.124 0.206-0.60 0.00
coef_mode_choice_logsum 1.40 0.125 11.19*** 0.00
coef_non_worker_departure 0.554 2.69e-13 BIG*** 0.00
coef_previous_tour_begins_this_arrival_hour 1.75 0.946 1.85 0.00
coef_previous_tour_ends_this_departure_hour-1.45 0.690-2.11* 0.00
coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours-16.7 18.9-0.88 0.00
coef_roundtrip_auto_time_to_work 0.00295 0.000437 6.74*** 0.00
coef_school_plus_work_tours_by_student_lt_6_hours 1.81 1.68 1.07 0.00
coef_school_plus_work_tours_by_worker_lt_6_hours 2.22 1.68 1.32 0.00
coef_student_driver_duration 0.0214 0.00880 2.43* 0.00
coef_subsequent_2plus_school_tours_duration-0.309 0.0368-8.41*** 0.00
coef_subsequent_of_2plus_school_lt_6_hours 1.52 0.493 3.09** 0.00
coef_subsequent_tour_must_start_after_previous_tour_ends-100. 0.00 NA 0.00fixed value
coef_univ_departure 0.282 0.0112 25.08*** 0.00
coef_univ_duration-0.288 0.0153-18.82*** 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -4114,7 +4237,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -4135,20 +4258,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -4167,7 +4279,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -4206,7 +4318,7 @@ " \n", " 1\n", " coef_roundtrip_auto_time_to_work\n", - " 0.005137\n", + " 0.002946\n", " F\n", " \n", " \n", @@ -4230,25 +4342,25 @@ " \n", " 5\n", " coef_univ_departure\n", - " 0.234367\n", + " 0.281763\n", " F\n", " \n", " \n", " 6\n", " coef_univ_duration\n", - " -0.409132\n", + " -0.287541\n", " F\n", " \n", " \n", " 7\n", " coef_student_driver_duration\n", - " -0.003958\n", + " 0.021414\n", " F\n", " \n", " \n", " 8\n", " coef_all_adults_ft_worker_duration\n", - " 0.052336\n", + " 0.079713\n", " F\n", " \n", " \n", @@ -4260,115 +4372,115 @@ " \n", " 10\n", " coef_first_of_2plus_school_tours_departure\n", - " -0.333830\n", + " -0.277161\n", " F\n", " \n", " \n", " 11\n", " coef_first_of_2plus_school_tours_duration\n", - " -0.042558\n", + " -0.077846\n", " F\n", " \n", " \n", " 12\n", " coef_subsequent_2plus_school_tours_duration\n", - " -0.188299\n", + " -0.309377\n", " F\n", " \n", " \n", " 13\n", " coef_hh_income_early_departure\n", - " -13.757852\n", + " -0.643531\n", " F\n", " \n", " \n", " 14\n", " coef_hh_income_late_arrival\n", - " 0.101726\n", + " -0.123912\n", " F\n", " \n", " \n", " 15\n", " coef_first_of_2plus_school_lt_6_hours\n", - " 0.169055\n", + " 1.768123\n", " F\n", " \n", " \n", " 16\n", " coef_subsequent_of_2plus_school_lt_6_hours\n", - " 25.000000\n", + " 1.522961\n", " F\n", " \n", " \n", " 17\n", " coef_school_plus_work_tours_by_student_lt_6_hours\n", - " -2.483313\n", + " 1.805060\n", " F\n", " \n", " \n", " 18\n", " coef_school_plus_work_tours_by_worker_lt_6_hours\n", - " -2.071313\n", + " 2.217060\n", " F\n", " \n", " \n", " 19\n", " coef_mode_choice_logsum\n", - " 0.056410\n", + " 1.403530\n", " F\n", " \n", " \n", " 20\n", " coef_previous_tour_ends_this_departure_hour\n", - " 0.298551\n", + " -1.454921\n", " F\n", " \n", " \n", " 21\n", " coef_previous_tour_begins_this_arrival_hour\n", - " -10.370632\n", + " 1.748525\n", " F\n", " \n", " \n", " 22\n", " coef_adjacent_window_exists_before_this_depart...\n", - " 1.656920\n", + " -0.419250\n", " F\n", " \n", " \n", " 23\n", " coef_adjacent_window_exists_after_this_arrival...\n", - " -0.414229\n", + " 0.232285\n", " F\n", " \n", " \n", " 24\n", " coef_adjacent_window_exists_before_this_depart...\n", - " 0.225722\n", + " -0.760747\n", " F\n", " \n", " \n", " 25\n", " coef_adjacent_window_exists_after_this_arrival...\n", - " -0.640186\n", + " -1.201676\n", " F\n", " \n", " \n", " 26\n", " coef_remaining_work_school_tours_to_be_schedul...\n", - " -25.000000\n", + " -16.666935\n", " F\n", " \n", " \n", " 27\n", " coef_departure_constants_early\n", - " -3.636770\n", + " -3.850945\n", " F\n", " \n", " \n", " 28\n", " coef_departure_constants_am_peak_1\n", - " -1.882694\n", + " -1.606835\n", " F\n", " \n", " \n", @@ -4380,67 +4492,67 @@ " \n", " 30\n", " coef_departure_constants_am_peak_3\n", - " -0.183985\n", + " -0.100582\n", " F\n", " \n", " \n", " 31\n", " coef_departure_constants_am_peak_4\n", - " -2.016403\n", + " -2.142432\n", " F\n", " \n", " \n", " 32\n", " coef_departure_constants_midday_1\n", - " -3.279864\n", + " -3.124481\n", " F\n", " \n", " \n", " 33\n", " coef_departure_constants_midday_2\n", - " -3.750548\n", + " -3.861525\n", " F\n", " \n", " \n", " 34\n", " coef_departure_constants_pm_peak\n", - " -3.093167\n", + " -3.281532\n", " F\n", " \n", " \n", " 35\n", " coef_departure_constants_evening\n", - " -5.258795\n", + " -5.546826\n", " F\n", " \n", " \n", " 36\n", " coef_departure_constants_late\n", - " -21.447622\n", + " -10.890722\n", " F\n", " \n", " \n", " 37\n", " coef_arrival_constants_early\n", - " -1.065980\n", + " -2.446580\n", " F\n", " \n", " \n", " 38\n", " coef_arrival_constants_am_peak\n", - " -2.239162\n", + " -2.595385\n", " F\n", " \n", " \n", " 39\n", " coef_arrival_constants_midday_1\n", - " -1.302330\n", + " -1.267988\n", " F\n", " \n", " \n", " 40\n", " coef_arrival_constants_midday_2\n", - " -0.554673\n", + " -0.523484\n", " F\n", " \n", " \n", @@ -4452,49 +4564,49 @@ " \n", " 42\n", " coef_arrival_constants_pm_peak_2\n", - " -0.441387\n", + " -0.360268\n", " F\n", " \n", " \n", " 43\n", " coef_arrival_constants_pm_peak_3\n", - " -0.281247\n", + " -0.096426\n", " F\n", " \n", " \n", " 44\n", " coef_arrival_constants_pm_peak_4\n", - " -0.370368\n", + " -0.127905\n", " F\n", " \n", " \n", " 45\n", " coef_arrival_constants_evening\n", - " -1.033329\n", + " -0.707272\n", " F\n", " \n", " \n", " 46\n", " coef_arrival_constants_late\n", - " -1.315910\n", + " -1.639520\n", " F\n", " \n", " \n", " 47\n", " coef_duration_constants_0_to_2_hours\n", - " -1.372110\n", + " -1.318085\n", " F\n", " \n", " \n", " 48\n", " coef_duration_constants_3_to_4_hours\n", - " -0.552200\n", + " -0.680239\n", " F\n", " \n", " \n", " 49\n", " coef_duration_constants_5_to_6_hours\n", - " -0.532627\n", + " -0.551126\n", " F\n", " \n", " \n", @@ -4506,31 +4618,31 @@ " \n", " 51\n", " coef_duration_constants_9_hours\n", - " -0.487609\n", + " -0.664353\n", " F\n", " \n", " \n", " 52\n", " coef_duration_constants_10_hours\n", - " -0.876448\n", + " -0.914359\n", " F\n", " \n", " \n", " 53\n", " coef_duration_constants_11_hours\n", - " -1.127264\n", + " -1.643692\n", " F\n", " \n", " \n", " 54\n", " coef_duration_constants_12_to_13_hours\n", - " -2.668346\n", + " -2.528269\n", " F\n", " \n", " \n", " 55\n", " coef_duration_constants_14_to_18_hours\n", - " -2.675974\n", + " -2.541672\n", " F\n", " \n", " \n", @@ -4540,64 +4652,64 @@ "text/plain": [ " coefficient_name value constrain\n", "0 coef_dummy 1.000000 T\n", - "1 coef_roundtrip_auto_time_to_work 0.005137 F\n", + "1 coef_roundtrip_auto_time_to_work 0.002946 F\n", "2 coef_ft_worker_departure 0.397100 F\n", "3 coef_ft_worker_duration -0.190800 F\n", "4 coef_non_worker_departure 0.553900 F\n", - "5 coef_univ_departure 0.234367 F\n", - "6 coef_univ_duration -0.409132 F\n", - "7 coef_student_driver_duration -0.003958 F\n", - "8 coef_all_adults_ft_worker_duration 0.052336 F\n", + "5 coef_univ_departure 0.281763 F\n", + "6 coef_univ_duration -0.287541 F\n", + "7 coef_student_driver_duration 0.021414 F\n", + "8 coef_all_adults_ft_worker_duration 0.079713 F\n", "9 coef_subsequent_tour_must_start_after_previous... -100.000000 T\n", - "10 coef_first_of_2plus_school_tours_departure -0.333830 F\n", - "11 coef_first_of_2plus_school_tours_duration -0.042558 F\n", - "12 coef_subsequent_2plus_school_tours_duration -0.188299 F\n", - "13 coef_hh_income_early_departure -13.757852 F\n", - "14 coef_hh_income_late_arrival 0.101726 F\n", - "15 coef_first_of_2plus_school_lt_6_hours 0.169055 F\n", - "16 coef_subsequent_of_2plus_school_lt_6_hours 25.000000 F\n", - "17 coef_school_plus_work_tours_by_student_lt_6_hours -2.483313 F\n", - "18 coef_school_plus_work_tours_by_worker_lt_6_hours -2.071313 F\n", - "19 coef_mode_choice_logsum 0.056410 F\n", - "20 coef_previous_tour_ends_this_departure_hour 0.298551 F\n", - "21 coef_previous_tour_begins_this_arrival_hour -10.370632 F\n", - "22 coef_adjacent_window_exists_before_this_depart... 1.656920 F\n", - "23 coef_adjacent_window_exists_after_this_arrival... -0.414229 F\n", - "24 coef_adjacent_window_exists_before_this_depart... 0.225722 F\n", - "25 coef_adjacent_window_exists_after_this_arrival... -0.640186 F\n", - "26 coef_remaining_work_school_tours_to_be_schedul... -25.000000 F\n", - "27 coef_departure_constants_early -3.636770 F\n", - "28 coef_departure_constants_am_peak_1 -1.882694 F\n", + "10 coef_first_of_2plus_school_tours_departure -0.277161 F\n", + "11 coef_first_of_2plus_school_tours_duration -0.077846 F\n", + "12 coef_subsequent_2plus_school_tours_duration -0.309377 F\n", + "13 coef_hh_income_early_departure -0.643531 F\n", + "14 coef_hh_income_late_arrival -0.123912 F\n", + "15 coef_first_of_2plus_school_lt_6_hours 1.768123 F\n", + "16 coef_subsequent_of_2plus_school_lt_6_hours 1.522961 F\n", + "17 coef_school_plus_work_tours_by_student_lt_6_hours 1.805060 F\n", + "18 coef_school_plus_work_tours_by_worker_lt_6_hours 2.217060 F\n", + "19 coef_mode_choice_logsum 1.403530 F\n", + "20 coef_previous_tour_ends_this_departure_hour -1.454921 F\n", + "21 coef_previous_tour_begins_this_arrival_hour 1.748525 F\n", + "22 coef_adjacent_window_exists_before_this_depart... -0.419250 F\n", + "23 coef_adjacent_window_exists_after_this_arrival... 0.232285 F\n", + "24 coef_adjacent_window_exists_before_this_depart... -0.760747 F\n", + "25 coef_adjacent_window_exists_after_this_arrival... -1.201676 F\n", + "26 coef_remaining_work_school_tours_to_be_schedul... -16.666935 F\n", + "27 coef_departure_constants_early -3.850945 F\n", + "28 coef_departure_constants_am_peak_1 -1.606835 F\n", "29 coef_departure_constants_am_peak_2 0.000000 T\n", - "30 coef_departure_constants_am_peak_3 -0.183985 F\n", - "31 coef_departure_constants_am_peak_4 -2.016403 F\n", - "32 coef_departure_constants_midday_1 -3.279864 F\n", - "33 coef_departure_constants_midday_2 -3.750548 F\n", - "34 coef_departure_constants_pm_peak -3.093167 F\n", - "35 coef_departure_constants_evening -5.258795 F\n", - "36 coef_departure_constants_late -21.447622 F\n", - "37 coef_arrival_constants_early -1.065980 F\n", - "38 coef_arrival_constants_am_peak -2.239162 F\n", - "39 coef_arrival_constants_midday_1 -1.302330 F\n", - "40 coef_arrival_constants_midday_2 -0.554673 F\n", + "30 coef_departure_constants_am_peak_3 -0.100582 F\n", + "31 coef_departure_constants_am_peak_4 -2.142432 F\n", + "32 coef_departure_constants_midday_1 -3.124481 F\n", + "33 coef_departure_constants_midday_2 -3.861525 F\n", + "34 coef_departure_constants_pm_peak -3.281532 F\n", + "35 coef_departure_constants_evening -5.546826 F\n", + "36 coef_departure_constants_late -10.890722 F\n", + "37 coef_arrival_constants_early -2.446580 F\n", + "38 coef_arrival_constants_am_peak -2.595385 F\n", + "39 coef_arrival_constants_midday_1 -1.267988 F\n", + "40 coef_arrival_constants_midday_2 -0.523484 F\n", "41 coef_arrival_constants_pm_peak_1 0.000000 T\n", - "42 coef_arrival_constants_pm_peak_2 -0.441387 F\n", - "43 coef_arrival_constants_pm_peak_3 -0.281247 F\n", - "44 coef_arrival_constants_pm_peak_4 -0.370368 F\n", - "45 coef_arrival_constants_evening -1.033329 F\n", - "46 coef_arrival_constants_late -1.315910 F\n", - "47 coef_duration_constants_0_to_2_hours -1.372110 F\n", - "48 coef_duration_constants_3_to_4_hours -0.552200 F\n", - "49 coef_duration_constants_5_to_6_hours -0.532627 F\n", + "42 coef_arrival_constants_pm_peak_2 -0.360268 F\n", + "43 coef_arrival_constants_pm_peak_3 -0.096426 F\n", + "44 coef_arrival_constants_pm_peak_4 -0.127905 F\n", + "45 coef_arrival_constants_evening -0.707272 F\n", + "46 coef_arrival_constants_late -1.639520 F\n", + "47 coef_duration_constants_0_to_2_hours -1.318085 F\n", + "48 coef_duration_constants_3_to_4_hours -0.680239 F\n", + "49 coef_duration_constants_5_to_6_hours -0.551126 F\n", "50 coef_duration_constants_7_to_8_hours 0.000000 T\n", - "51 coef_duration_constants_9_hours -0.487609 F\n", - "52 coef_duration_constants_10_hours -0.876448 F\n", - "53 coef_duration_constants_11_hours -1.127264 F\n", - "54 coef_duration_constants_12_to_13_hours -2.668346 F\n", - "55 coef_duration_constants_14_to_18_hours -2.675974 F" + "51 coef_duration_constants_9_hours -0.664353 F\n", + "52 coef_duration_constants_10_hours -0.914359 F\n", + "53 coef_duration_constants_11_hours -1.643692 F\n", + "54 coef_duration_constants_12_to_13_hours -2.528269 F\n", + "55 coef_duration_constants_14_to_18_hours -2.541672 F" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -4614,7 +4726,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -4628,7 +4740,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/10_joint_tour_freq.ipynb b/activitysim/examples/example_estimation/notebooks/10_joint_tour_freq.ipynb index a8d306f95a..4fd045c4dd 100644 --- a/activitysim/examples/example_estimation/notebooks/10_joint_tour_freq.ipynb +++ b/activitysim/examples/example_estimation/notebooks/10_joint_tour_freq.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +115,27 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/joint_tour_frequency/joint_tour_frequency_coefficients.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/joint_tour_frequency/joint_tour_frequency_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_frequency/joint_tour_frequency_values_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"joint_tour_frequency\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -766,7 +828,7 @@ " \n", " \n", " \n", - " 189748\n", + " 190236\n", " 0_tours\n", " 0_tours\n", " 1.0\n", @@ -778,20 +840,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " False\n", " False\n", " 0\n", - " 2.996\n", - " 0.0\n", - " 0.000\n", - " 6.041458\n", + " 2.996094\n", + " 0.000000\n", + " 0.000000\n", + " 5.661266\n", " 1\n", " \n", " \n", - " 189758\n", - " 1_Eat\n", + " 190592\n", + " 1_Disc\n", " 1_Eat\n", " 1.0\n", " 0.0\n", @@ -802,19 +864,19 @@ " 0.0\n", " 0.0\n", " ...\n", - " 2.0\n", + " 0.0\n", " 0.0\n", " False\n", " False\n", " 0\n", - " 2.303\n", - " 0.0\n", - " 0.000\n", - " 6.035642\n", + " 2.996094\n", + " 0.000000\n", + " 0.000000\n", + " 5.384032\n", " 4\n", " \n", " \n", - " 189833\n", + " 190998\n", " 0_tours\n", " 0_tours\n", " 1.0\n", @@ -826,21 +888,21 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " False\n", " False\n", " 0\n", - " 2.996\n", - " 0.0\n", - " 0.000\n", - " 5.601202\n", + " 2.564453\n", + " 0.000000\n", + " 0.000000\n", + " 4.529309\n", " 1\n", " \n", " \n", - " 190134\n", - " 0_tours\n", + " 191185\n", " 0_tours\n", + " 1_Shop\n", " 1.0\n", " 0.0\n", " 0.0\n", @@ -855,16 +917,16 @@ " False\n", " False\n", " 0\n", - " 2.996\n", - " 0.0\n", - " 0.000\n", - " 5.941369\n", - " 1\n", + " 2.996094\n", + " 0.000000\n", + " 0.000000\n", + " 4.015752\n", + " 2\n", " \n", " \n", - " 190153\n", - " 0_tours\n", + " 191276\n", " 0_tours\n", + " 1_Disc\n", " 1.0\n", " 0.0\n", " 0.0\n", @@ -879,11 +941,11 @@ " False\n", " False\n", " 0\n", - " 2.996\n", - " 0.0\n", - " 0.000\n", - " 5.876868\n", - " 1\n", + " 2.996094\n", + " 0.000000\n", + " 0.000000\n", + " 4.422027\n", + " 6\n", " \n", " \n", " ...\n", @@ -910,38 +972,38 @@ " ...\n", " \n", " \n", - " 2749929\n", + " 2759076\n", " 0_tours\n", " 0_tours\n", " 1.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", " 1.0\n", + " 2.0\n", " False\n", " True\n", " 0\n", - " 2.303\n", - " 0.0\n", - " 2.484\n", - " 3.937425\n", + " 2.996094\n", + " 1.946289\n", + " 2.564453\n", + " 6.481015\n", " 1\n", " \n", " \n", - " 2749970\n", + " 2759264\n", " 0_tours\n", " 0_tours\n", " 1.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -951,16 +1013,16 @@ " False\n", " True\n", " 0\n", - " 2.996\n", - " 0.0\n", - " 0.000\n", - " 5.523326\n", + " 2.996094\n", + " 0.000000\n", + " 0.000000\n", + " 6.343830\n", " 1\n", " \n", " \n", - " 2750003\n", - " 0_tours\n", + " 2759425\n", " 0_tours\n", + " 1_Disc\n", " 1.0\n", " 0.0\n", " 0.0\n", @@ -970,20 +1032,20 @@ " 0.0\n", " 0.0\n", " ...\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " False\n", " True\n", " 0\n", - " 2.080\n", - " 0.0\n", - " 0.000\n", - " 6.289115\n", - " 1\n", + " 2.996094\n", + " 0.000000\n", + " 2.996094\n", + " 4.507081\n", + " 6\n", " \n", " \n", - " 2758909\n", - " 0_tours\n", + " 2760422\n", + " 1_Shop\n", " 0_tours\n", " 1.0\n", " 0.0\n", @@ -999,14 +1061,14 @@ " False\n", " True\n", " 0\n", - " 2.484\n", - " 0.0\n", - " 0.000\n", - " 6.677761\n", + " 2.197266\n", + " 0.000000\n", + " 0.000000\n", + " 4.345421\n", " 1\n", " \n", " \n", - " 2759348\n", + " 2760425\n", " 0_tours\n", " 0_tours\n", " 1.0\n", @@ -1023,229 +1085,229 @@ " False\n", " True\n", " 0\n", - " 2.996\n", - " 0.0\n", - " 0.000\n", - " 5.760961\n", + " 2.080078\n", + " 0.000000\n", + " 0.000000\n", + " 3.586974\n", " 1\n", " \n", " \n", "\n", - "

1028 rows × 130 columns

\n", + "

13210 rows × 130 columns

\n", "" ], "text/plain": [ " model_choice override_choice \\\n", "household_id \n", - "189748 0_tours 0_tours \n", - "189758 1_Eat 1_Eat \n", - "189833 0_tours 0_tours \n", - "190134 0_tours 0_tours \n", - "190153 0_tours 0_tours \n", + "190236 0_tours 0_tours \n", + "190592 1_Disc 1_Eat \n", + "190998 0_tours 0_tours \n", + "191185 0_tours 1_Shop \n", + "191276 0_tours 1_Disc \n", "... ... ... \n", - "2749929 0_tours 0_tours \n", - "2749970 0_tours 0_tours \n", - "2750003 0_tours 0_tours \n", - "2758909 0_tours 0_tours \n", - "2759348 0_tours 0_tours \n", + "2759076 0_tours 0_tours \n", + "2759264 0_tours 0_tours \n", + "2759425 0_tours 1_Disc \n", + "2760422 1_Shop 0_tours \n", + "2760425 0_tours 0_tours \n", "\n", " util_alternative_specific_constants \\\n", "household_id \n", - "189748 1.0 \n", - "189758 1.0 \n", - "189833 1.0 \n", - "190134 1.0 \n", - "190153 1.0 \n", + "190236 1.0 \n", + "190592 1.0 \n", + "190998 1.0 \n", + "191185 1.0 \n", + "191276 1.0 \n", "... ... \n", - "2749929 1.0 \n", - "2749970 1.0 \n", - "2750003 1.0 \n", - "2758909 1.0 \n", - "2759348 1.0 \n", + "2759076 1.0 \n", + "2759264 1.0 \n", + "2759425 1.0 \n", + "2760422 1.0 \n", + "2760425 1.0 \n", "\n", " util_fullTimeHomeMaxThree_zero_tours \\\n", "household_id \n", - "189748 0.0 \n", - "189758 0.0 \n", - "189833 0.0 \n", - "190134 0.0 \n", - "190153 0.0 \n", + "190236 0.0 \n", + "190592 0.0 \n", + "190998 0.0 \n", + "191185 0.0 \n", + "191276 0.0 \n", "... ... \n", - "2749929 0.0 \n", - "2749970 0.0 \n", - "2750003 0.0 \n", - "2758909 0.0 \n", - "2759348 0.0 \n", + "2759076 2.0 \n", + "2759264 1.0 \n", + "2759425 0.0 \n", + "2760422 0.0 \n", + "2760425 0.0 \n", "\n", " util_partTimeHomeMaxThree_zero_tours \\\n", "household_id \n", - "189748 0.0 \n", - "189758 0.0 \n", - "189833 0.0 \n", - "190134 0.0 \n", - "190153 0.0 \n", + "190236 0.0 \n", + "190592 0.0 \n", + "190998 0.0 \n", + "191185 0.0 \n", + "191276 0.0 \n", "... ... \n", - "2749929 0.0 \n", - "2749970 0.0 \n", - "2750003 0.0 \n", - "2758909 0.0 \n", - "2759348 0.0 \n", + "2759076 0.0 \n", + "2759264 0.0 \n", + "2759425 0.0 \n", + "2760422 0.0 \n", + "2760425 0.0 \n", "\n", " util_nonWorkerHomeMaxThree_zero_tours \\\n", "household_id \n", - "189748 0.0 \n", - "189758 0.0 \n", - "189833 0.0 \n", - "190134 0.0 \n", - "190153 0.0 \n", + "190236 0.0 \n", + "190592 0.0 \n", + "190998 0.0 \n", + "191185 0.0 \n", + "191276 0.0 \n", "... ... \n", - "2749929 0.0 \n", - "2749970 0.0 \n", - "2750003 0.0 \n", - "2758909 0.0 \n", - "2759348 0.0 \n", + "2759076 0.0 \n", + "2759264 0.0 \n", + "2759425 0.0 \n", + "2760422 0.0 \n", + "2760425 0.0 \n", "\n", " util_retireeHomeMaxThree_zero_tours \\\n", "household_id \n", - "189748 0.0 \n", - "189758 0.0 \n", - "189833 0.0 \n", - "190134 0.0 \n", - "190153 0.0 \n", + "190236 0.0 \n", + "190592 0.0 \n", + "190998 0.0 \n", + "191185 0.0 \n", + "191276 0.0 \n", "... ... \n", - "2749929 0.0 \n", - "2749970 1.0 \n", - "2750003 0.0 \n", - "2758909 0.0 \n", - "2759348 0.0 \n", + "2759076 1.0 \n", + "2759264 0.0 \n", + "2759425 0.0 \n", + "2760422 0.0 \n", + "2760425 0.0 \n", "\n", " util_universityHomeMaxThree_univ_and_driving_zero_tours \\\n", "household_id \n", - "189748 0.0 \n", - "189758 0.0 \n", - "189833 0.0 \n", - "190134 0.0 \n", - "190153 0.0 \n", + "190236 0.0 \n", + "190592 0.0 \n", + "190998 0.0 \n", + "191185 0.0 \n", + "191276 0.0 \n", "... ... \n", - "2749929 0.0 \n", - "2749970 0.0 \n", - "2750003 0.0 \n", - "2758909 0.0 \n", - "2759348 0.0 \n", + "2759076 0.0 \n", + "2759264 0.0 \n", + "2759425 0.0 \n", + "2760422 0.0 \n", + "2760425 0.0 \n", "\n", " util_preDrivingHomeMaxThree_preschool_and_school_zero_tours \\\n", "household_id \n", - "189748 0.0 \n", - "189758 0.0 \n", - "189833 0.0 \n", - "190134 0.0 \n", - "190153 0.0 \n", + "190236 0.0 \n", + "190592 0.0 \n", + "190998 0.0 \n", + "191185 0.0 \n", + "191276 0.0 \n", "... ... \n", - "2749929 0.0 \n", - "2749970 0.0 \n", - "2750003 0.0 \n", - "2758909 0.0 \n", - "2759348 0.0 \n", + "2759076 0.0 \n", + "2759264 0.0 \n", + "2759425 0.0 \n", + "2760422 0.0 \n", + "2760425 0.0 \n", "\n", " util_fullTimeNonMandMaxThree_shopping ... \\\n", "household_id ... \n", - "189748 0.0 ... \n", - "189758 0.0 ... \n", - "189833 0.0 ... \n", - "190134 0.0 ... \n", - "190153 0.0 ... \n", + "190236 0.0 ... \n", + "190592 0.0 ... \n", + "190998 0.0 ... \n", + "191185 0.0 ... \n", + "191276 0.0 ... \n", "... ... ... \n", - "2749929 0.0 ... \n", - "2749970 0.0 ... \n", - "2750003 0.0 ... \n", - "2758909 0.0 ... \n", - "2759348 0.0 ... \n", + "2759076 0.0 ... \n", + "2759264 0.0 ... \n", + "2759425 0.0 ... \n", + "2760422 0.0 ... \n", + "2760425 0.0 ... \n", "\n", " cdap_mand_univ_driving_max3 cdap_mand_nondriving_child_max3 \\\n", "household_id \n", - "189748 0.0 0.0 \n", - "189758 2.0 0.0 \n", - "189833 0.0 0.0 \n", - "190134 0.0 0.0 \n", - "190153 0.0 0.0 \n", + "190236 1.0 0.0 \n", + "190592 0.0 0.0 \n", + "190998 1.0 0.0 \n", + "191185 0.0 0.0 \n", + "191276 0.0 0.0 \n", "... ... ... \n", - "2749929 0.0 1.0 \n", - "2749970 0.0 0.0 \n", - "2750003 0.0 0.0 \n", - "2758909 0.0 0.0 \n", - "2759348 0.0 0.0 \n", + "2759076 1.0 2.0 \n", + "2759264 0.0 0.0 \n", + "2759425 1.0 0.0 \n", + "2760422 0.0 0.0 \n", + "2760425 0.0 0.0 \n", "\n", " income_between_50_and_100 income_greater_than_100 \\\n", "household_id \n", - "189748 False False \n", - "189758 False False \n", - "189833 False False \n", - "190134 False False \n", - "190153 False False \n", + "190236 False False \n", + "190592 False False \n", + "190998 False False \n", + "191185 False False \n", + "191276 False False \n", "... ... ... \n", - "2749929 False True \n", - "2749970 False True \n", - "2750003 False True \n", - "2758909 False True \n", - "2759348 False True \n", + "2759076 False True \n", + "2759264 False True \n", + "2759425 False True \n", + "2760422 False True \n", + "2760425 False True \n", "\n", " income_missing log_time_window_overlap_adult \\\n", "household_id \n", - "189748 0 2.996 \n", - "189758 0 2.303 \n", - "189833 0 2.996 \n", - "190134 0 2.996 \n", - "190153 0 2.996 \n", + "190236 0 2.996094 \n", + "190592 0 2.996094 \n", + "190998 0 2.564453 \n", + "191185 0 2.996094 \n", + "191276 0 2.996094 \n", "... ... ... \n", - "2749929 0 2.303 \n", - "2749970 0 2.996 \n", - "2750003 0 2.080 \n", - "2758909 0 2.484 \n", - "2759348 0 2.996 \n", + "2759076 0 2.996094 \n", + "2759264 0 2.996094 \n", + "2759425 0 2.996094 \n", + "2760422 0 2.197266 \n", + "2760425 0 2.080078 \n", "\n", " log_time_window_overlap_child \\\n", "household_id \n", - "189748 0.0 \n", - "189758 0.0 \n", - "189833 0.0 \n", - "190134 0.0 \n", - "190153 0.0 \n", + "190236 0.000000 \n", + "190592 0.000000 \n", + "190998 0.000000 \n", + "191185 0.000000 \n", + "191276 0.000000 \n", "... ... \n", - "2749929 0.0 \n", - "2749970 0.0 \n", - "2750003 0.0 \n", - "2758909 0.0 \n", - "2759348 0.0 \n", + "2759076 1.946289 \n", + "2759264 0.000000 \n", + "2759425 0.000000 \n", + "2760422 0.000000 \n", + "2760425 0.000000 \n", "\n", " log_time_window_overlap_adult_child \\\n", "household_id \n", - "189748 0.000 \n", - "189758 0.000 \n", - "189833 0.000 \n", - "190134 0.000 \n", - "190153 0.000 \n", + "190236 0.000000 \n", + "190592 0.000000 \n", + "190998 0.000000 \n", + "191185 0.000000 \n", + "191276 0.000000 \n", "... ... \n", - "2749929 2.484 \n", - "2749970 0.000 \n", - "2750003 0.000 \n", - "2758909 0.000 \n", - "2759348 0.000 \n", + "2759076 2.564453 \n", + "2759264 0.000000 \n", + "2759425 2.996094 \n", + "2760422 0.000000 \n", + "2760425 0.000000 \n", "\n", " non_motorized_retail_accessibility override_choice_code \n", "household_id \n", - "189748 6.041458 1 \n", - "189758 6.035642 4 \n", - "189833 5.601202 1 \n", - "190134 5.941369 1 \n", - "190153 5.876868 1 \n", + "190236 5.661266 1 \n", + "190592 5.384032 4 \n", + "190998 4.529309 1 \n", + "191185 4.015752 2 \n", + "191276 4.422027 6 \n", "... ... ... \n", - "2749929 3.937425 1 \n", - "2749970 5.523326 1 \n", - "2750003 6.289115 1 \n", - "2758909 6.677761 1 \n", - "2759348 5.760961 1 \n", + "2759076 6.481015 1 \n", + "2759264 6.343830 1 \n", + "2759425 4.507081 6 \n", + "2760422 4.345421 1 \n", + "2760425 3.586974 1 \n", "\n", - "[1028 rows x 130 columns]" + "[13210 rows x 130 columns]" ] }, "execution_count": 6, @@ -1271,17 +1333,10 @@ "execution_count": 7, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

Iteration 067 [Optimization terminated successfully]

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Iteration 061 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1293,7 +1348,7 @@ { "data": { "text/html": [ - "

Best LL = -391.31509615209995

" + "

Best LL = -5583.026333343983

" ], "text/plain": [ "" @@ -1324,70 +1379,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_asc_0_tours\n", " 0.000000\n", + " 0.000000\n", " 0.0000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_asc_1_Disc\n", - " -5.857843\n", + " -5.351766\n", + " -5.351766\n", " -5.4806\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -5.857843\n", " \n", " \n", " coef_asc_1_Eat\n", - " -5.140469\n", + " -6.074061\n", + " -6.074061\n", " -6.3757\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -5.140469\n", " \n", " \n", " coef_asc_1_Main\n", - " -4.843654\n", + " -5.816690\n", + " -5.816690\n", " -5.7389\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.843654\n", " \n", " \n", " coef_asc_1_Shop\n", - " -7.244895\n", + " -6.045190\n", + " -6.045190\n", " -6.0149\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -7.244895\n", " \n", " \n", " ...\n", @@ -1398,124 +1457,97 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", " coef_universityNonMandMaxThree_shopping\n", - " 1.134054\n", + " 0.857729\n", + " 0.857729\n", " 0.7648\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.134054\n", " \n", " \n", " coef_universityNonMandMaxThree_visiting\n", - " -18.048773\n", + " 0.282416\n", + " 0.282416\n", " 0.2809\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -18.048773\n", " \n", " \n", " coef_walkRetailAccessibility_eatout\n", - " -0.027363\n", + " 0.042572\n", + " 0.042572\n", " 0.0620\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.027363\n", " \n", " \n", " coef_zeroAutomobiles_disc\n", - " -0.539939\n", + " -0.953758\n", + " -0.953758\n", " -0.9090\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.539939\n", " \n", " \n", " coef_zeroAutomobiles_visiting\n", - " -18.311268\n", + " -0.900518\n", + " -0.900518\n", " -0.9800\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -18.311268\n", " \n", " \n", "\n", - "

76 rows × 8 columns

\n", + "

76 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue nullvalue \\\n", - "coef_asc_0_tours 0.000000 0.0000 0.0 \n", - "coef_asc_1_Disc -5.857843 -5.4806 0.0 \n", - "coef_asc_1_Eat -5.140469 -6.3757 0.0 \n", - "coef_asc_1_Main -4.843654 -5.7389 0.0 \n", - "coef_asc_1_Shop -7.244895 -6.0149 0.0 \n", - "... ... ... ... \n", - "coef_universityNonMandMaxThree_shopping 1.134054 0.7648 0.0 \n", - "coef_universityNonMandMaxThree_visiting -18.048773 0.2809 0.0 \n", - "coef_walkRetailAccessibility_eatout -0.027363 0.0620 0.0 \n", - "coef_zeroAutomobiles_disc -0.539939 -0.9090 0.0 \n", - "coef_zeroAutomobiles_visiting -18.311268 -0.9800 0.0 \n", + " value best initvalue \\\n", + "param_name \n", + "coef_asc_0_tours 0.000000 0.000000 0.0000 \n", + "coef_asc_1_Disc -5.351766 -5.351766 -5.4806 \n", + "coef_asc_1_Eat -6.074061 -6.074061 -6.3757 \n", + "coef_asc_1_Main -5.816690 -5.816690 -5.7389 \n", + "coef_asc_1_Shop -6.045190 -6.045190 -6.0149 \n", + "... ... ... ... \n", + "coef_universityNonMandMaxThree_shopping 0.857729 0.857729 0.7648 \n", + "coef_universityNonMandMaxThree_visiting 0.282416 0.282416 0.2809 \n", + "coef_walkRetailAccessibility_eatout 0.042572 0.042572 0.0620 \n", + "coef_zeroAutomobiles_disc -0.953758 -0.953758 -0.9090 \n", + "coef_zeroAutomobiles_visiting -0.900518 -0.900518 -0.9800 \n", "\n", - " minimum maximum holdfast note \\\n", - "coef_asc_0_tours NaN NaN 1 \n", - "coef_asc_1_Disc NaN NaN 0 \n", - "coef_asc_1_Eat NaN NaN 0 \n", - "coef_asc_1_Main NaN NaN 0 \n", - "coef_asc_1_Shop NaN NaN 0 \n", - "... ... ... ... ... \n", - "coef_universityNonMandMaxThree_shopping NaN NaN 0 \n", - "coef_universityNonMandMaxThree_visiting NaN NaN 0 \n", - "coef_walkRetailAccessibility_eatout NaN NaN 0 \n", - "coef_zeroAutomobiles_disc NaN NaN 0 \n", - "coef_zeroAutomobiles_visiting NaN NaN 0 \n", + " minimum maximum nullvalue holdfast \n", + "param_name \n", + "coef_asc_0_tours 0.0 0.0 0.0 1 \n", + "coef_asc_1_Disc -50.0 50.0 0.0 0 \n", + "coef_asc_1_Eat -50.0 50.0 0.0 0 \n", + "coef_asc_1_Main -50.0 50.0 0.0 0 \n", + "coef_asc_1_Shop -50.0 50.0 0.0 0 \n", + "... ... ... ... ... \n", + "coef_universityNonMandMaxThree_shopping -50.0 50.0 0.0 0 \n", + "coef_universityNonMandMaxThree_visiting -50.0 50.0 0.0 0 \n", + "coef_walkRetailAccessibility_eatout -50.0 50.0 0.0 0 \n", + "coef_zeroAutomobiles_disc -50.0 50.0 0.0 0 \n", + "coef_zeroAutomobiles_visiting -50.0 50.0 0.0 0 \n", "\n", - " best \n", - "coef_asc_0_tours 0.000000 \n", - "coef_asc_1_Disc -5.857843 \n", - "coef_asc_1_Eat -5.140469 \n", - "coef_asc_1_Main -4.843654 \n", - "coef_asc_1_Shop -7.244895 \n", - "... ... \n", - "coef_universityNonMandMaxThree_shopping 1.134054 \n", - "coef_universityNonMandMaxThree_visiting -18.048773 \n", - "coef_walkRetailAccessibility_eatout -0.027363 \n", - "coef_zeroAutomobiles_disc -0.539939 \n", - "coef_zeroAutomobiles_visiting -18.311268 \n", - "\n", - "[76 rows x 8 columns]" + "[76 rows x 7 columns]" ] }, "metadata": {}, "output_type": "display_data" }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate(method='SLSQP')\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.4504151870310519e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n" - ] - }, { "data": { "text/html": [ @@ -1529,310 +1561,310 @@ " \n", " \n", " coef_asc_0_tours\n", - " 4.128662e-14\n", + " 0.000000\n", " \n", " \n", " coef_asc_1_Disc\n", - " -5.857843e+00\n", + " -5.351766\n", " \n", " \n", " coef_asc_1_Eat\n", - " -5.140469e+00\n", + " -6.074061\n", " \n", " \n", " coef_asc_1_Main\n", - " -4.843654e+00\n", + " -5.816690\n", " \n", " \n", " coef_asc_1_Shop\n", - " -7.244895e+00\n", + " -6.045190\n", " \n", " \n", " coef_asc_1_Visit\n", - " -5.962149e+00\n", + " -5.839951\n", " \n", " \n", " coef_asc_2_tours\n", - " -1.537957e+01\n", + " -14.545006\n", " \n", " \n", " coef_drivingAgeStuMandMaxThree_disc\n", - " 2.642061e-01\n", + " 0.283573\n", " \n", " \n", " coef_drivingAgeStuMandMaxThree_maint\n", - " -2.049784e-01\n", + " -0.332304\n", " \n", " \n", " coef_fewerCarsThanDrivers_maint\n", - " -2.361602e-01\n", + " 0.768933\n", " \n", " \n", " coef_fewerCarsThanDrivers_shopping\n", - " 6.120417e-01\n", + " 0.173631\n", " \n", " \n", " coef_fullTimeHomeMaxThree_zero_tours\n", - " 2.001437e+00\n", + " 0.941096\n", " \n", " \n", " coef_fullTimeMandMaxThree_maint\n", - " -4.624882e-01\n", + " -0.397212\n", " \n", " \n", " coef_fullTimeMandMaxThree_shopping\n", - " 1.435394e-01\n", + " -0.402774\n", " \n", " \n", " coef_fullTimeNonMandMaxThree_disc\n", - " 2.181760e-01\n", + " -0.019740\n", " \n", " \n", " coef_fullTimeNonMandMaxThree_eatout\n", - " 3.257307e-01\n", + " 0.053619\n", " \n", " \n", " coef_fullTimeNonMandMaxThree_maint\n", - " 7.596262e-01\n", + " 0.114785\n", " \n", " \n", " coef_fullTimeNonMandMaxThree_shopping\n", - " -8.881290e-01\n", + " -0.253055\n", " \n", " \n", " coef_fullTimeNonMandMaxThree_visiting\n", - " 7.885926e-01\n", + " 0.750690\n", " \n", " \n", " coef_incomeBetween50And100_disc\n", - " 8.352921e-03\n", + " 0.132487\n", " \n", " \n", " coef_incomeBetween50And100_eatout\n", - " 1.031886e-01\n", + " 0.268954\n", " \n", " \n", " coef_incomeGreaterThan100_disc\n", - " 6.249345e-01\n", + " 0.366581\n", " \n", " \n", " coef_incomeGreaterThan100_eatout\n", - " 6.353587e-01\n", + " 0.493932\n", " \n", " \n", " coef_incomeMissing_dummy_always_zero_disc\n", - " 3.723000e-01\n", + " 0.372300\n", " \n", " \n", " coef_incomeMissing_dummy_always_zero_eatout\n", - " 2.780000e-01\n", + " 0.278000\n", " \n", " \n", " coef_logTimeWindowOverlapAdultChild_disc\n", - " 1.502560e-01\n", + " 0.303504\n", " \n", " \n", " coef_logTimeWindowOverlapAdultChild_eatout\n", - " -3.203806e-01\n", + " -0.094351\n", " \n", " \n", " coef_logTimeWindowOverlapAdultChild_maint\n", - " 2.695922e-01\n", + " 0.398958\n", " \n", " \n", " coef_logTimeWindowOverlapAdultChild_shopping\n", - " -4.153246e-01\n", + " 0.017970\n", " \n", " \n", " coef_logTimeWindowOverlapAdult_disc\n", - " 5.596579e-01\n", + " 0.411850\n", " \n", " \n", " coef_logTimeWindowOverlapAdult_eatout\n", - " 5.606143e-01\n", + " 0.467283\n", " \n", " \n", " coef_logTimeWindowOverlapAdult_maint\n", - " 4.376387e-01\n", + " 0.359818\n", " \n", " \n", " coef_logTimeWindowOverlapAdult_shopping\n", - " 8.640588e-01\n", + " 0.862228\n", " \n", " \n", " coef_logTimeWindowOverlapChild_disc\n", - " -1.693893e-01\n", + " 0.150068\n", " \n", " \n", " coef_logTimeWindowOverlapChild_maint\n", - " -1.037855e-02\n", + " 0.295107\n", " \n", " \n", " coef_logTimeWindowOverlapChild_shopping\n", - " 1.036654e+00\n", + " 0.255944\n", " \n", " \n", " coef_moreCarsThanWorkers_eatout\n", - " 7.948089e-02\n", + " 0.294865\n", " \n", " \n", " coef_moreCarsThanWorkers_shopping\n", - " -6.278022e-01\n", + " -0.551877\n", " \n", " \n", " coef_nonWorkerHomeMaxThree_zero_tours\n", - " -1.694121e-01\n", + " 0.379269\n", " \n", " \n", " coef_nonWorkerNonMandMaxThree_disc\n", - " -1.190124e-01\n", + " 0.120934\n", " \n", " \n", " coef_nonWorkerNonMandMaxThree_eatout\n", - " -3.544771e-01\n", + " 0.045074\n", " \n", " \n", " coef_nonWorkerNonMandMaxThree_maint\n", - " 3.725508e-01\n", + " 0.351215\n", " \n", " \n", " coef_nonWorkerNonMandMaxThree_shopping\n", - " 5.232632e-01\n", + " 0.422604\n", " \n", " \n", " coef_nonWorkerNonMandMaxThree_visiting\n", - " -3.598996e-01\n", + " 0.454085\n", " \n", " \n", " coef_partTimeHomeMaxThree_zero_tours\n", - " 1.700075e+00\n", + " 0.928683\n", " \n", " \n", " coef_partTimeNonMandMaxThree_disc\n", - " 2.264406e-01\n", + " 0.668232\n", " \n", " \n", " coef_partTimeNonMandMaxThree_eatout\n", - " -1.577062e+01\n", + " 0.381935\n", " \n", " \n", " coef_partTimeNonMandMaxThree_maint\n", - " 1.215592e-01\n", + " 0.071116\n", " \n", " \n", " coef_partTimeNonMandMaxThree_shopping\n", - " -1.914973e-01\n", + " -0.021127\n", " \n", " \n", " coef_partTimeNonMandMaxThree_visiting\n", - " 3.484080e-01\n", + " 0.417675\n", " \n", " \n", " coef_preDrivingAgeMandMaxThree_disc\n", - " 5.883044e-01\n", + " 0.133605\n", " \n", " \n", " coef_preDrivingAgeMandMaxThree_maint\n", - " 5.724992e-02\n", + " 0.065271\n", " \n", " \n", " coef_preDrivingHomeMaxThree_preschool_and_school_zero_tours\n", - " -2.649396e-01\n", + " 0.086034\n", " \n", " \n", " coef_preDrivingNonMandMaxThree_disc\n", - " 4.697889e-01\n", + " 0.189119\n", " \n", " \n", " coef_preDrivingNonMandMaxThree_eatout\n", - " -1.367435e+01\n", + " 0.700510\n", " \n", " \n", " coef_preDrivingNonMandMaxThree_maint\n", - " -4.780032e-01\n", + " 0.163703\n", " \n", " \n", " coef_preDrivingNonMandMaxThree_shopping\n", - " 5.401680e-03\n", + " 0.448199\n", " \n", " \n", " coef_preDrivingNonMandMaxThree_visiting\n", - " -1.728326e+00\n", + " 0.241003\n", " \n", " \n", " coef_retireeHomeMaxThree_zero_tours\n", - " 3.072054e-01\n", + " 0.332620\n", " \n", " \n", " coef_retireeNonMandMaxThree_disc\n", - " 5.953927e-01\n", + " 0.596927\n", " \n", " \n", " coef_retireeNonMandMaxThree_eatout\n", - " 3.370647e-01\n", + " 0.444051\n", " \n", " \n", " coef_retireeNonMandMaxThree_maint\n", - " 9.306423e-01\n", + " 0.935537\n", " \n", " \n", " coef_retireeNonMandMaxThree_shopping\n", - " 9.523557e-01\n", + " 0.888533\n", " \n", " \n", " coef_retireeNonMandMaxThree_visiting\n", - " 1.743228e-01\n", + " 0.313616\n", " \n", " \n", " coef_timeWindowOverlapAdultChild_visiting\n", - " 1.404939e-01\n", + " 0.032122\n", " \n", " \n", " coef_timeWindowOverlapAdult_visiting\n", - " 1.103018e-01\n", + " 0.062728\n", " \n", " \n", " coef_timeWindowOverlapChild_visiting\n", - " -6.064464e-02\n", + " 0.037481\n", " \n", " \n", " coef_universityHomeMaxThree_univ_and_driving_zero_tours\n", - " -4.104066e-01\n", + " 0.115748\n", " \n", " \n", " coef_universityNonMandMaxThree_disc\n", - " -1.447281e-01\n", + " 0.478898\n", " \n", " \n", " coef_universityNonMandMaxThree_eatout\n", - " -1.408027e+01\n", + " 0.447854\n", " \n", " \n", " coef_universityNonMandMaxThree_maint\n", - " -4.377287e-01\n", + " -0.157965\n", " \n", " \n", " coef_universityNonMandMaxThree_shopping\n", - " 1.134054e+00\n", + " 0.857729\n", " \n", " \n", " coef_universityNonMandMaxThree_visiting\n", - " -1.804877e+01\n", + " 0.282416\n", " \n", " \n", " coef_walkRetailAccessibility_eatout\n", - " -2.736284e-02\n", + " 0.042572\n", " \n", " \n", " coef_zeroAutomobiles_disc\n", - " -5.399391e-01\n", + " -0.953758\n", " \n", " \n", " coef_zeroAutomobiles_visiting\n", - " -1.831127e+01\n", + " -0.900518\n", " \n", " \n", - "loglike-391.31509615209995d_loglike\n", + "
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coef_asc_0_tours0.000000e+000.000000
coef_asc_1_Disc1.523003e-040.000127
coef_asc_1_Eat6.759891e-050.000172
coef_asc_1_Main-2.935726e-04-0.000055
coef_asc_1_Shop-2.605190e-04-0.000097
coef_asc_1_Visit-1.539399e-04-0.000019
coef_asc_2_tours-7.190405e-050.000045
coef_drivingAgeStuMandMaxThree_disc-1.208006e-040.000034
coef_drivingAgeStuMandMaxThree_maint6.022683e-050.000009
coef_fewerCarsThanDrivers_maint-1.544212e-040.000025
coef_fewerCarsThanDrivers_shopping-5.384239e-050.000060
coef_fullTimeHomeMaxThree_zero_tours-2.514724e-040.000088
coef_fullTimeMandMaxThree_maint-2.064152e-04-0.000002
coef_fullTimeMandMaxThree_shopping-2.409727e-040.000014
coef_fullTimeNonMandMaxThree_disc1.867895e-040.000047
coef_fullTimeNonMandMaxThree_eatout-5.229114e-050.000034
coef_fullTimeNonMandMaxThree_maint-1.708359e-04-0.000036
coef_fullTimeNonMandMaxThree_shopping-8.986588e-050.000025
coef_fullTimeNonMandMaxThree_visiting-1.238448e-040.000019
coef_incomeBetween50And100_disc-3.214932e-040.000033
coef_incomeBetween50And100_eatout2.548977e-050.000004
coef_incomeGreaterThan100_disc1.527594e-050.000088
coef_incomeGreaterThan100_eatout-1.190833e-04-0.000003
coef_incomeMissing_dummy_always_zero_disc0.000000e+000.000000
coef_incomeMissing_dummy_always_zero_eatout0.000000e+000.000000
coef_logTimeWindowOverlapAdultChild_disc6.268423e-040.000322
coef_logTimeWindowOverlapAdultChild_eatout4.738068e-050.000270
coef_logTimeWindowOverlapAdultChild_maint-5.205643e-040.000069
coef_logTimeWindowOverlapAdultChild_shopping-7.016522e-040.000017
coef_logTimeWindowOverlapAdult_disc8.132405e-040.000280
coef_logTimeWindowOverlapAdult_eatout-5.191213e-050.000106
coef_logTimeWindowOverlapAdult_maint-7.074150e-04-0.000079
coef_logTimeWindowOverlapAdult_shopping-9.068285e-040.000016
coef_logTimeWindowOverlapChild_disc3.313056e-040.000050
coef_logTimeWindowOverlapChild_maint-3.411335e-04-0.000033
coef_logTimeWindowOverlapChild_shopping-6.088923e-040.000003
coef_moreCarsThanWorkers_eatout-1.693804e-040.000019
coef_moreCarsThanWorkers_shopping-7.535132e-05-0.000021
coef_nonWorkerHomeMaxThree_zero_tours1.546204e-04-0.000071
coef_nonWorkerNonMandMaxThree_disc2.251574e-04-0.000004
coef_nonWorkerNonMandMaxThree_eatout4.969366e-070.000084
coef_nonWorkerNonMandMaxThree_maint-8.922162e-050.000060
coef_nonWorkerNonMandMaxThree_shopping-2.254530e-04-0.000095
coef_nonWorkerNonMandMaxThree_visiting1.544757e-040.000032
coef_partTimeHomeMaxThree_zero_tours-5.144981e-050.000005
coef_partTimeNonMandMaxThree_disc1.814241e-040.000060
coef_partTimeNonMandMaxThree_eatout-3.175600e-07-0.000002
coef_partTimeNonMandMaxThree_maint-1.133846e-040.000030
coef_partTimeNonMandMaxThree_shopping1.063172e-040.000027
coef_partTimeNonMandMaxThree_visiting1.329104e-05-0.000037
coef_preDrivingAgeMandMaxThree_disc4.323394e-040.000164
coef_preDrivingAgeMandMaxThree_maint-1.660229e-040.000015
coef_preDrivingHomeMaxThree_preschool_and_school_zero_tours2.715906e-040.000030
coef_preDrivingNonMandMaxThree_disc9.520881e-050.000037
coef_preDrivingNonMandMaxThree_eatout-7.286290e-070.000027
coef_preDrivingNonMandMaxThree_maint-8.707705e-05-0.000060
coef_preDrivingNonMandMaxThree_shopping-7.017908e-050.000009
coef_preDrivingNonMandMaxThree_visiting1.106056e-040.000014
coef_retireeHomeMaxThree_zero_tours-3.000796e-040.000050
coef_retireeNonMandMaxThree_disc3.955978e-050.000028
coef_retireeNonMandMaxThree_eatout-8.864118e-05-0.000012
coef_retireeNonMandMaxThree_maint1.123175e-05-0.000058
coef_retireeNonMandMaxThree_shopping-8.375532e-050.000009
coef_retireeNonMandMaxThree_visiting-7.291644e-050.000075
coef_timeWindowOverlapAdultChild_visiting1.533203e-03-0.000362
coef_timeWindowOverlapAdult_visiting-4.187359e-040.000189
coef_timeWindowOverlapChild_visiting1.535922e-03-0.000253
coef_universityHomeMaxThree_univ_and_driving_zero_tours-2.916835e-040.000140
coef_universityNonMandMaxThree_disc4.189163e-050.000095
coef_universityNonMandMaxThree_eatout-6.392369e-070.000004
coef_universityNonMandMaxThree_maint-2.743951e-05-0.000123
coef_universityNonMandMaxThree_shopping-1.669075e-040.000013
coef_universityNonMandMaxThree_visiting-3.279064e-08-0.000090
coef_walkRetailAccessibility_eatout-3.988777e-040.000218
coef_zeroAutomobiles_disc-5.720641e-05-0.000027
coef_zeroAutomobiles_visiting-5.437687e-080.000058
nit67nfev131njev67status0message'Optimization terminated successfully'successTrueelapsed_time0:00:03.730310method'SLSQP'n_cases1028iteration_number67logloss0.3806567083191634" + "nit61nfev63njev61status0message'Optimization terminated successfully'successTrueelapsed_time0:00:02.374665method'SLSQP'n_cases13210iteration_number61loglike-5583.026333343983" ], "text/plain": [ - "┣ x: coef_asc_0_tours 4.128662e-14\n", - "┃ coef_asc_1_Disc -5.857843e+00\n", - "┃ coef_asc_1_Eat -5.140469e+00\n", - "┃ coef_asc_1_Main -4.843654e+00\n", - "┃ coef_asc_1_Shop -7.244895e+00\n", - "┃ ... \n", - "┃ coef_universityNonMandMaxThree_shopping 1.134054e+00\n", - "┃ coef_universityNonMandMaxThree_visiting -1.804877e+01\n", - "┃ coef_walkRetailAccessibility_eatout -2.736284e-02\n", - "┃ coef_zeroAutomobiles_disc -5.399391e-01\n", - "┃ coef_zeroAutomobiles_visiting -1.831127e+01\n", + "┣ x: coef_asc_0_tours 0.000000\n", + "┃ coef_asc_1_Disc -5.351766\n", + "┃ coef_asc_1_Eat -6.074061\n", + "┃ coef_asc_1_Main -5.816690\n", + "┃ coef_asc_1_Shop -6.045190\n", + "┃ ... \n", + "┃ coef_universityNonMandMaxThree_shopping 0.857729\n", + "┃ coef_universityNonMandMaxThree_visiting 0.282416\n", + "┃ coef_walkRetailAccessibility_eatout 0.042572\n", + "┃ coef_zeroAutomobiles_disc -0.953758\n", + "┃ coef_zeroAutomobiles_visiting -0.900518\n", "┃ Length: 76, dtype: float64\n", - "┣ loglike: -391.31509615209995\n", - "┣ d_loglike: coef_asc_0_tours 0.000000e+00\n", - "┃ coef_asc_1_Disc 1.523003e-04\n", - "┃ coef_asc_1_Eat 6.759891e-05\n", - "┃ coef_asc_1_Main -2.935726e-04\n", - "┃ coef_asc_1_Shop -2.605190e-04\n", - "┃ ... \n", - "┃ coef_universityNonMandMaxThree_shopping -1.669075e-04\n", - "┃ coef_universityNonMandMaxThree_visiting -3.279064e-08\n", - "┃ coef_walkRetailAccessibility_eatout -3.988777e-04\n", - "┃ coef_zeroAutomobiles_disc -5.720641e-05\n", - "┃ coef_zeroAutomobiles_visiting -5.437687e-08\n", + "┣ logloss: 0.4226363613432236\n", + "┣ d_logloss: coef_asc_0_tours 0.000000\n", + "┃ coef_asc_1_Disc 0.000127\n", + "┃ coef_asc_1_Eat 0.000172\n", + "┃ coef_asc_1_Main -0.000055\n", + "┃ coef_asc_1_Shop -0.000097\n", + "┃ ... \n", + "┃ coef_universityNonMandMaxThree_shopping 0.000013\n", + "┃ coef_universityNonMandMaxThree_visiting -0.000090\n", + "┃ coef_walkRetailAccessibility_eatout 0.000218\n", + "┃ coef_zeroAutomobiles_disc -0.000027\n", + "┃ coef_zeroAutomobiles_visiting 0.000058\n", "┃ Length: 76, dtype: float64\n", - "┣ nit: 67\n", - "┣ nfev: 131\n", - "┣ njev: 67\n", + "┣ nit: 61\n", + "┣ nfev: 63\n", + "┣ njev: 61\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=3, microseconds=730310)\n", + "┣ elapsed_time: datetime.timedelta(seconds=2, microseconds=374665)\n", "┣ method: 'SLSQP'\n", - "┣ n_cases: 1028\n", - "┣ iteration_number: 67\n", - "┣ logloss: 0.3806567083191634" + "┣ n_cases: 13210\n", + "┣ iteration_number: 61\n", + "┣ loglike: -5583.026333343983" ] }, "execution_count": 7, @@ -2210,704 +2242,730 @@ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Null Value Constrained
coef_asc_0_tours 0.00 NA NA 0.00fixed value
coef_asc_1_Disc-5.86 1.09-5.39*** 0.00
coef_asc_1_Eat-5.14 2.07-2.48* 0.00
coef_asc_1_Main-4.84 0.973-4.98*** 0.00
coef_asc_1_Shop-7.24 1.18-6.14*** 0.00
coef_asc_1_Visit-5.96 0.749-7.96*** 0.00
coef_asc_2_tours-15.4 2.26-6.81*** 0.00
coef_drivingAgeStuMandMaxThree_disc 0.264 0.406 0.65 0.00
coef_drivingAgeStuMandMaxThree_maint-0.205 0.491-0.42 0.00
coef_fewerCarsThanDrivers_maint-0.236 0.439-0.54 0.00
coef_fewerCarsThanDrivers_shopping 0.612 0.596 1.03 0.00
coef_fullTimeHomeMaxThree_zero_tours 2.00 0.828 2.42* 0.00
coef_fullTimeMandMaxThree_maint-0.462 0.313-1.48 0.00
coef_fullTimeMandMaxThree_shopping 0.144 0.288 0.50 0.00
coef_fullTimeNonMandMaxThree_disc 0.218 0.569 0.38 0.00
coef_fullTimeNonMandMaxThree_eatout 0.326 0.669 0.49 0.00
coef_fullTimeNonMandMaxThree_maint 0.760 0.430 1.77 0.00
coef_fullTimeNonMandMaxThree_shopping-0.888 1.03-0.86 0.00
coef_fullTimeNonMandMaxThree_visiting 0.789 0.626 1.26 0.00
coef_incomeBetween50And100_disc 0.00835 0.621 0.01 0.00
coef_incomeBetween50And100_eatout 0.103 0.741 0.14 0.00
coef_incomeGreaterThan100_disc 0.625 0.562 1.11 0.00
coef_incomeGreaterThan100_eatout 0.635 0.684 0.93 0.00
coef_incomeMissing_dummy_always_zero_disc 0.372 0.000320 BIG*** 0.00
coef_incomeMissing_dummy_always_zero_eatout 0.278 0.000386 720.45*** 0.00
coef_logTimeWindowOverlapAdultChild_disc 0.150 0.322 0.47 0.00
coef_logTimeWindowOverlapAdultChild_eatout-0.320 0.337-0.95 0.00
coef_logTimeWindowOverlapAdultChild_maint 0.270 0.294 0.92 0.00
coef_logTimeWindowOverlapAdultChild_shopping-0.415 0.493-0.84 0.00
coef_logTimeWindowOverlapAdult_disc 0.560 0.501 1.12 0.00
coef_logTimeWindowOverlapAdult_eatout 0.561 0.692 0.81 0.00
coef_logTimeWindowOverlapAdult_maint 0.438 0.430 1.02 0.00
coef_logTimeWindowOverlapAdult_shopping 0.864 0.553 1.56 0.00
coef_logTimeWindowOverlapChild_disc-0.169 0.433-0.39 0.00
coef_logTimeWindowOverlapChild_maint-0.0104 0.373-0.03 0.00
coef_logTimeWindowOverlapChild_shopping 1.04 0.543 1.91 0.00
coef_moreCarsThanWorkers_eatout 0.0795 0.805 0.10 0.00
coef_moreCarsThanWorkers_shopping-0.628 0.690-0.91 0.00
coef_nonWorkerHomeMaxThree_zero_tours-0.169 0.391-0.43 0.00
coef_nonWorkerNonMandMaxThree_disc-0.119 0.447-0.27 0.00
coef_nonWorkerNonMandMaxThree_eatout-0.354 0.700-0.51 0.00
coef_nonWorkerNonMandMaxThree_maint 0.373 0.380 0.98 0.00
coef_nonWorkerNonMandMaxThree_shopping 0.523 0.427 1.23 0.00
coef_nonWorkerNonMandMaxThree_visiting-0.360 0.587-0.61 0.00
coef_partTimeHomeMaxThree_zero_tours 1.70 1.16 1.47 0.00
coef_partTimeNonMandMaxThree_disc 0.226 0.652 0.35 0.00
coef_partTimeNonMandMaxThree_eatout-15.8 2.42e+03-0.01 0.00
coef_partTimeNonMandMaxThree_maint 0.122 0.660 0.18 0.00
coef_partTimeNonMandMaxThree_shopping-0.191 0.769-0.25 0.00
coef_partTimeNonMandMaxThree_visiting 0.348 0.880 0.40 0.00
coef_preDrivingAgeMandMaxThree_disc 0.588 0.583 1.01 0.00
coef_preDrivingAgeMandMaxThree_maint 0.0572 0.514 0.11 0.00
coef_preDrivingHomeMaxThree_preschool_and_school_zero_tours-0.265 0.450-0.59 0.00
coef_preDrivingNonMandMaxThree_disc 0.470 0.853 0.55 0.00
coef_preDrivingNonMandMaxThree_eatout-13.7 1.56e+03-0.01 0.00
coef_preDrivingNonMandMaxThree_maint-0.478 0.924-0.52 0.00
coef_preDrivingNonMandMaxThree_shopping 0.00540 0.540 0.01 0.00
coef_preDrivingNonMandMaxThree_visiting-1.73 1.27-1.36 0.00
coef_retireeHomeMaxThree_zero_tours 0.307 0.771 0.40 0.00
coef_retireeNonMandMaxThree_disc 0.595 0.430 1.38 0.00
coef_retireeNonMandMaxThree_eatout 0.337 0.553 0.61 0.00
coef_retireeNonMandMaxThree_maint 0.931 0.376 2.47* 0.00
coef_retireeNonMandMaxThree_shopping 0.952 0.504 1.89 0.00
coef_retireeNonMandMaxThree_visiting 0.174 0.583 0.30 0.00
coef_timeWindowOverlapAdultChild_visiting 0.140 0.0547 2.57* 0.00
coef_timeWindowOverlapAdult_visiting 0.110 0.0692 1.59 0.00
coef_timeWindowOverlapChild_visiting-0.0606 0.0845-0.72 0.00
coef_universityHomeMaxThree_univ_and_driving_zero_tours-0.410 0.677-0.61 0.00
coef_universityNonMandMaxThree_disc-0.145 1.02-0.14 0.00
coef_universityNonMandMaxThree_eatout-14.1 1.67e+03-0.01 0.00
coef_universityNonMandMaxThree_maint-0.438 0.999-0.44 0.00
coef_universityNonMandMaxThree_shopping 1.13 0.556 2.04* 0.00
coef_universityNonMandMaxThree_visiting-18.0 7.88e+03-0.00 0.00
coef_walkRetailAccessibility_eatout-0.0274 0.237-0.12 0.00
coef_zeroAutomobiles_disc-0.540 0.771-0.70 0.00
coef_zeroAutomobiles_visiting-18.3 6.06e+03-0.00 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_asc_0_tours 0.00 0.00 NA 0.00fixed value
coef_asc_1_Disc-5.35 0.217-24.68*** 0.00
coef_asc_1_Eat-6.07 0.382-15.88*** 0.00
coef_asc_1_Main-5.82 0.255-22.80*** 0.00
coef_asc_1_Shop-6.05 0.301-20.07*** 0.00
coef_asc_1_Visit-5.84 0.198-29.56*** 0.00
coef_asc_2_tours-14.5 0.456-31.88*** 0.00
coef_drivingAgeStuMandMaxThree_disc 0.284 0.0868 3.27** 0.00
coef_drivingAgeStuMandMaxThree_maint-0.332 0.148-2.24* 0.00
coef_fewerCarsThanDrivers_maint 0.769 0.142 5.42*** 0.00
coef_fewerCarsThanDrivers_shopping 0.174 0.141 1.23 0.00
coef_fullTimeHomeMaxThree_zero_tours 0.941 0.164 5.75*** 0.00
coef_fullTimeMandMaxThree_maint-0.397 0.0912-4.36*** 0.00
coef_fullTimeMandMaxThree_shopping-0.403 0.0941-4.28*** 0.00
coef_fullTimeNonMandMaxThree_disc-0.0197 0.143-0.14 0.00
coef_fullTimeNonMandMaxThree_eatout 0.0536 0.215 0.25 0.00
coef_fullTimeNonMandMaxThree_maint 0.115 0.177 0.65 0.00
coef_fullTimeNonMandMaxThree_shopping-0.253 0.198-1.28 0.00
coef_fullTimeNonMandMaxThree_visiting 0.751 0.171 4.38*** 0.00
coef_incomeBetween50And100_disc 0.132 0.128 1.04 0.00
coef_incomeBetween50And100_eatout 0.269 0.199 1.35 0.00
coef_incomeGreaterThan100_disc 0.367 0.125 2.94** 0.00
coef_incomeGreaterThan100_eatout 0.494 0.197 2.51* 0.00
coef_incomeMissing_dummy_always_zero_disc 0.372 7.15e-16 BIG*** 0.00
coef_incomeMissing_dummy_always_zero_eatout 0.278 9.58e-16 BIG*** 0.00
coef_logTimeWindowOverlapAdultChild_disc 0.304 0.0645 4.70*** 0.00
coef_logTimeWindowOverlapAdultChild_eatout-0.0944 0.0788-1.20 0.00
coef_logTimeWindowOverlapAdultChild_maint 0.399 0.0847 4.71*** 0.00
coef_logTimeWindowOverlapAdultChild_shopping 0.0180 0.0764 0.24 0.00
coef_logTimeWindowOverlapAdult_disc 0.412 0.101 4.09*** 0.00
coef_logTimeWindowOverlapAdult_eatout 0.467 0.167 2.80** 0.00
coef_logTimeWindowOverlapAdult_maint 0.360 0.117 3.07** 0.00
coef_logTimeWindowOverlapAdult_shopping 0.862 0.139 6.18*** 0.00
coef_logTimeWindowOverlapChild_disc 0.150 0.0771 1.95 0.00
coef_logTimeWindowOverlapChild_maint 0.295 0.0952 3.10** 0.00
coef_logTimeWindowOverlapChild_shopping 0.256 0.0873 2.93** 0.00
coef_moreCarsThanWorkers_eatout 0.295 0.188 1.57 0.00
coef_moreCarsThanWorkers_shopping-0.552 0.165-3.35*** 0.00
coef_nonWorkerHomeMaxThree_zero_tours 0.379 0.110 3.46*** 0.00
coef_nonWorkerNonMandMaxThree_disc 0.121 0.0878 1.38 0.00
coef_nonWorkerNonMandMaxThree_eatout 0.0451 0.150 0.30 0.00
coef_nonWorkerNonMandMaxThree_maint 0.351 0.104 3.37*** 0.00
coef_nonWorkerNonMandMaxThree_shopping 0.423 0.110 3.85*** 0.00
coef_nonWorkerNonMandMaxThree_visiting 0.454 0.139 3.26** 0.00
coef_partTimeHomeMaxThree_zero_tours 0.929 0.250 3.71*** 0.00
coef_partTimeNonMandMaxThree_disc 0.668 0.123 5.42*** 0.00
coef_partTimeNonMandMaxThree_eatout 0.382 0.210 1.82 0.00
coef_partTimeNonMandMaxThree_maint 0.0711 0.193 0.37 0.00
coef_partTimeNonMandMaxThree_shopping-0.0211 0.183-0.12 0.00
coef_partTimeNonMandMaxThree_visiting 0.418 0.214 1.95 0.00
coef_preDrivingAgeMandMaxThree_disc 0.134 0.0986 1.36 0.00
coef_preDrivingAgeMandMaxThree_maint 0.0653 0.118 0.56 0.00
coef_preDrivingHomeMaxThree_preschool_and_school_zero_tours 0.0860 0.102 0.85 0.00
coef_preDrivingNonMandMaxThree_disc 0.189 0.160 1.19 0.00
coef_preDrivingNonMandMaxThree_eatout 0.701 0.195 3.60*** 0.00
coef_preDrivingNonMandMaxThree_maint 0.164 0.190 0.86 0.00
coef_preDrivingNonMandMaxThree_shopping 0.448 0.152 2.95** 0.00
coef_preDrivingNonMandMaxThree_visiting 0.241 0.196 1.23 0.00
coef_retireeHomeMaxThree_zero_tours 0.333 0.175 1.90 0.00
coef_retireeNonMandMaxThree_disc 0.597 0.107 5.56*** 0.00
coef_retireeNonMandMaxThree_eatout 0.444 0.160 2.77** 0.00
coef_retireeNonMandMaxThree_maint 0.936 0.123 7.59*** 0.00
coef_retireeNonMandMaxThree_shopping 0.889 0.123 7.22*** 0.00
coef_retireeNonMandMaxThree_visiting 0.314 0.190 1.65 0.00
coef_timeWindowOverlapAdultChild_visiting 0.0321 0.0152 2.12* 0.00
coef_timeWindowOverlapAdult_visiting 0.0627 0.0194 3.24** 0.00
coef_timeWindowOverlapChild_visiting 0.0375 0.0181 2.08* 0.00
coef_universityHomeMaxThree_univ_and_driving_zero_tours 0.116 0.210 0.55 0.00
coef_universityNonMandMaxThree_disc 0.479 0.144 3.33*** 0.00
coef_universityNonMandMaxThree_eatout 0.448 0.244 1.84 0.00
coef_universityNonMandMaxThree_maint-0.158 0.284-0.56 0.00
coef_universityNonMandMaxThree_shopping 0.858 0.157 5.46*** 0.00
coef_universityNonMandMaxThree_visiting 0.282 0.256 1.10 0.00
coef_walkRetailAccessibility_eatout 0.0426 0.0475 0.90 0.00
coef_zeroAutomobiles_disc-0.954 0.441-2.16* 0.00
coef_zeroAutomobiles_visiting-0.901 0.678-1.33 0.00
\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 8, @@ -2954,18 +3012,7 @@ "cell_type": "code", "execution_count": 10, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -3023,25 +3070,25 @@ " \n", " 1\n", " coef_asc_1_Shop\n", - " -7.244895\n", + " -6.045190\n", " F\n", " \n", " \n", " 2\n", " coef_asc_1_Main\n", - " -4.843654\n", + " -5.816690\n", " F\n", " \n", " \n", " 3\n", " coef_asc_1_Eat\n", - " -5.140469\n", + " -6.074061\n", " F\n", " \n", " \n", " 4\n", " coef_asc_1_Visit\n", - " -5.962149\n", + " -5.839951\n", " F\n", " \n", " \n", @@ -3053,19 +3100,19 @@ " \n", " 71\n", " coef_logTimeWindowOverlapAdultChild_disc\n", - " 0.150256\n", + " 0.303504\n", " F\n", " \n", " \n", " 72\n", " coef_incomeBetween50And100_disc\n", - " 0.008353\n", + " 0.132487\n", " F\n", " \n", " \n", " 73\n", " coef_incomeGreaterThan100_disc\n", - " 0.624935\n", + " 0.366581\n", " F\n", " \n", " \n", @@ -3077,7 +3124,7 @@ " \n", " 75\n", " coef_zeroAutomobiles_disc\n", - " -0.539939\n", + " -0.953758\n", " F\n", " \n", " \n", @@ -3088,16 +3135,16 @@ "text/plain": [ " coefficient_name value constrain\n", "0 coef_asc_0_tours 0.000000 T\n", - "1 coef_asc_1_Shop -7.244895 F\n", - "2 coef_asc_1_Main -4.843654 F\n", - "3 coef_asc_1_Eat -5.140469 F\n", - "4 coef_asc_1_Visit -5.962149 F\n", + "1 coef_asc_1_Shop -6.045190 F\n", + "2 coef_asc_1_Main -5.816690 F\n", + "3 coef_asc_1_Eat -6.074061 F\n", + "4 coef_asc_1_Visit -5.839951 F\n", ".. ... ... ...\n", - "71 coef_logTimeWindowOverlapAdultChild_disc 0.150256 F\n", - "72 coef_incomeBetween50And100_disc 0.008353 F\n", - "73 coef_incomeGreaterThan100_disc 0.624935 F\n", + "71 coef_logTimeWindowOverlapAdultChild_disc 0.303504 F\n", + "72 coef_incomeBetween50And100_disc 0.132487 F\n", + "73 coef_incomeGreaterThan100_disc 0.366581 F\n", "74 coef_incomeMissing_dummy_always_zero_disc 0.372300 F\n", - "75 coef_zeroAutomobiles_disc -0.539939 F\n", + "75 coef_zeroAutomobiles_disc -0.953758 F\n", "\n", "[76 rows x 3 columns]" ] @@ -3119,7 +3166,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -3133,7 +3180,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/11_joint_tour_composition.ipynb b/activitysim/examples/example_estimation/notebooks/11_joint_tour_composition.ipynb index 89c68c52f7..99bd4cc7cd 100644 --- a/activitysim/examples/example_estimation/notebooks/11_joint_tour_composition.ipynb +++ b/activitysim/examples/example_estimation/notebooks/11_joint_tour_composition.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +115,27 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/joint_tour_composition/joint_tour_composition_coefficients.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/joint_tour_composition/joint_tour_composition_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_composition/joint_tour_composition_values_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"joint_tour_composition\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -798,8 +860,8 @@ " \n", " \n", " \n", - " 189758\n", - " 7785298\n", + " 190592\n", + " 7853686\n", " adults\n", " adults\n", " 1.0\n", @@ -807,23 +869,23 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 2.0\n", " 0.0\n", + " 2.0\n", " ...\n", - " 0.000\n", + " 0.000000\n", " 0.0\n", " 0.0\n", - " 2.0\n", " 0.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " False\n", + " True\n", " 1\n", " \n", " \n", - " 201016\n", - " 8708454\n", + " 191185\n", + " 7902318\n", " adults\n", " adults\n", " 1.0\n", @@ -831,23 +893,23 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 2.0\n", " 0.0\n", + " 2.0\n", " ...\n", - " 0.000\n", + " 0.000000\n", " 0.0\n", " 0.0\n", - " 2.0\n", " 0.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " False\n", + " True\n", " 1\n", " \n", " \n", - " 213291\n", - " 9715006\n", + " 191276\n", + " 7909776\n", " adults\n", " adults\n", " 1.0\n", @@ -855,14 +917,14 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 2.0\n", " 0.0\n", + " 2.0\n", " ...\n", - " 0.000\n", + " 0.000000\n", " 0.0\n", " 0.0\n", - " 2.0\n", " 0.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -870,8 +932,8 @@ " 1\n", " \n", " \n", - " 226902\n", - " 10831112\n", + " 192239\n", + " 7988742\n", " adults\n", " adults\n", " 1.0\n", @@ -879,43 +941,43 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 2.0\n", " 0.0\n", + " 1.0\n", " ...\n", - " 0.000\n", + " 0.000000\n", " 0.0\n", " 0.0\n", - " 2.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " False\n", + " True\n", " 1\n", " \n", " \n", - " 337259\n", - " 20334787\n", - " mixed\n", - " mixed\n", + " 193643\n", + " 8103874\n", + " adults\n", + " adults\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " 1.0\n", " ...\n", - " 2.197\n", - " 1.0\n", + " 0.000000\n", + " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " False\n", - " 3\n", + " 0.0\n", + " True\n", + " 1\n", " \n", " \n", " ...\n", @@ -942,8 +1004,8 @@ " ...\n", " \n", " \n", - " 2628704\n", - " 283676518\n", + " 2753390\n", + " 303771147\n", " mixed\n", " mixed\n", " 1.0\n", @@ -954,7 +1016,7 @@ " 0.0\n", " 0.0\n", " ...\n", - " 2.398\n", + " 2.708984\n", " 3.0\n", " 0.0\n", " 0.0\n", @@ -962,252 +1024,252 @@ " 2.0\n", " 0.0\n", " 0.0\n", - " False\n", + " True\n", " 3\n", " \n", " \n", - " 2678969\n", - " 295260168\n", - " adults\n", - " adults\n", + " 2754817\n", + " 304144212\n", + " mixed\n", + " mixed\n", " 1.0\n", " 0.0\n", " 0.0\n", " 3.0\n", - " 1.0\n", " 0.0\n", - " 3.0\n", + " 0.0\n", + " 2.0\n", " ...\n", - " 2.080\n", + " 2.996094\n", " 3.0\n", - " 1.0\n", " 0.0\n", - " 3.0\n", - " 1.0\n", + " 0.0\n", + " 2.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " False\n", - " 1\n", + " 3\n", " \n", " \n", - " 2704338\n", - " 297646485\n", - " adults\n", - " adults\n", + " 2756049\n", + " 304463637\n", + " mixed\n", + " mixed\n", " 1.0\n", " 0.0\n", " 0.0\n", + " 3.0\n", " 0.0\n", - " 0.0\n", - " 0.0\n", + " 2.0\n", " 0.0\n", " ...\n", - " 0.000\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 2.484375\n", + " 3.0\n", " 0.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " True\n", - " 1\n", + " 3\n", " \n", " \n", - " 2718585\n", - " 298814741\n", - " adults\n", - " adults\n", + " 2758936\n", + " 305125582\n", + " children\n", + " mixed\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 2.0\n", " 1.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 0.000\n", - " 0.0\n", + " 2.564453\n", + " 2.0\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 3.0\n", " 0.0\n", " False\n", - " 1\n", + " 3\n", " \n", " \n", - " 2744529\n", - " 301810980\n", - " adults\n", - " adults\n", + " 2759425\n", + " 305246245\n", + " mixed\n", + " mixed\n", " 1.0\n", " 0.0\n", " 0.0\n", + " 1.0\n", " 2.0\n", - " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " ...\n", - " 0.000\n", + " 2.996094\n", + " 1.0\n", " 2.0\n", + " 1.0\n", " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " False\n", - " 1\n", + " 3\n", " \n", " \n", "\n", - "

91 rows × 87 columns

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1277 rows × 87 columns

\n", "" ], "text/plain": [ " tour_id model_choice override_choice util_asc \\\n", "household_id \n", - "189758 7785298 adults adults 1.0 \n", - "201016 8708454 adults adults 1.0 \n", - "213291 9715006 adults adults 1.0 \n", - "226902 10831112 adults adults 1.0 \n", - "337259 20334787 mixed mixed 1.0 \n", + "190592 7853686 adults adults 1.0 \n", + "191185 7902318 adults adults 1.0 \n", + "191276 7909776 adults adults 1.0 \n", + "192239 7988742 adults adults 1.0 \n", + "193643 8103874 adults adults 1.0 \n", "... ... ... ... ... \n", - "2628704 283676518 mixed mixed 1.0 \n", - "2678969 295260168 adults adults 1.0 \n", - "2704338 297646485 adults adults 1.0 \n", - "2718585 298814741 adults adults 1.0 \n", - "2744529 301810980 adults adults 1.0 \n", + "2753390 303771147 mixed mixed 1.0 \n", + "2754817 304144212 mixed mixed 1.0 \n", + "2756049 304463637 mixed mixed 1.0 \n", + "2758936 305125582 children mixed 1.0 \n", + "2759425 305246245 mixed mixed 1.0 \n", "\n", " util_tour_purpose_is_eating_out \\\n", "household_id \n", - 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"189758 0.0 2.0 0.0 \n", - "201016 0.0 2.0 0.0 \n", - "213291 0.0 2.0 0.0 \n", - "226902 0.0 2.0 0.0 \n", - "337259 0.0 0.0 1.0 \n", + "190592 0.0 0.0 2.0 \n", + "191185 0.0 0.0 2.0 \n", + "191276 0.0 0.0 2.0 \n", + "192239 0.0 0.0 1.0 \n", + "193643 0.0 0.0 1.0 \n", "... ... ... ... \n", - "2628704 0.0 0.0 0.0 \n", - "2678969 1.0 0.0 3.0 \n", - "2704338 0.0 0.0 0.0 \n", - "2718585 1.0 0.0 0.0 \n", - "2744529 0.0 0.0 0.0 \n", + "2753390 0.0 0.0 0.0 \n", + "2754817 0.0 0.0 2.0 \n", + "2756049 0.0 2.0 0.0 \n", + "2758936 1.0 0.0 0.0 \n", + "2759425 2.0 1.0 0.0 \n", "\n", " num_preschool_max3 num_school_max3 num_driving_max3 \\\n", "household_id \n", - "189758 0.0 0.0 0.0 \n", - "201016 0.0 0.0 0.0 \n", - "213291 0.0 0.0 0.0 \n", - "226902 0.0 0.0 0.0 \n", - "337259 1.0 0.0 0.0 \n", + "190592 0.0 0.0 0.0 \n", + "191185 0.0 0.0 0.0 \n", + "191276 0.0 0.0 0.0 \n", + "192239 0.0 0.0 0.0 \n", + "193643 0.0 0.0 0.0 \n", "... ... ... ... \n", - "2628704 2.0 0.0 0.0 \n", - "2678969 1.0 0.0 0.0 \n", - 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"req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

Iteration 033 [Optimization terminated successfully]

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Iteration 095 [Optimization terminated successfully]

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Best LL = -9.786597596036862e-07

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Best LL = -263.2609116263491

" ], "text/plain": [ "" @@ -1286,493 +1341,475 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_asc_children\n", - " 121.627746\n", + " 6.744041\n", + " 6.744041\n", " 5.3517\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 121.627746\n", " \n", " \n", " coef_asc_mixed\n", - " -88.249613\n", + " 6.886657\n", + " 6.886657\n", " 5.6290\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -88.249613\n", " \n", " \n", " coef_household_has_more_cars_than_workers_adults\n", - " -40.894264\n", + " 3.138920\n", + " 3.138920\n", " 1.3860\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -40.894264\n", " \n", " \n", " coef_household_has_more_cars_than_workers_mixed\n", - " 153.815203\n", + " 0.384250\n", + " 0.384250\n", " 0.7510\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 153.815203\n", " \n", " \n", " coef_household_in_suburban_area_adults\n", - " 0.510500\n", + " -1.123570\n", + " -1.123570\n", " 0.5105\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.510500\n", " \n", " \n", " coef_household_in_suburban_area_mixed\n", - " 0.128300\n", + " 0.258299\n", + " 0.258299\n", " 0.1283\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.128300\n", " \n", " \n", " coef_household_in_urban_area\n", - " -21.823334\n", + " -0.441828\n", + " -0.441828\n", " 0.5741\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -21.823334\n", " \n", " \n", " coef_log_max_overlap_of_adults_time_windows\n", - " -36.285976\n", + " 1.288269\n", + " 1.288269\n", " 1.1920\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - 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" NaN\n", - " NaN\n", " 0\n", - " \n", - " -161.727385\n", " \n", " \n", " coef_number_of_children_too_young_for_school_children\n", - " -110.048280\n", + " 0.661222\n", + " 0.661222\n", " 0.7306\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -110.048280\n", " \n", " \n", " coef_number_of_children_too_young_for_school_mixed\n", - " 9.539326\n", + " 1.065525\n", + " 1.065525\n", " 0.7906\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 9.539326\n", " \n", " \n", " coef_number_of_driving_age_children_children\n", - " -172.311937\n", + " 0.646806\n", + " 0.646806\n", " -0.2667\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -172.311937\n", " \n", " \n", " coef_number_of_driving_age_children_mixed\n", - " 184.761407\n", + " 0.494992\n", + " 0.494992\n", " -0.9399\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 184.761407\n", " \n", " \n", " coef_number_of_full_time_workers_adults\n", - " 185.490311\n", + " 1.638383\n", + " 1.638383\n", " 1.0240\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 185.490311\n", " \n", " \n", " coef_number_of_full_time_workers_mixed\n", - " 50.943193\n", + " 0.106573\n", + " 0.106573\n", " 0.3624\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 50.943193\n", " \n", " \n", " coef_number_of_non_workers_adults\n", - " 40.041010\n", + " 0.344889\n", + " 0.344889\n", " 0.6263\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 40.041010\n", " \n", " \n", " coef_number_of_non_workers_mixed\n", - " -96.438666\n", + " -0.067851\n", + " -0.067851\n", " -0.3724\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -96.438666\n", " \n", " \n", " coef_number_of_part_time_workers_adults\n", - " 47.088158\n", + " 0.094715\n", + " 0.094715\n", " 0.5412\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 47.088158\n", " \n", " \n", " coef_number_of_part_time_workers_mixed\n", - " 58.958712\n", + " 0.182067\n", + " 0.182067\n", " 0.3164\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 58.958712\n", " \n", " \n", " coef_number_of_pre_driving_age_children_children\n", - " 12.678858\n", + " 0.256545\n", + " 0.256545\n", " 0.7306\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 12.678858\n", " \n", " \n", " coef_number_of_pre_driving_age_children_mixed\n", - " 158.960267\n", + " 0.311384\n", + " 0.311384\n", " 0.3532\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 158.960267\n", " \n", " \n", " coef_number_of_university_students\n", - " -5.007830\n", + " 0.067485\n", + " 0.067485\n", " 0.8245\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -5.007830\n", " \n", " \n", " coef_tour_purpose_is_discretionary_adults\n", " 0.764800\n", + " 0.764800\n", " 0.7648\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.764800\n", " \n", " \n", " coef_tour_purpose_is_discretionary_children\n", " 0.510100\n", + " 0.510100\n", " 0.5101\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.510100\n", " \n", " \n", " coef_tour_purpose_is_eating_out_children\n", " -0.967800\n", + " -0.967800\n", " -0.9678\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.967800\n", " \n", " \n", " coef_tour_purpose_is_eating_out_mixed\n", " -0.802700\n", + " -0.802700\n", " -0.8027\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.802700\n", " \n", " \n", " coef_unavailable\n", " -999.000000\n", + " -999.000000\n", " -999.0000\n", + " -999.0\n", + " -999.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_asc_children 121.627746 5.3517 \n", - "coef_asc_mixed -88.249613 5.6290 \n", - "coef_household_has_more_cars_than_workers_adults -40.894264 1.3860 \n", - "coef_household_has_more_cars_than_workers_mixed 153.815203 0.7510 \n", - "coef_household_in_suburban_area_adults 0.510500 0.5105 \n", - "coef_household_in_suburban_area_mixed 0.128300 0.1283 \n", - "coef_household_in_urban_area -21.823334 0.5741 \n", - "coef_log_max_overlap_of_adults_time_windows -36.285976 1.1920 \n", - "coef_log_max_overlap_of_childrens_time_windows 283.696667 1.8410 \n", - "coef_log_max_overlap_of_time_windows 196.728573 1.9580 \n", - "coef_low_income_households_adults -16.894954 1.2480 \n", - "coef_low_income_households_mixed -3.143593 0.5755 \n", - "coef_medium_income_households -161.727385 0.8369 \n", - "coef_number_of_children_too_young_for_school_ch... -110.048280 0.7306 \n", - "coef_number_of_children_too_young_for_school_mixed 9.539326 0.7906 \n", - "coef_number_of_driving_age_children_children -172.311937 -0.2667 \n", - "coef_number_of_driving_age_children_mixed 184.761407 -0.9399 \n", - "coef_number_of_full_time_workers_adults 185.490311 1.0240 \n", - "coef_number_of_full_time_workers_mixed 50.943193 0.3624 \n", - "coef_number_of_non_workers_adults 40.041010 0.6263 \n", - "coef_number_of_non_workers_mixed -96.438666 -0.3724 \n", - "coef_number_of_part_time_workers_adults 47.088158 0.5412 \n", - "coef_number_of_part_time_workers_mixed 58.958712 0.3164 \n", - "coef_number_of_pre_driving_age_children_children 12.678858 0.7306 \n", - "coef_number_of_pre_driving_age_children_mixed 158.960267 0.3532 \n", - "coef_number_of_university_students -5.007830 0.8245 \n", - "coef_tour_purpose_is_discretionary_adults 0.764800 0.7648 \n", - "coef_tour_purpose_is_discretionary_children 0.510100 0.5101 \n", - "coef_tour_purpose_is_eating_out_children -0.967800 -0.9678 \n", - "coef_tour_purpose_is_eating_out_mixed -0.802700 -0.8027 \n", - "coef_unavailable -999.000000 -999.0000 \n", + " value best \\\n", + "param_name \n", + "coef_asc_children 6.744041 6.744041 \n", + "coef_asc_mixed 6.886657 6.886657 \n", + "coef_household_has_more_cars_than_workers_adults 3.138920 3.138920 \n", + "coef_household_has_more_cars_than_workers_mixed 0.384250 0.384250 \n", + "coef_household_in_suburban_area_adults -1.123570 -1.123570 \n", + "coef_household_in_suburban_area_mixed 0.258299 0.258299 \n", + "coef_household_in_urban_area -0.441828 -0.441828 \n", + "coef_log_max_overlap_of_adults_time_windows 1.288269 1.288269 \n", + "coef_log_max_overlap_of_childrens_time_windows 1.783892 1.783892 \n", + "coef_log_max_overlap_of_time_windows 1.505521 1.505521 \n", + "coef_low_income_households_adults 2.520875 2.520875 \n", + "coef_low_income_households_mixed 0.683195 0.683195 \n", + "coef_medium_income_households 1.853225 1.853225 \n", + "coef_number_of_children_too_young_for_school_ch... 0.661222 0.661222 \n", + "coef_number_of_children_too_young_for_school_mixed 1.065525 1.065525 \n", + "coef_number_of_driving_age_children_children 0.646806 0.646806 \n", + "coef_number_of_driving_age_children_mixed 0.494992 0.494992 \n", + "coef_number_of_full_time_workers_adults 1.638383 1.638383 \n", + "coef_number_of_full_time_workers_mixed 0.106573 0.106573 \n", + "coef_number_of_non_workers_adults 0.344889 0.344889 \n", + "coef_number_of_non_workers_mixed -0.067851 -0.067851 \n", + "coef_number_of_part_time_workers_adults 0.094715 0.094715 \n", + "coef_number_of_part_time_workers_mixed 0.182067 0.182067 \n", + "coef_number_of_pre_driving_age_children_children 0.256545 0.256545 \n", + "coef_number_of_pre_driving_age_children_mixed 0.311384 0.311384 \n", + "coef_number_of_university_students 0.067485 0.067485 \n", + "coef_tour_purpose_is_discretionary_adults 0.764800 0.764800 \n", + "coef_tour_purpose_is_discretionary_children 0.510100 0.510100 \n", + "coef_tour_purpose_is_eating_out_children -0.967800 -0.967800 \n", + "coef_tour_purpose_is_eating_out_mixed -0.802700 -0.802700 \n", + "coef_unavailable -999.000000 -999.000000 \n", "\n", - " nullvalue minimum \\\n", - "coef_asc_children 0.0 NaN \n", - "coef_asc_mixed 0.0 NaN \n", - "coef_household_has_more_cars_than_workers_adults 0.0 NaN \n", - "coef_household_has_more_cars_than_workers_mixed 0.0 NaN \n", - "coef_household_in_suburban_area_adults 0.0 NaN \n", - "coef_household_in_suburban_area_mixed 0.0 NaN \n", - "coef_household_in_urban_area 0.0 NaN \n", - "coef_log_max_overlap_of_adults_time_windows 0.0 NaN \n", - "coef_log_max_overlap_of_childrens_time_windows 0.0 NaN \n", - "coef_log_max_overlap_of_time_windows 0.0 NaN \n", - "coef_low_income_households_adults 0.0 NaN \n", - "coef_low_income_households_mixed 0.0 NaN \n", - "coef_medium_income_households 0.0 NaN \n", - "coef_number_of_children_too_young_for_school_ch... 0.0 NaN \n", - "coef_number_of_children_too_young_for_school_mixed 0.0 NaN \n", - "coef_number_of_driving_age_children_children 0.0 NaN \n", - "coef_number_of_driving_age_children_mixed 0.0 NaN \n", - "coef_number_of_full_time_workers_adults 0.0 NaN \n", - "coef_number_of_full_time_workers_mixed 0.0 NaN \n", - "coef_number_of_non_workers_adults 0.0 NaN \n", - "coef_number_of_non_workers_mixed 0.0 NaN \n", - "coef_number_of_part_time_workers_adults 0.0 NaN \n", - "coef_number_of_part_time_workers_mixed 0.0 NaN \n", - "coef_number_of_pre_driving_age_children_children 0.0 NaN \n", - "coef_number_of_pre_driving_age_children_mixed 0.0 NaN \n", - "coef_number_of_university_students 0.0 NaN \n", - "coef_tour_purpose_is_discretionary_adults 0.0 NaN \n", - "coef_tour_purpose_is_discretionary_children 0.0 NaN \n", - "coef_tour_purpose_is_eating_out_children 0.0 NaN \n", - "coef_tour_purpose_is_eating_out_mixed 0.0 NaN \n", - "coef_unavailable 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_asc_children 5.3517 -50.0 \n", + "coef_asc_mixed 5.6290 -50.0 \n", + "coef_household_has_more_cars_than_workers_adults 1.3860 -50.0 \n", + "coef_household_has_more_cars_than_workers_mixed 0.7510 -50.0 \n", + "coef_household_in_suburban_area_adults 0.5105 -50.0 \n", + "coef_household_in_suburban_area_mixed 0.1283 -50.0 \n", + "coef_household_in_urban_area 0.5741 -50.0 \n", + "coef_log_max_overlap_of_adults_time_windows 1.1920 -50.0 \n", + "coef_log_max_overlap_of_childrens_time_windows 1.8410 -50.0 \n", + "coef_log_max_overlap_of_time_windows 1.9580 -50.0 \n", + "coef_low_income_households_adults 1.2480 -50.0 \n", + "coef_low_income_households_mixed 0.5755 -50.0 \n", + "coef_medium_income_households 0.8369 -50.0 \n", + "coef_number_of_children_too_young_for_school_ch... 0.7306 -50.0 \n", + "coef_number_of_children_too_young_for_school_mixed 0.7906 -50.0 \n", + "coef_number_of_driving_age_children_children -0.2667 -50.0 \n", + "coef_number_of_driving_age_children_mixed -0.9399 -50.0 \n", + "coef_number_of_full_time_workers_adults 1.0240 -50.0 \n", + "coef_number_of_full_time_workers_mixed 0.3624 -50.0 \n", + "coef_number_of_non_workers_adults 0.6263 -50.0 \n", + "coef_number_of_non_workers_mixed -0.3724 -50.0 \n", + "coef_number_of_part_time_workers_adults 0.5412 -50.0 \n", + "coef_number_of_part_time_workers_mixed 0.3164 -50.0 \n", + "coef_number_of_pre_driving_age_children_children 0.7306 -50.0 \n", + "coef_number_of_pre_driving_age_children_mixed 0.3532 -50.0 \n", + "coef_number_of_university_students 0.8245 -50.0 \n", + "coef_tour_purpose_is_discretionary_adults 0.7648 -50.0 \n", + "coef_tour_purpose_is_discretionary_children 0.5101 -50.0 \n", + "coef_tour_purpose_is_eating_out_children -0.9678 -50.0 \n", + "coef_tour_purpose_is_eating_out_mixed -0.8027 -50.0 \n", + "coef_unavailable -999.0000 -999.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_asc_children NaN 0 \n", - "coef_asc_mixed NaN 0 \n", - "coef_household_has_more_cars_than_workers_adults NaN 0 \n", - "coef_household_has_more_cars_than_workers_mixed NaN 0 \n", - "coef_household_in_suburban_area_adults NaN 0 \n", - "coef_household_in_suburban_area_mixed NaN 0 \n", - "coef_household_in_urban_area NaN 0 \n", - "coef_log_max_overlap_of_adults_time_windows NaN 0 \n", - "coef_log_max_overlap_of_childrens_time_windows NaN 0 \n", - "coef_log_max_overlap_of_time_windows NaN 0 \n", - "coef_low_income_households_adults NaN 0 \n", - "coef_low_income_households_mixed NaN 0 \n", - "coef_medium_income_households NaN 0 \n", - "coef_number_of_children_too_young_for_school_ch... NaN 0 \n", - "coef_number_of_children_too_young_for_school_mixed NaN 0 \n", - "coef_number_of_driving_age_children_children NaN 0 \n", - "coef_number_of_driving_age_children_mixed NaN 0 \n", - "coef_number_of_full_time_workers_adults NaN 0 \n", - "coef_number_of_full_time_workers_mixed NaN 0 \n", - "coef_number_of_non_workers_adults NaN 0 \n", - "coef_number_of_non_workers_mixed NaN 0 \n", - "coef_number_of_part_time_workers_adults NaN 0 \n", - "coef_number_of_part_time_workers_mixed NaN 0 \n", - "coef_number_of_pre_driving_age_children_children NaN 0 \n", - "coef_number_of_pre_driving_age_children_mixed NaN 0 \n", - "coef_number_of_university_students NaN 0 \n", - "coef_tour_purpose_is_discretionary_adults NaN 0 \n", - "coef_tour_purpose_is_discretionary_children NaN 0 \n", - "coef_tour_purpose_is_eating_out_children NaN 0 \n", - "coef_tour_purpose_is_eating_out_mixed NaN 0 \n", - "coef_unavailable NaN 1 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_asc_children 50.0 0.0 \n", + "coef_asc_mixed 50.0 0.0 \n", + "coef_household_has_more_cars_than_workers_adults 50.0 0.0 \n", + "coef_household_has_more_cars_than_workers_mixed 50.0 0.0 \n", + "coef_household_in_suburban_area_adults 50.0 0.0 \n", + "coef_household_in_suburban_area_mixed 50.0 0.0 \n", + "coef_household_in_urban_area 50.0 0.0 \n", + "coef_log_max_overlap_of_adults_time_windows 50.0 0.0 \n", + "coef_log_max_overlap_of_childrens_time_windows 50.0 0.0 \n", + "coef_log_max_overlap_of_time_windows 50.0 0.0 \n", + "coef_low_income_households_adults 50.0 0.0 \n", + "coef_low_income_households_mixed 50.0 0.0 \n", + "coef_medium_income_households 50.0 0.0 \n", + "coef_number_of_children_too_young_for_school_ch... 50.0 0.0 \n", + "coef_number_of_children_too_young_for_school_mixed 50.0 0.0 \n", + "coef_number_of_driving_age_children_children 50.0 0.0 \n", + "coef_number_of_driving_age_children_mixed 50.0 0.0 \n", + "coef_number_of_full_time_workers_adults 50.0 0.0 \n", + "coef_number_of_full_time_workers_mixed 50.0 0.0 \n", + "coef_number_of_non_workers_adults 50.0 0.0 \n", + "coef_number_of_non_workers_mixed 50.0 0.0 \n", + "coef_number_of_part_time_workers_adults 50.0 0.0 \n", + "coef_number_of_part_time_workers_mixed 50.0 0.0 \n", + "coef_number_of_pre_driving_age_children_children 50.0 0.0 \n", + "coef_number_of_pre_driving_age_children_mixed 50.0 0.0 \n", + "coef_number_of_university_students 50.0 0.0 \n", + "coef_tour_purpose_is_discretionary_adults 50.0 0.0 \n", + "coef_tour_purpose_is_discretionary_children 50.0 0.0 \n", + "coef_tour_purpose_is_eating_out_children 50.0 0.0 \n", + "coef_tour_purpose_is_eating_out_mixed 50.0 0.0 \n", + "coef_unavailable -999.0 0.0 \n", "\n", - " best \n", - "coef_asc_children 121.627746 \n", - "coef_asc_mixed -88.249613 \n", - "coef_household_has_more_cars_than_workers_adults -40.894264 \n", - "coef_household_has_more_cars_than_workers_mixed 153.815203 \n", - "coef_household_in_suburban_area_adults 0.510500 \n", - "coef_household_in_suburban_area_mixed 0.128300 \n", - "coef_household_in_urban_area -21.823334 \n", - "coef_log_max_overlap_of_adults_time_windows -36.285976 \n", - "coef_log_max_overlap_of_childrens_time_windows 283.696667 \n", - "coef_log_max_overlap_of_time_windows 196.728573 \n", - "coef_low_income_households_adults -16.894954 \n", - "coef_low_income_households_mixed -3.143593 \n", - "coef_medium_income_households -161.727385 \n", - "coef_number_of_children_too_young_for_school_ch... -110.048280 \n", - "coef_number_of_children_too_young_for_school_mixed 9.539326 \n", - "coef_number_of_driving_age_children_children -172.311937 \n", - "coef_number_of_driving_age_children_mixed 184.761407 \n", - "coef_number_of_full_time_workers_adults 185.490311 \n", - "coef_number_of_full_time_workers_mixed 50.943193 \n", - "coef_number_of_non_workers_adults 40.041010 \n", - "coef_number_of_non_workers_mixed -96.438666 \n", - "coef_number_of_part_time_workers_adults 47.088158 \n", - "coef_number_of_part_time_workers_mixed 58.958712 \n", - "coef_number_of_pre_driving_age_children_children 12.678858 \n", - "coef_number_of_pre_driving_age_children_mixed 158.960267 \n", - "coef_number_of_university_students -5.007830 \n", - "coef_tour_purpose_is_discretionary_adults 0.764800 \n", - "coef_tour_purpose_is_discretionary_children 0.510100 \n", - "coef_tour_purpose_is_eating_out_children -0.967800 \n", - "coef_tour_purpose_is_eating_out_mixed -0.802700 \n", - "coef_unavailable -999.000000 " + " holdfast \n", + "param_name \n", + "coef_asc_children 0 \n", + "coef_asc_mixed 0 \n", + "coef_household_has_more_cars_than_workers_adults 0 \n", + "coef_household_has_more_cars_than_workers_mixed 0 \n", + "coef_household_in_suburban_area_adults 0 \n", + "coef_household_in_suburban_area_mixed 0 \n", + "coef_household_in_urban_area 0 \n", + "coef_log_max_overlap_of_adults_time_windows 0 \n", + "coef_log_max_overlap_of_childrens_time_windows 0 \n", + "coef_log_max_overlap_of_time_windows 0 \n", + "coef_low_income_households_adults 0 \n", + "coef_low_income_households_mixed 0 \n", + "coef_medium_income_households 0 \n", + "coef_number_of_children_too_young_for_school_ch... 0 \n", + "coef_number_of_children_too_young_for_school_mixed 0 \n", + "coef_number_of_driving_age_children_children 0 \n", + "coef_number_of_driving_age_children_mixed 0 \n", + "coef_number_of_full_time_workers_adults 0 \n", + "coef_number_of_full_time_workers_mixed 0 \n", + "coef_number_of_non_workers_adults 0 \n", + "coef_number_of_non_workers_mixed 0 \n", + "coef_number_of_part_time_workers_adults 0 \n", + "coef_number_of_part_time_workers_mixed 0 \n", + "coef_number_of_pre_driving_age_children_children 0 \n", + "coef_number_of_pre_driving_age_children_mixed 0 \n", + "coef_number_of_university_students 0 \n", + "coef_tour_purpose_is_discretionary_adults 0 \n", + "coef_tour_purpose_is_discretionary_children 0 \n", + "coef_tour_purpose_is_eating_out_children 0 \n", + "coef_tour_purpose_is_eating_out_mixed 0 \n", + "coef_unavailable 1 " ] }, "metadata": {}, @@ -1782,12 +1819,8 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate(method='SLSQP')\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 0.0 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - ":1: RuntimeWarning: invalid value encountered in sqrt\n", - " model.estimate(method='SLSQP')\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { @@ -1803,107 +1836,107 @@ " \n", " \n", " coef_asc_children\n", - " 121.627746\n", + " 6.744041\n", " \n", " \n", " coef_asc_mixed\n", - " -88.249613\n", + " 6.886657\n", " \n", " \n", " coef_household_has_more_cars_than_workers_adults\n", - " -40.894264\n", + " 3.138920\n", " \n", " \n", " coef_household_has_more_cars_than_workers_mixed\n", - " 153.815203\n", + " 0.384250\n", " \n", " \n", " coef_household_in_suburban_area_adults\n", - " 0.510500\n", + " -1.123570\n", " \n", " \n", " coef_household_in_suburban_area_mixed\n", - " 0.128300\n", + " 0.258299\n", " \n", " \n", " coef_household_in_urban_area\n", - " -21.823334\n", + " -0.441828\n", " \n", " \n", " coef_log_max_overlap_of_adults_time_windows\n", - " -36.285976\n", + " 1.288269\n", " \n", " \n", " coef_log_max_overlap_of_childrens_time_windows\n", - " 283.696667\n", + " 1.783892\n", " \n", " \n", " coef_log_max_overlap_of_time_windows\n", - " 196.728573\n", + " 1.505521\n", " \n", " \n", " coef_low_income_households_adults\n", - " -16.894954\n", + " 2.520875\n", " \n", " \n", " coef_low_income_households_mixed\n", - " -3.143593\n", + " 0.683195\n", " \n", " \n", " coef_medium_income_households\n", - " -161.727385\n", + " 1.853225\n", " \n", " \n", " coef_number_of_children_too_young_for_school_children\n", - " -110.048280\n", + " 0.661222\n", " \n", " \n", " coef_number_of_children_too_young_for_school_mixed\n", - " 9.539326\n", + " 1.065525\n", " \n", " \n", " coef_number_of_driving_age_children_children\n", - " -172.311937\n", + " 0.646806\n", " \n", " \n", " coef_number_of_driving_age_children_mixed\n", - " 184.761407\n", + " 0.494992\n", " \n", " \n", " coef_number_of_full_time_workers_adults\n", - " 185.490311\n", + " 1.638383\n", " \n", " \n", " coef_number_of_full_time_workers_mixed\n", - " 50.943193\n", + " 0.106573\n", " \n", " \n", " coef_number_of_non_workers_adults\n", - " 40.041010\n", + " 0.344889\n", " \n", " \n", " coef_number_of_non_workers_mixed\n", - " -96.438666\n", + " -0.067851\n", " \n", " \n", " coef_number_of_part_time_workers_adults\n", - " 47.088158\n", + " 0.094715\n", " \n", " \n", " coef_number_of_part_time_workers_mixed\n", - " 58.958712\n", + " 0.182067\n", " \n", " \n", " coef_number_of_pre_driving_age_children_children\n", - " 12.678858\n", + " 0.256545\n", " \n", " \n", " coef_number_of_pre_driving_age_children_mixed\n", - " 158.960267\n", + " 0.311384\n", " \n", " \n", " coef_number_of_university_students\n", - " -5.007830\n", + " 0.067485\n", " \n", " \n", " coef_tour_purpose_is_discretionary_adults\n", @@ -1926,7 +1959,7 @@ " -999.000000\n", " \n", " \n", - "loglike-9.786597596036862e-07d_loglike\n", + "
logloss0.2061557647817926d_logloss\n", " \n", " \n", " \n", @@ -1936,107 +1969,107 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2059,85 +2092,85 @@ " \n", " \n", " \n", - "
coef_asc_children-1.199240e-064.680292e-05
coef_asc_mixed1.199240e-061.506794e-04
coef_household_has_more_cars_than_workers_adults-7.697895e-122-1.303235e-04
coef_household_has_more_cars_than_workers_mixed2.677106e-094.087211e-05
coef_household_in_suburban_area_adults0.000000e+00-2.788428e-05
coef_household_in_suburban_area_mixed0.000000e+00-2.733559e-05
coef_household_in_urban_area-1.311061e-38-1.695981e-04
coef_log_max_overlap_of_adults_time_windows-2.551704e-387.673766e-05
coef_log_max_overlap_of_childrens_time_windows-2.523891e-063.533351e-05
coef_log_max_overlap_of_time_windows2.726540e-062.703275e-05
coef_low_income_households_adults-4.843014e-79-1.364236e-04
coef_low_income_households_mixed4.440892e-165.443801e-05
coef_medium_income_households-1.620456e-77-7.972989e-05
coef_number_of_children_too_young_for_school_children8.759917e-08-1.415851e-04
coef_number_of_children_too_young_for_school_mixed-8.759917e-08-1.265584e-04
coef_number_of_driving_age_children_children-2.272077e-16-7.515067e-05
coef_number_of_driving_age_children_mixed4.440892e-16-7.904237e-05
coef_number_of_full_time_workers_adults-3.933184e-381.573128e-04
coef_number_of_full_time_workers_mixed2.196009e-064.624742e-05
coef_number_of_non_workers_adults-4.909798e-77-2.862258e-05
coef_number_of_non_workers_mixed2.677106e-09-1.424617e-05
coef_number_of_part_time_workers_adults-1.620456e-77-2.202661e-04
coef_number_of_part_time_workers_mixed-8.759917e-082.445794e-07
coef_number_of_pre_driving_age_children_children-2.486079e-06-1.084978e-05
coef_number_of_pre_driving_age_children_mixed2.486079e-063.508229e-05
coef_number_of_university_students-2.474369e-317-5.764209e-05
coef_tour_purpose_is_discretionary_adults0.000000e+00
nit33nfev39njev33status0message'Optimization terminated successfully'successTrueelapsed_time0:00:00.266490method'SLSQP'n_cases91iteration_number33logloss1.075450285278776e-08" + "nit95nfev95njev95status0message'Optimization terminated successfully'successTrueelapsed_time0:00:00.247365method'SLSQP'n_cases1277iteration_number95loglike-263.2609116263491" ], "text/plain": [ - "┣ x: coef_asc_children 121.627746\n", - "┃ coef_asc_mixed -88.249613\n", - "┃ coef_household_has_more_cars_than_workers_adults -40.894264\n", - "┃ coef_household_has_more_cars_than_workers_mixed 153.815203\n", - "┃ coef_household_in_suburban_area_adults 0.510500\n", - "┃ coef_household_in_suburban_area_mixed 0.128300\n", - "┃ coef_household_in_urban_area -21.823334\n", - "┃ coef_log_max_overlap_of_adults_time_windows -36.285976\n", - "┃ coef_log_max_overlap_of_childrens_time_windows 283.696667\n", - "┃ coef_log_max_overlap_of_time_windows 196.728573\n", - "┃ coef_low_income_households_adults -16.894954\n", - "┃ coef_low_income_households_mixed -3.143593\n", - "┃ coef_medium_income_households -161.727385\n", - "┃ coef_number_of_children_too_young_for_school_children -110.048280\n", - "┃ coef_number_of_children_too_young_for_school_mixed 9.539326\n", - "┃ coef_number_of_driving_age_children_children -172.311937\n", - "┃ coef_number_of_driving_age_children_mixed 184.761407\n", - "┃ coef_number_of_full_time_workers_adults 185.490311\n", - "┃ coef_number_of_full_time_workers_mixed 50.943193\n", - "┃ coef_number_of_non_workers_adults 40.041010\n", - "┃ coef_number_of_non_workers_mixed -96.438666\n", - "┃ coef_number_of_part_time_workers_adults 47.088158\n", - "┃ coef_number_of_part_time_workers_mixed 58.958712\n", - "┃ coef_number_of_pre_driving_age_children_children 12.678858\n", - "┃ coef_number_of_pre_driving_age_children_mixed 158.960267\n", - "┃ coef_number_of_university_students -5.007830\n", + "┣ x: coef_asc_children 6.744041\n", + "┃ coef_asc_mixed 6.886657\n", + "┃ coef_household_has_more_cars_than_workers_adults 3.138920\n", + "┃ coef_household_has_more_cars_than_workers_mixed 0.384250\n", + "┃ coef_household_in_suburban_area_adults -1.123570\n", + "┃ coef_household_in_suburban_area_mixed 0.258299\n", + "┃ coef_household_in_urban_area -0.441828\n", + "┃ coef_log_max_overlap_of_adults_time_windows 1.288269\n", + "┃ coef_log_max_overlap_of_childrens_time_windows 1.783892\n", + "┃ coef_log_max_overlap_of_time_windows 1.505521\n", + "┃ coef_low_income_households_adults 2.520875\n", + "┃ coef_low_income_households_mixed 0.683195\n", + "┃ coef_medium_income_households 1.853225\n", + "┃ coef_number_of_children_too_young_for_school_children 0.661222\n", + "┃ coef_number_of_children_too_young_for_school_mixed 1.065525\n", + "┃ coef_number_of_driving_age_children_children 0.646806\n", + "┃ coef_number_of_driving_age_children_mixed 0.494992\n", + "┃ coef_number_of_full_time_workers_adults 1.638383\n", + "┃ coef_number_of_full_time_workers_mixed 0.106573\n", + "┃ coef_number_of_non_workers_adults 0.344889\n", + "┃ coef_number_of_non_workers_mixed -0.067851\n", + "┃ coef_number_of_part_time_workers_adults 0.094715\n", + "┃ coef_number_of_part_time_workers_mixed 0.182067\n", + "┃ coef_number_of_pre_driving_age_children_children 0.256545\n", + "┃ coef_number_of_pre_driving_age_children_mixed 0.311384\n", + "┃ coef_number_of_university_students 0.067485\n", "┃ coef_tour_purpose_is_discretionary_adults 0.764800\n", "┃ coef_tour_purpose_is_discretionary_children 0.510100\n", "┃ coef_tour_purpose_is_eating_out_children -0.967800\n", "┃ coef_tour_purpose_is_eating_out_mixed -0.802700\n", "┃ coef_unavailable -999.000000\n", "┃ dtype: float64\n", - "┣ loglike: -9.786597596036862e-07\n", - "┣ d_loglike: coef_asc_children -1.199240e-06\n", - "┃ coef_asc_mixed 1.199240e-06\n", - "┃ coef_household_has_more_cars_than_workers_adults -7.697895e-122\n", - "┃ coef_household_has_more_cars_than_workers_mixed 2.677106e-09\n", - "┃ coef_household_in_suburban_area_adults 0.000000e+00\n", - "┃ coef_household_in_suburban_area_mixed 0.000000e+00\n", - "┃ coef_household_in_urban_area -1.311061e-38\n", - "┃ coef_log_max_overlap_of_adults_time_windows -2.551704e-38\n", - "┃ coef_log_max_overlap_of_childrens_time_windows -2.523891e-06\n", - "┃ coef_log_max_overlap_of_time_windows 2.726540e-06\n", - "┃ coef_low_income_households_adults -4.843014e-79\n", - "┃ coef_low_income_households_mixed 4.440892e-16\n", - "┃ coef_medium_income_households -1.620456e-77\n", - "┃ coef_number_of_children_too_young_for_school_children 8.759917e-08\n", - "┃ coef_number_of_children_too_young_for_school_mixed -8.759917e-08\n", - "┃ coef_number_of_driving_age_children_children -2.272077e-16\n", - "┃ coef_number_of_driving_age_children_mixed 4.440892e-16\n", - "┃ coef_number_of_full_time_workers_adults -3.933184e-38\n", - "┃ coef_number_of_full_time_workers_mixed 2.196009e-06\n", - "┃ coef_number_of_non_workers_adults -4.909798e-77\n", - "┃ coef_number_of_non_workers_mixed 2.677106e-09\n", - "┃ coef_number_of_part_time_workers_adults -1.620456e-77\n", - "┃ coef_number_of_part_time_workers_mixed -8.759917e-08\n", - "┃ coef_number_of_pre_driving_age_children_children -2.486079e-06\n", - "┃ coef_number_of_pre_driving_age_children_mixed 2.486079e-06\n", - "┃ coef_number_of_university_students -2.474369e-317\n", - "┃ coef_tour_purpose_is_discretionary_adults 0.000000e+00\n", - "┃ coef_tour_purpose_is_discretionary_children 0.000000e+00\n", - "┃ coef_tour_purpose_is_eating_out_children 0.000000e+00\n", - "┃ coef_tour_purpose_is_eating_out_mixed 0.000000e+00\n", - "┃ coef_unavailable 0.000000e+00\n", + "┣ logloss: 0.2061557647817926\n", + "┣ d_logloss: coef_asc_children 4.680292e-05\n", + "┃ coef_asc_mixed 1.506794e-04\n", + "┃ coef_household_has_more_cars_than_workers_adults -1.303235e-04\n", + "┃ coef_household_has_more_cars_than_workers_mixed 4.087211e-05\n", + "┃ coef_household_in_suburban_area_adults -2.788428e-05\n", + "┃ coef_household_in_suburban_area_mixed -2.733559e-05\n", + "┃ coef_household_in_urban_area -1.695981e-04\n", + "┃ coef_log_max_overlap_of_adults_time_windows 7.673766e-05\n", + "┃ coef_log_max_overlap_of_childrens_time_windows 3.533351e-05\n", + "┃ coef_log_max_overlap_of_time_windows 2.703275e-05\n", + "┃ coef_low_income_households_adults -1.364236e-04\n", + "┃ coef_low_income_households_mixed 5.443801e-05\n", + "┃ coef_medium_income_households -7.972989e-05\n", + "┃ coef_number_of_children_too_young_for_school_children -1.415851e-04\n", + "┃ coef_number_of_children_too_young_for_school_mixed -1.265584e-04\n", + "┃ coef_number_of_driving_age_children_children -7.515067e-05\n", + "┃ coef_number_of_driving_age_children_mixed -7.904237e-05\n", + "┃ coef_number_of_full_time_workers_adults 1.573128e-04\n", + "┃ coef_number_of_full_time_workers_mixed 4.624742e-05\n", + "┃ coef_number_of_non_workers_adults -2.862258e-05\n", + "┃ coef_number_of_non_workers_mixed -1.424617e-05\n", + "┃ coef_number_of_part_time_workers_adults -2.202661e-04\n", + "┃ coef_number_of_part_time_workers_mixed 2.445794e-07\n", + "┃ coef_number_of_pre_driving_age_children_children -1.084978e-05\n", + "┃ coef_number_of_pre_driving_age_children_mixed 3.508229e-05\n", + "┃ coef_number_of_university_students -5.764209e-05\n", + "┃ coef_tour_purpose_is_discretionary_adults 0.000000e+00\n", + "┃ coef_tour_purpose_is_discretionary_children 0.000000e+00\n", + "┃ coef_tour_purpose_is_eating_out_children 0.000000e+00\n", + "┃ coef_tour_purpose_is_eating_out_mixed 0.000000e+00\n", + "┃ coef_unavailable 0.000000e+00\n", "┃ dtype: float64\n", - "┣ nit: 33\n", - "┣ nfev: 39\n", - "┣ njev: 33\n", + "┣ nit: 95\n", + "┣ nfev: 95\n", + "┣ njev: 95\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(microseconds=266490)\n", + "┣ elapsed_time: datetime.timedelta(microseconds=247365)\n", "┣ method: 'SLSQP'\n", - "┣ n_cases: 91\n", - "┣ iteration_number: 33\n", - "┣ logloss: 1.075450285278776e-08" + "┣ n_cases: 1277\n", + "┣ iteration_number: 95\n", + "┣ loglike: -263.2609116263491" ] }, "execution_count": 7, @@ -2172,330 +2205,325 @@ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
coef_asc_children 122. NA NA[***] 306.42 0.00
coef_asc_mixed-88.2 2.20e+04-0.00 NA 0.00
coef_household_has_more_cars_than_workers_adults-40.9 NA NA[] 0.00 0.00
coef_household_has_more_cars_than_workers_mixed 154. 4.67e+04 0.00 NA 0.00
coef_household_in_suburban_area_adults 0.511 NA NA[] 0.00 0.00
coef_household_in_suburban_area_mixed 0.128 NA NA[] 0.00 0.00
coef_household_in_urban_area-21.8 NA NA[] 0.00 0.00
coef_log_max_overlap_of_adults_time_windows-36.3 NA NA[] 0.00 0.00
coef_log_max_overlap_of_childrens_time_windows 284. NA NA[***] BIG 0.00
coef_log_max_overlap_of_time_windows 197. 1.02e+04 0.02 NA 0.00
coef_low_income_households_adults-16.9 NA NA[] 0.00 0.00
coef_low_income_households_mixed-3.14 NA NA[] 0.00 0.00
coef_medium_income_households-162. NA NA[] 0.00 0.00
coef_number_of_children_too_young_for_school_children-110. 9.62e+03-0.01 NA 0.00
coef_number_of_children_too_young_for_school_mixed 9.54 4.19e+03 0.00 NA 0.00
coef_number_of_driving_age_children_children-172. 1.21e+05-0.00 NA 0.00
coef_number_of_driving_age_children_mixed 185. NA NA[***] 293.31 0.00
coef_number_of_full_time_workers_adults 185. NA NA[***] 216.30 0.00
coef_number_of_full_time_workers_mixed 50.9 3.72e+03 0.01 NA 0.00
coef_number_of_non_workers_adults 40.0 NA NA[] 0.00 0.00
coef_number_of_non_workers_mixed-96.4 2.02e+05-0.00 NA 0.00
coef_number_of_part_time_workers_adults 47.1 NA NA[] 0.00 0.00
coef_number_of_part_time_workers_mixed 59.0 4.19e+03 0.01 NA 0.00
coef_number_of_pre_driving_age_children_children 12.7 1.41e+04 0.00 NA 0.00
coef_number_of_pre_driving_age_children_mixed 159. 2.22e+04 0.01 NA 0.00
coef_number_of_university_students-5.01 0.00 NA[] 0.00 0.00
coef_tour_purpose_is_discretionary_adults 0.765 0.00 NA[] 0.00 0.00
coef_tour_purpose_is_discretionary_children 0.510 0.00 NA[] 0.00 0.00
coef_tour_purpose_is_eating_out_children-0.968 0.00 NA[] 0.00 0.00
coef_tour_purpose_is_eating_out_mixed-0.803 0.00 NA[] 0.00 0.00
coef_unavailable-999. NA NA NA 0.00fixed value
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_asc_children 6.74 NA NA 0.00
coef_asc_mixed 6.89 NA NA 0.00
coef_household_has_more_cars_than_workers_adults 3.14 1.19 2.64** 0.00
coef_household_has_more_cars_than_workers_mixed 0.384 0.275 1.40 0.00
coef_household_in_suburban_area_adults-1.12 NA NA 0.00
coef_household_in_suburban_area_mixed 0.258 0.272 0.95 0.00
coef_household_in_urban_area-0.442 NA NA 0.00
coef_log_max_overlap_of_adults_time_windows 1.29 0.921 1.40 0.00
coef_log_max_overlap_of_childrens_time_windows 1.78 0.379 4.71*** 0.00
coef_log_max_overlap_of_time_windows 1.51 0.376 4.00*** 0.00
coef_low_income_households_adults 2.52 1.01 2.48* 0.00
coef_low_income_households_mixed 0.683 0.345 1.98* 0.00
coef_medium_income_households 1.85 0.782 2.37* 0.00
coef_number_of_children_too_young_for_school_children 0.661 0.684 0.97 0.00
coef_number_of_children_too_young_for_school_mixed 1.07 0.653 1.63 0.00
coef_number_of_driving_age_children_children 0.647 0.901 0.72 0.00
coef_number_of_driving_age_children_mixed 0.495 0.870 0.57 0.00
coef_number_of_full_time_workers_adults 1.64 0.455 3.60*** 0.00
coef_number_of_full_time_workers_mixed 0.107 0.175 0.61 0.00
coef_number_of_non_workers_adults 0.345 0.455 0.76 0.00
coef_number_of_non_workers_mixed-0.0679 0.175-0.39 0.00
coef_number_of_part_time_workers_adults 0.0947 0.789 0.12 0.00
coef_number_of_part_time_workers_mixed 0.182 0.227 0.80 0.00
coef_number_of_pre_driving_age_children_children 0.257 0.503 0.51 0.00
coef_number_of_pre_driving_age_children_mixed 0.311 0.475 0.66 0.00
coef_number_of_university_students 0.0675 0.499 0.14 0.00
coef_tour_purpose_is_discretionary_adults 0.765 0.00 NA 0.00
coef_tour_purpose_is_discretionary_children 0.510 0.00 NA 0.00
coef_tour_purpose_is_eating_out_children-0.968 0.00 NA 0.00
coef_tour_purpose_is_eating_out_mixed-0.803 0.00 NA 0.00
coef_unavailable-999. 0.00 NA 0.00fixed value
\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 8, @@ -2542,18 +2570,7 @@ "cell_type": "code", "execution_count": 10, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -2611,13 +2628,13 @@ " \n", " 1\n", " coef_asc_children\n", - " 121.627746\n", + " 6.744041\n", " F\n", " \n", " \n", " 2\n", " coef_asc_mixed\n", - " -88.249613\n", + " 6.886657\n", " fF\n", " \n", " \n", @@ -2647,145 +2664,145 @@ " \n", " 7\n", " coef_number_of_full_time_workers_adults\n", - " 185.490311\n", + " 1.638383\n", " F\n", " \n", " \n", " 8\n", " coef_number_of_full_time_workers_mixed\n", - " 50.943193\n", + " 0.106573\n", " F\n", " \n", " \n", " 9\n", " coef_number_of_part_time_workers_adults\n", - " 47.088158\n", + " 0.094715\n", " F\n", " \n", " \n", " 10\n", " coef_number_of_part_time_workers_mixed\n", - " 58.958712\n", + " 0.182067\n", " F\n", " \n", " \n", " 11\n", " coef_number_of_university_students\n", - " -5.007830\n", + " 0.067485\n", " F\n", " \n", " \n", " 12\n", " coef_number_of_non_workers_adults\n", - " 40.041010\n", + " 0.344889\n", " F\n", " \n", " \n", " 13\n", " coef_number_of_non_workers_mixed\n", - " -96.438666\n", + " -0.067851\n", " F\n", " \n", " \n", " 14\n", " coef_number_of_children_too_young_for_school_c...\n", - " -110.048280\n", + " 0.661222\n", " F\n", " \n", " \n", " 15\n", " coef_number_of_children_too_young_for_school_m...\n", - " 9.539326\n", + " 1.065525\n", " F\n", " \n", " \n", " 16\n", " coef_number_of_pre_driving_age_children_children\n", - " 12.678858\n", + " 0.256545\n", " F\n", " \n", " \n", " 17\n", " coef_number_of_pre_driving_age_children_mixed\n", - " 158.960267\n", + " 0.311384\n", " F\n", " \n", " \n", " 18\n", " coef_number_of_driving_age_children_children\n", - " -172.311937\n", + " 0.646806\n", " F\n", " \n", " \n", " 19\n", " coef_number_of_driving_age_children_mixed\n", - " 184.761407\n", + " 0.494992\n", " F\n", " \n", " \n", " 20\n", " coef_low_income_households_adults\n", - " -16.894954\n", + " 2.520875\n", " F\n", " \n", " \n", " 21\n", " coef_low_income_households_mixed\n", - " -3.143593\n", + " 0.683195\n", " F\n", " \n", " \n", " 22\n", " coef_medium_income_households\n", - " -161.727385\n", + " 1.853225\n", " F\n", " \n", " \n", " 23\n", " coef_household_has_more_cars_than_workers_adults\n", - " -40.894264\n", + " 3.138920\n", " F\n", " \n", " \n", " 24\n", " coef_household_has_more_cars_than_workers_mixed\n", - " 153.815203\n", + " 0.384250\n", " F\n", " \n", " \n", " 25\n", " coef_household_in_urban_area\n", - " -21.823334\n", + " -0.441828\n", " F\n", " \n", " \n", " 26\n", " coef_household_in_suburban_area_adults\n", - " 0.510500\n", + " -1.123570\n", " F\n", " \n", " \n", " 27\n", " coef_household_in_suburban_area_mixed\n", - " 0.128300\n", + " 0.258299\n", " F\n", " \n", " \n", " 28\n", " coef_log_max_overlap_of_adults_time_windows\n", - " -36.285976\n", + " 1.288269\n", " F\n", " \n", " \n", " 29\n", " coef_log_max_overlap_of_childrens_time_windows\n", - " 283.696667\n", + " 1.783892\n", " F\n", " \n", " \n", " 30\n", " coef_log_max_overlap_of_time_windows\n", - " 196.728573\n", + " 1.505521\n", " F\n", " \n", " \n", @@ -2795,36 +2812,36 @@ "text/plain": [ " coefficient_name value constrain\n", "0 coef_unavailable -999.000000 T\n", - "1 coef_asc_children 121.627746 F\n", - "2 coef_asc_mixed -88.249613 fF\n", + "1 coef_asc_children 6.744041 F\n", + "2 coef_asc_mixed 6.886657 fF\n", "3 coef_tour_purpose_is_eating_out_children -0.967800 F\n", "4 coef_tour_purpose_is_eating_out_mixed -0.802700 F\n", "5 coef_tour_purpose_is_discretionary_adults 0.764800 F\n", "6 coef_tour_purpose_is_discretionary_children 0.510100 F\n", - "7 coef_number_of_full_time_workers_adults 185.490311 F\n", - "8 coef_number_of_full_time_workers_mixed 50.943193 F\n", - "9 coef_number_of_part_time_workers_adults 47.088158 F\n", - "10 coef_number_of_part_time_workers_mixed 58.958712 F\n", - "11 coef_number_of_university_students -5.007830 F\n", - "12 coef_number_of_non_workers_adults 40.041010 F\n", - "13 coef_number_of_non_workers_mixed -96.438666 F\n", - "14 coef_number_of_children_too_young_for_school_c... -110.048280 F\n", - "15 coef_number_of_children_too_young_for_school_m... 9.539326 F\n", - "16 coef_number_of_pre_driving_age_children_children 12.678858 F\n", - "17 coef_number_of_pre_driving_age_children_mixed 158.960267 F\n", - "18 coef_number_of_driving_age_children_children -172.311937 F\n", - "19 coef_number_of_driving_age_children_mixed 184.761407 F\n", - "20 coef_low_income_households_adults -16.894954 F\n", - "21 coef_low_income_households_mixed -3.143593 F\n", - "22 coef_medium_income_households -161.727385 F\n", - "23 coef_household_has_more_cars_than_workers_adults -40.894264 F\n", - "24 coef_household_has_more_cars_than_workers_mixed 153.815203 F\n", - "25 coef_household_in_urban_area -21.823334 F\n", - "26 coef_household_in_suburban_area_adults 0.510500 F\n", - "27 coef_household_in_suburban_area_mixed 0.128300 F\n", - "28 coef_log_max_overlap_of_adults_time_windows -36.285976 F\n", - "29 coef_log_max_overlap_of_childrens_time_windows 283.696667 F\n", - "30 coef_log_max_overlap_of_time_windows 196.728573 F" + "7 coef_number_of_full_time_workers_adults 1.638383 F\n", + "8 coef_number_of_full_time_workers_mixed 0.106573 F\n", + "9 coef_number_of_part_time_workers_adults 0.094715 F\n", + "10 coef_number_of_part_time_workers_mixed 0.182067 F\n", + "11 coef_number_of_university_students 0.067485 F\n", + "12 coef_number_of_non_workers_adults 0.344889 F\n", + "13 coef_number_of_non_workers_mixed -0.067851 F\n", + "14 coef_number_of_children_too_young_for_school_c... 0.661222 F\n", + "15 coef_number_of_children_too_young_for_school_m... 1.065525 F\n", + "16 coef_number_of_pre_driving_age_children_children 0.256545 F\n", + "17 coef_number_of_pre_driving_age_children_mixed 0.311384 F\n", + "18 coef_number_of_driving_age_children_children 0.646806 F\n", + "19 coef_number_of_driving_age_children_mixed 0.494992 F\n", + "20 coef_low_income_households_adults 2.520875 F\n", + "21 coef_low_income_households_mixed 0.683195 F\n", + "22 coef_medium_income_households 1.853225 F\n", + "23 coef_household_has_more_cars_than_workers_adults 3.138920 F\n", + "24 coef_household_has_more_cars_than_workers_mixed 0.384250 F\n", + "25 coef_household_in_urban_area -0.441828 F\n", + "26 coef_household_in_suburban_area_adults -1.123570 F\n", + "27 coef_household_in_suburban_area_mixed 0.258299 F\n", + "28 coef_log_max_overlap_of_adults_time_windows 1.288269 F\n", + "29 coef_log_max_overlap_of_childrens_time_windows 1.783892 F\n", + "30 coef_log_max_overlap_of_time_windows 1.505521 F" ] }, "execution_count": 11, @@ -2844,7 +2861,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -2858,7 +2875,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/12_joint_tour_participation.ipynb b/activitysim/examples/example_estimation/notebooks/12_joint_tour_participation.ipynb index 22eb78efae..6aa4c7d142 100644 --- a/activitysim/examples/example_estimation/notebooks/12_joint_tour_participation.ipynb +++ b/activitysim/examples/example_estimation/notebooks/12_joint_tour_participation.ipynb @@ -34,27 +34,75 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +116,27 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/joint_tour_participation/joint_tour_participation_coefficients.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/joint_tour_participation/joint_tour_participation_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_participation/joint_tour_participation_values_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"joint_tour_participation\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -794,14 +857,14 @@ " \n", " \n", " \n", - " 778529801\n", + " 785368601\n", " 0\n", " 0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -812,20 +875,20 @@ " True\n", " False\n", " False\n", + " True\n", " False\n", - " False\n", - " False\n", + " True\n", " 1\n", " \n", " \n", - " 778529802\n", + " 785368602\n", " 0\n", " 0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -836,20 +899,20 @@ " True\n", " False\n", " False\n", + " True\n", " False\n", - " False\n", - " False\n", + " True\n", " 1\n", " \n", " \n", - " 870845401\n", + " 790231801\n", " 0\n", " 0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -860,20 +923,20 @@ " True\n", " False\n", " False\n", + " True\n", " False\n", - " False\n", - " False\n", + " True\n", " 1\n", " \n", " \n", - " 870845402\n", + " 790231802\n", " 0\n", " 0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -884,20 +947,20 @@ " True\n", " False\n", " False\n", + " True\n", " False\n", - " False\n", - " False\n", + " True\n", " 1\n", " \n", " \n", - " 971500601\n", + " 790977601\n", " 0\n", " 0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -910,7 +973,7 @@ " False\n", " False\n", " False\n", - " False\n", + " True\n", " 1\n", " \n", " \n", @@ -938,10 +1001,9 @@ " ...\n", " \n", " \n", - " 29881474102\n", - " 0\n", - " 0\n", - " 0.0\n", + " 30524624502\n", + " 1\n", + " 1\n", " 1.0\n", " 0.0\n", " 0.0\n", @@ -949,25 +1011,26 @@ " 0.0\n", " 0.0\n", " 0.0\n", + " 0.0\n", " ...\n", " False\n", " False\n", " False\n", - " True\n", " False\n", " False\n", + " True\n", " False\n", " True\n", " False\n", - " 1\n", + " 2\n", " \n", " \n", - " 30181098001\n", - " 1\n", - " 1\n", - " 0.0\n", + " 30524624503\n", + " 0\n", + " 0\n", " 0.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -977,21 +1040,21 @@ " False\n", " False\n", " False\n", - " True\n", " False\n", " False\n", + " True\n", " False\n", " True\n", " False\n", - " 2\n", + " 1\n", " \n", " \n", - " 30181098002\n", + " 30524624504\n", " 0\n", " 0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -1001,22 +1064,22 @@ " False\n", " False\n", " False\n", - " True\n", " False\n", " False\n", + " True\n", " False\n", " True\n", " False\n", " 1\n", " \n", " \n", - " 30181098003\n", + " 30524624505\n", " 0\n", " 0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -1025,16 +1088,16 @@ " False\n", " False\n", " False\n", - " True\n", " False\n", " False\n", + " True\n", " False\n", " True\n", " False\n", " 1\n", " \n", " \n", - " 30181098004\n", + " 30524624506\n", " 0\n", " 0\n", " 0.0\n", @@ -1044,14 +1107,14 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " ...\n", + " True\n", " False\n", " False\n", " False\n", - " True\n", - " False\n", " False\n", + " True\n", " False\n", " True\n", " False\n", @@ -1059,193 +1122,193 @@ " \n", " \n", "\n", - "

304 rows × 226 columns

\n", + "

4500 rows × 226 columns

\n", "" ], "text/plain": [ " model_choice override_choice \\\n", "participant_id \n", - "778529801 0 0 \n", - "778529802 0 0 \n", - "870845401 0 0 \n", - "870845402 0 0 \n", - "971500601 0 0 \n", + "785368601 0 0 \n", + "785368602 0 0 \n", + "790231801 0 0 \n", + "790231802 0 0 \n", + "790977601 0 0 \n", "... ... ... \n", - "29881474102 0 0 \n", - "30181098001 1 1 \n", - "30181098002 0 0 \n", - "30181098003 0 0 \n", - "30181098004 0 0 \n", + "30524624502 1 1 \n", + "30524624503 0 0 \n", + "30524624504 0 0 \n", + "30524624505 0 0 \n", + "30524624506 0 0 \n", "\n", " util_full_time_worker_mixed_party \\\n", "participant_id \n", - "778529801 0.0 \n", - "778529802 0.0 \n", - "870845401 0.0 \n", - "870845402 0.0 \n", - "971500601 0.0 \n", + "785368601 0.0 \n", + "785368602 0.0 \n", + "790231801 0.0 \n", + "790231802 0.0 \n", + "790977601 0.0 \n", "... ... \n", - "29881474102 0.0 \n", - "30181098001 0.0 \n", - "30181098002 0.0 \n", - "30181098003 0.0 \n", - "30181098004 0.0 \n", + "30524624502 1.0 \n", + "30524624503 0.0 \n", + "30524624504 0.0 \n", + "30524624505 0.0 \n", + "30524624506 0.0 \n", "\n", " util_part_time_worker_adults_only_party \\\n", "participant_id \n", - 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"29881474102 False False False \n", - "30181098001 False False False \n", - "30181098002 False False False \n", - "30181098003 False False False \n", - "30181098004 False False False \n", + "30524624502 False False False \n", + "30524624503 False False False \n", + "30524624504 False False False \n", + "30524624505 False False False \n", + "30524624506 True False False \n", "\n", " tour_composition_is_adults tour_composition_is_children \\\n", "participant_id \n", - "778529801 True False \n", - "778529802 True False \n", - "870845401 True False \n", - "870845402 True False \n", - "971500601 True False \n", + "785368601 True False \n", + "785368602 True False \n", + "790231801 True False \n", + "790231802 True False \n", + "790977601 True False \n", "... ... ... \n", - "29881474102 True False \n", - "30181098001 True False \n", - "30181098002 True False \n", - "30181098003 True False \n", - "30181098004 True False \n", + "30524624502 False False \n", + "30524624503 False False \n", + "30524624504 False False \n", + "30524624505 False False \n", + "30524624506 False False \n", "\n", " tour_composition_is_mixed home_is_suburban high_income \\\n", "participant_id \n", - 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"29881474102 False 1 \n", - "30181098001 False 2 \n", - "30181098002 False 1 \n", - "30181098003 False 1 \n", - "30181098004 False 1 \n", + "30524624502 False 2 \n", + "30524624503 False 1 \n", + "30524624504 False 1 \n", + "30524624505 False 1 \n", + "30524624506 False 1 \n", "\n", - "[304 rows x 226 columns]" + "[4500 rows x 226 columns]" ] }, "execution_count": 6, @@ -1271,17 +1334,10 @@ "execution_count": 7, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

Iteration 112 [Optimization terminated successfully]

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Iteration 080 [Optimization terminated successfully]

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Best LL = -61.383086448632596

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Best LL = -1240.495238444391

" ], "text/plain": [ "" @@ -1324,913 +1380,867 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_adult_log_of_max_window_overlap_with_a_child_mixed\n", - " 4.595737\n", + " 2.125116\n", + " 2.125116\n", " 2.18900\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4.595737\n", " \n", " \n", " coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party\n", - " 1.692145\n", + " 1.280678\n", + " 1.280678\n", " 0.84360\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.692145\n", " \n", " \n", " coef_adult_more_automobiles_than_workers_adult_only_party\n", - " 0.311671\n", + " 0.121220\n", + " 0.121220\n", " -0.21330\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.311671\n", " \n", " \n", " coef_adult_more_automobiles_than_workers_mixed_party\n", - " -1.827740\n", + " -0.591966\n", + " -0.591966\n", " -0.60310\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.827740\n", " \n", " \n", " coef_adult_number_of_joint_tours_adult_only\n", - " -2.134054\n", + " -0.794091\n", + " -0.794091\n", " -0.32420\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.134054\n", " \n", " \n", " coef_adult_number_of_joint_tours_mixed\n", - " -28.572220\n", + " -1.417451\n", + " -1.417451\n", " -0.35840\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -28.572220\n", " \n", " \n", " coef_adult_number_of_other_adults_in_the_household_adults_only_party\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_adult_number_of_other_adults_in_the_household_mixed_party\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_child_log_of_max_window_overlap_with_a_child_child\n", - " 1.275585\n", + " 1.296000\n", + " 1.296000\n", " 1.29600\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.275585\n", " \n", " \n", " coef_child_log_of_max_window_overlap_with_an_adult_mixed\n", - " 1.539267\n", + " 1.538000\n", + " 1.538000\n", " 1.53800\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.539267\n", " \n", " \n", " coef_child_more_automobiles_than_workers_child_only_party\n", - " -0.394683\n", + " -0.421400\n", + " -0.421400\n", " -0.42140\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.394683\n", " \n", " \n", " coef_child_more_automobiles_than_workers_mixed_party\n", - " -1.551914\n", + " -0.366466\n", + " -0.366466\n", " -0.37760\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.551914\n", " \n", " \n", " coef_child_number_of_joint_tours_child_only\n", - " 4.977604\n", + " 0.866122\n", + " 0.866122\n", " 0.10470\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4.977604\n", " \n", " \n", " coef_child_number_of_joint_tours_mixed\n", - " 17.894892\n", + " -0.261747\n", + " -0.261747\n", " -0.50890\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 17.894892\n", " \n", " \n", " coef_child_number_of_other_children_in_the_household_child_only_party\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_child_number_of_other_children_in_the_household_mixed\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_child_too_young_for_school_children_only_party\n", - " -2.785631\n", + " -1.149596\n", + " -1.149596\n", " -2.78600\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.785631\n", " \n", " \n", " coef_child_too_young_for_school_mixed_party\n", - " 2.069934\n", + " 0.197836\n", + " 0.197836\n", " -1.89300\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2.069934\n", " \n", " \n", " coef_child_too_young_for_school_specific_to_discretionary_joint_tours\n", - " 0.128371\n", + " 0.128400\n", + " 0.128400\n", " 0.12840\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.128371\n", " \n", " \n", " coef_child_too_young_for_school_specific_to_eating_out_joint_tours\n", - " 0.658655\n", + " 0.658900\n", + " 0.658900\n", " 0.65890\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.658655\n", " \n", " \n", " coef_driving_age_student_children_only_party\n", - " -1.822000\n", + " -2.120496\n", + " -2.120496\n", " -1.82200\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.822000\n", " \n", " \n", " coef_driving_age_student_mixed_party\n", - " -28.998969\n", + " 0.322986\n", + " 0.322986\n", " -1.35300\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -28.998969\n", " \n", " \n", " coef_driving_age_student_specific_to_discretionary_joint_tours\n", " -0.667500\n", + " -0.667500\n", " -0.66750\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.667500\n", " \n", " \n", " coef_driving_age_student_specific_to_eating_out_joint_tours\n", " 2.344000\n", + " 2.344000\n", " 2.34400\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2.344000\n", " \n", " \n", " coef_dummy_for_high_income_for_adult_in_adult_party\n", - " 0.131783\n", + " -0.068202\n", + " -0.068202\n", " -0.16820\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.131783\n", " \n", " \n", " coef_dummy_for_high_income_for_adult_in_mixed_party\n", - " -0.378918\n", + " 0.112930\n", + " 0.112930\n", " -0.02613\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.378918\n", " \n", " \n", " coef_dummy_for_high_income_for_child_in_children_party\n", - " -0.561900\n", + " -0.211892\n", + " -0.211892\n", " -0.56190\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.561900\n", " \n", " \n", " coef_dummy_for_high_income_for_child_in_mixed_party\n", - " -0.513571\n", + " -0.013740\n", + " -0.013740\n", " -0.15280\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.513571\n", " \n", " \n", " coef_full_time_worker_mixed_party\n", - " -957.202749\n", + " -3.527365\n", + " -3.527365\n", " -3.56600\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -957.202749\n", " \n", " \n", " coef_full_time_worker_mixed_party_not\n", " 0.500000\n", + " 0.500000\n", " 0.50000\n", + " 0.5\n", + " 0.5\n", " 0.0\n", - " NaN\n", - " NaN\n", " 1\n", - " \n", - " 0.500000\n", " \n", " \n", " coef_full_time_worker_specific_to_discretionary_joint_tours\n", " 0.439200\n", + " 0.439200\n", " 0.43920\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.439200\n", " \n", " \n", " coef_full_time_worker_specific_to_discretionary_joint_tours_not\n", " 0.500000\n", + " 0.500000\n", " 0.50000\n", + " 0.5\n", + " 0.5\n", " 0.0\n", - " NaN\n", - " NaN\n", " 1\n", - " \n", - " 0.500000\n", " \n", " \n", " coef_full_time_worker_specific_to_eating_out_joint_tours\n", " 0.715700\n", + " 0.715700\n", " 0.71570\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.715700\n", " \n", " \n", " coef_full_time_worker_specific_to_eating_out_joint_tours_not\n", " 0.500000\n", + " 0.500000\n", " 0.50000\n", + " 0.5\n", + " 0.5\n", " 0.0\n", - " NaN\n", - " NaN\n", " 1\n", - " \n", - " 0.500000\n", " \n", " \n", " coef_household_in_suburban_area_adult_adult_only_party\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_household_in_suburban_area_adult_mixed_party\n", - " -0.060070\n", + " 1.239881\n", + " 1.239881\n", " -0.06007\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.060070\n", " \n", " \n", " coef_household_in_suburban_area_child_child_only_party\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_household_in_suburban_area_child_mixed_party\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_household_in_urban_area_adult_adult_only_party\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_household_in_urban_area_adult_mixed_party\n", - " 978.504490\n", + " 1.204039\n", + " 1.204039\n", " -0.13700\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 978.504490\n", " \n", " \n", " coef_household_in_urban_area_child_child_only_party\n", - " 6.082784\n", + " -0.145369\n", + " -0.145369\n", " 1.21000\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 6.082784\n", " \n", " \n", " coef_household_in_urban_area_child_mixed_party\n", - " -19.290030\n", + " -0.138857\n", + " -0.138857\n", " 0.62650\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -19.290030\n", " \n", " \n", " coef_non_worker_adults_only_party\n", - " -4.080384\n", + " -3.161945\n", + " -3.161945\n", " -3.16400\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.080384\n", " \n", " \n", " coef_non_worker_mixed_party\n", - " -125.288137\n", + " 1.059162\n", + " 1.059162\n", " 0.71520\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -125.288137\n", " \n", " \n", " coef_non_worker_specific_to_discretionary_joint_tours\n", " -0.183500\n", + " -0.183500\n", " -0.18350\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.183500\n", " \n", " \n", " coef_non_worker_specific_to_eating_out_joint_tours\n", " 0.161700\n", + " 0.161700\n", " 0.16170\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.161700\n", " \n", " \n", " coef_part_time_worker_adults_only_party\n", - " -3.248302\n", + " -3.631928\n", + " -3.631928\n", " -3.56600\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -3.248302\n", " \n", " \n", " coef_part_time_worker_adults_only_party_not\n", " 0.500000\n", + " 0.500000\n", " 0.50000\n", + " 0.5\n", + " 0.5\n", " 0.0\n", - " NaN\n", - " NaN\n", " 1\n", - " \n", - " 0.500000\n", " \n", " \n", " coef_part_time_worker_mixed_party\n", - " 2254.660944\n", + " -0.447984\n", + " -0.447984\n", " -0.36550\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2254.660944\n", " \n", " \n", " coef_part_time_worker_specific_to_discretionary_joint_tours\n", " 0.285000\n", + " 0.285000\n", " 0.28500\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.285000\n", " \n", " \n", " coef_part_time_worker_specific_to_eating_out_joint_tours\n", " 2.188000\n", + " 2.188000\n", " 2.18800\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2.188000\n", " \n", " \n", " coef_pre_driving_age_student_children_only_party\n", - " 4.151085\n", + " 0.991812\n", + " 0.991812\n", " -0.72170\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4.151085\n", " \n", " \n", " coef_pre_driving_age_student_mixed_party\n", - " 2.007228\n", + " -0.073175\n", + " -0.073175\n", " -1.75200\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2.007228\n", " \n", " \n", " coef_pre_driving_age_student_specific_to_discretionary_joint_tours\n", " 0.662600\n", + " 0.662600\n", " 0.66260\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.662600\n", " \n", " \n", " coef_pre_driving_age_student_specific_to_eating_out_joint_tours\n", " 1.391000\n", + " 1.391000\n", " 1.39100\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.391000\n", " \n", " \n", " coef_unavailable\n", " -999.000000\n", + " -999.000000\n", " -999.00000\n", + " -999.0\n", + " -999.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_university_student_mixed_party\n", - " -958.612314\n", + " -2.902637\n", + " -2.902637\n", " -3.04100\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -958.612314\n", " \n", " \n", " coef_university_student_specific_to_discretionary_joint_tours\n", " 0.000000\n", + " 0.000000\n", " 0.00000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_university_student_specific_to_eating_out_joint_tours\n", " -0.820000\n", + " -0.820000\n", " -0.82000\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.820000\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_adult_log_of_max_window_overlap_with_a_chi... 4.595737 2.18900 \n", - "coef_adult_log_of_max_window_overlap_with_an_ad... 1.692145 0.84360 \n", - "coef_adult_more_automobiles_than_workers_adult_... 0.311671 -0.21330 \n", - "coef_adult_more_automobiles_than_workers_mixed_... -1.827740 -0.60310 \n", - "coef_adult_number_of_joint_tours_adult_only -2.134054 -0.32420 \n", - "coef_adult_number_of_joint_tours_mixed -28.572220 -0.35840 \n", - "coef_adult_number_of_other_adults_in_the_househ... 0.000000 0.00000 \n", - "coef_adult_number_of_other_adults_in_the_househ... 0.000000 0.00000 \n", - "coef_child_log_of_max_window_overlap_with_a_chi... 1.275585 1.29600 \n", - "coef_child_log_of_max_window_overlap_with_an_ad... 1.539267 1.53800 \n", - "coef_child_more_automobiles_than_workers_child_... -0.394683 -0.42140 \n", - "coef_child_more_automobiles_than_workers_mixed_... -1.551914 -0.37760 \n", - "coef_child_number_of_joint_tours_child_only 4.977604 0.10470 \n", - "coef_child_number_of_joint_tours_mixed 17.894892 -0.50890 \n", - "coef_child_number_of_other_children_in_the_hous... 0.000000 0.00000 \n", - "coef_child_number_of_other_children_in_the_hous... 0.000000 0.00000 \n", - "coef_child_too_young_for_school_children_only_p... -2.785631 -2.78600 \n", - "coef_child_too_young_for_school_mixed_party 2.069934 -1.89300 \n", - "coef_child_too_young_for_school_specific_to_dis... 0.128371 0.12840 \n", - "coef_child_too_young_for_school_specific_to_eat... 0.658655 0.65890 \n", - "coef_driving_age_student_children_only_party -1.822000 -1.82200 \n", - "coef_driving_age_student_mixed_party -28.998969 -1.35300 \n", - "coef_driving_age_student_specific_to_discretion... -0.667500 -0.66750 \n", - "coef_driving_age_student_specific_to_eating_out... 2.344000 2.34400 \n", - "coef_dummy_for_high_income_for_adult_in_adult_p... 0.131783 -0.16820 \n", - "coef_dummy_for_high_income_for_adult_in_mixed_p... -0.378918 -0.02613 \n", - "coef_dummy_for_high_income_for_child_in_childre... -0.561900 -0.56190 \n", - "coef_dummy_for_high_income_for_child_in_mixed_p... -0.513571 -0.15280 \n", - "coef_full_time_worker_mixed_party -957.202749 -3.56600 \n", - "coef_full_time_worker_mixed_party_not 0.500000 0.50000 \n", - "coef_full_time_worker_specific_to_discretionary... 0.439200 0.43920 \n", - "coef_full_time_worker_specific_to_discretionary... 0.500000 0.50000 \n", - "coef_full_time_worker_specific_to_eating_out_jo... 0.715700 0.71570 \n", - "coef_full_time_worker_specific_to_eating_out_jo... 0.500000 0.50000 \n", - "coef_household_in_suburban_area_adult_adult_onl... 0.000000 0.00000 \n", - "coef_household_in_suburban_area_adult_mixed_party -0.060070 -0.06007 \n", - "coef_household_in_suburban_area_child_child_onl... 0.000000 0.00000 \n", - "coef_household_in_suburban_area_child_mixed_party 0.000000 0.00000 \n", - "coef_household_in_urban_area_adult_adult_only_p... 0.000000 0.00000 \n", - "coef_household_in_urban_area_adult_mixed_party 978.504490 -0.13700 \n", - "coef_household_in_urban_area_child_child_only_p... 6.082784 1.21000 \n", - "coef_household_in_urban_area_child_mixed_party -19.290030 0.62650 \n", - "coef_non_worker_adults_only_party -4.080384 -3.16400 \n", - "coef_non_worker_mixed_party -125.288137 0.71520 \n", - "coef_non_worker_specific_to_discretionary_joint... -0.183500 -0.18350 \n", - "coef_non_worker_specific_to_eating_out_joint_tours 0.161700 0.16170 \n", - "coef_part_time_worker_adults_only_party -3.248302 -3.56600 \n", - "coef_part_time_worker_adults_only_party_not 0.500000 0.50000 \n", - "coef_part_time_worker_mixed_party 2254.660944 -0.36550 \n", - "coef_part_time_worker_specific_to_discretionary... 0.285000 0.28500 \n", - "coef_part_time_worker_specific_to_eating_out_jo... 2.188000 2.18800 \n", - "coef_pre_driving_age_student_children_only_party 4.151085 -0.72170 \n", - "coef_pre_driving_age_student_mixed_party 2.007228 -1.75200 \n", - "coef_pre_driving_age_student_specific_to_discre... 0.662600 0.66260 \n", - "coef_pre_driving_age_student_specific_to_eating... 1.391000 1.39100 \n", - "coef_unavailable -999.000000 -999.00000 \n", - "coef_university_student_mixed_party -958.612314 -3.04100 \n", - "coef_university_student_specific_to_discretiona... 0.000000 0.00000 \n", - "coef_university_student_specific_to_eating_out_... -0.820000 -0.82000 \n", + " value best \\\n", + "param_name \n", + "coef_adult_log_of_max_window_overlap_with_a_chi... 2.125116 2.125116 \n", + "coef_adult_log_of_max_window_overlap_with_an_ad... 1.280678 1.280678 \n", + "coef_adult_more_automobiles_than_workers_adult_... 0.121220 0.121220 \n", + "coef_adult_more_automobiles_than_workers_mixed_... -0.591966 -0.591966 \n", + "coef_adult_number_of_joint_tours_adult_only -0.794091 -0.794091 \n", + "coef_adult_number_of_joint_tours_mixed -1.417451 -1.417451 \n", + "coef_adult_number_of_other_adults_in_the_househ... 0.000000 0.000000 \n", + "coef_adult_number_of_other_adults_in_the_househ... 0.000000 0.000000 \n", + "coef_child_log_of_max_window_overlap_with_a_chi... 1.296000 1.296000 \n", + "coef_child_log_of_max_window_overlap_with_an_ad... 1.538000 1.538000 \n", + "coef_child_more_automobiles_than_workers_child_... -0.421400 -0.421400 \n", + "coef_child_more_automobiles_than_workers_mixed_... -0.366466 -0.366466 \n", + "coef_child_number_of_joint_tours_child_only 0.866122 0.866122 \n", + "coef_child_number_of_joint_tours_mixed -0.261747 -0.261747 \n", + "coef_child_number_of_other_children_in_the_hous... 0.000000 0.000000 \n", + "coef_child_number_of_other_children_in_the_hous... 0.000000 0.000000 \n", + "coef_child_too_young_for_school_children_only_p... -1.149596 -1.149596 \n", + "coef_child_too_young_for_school_mixed_party 0.197836 0.197836 \n", + "coef_child_too_young_for_school_specific_to_dis... 0.128400 0.128400 \n", + "coef_child_too_young_for_school_specific_to_eat... 0.658900 0.658900 \n", + "coef_driving_age_student_children_only_party -2.120496 -2.120496 \n", + "coef_driving_age_student_mixed_party 0.322986 0.322986 \n", + "coef_driving_age_student_specific_to_discretion... -0.667500 -0.667500 \n", + "coef_driving_age_student_specific_to_eating_out... 2.344000 2.344000 \n", + "coef_dummy_for_high_income_for_adult_in_adult_p... -0.068202 -0.068202 \n", + "coef_dummy_for_high_income_for_adult_in_mixed_p... 0.112930 0.112930 \n", + "coef_dummy_for_high_income_for_child_in_childre... -0.211892 -0.211892 \n", + "coef_dummy_for_high_income_for_child_in_mixed_p... -0.013740 -0.013740 \n", + "coef_full_time_worker_mixed_party -3.527365 -3.527365 \n", + "coef_full_time_worker_mixed_party_not 0.500000 0.500000 \n", + "coef_full_time_worker_specific_to_discretionary... 0.439200 0.439200 \n", + "coef_full_time_worker_specific_to_discretionary... 0.500000 0.500000 \n", + "coef_full_time_worker_specific_to_eating_out_jo... 0.715700 0.715700 \n", + "coef_full_time_worker_specific_to_eating_out_jo... 0.500000 0.500000 \n", + "coef_household_in_suburban_area_adult_adult_onl... 0.000000 0.000000 \n", + "coef_household_in_suburban_area_adult_mixed_party 1.239881 1.239881 \n", + "coef_household_in_suburban_area_child_child_onl... 0.000000 0.000000 \n", + "coef_household_in_suburban_area_child_mixed_party 0.000000 0.000000 \n", + "coef_household_in_urban_area_adult_adult_only_p... 0.000000 0.000000 \n", + "coef_household_in_urban_area_adult_mixed_party 1.204039 1.204039 \n", + "coef_household_in_urban_area_child_child_only_p... -0.145369 -0.145369 \n", + "coef_household_in_urban_area_child_mixed_party -0.138857 -0.138857 \n", + "coef_non_worker_adults_only_party -3.161945 -3.161945 \n", + "coef_non_worker_mixed_party 1.059162 1.059162 \n", + "coef_non_worker_specific_to_discretionary_joint... -0.183500 -0.183500 \n", + "coef_non_worker_specific_to_eating_out_joint_tours 0.161700 0.161700 \n", + "coef_part_time_worker_adults_only_party -3.631928 -3.631928 \n", + "coef_part_time_worker_adults_only_party_not 0.500000 0.500000 \n", + "coef_part_time_worker_mixed_party -0.447984 -0.447984 \n", + "coef_part_time_worker_specific_to_discretionary... 0.285000 0.285000 \n", + "coef_part_time_worker_specific_to_eating_out_jo... 2.188000 2.188000 \n", + "coef_pre_driving_age_student_children_only_party 0.991812 0.991812 \n", + "coef_pre_driving_age_student_mixed_party -0.073175 -0.073175 \n", + "coef_pre_driving_age_student_specific_to_discre... 0.662600 0.662600 \n", + "coef_pre_driving_age_student_specific_to_eating... 1.391000 1.391000 \n", + "coef_unavailable -999.000000 -999.000000 \n", + "coef_university_student_mixed_party -2.902637 -2.902637 \n", + "coef_university_student_specific_to_discretiona... 0.000000 0.000000 \n", + "coef_university_student_specific_to_eating_out_... -0.820000 -0.820000 \n", "\n", - " nullvalue minimum \\\n", - "coef_adult_log_of_max_window_overlap_with_a_chi... 0.0 NaN \n", - "coef_adult_log_of_max_window_overlap_with_an_ad... 0.0 NaN \n", - "coef_adult_more_automobiles_than_workers_adult_... 0.0 NaN \n", - "coef_adult_more_automobiles_than_workers_mixed_... 0.0 NaN \n", - "coef_adult_number_of_joint_tours_adult_only 0.0 NaN \n", - "coef_adult_number_of_joint_tours_mixed 0.0 NaN \n", - "coef_adult_number_of_other_adults_in_the_househ... 0.0 NaN \n", - "coef_adult_number_of_other_adults_in_the_househ... 0.0 NaN \n", - "coef_child_log_of_max_window_overlap_with_a_chi... 0.0 NaN \n", - "coef_child_log_of_max_window_overlap_with_an_ad... 0.0 NaN \n", - "coef_child_more_automobiles_than_workers_child_... 0.0 NaN \n", - "coef_child_more_automobiles_than_workers_mixed_... 0.0 NaN \n", - "coef_child_number_of_joint_tours_child_only 0.0 NaN \n", - "coef_child_number_of_joint_tours_mixed 0.0 NaN \n", - "coef_child_number_of_other_children_in_the_hous... 0.0 NaN \n", - "coef_child_number_of_other_children_in_the_hous... 0.0 NaN \n", - "coef_child_too_young_for_school_children_only_p... 0.0 NaN \n", - "coef_child_too_young_for_school_mixed_party 0.0 NaN \n", - "coef_child_too_young_for_school_specific_to_dis... 0.0 NaN \n", - "coef_child_too_young_for_school_specific_to_eat... 0.0 NaN \n", - "coef_driving_age_student_children_only_party 0.0 NaN \n", - "coef_driving_age_student_mixed_party 0.0 NaN \n", - "coef_driving_age_student_specific_to_discretion... 0.0 NaN \n", - "coef_driving_age_student_specific_to_eating_out... 0.0 NaN \n", - "coef_dummy_for_high_income_for_adult_in_adult_p... 0.0 NaN \n", - "coef_dummy_for_high_income_for_adult_in_mixed_p... 0.0 NaN \n", - "coef_dummy_for_high_income_for_child_in_childre... 0.0 NaN \n", - "coef_dummy_for_high_income_for_child_in_mixed_p... 0.0 NaN \n", - "coef_full_time_worker_mixed_party 0.0 NaN \n", - "coef_full_time_worker_mixed_party_not 0.0 NaN \n", - "coef_full_time_worker_specific_to_discretionary... 0.0 NaN \n", - "coef_full_time_worker_specific_to_discretionary... 0.0 NaN \n", - "coef_full_time_worker_specific_to_eating_out_jo... 0.0 NaN \n", - "coef_full_time_worker_specific_to_eating_out_jo... 0.0 NaN \n", - "coef_household_in_suburban_area_adult_adult_onl... 0.0 NaN \n", - "coef_household_in_suburban_area_adult_mixed_party 0.0 NaN \n", - "coef_household_in_suburban_area_child_child_onl... 0.0 NaN \n", - "coef_household_in_suburban_area_child_mixed_party 0.0 NaN \n", - "coef_household_in_urban_area_adult_adult_only_p... 0.0 NaN \n", - "coef_household_in_urban_area_adult_mixed_party 0.0 NaN \n", - "coef_household_in_urban_area_child_child_only_p... 0.0 NaN \n", - "coef_household_in_urban_area_child_mixed_party 0.0 NaN \n", - "coef_non_worker_adults_only_party 0.0 NaN \n", - "coef_non_worker_mixed_party 0.0 NaN \n", - "coef_non_worker_specific_to_discretionary_joint... 0.0 NaN \n", - "coef_non_worker_specific_to_eating_out_joint_tours 0.0 NaN \n", - "coef_part_time_worker_adults_only_party 0.0 NaN \n", - "coef_part_time_worker_adults_only_party_not 0.0 NaN \n", - "coef_part_time_worker_mixed_party 0.0 NaN \n", - "coef_part_time_worker_specific_to_discretionary... 0.0 NaN \n", - "coef_part_time_worker_specific_to_eating_out_jo... 0.0 NaN \n", - "coef_pre_driving_age_student_children_only_party 0.0 NaN \n", - "coef_pre_driving_age_student_mixed_party 0.0 NaN \n", - "coef_pre_driving_age_student_specific_to_discre... 0.0 NaN \n", - "coef_pre_driving_age_student_specific_to_eating... 0.0 NaN \n", - "coef_unavailable 0.0 NaN \n", - "coef_university_student_mixed_party 0.0 NaN \n", - "coef_university_student_specific_to_discretiona... 0.0 NaN \n", - "coef_university_student_specific_to_eating_out_... 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_adult_log_of_max_window_overlap_with_a_chi... 2.18900 -50.0 \n", + "coef_adult_log_of_max_window_overlap_with_an_ad... 0.84360 -50.0 \n", + "coef_adult_more_automobiles_than_workers_adult_... -0.21330 -50.0 \n", + "coef_adult_more_automobiles_than_workers_mixed_... -0.60310 -50.0 \n", + "coef_adult_number_of_joint_tours_adult_only -0.32420 -50.0 \n", + "coef_adult_number_of_joint_tours_mixed -0.35840 -50.0 \n", + "coef_adult_number_of_other_adults_in_the_househ... 0.00000 0.0 \n", + "coef_adult_number_of_other_adults_in_the_househ... 0.00000 0.0 \n", + "coef_child_log_of_max_window_overlap_with_a_chi... 1.29600 -50.0 \n", + "coef_child_log_of_max_window_overlap_with_an_ad... 1.53800 -50.0 \n", + "coef_child_more_automobiles_than_workers_child_... -0.42140 -50.0 \n", + "coef_child_more_automobiles_than_workers_mixed_... -0.37760 -50.0 \n", + "coef_child_number_of_joint_tours_child_only 0.10470 -50.0 \n", + "coef_child_number_of_joint_tours_mixed -0.50890 -50.0 \n", + "coef_child_number_of_other_children_in_the_hous... 0.00000 0.0 \n", + "coef_child_number_of_other_children_in_the_hous... 0.00000 0.0 \n", + "coef_child_too_young_for_school_children_only_p... -2.78600 -50.0 \n", + "coef_child_too_young_for_school_mixed_party -1.89300 -50.0 \n", + "coef_child_too_young_for_school_specific_to_dis... 0.12840 -50.0 \n", + "coef_child_too_young_for_school_specific_to_eat... 0.65890 -50.0 \n", + "coef_driving_age_student_children_only_party -1.82200 -50.0 \n", + "coef_driving_age_student_mixed_party -1.35300 -50.0 \n", + "coef_driving_age_student_specific_to_discretion... -0.66750 -50.0 \n", + "coef_driving_age_student_specific_to_eating_out... 2.34400 -50.0 \n", + "coef_dummy_for_high_income_for_adult_in_adult_p... -0.16820 -50.0 \n", + "coef_dummy_for_high_income_for_adult_in_mixed_p... -0.02613 -50.0 \n", + "coef_dummy_for_high_income_for_child_in_childre... -0.56190 -50.0 \n", + "coef_dummy_for_high_income_for_child_in_mixed_p... -0.15280 -50.0 \n", + "coef_full_time_worker_mixed_party -3.56600 -50.0 \n", + "coef_full_time_worker_mixed_party_not 0.50000 0.5 \n", + "coef_full_time_worker_specific_to_discretionary... 0.43920 -50.0 \n", + "coef_full_time_worker_specific_to_discretionary... 0.50000 0.5 \n", + "coef_full_time_worker_specific_to_eating_out_jo... 0.71570 -50.0 \n", + "coef_full_time_worker_specific_to_eating_out_jo... 0.50000 0.5 \n", + "coef_household_in_suburban_area_adult_adult_onl... 0.00000 0.0 \n", + "coef_household_in_suburban_area_adult_mixed_party -0.06007 -50.0 \n", + "coef_household_in_suburban_area_child_child_onl... 0.00000 0.0 \n", + "coef_household_in_suburban_area_child_mixed_party 0.00000 0.0 \n", + "coef_household_in_urban_area_adult_adult_only_p... 0.00000 0.0 \n", + "coef_household_in_urban_area_adult_mixed_party -0.13700 -50.0 \n", + "coef_household_in_urban_area_child_child_only_p... 1.21000 -50.0 \n", + "coef_household_in_urban_area_child_mixed_party 0.62650 -50.0 \n", + "coef_non_worker_adults_only_party -3.16400 -50.0 \n", + "coef_non_worker_mixed_party 0.71520 -50.0 \n", + "coef_non_worker_specific_to_discretionary_joint... -0.18350 -50.0 \n", + "coef_non_worker_specific_to_eating_out_joint_tours 0.16170 -50.0 \n", + "coef_part_time_worker_adults_only_party -3.56600 -50.0 \n", + "coef_part_time_worker_adults_only_party_not 0.50000 0.5 \n", + "coef_part_time_worker_mixed_party -0.36550 -50.0 \n", + "coef_part_time_worker_specific_to_discretionary... 0.28500 -50.0 \n", + "coef_part_time_worker_specific_to_eating_out_jo... 2.18800 -50.0 \n", + "coef_pre_driving_age_student_children_only_party -0.72170 -50.0 \n", + "coef_pre_driving_age_student_mixed_party -1.75200 -50.0 \n", + "coef_pre_driving_age_student_specific_to_discre... 0.66260 -50.0 \n", + "coef_pre_driving_age_student_specific_to_eating... 1.39100 -50.0 \n", + "coef_unavailable -999.00000 -999.0 \n", + "coef_university_student_mixed_party -3.04100 -50.0 \n", + "coef_university_student_specific_to_discretiona... 0.00000 0.0 \n", + "coef_university_student_specific_to_eating_out_... -0.82000 -50.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_adult_log_of_max_window_overlap_with_a_chi... NaN 0 \n", - "coef_adult_log_of_max_window_overlap_with_an_ad... NaN 0 \n", - "coef_adult_more_automobiles_than_workers_adult_... NaN 0 \n", - "coef_adult_more_automobiles_than_workers_mixed_... NaN 0 \n", - "coef_adult_number_of_joint_tours_adult_only NaN 0 \n", - "coef_adult_number_of_joint_tours_mixed NaN 0 \n", - "coef_adult_number_of_other_adults_in_the_househ... NaN 1 \n", - "coef_adult_number_of_other_adults_in_the_househ... NaN 1 \n", - "coef_child_log_of_max_window_overlap_with_a_chi... NaN 0 \n", - "coef_child_log_of_max_window_overlap_with_an_ad... NaN 0 \n", - "coef_child_more_automobiles_than_workers_child_... NaN 0 \n", - "coef_child_more_automobiles_than_workers_mixed_... NaN 0 \n", - "coef_child_number_of_joint_tours_child_only NaN 0 \n", - "coef_child_number_of_joint_tours_mixed NaN 0 \n", - "coef_child_number_of_other_children_in_the_hous... NaN 1 \n", - "coef_child_number_of_other_children_in_the_hous... NaN 1 \n", - "coef_child_too_young_for_school_children_only_p... NaN 0 \n", - "coef_child_too_young_for_school_mixed_party NaN 0 \n", - "coef_child_too_young_for_school_specific_to_dis... NaN 0 \n", - "coef_child_too_young_for_school_specific_to_eat... NaN 0 \n", - "coef_driving_age_student_children_only_party NaN 0 \n", - "coef_driving_age_student_mixed_party NaN 0 \n", - "coef_driving_age_student_specific_to_discretion... NaN 0 \n", - "coef_driving_age_student_specific_to_eating_out... NaN 0 \n", - "coef_dummy_for_high_income_for_adult_in_adult_p... NaN 0 \n", - "coef_dummy_for_high_income_for_adult_in_mixed_p... NaN 0 \n", - "coef_dummy_for_high_income_for_child_in_childre... NaN 0 \n", - "coef_dummy_for_high_income_for_child_in_mixed_p... NaN 0 \n", - "coef_full_time_worker_mixed_party NaN 0 \n", - "coef_full_time_worker_mixed_party_not NaN 1 \n", - "coef_full_time_worker_specific_to_discretionary... NaN 0 \n", - "coef_full_time_worker_specific_to_discretionary... NaN 1 \n", - "coef_full_time_worker_specific_to_eating_out_jo... NaN 0 \n", - "coef_full_time_worker_specific_to_eating_out_jo... NaN 1 \n", - "coef_household_in_suburban_area_adult_adult_onl... NaN 1 \n", - "coef_household_in_suburban_area_adult_mixed_party NaN 0 \n", - "coef_household_in_suburban_area_child_child_onl... NaN 1 \n", - "coef_household_in_suburban_area_child_mixed_party NaN 1 \n", - "coef_household_in_urban_area_adult_adult_only_p... NaN 1 \n", - "coef_household_in_urban_area_adult_mixed_party NaN 0 \n", - "coef_household_in_urban_area_child_child_only_p... NaN 0 \n", - "coef_household_in_urban_area_child_mixed_party NaN 0 \n", - "coef_non_worker_adults_only_party NaN 0 \n", - "coef_non_worker_mixed_party NaN 0 \n", - "coef_non_worker_specific_to_discretionary_joint... NaN 0 \n", - "coef_non_worker_specific_to_eating_out_joint_tours NaN 0 \n", - "coef_part_time_worker_adults_only_party NaN 0 \n", - "coef_part_time_worker_adults_only_party_not NaN 1 \n", - "coef_part_time_worker_mixed_party NaN 0 \n", - "coef_part_time_worker_specific_to_discretionary... NaN 0 \n", - "coef_part_time_worker_specific_to_eating_out_jo... NaN 0 \n", - "coef_pre_driving_age_student_children_only_party NaN 0 \n", - "coef_pre_driving_age_student_mixed_party NaN 0 \n", - "coef_pre_driving_age_student_specific_to_discre... NaN 0 \n", - "coef_pre_driving_age_student_specific_to_eating... NaN 0 \n", - "coef_unavailable NaN 1 \n", - "coef_university_student_mixed_party NaN 0 \n", - "coef_university_student_specific_to_discretiona... NaN 1 \n", - "coef_university_student_specific_to_eating_out_... NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_adult_log_of_max_window_overlap_with_a_chi... 50.0 0.0 \n", + "coef_adult_log_of_max_window_overlap_with_an_ad... 50.0 0.0 \n", + "coef_adult_more_automobiles_than_workers_adult_... 50.0 0.0 \n", + "coef_adult_more_automobiles_than_workers_mixed_... 50.0 0.0 \n", + "coef_adult_number_of_joint_tours_adult_only 50.0 0.0 \n", + "coef_adult_number_of_joint_tours_mixed 50.0 0.0 \n", + "coef_adult_number_of_other_adults_in_the_househ... 0.0 0.0 \n", + "coef_adult_number_of_other_adults_in_the_househ... 0.0 0.0 \n", + "coef_child_log_of_max_window_overlap_with_a_chi... 50.0 0.0 \n", + "coef_child_log_of_max_window_overlap_with_an_ad... 50.0 0.0 \n", + "coef_child_more_automobiles_than_workers_child_... 50.0 0.0 \n", + "coef_child_more_automobiles_than_workers_mixed_... 50.0 0.0 \n", + "coef_child_number_of_joint_tours_child_only 50.0 0.0 \n", + "coef_child_number_of_joint_tours_mixed 50.0 0.0 \n", + "coef_child_number_of_other_children_in_the_hous... 0.0 0.0 \n", + "coef_child_number_of_other_children_in_the_hous... 0.0 0.0 \n", + "coef_child_too_young_for_school_children_only_p... 50.0 0.0 \n", + "coef_child_too_young_for_school_mixed_party 50.0 0.0 \n", + "coef_child_too_young_for_school_specific_to_dis... 50.0 0.0 \n", + "coef_child_too_young_for_school_specific_to_eat... 50.0 0.0 \n", + "coef_driving_age_student_children_only_party 50.0 0.0 \n", + "coef_driving_age_student_mixed_party 50.0 0.0 \n", + "coef_driving_age_student_specific_to_discretion... 50.0 0.0 \n", + "coef_driving_age_student_specific_to_eating_out... 50.0 0.0 \n", + "coef_dummy_for_high_income_for_adult_in_adult_p... 50.0 0.0 \n", + "coef_dummy_for_high_income_for_adult_in_mixed_p... 50.0 0.0 \n", + "coef_dummy_for_high_income_for_child_in_childre... 50.0 0.0 \n", + "coef_dummy_for_high_income_for_child_in_mixed_p... 50.0 0.0 \n", + "coef_full_time_worker_mixed_party 50.0 0.0 \n", + "coef_full_time_worker_mixed_party_not 0.5 0.0 \n", + "coef_full_time_worker_specific_to_discretionary... 50.0 0.0 \n", + "coef_full_time_worker_specific_to_discretionary... 0.5 0.0 \n", + "coef_full_time_worker_specific_to_eating_out_jo... 50.0 0.0 \n", + "coef_full_time_worker_specific_to_eating_out_jo... 0.5 0.0 \n", + "coef_household_in_suburban_area_adult_adult_onl... 0.0 0.0 \n", + "coef_household_in_suburban_area_adult_mixed_party 50.0 0.0 \n", + "coef_household_in_suburban_area_child_child_onl... 0.0 0.0 \n", + "coef_household_in_suburban_area_child_mixed_party 0.0 0.0 \n", + "coef_household_in_urban_area_adult_adult_only_p... 0.0 0.0 \n", + "coef_household_in_urban_area_adult_mixed_party 50.0 0.0 \n", + "coef_household_in_urban_area_child_child_only_p... 50.0 0.0 \n", + "coef_household_in_urban_area_child_mixed_party 50.0 0.0 \n", + "coef_non_worker_adults_only_party 50.0 0.0 \n", + "coef_non_worker_mixed_party 50.0 0.0 \n", + "coef_non_worker_specific_to_discretionary_joint... 50.0 0.0 \n", + "coef_non_worker_specific_to_eating_out_joint_tours 50.0 0.0 \n", + "coef_part_time_worker_adults_only_party 50.0 0.0 \n", + "coef_part_time_worker_adults_only_party_not 0.5 0.0 \n", + "coef_part_time_worker_mixed_party 50.0 0.0 \n", + "coef_part_time_worker_specific_to_discretionary... 50.0 0.0 \n", + "coef_part_time_worker_specific_to_eating_out_jo... 50.0 0.0 \n", + "coef_pre_driving_age_student_children_only_party 50.0 0.0 \n", + "coef_pre_driving_age_student_mixed_party 50.0 0.0 \n", + "coef_pre_driving_age_student_specific_to_discre... 50.0 0.0 \n", + "coef_pre_driving_age_student_specific_to_eating... 50.0 0.0 \n", + "coef_unavailable -999.0 0.0 \n", + "coef_university_student_mixed_party 50.0 0.0 \n", + "coef_university_student_specific_to_discretiona... 0.0 0.0 \n", + "coef_university_student_specific_to_eating_out_... 50.0 0.0 \n", "\n", - " best \n", - "coef_adult_log_of_max_window_overlap_with_a_chi... 4.595737 \n", - "coef_adult_log_of_max_window_overlap_with_an_ad... 1.692145 \n", - "coef_adult_more_automobiles_than_workers_adult_... 0.311671 \n", - "coef_adult_more_automobiles_than_workers_mixed_... -1.827740 \n", - "coef_adult_number_of_joint_tours_adult_only -2.134054 \n", - "coef_adult_number_of_joint_tours_mixed -28.572220 \n", - "coef_adult_number_of_other_adults_in_the_househ... 0.000000 \n", - "coef_adult_number_of_other_adults_in_the_househ... 0.000000 \n", - "coef_child_log_of_max_window_overlap_with_a_chi... 1.275585 \n", - "coef_child_log_of_max_window_overlap_with_an_ad... 1.539267 \n", - "coef_child_more_automobiles_than_workers_child_... -0.394683 \n", - "coef_child_more_automobiles_than_workers_mixed_... -1.551914 \n", - "coef_child_number_of_joint_tours_child_only 4.977604 \n", - "coef_child_number_of_joint_tours_mixed 17.894892 \n", - "coef_child_number_of_other_children_in_the_hous... 0.000000 \n", - "coef_child_number_of_other_children_in_the_hous... 0.000000 \n", - "coef_child_too_young_for_school_children_only_p... -2.785631 \n", - "coef_child_too_young_for_school_mixed_party 2.069934 \n", - "coef_child_too_young_for_school_specific_to_dis... 0.128371 \n", - "coef_child_too_young_for_school_specific_to_eat... 0.658655 \n", - "coef_driving_age_student_children_only_party -1.822000 \n", - "coef_driving_age_student_mixed_party -28.998969 \n", - "coef_driving_age_student_specific_to_discretion... -0.667500 \n", - "coef_driving_age_student_specific_to_eating_out... 2.344000 \n", - "coef_dummy_for_high_income_for_adult_in_adult_p... 0.131783 \n", - "coef_dummy_for_high_income_for_adult_in_mixed_p... -0.378918 \n", - "coef_dummy_for_high_income_for_child_in_childre... -0.561900 \n", - "coef_dummy_for_high_income_for_child_in_mixed_p... -0.513571 \n", - "coef_full_time_worker_mixed_party -957.202749 \n", - "coef_full_time_worker_mixed_party_not 0.500000 \n", - "coef_full_time_worker_specific_to_discretionary... 0.439200 \n", - "coef_full_time_worker_specific_to_discretionary... 0.500000 \n", - "coef_full_time_worker_specific_to_eating_out_jo... 0.715700 \n", - "coef_full_time_worker_specific_to_eating_out_jo... 0.500000 \n", - "coef_household_in_suburban_area_adult_adult_onl... 0.000000 \n", - "coef_household_in_suburban_area_adult_mixed_party -0.060070 \n", - "coef_household_in_suburban_area_child_child_onl... 0.000000 \n", - "coef_household_in_suburban_area_child_mixed_party 0.000000 \n", - "coef_household_in_urban_area_adult_adult_only_p... 0.000000 \n", - "coef_household_in_urban_area_adult_mixed_party 978.504490 \n", - "coef_household_in_urban_area_child_child_only_p... 6.082784 \n", - "coef_household_in_urban_area_child_mixed_party -19.290030 \n", - "coef_non_worker_adults_only_party -4.080384 \n", - "coef_non_worker_mixed_party -125.288137 \n", - "coef_non_worker_specific_to_discretionary_joint... -0.183500 \n", - "coef_non_worker_specific_to_eating_out_joint_tours 0.161700 \n", - "coef_part_time_worker_adults_only_party -3.248302 \n", - "coef_part_time_worker_adults_only_party_not 0.500000 \n", - "coef_part_time_worker_mixed_party 2254.660944 \n", - "coef_part_time_worker_specific_to_discretionary... 0.285000 \n", - "coef_part_time_worker_specific_to_eating_out_jo... 2.188000 \n", - "coef_pre_driving_age_student_children_only_party 4.151085 \n", - "coef_pre_driving_age_student_mixed_party 2.007228 \n", - "coef_pre_driving_age_student_specific_to_discre... 0.662600 \n", - "coef_pre_driving_age_student_specific_to_eating... 1.391000 \n", - "coef_unavailable -999.000000 \n", - "coef_university_student_mixed_party -958.612314 \n", - "coef_university_student_specific_to_discretiona... 0.000000 \n", - "coef_university_student_specific_to_eating_out_... -0.820000 " + " holdfast \n", + "param_name \n", + "coef_adult_log_of_max_window_overlap_with_a_chi... 0 \n", + "coef_adult_log_of_max_window_overlap_with_an_ad... 0 \n", + "coef_adult_more_automobiles_than_workers_adult_... 0 \n", + "coef_adult_more_automobiles_than_workers_mixed_... 0 \n", + "coef_adult_number_of_joint_tours_adult_only 0 \n", + "coef_adult_number_of_joint_tours_mixed 0 \n", + "coef_adult_number_of_other_adults_in_the_househ... 1 \n", + "coef_adult_number_of_other_adults_in_the_househ... 1 \n", + "coef_child_log_of_max_window_overlap_with_a_chi... 0 \n", + "coef_child_log_of_max_window_overlap_with_an_ad... 0 \n", + "coef_child_more_automobiles_than_workers_child_... 0 \n", + "coef_child_more_automobiles_than_workers_mixed_... 0 \n", + "coef_child_number_of_joint_tours_child_only 0 \n", + "coef_child_number_of_joint_tours_mixed 0 \n", + "coef_child_number_of_other_children_in_the_hous... 1 \n", + "coef_child_number_of_other_children_in_the_hous... 1 \n", + "coef_child_too_young_for_school_children_only_p... 0 \n", + "coef_child_too_young_for_school_mixed_party 0 \n", + "coef_child_too_young_for_school_specific_to_dis... 0 \n", + "coef_child_too_young_for_school_specific_to_eat... 0 \n", + "coef_driving_age_student_children_only_party 0 \n", + "coef_driving_age_student_mixed_party 0 \n", + "coef_driving_age_student_specific_to_discretion... 0 \n", + "coef_driving_age_student_specific_to_eating_out... 0 \n", + "coef_dummy_for_high_income_for_adult_in_adult_p... 0 \n", + "coef_dummy_for_high_income_for_adult_in_mixed_p... 0 \n", + "coef_dummy_for_high_income_for_child_in_childre... 0 \n", + "coef_dummy_for_high_income_for_child_in_mixed_p... 0 \n", + "coef_full_time_worker_mixed_party 0 \n", + "coef_full_time_worker_mixed_party_not 1 \n", + "coef_full_time_worker_specific_to_discretionary... 0 \n", + "coef_full_time_worker_specific_to_discretionary... 1 \n", + "coef_full_time_worker_specific_to_eating_out_jo... 0 \n", + "coef_full_time_worker_specific_to_eating_out_jo... 1 \n", + "coef_household_in_suburban_area_adult_adult_onl... 1 \n", + "coef_household_in_suburban_area_adult_mixed_party 0 \n", + "coef_household_in_suburban_area_child_child_onl... 1 \n", + "coef_household_in_suburban_area_child_mixed_party 1 \n", + "coef_household_in_urban_area_adult_adult_only_p... 1 \n", + "coef_household_in_urban_area_adult_mixed_party 0 \n", + "coef_household_in_urban_area_child_child_only_p... 0 \n", + "coef_household_in_urban_area_child_mixed_party 0 \n", + "coef_non_worker_adults_only_party 0 \n", + "coef_non_worker_mixed_party 0 \n", + "coef_non_worker_specific_to_discretionary_joint... 0 \n", + "coef_non_worker_specific_to_eating_out_joint_tours 0 \n", + "coef_part_time_worker_adults_only_party 0 \n", + "coef_part_time_worker_adults_only_party_not 1 \n", + "coef_part_time_worker_mixed_party 0 \n", + "coef_part_time_worker_specific_to_discretionary... 0 \n", + "coef_part_time_worker_specific_to_eating_out_jo... 0 \n", + "coef_pre_driving_age_student_children_only_party 0 \n", + "coef_pre_driving_age_student_mixed_party 0 \n", + "coef_pre_driving_age_student_specific_to_discre... 0 \n", + "coef_pre_driving_age_student_specific_to_eating... 0 \n", + "coef_unavailable 1 \n", + "coef_university_student_mixed_party 0 \n", + "coef_university_student_specific_to_discretiona... 1 \n", + "coef_university_student_specific_to_eating_out_... 0 " ] }, "metadata": {}, @@ -2240,16 +2250,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 0.0 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 0.0 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate()\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 0.0 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - ":1: RuntimeWarning: invalid value encountered in sqrt\n", - " model.estimate()\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { @@ -2265,242 +2267,242 @@ " \n", " \n", " coef_adult_log_of_max_window_overlap_with_a_child_mixed\n", - " 4.595737e+00\n", + " 2.125116\n", " \n", " \n", " coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party\n", - " 1.692145e+00\n", + " 1.280678\n", " \n", " \n", " coef_adult_more_automobiles_than_workers_adult_only_party\n", - " 3.116710e-01\n", + " 0.121220\n", " \n", " \n", " coef_adult_more_automobiles_than_workers_mixed_party\n", - " -1.827740e+00\n", + " -0.591966\n", " \n", " \n", " coef_adult_number_of_joint_tours_adult_only\n", - " -2.134054e+00\n", + " -0.794091\n", " \n", " \n", " coef_adult_number_of_joint_tours_mixed\n", - " -2.857222e+01\n", + " -1.417451\n", " \n", " \n", " coef_adult_number_of_other_adults_in_the_household_adults_only_party\n", - " -1.648956e-17\n", + " 0.000000\n", " \n", " \n", " coef_adult_number_of_other_adults_in_the_household_mixed_party\n", - " 7.224396e-18\n", + " 0.000000\n", " \n", " \n", " coef_child_log_of_max_window_overlap_with_a_child_child\n", - " 1.275585e+00\n", + " 1.296000\n", " \n", " \n", " coef_child_log_of_max_window_overlap_with_an_adult_mixed\n", - " 1.539267e+00\n", + " 1.538000\n", " \n", " \n", " coef_child_more_automobiles_than_workers_child_only_party\n", - " -3.946825e-01\n", + " -0.421400\n", " \n", " \n", " coef_child_more_automobiles_than_workers_mixed_party\n", - " -1.551914e+00\n", + " -0.366466\n", " \n", " \n", " coef_child_number_of_joint_tours_child_only\n", - " 4.977604e+00\n", + " 0.866122\n", " \n", " \n", " coef_child_number_of_joint_tours_mixed\n", - " 1.789489e+01\n", + " -0.261747\n", " \n", " \n", " coef_child_number_of_other_children_in_the_household_child_only_party\n", - " -2.228152e-18\n", + " 0.000000\n", " \n", " \n", " coef_child_number_of_other_children_in_the_household_mixed\n", - " -3.324715e-17\n", + " 0.000000\n", " \n", " \n", " coef_child_too_young_for_school_children_only_party\n", - " -2.785631e+00\n", + " -1.149596\n", " \n", " \n", " coef_child_too_young_for_school_mixed_party\n", - " 2.069934e+00\n", + " 0.197836\n", " \n", " \n", " coef_child_too_young_for_school_specific_to_discretionary_joint_tours\n", - " 1.283705e-01\n", + " 0.128400\n", " \n", " \n", " coef_child_too_young_for_school_specific_to_eating_out_joint_tours\n", - " 6.586549e-01\n", + " 0.658900\n", " \n", " \n", " coef_driving_age_student_children_only_party\n", - " -1.822000e+00\n", + " -2.120496\n", " \n", " \n", " coef_driving_age_student_mixed_party\n", - " -2.899897e+01\n", + " 0.322986\n", " \n", " \n", " coef_driving_age_student_specific_to_discretionary_joint_tours\n", - " -6.675000e-01\n", + " -0.667500\n", " \n", " \n", " coef_driving_age_student_specific_to_eating_out_joint_tours\n", - " 2.344000e+00\n", + " 2.344000\n", " \n", " \n", " coef_dummy_for_high_income_for_adult_in_adult_party\n", - " 1.317830e-01\n", + " -0.068202\n", " \n", " \n", " coef_dummy_for_high_income_for_adult_in_mixed_party\n", - " -3.789182e-01\n", + " 0.112930\n", " \n", " \n", " coef_dummy_for_high_income_for_child_in_children_party\n", - " -5.619000e-01\n", + " -0.211892\n", " \n", " \n", " coef_dummy_for_high_income_for_child_in_mixed_party\n", - " -5.135707e-01\n", + " -0.013740\n", " \n", " \n", " coef_full_time_worker_mixed_party\n", - " -9.572027e+02\n", + " -3.527365\n", " \n", " \n", " coef_full_time_worker_mixed_party_not\n", - " 5.000000e-01\n", + " 0.500000\n", " \n", " \n", " coef_full_time_worker_specific_to_discretionary_joint_tours\n", - " 4.392000e-01\n", + " 0.439200\n", " \n", " \n", " coef_full_time_worker_specific_to_discretionary_joint_tours_not\n", - " 5.000000e-01\n", + " 0.500000\n", " \n", " \n", " coef_full_time_worker_specific_to_eating_out_joint_tours\n", - " 7.157000e-01\n", + " 0.715700\n", " \n", " \n", " coef_full_time_worker_specific_to_eating_out_joint_tours_not\n", - " 5.000000e-01\n", + " 0.500000\n", " \n", " \n", " coef_household_in_suburban_area_adult_adult_only_party\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coef_household_in_suburban_area_adult_mixed_party\n", - " -6.007000e-02\n", + " 1.239881\n", " \n", " \n", " coef_household_in_suburban_area_child_child_only_party\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coef_household_in_suburban_area_child_mixed_party\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coef_household_in_urban_area_adult_adult_only_party\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coef_household_in_urban_area_adult_mixed_party\n", - " 9.785045e+02\n", + " 1.204039\n", " \n", " \n", " coef_household_in_urban_area_child_child_only_party\n", - " 6.082784e+00\n", + " -0.145369\n", " \n", " \n", " coef_household_in_urban_area_child_mixed_party\n", - " -1.929003e+01\n", + " -0.138857\n", " \n", " \n", " coef_non_worker_adults_only_party\n", - " -4.080384e+00\n", + " -3.161945\n", " \n", " \n", " coef_non_worker_mixed_party\n", - " -1.252881e+02\n", + " 1.059162\n", " \n", " \n", " coef_non_worker_specific_to_discretionary_joint_tours\n", - " -1.835000e-01\n", + " -0.183500\n", " \n", " \n", " coef_non_worker_specific_to_eating_out_joint_tours\n", - " 1.617000e-01\n", + " 0.161700\n", " \n", " \n", " coef_part_time_worker_adults_only_party\n", - " -3.248302e+00\n", + " -3.631928\n", " \n", " \n", " coef_part_time_worker_adults_only_party_not\n", - " 5.000000e-01\n", + " 0.500000\n", " \n", " \n", " coef_part_time_worker_mixed_party\n", - " 2.254661e+03\n", + " -0.447984\n", " \n", " \n", " coef_part_time_worker_specific_to_discretionary_joint_tours\n", - " 2.850000e-01\n", + " 0.285000\n", " \n", " \n", " coef_part_time_worker_specific_to_eating_out_joint_tours\n", - " 2.188000e+00\n", + " 2.188000\n", " \n", " \n", " coef_pre_driving_age_student_children_only_party\n", - " 4.151085e+00\n", + " 0.991812\n", " \n", " \n", " coef_pre_driving_age_student_mixed_party\n", - " 2.007228e+00\n", + " -0.073175\n", " \n", " \n", " coef_pre_driving_age_student_specific_to_discretionary_joint_tours\n", - " 6.626000e-01\n", + " 0.662600\n", " \n", " \n", " coef_pre_driving_age_student_specific_to_eating_out_joint_tours\n", - " 1.391000e+00\n", + " 1.391000\n", " \n", " \n", " coef_unavailable\n", - " -9.990000e+02\n", + " -999.000000\n", " \n", " \n", " coef_university_student_mixed_party\n", - " -9.586123e+02\n", + " -2.902637\n", " \n", " \n", " coef_university_student_specific_to_discretionary_joint_tours\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coef_university_student_specific_to_eating_out_joint_tours\n", - " -8.200000e-01\n", + " -0.820000\n", " \n", " \n", - "loglike-61.383086448632596d_loglike\n", + "
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coef_adult_log_of_max_window_overlap_with_a_child_mixed-4.096171e-040.000012
coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party2.436129e-050.000013
coef_adult_more_automobiles_than_workers_adult_only_party5.345149e-05-0.000165
coef_adult_more_automobiles_than_workers_mixed_party1.722466e-04-0.000051
coef_adult_number_of_joint_tours_adult_only1.769263e-04-0.000006
coef_adult_number_of_joint_tours_mixed3.181344e-04-0.000088
coef_adult_number_of_other_adults_in_the_household_adults_only_party0.000000e+000.000000
coef_adult_number_of_other_adults_in_the_household_mixed_party0.000000e+000.000000
coef_child_log_of_max_window_overlap_with_a_child_child0.000000e+000.000000
coef_child_log_of_max_window_overlap_with_an_adult_mixed0.000000e+000.000000
coef_child_more_automobiles_than_workers_child_only_party0.000000e+000.000000
coef_child_more_automobiles_than_workers_mixed_party1.722466e-04-0.000051
coef_child_number_of_joint_tours_child_only7.427872e-07-0.000119
coef_child_number_of_joint_tours_mixed-7.098060e-05-0.000047
coef_child_number_of_other_children_in_the_household_child_only_party0.000000e+000.000000
coef_child_number_of_other_children_in_the_household_mixed0.000000e+000.000000
coef_child_too_young_for_school_children_only_party0.000000e+000.000066
coef_child_too_young_for_school_mixed_party-4.267128e-050.000136
coef_child_too_young_for_school_specific_to_discretionary_joint_tours0.000000e+000.000000
coef_child_too_young_for_school_specific_to_eating_out_joint_tours0.000000e+000.000000
coef_driving_age_student_children_only_party0.000000e+000.000265
coef_driving_age_student_mixed_party-7.460379e-06-0.000060
coef_driving_age_student_specific_to_discretionary_joint_tours0.000000e+000.000000
coef_driving_age_student_specific_to_eating_out_joint_tours0.000000e+000.000000
coef_dummy_for_high_income_for_adult_in_adult_party-2.777090e-040.000017
coef_dummy_for_high_income_for_adult_in_mixed_party7.481814e-050.000026
coef_dummy_for_high_income_for_child_in_children_party0.000000e+000.000114
coef_dummy_for_high_income_for_child_in_mixed_party7.481814e-050.000026
coef_full_time_worker_mixed_party1.834492e-05-0.000152
coef_full_time_worker_mixed_party_not0.000000e+000.000000
coef_full_time_worker_specific_to_discretionary_joint_tours0.000000e+000.000000
coef_full_time_worker_specific_to_discretionary_joint_tours_not0.000000e+000.000000
coef_full_time_worker_specific_to_eating_out_joint_tours0.000000e+000.000000
coef_full_time_worker_specific_to_eating_out_joint_tours_not0.000000e+000.000000
coef_household_in_suburban_area_adult_adult_only_party0.000000e+000.000000
coef_household_in_suburban_area_adult_mixed_party0.000000e+000.000250
coef_household_in_suburban_area_child_child_only_party0.000000e+000.000000
coef_household_in_suburban_area_child_mixed_party0.000000e+000.000000
coef_household_in_urban_area_adult_adult_only_party0.000000e+000.000000
coef_household_in_urban_area_adult_mixed_party3.181344e-04-0.000179
coef_household_in_urban_area_child_child_only_party7.427872e-070.000131
coef_household_in_urban_area_child_mixed_party-6.353745e-05-0.000081
coef_non_worker_adults_only_party3.691375e-040.000062
coef_non_worker_mixed_party-1.839038e-700.000002
coef_non_worker_specific_to_discretionary_joint_tours0.000000e+000.000000
coef_non_worker_specific_to_eating_out_joint_tours0.000000e+000.000000
coef_part_time_worker_adults_only_party5.695694e-050.000239
coef_part_time_worker_adults_only_party_not0.000000e+000.000000
coef_part_time_worker_mixed_party0.000000e+00-0.000099
coef_part_time_worker_specific_to_discretionary_joint_tours0.000000e+000.000000
coef_part_time_worker_specific_to_eating_out_joint_tours0.000000e+000.000000
coef_pre_driving_age_student_children_only_party7.427872e-07-0.000108
coef_pre_driving_age_student_mixed_party-1.340579e-05-0.000009
coef_pre_driving_age_student_specific_to_discretionary_joint_tours0.000000e+000.000000
coef_pre_driving_age_student_specific_to_eating_out_joint_tours0.000000e+000.000000
coef_unavailable0.000000e+000.000000
coef_university_student_mixed_party2.997895e-040.000080
coef_university_student_specific_to_discretionary_joint_tours0.000000e+000.000000
coef_university_student_specific_to_eating_out_joint_tours0.000000e+000.000000
nit13nfev22njev13status0message'Optimization terminated successfully'successTrueelapsed_time0:00:00.868469method'bhhh|slsqp'n_cases304iteration_number112logloss0.2019180475283967" + "nit80nfev81njev80status0message'Optimization terminated successfully'successTrueelapsed_time0:00:00.325635method'slsqp'n_cases4500iteration_number80loglike-1240.495238444391" ], "text/plain": [ - "┣ x: coef_adult_log_of_max_window_overlap_with_a_child_mixed 4.595737e+00\n", - "┃ coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party 1.692145e+00\n", - "┃ coef_adult_more_automobiles_than_workers_adult_only_party 3.116710e-01\n", - "┃ coef_adult_more_automobiles_than_workers_mixed_party -1.827740e+00\n", - "┃ coef_adult_number_of_joint_tours_adult_only -2.134054e+00\n", - "┃ coef_adult_number_of_joint_tours_mixed -2.857222e+01\n", - "┃ coef_adult_number_of_other_adults_in_the_household_adults_only_party -1.648956e-17\n", - "┃ coef_adult_number_of_other_adults_in_the_household_mixed_party 7.224396e-18\n", - "┃ coef_child_log_of_max_window_overlap_with_a_child_child 1.275585e+00\n", - "┃ coef_child_log_of_max_window_overlap_with_an_adult_mixed 1.539267e+00\n", - "┃ coef_child_more_automobiles_than_workers_child_only_party -3.946825e-01\n", - "┃ coef_child_more_automobiles_than_workers_mixed_party -1.551914e+00\n", - "┃ coef_child_number_of_joint_tours_child_only 4.977604e+00\n", - "┃ coef_child_number_of_joint_tours_mixed 1.789489e+01\n", - "┃ coef_child_number_of_other_children_in_the_household_child_only_party -2.228152e-18\n", - "┃ coef_child_number_of_other_children_in_the_household_mixed -3.324715e-17\n", - "┃ coef_child_too_young_for_school_children_only_party -2.785631e+00\n", - "┃ coef_child_too_young_for_school_mixed_party 2.069934e+00\n", - "┃ coef_child_too_young_for_school_specific_to_discretionary_joint_tours 1.283705e-01\n", - "┃ coef_child_too_young_for_school_specific_to_eating_out_joint_tours 6.586549e-01\n", - "┃ coef_driving_age_student_children_only_party -1.822000e+00\n", - "┃ coef_driving_age_student_mixed_party -2.899897e+01\n", - "┃ coef_driving_age_student_specific_to_discretionary_joint_tours -6.675000e-01\n", - "┃ coef_driving_age_student_specific_to_eating_out_joint_tours 2.344000e+00\n", - "┃ coef_dummy_for_high_income_for_adult_in_adult_party 1.317830e-01\n", - "┃ coef_dummy_for_high_income_for_adult_in_mixed_party -3.789182e-01\n", - "┃ coef_dummy_for_high_income_for_child_in_children_party -5.619000e-01\n", - "┃ coef_dummy_for_high_income_for_child_in_mixed_party -5.135707e-01\n", - "┃ coef_full_time_worker_mixed_party -9.572027e+02\n", - "┃ coef_full_time_worker_mixed_party_not 5.000000e-01\n", - "┃ coef_full_time_worker_specific_to_discretionary_joint_tours 4.392000e-01\n", - "┃ coef_full_time_worker_specific_to_discretionary_joint_tours_not 5.000000e-01\n", - "┃ coef_full_time_worker_specific_to_eating_out_joint_tours 7.157000e-01\n", - "┃ coef_full_time_worker_specific_to_eating_out_joint_tours_not 5.000000e-01\n", - "┃ coef_household_in_suburban_area_adult_adult_only_party 0.000000e+00\n", - "┃ coef_household_in_suburban_area_adult_mixed_party -6.007000e-02\n", - "┃ coef_household_in_suburban_area_child_child_only_party 0.000000e+00\n", - "┃ coef_household_in_suburban_area_child_mixed_party 0.000000e+00\n", - "┃ coef_household_in_urban_area_adult_adult_only_party 0.000000e+00\n", - "┃ coef_household_in_urban_area_adult_mixed_party 9.785045e+02\n", - "┃ coef_household_in_urban_area_child_child_only_party 6.082784e+00\n", - "┃ coef_household_in_urban_area_child_mixed_party -1.929003e+01\n", - "┃ coef_non_worker_adults_only_party -4.080384e+00\n", - "┃ coef_non_worker_mixed_party -1.252881e+02\n", - "┃ coef_non_worker_specific_to_discretionary_joint_tours -1.835000e-01\n", - "┃ coef_non_worker_specific_to_eating_out_joint_tours 1.617000e-01\n", - "┃ coef_part_time_worker_adults_only_party -3.248302e+00\n", - "┃ coef_part_time_worker_adults_only_party_not 5.000000e-01\n", - "┃ coef_part_time_worker_mixed_party 2.254661e+03\n", - "┃ coef_part_time_worker_specific_to_discretionary_joint_tours 2.850000e-01\n", - "┃ coef_part_time_worker_specific_to_eating_out_joint_tours 2.188000e+00\n", - "┃ coef_pre_driving_age_student_children_only_party 4.151085e+00\n", - "┃ coef_pre_driving_age_student_mixed_party 2.007228e+00\n", - "┃ coef_pre_driving_age_student_specific_to_discretionary_joint_tours 6.626000e-01\n", - "┃ coef_pre_driving_age_student_specific_to_eating_out_joint_tours 1.391000e+00\n", - "┃ coef_unavailable -9.990000e+02\n", - "┃ coef_university_student_mixed_party -9.586123e+02\n", - "┃ coef_university_student_specific_to_discretionary_joint_tours 0.000000e+00\n", - "┃ coef_university_student_specific_to_eating_out_joint_tours -8.200000e-01\n", + "┣ x: coef_adult_log_of_max_window_overlap_with_a_child_mixed 2.125116\n", + "┃ coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party 1.280678\n", + "┃ coef_adult_more_automobiles_than_workers_adult_only_party 0.121220\n", + "┃ coef_adult_more_automobiles_than_workers_mixed_party -0.591966\n", + "┃ coef_adult_number_of_joint_tours_adult_only -0.794091\n", + "┃ coef_adult_number_of_joint_tours_mixed -1.417451\n", + "┃ coef_adult_number_of_other_adults_in_the_household_adults_only_party 0.000000\n", + "┃ coef_adult_number_of_other_adults_in_the_household_mixed_party 0.000000\n", + "┃ coef_child_log_of_max_window_overlap_with_a_child_child 1.296000\n", + "┃ coef_child_log_of_max_window_overlap_with_an_adult_mixed 1.538000\n", + "┃ coef_child_more_automobiles_than_workers_child_only_party -0.421400\n", + "┃ coef_child_more_automobiles_than_workers_mixed_party -0.366466\n", + "┃ coef_child_number_of_joint_tours_child_only 0.866122\n", + "┃ coef_child_number_of_joint_tours_mixed -0.261747\n", + "┃ coef_child_number_of_other_children_in_the_household_child_only_party 0.000000\n", + "┃ coef_child_number_of_other_children_in_the_household_mixed 0.000000\n", + "┃ coef_child_too_young_for_school_children_only_party -1.149596\n", + "┃ coef_child_too_young_for_school_mixed_party 0.197836\n", + "┃ coef_child_too_young_for_school_specific_to_discretionary_joint_tours 0.128400\n", + "┃ coef_child_too_young_for_school_specific_to_eating_out_joint_tours 0.658900\n", + "┃ coef_driving_age_student_children_only_party -2.120496\n", + "┃ coef_driving_age_student_mixed_party 0.322986\n", + "┃ coef_driving_age_student_specific_to_discretionary_joint_tours -0.667500\n", + "┃ coef_driving_age_student_specific_to_eating_out_joint_tours 2.344000\n", + "┃ coef_dummy_for_high_income_for_adult_in_adult_party -0.068202\n", + "┃ coef_dummy_for_high_income_for_adult_in_mixed_party 0.112930\n", + "┃ coef_dummy_for_high_income_for_child_in_children_party -0.211892\n", + "┃ coef_dummy_for_high_income_for_child_in_mixed_party -0.013740\n", + "┃ coef_full_time_worker_mixed_party -3.527365\n", + "┃ coef_full_time_worker_mixed_party_not 0.500000\n", + "┃ coef_full_time_worker_specific_to_discretionary_joint_tours 0.439200\n", + "┃ coef_full_time_worker_specific_to_discretionary_joint_tours_not 0.500000\n", + "┃ coef_full_time_worker_specific_to_eating_out_joint_tours 0.715700\n", + "┃ coef_full_time_worker_specific_to_eating_out_joint_tours_not 0.500000\n", + "┃ coef_household_in_suburban_area_adult_adult_only_party 0.000000\n", + "┃ coef_household_in_suburban_area_adult_mixed_party 1.239881\n", + "┃ coef_household_in_suburban_area_child_child_only_party 0.000000\n", + "┃ coef_household_in_suburban_area_child_mixed_party 0.000000\n", + "┃ coef_household_in_urban_area_adult_adult_only_party 0.000000\n", + "┃ coef_household_in_urban_area_adult_mixed_party 1.204039\n", + "┃ coef_household_in_urban_area_child_child_only_party -0.145369\n", + "┃ coef_household_in_urban_area_child_mixed_party -0.138857\n", + "┃ coef_non_worker_adults_only_party -3.161945\n", + "┃ coef_non_worker_mixed_party 1.059162\n", + "┃ coef_non_worker_specific_to_discretionary_joint_tours -0.183500\n", + "┃ coef_non_worker_specific_to_eating_out_joint_tours 0.161700\n", + "┃ coef_part_time_worker_adults_only_party -3.631928\n", + "┃ coef_part_time_worker_adults_only_party_not 0.500000\n", + "┃ coef_part_time_worker_mixed_party -0.447984\n", + "┃ coef_part_time_worker_specific_to_discretionary_joint_tours 0.285000\n", + "┃ coef_part_time_worker_specific_to_eating_out_joint_tours 2.188000\n", + "┃ coef_pre_driving_age_student_children_only_party 0.991812\n", + "┃ coef_pre_driving_age_student_mixed_party -0.073175\n", + "┃ coef_pre_driving_age_student_specific_to_discretionary_joint_tours 0.662600\n", + "┃ coef_pre_driving_age_student_specific_to_eating_out_joint_tours 1.391000\n", + "┃ coef_unavailable -999.000000\n", + "┃ coef_university_student_mixed_party -2.902637\n", + "┃ coef_university_student_specific_to_discretionary_joint_tours 0.000000\n", + "┃ coef_university_student_specific_to_eating_out_joint_tours -0.820000\n", "┃ dtype: float64\n", - "┣ loglike: -61.383086448632596\n", - "┣ d_loglike: coef_adult_log_of_max_window_overlap_with_a_child_mixed -4.096171e-04\n", - "┃ coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party 2.436129e-05\n", - "┃ coef_adult_more_automobiles_than_workers_adult_only_party 5.345149e-05\n", - "┃ coef_adult_more_automobiles_than_workers_mixed_party 1.722466e-04\n", - "┃ coef_adult_number_of_joint_tours_adult_only 1.769263e-04\n", - "┃ coef_adult_number_of_joint_tours_mixed 3.181344e-04\n", - "┃ coef_adult_number_of_other_adults_in_the_household_adults_only_party 0.000000e+00\n", - "┃ coef_adult_number_of_other_adults_in_the_household_mixed_party 0.000000e+00\n", - "┃ coef_child_log_of_max_window_overlap_with_a_child_child 0.000000e+00\n", - "┃ coef_child_log_of_max_window_overlap_with_an_adult_mixed 0.000000e+00\n", - "┃ coef_child_more_automobiles_than_workers_child_only_party 0.000000e+00\n", - "┃ coef_child_more_automobiles_than_workers_mixed_party 1.722466e-04\n", - "┃ coef_child_number_of_joint_tours_child_only 7.427872e-07\n", - "┃ coef_child_number_of_joint_tours_mixed -7.098060e-05\n", - "┃ coef_child_number_of_other_children_in_the_household_child_only_party 0.000000e+00\n", - "┃ coef_child_number_of_other_children_in_the_household_mixed 0.000000e+00\n", - "┃ coef_child_too_young_for_school_children_only_party 0.000000e+00\n", - "┃ coef_child_too_young_for_school_mixed_party -4.267128e-05\n", - "┃ coef_child_too_young_for_school_specific_to_discretionary_joint_tours 0.000000e+00\n", - "┃ coef_child_too_young_for_school_specific_to_eating_out_joint_tours 0.000000e+00\n", - "┃ coef_driving_age_student_children_only_party 0.000000e+00\n", - "┃ coef_driving_age_student_mixed_party -7.460379e-06\n", - "┃ coef_driving_age_student_specific_to_discretionary_joint_tours 0.000000e+00\n", - "┃ coef_driving_age_student_specific_to_eating_out_joint_tours 0.000000e+00\n", - "┃ coef_dummy_for_high_income_for_adult_in_adult_party -2.777090e-04\n", - "┃ coef_dummy_for_high_income_for_adult_in_mixed_party 7.481814e-05\n", - "┃ coef_dummy_for_high_income_for_child_in_children_party 0.000000e+00\n", - "┃ coef_dummy_for_high_income_for_child_in_mixed_party 7.481814e-05\n", - "┃ coef_full_time_worker_mixed_party 1.834492e-05\n", - "┃ coef_full_time_worker_mixed_party_not 0.000000e+00\n", - "┃ coef_full_time_worker_specific_to_discretionary_joint_tours 0.000000e+00\n", - "┃ coef_full_time_worker_specific_to_discretionary_joint_tours_not 0.000000e+00\n", - "┃ coef_full_time_worker_specific_to_eating_out_joint_tours 0.000000e+00\n", - "┃ coef_full_time_worker_specific_to_eating_out_joint_tours_not 0.000000e+00\n", - "┃ coef_household_in_suburban_area_adult_adult_only_party 0.000000e+00\n", - "┃ coef_household_in_suburban_area_adult_mixed_party 0.000000e+00\n", - "┃ coef_household_in_suburban_area_child_child_only_party 0.000000e+00\n", - "┃ coef_household_in_suburban_area_child_mixed_party 0.000000e+00\n", - "┃ coef_household_in_urban_area_adult_adult_only_party 0.000000e+00\n", - "┃ coef_household_in_urban_area_adult_mixed_party 3.181344e-04\n", - "┃ coef_household_in_urban_area_child_child_only_party 7.427872e-07\n", - "┃ coef_household_in_urban_area_child_mixed_party -6.353745e-05\n", - "┃ coef_non_worker_adults_only_party 3.691375e-04\n", - "┃ coef_non_worker_mixed_party -1.839038e-70\n", - "┃ coef_non_worker_specific_to_discretionary_joint_tours 0.000000e+00\n", - "┃ coef_non_worker_specific_to_eating_out_joint_tours 0.000000e+00\n", - "┃ coef_part_time_worker_adults_only_party 5.695694e-05\n", - "┃ coef_part_time_worker_adults_only_party_not 0.000000e+00\n", - "┃ coef_part_time_worker_mixed_party 0.000000e+00\n", - "┃ coef_part_time_worker_specific_to_discretionary_joint_tours 0.000000e+00\n", - "┃ coef_part_time_worker_specific_to_eating_out_joint_tours 0.000000e+00\n", - "┃ coef_pre_driving_age_student_children_only_party 7.427872e-07\n", - "┃ coef_pre_driving_age_student_mixed_party -1.340579e-05\n", - "┃ coef_pre_driving_age_student_specific_to_discretionary_joint_tours 0.000000e+00\n", - "┃ coef_pre_driving_age_student_specific_to_eating_out_joint_tours 0.000000e+00\n", - "┃ coef_unavailable 0.000000e+00\n", - "┃ coef_university_student_mixed_party 2.997895e-04\n", - "┃ coef_university_student_specific_to_discretionary_joint_tours 0.000000e+00\n", - "┃ coef_university_student_specific_to_eating_out_joint_tours 0.000000e+00\n", + "┣ logloss: 0.275665608543198\n", + "┣ d_logloss: coef_adult_log_of_max_window_overlap_with_a_child_mixed 0.000012\n", + "┃ coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party 0.000013\n", + "┃ coef_adult_more_automobiles_than_workers_adult_only_party -0.000165\n", + "┃ coef_adult_more_automobiles_than_workers_mixed_party -0.000051\n", + "┃ coef_adult_number_of_joint_tours_adult_only -0.000006\n", + "┃ coef_adult_number_of_joint_tours_mixed -0.000088\n", + "┃ coef_adult_number_of_other_adults_in_the_household_adults_only_party 0.000000\n", + "┃ coef_adult_number_of_other_adults_in_the_household_mixed_party 0.000000\n", + "┃ coef_child_log_of_max_window_overlap_with_a_child_child 0.000000\n", + "┃ coef_child_log_of_max_window_overlap_with_an_adult_mixed 0.000000\n", + "┃ coef_child_more_automobiles_than_workers_child_only_party 0.000000\n", + "┃ coef_child_more_automobiles_than_workers_mixed_party -0.000051\n", + "┃ coef_child_number_of_joint_tours_child_only -0.000119\n", + "┃ coef_child_number_of_joint_tours_mixed -0.000047\n", + "┃ coef_child_number_of_other_children_in_the_household_child_only_party 0.000000\n", + "┃ coef_child_number_of_other_children_in_the_household_mixed 0.000000\n", + "┃ coef_child_too_young_for_school_children_only_party 0.000066\n", + "┃ coef_child_too_young_for_school_mixed_party 0.000136\n", + "┃ coef_child_too_young_for_school_specific_to_discretionary_joint_tours 0.000000\n", + "┃ coef_child_too_young_for_school_specific_to_eating_out_joint_tours 0.000000\n", + "┃ coef_driving_age_student_children_only_party 0.000265\n", + "┃ coef_driving_age_student_mixed_party -0.000060\n", + "┃ coef_driving_age_student_specific_to_discretionary_joint_tours 0.000000\n", + "┃ coef_driving_age_student_specific_to_eating_out_joint_tours 0.000000\n", + "┃ coef_dummy_for_high_income_for_adult_in_adult_party 0.000017\n", + "┃ coef_dummy_for_high_income_for_adult_in_mixed_party 0.000026\n", + "┃ coef_dummy_for_high_income_for_child_in_children_party 0.000114\n", + "┃ coef_dummy_for_high_income_for_child_in_mixed_party 0.000026\n", + "┃ coef_full_time_worker_mixed_party -0.000152\n", + "┃ coef_full_time_worker_mixed_party_not 0.000000\n", + "┃ coef_full_time_worker_specific_to_discretionary_joint_tours 0.000000\n", + "┃ coef_full_time_worker_specific_to_discretionary_joint_tours_not 0.000000\n", + "┃ coef_full_time_worker_specific_to_eating_out_joint_tours 0.000000\n", + "┃ coef_full_time_worker_specific_to_eating_out_joint_tours_not 0.000000\n", + "┃ coef_household_in_suburban_area_adult_adult_only_party 0.000000\n", + "┃ coef_household_in_suburban_area_adult_mixed_party 0.000250\n", + "┃ coef_household_in_suburban_area_child_child_only_party 0.000000\n", + "┃ coef_household_in_suburban_area_child_mixed_party 0.000000\n", + "┃ coef_household_in_urban_area_adult_adult_only_party 0.000000\n", + "┃ coef_household_in_urban_area_adult_mixed_party -0.000179\n", + "┃ coef_household_in_urban_area_child_child_only_party 0.000131\n", + "┃ coef_household_in_urban_area_child_mixed_party -0.000081\n", + "┃ coef_non_worker_adults_only_party 0.000062\n", + "┃ coef_non_worker_mixed_party 0.000002\n", + "┃ coef_non_worker_specific_to_discretionary_joint_tours 0.000000\n", + "┃ coef_non_worker_specific_to_eating_out_joint_tours 0.000000\n", + "┃ coef_part_time_worker_adults_only_party 0.000239\n", + "┃ coef_part_time_worker_adults_only_party_not 0.000000\n", + "┃ coef_part_time_worker_mixed_party -0.000099\n", + "┃ coef_part_time_worker_specific_to_discretionary_joint_tours 0.000000\n", + "┃ coef_part_time_worker_specific_to_eating_out_joint_tours 0.000000\n", + "┃ coef_pre_driving_age_student_children_only_party -0.000108\n", + "┃ coef_pre_driving_age_student_mixed_party -0.000009\n", + "┃ coef_pre_driving_age_student_specific_to_discretionary_joint_tours 0.000000\n", + "┃ coef_pre_driving_age_student_specific_to_eating_out_joint_tours 0.000000\n", + "┃ coef_unavailable 0.000000\n", + "┃ coef_university_student_mixed_party 0.000080\n", + "┃ coef_university_student_specific_to_discretionary_joint_tours 0.000000\n", + "┃ coef_university_student_specific_to_eating_out_joint_tours 0.000000\n", "┃ dtype: float64\n", - "┣ nit: 13\n", - "┣ nfev: 22\n", - "┣ njev: 13\n", + "┣ nit: 80\n", + "┣ nfev: 81\n", + "┣ njev: 80\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(microseconds=868469)\n", - "┣ method: 'bhhh|slsqp'\n", - "┣ n_cases: 304\n", - "┣ iteration_number: 112\n", - "┣ logloss: 0.2019180475283967" + "┣ elapsed_time: datetime.timedelta(microseconds=325635)\n", + "┣ method: 'slsqp'\n", + "┣ n_cases: 4500\n", + "┣ iteration_number: 80\n", + "┣ loglike: -1240.495238444391" ] }, "execution_count": 7, @@ -2926,30 +2928,30 @@ " \n", " 1\n", " participate\n", - " 228.0\n", - " 304.0\n", + " 3317\n", + " 4500\n", " \n", " \n", " 2\n", " not_participate\n", - " 76.0\n", - " 304.0\n", + " 1183\n", + " 4500\n", " \n", " \n", " < Total All Alternatives >\n", " \n", - " 304.0\n", - " \n", + " 4500\n", + " <NA>\n", " \n", " \n", "\n", "" ], "text/plain": [ - " name chosen available\n", - "1 participate 228.0 304.0\n", - "2 not_participate 76.0 304.0\n", - "< Total All Alternatives > 304.0 " + " name chosen available\n", + "1 participate 3317 4500\n", + "2 not_participate 1183 4500\n", + "< Total All Alternatives > 4500 " ] }, "execution_count": 8, @@ -2958,7 +2960,7 @@ } ], "source": [ - "model.dataframes.choice_avail_summary()" + "model.choice_avail_summary()" ] }, { @@ -2976,610 +2978,577 @@ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
coef_adult_log_of_max_window_overlap_with_a_child_mixed 4.60 1.53 3.00** NA 0.00
coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party 1.69 0.833 2.03* NA 0.00
coef_adult_more_automobiles_than_workers_adult_only_party 0.312 1.08 0.29 NA 0.00
coef_adult_more_automobiles_than_workers_mixed_party-1.83 0.672-2.72** NA 0.00
coef_adult_number_of_joint_tours_adult_only-2.13 2.00-1.07 NA 0.00
coef_adult_number_of_joint_tours_mixed-28.6 NA NA[***] 499.96 0.00
coef_adult_number_of_other_adults_in_the_household_adults_only_party 0.00 NA NA NA 0.00fixed value
coef_adult_number_of_other_adults_in_the_household_mixed_party 0.00 NA NA NA 0.00fixed value
coef_child_log_of_max_window_overlap_with_a_child_child 1.28 0.00450 283.43*** NA 0.00
coef_child_log_of_max_window_overlap_with_an_adult_mixed 1.54 0.00635 242.24*** NA 0.00
coef_child_more_automobiles_than_workers_child_only_party-0.395 0.0443-8.91*** NA 0.00
coef_child_more_automobiles_than_workers_mixed_party-1.55 0.672-2.31* NA 0.00
coef_child_number_of_joint_tours_child_only 4.98 388. 0.01 NA 0.00
coef_child_number_of_joint_tours_mixed 17.9 3.48e+03 0.01 NA 0.00
coef_child_number_of_other_children_in_the_household_child_only_party 0.00 NA NA NA 0.00fixed value
coef_child_number_of_other_children_in_the_household_mixed 0.00 NA NA NA 0.00fixed value
coef_child_too_young_for_school_children_only_party-2.79 0.000873-BIG*** NA 0.00
coef_child_too_young_for_school_mixed_party 2.07 1.97e+04 0.00 NA 0.00
coef_child_too_young_for_school_specific_to_discretionary_joint_tours 0.128 0.000270 475.53*** NA 0.00
coef_child_too_young_for_school_specific_to_eating_out_joint_tours 0.659 3.84e-10 BIG*** NA 0.00
coef_driving_age_student_children_only_party-1.82 1.84e-10-BIG*** NA 0.00
coef_driving_age_student_mixed_party-29.0 2.06e+04-0.00 NA 0.00
coef_driving_age_student_specific_to_discretionary_joint_tours-0.667 5.70e-13-BIG*** NA 0.00
coef_driving_age_student_specific_to_eating_out_joint_tours 2.34 0.00 NA[] 0.00 0.00
coef_dummy_for_high_income_for_adult_in_adult_party 0.132 0.897 0.15 NA 0.00
coef_dummy_for_high_income_for_adult_in_mixed_party-0.379 0.321-1.18 NA 0.00
coef_dummy_for_high_income_for_child_in_children_party-0.562 0.00 NA[] 0.00 0.00
coef_dummy_for_high_income_for_child_in_mixed_party-0.514 0.321-1.60 NA 0.00
coef_full_time_worker_mixed_party-957. NA NA[***] NA 0.00
coef_full_time_worker_mixed_party_not 0.500 NA NA NA 0.00fixed value
coef_full_time_worker_specific_to_discretionary_joint_tours 0.439 0.00 NA[] 0.00 0.00
coef_full_time_worker_specific_to_discretionary_joint_tours_not 0.500 NA NA NA 0.00fixed value
coef_full_time_worker_specific_to_eating_out_joint_tours 0.716 0.00 NA[] 0.00 0.00
coef_full_time_worker_specific_to_eating_out_joint_tours_not 0.500 NA NA NA 0.00fixed value
coef_household_in_suburban_area_adult_adult_only_party 0.00 NA NA NA 0.00fixed value
coef_household_in_suburban_area_adult_mixed_party-0.0601 0.00 NA[] 0.00 0.00
coef_household_in_suburban_area_child_child_only_party 0.00 NA NA NA 0.00fixed value
coef_household_in_suburban_area_child_mixed_party 0.00 NA NA NA 0.00fixed value
coef_household_in_urban_area_adult_adult_only_party 0.00 NA NA NA 0.00fixed value
coef_household_in_urban_area_adult_mixed_party 979. 3.97e+03 0.25 NA 0.00
coef_household_in_urban_area_child_child_only_party 6.08 388. 0.02 NA 0.00
coef_household_in_urban_area_child_mixed_party-19.3 1.94e+04-0.00 NA 0.00
coef_non_worker_adults_only_party-4.08 1.45-2.81** NA 0.00
coef_non_worker_mixed_party-125. 0.00 NA[] 0.00 0.00
coef_non_worker_specific_to_discretionary_joint_tours-0.183 0.00 NA[] 0.00 0.00
coef_non_worker_specific_to_eating_out_joint_tours 0.162 0.00 NA[] 0.00 0.00
coef_part_time_worker_adults_only_party-3.25 1.03-3.14** NA 0.00
coef_part_time_worker_adults_only_party_not 0.500 NA NA NA 0.00fixed value
coef_part_time_worker_mixed_party 2.25e+03 0.00 NA[] 0.00 0.00
coef_part_time_worker_specific_to_discretionary_joint_tours 0.285 0.00 NA[] 0.00 0.00
coef_part_time_worker_specific_to_eating_out_joint_tours 2.19 0.00 NA[] 0.00 0.00
coef_pre_driving_age_student_children_only_party 4.15 388. 0.01 NA 0.00
coef_pre_driving_age_student_mixed_party 2.01 1.97e+04 0.00 NA 0.00
coef_pre_driving_age_student_specific_to_discretionary_joint_tours 0.663 0.00 NA[] 0.00 0.00
coef_pre_driving_age_student_specific_to_eating_out_joint_tours 1.39 0.00 NA[] 0.00 0.00
coef_unavailable-999. NA NA NA 0.00fixed value
coef_university_student_mixed_party-959. NA NA[***] NA 0.00
coef_university_student_specific_to_discretionary_joint_tours 0.00 NA NA NA 0.00fixed value
coef_university_student_specific_to_eating_out_joint_tours-0.820 0.00 NA[] 0.00 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_adult_log_of_max_window_overlap_with_a_child_mixed 2.13 0.234 9.09*** 0.00
coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party 1.28 0.229 5.59*** 0.00
coef_adult_more_automobiles_than_workers_adult_only_party 0.121 0.233 0.52 0.00
coef_adult_more_automobiles_than_workers_mixed_party-0.592 0.0889-6.66*** 0.00
coef_adult_number_of_joint_tours_adult_only-0.794 0.488-1.63 0.00
coef_adult_number_of_joint_tours_mixed-1.42 0.525-2.70** 0.00
coef_adult_number_of_other_adults_in_the_household_adults_only_party 0.00 0.00 NA 0.00fixed value
coef_adult_number_of_other_adults_in_the_household_mixed_party 0.00 0.00 NA 0.00fixed value
coef_child_log_of_max_window_overlap_with_a_child_child 1.30 NA NA 0.00
coef_child_log_of_max_window_overlap_with_an_adult_mixed 1.54 NA NA 0.00
coef_child_more_automobiles_than_workers_child_only_party-0.421 6.40e-14-BIG*** 0.00
coef_child_more_automobiles_than_workers_mixed_party-0.366 0.0889-4.12*** 0.00
coef_child_number_of_joint_tours_child_only 0.866 1.10 0.79 0.00
coef_child_number_of_joint_tours_mixed-0.262 0.497-0.53 0.00
coef_child_number_of_other_children_in_the_household_child_only_party 0.00 0.00 NA 0.00fixed value
coef_child_number_of_other_children_in_the_household_mixed 0.00 0.00 NA 0.00fixed value
coef_child_too_young_for_school_children_only_party-1.15 1.19-0.97 0.00
coef_child_too_young_for_school_mixed_party 0.198 0.525 0.38 0.00
coef_child_too_young_for_school_specific_to_discretionary_joint_tours 0.128 NA NA 0.00
coef_child_too_young_for_school_specific_to_eating_out_joint_tours 0.659 1.08e-14 BIG*** 0.00
coef_driving_age_student_children_only_party-2.12 1.40-1.51 0.00
coef_driving_age_student_mixed_party 0.323 0.613 0.53 0.00
coef_driving_age_student_specific_to_discretionary_joint_tours-0.668 4.92e-15-BIG*** 0.00
coef_driving_age_student_specific_to_eating_out_joint_tours 2.34 NA NA 0.00
coef_dummy_for_high_income_for_adult_in_adult_party-0.0682 0.231-0.29 0.00
coef_dummy_for_high_income_for_adult_in_mixed_party 0.113 0.0599 1.89 0.00
coef_dummy_for_high_income_for_child_in_children_party-0.212 0.453-0.47 0.00
coef_dummy_for_high_income_for_child_in_mixed_party-0.0137 0.0599-0.23 0.00
coef_full_time_worker_mixed_party-3.53 0.837-4.21*** 0.00
coef_full_time_worker_mixed_party_not 0.500 0.00 NA 0.00fixed value
coef_full_time_worker_specific_to_discretionary_joint_tours 0.439 7.59e-16 BIG*** 0.00
coef_full_time_worker_specific_to_discretionary_joint_tours_not 0.500 0.00 NA 0.00fixed value
coef_full_time_worker_specific_to_eating_out_joint_tours 0.716 1.68e-16 BIG*** 0.00
coef_full_time_worker_specific_to_eating_out_joint_tours_not 0.500 0.00 NA 0.00fixed value
coef_household_in_suburban_area_adult_adult_only_party 0.00 0.00 NA 0.00fixed value
coef_household_in_suburban_area_adult_mixed_party 1.24 1.10 1.13 0.00
coef_household_in_suburban_area_child_child_only_party 0.00 0.00 NA 0.00fixed value
coef_household_in_suburban_area_child_mixed_party 0.00 0.00 NA 0.00fixed value
coef_household_in_urban_area_adult_adult_only_party 0.00 0.00 NA 0.00fixed value
coef_household_in_urban_area_adult_mixed_party 1.20 1.11 1.09 0.00
coef_household_in_urban_area_child_child_only_party-0.145 0.520-0.28 0.00
coef_household_in_urban_area_child_mixed_party-0.139 0.189-0.74 0.00
coef_non_worker_adults_only_party-3.16 0.310-10.20*** 0.00
coef_non_worker_mixed_party 1.06 1.05 1.01 0.00
coef_non_worker_specific_to_discretionary_joint_tours-0.184 0.00 NA 0.00
coef_non_worker_specific_to_eating_out_joint_tours 0.162 0.00 NA 0.00
coef_part_time_worker_adults_only_party-3.63 0.389-9.33*** 0.00
coef_part_time_worker_adults_only_party_not 0.500 0.00 NA 0.00fixed value
coef_part_time_worker_mixed_party-0.448 0.942-0.48 0.00
coef_part_time_worker_specific_to_discretionary_joint_tours 0.285 0.00 NA 0.00
coef_part_time_worker_specific_to_eating_out_joint_tours 2.19 0.00 NA 0.00
coef_pre_driving_age_student_children_only_party 0.992 1.18 0.84 0.00
coef_pre_driving_age_student_mixed_party-0.0732 0.527-0.14 0.00
coef_pre_driving_age_student_specific_to_discretionary_joint_tours 0.663 0.00 NA 0.00
coef_pre_driving_age_student_specific_to_eating_out_joint_tours 1.39 0.00 NA 0.00
coef_unavailable-999. 0.00 NA 0.00fixed value
coef_university_student_mixed_party-2.90 0.860-3.38*** 0.00
coef_university_student_specific_to_discretionary_joint_tours 0.00 0.00 NA 0.00fixed value
coef_university_student_specific_to_eating_out_joint_tours-0.820 0.00 NA 0.00
\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 9, @@ -3626,18 +3595,7 @@ "cell_type": "code", "execution_count": 11, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -3695,7 +3653,7 @@ " \n", " 1\n", " coef_full_time_worker_mixed_party\n", - " -957.202749\n", + " -3.527365\n", " F\n", " \n", " \n", @@ -3707,7 +3665,7 @@ " \n", " 3\n", " coef_part_time_worker_adults_only_party\n", - " -3.248302\n", + " -3.631928\n", " F\n", " \n", " \n", @@ -3719,61 +3677,61 @@ " \n", " 5\n", " coef_part_time_worker_mixed_party\n", - " 2254.660944\n", + " -0.447984\n", " F\n", " \n", " \n", " 6\n", " coef_university_student_mixed_party\n", - " -958.612314\n", + " -2.902637\n", " F\n", " \n", " \n", " 7\n", " coef_non_worker_adults_only_party\n", - " -4.080384\n", + " -3.161945\n", " F\n", " \n", " \n", " 8\n", " coef_non_worker_mixed_party\n", - " -125.288137\n", + " 1.059162\n", " F\n", " \n", " \n", " 9\n", " coef_child_too_young_for_school_children_only_...\n", - " -2.785631\n", + " -1.149596\n", " F\n", " \n", " \n", " 10\n", " coef_child_too_young_for_school_mixed_party\n", - " 2.069934\n", + " 0.197836\n", " F\n", " \n", " \n", " 11\n", " coef_pre_driving_age_student_children_only_party\n", - " 4.151085\n", + " 0.991812\n", " F\n", " \n", " \n", " 12\n", " coef_pre_driving_age_student_mixed_party\n", - " 2.007228\n", + " -0.073175\n", " F\n", " \n", " \n", " 13\n", " coef_driving_age_student_children_only_party\n", - " -1.822000\n", + " -2.120496\n", " F\n", " \n", " \n", " 14\n", " coef_driving_age_student_mixed_party\n", - " -28.998969\n", + " 0.322986\n", " F\n", " \n", " \n", @@ -3839,13 +3797,13 @@ " \n", " 25\n", " coef_child_too_young_for_school_specific_to_ea...\n", - " 0.658655\n", + " 0.658900\n", " F\n", " \n", " \n", " 26\n", " coef_child_too_young_for_school_specific_to_di...\n", - " 0.128371\n", + " 0.128400\n", " F\n", " \n", " \n", @@ -3881,19 +3839,19 @@ " \n", " 32\n", " coef_household_in_urban_area_adult_mixed_party\n", - " 978.504490\n", + " 1.204039\n", " F\n", " \n", " \n", " 33\n", " coef_household_in_urban_area_child_child_only_...\n", - " 6.082784\n", + " -0.145369\n", " F\n", " \n", " \n", " 34\n", " coef_household_in_urban_area_child_mixed_party\n", - " -19.290030\n", + " -0.138857\n", " F\n", " \n", " \n", @@ -3905,7 +3863,7 @@ " \n", " 36\n", " coef_household_in_suburban_area_adult_mixed_party\n", - " -0.060070\n", + " 1.239881\n", " F\n", " \n", " \n", @@ -3923,73 +3881,73 @@ " \n", " 39\n", " coef_adult_more_automobiles_than_workers_adult...\n", - " 0.311671\n", + " 0.121220\n", " F\n", " \n", " \n", " 40\n", " coef_adult_more_automobiles_than_workers_mixed...\n", - " -1.827740\n", + " -0.591966\n", " F\n", " \n", " \n", " 41\n", " coef_child_more_automobiles_than_workers_child...\n", - " -0.394683\n", + " -0.421400\n", " F\n", " \n", " \n", " 42\n", " coef_child_more_automobiles_than_workers_mixed...\n", - " -1.551914\n", + " -0.366466\n", " F\n", " \n", " \n", " 43\n", " coef_dummy_for_high_income_for_adult_in_adult_...\n", - " 0.131783\n", + " -0.068202\n", " F\n", " \n", " \n", " 44\n", " coef_dummy_for_high_income_for_adult_in_mixed_...\n", - " -0.378918\n", + " 0.112930\n", " F\n", " \n", " \n", " 45\n", " coef_dummy_for_high_income_for_child_in_childr...\n", - " -0.561900\n", + " -0.211892\n", " F\n", " \n", " \n", " 46\n", " coef_dummy_for_high_income_for_child_in_mixed_...\n", - " -0.513571\n", + " -0.013740\n", " F\n", " \n", " \n", " 47\n", " coef_adult_number_of_joint_tours_adult_only\n", - " -2.134054\n", + " -0.794091\n", " F\n", " \n", " \n", " 48\n", " coef_adult_number_of_joint_tours_mixed\n", - " -28.572220\n", + " -1.417451\n", " F\n", " \n", " \n", " 49\n", " coef_child_number_of_joint_tours_child_only\n", - " 4.977604\n", + " 0.866122\n", " F\n", " \n", " \n", " 50\n", " coef_child_number_of_joint_tours_mixed\n", - " 17.894892\n", + " -0.261747\n", " F\n", " \n", " \n", @@ -4019,25 +3977,25 @@ " \n", " 55\n", " coef_adult_log_of_max_window_overlap_with_an_a...\n", - " 1.692145\n", + " 1.280678\n", " F\n", " \n", " \n", " 56\n", " coef_adult_log_of_max_window_overlap_with_a_ch...\n", - " 4.595737\n", + " 2.125116\n", " F\n", " \n", " \n", " 57\n", " coef_child_log_of_max_window_overlap_with_an_a...\n", - " 1.539267\n", + " 1.538000\n", " F\n", " \n", " \n", " 58\n", " coef_child_log_of_max_window_overlap_with_a_ch...\n", - " 1.275585\n", + " 1.296000\n", " F\n", " \n", " \n", @@ -4045,66 +4003,66 @@ "" ], "text/plain": [ - " coefficient_name value constrain\n", - "0 coef_unavailable -999.000000 T\n", - "1 coef_full_time_worker_mixed_party -957.202749 F\n", - "2 coef_full_time_worker_mixed_party_not 0.500000 T\n", - "3 coef_part_time_worker_adults_only_party -3.248302 F\n", - "4 coef_part_time_worker_adults_only_party_not 0.500000 T\n", - "5 coef_part_time_worker_mixed_party 2254.660944 F\n", - "6 coef_university_student_mixed_party -958.612314 F\n", - "7 coef_non_worker_adults_only_party -4.080384 F\n", - "8 coef_non_worker_mixed_party -125.288137 F\n", - "9 coef_child_too_young_for_school_children_only_... -2.785631 F\n", - "10 coef_child_too_young_for_school_mixed_party 2.069934 F\n", - "11 coef_pre_driving_age_student_children_only_party 4.151085 F\n", - "12 coef_pre_driving_age_student_mixed_party 2.007228 F\n", - "13 coef_driving_age_student_children_only_party -1.822000 F\n", - "14 coef_driving_age_student_mixed_party -28.998969 F\n", - "15 coef_full_time_worker_specific_to_eating_out_j... 0.715700 F\n", - "16 coef_full_time_worker_specific_to_eating_out_j... 0.500000 T\n", - "17 coef_full_time_worker_specific_to_discretionar... 0.439200 F\n", - "18 coef_full_time_worker_specific_to_discretionar... 0.500000 T\n", - "19 coef_part_time_worker_specific_to_eating_out_j... 2.188000 F\n", - "20 coef_part_time_worker_specific_to_discretionar... 0.285000 F\n", - "21 coef_university_student_specific_to_eating_out... -0.820000 F\n", - "22 coef_university_student_specific_to_discretion... 0.000000 T\n", - "23 coef_non_worker_specific_to_eating_out_joint_t... 0.161700 F\n", - "24 coef_non_worker_specific_to_discretionary_join... -0.183500 F\n", - "25 coef_child_too_young_for_school_specific_to_ea... 0.658655 F\n", - "26 coef_child_too_young_for_school_specific_to_di... 0.128371 F\n", - "27 coef_pre_driving_age_student_specific_to_eatin... 1.391000 F\n", - "28 coef_pre_driving_age_student_specific_to_discr... 0.662600 F\n", - "29 coef_driving_age_student_specific_to_eating_ou... 2.344000 F\n", - "30 coef_driving_age_student_specific_to_discretio... -0.667500 F\n", - "31 coef_household_in_urban_area_adult_adult_only_... 0.000000 T\n", - "32 coef_household_in_urban_area_adult_mixed_party 978.504490 F\n", - "33 coef_household_in_urban_area_child_child_only_... 6.082784 F\n", - "34 coef_household_in_urban_area_child_mixed_party -19.290030 F\n", - "35 coef_household_in_suburban_area_adult_adult_on... 0.000000 T\n", - "36 coef_household_in_suburban_area_adult_mixed_party -0.060070 F\n", - "37 coef_household_in_suburban_area_child_child_on... 0.000000 T\n", - "38 coef_household_in_suburban_area_child_mixed_party 0.000000 T\n", - "39 coef_adult_more_automobiles_than_workers_adult... 0.311671 F\n", - "40 coef_adult_more_automobiles_than_workers_mixed... -1.827740 F\n", - "41 coef_child_more_automobiles_than_workers_child... -0.394683 F\n", - "42 coef_child_more_automobiles_than_workers_mixed... -1.551914 F\n", - "43 coef_dummy_for_high_income_for_adult_in_adult_... 0.131783 F\n", - "44 coef_dummy_for_high_income_for_adult_in_mixed_... -0.378918 F\n", - "45 coef_dummy_for_high_income_for_child_in_childr... -0.561900 F\n", - "46 coef_dummy_for_high_income_for_child_in_mixed_... -0.513571 F\n", - "47 coef_adult_number_of_joint_tours_adult_only -2.134054 F\n", - "48 coef_adult_number_of_joint_tours_mixed -28.572220 F\n", - "49 coef_child_number_of_joint_tours_child_only 4.977604 F\n", - "50 coef_child_number_of_joint_tours_mixed 17.894892 F\n", - "51 coef_adult_number_of_other_adults_in_the_house... 0.000000 T\n", - "52 coef_adult_number_of_other_adults_in_the_house... 0.000000 T\n", - "53 coef_child_number_of_other_children_in_the_hou... 0.000000 T\n", - "54 coef_child_number_of_other_children_in_the_hou... 0.000000 T\n", - "55 coef_adult_log_of_max_window_overlap_with_an_a... 1.692145 F\n", - "56 coef_adult_log_of_max_window_overlap_with_a_ch... 4.595737 F\n", - "57 coef_child_log_of_max_window_overlap_with_an_a... 1.539267 F\n", - "58 coef_child_log_of_max_window_overlap_with_a_ch... 1.275585 F" + " coefficient_name value constrain\n", + "0 coef_unavailable -999.000000 T\n", + "1 coef_full_time_worker_mixed_party -3.527365 F\n", + "2 coef_full_time_worker_mixed_party_not 0.500000 T\n", + "3 coef_part_time_worker_adults_only_party -3.631928 F\n", + "4 coef_part_time_worker_adults_only_party_not 0.500000 T\n", + "5 coef_part_time_worker_mixed_party -0.447984 F\n", + "6 coef_university_student_mixed_party -2.902637 F\n", + "7 coef_non_worker_adults_only_party -3.161945 F\n", + "8 coef_non_worker_mixed_party 1.059162 F\n", + "9 coef_child_too_young_for_school_children_only_... -1.149596 F\n", + "10 coef_child_too_young_for_school_mixed_party 0.197836 F\n", + "11 coef_pre_driving_age_student_children_only_party 0.991812 F\n", + "12 coef_pre_driving_age_student_mixed_party -0.073175 F\n", + "13 coef_driving_age_student_children_only_party -2.120496 F\n", + "14 coef_driving_age_student_mixed_party 0.322986 F\n", + "15 coef_full_time_worker_specific_to_eating_out_j... 0.715700 F\n", + "16 coef_full_time_worker_specific_to_eating_out_j... 0.500000 T\n", + "17 coef_full_time_worker_specific_to_discretionar... 0.439200 F\n", + "18 coef_full_time_worker_specific_to_discretionar... 0.500000 T\n", + "19 coef_part_time_worker_specific_to_eating_out_j... 2.188000 F\n", + "20 coef_part_time_worker_specific_to_discretionar... 0.285000 F\n", + "21 coef_university_student_specific_to_eating_out... -0.820000 F\n", + "22 coef_university_student_specific_to_discretion... 0.000000 T\n", + "23 coef_non_worker_specific_to_eating_out_joint_t... 0.161700 F\n", + "24 coef_non_worker_specific_to_discretionary_join... -0.183500 F\n", + "25 coef_child_too_young_for_school_specific_to_ea... 0.658900 F\n", + "26 coef_child_too_young_for_school_specific_to_di... 0.128400 F\n", + "27 coef_pre_driving_age_student_specific_to_eatin... 1.391000 F\n", + "28 coef_pre_driving_age_student_specific_to_discr... 0.662600 F\n", + "29 coef_driving_age_student_specific_to_eating_ou... 2.344000 F\n", + "30 coef_driving_age_student_specific_to_discretio... -0.667500 F\n", + "31 coef_household_in_urban_area_adult_adult_only_... 0.000000 T\n", + "32 coef_household_in_urban_area_adult_mixed_party 1.204039 F\n", + "33 coef_household_in_urban_area_child_child_only_... -0.145369 F\n", + "34 coef_household_in_urban_area_child_mixed_party -0.138857 F\n", + "35 coef_household_in_suburban_area_adult_adult_on... 0.000000 T\n", + "36 coef_household_in_suburban_area_adult_mixed_party 1.239881 F\n", + "37 coef_household_in_suburban_area_child_child_on... 0.000000 T\n", + "38 coef_household_in_suburban_area_child_mixed_party 0.000000 T\n", + "39 coef_adult_more_automobiles_than_workers_adult... 0.121220 F\n", + "40 coef_adult_more_automobiles_than_workers_mixed... -0.591966 F\n", + "41 coef_child_more_automobiles_than_workers_child... -0.421400 F\n", + "42 coef_child_more_automobiles_than_workers_mixed... -0.366466 F\n", + "43 coef_dummy_for_high_income_for_adult_in_adult_... -0.068202 F\n", + "44 coef_dummy_for_high_income_for_adult_in_mixed_... 0.112930 F\n", + "45 coef_dummy_for_high_income_for_child_in_childr... -0.211892 F\n", + "46 coef_dummy_for_high_income_for_child_in_mixed_... -0.013740 F\n", + "47 coef_adult_number_of_joint_tours_adult_only -0.794091 F\n", + "48 coef_adult_number_of_joint_tours_mixed -1.417451 F\n", + "49 coef_child_number_of_joint_tours_child_only 0.866122 F\n", + "50 coef_child_number_of_joint_tours_mixed -0.261747 F\n", + "51 coef_adult_number_of_other_adults_in_the_house... 0.000000 T\n", + "52 coef_adult_number_of_other_adults_in_the_house... 0.000000 T\n", + "53 coef_child_number_of_other_children_in_the_hou... 0.000000 T\n", + "54 coef_child_number_of_other_children_in_the_hou... 0.000000 T\n", + "55 coef_adult_log_of_max_window_overlap_with_an_a... 1.280678 F\n", + "56 coef_adult_log_of_max_window_overlap_with_a_ch... 2.125116 F\n", + "57 coef_child_log_of_max_window_overlap_with_an_a... 1.538000 F\n", + "58 coef_child_log_of_max_window_overlap_with_a_ch... 1.296000 F" ] }, "execution_count": 12, @@ -4124,7 +4082,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -4138,7 +4096,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/13_joint_nonmand_tour_dest.ipynb b/activitysim/examples/example_estimation/notebooks/13_joint_nonmand_tour_dest.ipynb index 82fc07c165..20b9d7cac1 100644 --- a/activitysim/examples/example_estimation/notebooks/13_joint_nonmand_tour_dest.ipynb +++ b/activitysim/examples/example_estimation/notebooks/13_joint_nonmand_tour_dest.ipynb @@ -28,30 +28,74 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import larch # !conda install larch #for estimation\n", + "import larch as lx\n", "import pandas as pd\n", - "import numpy as np\n", - "import yaml \n", - "import larch.util.excel\n", - "import os" + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -65,19 +109,36 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], - "source": [ - "modelnames = (\"non_mandatory_tour_destination\", \"joint_tour_destination\")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_destination/non_mandatory_tour_destination_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_destination/non_mandatory_tour_destination_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_destination/non_mandatory_tour_destination_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_destination/non_mandatory_tour_destination_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_destination/non_mandatory_tour_destination_landuse.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_destination/non_mandatory_tour_destination_size_terms.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_destination/non_mandatory_tour_destination_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_destination/joint_tour_destination_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_destination/joint_tour_destination_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_destination/joint_tour_destination_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_destination/joint_tour_destination_landuse.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_destination/joint_tour_destination_size_terms.csv\n" + ] + } + ], "source": [ + "modelnames = (\"non_mandatory_tour_destination\", \"joint_tour_destination\")\n", + "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelnames, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelnames,\n", + " edb_directory=\"output-est-mode/estimation_data_bundle/{name}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -89,26 +150,6 @@ "all models in the group." ] }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "larch.model.model_group.ModelGroup" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "type(model)" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -127,7 +168,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -272,7 +313,7 @@ "coef_othdiscr_dist_5_plus -0.1193 F" ] }, - "execution_count": 6, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -290,7 +331,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -315,148 +356,88 @@ " \n", " \n", " tour_id\n", - " variable\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", - " 8\n", - " ...\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", - " 190\n", + " alt_dest\n", + " variable_label0000\n", + " variable_label0001\n", + " variable_label0002\n", + " variable_label0003\n", + " variable_label0004\n", + " variable_label0005\n", + " variable_label0006\n", + " variable_label0007\n", + " variable_label0008\n", " \n", " \n", " \n", " \n", " 0\n", - " 6812\n", - " variable_label0001\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " ...\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", + " 1870\n", + " 8\n", " 1.0\n", + " 1.00\n", + " 2.06\n", + " 0.0\n", + " 0.0\n", + " 7.492867\n", + " False\n", + " -0.349936\n", + " 4.970833\n", " \n", " \n", " 1\n", - " 6812\n", - " variable_label0004\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ...\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 1870\n", + " 16\n", + " 1.0\n", + " 1.00\n", + " 2.74\n", " 0.0\n", " 0.0\n", + " 8.289751\n", + " False\n", + " -0.487843\n", + " 4.510890\n", " \n", " \n", " 2\n", - " 6812\n", - " variable_label0002\n", - " 1.3199999332427979\n", - " 1.0299999713897705\n", - " 0.8499999046325684\n", - " 1.190000057220459\n", - " 1.0299999713897705\n", - " 0.7799999713897705\n", - " 0.8399999141693115\n", - " 0.9900000095367432\n", - " ...\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", - " 2.7800002098083496\n", - " 2.25\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", + " 1870\n", + " 17\n", + " 1.0\n", + " 1.00\n", + " 3.00\n", + " 0.1\n", + " 0.0\n", + " 7.651656\n", + " False\n", + " -0.537413\n", + " 5.289744\n", " \n", " \n", " 3\n", - " 6812\n", - " variable_label0003\n", - " 0.0\n", - " 0.0\n", - 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22410 rows × 192 columns

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"814 5.563462376541104 7.432773706720803 3.829901471825824 \n", - "815 False False False \n", - "816 5.61268490695845 3.809978548664433 7.98807577917251 \n", - "817 1.0 1.0 1.0 \n", - "818 -0.2398310223012045 -0.27770426926470554 -0.45370314739749773 \n", - "\n", - " 190 \n", - "0 1.0 \n", - "1 0.0 \n", - "2 1.9100000858306885 \n", - "3 0.0 \n", - "4 5.304200029706192 \n", - ".. ... \n", - "814 5.955267258796094 \n", - "815 False \n", - "816 5.735554926665741 \n", - "817 1.0 \n", - "818 -0.42464839165931 \n", - "\n", - "[819 rows x 192 columns]" + "[32631 rows x 11 columns]" ] }, - "execution_count": 8, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -1143,7 +866,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -1178,48 +901,48 @@ " \n", " \n", " 0\n", - " 6812\n", - " 72\n", - " 72.0\n", - " 166\n", - " eatout\n", - " 71\n", + " 1870\n", + " 70\n", + " 26\n", + " 45\n", + " othdiscr\n", + " 52\n", " \n", " \n", " 1\n", - " 8110\n", - " 62\n", - " 47.0\n", - " 197\n", - " shopping\n", - " 80\n", + " 20468\n", + " 138\n", + " 161\n", + " 499\n", + " escort\n", + " 124\n", " \n", " \n", " 2\n", - " 11013\n", - " 33\n", - " 32.0\n", - " 268\n", - " othdiscr\n", - " 91\n", + " 27055\n", + " 133\n", + " 185\n", + " 659\n", + " social\n", + " 132\n", " \n", " \n", " 3\n", - " 11016\n", - " 71\n", - " 71.0\n", - " 268\n", - " othmaint\n", - " 91\n", + " 38877\n", + " 115\n", + " 147\n", + " 948\n", + " escort\n", + " 148\n", " \n", " \n", " 4\n", - " 15403\n", - " 67\n", - " 67.0\n", - " 375\n", - " othmaint\n", - " 105\n", + " 38904\n", + " 107\n", + " 104\n", + " 948\n", + " social\n", + " 148\n", " \n", " \n", " ...\n", @@ -1231,86 +954,86 @@ " ...\n", " \n", " \n", - " 2485\n", - " 309760814\n", - " 154\n", - " 154.0\n", - " 7555141\n", + " 29664\n", + " 310197956\n", + " 1374\n", + " 1384\n", + " 7565803\n", " shopping\n", - " 85\n", + " 1386\n", " \n", " \n", - " 2486\n", - " 309760815\n", - " 41\n", - " 41.0\n", - " 7555141\n", - " shopping\n", - " 85\n", + " 29665\n", + " 310202376\n", + " 1402\n", + " 1402\n", + " 7565911\n", + " othdiscr\n", + " 1402\n", " \n", " \n", - " 2487\n", - " 309790009\n", - " 36\n", - " 36.0\n", - " 7555853\n", - " social\n", - " 115\n", + " 29666\n", + " 310202384\n", + " 1402\n", + " 1402\n", + " 7565911\n", + " shopping\n", + " 1402\n", " \n", " \n", - " 2488\n", - " 309796968\n", - " 94\n", - " 94.0\n", - " 7556023\n", - " othdiscr\n", - " 136\n", + " 29667\n", + " 310212634\n", + " 1405\n", + " 1422\n", + " 7566161\n", + " shopping\n", + " 1421\n", " \n", " \n", - " 2489\n", - " 309796969\n", - " 129\n", - " 128.0\n", - " 7556023\n", - " othdiscr\n", - " 136\n", + " 29668\n", + " 310220296\n", + " 1156\n", + " 1430\n", + " 7566348\n", + " othmaint\n", + " 1437\n", " \n", " \n", "\n", - "

2490 rows × 6 columns

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29669 rows × 6 columns

\n", "" ], "text/plain": [ - " tour_id model_choice override_choice person_id tour_type \\\n", - "0 6812 72 72.0 166 eatout \n", - "1 8110 62 47.0 197 shopping \n", - "2 11013 33 32.0 268 othdiscr \n", - "3 11016 71 71.0 268 othmaint \n", - "4 15403 67 67.0 375 othmaint \n", - "... ... ... ... ... ... \n", - "2485 309760814 154 154.0 7555141 shopping \n", - "2486 309760815 41 41.0 7555141 shopping \n", - "2487 309790009 36 36.0 7555853 social \n", - "2488 309796968 94 94.0 7556023 othdiscr \n", - "2489 309796969 129 128.0 7556023 othdiscr \n", + " tour_id model_choice override_choice person_id tour_type \\\n", + "0 1870 70 26 45 othdiscr \n", + "1 20468 138 161 499 escort \n", + "2 27055 133 185 659 social \n", + "3 38877 115 147 948 escort \n", + "4 38904 107 104 948 social \n", + "... ... ... ... ... ... \n", + "29664 310197956 1374 1384 7565803 shopping \n", + "29665 310202376 1402 1402 7565911 othdiscr \n", + "29666 310202384 1402 1402 7565911 shopping \n", + "29667 310212634 1405 1422 7566161 shopping \n", + "29668 310220296 1156 1430 7566348 othmaint \n", "\n", - " home_zone_id \n", - "0 71 \n", - "1 80 \n", - "2 91 \n", - "3 91 \n", - "4 105 \n", - "... ... \n", - "2485 85 \n", - "2486 85 \n", - "2487 115 \n", - "2488 136 \n", - "2489 136 \n", + " home_zone_id \n", + "0 52 \n", + "1 124 \n", + "2 132 \n", + "3 148 \n", + "4 148 \n", + "... ... \n", + "29664 1386 \n", + "29665 1402 \n", + "29666 1402 \n", + "29667 1421 \n", + "29668 1437 \n", "\n", - "[2490 rows x 6 columns]" + "[29669 rows x 6 columns]" ] }, - "execution_count": 9, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -1321,7 +1044,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -1356,48 +1079,48 @@ " \n", " \n", " 0\n", - " 7785298\n", - " 113\n", - " 103.0\n", - " 189885\n", + " 7853686\n", + " 131\n", + " 131\n", + " 191553\n", " eatout\n", - " 135\n", + " 217\n", " \n", " \n", " 1\n", - " 8708454\n", - " 103\n", - " 106.0\n", - " 212401\n", - " eatout\n", - " 8\n", + " 7902318\n", + " 321\n", + " 323\n", + " 192739\n", + " shopping\n", + " 322\n", " \n", " \n", " 2\n", - " 9715006\n", - " 188\n", - " 188.0\n", - " 236951\n", + " 7909776\n", + " 350\n", + " 320\n", + " 192921\n", " othdiscr\n", - " 183\n", + " 330\n", " \n", " \n", " 3\n", - " 10831112\n", - " 105\n", - " 105.0\n", - " 264173\n", - " shopping\n", - " 10\n", + " 7988742\n", + " 527\n", + " 637\n", + " 194847\n", + " othdiscr\n", + " 526\n", " \n", " \n", " 4\n", - " 20334787\n", - " 157\n", - " 157.0\n", - " 495970\n", - " othmaint\n", - " 140\n", + " 8103874\n", + " 591\n", + " 687\n", + " 197655\n", + " shopping\n", + " 683\n", " \n", " \n", " ...\n", @@ -1409,86 +1132,86 @@ " ...\n", " \n", " \n", - " 86\n", - " 283676518\n", - " 115\n", - " 115.0\n", - " 6918939\n", - " shopping\n", - " 121\n", + " 1272\n", + " 303771147\n", + " 484\n", + " 673\n", + " 7409052\n", + " othdiscr\n", + " 675\n", " \n", " \n", - " 87\n", - " 295260168\n", - " 7\n", - " 7.0\n", - " 7201469\n", + " 1273\n", + " 304144212\n", + " 796\n", + " 843\n", + " 7418154\n", " social\n", - " 114\n", + " 806\n", " \n", " \n", - " 88\n", - " 297646485\n", - " 90\n", - " 89.0\n", - " 7259670\n", + " 1274\n", + " 304463637\n", + " 9\n", + " 38\n", + " 7425942\n", " othdiscr\n", - " 25\n", + " 1043\n", " \n", " \n", - " 89\n", - " 298814741\n", - " 147\n", - " 147.0\n", - " 7288164\n", - " othmaint\n", - " 74\n", + " 1275\n", + " 305125582\n", + " 29\n", + " 98\n", + " 7442087\n", + " othdiscr\n", + " 50\n", " \n", " \n", - " 90\n", - " 301810980\n", - " 66\n", - " 66.0\n", - " 7361244\n", - " othmaint\n", - " 177\n", + " 1276\n", + " 305246245\n", + " 2\n", + " 149\n", + " 7445030\n", + " othdiscr\n", + " 149\n", " \n", " \n", "\n", - "

91 rows × 6 columns

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1277 rows × 6 columns

\n", "" ], "text/plain": [ - " tour_id model_choice override_choice person_id tour_type \\\n", - "0 7785298 113 103.0 189885 eatout \n", - "1 8708454 103 106.0 212401 eatout \n", - "2 9715006 188 188.0 236951 othdiscr \n", - "3 10831112 105 105.0 264173 shopping \n", - "4 20334787 157 157.0 495970 othmaint \n", - ".. ... ... ... ... ... \n", - "86 283676518 115 115.0 6918939 shopping \n", - "87 295260168 7 7.0 7201469 social \n", - "88 297646485 90 89.0 7259670 othdiscr \n", - "89 298814741 147 147.0 7288164 othmaint \n", - "90 301810980 66 66.0 7361244 othmaint \n", + " tour_id model_choice override_choice person_id tour_type \\\n", + "0 7853686 131 131 191553 eatout \n", + "1 7902318 321 323 192739 shopping \n", + "2 7909776 350 320 192921 othdiscr \n", + "3 7988742 527 637 194847 othdiscr \n", + "4 8103874 591 687 197655 shopping \n", + "... ... ... ... ... ... \n", + "1272 303771147 484 673 7409052 othdiscr \n", + "1273 304144212 796 843 7418154 social \n", + "1274 304463637 9 38 7425942 othdiscr \n", + "1275 305125582 29 98 7442087 othdiscr \n", + "1276 305246245 2 149 7445030 othdiscr \n", "\n", - " home_zone_id \n", - "0 135 \n", - "1 8 \n", - "2 183 \n", - "3 10 \n", - "4 140 \n", - ".. ... \n", - "86 121 \n", - "87 114 \n", - "88 25 \n", - "89 74 \n", - "90 177 \n", + " home_zone_id \n", + "0 217 \n", + "1 322 \n", + "2 330 \n", + "3 526 \n", + "4 683 \n", + "... ... \n", + "1272 675 \n", + "1273 806 \n", + "1274 1043 \n", + "1275 50 \n", + "1276 149 \n", "\n", - "[91 rows x 6 columns]" + "[1277 rows x 6 columns]" ] }, - "execution_count": 10, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1506,7 +1229,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -1592,9 +1315,9 @@ " 7\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 3\n", " 5.89564\n", " 2.875000\n", @@ -1616,9 +1339,9 @@ " 19\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.84871\n", " 5.195214\n", @@ -1640,9 +1363,9 @@ " 38\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.53231\n", " 80.470405\n", @@ -1664,9 +1387,9 @@ " 20\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 2\n", " 5.64330\n", " 7.947368\n", @@ -1688,9 +1411,9 @@ " 86\n", " ...\n", " 0\n", - " 0.00000\n", + " 0.0\n", " 72.14684\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.52555\n", " 38.187500\n", @@ -1723,191 +1446,191 @@ " ...\n", " \n", " \n", - " 186\n", - " 4\n", - " 4\n", - " 1\n", - " 2779\n", - " 8062\n", - " 376.0\n", - " 172.0\n", - " 15.00000\n", - " 1760\n", - " 1178\n", + " 1450\n", + " 34\n", + " 34\n", + " 9\n", + " 2724\n", + " 6493\n", + " 1320.0\n", + " 630.0\n", + " 69.00000\n", + " 1046\n", + " 1013\n", " ...\n", - " 3\n", - " 0.00000\n", - " 0.00000\n", + " 4\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - " 2.04173\n", - " 14.860963\n", - " 9.411765\n", - " 5.762347\n", + " 1.12116\n", + " 3.896996\n", + " 1.496423\n", + " 1.081235\n", " False\n", " \n", " \n", - " 187\n", - 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" 3.413233\n", + " 1.17587\n", + " 3.419152\n", + " 3.312402\n", + " 1.682465\n", " False\n", " \n", " \n", - " 189\n", - " 4\n", - " 4\n", - " 1\n", - " 3546\n", - " 8476\n", - " 201.0\n", - " 72.0\n", - " 6.00000\n", - " 226\n", - " 1057\n", + " 1453\n", + " 34\n", + " 34\n", + " 9\n", + " 298\n", + " 779\n", + " 14195.0\n", + " 429.0\n", + " 4.00000\n", + " 922\n", + " 88\n", " ...\n", - " 2\n", - " 0.00000\n", - " 0.00000\n", + " 5\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - " 2.88773\n", - " 45.461538\n", - " 2.897436\n", - " 2.723836\n", + " 1.01972\n", + " 0.688222\n", + " 2.129330\n", + " 0.520115\n", " False\n", " \n", " \n", - " 190\n", - " 4\n", - " 4\n", - " 1\n", - " 968\n", - " 1647\n", - " 1381.0\n", - " 14.0\n", - " 28.00000\n", - " 1010\n", - " 114\n", + " 1454\n", + " 34\n", + " 34\n", + " 9\n", + " 1068\n", + " 2337\n", + " 10469.0\n", + " 1114.0\n", + " 27.00000\n", + " 607\n", + " 418\n", " ...\n", - " 3\n", - " 0.00000\n", - " 0.00000\n", + " 5\n", + " 0.0\n", " 0.00000\n", + " 0.0\n", " 1\n", - 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190 rows × 28 columns

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1454 rows × 28 columns

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" COLLPTE TOPOLOGY TERMINAL household_density \\\n", - "zone_id \n", - "1 0.00000 3 5.89564 2.875000 \n", - "2 0.00000 1 5.84871 5.195214 \n", - "3 0.00000 1 5.53231 80.470405 \n", - "4 0.00000 2 5.64330 7.947368 \n", - "5 0.00000 1 5.52555 38.187500 \n", - "... ... ... ... ... \n", - "186 0.00000 1 2.04173 14.860963 \n", - "187 0.00000 2 1.73676 11.841270 \n", - "188 11152.93652 1 2.28992 3.984127 \n", - "189 0.00000 1 2.88773 45.461538 \n", - "190 0.00000 1 2.60309 23.047619 \n", + " TOPOLOGY TERMINAL household_density employment_density \\\n", + "zone_id \n", + "1 3 5.89564 2.875000 1707.375000 \n", + "2 1 5.84871 5.195214 1631.374751 \n", + "3 1 5.53231 80.470405 736.891913 \n", + "4 2 5.64330 7.947368 1180.736842 \n", + "5 1 5.52555 38.187500 978.875000 \n", + "... ... ... ... ... \n", + "1450 1 1.12116 3.896996 1.496423 \n", + "1451 1 1.17116 4.777251 1.793839 \n", + "1452 1 1.17587 3.419152 3.312402 \n", + "1453 1 1.01972 0.688222 2.129330 \n", + "1454 1 0.95542 0.936021 0.531989 \n", "\n", - 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"execution_count": 12, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -2141,7 +1864,7 @@ "7 1 " ] }, - "execution_count": 12, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -2159,7 +1882,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -2270,7 +1993,7 @@ "othdiscr 0.252 0.212 0.272 0.165 0.000 0.098" ] }, - "execution_count": 13, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -2290,21 +2013,13 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

Iteration 029 [Optimization terminated successfully]

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Iteration 046 [Optimization terminated successfully]

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Best LL = -13268.709190928732

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Best LL = -85747.12036028807

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" NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.579932\n", " \n", " \n", " coef_othmaint_dist_5_plus\n", - " -0.229655\n", + " -0.156745\n", + " -0.156745\n", " -0.109300\n", + " -25.000000\n", + " 25.000000\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.229655\n", " \n", " \n", " coef_shopping_dist_2_5\n", - " -0.629792\n", + " -0.704553\n", + " -0.704553\n", " -0.565500\n", + " -25.000000\n", + " 25.000000\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.629792\n", " \n", " \n", " coef_shopping_dist_5_plus\n", - " -0.130649\n", + " -0.234821\n", + " -0.234821\n", " -0.183200\n", + " -25.000000\n", + " 25.000000\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.130649\n", " \n", " \n", " coef_social_dist_2_5\n", - " -0.245175\n", + " -0.464176\n", + " -0.464176\n", " -0.348500\n", + " -25.000000\n", + " 25.000000\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.245175\n", " \n", " \n", " coef_social_dist_5_plus\n", - " -0.190239\n", + " -0.176446\n", + " -0.176446\n", " -0.130600\n", + " -25.000000\n", + " 25.000000\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.190239\n", " \n", " \n", " eatout_HEREMPN\n", - " -0.946877\n", + " -1.601448\n", + " -1.601448\n", " -1.354796\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -0.946877\n", " \n", " \n", " eatout_RETEMPN\n", " -0.298406\n", " -0.298406\n", + " -0.298406\n", + " -0.298406\n", + " -0.298406\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -0.298406\n", " \n", " \n", " escort_AGE0519\n", - " -1.171241\n", + " -0.765963\n", + " -0.765963\n", " -0.765718\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -1.171241\n", " \n", " \n", " escort_HEREMPN\n", - " -2.450057\n", + " -1.996310\n", + " -1.996310\n", " -1.937942\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -2.450057\n", " \n", " \n", " escort_HSENROLL\n", - " -3.304440\n", - " -1.795767\n", + " -1.872611\n", + " -1.872611\n", + " -1.795768\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -3.304440\n", " \n", " \n", " escort_RETEMPN\n", " -1.491655\n", " -1.491655\n", + " -1.491655\n", + " -1.491655\n", + " -1.491655\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -1.491655\n", " \n", " \n", " othdiscr_HEREMPN\n", - " -1.584964\n", + " -1.342128\n", + " -1.342128\n", " -1.301953\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -1.584964\n", " \n", " \n", " othdiscr_HSENROLL\n", - " -2.466750\n", + " -2.287886\n", + " -2.287886\n", " -2.322788\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -2.466750\n", " \n", " \n", " othdiscr_OTHEMPN\n", - " -2.370292\n", + " -1.905661\n", + " -1.905661\n", " -1.801810\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -2.370292\n", " \n", " \n", " othdiscr_RETEMPN\n", - " -1.238181\n", + " -1.550175\n", + " -1.550175\n", " -1.551169\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -1.238181\n", " \n", " \n", " othdiscr_TOTHH\n", " -1.378326\n", " -1.378326\n", + " -1.378326\n", + " -1.378326\n", + " -1.378326\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -1.378326\n", " \n", " \n", " othmaint_HEREMPN\n", - " -0.668952\n", + " -0.689025\n", + " -0.689025\n", " -0.657780\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -0.668952\n", " \n", " \n", " othmaint_RETEMPN\n", " -0.729811\n", " -0.729811\n", + " -0.729811\n", + " -0.729811\n", + " -0.729811\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -0.729811\n", " \n", " \n", " shopping_RETEMPN\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " social_HEREMPN\n", - " -0.302843\n", + " -0.831065\n", + " -0.831065\n", " -0.738145\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -0.302843\n", " \n", " \n", " social_RETEMPN\n", " -0.650088\n", " -0.650088\n", + " -0.650088\n", + " -0.650088\n", + " -0.650088\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -0.650088\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue nullvalue minimum \\\n", - "-999 -999.000000 -999.000000 -999.0 -999.0 \n", - "0 0.000000 0.000000 0.0 0.0 \n", - "1 1.000000 1.000000 1.0 1.0 \n", - "coef_eatout_dist_0_2 -0.767979 -0.560900 0.0 NaN \n", - "coef_eatout_dist_2_5 -0.226448 -0.319200 0.0 NaN \n", - "coef_eatout_dist_5_plus -0.188137 -0.123800 0.0 NaN \n", - "coef_escort_dist_0_2 0.226691 -0.149900 0.0 NaN \n", - "coef_escort_dist_2_5 -0.813494 -0.867100 0.0 NaN \n", - "coef_escort_dist_5_plus -0.255056 -0.213700 0.0 NaN \n", - "coef_mode_logsum 0.662937 0.675500 0.0 NaN \n", - "coef_othdiscr_dist_0_2 -0.203187 -0.167700 0.0 NaN \n", - "coef_othdiscr_dist_2_5 -0.550945 -0.495500 0.0 NaN \n", - "coef_othdiscr_dist_5_plus -0.000141 -0.119300 0.0 NaN \n", - "coef_othmaint_dist_2_5 -0.579932 -0.605500 0.0 NaN \n", - "coef_othmaint_dist_5_plus -0.229655 -0.109300 0.0 NaN \n", - "coef_shopping_dist_2_5 -0.629792 -0.565500 0.0 NaN \n", - "coef_shopping_dist_5_plus -0.130649 -0.183200 0.0 NaN \n", - "coef_social_dist_2_5 -0.245175 -0.348500 0.0 NaN \n", - "coef_social_dist_5_plus -0.190239 -0.130600 0.0 NaN \n", - "eatout_HEREMPN -0.946877 -1.354796 0.0 -6.0 \n", - "eatout_RETEMPN -0.298406 -0.298406 0.0 -6.0 \n", - "escort_AGE0519 -1.171241 -0.765718 0.0 -6.0 \n", - "escort_HEREMPN -2.450057 -1.937942 0.0 -6.0 \n", - "escort_HSENROLL -3.304440 -1.795767 0.0 -6.0 \n", - "escort_RETEMPN -1.491655 -1.491655 0.0 -6.0 \n", - "othdiscr_HEREMPN -1.584964 -1.301953 0.0 -6.0 \n", - "othdiscr_HSENROLL -2.466750 -2.322788 0.0 -6.0 \n", - "othdiscr_OTHEMPN -2.370292 -1.801810 0.0 -6.0 \n", - "othdiscr_RETEMPN -1.238181 -1.551169 0.0 -6.0 \n", - "othdiscr_TOTHH -1.378326 -1.378326 0.0 -6.0 \n", - "othmaint_HEREMPN -0.668952 -0.657780 0.0 -6.0 \n", - "othmaint_RETEMPN -0.729811 -0.729811 0.0 -6.0 \n", - "shopping_RETEMPN 0.000000 0.000000 0.0 -6.0 \n", - "social_HEREMPN -0.302843 -0.738145 0.0 -6.0 \n", - "social_RETEMPN -0.650088 -0.650088 0.0 -6.0 \n", + " value best initvalue minimum \\\n", + "param_name \n", + "-999 -999.000000 -999.000000 -999.000000 -999.000000 \n", + "0 0.000000 0.000000 0.000000 0.000000 \n", + "1 1.000000 1.000000 1.000000 1.000000 \n", + "coef_eatout_dist_0_2 -0.959646 -0.959646 -0.560900 -25.000000 \n", + "coef_eatout_dist_2_5 -0.427890 -0.427890 -0.319200 -25.000000 \n", + "coef_eatout_dist_5_plus -0.182199 -0.182199 -0.123800 -25.000000 \n", + "coef_escort_dist_0_2 -0.290871 -0.290871 -0.149900 -25.000000 \n", + "coef_escort_dist_2_5 -0.959038 -0.959038 -0.867100 -25.000000 \n", + "coef_escort_dist_5_plus -0.264682 -0.264682 -0.213700 -25.000000 \n", + "coef_mode_logsum 0.165346 0.165346 0.675500 -25.000000 \n", + "coef_othdiscr_dist_0_2 -0.424399 -0.424399 -0.167700 -25.000000 \n", + "coef_othdiscr_dist_2_5 -0.615669 -0.615669 -0.495500 -25.000000 \n", + "coef_othdiscr_dist_5_plus -0.171387 -0.171387 -0.119300 -25.000000 \n", + "coef_othmaint_dist_2_5 -0.796780 -0.796780 -0.605500 -25.000000 \n", + "coef_othmaint_dist_5_plus -0.156745 -0.156745 -0.109300 -25.000000 \n", + "coef_shopping_dist_2_5 -0.704553 -0.704553 -0.565500 -25.000000 \n", + "coef_shopping_dist_5_plus -0.234821 -0.234821 -0.183200 -25.000000 \n", + "coef_social_dist_2_5 -0.464176 -0.464176 -0.348500 -25.000000 \n", + "coef_social_dist_5_plus -0.176446 -0.176446 -0.130600 -25.000000 \n", + "eatout_HEREMPN -1.601448 -1.601448 -1.354796 -6.000000 \n", + "eatout_RETEMPN -0.298406 -0.298406 -0.298406 -0.298406 \n", + "escort_AGE0519 -0.765963 -0.765963 -0.765718 -6.000000 \n", + "escort_HEREMPN -1.996310 -1.996310 -1.937942 -6.000000 \n", + "escort_HSENROLL -1.872611 -1.872611 -1.795768 -6.000000 \n", + "escort_RETEMPN -1.491655 -1.491655 -1.491655 -1.491655 \n", + "othdiscr_HEREMPN -1.342128 -1.342128 -1.301953 -6.000000 \n", + "othdiscr_HSENROLL -2.287886 -2.287886 -2.322788 -6.000000 \n", + "othdiscr_OTHEMPN -1.905661 -1.905661 -1.801810 -6.000000 \n", + "othdiscr_RETEMPN -1.550175 -1.550175 -1.551169 -6.000000 \n", + "othdiscr_TOTHH -1.378326 -1.378326 -1.378326 -1.378326 \n", + "othmaint_HEREMPN -0.689025 -0.689025 -0.657780 -6.000000 \n", + "othmaint_RETEMPN -0.729811 -0.729811 -0.729811 -0.729811 \n", + "shopping_RETEMPN 0.000000 0.000000 0.000000 0.000000 \n", + "social_HEREMPN -0.831065 -0.831065 -0.738145 -6.000000 \n", + "social_RETEMPN -0.650088 -0.650088 -0.650088 -0.650088 \n", "\n", - " maximum holdfast note best \n", - "-999 -999.0 1 -999.000000 \n", - "0 0.0 1 0.000000 \n", - "1 1.0 1 1.000000 \n", - "coef_eatout_dist_0_2 NaN 0 -0.767979 \n", - "coef_eatout_dist_2_5 NaN 0 -0.226448 \n", - "coef_eatout_dist_5_plus NaN 0 -0.188137 \n", - "coef_escort_dist_0_2 NaN 0 0.226691 \n", - "coef_escort_dist_2_5 NaN 0 -0.813494 \n", - "coef_escort_dist_5_plus NaN 0 -0.255056 \n", - "coef_mode_logsum NaN 0 0.662937 \n", - "coef_othdiscr_dist_0_2 NaN 0 -0.203187 \n", - "coef_othdiscr_dist_2_5 NaN 0 -0.550945 \n", - "coef_othdiscr_dist_5_plus NaN 0 -0.000141 \n", - "coef_othmaint_dist_2_5 NaN 0 -0.579932 \n", - "coef_othmaint_dist_5_plus NaN 0 -0.229655 \n", - "coef_shopping_dist_2_5 NaN 0 -0.629792 \n", - "coef_shopping_dist_5_plus NaN 0 -0.130649 \n", - "coef_social_dist_2_5 NaN 0 -0.245175 \n", - "coef_social_dist_5_plus NaN 0 -0.190239 \n", - "eatout_HEREMPN 6.0 0 -0.946877 \n", - "eatout_RETEMPN 6.0 1 -0.298406 \n", - "escort_AGE0519 6.0 0 -1.171241 \n", - "escort_HEREMPN 6.0 0 -2.450057 \n", - "escort_HSENROLL 6.0 0 -3.304440 \n", - "escort_RETEMPN 6.0 1 -1.491655 \n", - "othdiscr_HEREMPN 6.0 0 -1.584964 \n", - "othdiscr_HSENROLL 6.0 0 -2.466750 \n", - "othdiscr_OTHEMPN 6.0 0 -2.370292 \n", - "othdiscr_RETEMPN 6.0 0 -1.238181 \n", - "othdiscr_TOTHH 6.0 1 -1.378326 \n", - "othmaint_HEREMPN 6.0 0 -0.668952 \n", - "othmaint_RETEMPN 6.0 1 -0.729811 \n", - "shopping_RETEMPN 6.0 1 0.000000 \n", - "social_HEREMPN 6.0 0 -0.302843 \n", - "social_RETEMPN 6.0 1 -0.650088 " + " maximum nullvalue holdfast \n", + "param_name \n", + "-999 -999.000000 0.0 1 \n", + "0 0.000000 0.0 1 \n", + "1 1.000000 0.0 1 \n", + "coef_eatout_dist_0_2 25.000000 0.0 0 \n", + "coef_eatout_dist_2_5 25.000000 0.0 0 \n", + "coef_eatout_dist_5_plus 25.000000 0.0 0 \n", + "coef_escort_dist_0_2 25.000000 0.0 0 \n", + "coef_escort_dist_2_5 25.000000 0.0 0 \n", + "coef_escort_dist_5_plus 25.000000 0.0 0 \n", + "coef_mode_logsum 25.000000 0.0 0 \n", + "coef_othdiscr_dist_0_2 25.000000 0.0 0 \n", + "coef_othdiscr_dist_2_5 25.000000 0.0 0 \n", + "coef_othdiscr_dist_5_plus 25.000000 0.0 0 \n", + "coef_othmaint_dist_2_5 25.000000 0.0 0 \n", + "coef_othmaint_dist_5_plus 25.000000 0.0 0 \n", + "coef_shopping_dist_2_5 25.000000 0.0 0 \n", + "coef_shopping_dist_5_plus 25.000000 0.0 0 \n", + "coef_social_dist_2_5 25.000000 0.0 0 \n", + "coef_social_dist_5_plus 25.000000 0.0 0 \n", + "eatout_HEREMPN 6.000000 0.0 0 \n", + "eatout_RETEMPN -0.298406 0.0 1 \n", + "escort_AGE0519 6.000000 0.0 0 \n", + "escort_HEREMPN 6.000000 0.0 0 \n", + "escort_HSENROLL 6.000000 0.0 0 \n", + "escort_RETEMPN -1.491655 0.0 1 \n", + "othdiscr_HEREMPN 6.000000 0.0 0 \n", + "othdiscr_HSENROLL 6.000000 0.0 0 \n", + "othdiscr_OTHEMPN 6.000000 0.0 0 \n", + "othdiscr_RETEMPN 6.000000 0.0 0 \n", + "othdiscr_TOTHH -1.378326 0.0 1 \n", + "othmaint_HEREMPN 6.000000 0.0 0 \n", + "othmaint_RETEMPN -0.729811 0.0 1 \n", + "shopping_RETEMPN 0.000000 0.0 1 \n", + "social_HEREMPN 6.000000 0.0 0 \n", + "social_RETEMPN -0.650088 0.0 1 " ] }, "metadata": {}, @@ -2850,71 +2541,71 @@ " \n", " \n", " coef_eatout_dist_0_2\n", - " -0.767979\n", + " -0.959646\n", " \n", " \n", " coef_eatout_dist_2_5\n", - " -0.226448\n", + " -0.427890\n", " \n", " \n", " coef_eatout_dist_5_plus\n", - " -0.188137\n", + " -0.182199\n", " \n", " \n", " coef_escort_dist_0_2\n", - " 0.226691\n", + " -0.290871\n", " \n", " \n", " coef_escort_dist_2_5\n", - " -0.813494\n", + " -0.959038\n", " \n", " \n", " coef_escort_dist_5_plus\n", - " -0.255056\n", + " -0.264682\n", " \n", " \n", " coef_mode_logsum\n", - " 0.662937\n", + " 0.165346\n", " \n", " \n", " coef_othdiscr_dist_0_2\n", - " -0.203187\n", + " -0.424399\n", " \n", " \n", " coef_othdiscr_dist_2_5\n", - " -0.550945\n", + " -0.615669\n", " \n", " \n", " coef_othdiscr_dist_5_plus\n", - " -0.000141\n", + " -0.171387\n", " \n", " \n", " coef_othmaint_dist_2_5\n", - " -0.579932\n", + " -0.796780\n", " \n", " \n", " coef_othmaint_dist_5_plus\n", - " -0.229655\n", + " -0.156745\n", " \n", " \n", " coef_shopping_dist_2_5\n", - " -0.629792\n", + " -0.704553\n", " \n", " \n", " coef_shopping_dist_5_plus\n", - " -0.130649\n", + " -0.234821\n", " \n", " \n", " coef_social_dist_2_5\n", - " -0.245175\n", + " -0.464176\n", " \n", " \n", " coef_social_dist_5_plus\n", - " -0.190239\n", + " -0.176446\n", " \n", " \n", " eatout_HEREMPN\n", - " -0.946877\n", + " -1.601448\n", " \n", " \n", " eatout_RETEMPN\n", @@ -2922,15 +2613,15 @@ " \n", " \n", " escort_AGE0519\n", - " -1.171241\n", + " -0.765963\n", " \n", " \n", " escort_HEREMPN\n", - " -2.450057\n", + " -1.996310\n", " \n", " \n", " escort_HSENROLL\n", - " -3.304440\n", + " -1.872611\n", " \n", " \n", " escort_RETEMPN\n", @@ -2938,19 +2629,19 @@ " \n", " \n", " othdiscr_HEREMPN\n", - " -1.584964\n", + " -1.342128\n", " \n", " \n", " othdiscr_HSENROLL\n", - " -2.466750\n", + " -2.287886\n", " \n", " \n", " othdiscr_OTHEMPN\n", - " -2.370292\n", + " -1.905661\n", " \n", " \n", " othdiscr_RETEMPN\n", - " -1.238181\n", + " -1.550175\n", " \n", " \n", " othdiscr_TOTHH\n", @@ -2958,7 +2649,7 @@ " \n", " \n", " othmaint_HEREMPN\n", - " -0.668952\n", + " -0.689025\n", " \n", " \n", " othmaint_RETEMPN\n", @@ -2970,14 +2661,14 @@ " \n", " \n", " social_HEREMPN\n", - " -0.302843\n", + " -0.831065\n", " \n", " \n", " social_RETEMPN\n", " -0.650088\n", " \n", " \n", - "loglike-13268.709190928732d_loglike\n", + "
logloss2.770862804895239d_logloss\n", " \n", " \n", " \n", @@ -2999,71 +2690,71 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3071,15 +2762,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3087,19 +2778,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3107,7 +2798,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3119,109 +2810,109 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - "
coef_eatout_dist_0_20.0003340.000068
coef_eatout_dist_2_50.0006060.000060
coef_eatout_dist_5_plus-0.0012540.000251
coef_escort_dist_0_20.0000040.000236
coef_escort_dist_2_5-0.001135-0.000043
coef_escort_dist_5_plus-0.0005190.000007
coef_mode_logsum0.000531-0.000027
coef_othdiscr_dist_0_2-0.001077-0.000193
coef_othdiscr_dist_2_5-0.001877-0.000067
coef_othdiscr_dist_5_plus-0.0013870.000015
coef_othmaint_dist_2_5-0.000112-0.000110
coef_othmaint_dist_5_plus-0.000787-0.000227
coef_shopping_dist_2_5-0.0002320.000147
coef_shopping_dist_5_plus-0.0007950.000482
coef_social_dist_2_5-0.000397-0.000027
coef_social_dist_5_plus0.000937-0.000062
eatout_HEREMPN-0.0002880.000078
eatout_RETEMPN
escort_AGE0519-0.000725-0.000137
escort_HEREMPN0.000389-0.000064
escort_HSENROLL-0.000033-0.000067
escort_RETEMPN
othdiscr_HEREMPN0.0013260.000065
othdiscr_HSENROLL0.0000250.000034
othdiscr_OTHEMPN0.000044-0.000049
othdiscr_RETEMPN-0.0002870.000009
othdiscr_TOTHH
othmaint_HEREMPN0.000035-0.000002
othmaint_RETEMPN
social_HEREMPN-0.000091-0.000084
social_RETEMPN0.000000
nit29nfev79njev29status0message'Optimization terminated successfully'successTrueelapsed_time0:00:07.087910method'SLSQP'n_cases2581iteration_number29logloss5.140917935268784" + "nit46nfev46njev46status0message'Optimization terminated successfully'successTrueelapsed_time0:00:06.714015method'slsqp'n_cases30946iteration_number46loglike-85747.12036028807" ], "text/plain": [ "┣ x: -999 -999.000000\n", "┃ 0 0.000000\n", "┃ 1 1.000000\n", - "┃ coef_eatout_dist_0_2 -0.767979\n", - "┃ coef_eatout_dist_2_5 -0.226448\n", - "┃ coef_eatout_dist_5_plus -0.188137\n", - "┃ coef_escort_dist_0_2 0.226691\n", - "┃ coef_escort_dist_2_5 -0.813494\n", - "┃ coef_escort_dist_5_plus -0.255056\n", - "┃ coef_mode_logsum 0.662937\n", - "┃ coef_othdiscr_dist_0_2 -0.203187\n", - "┃ coef_othdiscr_dist_2_5 -0.550945\n", - "┃ coef_othdiscr_dist_5_plus -0.000141\n", - "┃ coef_othmaint_dist_2_5 -0.579932\n", - "┃ coef_othmaint_dist_5_plus -0.229655\n", - "┃ coef_shopping_dist_2_5 -0.629792\n", - "┃ coef_shopping_dist_5_plus -0.130649\n", - "┃ coef_social_dist_2_5 -0.245175\n", - "┃ coef_social_dist_5_plus -0.190239\n", - "┃ eatout_HEREMPN -0.946877\n", + "┃ coef_eatout_dist_0_2 -0.959646\n", + "┃ coef_eatout_dist_2_5 -0.427890\n", + "┃ coef_eatout_dist_5_plus -0.182199\n", + "┃ coef_escort_dist_0_2 -0.290871\n", + "┃ coef_escort_dist_2_5 -0.959038\n", + "┃ coef_escort_dist_5_plus -0.264682\n", + "┃ coef_mode_logsum 0.165346\n", + "┃ coef_othdiscr_dist_0_2 -0.424399\n", + "┃ coef_othdiscr_dist_2_5 -0.615669\n", + "┃ coef_othdiscr_dist_5_plus -0.171387\n", + "┃ coef_othmaint_dist_2_5 -0.796780\n", + "┃ coef_othmaint_dist_5_plus -0.156745\n", + "┃ coef_shopping_dist_2_5 -0.704553\n", + "┃ coef_shopping_dist_5_plus -0.234821\n", + "┃ coef_social_dist_2_5 -0.464176\n", + "┃ coef_social_dist_5_plus -0.176446\n", + "┃ eatout_HEREMPN -1.601448\n", "┃ eatout_RETEMPN -0.298406\n", - "┃ escort_AGE0519 -1.171241\n", - "┃ escort_HEREMPN -2.450057\n", - "┃ escort_HSENROLL -3.304440\n", + "┃ escort_AGE0519 -0.765963\n", + "┃ escort_HEREMPN -1.996310\n", + "┃ escort_HSENROLL -1.872611\n", "┃ escort_RETEMPN -1.491655\n", - "┃ othdiscr_HEREMPN -1.584964\n", - "┃ othdiscr_HSENROLL -2.466750\n", - "┃ othdiscr_OTHEMPN -2.370292\n", - "┃ othdiscr_RETEMPN -1.238181\n", + "┃ othdiscr_HEREMPN -1.342128\n", + "┃ othdiscr_HSENROLL -2.287886\n", + "┃ othdiscr_OTHEMPN -1.905661\n", + "┃ othdiscr_RETEMPN -1.550175\n", "┃ othdiscr_TOTHH -1.378326\n", - "┃ othmaint_HEREMPN -0.668952\n", + "┃ othmaint_HEREMPN -0.689025\n", "┃ othmaint_RETEMPN -0.729811\n", "┃ shopping_RETEMPN 0.000000\n", - "┃ social_HEREMPN -0.302843\n", + "┃ social_HEREMPN -0.831065\n", "┃ social_RETEMPN -0.650088\n", "┃ dtype: float64\n", - "┣ loglike: -13268.709190928732\n", - "┣ d_loglike: -999 0.000000\n", + "┣ logloss: 2.770862804895239\n", + "┣ d_logloss: -999 0.000000\n", "┃ 0 0.000000\n", "┃ 1 0.000000\n", - "┃ coef_eatout_dist_0_2 0.000334\n", - "┃ coef_eatout_dist_2_5 0.000606\n", - "┃ coef_eatout_dist_5_plus -0.001254\n", - "┃ coef_escort_dist_0_2 0.000004\n", - "┃ coef_escort_dist_2_5 -0.001135\n", - "┃ coef_escort_dist_5_plus -0.000519\n", - "┃ coef_mode_logsum 0.000531\n", - "┃ coef_othdiscr_dist_0_2 -0.001077\n", - "┃ coef_othdiscr_dist_2_5 -0.001877\n", - "┃ coef_othdiscr_dist_5_plus -0.001387\n", - "┃ coef_othmaint_dist_2_5 -0.000112\n", - "┃ coef_othmaint_dist_5_plus -0.000787\n", - "┃ coef_shopping_dist_2_5 -0.000232\n", - "┃ coef_shopping_dist_5_plus -0.000795\n", - "┃ coef_social_dist_2_5 -0.000397\n", - "┃ coef_social_dist_5_plus 0.000937\n", - "┃ eatout_HEREMPN -0.000288\n", + "┃ coef_eatout_dist_0_2 0.000068\n", + "┃ coef_eatout_dist_2_5 0.000060\n", + "┃ coef_eatout_dist_5_plus 0.000251\n", + "┃ coef_escort_dist_0_2 0.000236\n", + "┃ coef_escort_dist_2_5 -0.000043\n", + "┃ coef_escort_dist_5_plus 0.000007\n", + "┃ coef_mode_logsum -0.000027\n", + "┃ coef_othdiscr_dist_0_2 -0.000193\n", + "┃ coef_othdiscr_dist_2_5 -0.000067\n", + "┃ coef_othdiscr_dist_5_plus 0.000015\n", + "┃ coef_othmaint_dist_2_5 -0.000110\n", + "┃ coef_othmaint_dist_5_plus -0.000227\n", + "┃ coef_shopping_dist_2_5 0.000147\n", + "┃ coef_shopping_dist_5_plus 0.000482\n", + "┃ coef_social_dist_2_5 -0.000027\n", + "┃ coef_social_dist_5_plus -0.000062\n", + "┃ eatout_HEREMPN 0.000078\n", "┃ eatout_RETEMPN 0.000000\n", - "┃ escort_AGE0519 -0.000725\n", - "┃ escort_HEREMPN 0.000389\n", - "┃ escort_HSENROLL -0.000033\n", + "┃ escort_AGE0519 -0.000137\n", + "┃ escort_HEREMPN -0.000064\n", + "┃ escort_HSENROLL -0.000067\n", "┃ escort_RETEMPN 0.000000\n", - "┃ othdiscr_HEREMPN 0.001326\n", - "┃ othdiscr_HSENROLL 0.000025\n", - "┃ othdiscr_OTHEMPN 0.000044\n", - "┃ othdiscr_RETEMPN -0.000287\n", + "┃ othdiscr_HEREMPN 0.000065\n", + "┃ othdiscr_HSENROLL 0.000034\n", + "┃ othdiscr_OTHEMPN -0.000049\n", + "┃ othdiscr_RETEMPN 0.000009\n", "┃ othdiscr_TOTHH 0.000000\n", - "┃ othmaint_HEREMPN 0.000035\n", + "┃ othmaint_HEREMPN -0.000002\n", "┃ othmaint_RETEMPN 0.000000\n", "┃ shopping_RETEMPN 0.000000\n", - "┃ social_HEREMPN -0.000091\n", + "┃ social_HEREMPN -0.000084\n", "┃ social_RETEMPN 0.000000\n", "┃ dtype: float64\n", - "┣ nit: 29\n", - "┣ nfev: 79\n", - "┣ njev: 29\n", + "┣ nit: 46\n", + "┣ nfev: 46\n", + "┣ njev: 46\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=7, microseconds=87910)\n", - "┣ method: 'SLSQP'\n", - "┣ n_cases: 2581\n", - "┣ iteration_number: 29\n", - "┣ logloss: 5.140917935268784" + "┣ elapsed_time: datetime.timedelta(seconds=6, microseconds=714015)\n", + "┣ method: 'slsqp'\n", + "┣ n_cases: 30946\n", + "┣ iteration_number: 46\n", + "┣ loglike: -85747.12036028807" ] }, - "execution_count": 14, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.estimate(method='SLSQP')" + "model.estimate(maxiter=900)" ] }, { @@ -3233,309 +2924,333 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Null Value
-999-999. 0.00 NA-999.00
0 0.00 0.00 NA 0.00
1 1.00 0.00 NA 1.00
coef_eatout_dist_0_2-0.768 0.138-5.58*** 0.00
coef_eatout_dist_2_5-0.226 0.0689-3.29** 0.00
coef_eatout_dist_5_plus-0.188 0.105-1.80 0.00
coef_escort_dist_0_2 0.227 0.197 1.15 0.00
coef_escort_dist_2_5-0.813 0.0600-13.57*** 0.00
coef_escort_dist_5_plus-0.255 0.0751-3.39*** 0.00
coef_mode_logsum 0.663 0.0562 11.80*** 0.00
coef_othdiscr_dist_0_2-0.203 0.127-1.61 0.00
coef_othdiscr_dist_2_5-0.551 0.0530-10.39*** 0.00
coef_othdiscr_dist_5_plus-0.000141 0.0704-0.00 0.00
coef_othmaint_dist_2_5-0.580 0.0552-10.51*** 0.00
coef_othmaint_dist_5_plus-0.230 0.0903-2.54* 0.00
coef_shopping_dist_2_5-0.630 0.0445-14.16*** 0.00
coef_shopping_dist_5_plus-0.131 0.0623-2.10* 0.00
coef_social_dist_2_5-0.245 0.0817-3.00** 0.00
coef_social_dist_5_plus-0.190 0.129-1.48 0.00
eatout_HEREMPN-0.947 0.265-3.57*** 0.00
eatout_RETEMPN-0.298 0.00 NA 0.00
escort_AGE0519-1.17 0.413-2.84** 0.00
escort_HEREMPN-2.45 0.502-4.88*** 0.00
escort_HSENROLL-3.30 1.25-2.64** 0.00
escort_RETEMPN-1.49 0.00 NA 0.00
othdiscr_HEREMPN-1.58 0.284-5.58*** 0.00
othdiscr_HSENROLL-2.47 0.962-2.56* 0.00
othdiscr_OTHEMPN-2.37 0.595-3.98*** 0.00
othdiscr_RETEMPN-1.24 0.836-1.48 0.00
othdiscr_TOTHH-1.38 0.00 NA 0.00
othmaint_HEREMPN-0.669 0.275-2.44* 0.00
othmaint_RETEMPN-0.730 0.00 NA 0.00
shopping_RETEMPN 0.00 0.00 NA 0.00
social_HEREMPN-0.303 0.458-0.66 0.00
social_RETEMPN-0.650 0.00 NA 0.00
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 ValueStd Errt StatSignifNull Value
Parameter     
-999-999. 0.00 NA 0.00
0 0.00 0.00 NA 0.00
1 1.00 0.00 NA 0.00
coef_eatout_dist_0_2-0.960 0.0437-21.97*** 0.00
coef_eatout_dist_2_5-0.428 0.0207-20.70*** 0.00
coef_eatout_dist_5_plus-0.182 0.00484-37.68*** 0.00
coef_escort_dist_0_2-0.291 0.0329-8.85*** 0.00
coef_escort_dist_2_5-0.959 0.0161-59.53*** 0.00
coef_escort_dist_5_plus-0.265 0.00711-37.23*** 0.00
coef_mode_logsum 0.165 0.0124 13.36*** 0.00
coef_othdiscr_dist_0_2-0.424 0.0382-11.12*** 0.00
coef_othdiscr_dist_2_5-0.616 0.0146-42.26*** 0.00
coef_othdiscr_dist_5_plus-0.171 0.00349-49.12*** 0.00
coef_othmaint_dist_2_5-0.797 0.0158-50.41*** 0.00
coef_othmaint_dist_5_plus-0.157 0.00396-39.57*** 0.00
coef_shopping_dist_2_5-0.705 0.0120-58.52*** 0.00
coef_shopping_dist_5_plus-0.235 0.00446-52.69*** 0.00
coef_social_dist_2_5-0.464 0.0245-18.97*** 0.00
coef_social_dist_5_plus-0.176 0.00583-30.29*** 0.00
eatout_HEREMPN-1.60 0.0888-18.04*** 0.00
eatout_RETEMPN-0.298 0.00 NA 0.00
escort_AGE0519-0.766 0.185-4.15*** 0.00
escort_HEREMPN-2.00 0.229-8.71*** 0.00
escort_HSENROLL-1.87 0.200-9.36*** 0.00
escort_RETEMPN-1.49 0.00 NA 0.00
othdiscr_HEREMPN-1.34 0.0798-16.83*** 0.00
othdiscr_HSENROLL-2.29 0.182-12.56*** 0.00
othdiscr_OTHEMPN-1.91 0.128-14.93*** 0.00
othdiscr_RETEMPN-1.55 0.240-6.46*** 0.00
othdiscr_TOTHH-1.38 0.00 NA 0.00
othmaint_HEREMPN-0.689 0.0969-7.11*** 0.00
othmaint_RETEMPN-0.730 0.00 NA 0.00
shopping_RETEMPN 0.00 0.00 NA 0.00
social_HEREMPN-0.831 0.133-6.25*** 0.00
social_RETEMPN-0.650 0.00 NA 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 15, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -3556,7 +3271,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -3582,7 +3297,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -3591,7 +3306,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -3610,7 +3325,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -3767,14 +3482,14 @@ " escort\n", " non_mandatory\n", " 0.000000\n", - " 0.341950\n", + " 0.229722\n", " 0.000000\n", - " 0.131140\n", + " 0.138687\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", - " 0.471104\n", - " 0.055806\n", + " 0.474643\n", + " 0.156948\n", " 0.000000\n", " 0.000000\n", " \n", @@ -3799,9 +3514,9 @@ " eatout\n", " non_mandatory\n", " 0.000000\n", - " 0.656666\n", + " 0.786346\n", " 0.000000\n", - " 0.343334\n", + " 0.213654\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -3815,9 +3530,9 @@ " othmaint\n", " non_mandatory\n", " 0.000000\n", - " 0.484790\n", + " 0.489805\n", " 0.000000\n", - " 0.515210\n", + " 0.510195\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -3831,9 +3546,9 @@ " social\n", " non_mandatory\n", " 0.000000\n", - " 0.414051\n", + " 0.545121\n", " 0.000000\n", - " 0.585949\n", + " 0.454879\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -3846,15 +3561,15 @@ " 12\n", " othdiscr\n", " non_mandatory\n", - " 0.272379\n", - " 0.313357\n", + " 0.258275\n", + " 0.217495\n", " 0.000000\n", - " 0.221530\n", - " 0.101011\n", + " 0.267795\n", + " 0.152428\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", - " 0.091723\n", + " 0.104008\n", " 0.000000\n", " 0.000000\n", " \n", @@ -4015,12 +3730,12 @@ "4 university school 0.000000 0.000000 0.000000 0.000000 \n", "5 gradeschool school 0.000000 0.000000 0.000000 0.000000 \n", "6 highschool school 0.000000 0.000000 0.000000 0.000000 \n", - "7 escort non_mandatory 0.000000 0.341950 0.000000 0.131140 \n", + "7 escort non_mandatory 0.000000 0.229722 0.000000 0.138687 \n", "8 shopping non_mandatory 0.000000 1.000000 0.000000 0.000000 \n", - "9 eatout non_mandatory 0.000000 0.656666 0.000000 0.343334 \n", - "10 othmaint non_mandatory 0.000000 0.484790 0.000000 0.515210 \n", - "11 social non_mandatory 0.000000 0.414051 0.000000 0.585949 \n", - "12 othdiscr non_mandatory 0.272379 0.313357 0.000000 0.221530 \n", + "9 eatout non_mandatory 0.000000 0.786346 0.000000 0.213654 \n", + "10 othmaint non_mandatory 0.000000 0.489805 0.000000 0.510195 \n", + "11 social non_mandatory 0.000000 0.545121 0.000000 0.454879 \n", + "12 othdiscr non_mandatory 0.258275 0.217495 0.000000 0.267795 \n", "13 atwork atwork 0.000000 0.742000 0.000000 0.258000 \n", "14 work trip 0.000000 0.166667 0.166667 0.166667 \n", "15 escort trip 0.001000 0.225000 0.000000 0.144000 \n", @@ -4039,12 +3754,12 @@ "4 0.000000 0.000000 0.000000 0.000000 0.000000 0.592000 0.408000 \n", "5 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 \n", "6 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 \n", - "7 0.000000 0.000000 0.000000 0.471104 0.055806 0.000000 0.000000 \n", + "7 0.000000 0.000000 0.000000 0.474643 0.156948 0.000000 0.000000 \n", "8 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "9 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "10 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "11 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "12 0.101011 0.000000 0.000000 0.000000 0.091723 0.000000 0.000000 \n", + "12 0.152428 0.000000 0.000000 0.000000 0.104008 0.000000 0.000000 \n", "13 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "14 0.166667 0.166667 0.166667 0.000000 0.000000 0.000000 0.000000 \n", "15 0.000000 0.000000 0.000000 0.464000 0.166000 0.000000 0.000000 \n", @@ -4056,7 +3771,7 @@ "21 0.000000 0.000000 0.000000 0.000000 0.000000 0.591409 0.407592 " ] }, - "execution_count": 19, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -4085,7 +3800,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -4113,7 +3828,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -4146,19 +3861,19 @@ " \n", " 0\n", " coef_mode_logsum\n", - " 0.662937\n", + " 0.165346\n", " F\n", " \n", " \n", " 1\n", " coef_escort_dist_0_2\n", - " 0.226691\n", + " -0.290871\n", " F\n", " \n", " \n", " 2\n", " coef_eatout_dist_0_2\n", - " -0.767979\n", + " -0.959646\n", " F\n", " \n", " \n", @@ -4170,79 +3885,79 @@ " \n", " 4\n", " coef_othdiscr_dist_0_2\n", - " -0.203187\n", + " -0.424399\n", " F\n", " \n", " \n", " 5\n", " coef_escort_dist_2_5\n", - " -0.813494\n", + " -0.959038\n", " F\n", " \n", " \n", " 6\n", " coef_shopping_dist_2_5\n", - " -0.629792\n", + " -0.704553\n", " F\n", " \n", " \n", " 7\n", " coef_eatout_dist_2_5\n", - " -0.226448\n", + " -0.427890\n", " F\n", " \n", " \n", " 8\n", " coef_othmaint_dist_2_5\n", - " -0.579932\n", + " -0.796780\n", " F\n", " \n", " \n", " 9\n", " coef_social_dist_2_5\n", - " -0.245175\n", + " -0.464176\n", " F\n", " \n", " \n", " 10\n", " coef_othdiscr_dist_2_5\n", - " -0.550945\n", + " -0.615669\n", " F\n", " \n", " \n", " 11\n", " coef_escort_dist_5_plus\n", - " -0.255056\n", + " -0.264682\n", " F\n", " \n", " \n", " 12\n", " coef_shopping_dist_5_plus\n", - " -0.130649\n", + " -0.234821\n", " F\n", " \n", " \n", " 13\n", " coef_eatout_dist_5_plus\n", - " -0.188137\n", + " -0.182199\n", " F\n", " \n", " \n", " 14\n", " coef_othmaint_dist_5_plus\n", - " -0.229655\n", + " -0.156745\n", " F\n", " \n", " \n", " 15\n", " coef_social_dist_5_plus\n", - " -0.190239\n", + " -0.176446\n", " F\n", " \n", " \n", " 16\n", " coef_othdiscr_dist_5_plus\n", - " -0.000141\n", + " -0.171387\n", " F\n", " \n", " \n", @@ -4251,26 +3966,26 @@ ], "text/plain": [ " coefficient_name value constrain\n", - "0 coef_mode_logsum 0.662937 F\n", - "1 coef_escort_dist_0_2 0.226691 F\n", - "2 coef_eatout_dist_0_2 -0.767979 F\n", + "0 coef_mode_logsum 0.165346 F\n", + "1 coef_escort_dist_0_2 -0.290871 F\n", + "2 coef_eatout_dist_0_2 -0.959646 F\n", "3 coef_eatout_social_0_2 -0.560900 F\n", - "4 coef_othdiscr_dist_0_2 -0.203187 F\n", - "5 coef_escort_dist_2_5 -0.813494 F\n", - "6 coef_shopping_dist_2_5 -0.629792 F\n", - "7 coef_eatout_dist_2_5 -0.226448 F\n", - "8 coef_othmaint_dist_2_5 -0.579932 F\n", - "9 coef_social_dist_2_5 -0.245175 F\n", - "10 coef_othdiscr_dist_2_5 -0.550945 F\n", - "11 coef_escort_dist_5_plus -0.255056 F\n", - "12 coef_shopping_dist_5_plus -0.130649 F\n", - "13 coef_eatout_dist_5_plus -0.188137 F\n", - "14 coef_othmaint_dist_5_plus -0.229655 F\n", - "15 coef_social_dist_5_plus -0.190239 F\n", - "16 coef_othdiscr_dist_5_plus -0.000141 F" + "4 coef_othdiscr_dist_0_2 -0.424399 F\n", + "5 coef_escort_dist_2_5 -0.959038 F\n", + "6 coef_shopping_dist_2_5 -0.704553 F\n", + "7 coef_eatout_dist_2_5 -0.427890 F\n", + "8 coef_othmaint_dist_2_5 -0.796780 F\n", + "9 coef_social_dist_2_5 -0.464176 F\n", + "10 coef_othdiscr_dist_2_5 -0.615669 F\n", + "11 coef_escort_dist_5_plus -0.264682 F\n", + "12 coef_shopping_dist_5_plus -0.234821 F\n", + "13 coef_eatout_dist_5_plus -0.182199 F\n", + "14 coef_othmaint_dist_5_plus -0.156745 F\n", + "15 coef_social_dist_5_plus -0.176446 F\n", + "16 coef_othdiscr_dist_5_plus -0.171387 F" ] }, - "execution_count": 21, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -4281,7 +3996,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -4447,14 +4162,14 @@ " escort\n", " non_mandatory\n", " 0.000000\n", - " 0.341950\n", + " 0.229722\n", " 0.000000\n", - " 0.131140\n", + " 0.138687\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", - " 0.471104\n", - " 0.055806\n", + " 0.474643\n", + " 0.156948\n", " 0.000000\n", " 0.000000\n", " \n", @@ -4481,9 +4196,9 @@ " eatout\n", " non_mandatory\n", " 0.000000\n", - " 0.656666\n", + " 0.786346\n", " 0.000000\n", - " 0.343334\n", + " 0.213654\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4498,9 +4213,9 @@ " othmaint\n", " non_mandatory\n", " 0.000000\n", - " 0.484790\n", + " 0.489805\n", " 0.000000\n", - " 0.515210\n", + " 0.510195\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4515,9 +4230,9 @@ " social\n", " non_mandatory\n", " 0.000000\n", - " 0.414051\n", + " 0.545121\n", " 0.000000\n", - " 0.585949\n", + " 0.454879\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4531,15 +4246,15 @@ " 12\n", " othdiscr\n", " non_mandatory\n", - " 0.272379\n", - " 0.313357\n", + " 0.258275\n", + " 0.217495\n", " 0.000000\n", - " 0.221530\n", - " 0.101011\n", + " 0.267795\n", + " 0.152428\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", - " 0.091723\n", + " 0.104008\n", " 0.000000\n", " 0.000000\n", " \n", @@ -4709,12 +4424,12 @@ "4 4 university school 0.000000 0.000000 0.000000 \n", "5 5 gradeschool school 0.000000 0.000000 0.000000 \n", "6 6 highschool school 0.000000 0.000000 0.000000 \n", - "7 7 escort non_mandatory 0.000000 0.341950 0.000000 \n", + "7 7 escort non_mandatory 0.000000 0.229722 0.000000 \n", "8 8 shopping non_mandatory 0.000000 1.000000 0.000000 \n", - "9 9 eatout non_mandatory 0.000000 0.656666 0.000000 \n", - "10 10 othmaint non_mandatory 0.000000 0.484790 0.000000 \n", - "11 11 social non_mandatory 0.000000 0.414051 0.000000 \n", - "12 12 othdiscr non_mandatory 0.272379 0.313357 0.000000 \n", + "9 9 eatout non_mandatory 0.000000 0.786346 0.000000 \n", + "10 10 othmaint non_mandatory 0.000000 0.489805 0.000000 \n", + "11 11 social non_mandatory 0.000000 0.545121 0.000000 \n", + "12 12 othdiscr non_mandatory 0.258275 0.217495 0.000000 \n", "13 13 atwork atwork 0.000000 0.742000 0.000000 \n", "14 14 work trip 0.000000 0.166667 0.166667 \n", "15 15 escort trip 0.001000 0.225000 0.000000 \n", @@ -4733,12 +4448,12 @@ "4 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.592000 \n", "5 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 \n", "6 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 \n", - "7 0.131140 0.000000 0.000000 0.000000 0.471104 0.055806 0.000000 \n", + "7 0.138687 0.000000 0.000000 0.000000 0.474643 0.156948 0.000000 \n", "8 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "9 0.343334 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "10 0.515210 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "11 0.585949 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "12 0.221530 0.101011 0.000000 0.000000 0.000000 0.091723 0.000000 \n", + "9 0.213654 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "10 0.510195 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "11 0.454879 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "12 0.267795 0.152428 0.000000 0.000000 0.000000 0.104008 0.000000 \n", "13 0.258000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "14 0.166667 0.166667 0.166667 0.166667 0.000000 0.000000 0.000000 \n", "15 0.144000 0.000000 0.000000 0.000000 0.464000 0.166000 0.000000 \n", @@ -4774,7 +4489,7 @@ "21 0.407592 " ] }, - "execution_count": 22, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -4791,7 +4506,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -4805,7 +4520,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/14_joint_tour_scheduling.ipynb b/activitysim/examples/example_estimation/notebooks/14_joint_tour_scheduling.ipynb index c2973c29b1..b05d68490e 100644 --- a/activitysim/examples/example_estimation/notebooks/14_joint_tour_scheduling.ipynb +++ b/activitysim/examples/example_estimation/notebooks/14_joint_tour_scheduling.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +115,28 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/joint_tour_scheduling/tour_scheduling_joint_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_scheduling/joint_tour_scheduling_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_scheduling/joint_tour_scheduling_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/joint_tour_scheduling/joint_tour_scheduling_choosers_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"joint_tour_scheduling\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -746,28 +809,28 @@ " 30\n", " util_adjacent_window_exists_before_this_depart...\n", " Adjacent window exists before this departure h...\n", - " @(df.tour_type_count>1) & (df.tour_type_num ==...\n", + " @(df.tour_type_count>1) * (df.tour_type_num ==...\n", " coef_adjacent_window_exists_before_this_depart...\n", " \n", " \n", " 31\n", " util_adjacent_window_exists_after_this_arrival...\n", " Adjacent window exists after this arrival hour...\n", - " @(df.tour_type_count>1) & (df.tour_type_num ==...\n", + " @(df.tour_type_count>1) * (df.tour_type_num ==...\n", " coef_adjacent_window_exists_after_this_arrival...\n", " \n", " \n", " 32\n", " util_adjacent_window_exists_before_this_depart...\n", " Adjacent window exists before this departure h...\n", - " @(df.tour_type_num > 1) & _adjacent_window_before\n", + " @(df.tour_type_num > 1) * _adjacent_window_before\n", " coef_adjacent_window_exists_before_this_depart...\n", " \n", " \n", " 33\n", " util_adjacent_window_exists_after_this_arrival...\n", " Adjacent window exists after this arrival hour...\n", - " @(df.tour_type_num > 1) & _adjacent_window_after\n", + " @(df.tour_type_num > 1) * _adjacent_window_after\n", " coef_adjacent_window_exists_after_this_arrival...\n", " \n", " \n", @@ -1115,10 +1178,10 @@ "25 adult & (num_children > 0) & ( end > 18 ) & ( ... \n", "28 @tt.previous_tour_ends(df.tour_id, df.start) \n", "29 @tt.previous_tour_begins(df.tour_id, df.end) \n", - "30 @(df.tour_type_count>1) & (df.tour_type_num ==... \n", - "31 @(df.tour_type_count>1) & (df.tour_type_num ==... \n", - "32 @(df.tour_type_num > 1) & _adjacent_window_before \n", - "33 @(df.tour_type_num > 1) & _adjacent_window_after \n", + "30 @(df.tour_type_count>1) * (df.tour_type_num ==... \n", + "31 @(df.tour_type_count>1) * (df.tour_type_num ==... \n", + "32 @(df.tour_type_num > 1) * _adjacent_window_before \n", + "33 @(df.tour_type_num > 1) * _adjacent_window_after \n", "34 (tour_type != 'escort') & (start < 6) \n", "35 (tour_type != 'escort') & (start == 6) \n", "36 (tour_type != 'escort') & (start == 7) \n", @@ -1262,14 +1325,14 @@ " tour_count\n", " tour_category\n", " ...\n", - " COLLPTE\n", - " TOPOLOGY\n", - " TERMINAL\n", - " household_density\n", - " employment_density\n", - " density_index\n", - " is_cbd\n", - " tour_id.1\n", + " auOpRetail\n", + " auOpTotal\n", + " trPkRetail\n", + " trPkTotal\n", + " trOpRetail\n", + " trOpTotal\n", + " nmRetail\n", + " nmTotal\n", " start_previous\n", " end_previous\n", " \n", @@ -1277,10 +1340,10 @@ " \n", " \n", " 0\n", - " 7785298\n", - " 146\n", - " 146\n", - " 189885\n", + " 7853686\n", + " 115\n", + " 104\n", + " 191553\n", " eatout\n", " 1\n", " 1\n", @@ -1288,47 +1351,47 @@ " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 1\n", - " 2.94885\n", - " 23.215385\n", - " 11.646154\n", - " 7.755537\n", - " False\n", - " 7785298\n", + " 10.032432\n", + " 12.426053\n", + " 4.842958\n", + " 6.577576\n", + " 4.825284\n", + " 6.554185\n", + " 5.384032\n", + " 6.267720\n", " 5\n", " 5\n", " \n", " \n", " 1\n", - " 8708454\n", - " 145\n", - " 145\n", - " 212401\n", - " eatout\n", + " 7902318\n", + " 127\n", + " 91\n", + " 192739\n", + " shopping\n", " 1\n", " 1\n", " 1\n", " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 2\n", - " 4.64648\n", - " 196.395950\n", - " 178.779465\n", - " 93.587057\n", - " False\n", - " 8708454\n", + " 9.804714\n", + " 12.378032\n", + " 2.085722\n", + " 3.940109\n", + " 2.097132\n", + " 3.946235\n", + " 4.015752\n", + " 6.526846\n", " 5\n", " 5\n", " \n", " \n", " 2\n", - " 9715006\n", - " 115\n", - " 115\n", - " 236951\n", + " 7909776\n", + " 90\n", + " 105\n", + " 192921\n", " othdiscr\n", " 1\n", " 1\n", @@ -1336,62 +1399,62 @@ " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 1\n", - " 2.08699\n", - " 16.952703\n", - " 7.608108\n", - " 5.251374\n", - " False\n", - " 9715006\n", + " 9.924635\n", + " 12.521312\n", + " 1.451325\n", + " 3.811134\n", + " 1.458624\n", + " 3.813040\n", + " 4.422027\n", + " 6.644415\n", " 5\n", " 5\n", " \n", " \n", " 3\n", - " 10831112\n", - " 115\n", - " 115\n", - " 264173\n", - " shopping\n", + " 7988742\n", + " 101\n", + " 101\n", + " 194847\n", + " othdiscr\n", " 1\n", " 1\n", " 1\n", " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 3\n", - " 4.73802\n", - " 117.769796\n", - " 246.205869\n", - " 79.663609\n", - " False\n", - " 10831112\n", + " 10.124314\n", + " 12.525120\n", + " 2.760744\n", + " 4.989736\n", + " 2.749302\n", + " 4.964188\n", + " 4.106787\n", + " 6.259962\n", " 5\n", " 5\n", " \n", " \n", " 4\n", - " 20334787\n", - " 37\n", - " 37\n", - " 495970\n", - " othmaint\n", + " 8103874\n", + " 74\n", + " 74\n", + " 197655\n", + " shopping\n", " 1\n", " 1\n", " 1\n", " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 1\n", - " 2.17734\n", - " 17.968750\n", - " 4.109375\n", - " 3.344502\n", - " False\n", - " 20334787\n", + " 9.966499\n", + " 12.292832\n", + " 2.097899\n", + " 4.282017\n", + " 0.920538\n", + " 2.790691\n", + " 5.043413\n", + " 6.194205\n", " 5\n", " 5\n", " \n", @@ -1420,35 +1483,35 @@ " ...\n", " \n", " \n", - " 86\n", - " 283676518\n", - " 145\n", - " 145\n", - " 6918939\n", - " shopping\n", + " 1272\n", + " 303771147\n", + " 171\n", + " 171\n", + " 7409052\n", + " othdiscr\n", " 1\n", " 1\n", " 1\n", " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 1\n", - " 2.18894\n", - " 20.746032\n", - " 9.793651\n", - " 6.652963\n", - " False\n", - " 283676518\n", + " 9.795165\n", + " 12.124129\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 4.666818\n", + " 6.381846\n", " 5\n", " 5\n", " \n", " \n", - " 87\n", - " 295260168\n", - " 158\n", - " 158\n", - " 7201469\n", + " 1273\n", + " 304144212\n", + " 77\n", + " 126\n", + " 7418154\n", " social\n", " 1\n", " 1\n", @@ -1456,23 +1519,23 @@ " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 1\n", - " 3.19780\n", - " 25.035085\n", - " 34.002224\n", - " 14.418824\n", - " False\n", - " 295260168\n", + " 9.808362\n", + " 12.224503\n", + " 0.198489\n", + " 0.838468\n", + " 0.197857\n", + " 0.826233\n", + " 5.214767\n", + " 7.781673\n", " 5\n", " 5\n", " \n", " \n", - " 88\n", - " 297646485\n", - " 104\n", - " 104\n", - " 7259670\n", + " 1274\n", + " 304463637\n", + " 138\n", + " 127\n", + " 7425942\n", " othdiscr\n", " 1\n", " 1\n", @@ -1480,124 +1543,124 @@ " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 1\n", - " 4.89113\n", - " 193.875000\n", - " 201.000000\n", - " 98.686610\n", - " False\n", - " 297646485\n", + " 9.674598\n", + " 12.273909\n", + " 2.314454\n", + " 5.062339\n", + " 2.170577\n", + " 4.928170\n", + " 3.927607\n", + " 5.937753\n", " 5\n", " 5\n", " \n", " \n", - " 89\n", - " 298814741\n", - " 74\n", - " 74\n", - " 7288164\n", - " othmaint\n", + " 1275\n", + " 305125582\n", + " 156\n", + " 177\n", + " 7442087\n", + " othdiscr\n", " 1\n", " 1\n", " 1\n", " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 1\n", - " 4.29646\n", - " 57.195122\n", - " 95.975610\n", - " 35.838026\n", - " True\n", - " 298814741\n", + " 10.150831\n", + " 12.839956\n", + " 6.746949\n", + " 9.644580\n", + " 6.245710\n", + " 8.925880\n", + " 6.393693\n", + " 8.676755\n", " 5\n", " 5\n", " \n", " \n", - " 90\n", - " 301810980\n", + " 1276\n", + " 305246245\n", " 54\n", " 54\n", - " 7361244\n", - " othmaint\n", + " 7445030\n", + " othdiscr\n", " 1\n", " 1\n", " 1\n", " 1\n", " joint\n", " ...\n", - " 0.0\n", - " 1\n", - " 2.47787\n", - " 23.993197\n", - " 11.945578\n", - " 7.975024\n", - " False\n", - " 301810980\n", + " 10.154352\n", + " 12.772396\n", + " 5.492171\n", + " 8.363419\n", + " 5.092918\n", + " 7.921567\n", + " 4.507081\n", + " 7.061687\n", " 5\n", " 5\n", " \n", " \n", "\n", - "

91 rows × 151 columns

\n", + "

1277 rows × 150 columns

\n", "" ], "text/plain": [ - " tour_id model_choice override_choice person_id tour_type \\\n", - "0 7785298 146 146 189885 eatout \n", - "1 8708454 145 145 212401 eatout \n", - "2 9715006 115 115 236951 othdiscr \n", - "3 10831112 115 115 264173 shopping \n", - "4 20334787 37 37 495970 othmaint \n", - ".. ... ... ... ... ... \n", - "86 283676518 145 145 6918939 shopping \n", - "87 295260168 158 158 7201469 social \n", - "88 297646485 104 104 7259670 othdiscr \n", - "89 298814741 74 74 7288164 othmaint \n", - "90 301810980 54 54 7361244 othmaint \n", + " tour_id model_choice override_choice person_id tour_type \\\n", + "0 7853686 115 104 191553 eatout \n", + "1 7902318 127 91 192739 shopping \n", + "2 7909776 90 105 192921 othdiscr \n", + "3 7988742 101 101 194847 othdiscr \n", + "4 8103874 74 74 197655 shopping \n", + "... ... ... ... ... ... \n", + "1272 303771147 171 171 7409052 othdiscr \n", + "1273 304144212 77 126 7418154 social \n", + "1274 304463637 138 127 7425942 othdiscr \n", + "1275 305125582 156 177 7442087 othdiscr \n", + "1276 305246245 54 54 7445030 othdiscr \n", "\n", - " tour_type_count tour_type_num tour_num tour_count tour_category ... \\\n", - "0 1 1 1 1 joint ... \n", - "1 1 1 1 1 joint ... \n", - "2 1 1 1 1 joint ... \n", - "3 1 1 1 1 joint ... \n", - "4 1 1 1 1 joint ... \n", - ".. ... ... ... ... ... ... \n", - "86 1 1 1 1 joint ... \n", - "87 1 1 1 1 joint ... \n", - "88 1 1 1 1 joint ... \n", - "89 1 1 1 1 joint ... \n", - "90 1 1 1 1 joint ... \n", + " tour_type_count tour_type_num tour_num tour_count tour_category ... \\\n", + "0 1 1 1 1 joint ... \n", + "1 1 1 1 1 joint ... \n", + "2 1 1 1 1 joint ... \n", + "3 1 1 1 1 joint ... \n", + "4 1 1 1 1 joint ... \n", + "... ... ... ... ... ... ... \n", + "1272 1 1 1 1 joint ... \n", + "1273 1 1 1 1 joint ... \n", + "1274 1 1 1 1 joint ... \n", + "1275 1 1 1 1 joint ... \n", + "1276 1 1 1 1 joint ... \n", "\n", - " COLLPTE TOPOLOGY TERMINAL household_density employment_density \\\n", - "0 0.0 1 2.94885 23.215385 11.646154 \n", - "1 0.0 2 4.64648 196.395950 178.779465 \n", - "2 0.0 1 2.08699 16.952703 7.608108 \n", - "3 0.0 3 4.73802 117.769796 246.205869 \n", - "4 0.0 1 2.17734 17.968750 4.109375 \n", - ".. ... ... ... ... ... \n", - "86 0.0 1 2.18894 20.746032 9.793651 \n", - "87 0.0 1 3.19780 25.035085 34.002224 \n", - "88 0.0 1 4.89113 193.875000 201.000000 \n", - "89 0.0 1 4.29646 57.195122 95.975610 \n", - "90 0.0 1 2.47787 23.993197 11.945578 \n", + " auOpRetail auOpTotal trPkRetail trPkTotal trOpRetail trOpTotal \\\n", + "0 10.032432 12.426053 4.842958 6.577576 4.825284 6.554185 \n", + "1 9.804714 12.378032 2.085722 3.940109 2.097132 3.946235 \n", + "2 9.924635 12.521312 1.451325 3.811134 1.458624 3.813040 \n", + "3 10.124314 12.525120 2.760744 4.989736 2.749302 4.964188 \n", + "4 9.966499 12.292832 2.097899 4.282017 0.920538 2.790691 \n", + "... ... ... ... ... ... ... \n", + "1272 9.795165 12.124129 0.000000 0.000000 0.000000 0.000000 \n", + "1273 9.808362 12.224503 0.198489 0.838468 0.197857 0.826233 \n", + "1274 9.674598 12.273909 2.314454 5.062339 2.170577 4.928170 \n", + "1275 10.150831 12.839956 6.746949 9.644580 6.245710 8.925880 \n", + "1276 10.154352 12.772396 5.492171 8.363419 5.092918 7.921567 \n", "\n", - " density_index is_cbd tour_id.1 start_previous end_previous \n", - "0 7.755537 False 7785298 5 5 \n", - "1 93.587057 False 8708454 5 5 \n", - "2 5.251374 False 9715006 5 5 \n", - "3 79.663609 False 10831112 5 5 \n", - "4 3.344502 False 20334787 5 5 \n", - ".. ... ... ... ... ... \n", - "86 6.652963 False 283676518 5 5 \n", - "87 14.418824 False 295260168 5 5 \n", - "88 98.686610 False 297646485 5 5 \n", - "89 35.838026 True 298814741 5 5 \n", - "90 7.975024 False 301810980 5 5 \n", + " nmRetail nmTotal start_previous end_previous \n", + "0 5.384032 6.267720 5 5 \n", + "1 4.015752 6.526846 5 5 \n", + "2 4.422027 6.644415 5 5 \n", + "3 4.106787 6.259962 5 5 \n", + "4 5.043413 6.194205 5 5 \n", + "... ... ... ... ... \n", + "1272 4.666818 6.381846 5 5 \n", + "1273 5.214767 7.781673 5 5 \n", + "1274 3.927607 5.937753 5 5 \n", + "1275 6.393693 8.676755 5 5 \n", + "1276 4.507081 7.061687 5 5 \n", "\n", - "[91 rows x 151 columns]" + "[1277 rows x 150 columns]" ] }, "execution_count": 6, @@ -1643,135 +1706,135 @@ " \n", " \n", " tour_id\n", - " variable\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", + " start\n", + " end\n", + " duration\n", + " tdd\n", + " mode_choice_logsum\n", + " util_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends\n", + " util_free_flow_round_trip_auto_time_shift_effects_duration\n", + " util_shopping_tour_departure_shift_effects\n", + " util_shopping_tour_duration_shift_effects\n", " ...\n", - " 180\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", + " util_arrival_constants_pm_peak_4\n", + " util_arrival_constants_evening\n", + " util_arrival_constants_late\n", + " util_duration_constants_0_to_1_hours\n", + " util_duration_constants_2_to_3_hours\n", + " util_duration_constants_4_to_5_hours\n", + " util_duration_constants_6_to_7_hours\n", + " util_duration_constants_8_to_10_hours\n", + " util_duration_constants_11_to_13_hours\n", + " util_duration_constants_14_to_18_hours\n", " \n", " \n", " \n", " \n", " 0\n", - " 7785298\n", - " duration\n", - " 0.0\n", - " 1.0\n", - " 2.0\n", + " 7853686\n", + " 5\n", + " 5\n", " 0\n", " 0\n", " 0\n", + " False\n", + " 0.000000\n", " 0\n", " 0\n", " ...\n", - " 0.0\n", - " 1.0\n", - " 2.0\n", - " 3.0\n", - " 0.0\n", - " 1.0\n", - " 2.0\n", - " 0.0\n", - " 1.0\n", - " 0.0\n", + " False\n", + " False\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 1\n", - " 7785298\n", - " end\n", - " 5.0\n", - " 6.0\n", - " 7.0\n", - " 0\n", - " 0\n", + " 7853686\n", + " 5\n", + " 6\n", + " 1\n", + " 1\n", " 0\n", + " False\n", + " 24.259998\n", " 0\n", " 0\n", " ...\n", - " 20.0\n", - " 21.0\n", - " 22.0\n", - " 23.0\n", - " 21.0\n", - " 22.0\n", - " 23.0\n", - " 22.0\n", - " 23.0\n", - " 23.0\n", + " False\n", + " False\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 2\n", - " 7785298\n", - " mode_choice_logsum\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0\n", - " 0\n", + " 7853686\n", + " 5\n", + " 7\n", + " 2\n", + " 2\n", " 0\n", + " False\n", + " 48.519997\n", " 0\n", " 0\n", " ...\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 3\n", - " 7785298\n", - " start\n", - " 5.0\n", - " 5.0\n", - " 5.0\n", - " 0\n", - " 0\n", + " 7853686\n", + " 5\n", + " 8\n", + " 3\n", + " 3\n", " 0\n", + " False\n", + " 72.779999\n", " 0\n", " 0\n", " ...\n", - " 20.0\n", - " 20.0\n", - " 20.0\n", - " 20.0\n", - " 21.0\n", - " 21.0\n", - " 21.0\n", - " 22.0\n", - " 22.0\n", - " 23.0\n", - " \n", - " \n", - " 4\n", - " 7785298\n", - " util_adjacent_window_exists_after_this_arrival...\n", " False\n", " False\n", " False\n", + " False\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " \n", + " \n", + " 4\n", + " 7853686\n", + " 5\n", + " 9\n", + " 4\n", + " 4\n", " 0\n", - " 0\n", - " 0\n", + " False\n", + " 97.039993\n", " 0\n", " 0\n", " ...\n", @@ -1780,7 +1843,7 @@ " False\n", " False\n", " False\n", - " False\n", + " True\n", " False\n", " False\n", " False\n", @@ -1811,47 +1874,47 @@ " ...\n", " \n", " \n", - " 5728\n", - " 301810980\n", - " util_subsequent_of_2_plus_tours_for_same_purpo...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 107101\n", + " 305246245\n", + " 21\n", + " 22\n", + " 1\n", + " 185\n", " 0\n", + " False\n", + " 2.480000\n", " 0\n", " 0\n", " ...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " \n", - " \n", - " 5729\n", - " 301810980\n", - " util_subsequent_tour_must_start_after_previous...\n", + " False\n", + " False\n", + " True\n", + " True\n", " False\n", " False\n", " False\n", " False\n", + " False\n", + " False\n", + " \n", + " \n", + " 107102\n", + " 305246245\n", + " 21\n", + " 23\n", + " 2\n", + " 186\n", " 0\n", - " 0\n", + " False\n", + " 4.960000\n", " 0\n", " 0\n", " ...\n", " False\n", " False\n", + " True\n", " False\n", - " False\n", - " False\n", + " True\n", " False\n", " False\n", " False\n", @@ -1859,22 +1922,22 @@ " False\n", " \n", " \n", - " 5730\n", - " 301810980\n", - " util_university_student_arrive_after_22\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 107103\n", + " 305246245\n", + " 22\n", + " 22\n", " 0\n", + " 187\n", " 0\n", + " False\n", + " 0.000000\n", " 0\n", " 0\n", " ...\n", " False\n", " False\n", - " False\n", - " False\n", + " True\n", + " True\n", " False\n", " False\n", " False\n", @@ -1883,99 +1946,229 @@ " False\n", " \n", " \n", - " 5731\n", - " 301810980\n", - " util_visit_tour_departure_shift_effects\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 107104\n", + " 305246245\n", + " 22\n", + " 23\n", + " 1\n", + " 188\n", " 0\n", + " False\n", + " 2.480000\n", " 0\n", " 0\n", " ...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " True\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", - " 5732\n", - " 301810980\n", - " util_visit_tour_duration_shift_effects\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 107105\n", + " 305246245\n", + " 23\n", + " 23\n", " 0\n", + " 189\n", " 0\n", + " False\n", + " 0.000000\n", " 0\n", " 0\n", " ...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " True\n", + " True\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", "\n", - "

5733 rows × 192 columns

\n", + "

107106 rows × 65 columns

\n", "" ], "text/plain": [ - " tour_id variable 0 \\\n", - "0 7785298 duration 0.0 \n", - "1 7785298 end 5.0 \n", - "2 7785298 mode_choice_logsum 0.0 \n", - "3 7785298 start 5.0 \n", - "4 7785298 util_adjacent_window_exists_after_this_arrival... False \n", - "... ... ... ... \n", - "5728 301810980 util_subsequent_of_2_plus_tours_for_same_purpo... 0 \n", - "5729 301810980 util_subsequent_tour_must_start_after_previous... False \n", - "5730 301810980 util_university_student_arrive_after_22 False \n", - "5731 301810980 util_visit_tour_departure_shift_effects 0 \n", - "5732 301810980 util_visit_tour_duration_shift_effects 0 \n", + " tour_id start end duration tdd mode_choice_logsum \\\n", + "0 7853686 5 5 0 0 0 \n", + "1 7853686 5 6 1 1 0 \n", + "2 7853686 5 7 2 2 0 \n", + "3 7853686 5 8 3 3 0 \n", + "4 7853686 5 9 4 4 0 \n", + "... ... ... ... ... ... ... \n", + "107101 305246245 21 22 1 185 0 \n", + "107102 305246245 21 23 2 186 0 \n", + "107103 305246245 22 22 0 187 0 \n", + "107104 305246245 22 23 1 188 0 \n", + "107105 305246245 23 23 0 189 0 \n", + "\n", + " util_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "107101 False \n", + "107102 False \n", + "107103 False \n", + "107104 False \n", + "107105 False \n", + "\n", + " util_free_flow_round_trip_auto_time_shift_effects_duration \\\n", + "0 0.000000 \n", + "1 24.259998 \n", + "2 48.519997 \n", + "3 72.779999 \n", + "4 97.039993 \n", + "... ... \n", + "107101 2.480000 \n", + "107102 4.960000 \n", + "107103 0.000000 \n", + "107104 2.480000 \n", + "107105 0.000000 \n", + "\n", + " util_shopping_tour_departure_shift_effects \\\n", + "0 0 \n", + "1 0 \n", + "2 0 \n", + "3 0 \n", + "4 0 \n", + "... ... \n", + "107101 0 \n", + "107102 0 \n", + "107103 0 \n", + "107104 0 \n", + "107105 0 \n", + "\n", + " util_shopping_tour_duration_shift_effects ... \\\n", + "0 0 ... \n", + "1 0 ... \n", + "2 0 ... \n", + "3 0 ... \n", + "4 0 ... \n", + "... ... ... \n", + "107101 0 ... \n", + "107102 0 ... \n", + "107103 0 ... \n", + "107104 0 ... \n", + "107105 0 ... \n", + "\n", + " util_arrival_constants_pm_peak_4 util_arrival_constants_evening \\\n", + "0 False False \n", + "1 False False \n", + "2 False False \n", + "3 False False \n", + "4 False False \n", + "... ... ... \n", + "107101 False False \n", + "107102 False False \n", + "107103 False False \n", + "107104 False False \n", + "107105 False False \n", + "\n", + " util_arrival_constants_late util_duration_constants_0_to_1_hours \\\n", + "0 False True \n", + "1 False True \n", + "2 False False \n", + "3 False False \n", + "4 False False \n", + "... ... ... \n", + "107101 True True \n", + "107102 True False \n", + "107103 True True \n", + "107104 True True \n", + "107105 True True \n", + "\n", + " util_duration_constants_2_to_3_hours \\\n", + "0 False \n", + "1 False \n", + "2 True \n", + "3 True \n", + "4 False \n", + "... ... \n", + "107101 False \n", + "107102 True \n", + "107103 False \n", + "107104 False \n", + "107105 False \n", "\n", - " 1 2 3 4 5 6 7 ... 180 181 182 183 184 \\\n", - "0 1.0 2.0 0 0 0 0 0 ... 0.0 1.0 2.0 3.0 0.0 \n", - "1 6.0 7.0 0 0 0 0 0 ... 20.0 21.0 22.0 23.0 21.0 \n", - "2 0.0 0.0 0 0 0 0 0 ... 0.0 0.0 0.0 0.0 0.0 \n", - "3 5.0 5.0 0 0 0 0 0 ... 20.0 20.0 20.0 20.0 21.0 \n", - "4 False False 0 0 0 0 0 ... False False False False False \n", - "... ... ... ... .. .. .. .. ... ... ... ... ... ... \n", - "5728 0 0 0 0 0 0 0 ... 0 0 0 0 0 \n", - "5729 False False False 0 0 0 0 ... False False False False False \n", - "5730 False False False 0 0 0 0 ... False False False False False \n", - "5731 0 0 0 0 0 0 0 ... 0 0 0 0 0 \n", - "5732 0 0 0 0 0 0 0 ... 0 0 0 0 0 \n", + " util_duration_constants_4_to_5_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 True \n", + "... ... \n", + "107101 False \n", + "107102 False \n", + "107103 False \n", + "107104 False \n", + "107105 False \n", "\n", - " 185 186 187 188 189 \n", - "0 1.0 2.0 0.0 1.0 0.0 \n", - "1 22.0 23.0 22.0 23.0 23.0 \n", - "2 0.0 0.0 0.0 0.0 0.0 \n", - "3 21.0 21.0 22.0 22.0 23.0 \n", - "4 False False False False False \n", - "... ... ... ... ... ... \n", - "5728 0 0 0 0 0 \n", - "5729 False False False False False \n", - "5730 False False False False False \n", - "5731 0 0 0 0 0 \n", - "5732 0 0 0 0 0 \n", + " util_duration_constants_6_to_7_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "107101 False \n", + "107102 False \n", + "107103 False \n", + "107104 False \n", + "107105 False \n", "\n", - "[5733 rows x 192 columns]" + " util_duration_constants_8_to_10_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "107101 False \n", + "107102 False \n", + "107103 False \n", + "107104 False \n", + "107105 False \n", + "\n", + " util_duration_constants_11_to_13_hours \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "107101 False \n", + "107102 False \n", + "107103 False \n", + "107104 False \n", + "107105 False \n", + "\n", + " util_duration_constants_14_to_18_hours \n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "107101 False \n", + "107102 False \n", + "107103 False \n", + "107104 False \n", + "107105 False \n", + "\n", + "[107106 rows x 65 columns]" ] }, "execution_count": 7, @@ -2005,13 +2198,36 @@ "name": "stderr", "output_type": "stream", "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "problem: chosen_but_not_available has (2 issues)\n" ] }, + { + "data": { + "text/plain": [ + "(,\n", + " ┣ chosen_but_not_available: altid n example rows\n", + " ┃ 0 115 1 356\n", + " ┃ 1 149 2 732, 1183)" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.doctor(repair_ch_av=\"-\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ { "data": { "text/html": [ - "

Iteration 067 [Optimization terminated successfully]

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Iteration 144 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -2023,7 +2239,7 @@ { "data": { "text/html": [ - "

Best LL = -173.82837615906058

" + "

Best LL = -2789.512559021124

" ], "text/plain": [ "" @@ -2054,913 +2270,867 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction\n", - " -13.526580\n", + " 0.800851\n", + " 0.800851\n", " -0.025700\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -13.526580\n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction\n", - " -14.169341\n", + " 0.494438\n", + " 0.494438\n", " -0.027340\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -14.169341\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction\n", - " -13.495922\n", + " 0.008839\n", + " 0.008839\n", " 0.008442\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -13.495922\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction\n", - " -7.716247\n", + " -0.549692\n", + " -0.549692\n", " -0.059300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -7.716247\n", " \n", " \n", " coef_adult_with_children_in_hh_arrive_19_21\n", - " -0.002541\n", + " -0.078997\n", + " -0.078997\n", " 0.336000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.002541\n", " \n", " \n", " coef_arrival_constants_am_peak\n", - " 4.647673\n", + " -8.413713\n", + " -8.413713\n", " -8.728880\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 4.647673\n", " \n", " \n", " coef_arrival_constants_early\n", - " 24.793142\n", + " -6.758955\n", + " -6.758955\n", " -8.728880\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 24.793142\n", " \n", " \n", " coef_arrival_constants_evening\n", - " -4.291783\n", + " -2.675953\n", + " -2.675953\n", " -2.748940\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -4.291783\n", " \n", " \n", " coef_arrival_constants_late\n", - " -9.617038\n", + " -4.194942\n", + " -4.194942\n", " -4.242530\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -9.617038\n", " \n", " \n", " coef_arrival_constants_midday_1\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_arrival_constants_midday_2\n", - " 2.692519\n", + " 1.416723\n", + " 1.416723\n", " 1.408040\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 2.692519\n", " \n", " \n", " coef_arrival_constants_pm_peak_1\n", - " 1.849237\n", + " 0.964024\n", + " 0.964024\n", " 1.020360\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 1.849237\n", " \n", " \n", " coef_arrival_constants_pm_peak_2\n", - " 1.518410\n", + " 1.200835\n", + " 1.200835\n", " 1.068630\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 1.518410\n", " \n", " \n", " coef_arrival_constants_pm_peak_3\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_arrival_constants_pm_peak_4\n", - " -1.182768\n", + " -0.725959\n", + " -0.725959\n", " -0.596260\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.182768\n", " \n", " \n", " coef_departure_constants_am_peak_1\n", - " -25.000000\n", + " -13.990759\n", + " -13.990759\n", " -11.595050\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -25.000000\n", " \n", " \n", " coef_departure_constants_am_peak_2\n", - " -4.236849\n", + " -10.163788\n", + " -10.163788\n", " -9.005190\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -4.236849\n", " \n", " \n", " coef_departure_constants_am_peak_3\n", - " 0.806223\n", + " -2.799430\n", + " -2.799430\n", " -2.733150\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.806223\n", " \n", " \n", " coef_departure_constants_am_peak_4\n", - " 1.408142\n", + " 0.514393\n", + " 0.514393\n", " 0.266540\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 1.408142\n", " \n", " \n", " coef_departure_constants_early\n", - " -24.418086\n", + " -17.865880\n", + " -17.865880\n", " -14.477080\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -24.418086\n", " \n", " \n", " coef_departure_constants_evening\n", - " -14.557517\n", + " -19.574287\n", + " -19.574287\n", " -18.987370\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -14.557517\n", " \n", " \n", " coef_departure_constants_late\n", - " -20.421814\n", + " -21.444922\n", + " -21.444922\n", " -20.278070\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -20.421814\n", " \n", " \n", " coef_departure_constants_midday_1\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_departure_constants_midday_2\n", - " -4.501238\n", + " -1.886316\n", + " -1.886316\n", " -1.602600\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -4.501238\n", " \n", " \n", " coef_departure_constants_pm_peak\n", - " -12.638403\n", + " -18.238556\n", + " -18.238556\n", " -17.695980\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -12.638403\n", " \n", " \n", " coef_destination_in_cbd_duration_shift_effects\n", - " 0.572330\n", + " 0.130935\n", + " 0.130935\n", " 0.106700\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.572330\n", " \n", " \n", " coef_discretionary_tour_duration_lt_2_hours\n", - " -1.022488\n", + " -0.772425\n", + " -0.772425\n", " -0.697400\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.022488\n", " \n", " \n", " coef_duration_constants_0_to_1_hours\n", - " -2.750481\n", + " -2.021348\n", + " -2.021348\n", " -2.228260\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.750481\n", " \n", " \n", " coef_duration_constants_11_to_13_hours\n", - " -6.162737\n", + " -1.608105\n", + " -1.608105\n", " -0.815190\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -6.162737\n", " \n", " \n", " coef_duration_constants_14_to_18_hours\n", - " -2.800706\n", + " -3.067613\n", + " -3.067613\n", " -2.738440\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.800706\n", " \n", " \n", " coef_duration_constants_2_to_3_hours\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_duration_constants_4_to_5_hours\n", - " 0.301145\n", + " -0.519561\n", + " -0.519561\n", " -0.561740\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.301145\n", " \n", " \n", " coef_duration_constants_6_to_7_hours\n", - " 0.144072\n", + " -0.868309\n", + " -0.868309\n", " -0.655470\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.144072\n", " \n", " \n", " coef_duration_constants_8_to_10_hours\n", - " -10.570858\n", + " -1.020095\n", + " -1.020095\n", " -0.740620\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -10.570858\n", " \n", " \n", " coef_eat_out_tour_departure_shift_effects\n", - " -0.024649\n", + " 0.056578\n", + " 0.056578\n", " 0.075490\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.024649\n", " \n", " \n", " coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect\n", - " -1.329351\n", + " -0.506782\n", + " -0.506782\n", " -0.236400\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.329351\n", " \n", " \n", " coef_free_flow_round_trip_auto_time_shift_effects_duration\n", - " 0.017752\n", + " 0.003622\n", + " 0.003622\n", " 0.003195\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.017752\n", " \n", " \n", " coef_maintenance_tour_depart_before_7\n", - " 1.154584\n", + " -0.523693\n", + " -0.523693\n", " -0.882600\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 1.154584\n", " \n", " \n", " coef_maintenance_tour_departure_shift_effects\n", - " -0.159210\n", + " -0.135634\n", + " -0.135634\n", " -0.148900\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.159210\n", " \n", " \n", " coef_maintenance_tour_duration_shift_effects\n", - " -0.146459\n", + " -0.038428\n", + " -0.038428\n", " -0.083720\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.146459\n", " \n", " \n", " coef_number_of_joint_tours_departure_shift_effects\n", - " 1.356173\n", + " 0.128742\n", + " 0.128742\n", " 0.052080\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 1.356173\n", " \n", " \n", " coef_number_of_mandatory_tours_departure_shift_effects\n", - " 0.076326\n", + " -0.009788\n", + " -0.009788\n", " 0.046730\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.076326\n", " \n", " \n", " coef_school_child_age_16_plus_departure_shift_effects\n", + " 0.106395\n", + " 0.106395\n", " 0.072660\n", - " 0.072660\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.072660\n", " \n", " \n", " coef_school_child_age_16_plus_duration_shift_effects\n", + " 0.315781\n", + " 0.315781\n", " 0.209500\n", - " 0.209500\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.209500\n", " \n", " \n", " coef_school_child_age_under_16_departure_shift_effects\n", - " 0.239007\n", + " 0.015473\n", + " 0.015473\n", " 0.046570\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.239007\n", " \n", " \n", " coef_school_child_age_under_16_duration_shift_effects\n", - " -0.567863\n", + " 0.327527\n", + " 0.327527\n", " 0.327200\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.567863\n", " \n", " \n", " coef_school_child_under_16_arrive_after_22\n", - " -6.147237\n", + " -5.038827\n", + " -5.038827\n", " -1.180000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -6.147237\n", " \n", " \n", " coef_shopping_tour_arrive_after_22\n", - " -7.221041\n", + " -0.033268\n", + " -0.033268\n", " -0.602700\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -7.221041\n", " \n", " \n", " coef_shopping_tour_depart_before_8\n", - " 1.458488\n", + " -1.484109\n", + " -1.484109\n", " -1.037000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 1.458488\n", " \n", " \n", " coef_shopping_tour_departure_shift_effects\n", - " -0.045633\n", + " -0.099254\n", + " -0.099254\n", " -0.060150\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.045633\n", " \n", " \n", " coef_shopping_tour_duration_lt_2_hours\n", - " 0.189427\n", + " 0.699700\n", + " 0.699700\n", " 0.516800\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.189427\n", " \n", " \n", " coef_shopping_tour_duration_shift_effects\n", - " -0.359705\n", + " -0.101207\n", + " -0.101207\n", " -0.120800\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.359705\n", " \n", " \n", " coef_some_previously_scheduled_tour_begins_in_this_arrival_hour\n", - " 0.411979\n", + " -0.017681\n", + " -0.017681\n", " -0.399200\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.411979\n", " \n", " \n", " coef_some_previously_scheduled_tour_ends_in_this_departure_hour\n", - " 0.282029\n", + " -0.288048\n", + " -0.288048\n", " -0.456200\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.282029\n", " \n", " \n", " coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect\n", - " 0.191264\n", + " 0.062417\n", + " 0.062417\n", " -0.173100\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.191264\n", " \n", " \n", " coef_unavailable\n", " -999.000000\n", " -999.000000\n", + " -999.000000\n", + " -999.0\n", + " -999.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_university_student_arrive_after_22\n", - " -9.181095\n", + " 0.360948\n", + " 0.360948\n", " 0.546600\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -9.181095\n", " \n", " \n", " coef_visit_tour_departure_shift_effects\n", - " -0.109515\n", + " 0.136717\n", + " 0.136717\n", " 0.096880\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.109515\n", " \n", " \n", " coef_visit_tour_duration_shift_effects\n", - " -0.123814\n", + " 0.172436\n", + " 0.172436\n", " 0.163800\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.123814\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_adjacent_window_exists_after_this_arrival_... -13.526580 -0.025700 \n", - "coef_adjacent_window_exists_after_this_arrival_... -14.169341 -0.027340 \n", - "coef_adjacent_window_exists_before_this_departu... -13.495922 0.008442 \n", - "coef_adjacent_window_exists_before_this_departu... -7.716247 -0.059300 \n", - "coef_adult_with_children_in_hh_arrive_19_21 -0.002541 0.336000 \n", - "coef_arrival_constants_am_peak 4.647673 -8.728880 \n", - "coef_arrival_constants_early 24.793142 -8.728880 \n", - "coef_arrival_constants_evening -4.291783 -2.748940 \n", - "coef_arrival_constants_late -9.617038 -4.242530 \n", + " value best \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 0.800851 0.800851 \n", + "coef_adjacent_window_exists_after_this_arrival_... 0.494438 0.494438 \n", + "coef_adjacent_window_exists_before_this_departu... 0.008839 0.008839 \n", + "coef_adjacent_window_exists_before_this_departu... -0.549692 -0.549692 \n", + "coef_adult_with_children_in_hh_arrive_19_21 -0.078997 -0.078997 \n", + "coef_arrival_constants_am_peak -8.413713 -8.413713 \n", + "coef_arrival_constants_early -6.758955 -6.758955 \n", + "coef_arrival_constants_evening -2.675953 -2.675953 \n", + "coef_arrival_constants_late -4.194942 -4.194942 \n", "coef_arrival_constants_midday_1 0.000000 0.000000 \n", - "coef_arrival_constants_midday_2 2.692519 1.408040 \n", - "coef_arrival_constants_pm_peak_1 1.849237 1.020360 \n", - "coef_arrival_constants_pm_peak_2 1.518410 1.068630 \n", + "coef_arrival_constants_midday_2 1.416723 1.416723 \n", + "coef_arrival_constants_pm_peak_1 0.964024 0.964024 \n", + "coef_arrival_constants_pm_peak_2 1.200835 1.200835 \n", "coef_arrival_constants_pm_peak_3 0.000000 0.000000 \n", - "coef_arrival_constants_pm_peak_4 -1.182768 -0.596260 \n", - "coef_departure_constants_am_peak_1 -25.000000 -11.595050 \n", - "coef_departure_constants_am_peak_2 -4.236849 -9.005190 \n", - "coef_departure_constants_am_peak_3 0.806223 -2.733150 \n", - "coef_departure_constants_am_peak_4 1.408142 0.266540 \n", - "coef_departure_constants_early -24.418086 -14.477080 \n", - "coef_departure_constants_evening -14.557517 -18.987370 \n", - "coef_departure_constants_late -20.421814 -20.278070 \n", + "coef_arrival_constants_pm_peak_4 -0.725959 -0.725959 \n", + "coef_departure_constants_am_peak_1 -13.990759 -13.990759 \n", + "coef_departure_constants_am_peak_2 -10.163788 -10.163788 \n", + "coef_departure_constants_am_peak_3 -2.799430 -2.799430 \n", + "coef_departure_constants_am_peak_4 0.514393 0.514393 \n", + "coef_departure_constants_early -17.865880 -17.865880 \n", + "coef_departure_constants_evening -19.574287 -19.574287 \n", + "coef_departure_constants_late -21.444922 -21.444922 \n", "coef_departure_constants_midday_1 0.000000 0.000000 \n", - "coef_departure_constants_midday_2 -4.501238 -1.602600 \n", - "coef_departure_constants_pm_peak -12.638403 -17.695980 \n", - "coef_destination_in_cbd_duration_shift_effects 0.572330 0.106700 \n", - "coef_discretionary_tour_duration_lt_2_hours -1.022488 -0.697400 \n", - "coef_duration_constants_0_to_1_hours -2.750481 -2.228260 \n", - "coef_duration_constants_11_to_13_hours -6.162737 -0.815190 \n", - "coef_duration_constants_14_to_18_hours -2.800706 -2.738440 \n", + "coef_departure_constants_midday_2 -1.886316 -1.886316 \n", + "coef_departure_constants_pm_peak -18.238556 -18.238556 \n", + "coef_destination_in_cbd_duration_shift_effects 0.130935 0.130935 \n", + "coef_discretionary_tour_duration_lt_2_hours -0.772425 -0.772425 \n", + "coef_duration_constants_0_to_1_hours -2.021348 -2.021348 \n", + "coef_duration_constants_11_to_13_hours -1.608105 -1.608105 \n", + "coef_duration_constants_14_to_18_hours -3.067613 -3.067613 \n", "coef_duration_constants_2_to_3_hours 0.000000 0.000000 \n", - "coef_duration_constants_4_to_5_hours 0.301145 -0.561740 \n", - "coef_duration_constants_6_to_7_hours 0.144072 -0.655470 \n", - "coef_duration_constants_8_to_10_hours -10.570858 -0.740620 \n", - "coef_eat_out_tour_departure_shift_effects -0.024649 0.075490 \n", - "coef_first_of_2_plus_tours_for_same_purpose_dep... -1.329351 -0.236400 \n", - "coef_free_flow_round_trip_auto_time_shift_effec... 0.017752 0.003195 \n", - "coef_maintenance_tour_depart_before_7 1.154584 -0.882600 \n", - "coef_maintenance_tour_departure_shift_effects -0.159210 -0.148900 \n", - "coef_maintenance_tour_duration_shift_effects -0.146459 -0.083720 \n", - "coef_number_of_joint_tours_departure_shift_effects 1.356173 0.052080 \n", - "coef_number_of_mandatory_tours_departure_shift_... 0.076326 0.046730 \n", - "coef_school_child_age_16_plus_departure_shift_e... 0.072660 0.072660 \n", - "coef_school_child_age_16_plus_duration_shift_ef... 0.209500 0.209500 \n", - "coef_school_child_age_under_16_departure_shift_... 0.239007 0.046570 \n", - "coef_school_child_age_under_16_duration_shift_e... -0.567863 0.327200 \n", - "coef_school_child_under_16_arrive_after_22 -6.147237 -1.180000 \n", - "coef_shopping_tour_arrive_after_22 -7.221041 -0.602700 \n", - "coef_shopping_tour_depart_before_8 1.458488 -1.037000 \n", - "coef_shopping_tour_departure_shift_effects -0.045633 -0.060150 \n", - "coef_shopping_tour_duration_lt_2_hours 0.189427 0.516800 \n", - "coef_shopping_tour_duration_shift_effects -0.359705 -0.120800 \n", - "coef_some_previously_scheduled_tour_begins_in_t... 0.411979 -0.399200 \n", - "coef_some_previously_scheduled_tour_ends_in_thi... 0.282029 -0.456200 \n", - "coef_subsequent_of_2_plus_tours_for_same_purpos... 0.191264 -0.173100 \n", + "coef_duration_constants_4_to_5_hours -0.519561 -0.519561 \n", + "coef_duration_constants_6_to_7_hours -0.868309 -0.868309 \n", + "coef_duration_constants_8_to_10_hours -1.020095 -1.020095 \n", + "coef_eat_out_tour_departure_shift_effects 0.056578 0.056578 \n", + "coef_first_of_2_plus_tours_for_same_purpose_dep... -0.506782 -0.506782 \n", + "coef_free_flow_round_trip_auto_time_shift_effec... 0.003622 0.003622 \n", + "coef_maintenance_tour_depart_before_7 -0.523693 -0.523693 \n", + "coef_maintenance_tour_departure_shift_effects -0.135634 -0.135634 \n", + "coef_maintenance_tour_duration_shift_effects -0.038428 -0.038428 \n", + "coef_number_of_joint_tours_departure_shift_effects 0.128742 0.128742 \n", + "coef_number_of_mandatory_tours_departure_shift_... -0.009788 -0.009788 \n", + "coef_school_child_age_16_plus_departure_shift_e... 0.106395 0.106395 \n", + "coef_school_child_age_16_plus_duration_shift_ef... 0.315781 0.315781 \n", + "coef_school_child_age_under_16_departure_shift_... 0.015473 0.015473 \n", + "coef_school_child_age_under_16_duration_shift_e... 0.327527 0.327527 \n", + "coef_school_child_under_16_arrive_after_22 -5.038827 -5.038827 \n", + "coef_shopping_tour_arrive_after_22 -0.033268 -0.033268 \n", + "coef_shopping_tour_depart_before_8 -1.484109 -1.484109 \n", + "coef_shopping_tour_departure_shift_effects -0.099254 -0.099254 \n", + "coef_shopping_tour_duration_lt_2_hours 0.699700 0.699700 \n", + "coef_shopping_tour_duration_shift_effects -0.101207 -0.101207 \n", + "coef_some_previously_scheduled_tour_begins_in_t... -0.017681 -0.017681 \n", + "coef_some_previously_scheduled_tour_ends_in_thi... -0.288048 -0.288048 \n", + "coef_subsequent_of_2_plus_tours_for_same_purpos... 0.062417 0.062417 \n", "coef_unavailable -999.000000 -999.000000 \n", - "coef_university_student_arrive_after_22 -9.181095 0.546600 \n", - "coef_visit_tour_departure_shift_effects -0.109515 0.096880 \n", - "coef_visit_tour_duration_shift_effects -0.123814 0.163800 \n", + "coef_university_student_arrive_after_22 0.360948 0.360948 \n", + "coef_visit_tour_departure_shift_effects 0.136717 0.136717 \n", + "coef_visit_tour_duration_shift_effects 0.172436 0.172436 \n", "\n", - " nullvalue minimum \\\n", - "coef_adjacent_window_exists_after_this_arrival_... 0.0 -25.0 \n", - "coef_adjacent_window_exists_after_this_arrival_... 0.0 -25.0 \n", - "coef_adjacent_window_exists_before_this_departu... 0.0 -25.0 \n", - "coef_adjacent_window_exists_before_this_departu... 0.0 -25.0 \n", - "coef_adult_with_children_in_hh_arrive_19_21 0.0 -25.0 \n", - "coef_arrival_constants_am_peak 0.0 -25.0 \n", - "coef_arrival_constants_early 0.0 -25.0 \n", - "coef_arrival_constants_evening 0.0 -25.0 \n", - "coef_arrival_constants_late 0.0 -25.0 \n", - "coef_arrival_constants_midday_1 0.0 -25.0 \n", - "coef_arrival_constants_midday_2 0.0 -25.0 \n", - "coef_arrival_constants_pm_peak_1 0.0 -25.0 \n", - "coef_arrival_constants_pm_peak_2 0.0 -25.0 \n", - "coef_arrival_constants_pm_peak_3 0.0 -25.0 \n", - "coef_arrival_constants_pm_peak_4 0.0 -25.0 \n", - "coef_departure_constants_am_peak_1 0.0 -25.0 \n", - "coef_departure_constants_am_peak_2 0.0 -25.0 \n", - "coef_departure_constants_am_peak_3 0.0 -25.0 \n", - "coef_departure_constants_am_peak_4 0.0 -25.0 \n", - "coef_departure_constants_early 0.0 -25.0 \n", - "coef_departure_constants_evening 0.0 -25.0 \n", - "coef_departure_constants_late 0.0 -25.0 \n", - "coef_departure_constants_midday_1 0.0 -25.0 \n", - "coef_departure_constants_midday_2 0.0 -25.0 \n", - "coef_departure_constants_pm_peak 0.0 -25.0 \n", - "coef_destination_in_cbd_duration_shift_effects 0.0 -25.0 \n", - "coef_discretionary_tour_duration_lt_2_hours 0.0 -25.0 \n", - "coef_duration_constants_0_to_1_hours 0.0 -25.0 \n", - "coef_duration_constants_11_to_13_hours 0.0 -25.0 \n", - "coef_duration_constants_14_to_18_hours 0.0 -25.0 \n", - "coef_duration_constants_2_to_3_hours 0.0 -25.0 \n", - "coef_duration_constants_4_to_5_hours 0.0 -25.0 \n", - "coef_duration_constants_6_to_7_hours 0.0 -25.0 \n", - "coef_duration_constants_8_to_10_hours 0.0 -25.0 \n", - "coef_eat_out_tour_departure_shift_effects 0.0 -25.0 \n", - "coef_first_of_2_plus_tours_for_same_purpose_dep... 0.0 -25.0 \n", - "coef_free_flow_round_trip_auto_time_shift_effec... 0.0 -25.0 \n", - "coef_maintenance_tour_depart_before_7 0.0 -25.0 \n", - "coef_maintenance_tour_departure_shift_effects 0.0 -25.0 \n", - "coef_maintenance_tour_duration_shift_effects 0.0 -25.0 \n", - "coef_number_of_joint_tours_departure_shift_effects 0.0 -25.0 \n", - "coef_number_of_mandatory_tours_departure_shift_... 0.0 -25.0 \n", - "coef_school_child_age_16_plus_departure_shift_e... 0.0 -25.0 \n", - "coef_school_child_age_16_plus_duration_shift_ef... 0.0 -25.0 \n", - "coef_school_child_age_under_16_departure_shift_... 0.0 -25.0 \n", - "coef_school_child_age_under_16_duration_shift_e... 0.0 -25.0 \n", - "coef_school_child_under_16_arrive_after_22 0.0 -25.0 \n", - "coef_shopping_tour_arrive_after_22 0.0 -25.0 \n", - "coef_shopping_tour_depart_before_8 0.0 -25.0 \n", - "coef_shopping_tour_departure_shift_effects 0.0 -25.0 \n", - "coef_shopping_tour_duration_lt_2_hours 0.0 -25.0 \n", - "coef_shopping_tour_duration_shift_effects 0.0 -25.0 \n", - "coef_some_previously_scheduled_tour_begins_in_t... 0.0 -25.0 \n", - "coef_some_previously_scheduled_tour_ends_in_thi... 0.0 -25.0 \n", - "coef_subsequent_of_2_plus_tours_for_same_purpos... 0.0 -25.0 \n", - "coef_unavailable 0.0 -25.0 \n", - "coef_university_student_arrive_after_22 0.0 -25.0 \n", - "coef_visit_tour_departure_shift_effects 0.0 -25.0 \n", - "coef_visit_tour_duration_shift_effects 0.0 -25.0 \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... -0.025700 -25.0 \n", + "coef_adjacent_window_exists_after_this_arrival_... -0.027340 -25.0 \n", + "coef_adjacent_window_exists_before_this_departu... 0.008442 -25.0 \n", + "coef_adjacent_window_exists_before_this_departu... -0.059300 -25.0 \n", + "coef_adult_with_children_in_hh_arrive_19_21 0.336000 -25.0 \n", + "coef_arrival_constants_am_peak -8.728880 -25.0 \n", + "coef_arrival_constants_early -8.728880 -25.0 \n", + "coef_arrival_constants_evening -2.748940 -25.0 \n", + "coef_arrival_constants_late -4.242530 -25.0 \n", + "coef_arrival_constants_midday_1 0.000000 0.0 \n", + "coef_arrival_constants_midday_2 1.408040 -25.0 \n", + "coef_arrival_constants_pm_peak_1 1.020360 -25.0 \n", + "coef_arrival_constants_pm_peak_2 1.068630 -25.0 \n", + "coef_arrival_constants_pm_peak_3 0.000000 0.0 \n", + "coef_arrival_constants_pm_peak_4 -0.596260 -25.0 \n", + "coef_departure_constants_am_peak_1 -11.595050 -25.0 \n", + "coef_departure_constants_am_peak_2 -9.005190 -25.0 \n", + "coef_departure_constants_am_peak_3 -2.733150 -25.0 \n", + "coef_departure_constants_am_peak_4 0.266540 -25.0 \n", + "coef_departure_constants_early -14.477080 -25.0 \n", + "coef_departure_constants_evening -18.987370 -25.0 \n", + "coef_departure_constants_late -20.278070 -25.0 \n", + "coef_departure_constants_midday_1 0.000000 0.0 \n", + "coef_departure_constants_midday_2 -1.602600 -25.0 \n", + "coef_departure_constants_pm_peak -17.695980 -25.0 \n", + "coef_destination_in_cbd_duration_shift_effects 0.106700 -25.0 \n", + "coef_discretionary_tour_duration_lt_2_hours -0.697400 -25.0 \n", + "coef_duration_constants_0_to_1_hours -2.228260 -25.0 \n", + "coef_duration_constants_11_to_13_hours -0.815190 -25.0 \n", + "coef_duration_constants_14_to_18_hours -2.738440 -25.0 \n", + "coef_duration_constants_2_to_3_hours 0.000000 0.0 \n", + "coef_duration_constants_4_to_5_hours -0.561740 -25.0 \n", + "coef_duration_constants_6_to_7_hours -0.655470 -25.0 \n", + "coef_duration_constants_8_to_10_hours -0.740620 -25.0 \n", + "coef_eat_out_tour_departure_shift_effects 0.075490 -25.0 \n", + "coef_first_of_2_plus_tours_for_same_purpose_dep... -0.236400 -25.0 \n", + "coef_free_flow_round_trip_auto_time_shift_effec... 0.003195 -25.0 \n", + "coef_maintenance_tour_depart_before_7 -0.882600 -25.0 \n", + "coef_maintenance_tour_departure_shift_effects -0.148900 -25.0 \n", + "coef_maintenance_tour_duration_shift_effects -0.083720 -25.0 \n", + "coef_number_of_joint_tours_departure_shift_effects 0.052080 -25.0 \n", + "coef_number_of_mandatory_tours_departure_shift_... 0.046730 -25.0 \n", + "coef_school_child_age_16_plus_departure_shift_e... 0.072660 -25.0 \n", + "coef_school_child_age_16_plus_duration_shift_ef... 0.209500 -25.0 \n", + "coef_school_child_age_under_16_departure_shift_... 0.046570 -25.0 \n", + "coef_school_child_age_under_16_duration_shift_e... 0.327200 -25.0 \n", + "coef_school_child_under_16_arrive_after_22 -1.180000 -25.0 \n", + "coef_shopping_tour_arrive_after_22 -0.602700 -25.0 \n", + "coef_shopping_tour_depart_before_8 -1.037000 -25.0 \n", + "coef_shopping_tour_departure_shift_effects -0.060150 -25.0 \n", + "coef_shopping_tour_duration_lt_2_hours 0.516800 -25.0 \n", + "coef_shopping_tour_duration_shift_effects -0.120800 -25.0 \n", + "coef_some_previously_scheduled_tour_begins_in_t... -0.399200 -25.0 \n", + "coef_some_previously_scheduled_tour_ends_in_thi... -0.456200 -25.0 \n", + "coef_subsequent_of_2_plus_tours_for_same_purpos... -0.173100 -25.0 \n", + "coef_unavailable -999.000000 -999.0 \n", + "coef_university_student_arrive_after_22 0.546600 -25.0 \n", + "coef_visit_tour_departure_shift_effects 0.096880 -25.0 \n", + "coef_visit_tour_duration_shift_effects 0.163800 -25.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_adjacent_window_exists_after_this_arrival_... 25.0 0 \n", - "coef_adjacent_window_exists_after_this_arrival_... 25.0 0 \n", - "coef_adjacent_window_exists_before_this_departu... 25.0 0 \n", - "coef_adjacent_window_exists_before_this_departu... 25.0 0 \n", - "coef_adult_with_children_in_hh_arrive_19_21 25.0 0 \n", - "coef_arrival_constants_am_peak 25.0 0 \n", - "coef_arrival_constants_early 25.0 0 \n", - "coef_arrival_constants_evening 25.0 0 \n", - "coef_arrival_constants_late 25.0 0 \n", - "coef_arrival_constants_midday_1 25.0 1 \n", - "coef_arrival_constants_midday_2 25.0 0 \n", - "coef_arrival_constants_pm_peak_1 25.0 0 \n", - "coef_arrival_constants_pm_peak_2 25.0 0 \n", - "coef_arrival_constants_pm_peak_3 25.0 1 \n", - "coef_arrival_constants_pm_peak_4 25.0 0 \n", - "coef_departure_constants_am_peak_1 25.0 0 \n", - "coef_departure_constants_am_peak_2 25.0 0 \n", - "coef_departure_constants_am_peak_3 25.0 0 \n", - "coef_departure_constants_am_peak_4 25.0 0 \n", - "coef_departure_constants_early 25.0 0 \n", - "coef_departure_constants_evening 25.0 0 \n", - "coef_departure_constants_late 25.0 0 \n", - "coef_departure_constants_midday_1 25.0 1 \n", - "coef_departure_constants_midday_2 25.0 0 \n", - "coef_departure_constants_pm_peak 25.0 0 \n", - "coef_destination_in_cbd_duration_shift_effects 25.0 0 \n", - "coef_discretionary_tour_duration_lt_2_hours 25.0 0 \n", - "coef_duration_constants_0_to_1_hours 25.0 0 \n", - "coef_duration_constants_11_to_13_hours 25.0 0 \n", - "coef_duration_constants_14_to_18_hours 25.0 0 \n", - "coef_duration_constants_2_to_3_hours 25.0 1 \n", - "coef_duration_constants_4_to_5_hours 25.0 0 \n", - "coef_duration_constants_6_to_7_hours 25.0 0 \n", - "coef_duration_constants_8_to_10_hours 25.0 0 \n", - "coef_eat_out_tour_departure_shift_effects 25.0 0 \n", - "coef_first_of_2_plus_tours_for_same_purpose_dep... 25.0 0 \n", - "coef_free_flow_round_trip_auto_time_shift_effec... 25.0 0 \n", - "coef_maintenance_tour_depart_before_7 25.0 0 \n", - "coef_maintenance_tour_departure_shift_effects 25.0 0 \n", - "coef_maintenance_tour_duration_shift_effects 25.0 0 \n", - "coef_number_of_joint_tours_departure_shift_effects 25.0 0 \n", - "coef_number_of_mandatory_tours_departure_shift_... 25.0 0 \n", - "coef_school_child_age_16_plus_departure_shift_e... 25.0 0 \n", - "coef_school_child_age_16_plus_duration_shift_ef... 25.0 0 \n", - "coef_school_child_age_under_16_departure_shift_... 25.0 0 \n", - "coef_school_child_age_under_16_duration_shift_e... 25.0 0 \n", - "coef_school_child_under_16_arrive_after_22 25.0 0 \n", - "coef_shopping_tour_arrive_after_22 25.0 0 \n", - "coef_shopping_tour_depart_before_8 25.0 0 \n", - "coef_shopping_tour_departure_shift_effects 25.0 0 \n", - "coef_shopping_tour_duration_lt_2_hours 25.0 0 \n", - "coef_shopping_tour_duration_shift_effects 25.0 0 \n", - "coef_some_previously_scheduled_tour_begins_in_t... 25.0 0 \n", - "coef_some_previously_scheduled_tour_ends_in_thi... 25.0 0 \n", - "coef_subsequent_of_2_plus_tours_for_same_purpos... 25.0 0 \n", - "coef_unavailable 25.0 1 \n", - "coef_university_student_arrive_after_22 25.0 0 \n", - "coef_visit_tour_departure_shift_effects 25.0 0 \n", - "coef_visit_tour_duration_shift_effects 25.0 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 25.0 0.0 \n", + "coef_adjacent_window_exists_after_this_arrival_... 25.0 0.0 \n", + "coef_adjacent_window_exists_before_this_departu... 25.0 0.0 \n", + "coef_adjacent_window_exists_before_this_departu... 25.0 0.0 \n", + "coef_adult_with_children_in_hh_arrive_19_21 25.0 0.0 \n", + "coef_arrival_constants_am_peak 25.0 0.0 \n", + "coef_arrival_constants_early 25.0 0.0 \n", + "coef_arrival_constants_evening 25.0 0.0 \n", + "coef_arrival_constants_late 25.0 0.0 \n", + "coef_arrival_constants_midday_1 0.0 0.0 \n", + "coef_arrival_constants_midday_2 25.0 0.0 \n", + "coef_arrival_constants_pm_peak_1 25.0 0.0 \n", + "coef_arrival_constants_pm_peak_2 25.0 0.0 \n", + "coef_arrival_constants_pm_peak_3 0.0 0.0 \n", + "coef_arrival_constants_pm_peak_4 25.0 0.0 \n", + "coef_departure_constants_am_peak_1 25.0 0.0 \n", + "coef_departure_constants_am_peak_2 25.0 0.0 \n", + "coef_departure_constants_am_peak_3 25.0 0.0 \n", + "coef_departure_constants_am_peak_4 25.0 0.0 \n", + "coef_departure_constants_early 25.0 0.0 \n", + "coef_departure_constants_evening 25.0 0.0 \n", + "coef_departure_constants_late 25.0 0.0 \n", + "coef_departure_constants_midday_1 0.0 0.0 \n", + "coef_departure_constants_midday_2 25.0 0.0 \n", + "coef_departure_constants_pm_peak 25.0 0.0 \n", + "coef_destination_in_cbd_duration_shift_effects 25.0 0.0 \n", + "coef_discretionary_tour_duration_lt_2_hours 25.0 0.0 \n", + "coef_duration_constants_0_to_1_hours 25.0 0.0 \n", + "coef_duration_constants_11_to_13_hours 25.0 0.0 \n", + "coef_duration_constants_14_to_18_hours 25.0 0.0 \n", + "coef_duration_constants_2_to_3_hours 0.0 0.0 \n", + "coef_duration_constants_4_to_5_hours 25.0 0.0 \n", + "coef_duration_constants_6_to_7_hours 25.0 0.0 \n", + "coef_duration_constants_8_to_10_hours 25.0 0.0 \n", + "coef_eat_out_tour_departure_shift_effects 25.0 0.0 \n", + "coef_first_of_2_plus_tours_for_same_purpose_dep... 25.0 0.0 \n", + "coef_free_flow_round_trip_auto_time_shift_effec... 25.0 0.0 \n", + "coef_maintenance_tour_depart_before_7 25.0 0.0 \n", + "coef_maintenance_tour_departure_shift_effects 25.0 0.0 \n", + "coef_maintenance_tour_duration_shift_effects 25.0 0.0 \n", + "coef_number_of_joint_tours_departure_shift_effects 25.0 0.0 \n", + "coef_number_of_mandatory_tours_departure_shift_... 25.0 0.0 \n", + "coef_school_child_age_16_plus_departure_shift_e... 25.0 0.0 \n", + "coef_school_child_age_16_plus_duration_shift_ef... 25.0 0.0 \n", + "coef_school_child_age_under_16_departure_shift_... 25.0 0.0 \n", + "coef_school_child_age_under_16_duration_shift_e... 25.0 0.0 \n", + "coef_school_child_under_16_arrive_after_22 25.0 0.0 \n", + "coef_shopping_tour_arrive_after_22 25.0 0.0 \n", + "coef_shopping_tour_depart_before_8 25.0 0.0 \n", + "coef_shopping_tour_departure_shift_effects 25.0 0.0 \n", + "coef_shopping_tour_duration_lt_2_hours 25.0 0.0 \n", + "coef_shopping_tour_duration_shift_effects 25.0 0.0 \n", + "coef_some_previously_scheduled_tour_begins_in_t... 25.0 0.0 \n", + "coef_some_previously_scheduled_tour_ends_in_thi... 25.0 0.0 \n", + "coef_subsequent_of_2_plus_tours_for_same_purpos... 25.0 0.0 \n", + "coef_unavailable -999.0 0.0 \n", + "coef_university_student_arrive_after_22 25.0 0.0 \n", + "coef_visit_tour_departure_shift_effects 25.0 0.0 \n", + "coef_visit_tour_duration_shift_effects 25.0 0.0 \n", "\n", - " best \n", - "coef_adjacent_window_exists_after_this_arrival_... -13.526580 \n", - "coef_adjacent_window_exists_after_this_arrival_... -14.169341 \n", - "coef_adjacent_window_exists_before_this_departu... -13.495922 \n", - "coef_adjacent_window_exists_before_this_departu... -7.716247 \n", - "coef_adult_with_children_in_hh_arrive_19_21 -0.002541 \n", - "coef_arrival_constants_am_peak 4.647673 \n", - "coef_arrival_constants_early 24.793142 \n", - "coef_arrival_constants_evening -4.291783 \n", - "coef_arrival_constants_late -9.617038 \n", - "coef_arrival_constants_midday_1 0.000000 \n", - "coef_arrival_constants_midday_2 2.692519 \n", - "coef_arrival_constants_pm_peak_1 1.849237 \n", - "coef_arrival_constants_pm_peak_2 1.518410 \n", - "coef_arrival_constants_pm_peak_3 0.000000 \n", - "coef_arrival_constants_pm_peak_4 -1.182768 \n", - "coef_departure_constants_am_peak_1 -25.000000 \n", - "coef_departure_constants_am_peak_2 -4.236849 \n", - "coef_departure_constants_am_peak_3 0.806223 \n", - "coef_departure_constants_am_peak_4 1.408142 \n", - "coef_departure_constants_early -24.418086 \n", - "coef_departure_constants_evening -14.557517 \n", - "coef_departure_constants_late -20.421814 \n", - "coef_departure_constants_midday_1 0.000000 \n", - "coef_departure_constants_midday_2 -4.501238 \n", - "coef_departure_constants_pm_peak -12.638403 \n", - "coef_destination_in_cbd_duration_shift_effects 0.572330 \n", - "coef_discretionary_tour_duration_lt_2_hours -1.022488 \n", - "coef_duration_constants_0_to_1_hours -2.750481 \n", - "coef_duration_constants_11_to_13_hours -6.162737 \n", - "coef_duration_constants_14_to_18_hours -2.800706 \n", - "coef_duration_constants_2_to_3_hours 0.000000 \n", - "coef_duration_constants_4_to_5_hours 0.301145 \n", - "coef_duration_constants_6_to_7_hours 0.144072 \n", - "coef_duration_constants_8_to_10_hours -10.570858 \n", - "coef_eat_out_tour_departure_shift_effects -0.024649 \n", - "coef_first_of_2_plus_tours_for_same_purpose_dep... -1.329351 \n", - "coef_free_flow_round_trip_auto_time_shift_effec... 0.017752 \n", - "coef_maintenance_tour_depart_before_7 1.154584 \n", - "coef_maintenance_tour_departure_shift_effects -0.159210 \n", - "coef_maintenance_tour_duration_shift_effects -0.146459 \n", - "coef_number_of_joint_tours_departure_shift_effects 1.356173 \n", - "coef_number_of_mandatory_tours_departure_shift_... 0.076326 \n", - "coef_school_child_age_16_plus_departure_shift_e... 0.072660 \n", - "coef_school_child_age_16_plus_duration_shift_ef... 0.209500 \n", - "coef_school_child_age_under_16_departure_shift_... 0.239007 \n", - "coef_school_child_age_under_16_duration_shift_e... -0.567863 \n", - "coef_school_child_under_16_arrive_after_22 -6.147237 \n", - "coef_shopping_tour_arrive_after_22 -7.221041 \n", - "coef_shopping_tour_depart_before_8 1.458488 \n", - "coef_shopping_tour_departure_shift_effects -0.045633 \n", - "coef_shopping_tour_duration_lt_2_hours 0.189427 \n", - "coef_shopping_tour_duration_shift_effects -0.359705 \n", - "coef_some_previously_scheduled_tour_begins_in_t... 0.411979 \n", - "coef_some_previously_scheduled_tour_ends_in_thi... 0.282029 \n", - "coef_subsequent_of_2_plus_tours_for_same_purpos... 0.191264 \n", - "coef_unavailable -999.000000 \n", - "coef_university_student_arrive_after_22 -9.181095 \n", - "coef_visit_tour_departure_shift_effects -0.109515 \n", - "coef_visit_tour_duration_shift_effects -0.123814 " + " holdfast \n", + "param_name \n", + "coef_adjacent_window_exists_after_this_arrival_... 0 \n", + "coef_adjacent_window_exists_after_this_arrival_... 0 \n", + "coef_adjacent_window_exists_before_this_departu... 0 \n", + "coef_adjacent_window_exists_before_this_departu... 0 \n", + "coef_adult_with_children_in_hh_arrive_19_21 0 \n", + "coef_arrival_constants_am_peak 0 \n", + "coef_arrival_constants_early 0 \n", + "coef_arrival_constants_evening 0 \n", + "coef_arrival_constants_late 0 \n", + "coef_arrival_constants_midday_1 1 \n", + "coef_arrival_constants_midday_2 0 \n", + "coef_arrival_constants_pm_peak_1 0 \n", + "coef_arrival_constants_pm_peak_2 0 \n", + "coef_arrival_constants_pm_peak_3 1 \n", + "coef_arrival_constants_pm_peak_4 0 \n", + "coef_departure_constants_am_peak_1 0 \n", + "coef_departure_constants_am_peak_2 0 \n", + "coef_departure_constants_am_peak_3 0 \n", + "coef_departure_constants_am_peak_4 0 \n", + "coef_departure_constants_early 0 \n", + "coef_departure_constants_evening 0 \n", + "coef_departure_constants_late 0 \n", + "coef_departure_constants_midday_1 1 \n", + "coef_departure_constants_midday_2 0 \n", + "coef_departure_constants_pm_peak 0 \n", + "coef_destination_in_cbd_duration_shift_effects 0 \n", + "coef_discretionary_tour_duration_lt_2_hours 0 \n", + "coef_duration_constants_0_to_1_hours 0 \n", + "coef_duration_constants_11_to_13_hours 0 \n", + "coef_duration_constants_14_to_18_hours 0 \n", + "coef_duration_constants_2_to_3_hours 1 \n", + "coef_duration_constants_4_to_5_hours 0 \n", + "coef_duration_constants_6_to_7_hours 0 \n", + "coef_duration_constants_8_to_10_hours 0 \n", + "coef_eat_out_tour_departure_shift_effects 0 \n", + "coef_first_of_2_plus_tours_for_same_purpose_dep... 0 \n", + "coef_free_flow_round_trip_auto_time_shift_effec... 0 \n", + "coef_maintenance_tour_depart_before_7 0 \n", + "coef_maintenance_tour_departure_shift_effects 0 \n", + "coef_maintenance_tour_duration_shift_effects 0 \n", + "coef_number_of_joint_tours_departure_shift_effects 0 \n", + "coef_number_of_mandatory_tours_departure_shift_... 0 \n", + "coef_school_child_age_16_plus_departure_shift_e... 0 \n", + "coef_school_child_age_16_plus_duration_shift_ef... 0 \n", + "coef_school_child_age_under_16_departure_shift_... 0 \n", + "coef_school_child_age_under_16_duration_shift_e... 0 \n", + "coef_school_child_under_16_arrive_after_22 0 \n", + "coef_shopping_tour_arrive_after_22 0 \n", + "coef_shopping_tour_depart_before_8 0 \n", + "coef_shopping_tour_departure_shift_effects 0 \n", + "coef_shopping_tour_duration_lt_2_hours 0 \n", + "coef_shopping_tour_duration_shift_effects 0 \n", + "coef_some_previously_scheduled_tour_begins_in_t... 0 \n", + "coef_some_previously_scheduled_tour_ends_in_thi... 0 \n", + "coef_subsequent_of_2_plus_tours_for_same_purpos... 0 \n", + "coef_unavailable 1 \n", + "coef_university_student_arrive_after_22 0 \n", + "coef_visit_tour_departure_shift_effects 0 \n", + "coef_visit_tour_duration_shift_effects 0 " ] }, "metadata": {}, @@ -2970,10 +3140,8 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate()\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.472441734021349e-17 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { @@ -2989,39 +3157,39 @@ " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction\n", - " -13.526580\n", + " 0.800851\n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction\n", - " -14.169341\n", + " 0.494438\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction\n", - " -13.495922\n", + " 0.008839\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction\n", - " -7.716247\n", + " -0.549692\n", " \n", " \n", " coef_adult_with_children_in_hh_arrive_19_21\n", - " -0.002541\n", + " -0.078997\n", " \n", " \n", " coef_arrival_constants_am_peak\n", - " 4.647673\n", + " -8.413713\n", " \n", " \n", " coef_arrival_constants_early\n", - " 24.793142\n", + " -6.758955\n", " \n", " \n", " coef_arrival_constants_evening\n", - " -4.291783\n", + " -2.675953\n", " \n", " \n", " coef_arrival_constants_late\n", - " -9.617038\n", + " -4.194942\n", " \n", " \n", " coef_arrival_constants_midday_1\n", @@ -3029,15 +3197,15 @@ " \n", " \n", " coef_arrival_constants_midday_2\n", - " 2.692519\n", + " 1.416723\n", " \n", " \n", " coef_arrival_constants_pm_peak_1\n", - " 1.849237\n", + " 0.964024\n", " \n", " \n", " coef_arrival_constants_pm_peak_2\n", - " 1.518410\n", + " 1.200835\n", " \n", " \n", " coef_arrival_constants_pm_peak_3\n", @@ -3045,35 +3213,35 @@ " \n", " \n", " coef_arrival_constants_pm_peak_4\n", - " -1.182768\n", + " -0.725959\n", " \n", " \n", " coef_departure_constants_am_peak_1\n", - " -25.000000\n", + " -13.990759\n", " \n", " \n", " coef_departure_constants_am_peak_2\n", - " -4.236849\n", + " -10.163788\n", " \n", " \n", " coef_departure_constants_am_peak_3\n", - " 0.806223\n", + " -2.799430\n", " \n", " \n", " coef_departure_constants_am_peak_4\n", - " 1.408142\n", + " 0.514393\n", " \n", " \n", " coef_departure_constants_early\n", - " -24.418086\n", + " -17.865880\n", " \n", " \n", " coef_departure_constants_evening\n", - " -14.557517\n", + " -19.574287\n", " \n", " \n", " coef_departure_constants_late\n", - " -20.421814\n", + " -21.444922\n", " \n", " \n", " coef_departure_constants_midday_1\n", @@ -3081,31 +3249,31 @@ " \n", " \n", " coef_departure_constants_midday_2\n", - " -4.501238\n", + " -1.886316\n", " \n", " \n", " coef_departure_constants_pm_peak\n", - " -12.638403\n", + " -18.238556\n", " \n", " \n", " coef_destination_in_cbd_duration_shift_effects\n", - " 0.572330\n", + " 0.130935\n", " \n", " \n", " coef_discretionary_tour_duration_lt_2_hours\n", - " -1.022488\n", + " -0.772425\n", " \n", " \n", " coef_duration_constants_0_to_1_hours\n", - " -2.750481\n", + " -2.021348\n", " \n", " \n", " coef_duration_constants_11_to_13_hours\n", - " -6.162737\n", + " -1.608105\n", " \n", " \n", " coef_duration_constants_14_to_18_hours\n", - " -2.800706\n", + " -3.067613\n", " \n", " \n", " coef_duration_constants_2_to_3_hours\n", @@ -3113,118 +3281,118 @@ " \n", " \n", " coef_duration_constants_4_to_5_hours\n", - " 0.301145\n", + " -0.519561\n", " \n", " \n", " coef_duration_constants_6_to_7_hours\n", - " 0.144072\n", + " -0.868309\n", " \n", " \n", " coef_duration_constants_8_to_10_hours\n", - " -10.570858\n", + " -1.020095\n", " \n", " \n", " coef_eat_out_tour_departure_shift_effects\n", - " -0.024649\n", + " 0.056578\n", " \n", " \n", " coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect\n", - " -1.329351\n", + " -0.506782\n", " \n", " \n", " coef_free_flow_round_trip_auto_time_shift_effects_duration\n", - " 0.017752\n", + " 0.003622\n", " \n", " \n", " coef_maintenance_tour_depart_before_7\n", - " 1.154584\n", + " -0.523693\n", " \n", " \n", " coef_maintenance_tour_departure_shift_effects\n", - " -0.159210\n", + " -0.135634\n", " \n", " \n", " coef_maintenance_tour_duration_shift_effects\n", - " -0.146459\n", + " -0.038428\n", " \n", " \n", " coef_number_of_joint_tours_departure_shift_effects\n", - " 1.356173\n", + " 0.128742\n", " \n", " \n", " coef_number_of_mandatory_tours_departure_shift_effects\n", - " 0.076326\n", + " -0.009788\n", " \n", " \n", " coef_school_child_age_16_plus_departure_shift_effects\n", - " 0.072660\n", + " 0.106395\n", " \n", " \n", " coef_school_child_age_16_plus_duration_shift_effects\n", - " 0.209500\n", + " 0.315781\n", " \n", " \n", " coef_school_child_age_under_16_departure_shift_effects\n", - " 0.239007\n", + " 0.015473\n", " \n", " \n", " coef_school_child_age_under_16_duration_shift_effects\n", - " -0.567863\n", + " 0.327527\n", " \n", " \n", " coef_school_child_under_16_arrive_after_22\n", - " -6.147237\n", + " -5.038827\n", " \n", " \n", " coef_shopping_tour_arrive_after_22\n", - " -7.221041\n", + " -0.033268\n", " \n", " \n", " coef_shopping_tour_depart_before_8\n", - " 1.458488\n", + " -1.484109\n", " \n", " \n", " coef_shopping_tour_departure_shift_effects\n", - " -0.045633\n", + " -0.099254\n", " \n", " \n", " coef_shopping_tour_duration_lt_2_hours\n", - " 0.189427\n", + " 0.699700\n", " \n", " \n", " coef_shopping_tour_duration_shift_effects\n", - " -0.359705\n", + " -0.101207\n", " \n", " \n", " coef_some_previously_scheduled_tour_begins_in_this_arrival_hour\n", - " 0.411979\n", + " -0.017681\n", " \n", " \n", " coef_some_previously_scheduled_tour_ends_in_this_departure_hour\n", - " 0.282029\n", + " -0.288048\n", " \n", " \n", " coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect\n", - " 0.191264\n", + " 0.062417\n", " \n", " \n", " coef_unavailable\n", - " -25.000000\n", + " -999.000000\n", " \n", " \n", " coef_university_student_arrive_after_22\n", - " -9.181095\n", + " 0.360948\n", " \n", " \n", " coef_visit_tour_departure_shift_effects\n", - " -0.109515\n", + " 0.136717\n", " \n", " \n", " coef_visit_tour_duration_shift_effects\n", - " -0.123814\n", + " 0.172436\n", " \n", " \n", - "loglike-173.82837615906058d_loglike\n", + "
logloss2.1895702975048073d_logloss\n", " \n", " \n", " \n", @@ -3234,39 +3402,39 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3274,15 +3442,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3290,35 +3458,35 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3326,31 +3494,31 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3358,99 +3526,99 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3458,161 +3626,161 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - "
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction-9.350492e-076.340297e-05
coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction-3.831848e-074.838604e-05
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction-1.411114e-062.000787e-08
coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction-8.562988e-066.385755e-05
coef_adult_with_children_in_hh_arrive_19_219.515373e-051.672535e-04
coef_arrival_constants_am_peak-5.959256e-054.015659e-05
coef_arrival_constants_early-6.500054e-05-7.121334e-05
coef_arrival_constants_evening2.456794e-041.588972e-05
coef_arrival_constants_late-2.788545e-041.960950e-04
coef_arrival_constants_midday_1
coef_arrival_constants_midday_2-2.921253e-05-7.425169e-06
coef_arrival_constants_pm_peak_1-8.553639e-05-8.554627e-05
coef_arrival_constants_pm_peak_22.958919e-05-2.178755e-05
coef_arrival_constants_pm_peak_3
coef_arrival_constants_pm_peak_4-6.027051e-063.187347e-05
coef_departure_constants_am_peak_1-9.035869e-057.176011e-06
coef_departure_constants_am_peak_2-3.843278e-071.002541e-04
coef_departure_constants_am_peak_3-1.038927e-045.286380e-05
coef_departure_constants_am_peak_42.089562e-055.196924e-06
coef_departure_constants_early2.533008e-05-4.734722e-05
coef_departure_constants_evening9.169928e-06-5.250786e-05
coef_departure_constants_late-5.558022e-044.394692e-05
coef_departure_constants_midday_1
coef_departure_constants_midday_22.692412e-05-1.886914e-04
coef_departure_constants_pm_peak1.942225e-043.759255e-05
coef_destination_in_cbd_duration_shift_effects3.441152e-041.613685e-05
coef_discretionary_tour_duration_lt_2_hours7.722617e-05-2.070609e-04
coef_duration_constants_0_to_1_hours-1.588601e-044.953135e-05
coef_duration_constants_11_to_13_hours-3.605513e-042.382282e-05
coef_duration_constants_14_to_18_hours-1.774351e-04-3.488047e-05
coef_duration_constants_2_to_3_hours
coef_duration_constants_4_to_5_hours2.266202e-05-7.768694e-07
coef_duration_constants_6_to_7_hours-4.640922e-05-1.838870e-05
coef_duration_constants_8_to_10_hours-2.554467e-05-2.938670e-05
coef_eat_out_tour_departure_shift_effects-3.267677e-042.917206e-05
coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect-1.021958e-059.739371e-05
coef_free_flow_round_trip_auto_time_shift_effects_duration8.421848e-03-1.212989e-05
coef_maintenance_tour_depart_before_7-1.129004e-048.298165e-06
coef_maintenance_tour_departure_shift_effects-2.093211e-031.059914e-04
coef_maintenance_tour_duration_shift_effects2.786266e-042.022297e-05
coef_number_of_joint_tours_departure_shift_effects-2.856908e-03-1.252624e-04
coef_number_of_mandatory_tours_departure_shift_effects-2.687845e-03-1.288240e-04
coef_school_child_age_16_plus_departure_shift_effects0.000000e+001.808366e-04
coef_school_child_age_16_plus_duration_shift_effects0.000000e+004.559202e-05
coef_school_child_age_under_16_departure_shift_effects-1.932195e-04-1.455769e-05
coef_school_child_age_under_16_duration_shift_effects1.479815e-04-4.476322e-05
coef_school_child_under_16_arrive_after_22-9.565965e-05-4.170945e-05
coef_shopping_tour_arrive_after_22-7.152259e-05-8.668123e-05
coef_shopping_tour_depart_before_8-3.306479e-056.613654e-05
coef_shopping_tour_departure_shift_effects-2.740920e-049.925783e-05
coef_shopping_tour_duration_lt_2_hours3.816925e-058.629531e-05
coef_shopping_tour_duration_shift_effects1.258312e-041.970358e-05
coef_some_previously_scheduled_tour_begins_in_this_arrival_hour3.226289e-056.069742e-05
coef_some_previously_scheduled_tour_ends_in_this_departure_hour3.161563e-043.334213e-05
coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect1.181360e-05-1.230984e-04
coef_unavailable
coef_university_student_arrive_after_22-2.193359e-06-5.714988e-05
coef_visit_tour_departure_shift_effects-4.986513e-04-1.378200e-04
coef_visit_tour_duration_shift_effects2.469947e-04-2.132350e-05
nit67nfev106njev67status0message'Optimization terminated successfully'successTrueelapsed_time0:00:00.587568method'slsqp'n_cases91iteration_number67logloss1.9102019358138524" + "nit144nfev148njev144status0message'Optimization terminated successfully'successTrueelapsed_time0:00:03.104941method'slsqp'n_cases1277iteration_number144loglike-2789.5125590211246" ], "text/plain": [ - "┣ x: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction -13.526580\n", - "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction -14.169341\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction -13.495922\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction -7.716247\n", - "┃ coef_adult_with_children_in_hh_arrive_19_21 -0.002541\n", - "┃ coef_arrival_constants_am_peak 4.647673\n", - "┃ coef_arrival_constants_early 24.793142\n", - "┃ coef_arrival_constants_evening -4.291783\n", - "┃ coef_arrival_constants_late -9.617038\n", - "┃ coef_arrival_constants_midday_1 0.000000\n", - "┃ coef_arrival_constants_midday_2 2.692519\n", - "┃ coef_arrival_constants_pm_peak_1 1.849237\n", - "┃ coef_arrival_constants_pm_peak_2 1.518410\n", - "┃ coef_arrival_constants_pm_peak_3 0.000000\n", - "┃ coef_arrival_constants_pm_peak_4 -1.182768\n", - "┃ coef_departure_constants_am_peak_1 -25.000000\n", - "┃ coef_departure_constants_am_peak_2 -4.236849\n", - "┃ coef_departure_constants_am_peak_3 0.806223\n", - "┃ coef_departure_constants_am_peak_4 1.408142\n", - "┃ coef_departure_constants_early -24.418086\n", - "┃ coef_departure_constants_evening -14.557517\n", - "┃ coef_departure_constants_late -20.421814\n", - "┃ coef_departure_constants_midday_1 0.000000\n", - "┃ coef_departure_constants_midday_2 -4.501238\n", - "┃ coef_departure_constants_pm_peak -12.638403\n", - "┃ coef_destination_in_cbd_duration_shift_effects 0.572330\n", - "┃ coef_discretionary_tour_duration_lt_2_hours -1.022488\n", - "┃ coef_duration_constants_0_to_1_hours -2.750481\n", - "┃ coef_duration_constants_11_to_13_hours -6.162737\n", - "┃ coef_duration_constants_14_to_18_hours -2.800706\n", - "┃ coef_duration_constants_2_to_3_hours 0.000000\n", - "┃ coef_duration_constants_4_to_5_hours 0.301145\n", - "┃ coef_duration_constants_6_to_7_hours 0.144072\n", - "┃ coef_duration_constants_8_to_10_hours -10.570858\n", - "┃ coef_eat_out_tour_departure_shift_effects -0.024649\n", - "┃ coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect -1.329351\n", - "┃ coef_free_flow_round_trip_auto_time_shift_effects_duration 0.017752\n", - "┃ coef_maintenance_tour_depart_before_7 1.154584\n", - "┃ coef_maintenance_tour_departure_shift_effects -0.159210\n", - "┃ coef_maintenance_tour_duration_shift_effects -0.146459\n", - "┃ coef_number_of_joint_tours_departure_shift_effects 1.356173\n", - "┃ coef_number_of_mandatory_tours_departure_shift_effects 0.076326\n", - "┃ coef_school_child_age_16_plus_departure_shift_effects 0.072660\n", - "┃ coef_school_child_age_16_plus_duration_shift_effects 0.209500\n", - "┃ coef_school_child_age_under_16_departure_shift_effects 0.239007\n", - "┃ coef_school_child_age_under_16_duration_shift_effects -0.567863\n", - "┃ coef_school_child_under_16_arrive_after_22 -6.147237\n", - "┃ coef_shopping_tour_arrive_after_22 -7.221041\n", - "┃ coef_shopping_tour_depart_before_8 1.458488\n", - "┃ coef_shopping_tour_departure_shift_effects -0.045633\n", - "┃ coef_shopping_tour_duration_lt_2_hours 0.189427\n", - "┃ coef_shopping_tour_duration_shift_effects -0.359705\n", - "┃ coef_some_previously_scheduled_tour_begins_in_this_arrival_hour 0.411979\n", - "┃ coef_some_previously_scheduled_tour_ends_in_this_departure_hour 0.282029\n", - "┃ coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect 0.191264\n", - "┃ coef_unavailable -25.000000\n", - "┃ coef_university_student_arrive_after_22 -9.181095\n", - "┃ coef_visit_tour_departure_shift_effects -0.109515\n", - "┃ coef_visit_tour_duration_shift_effects -0.123814\n", + "┣ x: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.800851\n", + "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction 0.494438\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.008839\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction -0.549692\n", + "┃ coef_adult_with_children_in_hh_arrive_19_21 -0.078997\n", + "┃ coef_arrival_constants_am_peak -8.413713\n", + "┃ coef_arrival_constants_early -6.758955\n", + "┃ coef_arrival_constants_evening -2.675953\n", + "┃ coef_arrival_constants_late -4.194942\n", + "┃ coef_arrival_constants_midday_1 0.000000\n", + "┃ coef_arrival_constants_midday_2 1.416723\n", + "┃ coef_arrival_constants_pm_peak_1 0.964024\n", + "┃ coef_arrival_constants_pm_peak_2 1.200835\n", + "┃ coef_arrival_constants_pm_peak_3 0.000000\n", + "┃ coef_arrival_constants_pm_peak_4 -0.725959\n", + "┃ coef_departure_constants_am_peak_1 -13.990759\n", + "┃ coef_departure_constants_am_peak_2 -10.163788\n", + "┃ coef_departure_constants_am_peak_3 -2.799430\n", + "┃ coef_departure_constants_am_peak_4 0.514393\n", + "┃ coef_departure_constants_early -17.865880\n", + "┃ coef_departure_constants_evening -19.574287\n", + "┃ coef_departure_constants_late -21.444922\n", + "┃ coef_departure_constants_midday_1 0.000000\n", + "┃ coef_departure_constants_midday_2 -1.886316\n", + "┃ coef_departure_constants_pm_peak -18.238556\n", + "┃ coef_destination_in_cbd_duration_shift_effects 0.130935\n", + "┃ coef_discretionary_tour_duration_lt_2_hours -0.772425\n", + "┃ coef_duration_constants_0_to_1_hours -2.021348\n", + "┃ coef_duration_constants_11_to_13_hours -1.608105\n", + "┃ coef_duration_constants_14_to_18_hours -3.067613\n", + "┃ coef_duration_constants_2_to_3_hours 0.000000\n", + "┃ coef_duration_constants_4_to_5_hours -0.519561\n", + "┃ coef_duration_constants_6_to_7_hours -0.868309\n", + "┃ coef_duration_constants_8_to_10_hours -1.020095\n", + "┃ coef_eat_out_tour_departure_shift_effects 0.056578\n", + "┃ coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect -0.506782\n", + "┃ coef_free_flow_round_trip_auto_time_shift_effects_duration 0.003622\n", + "┃ coef_maintenance_tour_depart_before_7 -0.523693\n", + "┃ coef_maintenance_tour_departure_shift_effects -0.135634\n", + "┃ coef_maintenance_tour_duration_shift_effects -0.038428\n", + "┃ coef_number_of_joint_tours_departure_shift_effects 0.128742\n", + "┃ coef_number_of_mandatory_tours_departure_shift_effects -0.009788\n", + "┃ coef_school_child_age_16_plus_departure_shift_effects 0.106395\n", + "┃ coef_school_child_age_16_plus_duration_shift_effects 0.315781\n", + "┃ coef_school_child_age_under_16_departure_shift_effects 0.015473\n", + "┃ coef_school_child_age_under_16_duration_shift_effects 0.327527\n", + "┃ coef_school_child_under_16_arrive_after_22 -5.038827\n", + "┃ coef_shopping_tour_arrive_after_22 -0.033268\n", + "┃ coef_shopping_tour_depart_before_8 -1.484109\n", + "┃ coef_shopping_tour_departure_shift_effects -0.099254\n", + "┃ coef_shopping_tour_duration_lt_2_hours 0.699700\n", + "┃ coef_shopping_tour_duration_shift_effects -0.101207\n", + "┃ coef_some_previously_scheduled_tour_begins_in_this_arrival_hour -0.017681\n", + "┃ coef_some_previously_scheduled_tour_ends_in_this_departure_hour -0.288048\n", + "┃ coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect 0.062417\n", + "┃ coef_unavailable -999.000000\n", + "┃ coef_university_student_arrive_after_22 0.360948\n", + "┃ coef_visit_tour_departure_shift_effects 0.136717\n", + "┃ coef_visit_tour_duration_shift_effects 0.172436\n", "┃ dtype: float64\n", - "┣ loglike: -173.82837615906058\n", - "┣ d_loglike: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction -9.350492e-07\n", - "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction -3.831848e-07\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction -1.411114e-06\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction -8.562988e-06\n", - "┃ coef_adult_with_children_in_hh_arrive_19_21 9.515373e-05\n", - "┃ coef_arrival_constants_am_peak -5.959256e-05\n", - "┃ coef_arrival_constants_early -6.500054e-05\n", - "┃ coef_arrival_constants_evening 2.456794e-04\n", - "┃ coef_arrival_constants_late -2.788545e-04\n", + "┣ logloss: 2.1895702975048073\n", + "┣ d_logloss: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 6.340297e-05\n", + "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction 4.838604e-05\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 2.000787e-08\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction 6.385755e-05\n", + "┃ coef_adult_with_children_in_hh_arrive_19_21 1.672535e-04\n", + "┃ coef_arrival_constants_am_peak 4.015659e-05\n", + "┃ coef_arrival_constants_early -7.121334e-05\n", + "┃ coef_arrival_constants_evening 1.588972e-05\n", + "┃ coef_arrival_constants_late 1.960950e-04\n", "┃ coef_arrival_constants_midday_1 0.000000e+00\n", - "┃ coef_arrival_constants_midday_2 -2.921253e-05\n", - "┃ coef_arrival_constants_pm_peak_1 -8.553639e-05\n", - "┃ coef_arrival_constants_pm_peak_2 2.958919e-05\n", + "┃ coef_arrival_constants_midday_2 -7.425169e-06\n", + "┃ coef_arrival_constants_pm_peak_1 -8.554627e-05\n", + "┃ coef_arrival_constants_pm_peak_2 -2.178755e-05\n", "┃ coef_arrival_constants_pm_peak_3 0.000000e+00\n", - "┃ coef_arrival_constants_pm_peak_4 -6.027051e-06\n", - "┃ coef_departure_constants_am_peak_1 -9.035869e-05\n", - "┃ coef_departure_constants_am_peak_2 -3.843278e-07\n", - "┃ coef_departure_constants_am_peak_3 -1.038927e-04\n", - "┃ coef_departure_constants_am_peak_4 2.089562e-05\n", - "┃ coef_departure_constants_early 2.533008e-05\n", - "┃ coef_departure_constants_evening 9.169928e-06\n", - "┃ coef_departure_constants_late -5.558022e-04\n", + "┃ coef_arrival_constants_pm_peak_4 3.187347e-05\n", + "┃ coef_departure_constants_am_peak_1 7.176011e-06\n", + "┃ coef_departure_constants_am_peak_2 1.002541e-04\n", + "┃ coef_departure_constants_am_peak_3 5.286380e-05\n", + "┃ coef_departure_constants_am_peak_4 5.196924e-06\n", + "┃ coef_departure_constants_early -4.734722e-05\n", + "┃ coef_departure_constants_evening -5.250786e-05\n", + "┃ coef_departure_constants_late 4.394692e-05\n", "┃ coef_departure_constants_midday_1 0.000000e+00\n", - "┃ coef_departure_constants_midday_2 2.692412e-05\n", - "┃ coef_departure_constants_pm_peak 1.942225e-04\n", - "┃ coef_destination_in_cbd_duration_shift_effects 3.441152e-04\n", - "┃ coef_discretionary_tour_duration_lt_2_hours 7.722617e-05\n", - "┃ coef_duration_constants_0_to_1_hours -1.588601e-04\n", - "┃ coef_duration_constants_11_to_13_hours -3.605513e-04\n", - "┃ coef_duration_constants_14_to_18_hours -1.774351e-04\n", + "┃ coef_departure_constants_midday_2 -1.886914e-04\n", + "┃ coef_departure_constants_pm_peak 3.759255e-05\n", + "┃ coef_destination_in_cbd_duration_shift_effects 1.613685e-05\n", + "┃ coef_discretionary_tour_duration_lt_2_hours -2.070609e-04\n", + "┃ coef_duration_constants_0_to_1_hours 4.953135e-05\n", + "┃ coef_duration_constants_11_to_13_hours 2.382282e-05\n", + "┃ coef_duration_constants_14_to_18_hours -3.488047e-05\n", "┃ coef_duration_constants_2_to_3_hours 0.000000e+00\n", - "┃ coef_duration_constants_4_to_5_hours 2.266202e-05\n", - "┃ coef_duration_constants_6_to_7_hours -4.640922e-05\n", - "┃ coef_duration_constants_8_to_10_hours -2.554467e-05\n", - "┃ coef_eat_out_tour_departure_shift_effects -3.267677e-04\n", - "┃ coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect -1.021958e-05\n", - "┃ coef_free_flow_round_trip_auto_time_shift_effects_duration 8.421848e-03\n", - "┃ coef_maintenance_tour_depart_before_7 -1.129004e-04\n", - "┃ coef_maintenance_tour_departure_shift_effects -2.093211e-03\n", - "┃ coef_maintenance_tour_duration_shift_effects 2.786266e-04\n", - "┃ coef_number_of_joint_tours_departure_shift_effects -2.856908e-03\n", - "┃ coef_number_of_mandatory_tours_departure_shift_effects -2.687845e-03\n", - "┃ coef_school_child_age_16_plus_departure_shift_effects 0.000000e+00\n", - "┃ coef_school_child_age_16_plus_duration_shift_effects 0.000000e+00\n", - "┃ coef_school_child_age_under_16_departure_shift_effects -1.932195e-04\n", - "┃ coef_school_child_age_under_16_duration_shift_effects 1.479815e-04\n", - "┃ coef_school_child_under_16_arrive_after_22 -9.565965e-05\n", - "┃ coef_shopping_tour_arrive_after_22 -7.152259e-05\n", - "┃ coef_shopping_tour_depart_before_8 -3.306479e-05\n", - "┃ coef_shopping_tour_departure_shift_effects -2.740920e-04\n", - "┃ coef_shopping_tour_duration_lt_2_hours 3.816925e-05\n", - "┃ coef_shopping_tour_duration_shift_effects 1.258312e-04\n", - "┃ coef_some_previously_scheduled_tour_begins_in_this_arrival_hour 3.226289e-05\n", - "┃ coef_some_previously_scheduled_tour_ends_in_this_departure_hour 3.161563e-04\n", - "┃ coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect 1.181360e-05\n", + "┃ coef_duration_constants_4_to_5_hours -7.768694e-07\n", + "┃ coef_duration_constants_6_to_7_hours -1.838870e-05\n", + "┃ coef_duration_constants_8_to_10_hours -2.938670e-05\n", + "┃ coef_eat_out_tour_departure_shift_effects 2.917206e-05\n", + "┃ coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect 9.739371e-05\n", + "┃ coef_free_flow_round_trip_auto_time_shift_effects_duration -1.212989e-05\n", + "┃ coef_maintenance_tour_depart_before_7 8.298165e-06\n", + "┃ coef_maintenance_tour_departure_shift_effects 1.059914e-04\n", + "┃ coef_maintenance_tour_duration_shift_effects 2.022297e-05\n", + "┃ coef_number_of_joint_tours_departure_shift_effects -1.252624e-04\n", + "┃ coef_number_of_mandatory_tours_departure_shift_effects -1.288240e-04\n", + "┃ coef_school_child_age_16_plus_departure_shift_effects 1.808366e-04\n", + "┃ coef_school_child_age_16_plus_duration_shift_effects 4.559202e-05\n", + "┃ coef_school_child_age_under_16_departure_shift_effects -1.455769e-05\n", + "┃ coef_school_child_age_under_16_duration_shift_effects -4.476322e-05\n", + "┃ coef_school_child_under_16_arrive_after_22 -4.170945e-05\n", + "┃ coef_shopping_tour_arrive_after_22 -8.668123e-05\n", + "┃ coef_shopping_tour_depart_before_8 6.613654e-05\n", + "┃ coef_shopping_tour_departure_shift_effects 9.925783e-05\n", + "┃ coef_shopping_tour_duration_lt_2_hours 8.629531e-05\n", + "┃ coef_shopping_tour_duration_shift_effects 1.970358e-05\n", + "┃ coef_some_previously_scheduled_tour_begins_in_this_arrival_hour 6.069742e-05\n", + "┃ coef_some_previously_scheduled_tour_ends_in_this_departure_hour 3.334213e-05\n", + "┃ coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect -1.230984e-04\n", "┃ coef_unavailable 0.000000e+00\n", - "┃ coef_university_student_arrive_after_22 -2.193359e-06\n", - "┃ coef_visit_tour_departure_shift_effects -4.986513e-04\n", - "┃ coef_visit_tour_duration_shift_effects 2.469947e-04\n", + "┃ coef_university_student_arrive_after_22 -5.714988e-05\n", + "┃ coef_visit_tour_departure_shift_effects -1.378200e-04\n", + "┃ coef_visit_tour_duration_shift_effects -2.132350e-05\n", "┃ dtype: float64\n", - "┣ nit: 67\n", - "┣ nfev: 106\n", - "┣ njev: 67\n", + "┣ nit: 144\n", + "┣ nfev: 148\n", + "┣ njev: 144\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(microseconds=587568)\n", + "┣ elapsed_time: datetime.timedelta(seconds=3, microseconds=104941)\n", "┣ method: 'slsqp'\n", - "┣ n_cases: 91\n", - "┣ iteration_number: 67\n", - "┣ logloss: 1.9102019358138524" + "┣ n_cases: 1277\n", + "┣ iteration_number: 144\n", + "┣ loglike: -2789.5125590211246" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction-13.5 1.03e+03-0.01 NA 0.00
coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction-14.2 1.62e+03-0.01 NA 0.00
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction-13.5 842.-0.02 NA 0.00
coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction-7.72 342.-0.02 NA 0.00
coef_adult_with_children_in_hh_arrive_19_21-0.00254 0.815-0.00 NA 0.00
coef_arrival_constants_am_peak 4.65 1.75 2.66** NA 0.00
coef_arrival_constants_early 24.8 1.71 14.53*** NA 0.00
coef_arrival_constants_evening-4.29 0.931-4.61*** NA 0.00
coef_arrival_constants_late-9.62 1.70-5.65*** NA 0.00
coef_arrival_constants_midday_1 0.00 NA NA NA 0.00fixed value
coef_arrival_constants_midday_2 2.69 0.752 3.58*** NA 0.00
coef_arrival_constants_pm_peak_1 1.85 0.647 2.86** NA 0.00
coef_arrival_constants_pm_peak_2 1.52 0.532 2.85** NA 0.00
coef_arrival_constants_pm_peak_3 0.00 NA NA NA 0.00fixed value
coef_arrival_constants_pm_peak_4-1.18 0.567-2.08* NA 0.00
coef_departure_constants_am_peak_1-25.0 NA NA[***] BIG 0.00coef_departure_constants_am_peak_1 ≥ -25.0
coef_departure_constants_am_peak_2-4.24 1.90-2.23* NA 0.00
coef_departure_constants_am_peak_3 0.806 1.29 0.62 NA 0.00
coef_departure_constants_am_peak_4 1.41 0.775 1.82 NA 0.00
coef_departure_constants_early-24.4 1.04-23.39*** NA 0.00
coef_departure_constants_evening-14.6 2.93-4.96*** NA 0.00
coef_departure_constants_late-20.4 42.5-0.48 NA 0.00
coef_departure_constants_midday_1 0.00 NA NA NA 0.00fixed value
coef_departure_constants_midday_2-4.50 1.17-3.85*** NA 0.00
coef_departure_constants_pm_peak-12.6 2.65-4.77*** NA 0.00
coef_destination_in_cbd_duration_shift_effects 0.572 0.222 2.58** NA 0.00
coef_discretionary_tour_duration_lt_2_hours-1.02 1.10-0.93 NA 0.00
coef_duration_constants_0_to_1_hours-2.75 0.678-4.05*** NA 0.00
coef_duration_constants_11_to_13_hours-6.16 52.7-0.12 NA 0.00
coef_duration_constants_14_to_18_hours-2.80 75.2-0.04 NA 0.00
coef_duration_constants_2_to_3_hours 0.00 NA NA NA 0.00fixed value
coef_duration_constants_4_to_5_hours 0.301 0.552 0.55 NA 0.00
coef_duration_constants_6_to_7_hours 0.144 1.03 0.14 NA 0.00
coef_duration_constants_8_to_10_hours-10.6 198.-0.05 NA 0.00
coef_eat_out_tour_departure_shift_effects-0.0246 0.146-0.17 NA 0.00
coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect-1.33 0.662-2.01* NA 0.00
coef_free_flow_round_trip_auto_time_shift_effects_duration 0.0178 0.00963 1.84 NA 0.00
coef_maintenance_tour_depart_before_7 1.15 1.69 0.68 NA 0.00
coef_maintenance_tour_departure_shift_effects-0.159 0.129-1.23 NA 0.00
coef_maintenance_tour_duration_shift_effects-0.146 0.234-0.62 NA 0.00
coef_number_of_joint_tours_departure_shift_effects 1.36 0.199 6.82*** NA 0.00
coef_number_of_mandatory_tours_departure_shift_effects 0.0763 0.0738 1.03 NA 0.00
coef_school_child_age_16_plus_departure_shift_effects 0.0727 6.26e-07 BIG*** NA 0.00
coef_school_child_age_16_plus_duration_shift_effects 0.209 2.94e-07 BIG*** NA 0.00
coef_school_child_age_under_16_departure_shift_effects 0.239 0.289 0.83 NA 0.00
coef_school_child_age_under_16_duration_shift_effects-0.568 0.535-1.06 NA 0.00
coef_school_child_under_16_arrive_after_22-6.15 102.-0.06 NA 0.00
coef_shopping_tour_arrive_after_22-7.22 118.-0.06 NA 0.00
coef_shopping_tour_depart_before_8 1.46 2.09 0.70 NA 0.00
coef_shopping_tour_departure_shift_effects-0.0456 0.177-0.26 NA 0.00
coef_shopping_tour_duration_lt_2_hours 0.189 1.14 0.17 NA 0.00
coef_shopping_tour_duration_shift_effects-0.360 0.344-1.04 NA 0.00
coef_some_previously_scheduled_tour_begins_in_this_arrival_hour 0.412 0.861 0.48 NA 0.00
coef_some_previously_scheduled_tour_ends_in_this_departure_hour 0.282 0.440 0.64 NA 0.00
coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect 0.191 0.745 0.26 NA 0.00
coef_unavailable-999. NA NA NA 0.00fixed value
coef_university_student_arrive_after_22-9.18 675.-0.01 NA 0.00
coef_visit_tour_departure_shift_effects-0.110 0.135-0.81 NA 0.00
coef_visit_tour_duration_shift_effects-0.124 0.317-0.39 NA 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.801 3.59 0.22 0.00
coef_adjacent_window_exists_after_this_arrival_hour_second_tour_interaction 0.494 4.24 0.12 0.00
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.00884 198. 0.00 0.00
coef_adjacent_window_exists_before_this_departure_hour_second_tour_interaction-0.550 1.32-0.42 0.00
coef_adult_with_children_in_hh_arrive_19_21-0.0790 0.205-0.39 0.00
coef_arrival_constants_am_peak-8.41 19.7-0.43 0.00
coef_arrival_constants_early-6.76 19.7-0.34 0.00
coef_arrival_constants_evening-2.68 0.227-11.78*** 0.00
coef_arrival_constants_late-4.19 0.286-14.65*** 0.00
coef_arrival_constants_midday_1 0.00 0.00 NA 0.00fixed value
coef_arrival_constants_midday_2 1.42 0.133 10.62*** 0.00
coef_arrival_constants_pm_peak_1 0.964 0.146 6.59*** 0.00
coef_arrival_constants_pm_peak_2 1.20 0.131 9.17*** 0.00
coef_arrival_constants_pm_peak_3 0.00 0.00 NA 0.00fixed value
coef_arrival_constants_pm_peak_4-0.726 0.157-4.63*** 0.00
coef_departure_constants_am_peak_1-14.0 1.35-10.33*** 0.00
coef_departure_constants_am_peak_2-10.2 0.850-11.96*** 0.00
coef_departure_constants_am_peak_3-2.80 0.381-7.35*** 0.00
coef_departure_constants_am_peak_4 0.514 0.155 3.32*** 0.00
coef_departure_constants_early-17.9 1.63-10.95*** 0.00
coef_departure_constants_evening-19.6 19.7-0.99 0.00
coef_departure_constants_late-21.4 19.7-1.09 0.00
coef_departure_constants_midday_1 0.00 0.00 NA 0.00fixed value
coef_departure_constants_midday_2-1.89 0.244-7.72*** 0.00
coef_departure_constants_pm_peak-18.2 19.7-0.93 0.00
coef_destination_in_cbd_duration_shift_effects 0.131 0.0653 2.01* 0.00
coef_discretionary_tour_duration_lt_2_hours-0.772 0.233-3.32*** 0.00
coef_duration_constants_0_to_1_hours-2.02 0.171-11.83*** 0.00
coef_duration_constants_11_to_13_hours-1.61 0.861-1.87 0.00
coef_duration_constants_14_to_18_hours-3.07 4.80-0.64 0.00
coef_duration_constants_2_to_3_hours 0.00 0.00 NA 0.00fixed value
coef_duration_constants_4_to_5_hours-0.520 0.116-4.49*** 0.00
coef_duration_constants_6_to_7_hours-0.868 0.210-4.13*** 0.00
coef_duration_constants_8_to_10_hours-1.02 0.359-2.84** 0.00
coef_eat_out_tour_departure_shift_effects 0.0566 0.0437 1.29 0.00
coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect-0.507 0.511-0.99 0.00
coef_free_flow_round_trip_auto_time_shift_effects_duration 0.00362 0.00112 3.25** 0.00
coef_maintenance_tour_depart_before_7-0.524 0.819-0.64 0.00
coef_maintenance_tour_departure_shift_effects-0.136 0.0418-3.24** 0.00
coef_maintenance_tour_duration_shift_effects-0.0384 0.0575-0.67 0.00
coef_number_of_joint_tours_departure_shift_effects 0.129 0.0651 1.98* 0.00
coef_number_of_mandatory_tours_departure_shift_effects-0.00979 0.0303-0.32 0.00
coef_school_child_age_16_plus_departure_shift_effects 0.106 0.110 0.96 0.00
coef_school_child_age_16_plus_duration_shift_effects 0.316 0.131 2.40* 0.00
coef_school_child_age_under_16_departure_shift_effects 0.0155 0.0681 0.23 0.00
coef_school_child_age_under_16_duration_shift_effects 0.328 0.0792 4.13*** 0.00
coef_school_child_under_16_arrive_after_22-5.04 4.37-1.15 0.00
coef_shopping_tour_arrive_after_22-0.0333 0.576-0.06 0.00
coef_shopping_tour_depart_before_8-1.48 1.11-1.34 0.00
coef_shopping_tour_departure_shift_effects-0.0993 0.0762-1.30 0.00
coef_shopping_tour_duration_lt_2_hours 0.700 0.275 2.54* 0.00
coef_shopping_tour_duration_shift_effects-0.101 0.0665-1.52 0.00
coef_some_previously_scheduled_tour_begins_in_this_arrival_hour-0.0177 0.224-0.08 0.00
coef_some_previously_scheduled_tour_ends_in_this_departure_hour-0.288 0.121-2.38* 0.00
coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect 0.0624 0.340 0.18 0.00
coef_unavailable-999. 0.00 NA 0.00fixed value
coef_university_student_arrive_after_22 0.361 0.694 0.52 0.00
coef_visit_tour_departure_shift_effects 0.137 0.0492 2.78** 0.00
coef_visit_tour_duration_shift_effects 0.172 0.0622 2.77** 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -4257,7 +4392,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -4278,20 +4413,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -4310,7 +4434,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -4355,217 +4479,217 @@ " \n", " 2\n", " coef_free_flow_round_trip_auto_time_shift_effe...\n", - " 0.017752\n", + " 0.003622\n", " F\n", " \n", " \n", " 3\n", " coef_shopping_tour_departure_shift_effects\n", - " -0.045633\n", + " -0.099254\n", " F\n", " \n", " \n", " 4\n", " coef_shopping_tour_duration_shift_effects\n", - " -0.359705\n", + " -0.101207\n", " F\n", " \n", " \n", " 5\n", " coef_maintenance_tour_departure_shift_effects\n", - " -0.159210\n", + " -0.135634\n", " F\n", " \n", " \n", " 6\n", " coef_maintenance_tour_duration_shift_effects\n", - " -0.146459\n", + " -0.038428\n", " F\n", " \n", " \n", " 7\n", " coef_visit_tour_departure_shift_effects\n", - " -0.109515\n", + " 0.136717\n", " F\n", " \n", " \n", " 8\n", " coef_visit_tour_duration_shift_effects\n", - " -0.123814\n", + " 0.172436\n", " F\n", " \n", " \n", " 9\n", " coef_eat_out_tour_departure_shift_effects\n", - " -0.024649\n", + " 0.056578\n", " F\n", " \n", " \n", " 10\n", " coef_school_child_age_16_plus_departure_shift_...\n", - " 0.072660\n", + " 0.106395\n", " F\n", " \n", " \n", " 11\n", " coef_school_child_age_16_plus_duration_shift_e...\n", - " 0.209500\n", + " 0.315781\n", " F\n", " \n", " \n", " 12\n", " coef_school_child_age_under_16_departure_shift...\n", - " 0.239007\n", + " 0.015473\n", " F\n", " \n", " \n", " 13\n", " coef_school_child_age_under_16_duration_shift_...\n", - " -0.567863\n", + " 0.327527\n", " F\n", " \n", " \n", " 14\n", " coef_destination_in_cbd_duration_shift_effects\n", - " 0.572330\n", + " 0.130935\n", " F\n", " \n", " \n", " 15\n", " coef_number_of_mandatory_tours_departure_shift...\n", - " 0.076326\n", + " -0.009788\n", " F\n", " \n", " \n", " 16\n", " coef_number_of_joint_tours_departure_shift_eff...\n", - " 1.356173\n", + " 0.128742\n", " F\n", " \n", " \n", " 17\n", " coef_first_of_2_plus_tours_for_same_purpose_de...\n", - " -1.329351\n", + " -0.506782\n", " F\n", " \n", " \n", " 18\n", " coef_subsequent_of_2_plus_tours_for_same_purpo...\n", - " 0.191264\n", + " 0.062417\n", " F\n", " \n", " \n", " 19\n", " coef_maintenance_tour_depart_before_7\n", - " 1.154584\n", + " -0.523693\n", " F\n", " \n", " \n", " 20\n", " coef_shopping_tour_depart_before_8\n", - " 1.458488\n", + " -1.484109\n", " F\n", " \n", " \n", " 21\n", " coef_shopping_tour_arrive_after_22\n", - " -7.221041\n", + " -0.033268\n", " F\n", " \n", " \n", " 22\n", " coef_school_child_under_16_arrive_after_22\n", - " -6.147237\n", + " -5.038827\n", " F\n", " \n", " \n", " 23\n", " coef_university_student_arrive_after_22\n", - " -9.181095\n", + " 0.360948\n", " F\n", " \n", " \n", " 24\n", " coef_shopping_tour_duration_lt_2_hours\n", - " 0.189427\n", + " 0.699700\n", " F\n", " \n", " \n", " 25\n", " coef_discretionary_tour_duration_lt_2_hours\n", - " -1.022488\n", + " -0.772425\n", " F\n", " \n", " \n", " 26\n", " coef_adult_with_children_in_hh_arrive_19_21\n", - " -0.002541\n", + " -0.078997\n", " F\n", " \n", " \n", " 27\n", " coef_some_previously_scheduled_tour_ends_in_th...\n", - " 0.282029\n", + " -0.288048\n", " F\n", " \n", " \n", " 28\n", " coef_some_previously_scheduled_tour_begins_in_...\n", - " 0.411979\n", + " -0.017681\n", " F\n", " \n", " \n", " 29\n", " coef_adjacent_window_exists_before_this_depart...\n", - " -13.495922\n", + " 0.008839\n", " F\n", " \n", " \n", " 30\n", " coef_adjacent_window_exists_after_this_arrival...\n", - " -13.526580\n", + " 0.800851\n", " F\n", " \n", " \n", " 31\n", " coef_adjacent_window_exists_before_this_depart...\n", - " -7.716247\n", + " -0.549692\n", " F\n", " \n", " \n", " 32\n", " coef_adjacent_window_exists_after_this_arrival...\n", - " -14.169341\n", + " 0.494438\n", " F\n", " \n", " \n", " 33\n", " coef_departure_constants_early\n", - " -24.418086\n", + " -17.865880\n", " F\n", " \n", " \n", " 34\n", " coef_departure_constants_am_peak_1\n", - " -25.000000\n", + " -13.990759\n", " F\n", " \n", " \n", " 35\n", " coef_departure_constants_am_peak_2\n", - " -4.236849\n", + " -10.163788\n", " F\n", " \n", " \n", " 36\n", " coef_departure_constants_am_peak_3\n", - " 0.806223\n", + " -2.799430\n", " F\n", " \n", " \n", " 37\n", " coef_departure_constants_am_peak_4\n", - " 1.408142\n", + " 0.514393\n", " F\n", " \n", " \n", @@ -4577,37 +4701,37 @@ " \n", " 39\n", " coef_departure_constants_midday_2\n", - " -4.501238\n", + " -1.886316\n", " F\n", " \n", " \n", " 40\n", " coef_departure_constants_pm_peak\n", - " -12.638403\n", + " -18.238556\n", " F\n", " \n", " \n", " 41\n", " coef_departure_constants_evening\n", - " -14.557517\n", + " -19.574287\n", " F\n", " \n", " \n", " 42\n", " coef_departure_constants_late\n", - " -20.421814\n", + " -21.444922\n", " F\n", " \n", " \n", " 43\n", " coef_arrival_constants_early\n", - " 24.793142\n", + " -6.758955\n", " F\n", " \n", " \n", " 44\n", " coef_arrival_constants_am_peak\n", - " 4.647673\n", + " -8.413713\n", " F\n", " \n", " \n", @@ -4619,19 +4743,19 @@ " \n", " 46\n", " coef_arrival_constants_midday_2\n", - " 2.692519\n", + " 1.416723\n", " F\n", " \n", " \n", " 47\n", " coef_arrival_constants_pm_peak_1\n", - " 1.849237\n", + " 0.964024\n", " F\n", " \n", " \n", " 48\n", " coef_arrival_constants_pm_peak_2\n", - " 1.518410\n", + " 1.200835\n", " F\n", " \n", " \n", @@ -4643,25 +4767,25 @@ " \n", " 50\n", " coef_arrival_constants_pm_peak_4\n", - " -1.182768\n", + " -0.725959\n", " F\n", " \n", " \n", " 51\n", " coef_arrival_constants_evening\n", - " -4.291783\n", + " -2.675953\n", " F\n", " \n", " \n", " 52\n", " coef_arrival_constants_late\n", - " -9.617038\n", + " -4.194942\n", " F\n", " \n", " \n", " 53\n", " coef_duration_constants_0_to_1_hours\n", - " -2.750481\n", + " -2.021348\n", " F\n", " \n", " \n", @@ -4673,31 +4797,31 @@ " \n", " 55\n", " coef_duration_constants_4_to_5_hours\n", - " 0.301145\n", + " -0.519561\n", " F\n", " \n", " \n", " 56\n", " coef_duration_constants_6_to_7_hours\n", - " 0.144072\n", + " -0.868309\n", " F\n", " \n", " \n", " 57\n", " coef_duration_constants_8_to_10_hours\n", - " -10.570858\n", + " -1.020095\n", " F\n", " \n", " \n", " 58\n", " coef_duration_constants_11_to_13_hours\n", - " -6.162737\n", + " -1.608105\n", " F\n", " \n", " \n", " 59\n", " coef_duration_constants_14_to_18_hours\n", - " -2.800706\n", + " -3.067613\n", " F\n", " \n", " \n", @@ -4708,67 +4832,67 @@ " coefficient_name value constrain\n", "0 coef_dummy 1.000000 T\n", "1 coef_unavailable -999.000000 T\n", - "2 coef_free_flow_round_trip_auto_time_shift_effe... 0.017752 F\n", - "3 coef_shopping_tour_departure_shift_effects -0.045633 F\n", - "4 coef_shopping_tour_duration_shift_effects -0.359705 F\n", - "5 coef_maintenance_tour_departure_shift_effects -0.159210 F\n", - "6 coef_maintenance_tour_duration_shift_effects -0.146459 F\n", - "7 coef_visit_tour_departure_shift_effects -0.109515 F\n", - "8 coef_visit_tour_duration_shift_effects -0.123814 F\n", - "9 coef_eat_out_tour_departure_shift_effects -0.024649 F\n", - "10 coef_school_child_age_16_plus_departure_shift_... 0.072660 F\n", - "11 coef_school_child_age_16_plus_duration_shift_e... 0.209500 F\n", - "12 coef_school_child_age_under_16_departure_shift... 0.239007 F\n", - "13 coef_school_child_age_under_16_duration_shift_... -0.567863 F\n", - "14 coef_destination_in_cbd_duration_shift_effects 0.572330 F\n", - "15 coef_number_of_mandatory_tours_departure_shift... 0.076326 F\n", - "16 coef_number_of_joint_tours_departure_shift_eff... 1.356173 F\n", - "17 coef_first_of_2_plus_tours_for_same_purpose_de... -1.329351 F\n", - "18 coef_subsequent_of_2_plus_tours_for_same_purpo... 0.191264 F\n", - "19 coef_maintenance_tour_depart_before_7 1.154584 F\n", - "20 coef_shopping_tour_depart_before_8 1.458488 F\n", - "21 coef_shopping_tour_arrive_after_22 -7.221041 F\n", - "22 coef_school_child_under_16_arrive_after_22 -6.147237 F\n", - "23 coef_university_student_arrive_after_22 -9.181095 F\n", - "24 coef_shopping_tour_duration_lt_2_hours 0.189427 F\n", - "25 coef_discretionary_tour_duration_lt_2_hours -1.022488 F\n", - "26 coef_adult_with_children_in_hh_arrive_19_21 -0.002541 F\n", - "27 coef_some_previously_scheduled_tour_ends_in_th... 0.282029 F\n", - "28 coef_some_previously_scheduled_tour_begins_in_... 0.411979 F\n", - "29 coef_adjacent_window_exists_before_this_depart... -13.495922 F\n", - "30 coef_adjacent_window_exists_after_this_arrival... -13.526580 F\n", - "31 coef_adjacent_window_exists_before_this_depart... -7.716247 F\n", - "32 coef_adjacent_window_exists_after_this_arrival... -14.169341 F\n", - "33 coef_departure_constants_early -24.418086 F\n", - "34 coef_departure_constants_am_peak_1 -25.000000 F\n", - "35 coef_departure_constants_am_peak_2 -4.236849 F\n", - "36 coef_departure_constants_am_peak_3 0.806223 F\n", - "37 coef_departure_constants_am_peak_4 1.408142 F\n", + "2 coef_free_flow_round_trip_auto_time_shift_effe... 0.003622 F\n", + "3 coef_shopping_tour_departure_shift_effects -0.099254 F\n", + "4 coef_shopping_tour_duration_shift_effects -0.101207 F\n", + "5 coef_maintenance_tour_departure_shift_effects -0.135634 F\n", + "6 coef_maintenance_tour_duration_shift_effects -0.038428 F\n", + "7 coef_visit_tour_departure_shift_effects 0.136717 F\n", + "8 coef_visit_tour_duration_shift_effects 0.172436 F\n", + "9 coef_eat_out_tour_departure_shift_effects 0.056578 F\n", + "10 coef_school_child_age_16_plus_departure_shift_... 0.106395 F\n", + "11 coef_school_child_age_16_plus_duration_shift_e... 0.315781 F\n", + "12 coef_school_child_age_under_16_departure_shift... 0.015473 F\n", + "13 coef_school_child_age_under_16_duration_shift_... 0.327527 F\n", + "14 coef_destination_in_cbd_duration_shift_effects 0.130935 F\n", + "15 coef_number_of_mandatory_tours_departure_shift... -0.009788 F\n", + "16 coef_number_of_joint_tours_departure_shift_eff... 0.128742 F\n", + "17 coef_first_of_2_plus_tours_for_same_purpose_de... -0.506782 F\n", + "18 coef_subsequent_of_2_plus_tours_for_same_purpo... 0.062417 F\n", + "19 coef_maintenance_tour_depart_before_7 -0.523693 F\n", + "20 coef_shopping_tour_depart_before_8 -1.484109 F\n", + "21 coef_shopping_tour_arrive_after_22 -0.033268 F\n", + "22 coef_school_child_under_16_arrive_after_22 -5.038827 F\n", + "23 coef_university_student_arrive_after_22 0.360948 F\n", + "24 coef_shopping_tour_duration_lt_2_hours 0.699700 F\n", + "25 coef_discretionary_tour_duration_lt_2_hours -0.772425 F\n", + "26 coef_adult_with_children_in_hh_arrive_19_21 -0.078997 F\n", + "27 coef_some_previously_scheduled_tour_ends_in_th... -0.288048 F\n", + "28 coef_some_previously_scheduled_tour_begins_in_... -0.017681 F\n", + "29 coef_adjacent_window_exists_before_this_depart... 0.008839 F\n", + "30 coef_adjacent_window_exists_after_this_arrival... 0.800851 F\n", + "31 coef_adjacent_window_exists_before_this_depart... -0.549692 F\n", + "32 coef_adjacent_window_exists_after_this_arrival... 0.494438 F\n", + "33 coef_departure_constants_early -17.865880 F\n", + "34 coef_departure_constants_am_peak_1 -13.990759 F\n", + "35 coef_departure_constants_am_peak_2 -10.163788 F\n", + "36 coef_departure_constants_am_peak_3 -2.799430 F\n", + "37 coef_departure_constants_am_peak_4 0.514393 F\n", "38 coef_departure_constants_midday_1 0.000000 T\n", - "39 coef_departure_constants_midday_2 -4.501238 F\n", - "40 coef_departure_constants_pm_peak -12.638403 F\n", - "41 coef_departure_constants_evening -14.557517 F\n", - "42 coef_departure_constants_late -20.421814 F\n", - "43 coef_arrival_constants_early 24.793142 F\n", - "44 coef_arrival_constants_am_peak 4.647673 F\n", + "39 coef_departure_constants_midday_2 -1.886316 F\n", + "40 coef_departure_constants_pm_peak -18.238556 F\n", + "41 coef_departure_constants_evening -19.574287 F\n", + "42 coef_departure_constants_late -21.444922 F\n", + "43 coef_arrival_constants_early -6.758955 F\n", + "44 coef_arrival_constants_am_peak -8.413713 F\n", "45 coef_arrival_constants_midday_1 0.000000 T\n", - "46 coef_arrival_constants_midday_2 2.692519 F\n", - "47 coef_arrival_constants_pm_peak_1 1.849237 F\n", - "48 coef_arrival_constants_pm_peak_2 1.518410 F\n", + "46 coef_arrival_constants_midday_2 1.416723 F\n", + "47 coef_arrival_constants_pm_peak_1 0.964024 F\n", + "48 coef_arrival_constants_pm_peak_2 1.200835 F\n", "49 coef_arrival_constants_pm_peak_3 0.000000 T\n", - "50 coef_arrival_constants_pm_peak_4 -1.182768 F\n", - "51 coef_arrival_constants_evening -4.291783 F\n", - "52 coef_arrival_constants_late -9.617038 F\n", - "53 coef_duration_constants_0_to_1_hours -2.750481 F\n", + "50 coef_arrival_constants_pm_peak_4 -0.725959 F\n", + "51 coef_arrival_constants_evening -2.675953 F\n", + "52 coef_arrival_constants_late -4.194942 F\n", + "53 coef_duration_constants_0_to_1_hours -2.021348 F\n", "54 coef_duration_constants_2_to_3_hours 0.000000 T\n", - "55 coef_duration_constants_4_to_5_hours 0.301145 F\n", - "56 coef_duration_constants_6_to_7_hours 0.144072 F\n", - "57 coef_duration_constants_8_to_10_hours -10.570858 F\n", - "58 coef_duration_constants_11_to_13_hours -6.162737 F\n", - "59 coef_duration_constants_14_to_18_hours -2.800706 F" + "55 coef_duration_constants_4_to_5_hours -0.519561 F\n", + "56 coef_duration_constants_6_to_7_hours -0.868309 F\n", + "57 coef_duration_constants_8_to_10_hours -1.020095 F\n", + "58 coef_duration_constants_11_to_13_hours -1.608105 F\n", + "59 coef_duration_constants_14_to_18_hours -3.067613 F" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -4785,7 +4909,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -4799,7 +4923,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/15_non_mand_tour_freq.ipynb b/activitysim/examples/example_estimation/notebooks/15_non_mand_tour_freq.ipynb index 81092083fc..933656370f 100644 --- a/activitysim/examples/example_estimation/notebooks/15_non_mand_tour_freq.ipynb +++ b/activitysim/examples/example_estimation/notebooks/15_non_mand_tour_freq.ipynb @@ -35,10 +35,22 @@ "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, { "data": { "text/plain": [ - "'1.1.0'" + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" ] }, "execution_count": 1, @@ -47,27 +59,49 @@ } ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", + "import larch as lx\n", "import pandas as pd\n", - "import activitysim\n", - "activitysim.__version__" + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -81,12 +115,67 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading EDB for PTYPE_FULL segment\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_FULL/non_mandatory_tour_frequency_coefficients_PTYPE_FULL.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_FULL/non_mandatory_tour_frequency_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_FULL/non_mandatory_tour_frequency_interaction_expression_values.parquet\n", + "Loading EDB for PTYPE_PART segment\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_PART/non_mandatory_tour_frequency_coefficients_PTYPE_PART.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_PART/non_mandatory_tour_frequency_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_PART/non_mandatory_tour_frequency_interaction_expression_values.parquet\n", + "Loading EDB for PTYPE_UNIVERSITY segment\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_UNIVERSITY/non_mandatory_tour_frequency_coefficients_PTYPE_UNIVERSITY.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_UNIVERSITY/non_mandatory_tour_frequency_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_UNIVERSITY/non_mandatory_tour_frequency_interaction_expression_values.parquet\n", + "Loading EDB for PTYPE_NONWORK segment\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_NONWORK/non_mandatory_tour_frequency_coefficients_PTYPE_NONWORK.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_NONWORK/non_mandatory_tour_frequency_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_NONWORK/non_mandatory_tour_frequency_interaction_expression_values.parquet\n", + "Loading EDB for PTYPE_RETIRED segment\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_RETIRED/non_mandatory_tour_frequency_coefficients_PTYPE_RETIRED.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_RETIRED/non_mandatory_tour_frequency_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_RETIRED/non_mandatory_tour_frequency_interaction_expression_values.parquet\n", + "Loading EDB for PTYPE_DRIVING segment\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_DRIVING/non_mandatory_tour_frequency_coefficients_PTYPE_DRIVING.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_DRIVING/non_mandatory_tour_frequency_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_DRIVING/non_mandatory_tour_frequency_interaction_expression_values.parquet\n", + "Loading EDB for PTYPE_SCHOOL segment\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_SCHOOL/non_mandatory_tour_frequency_coefficients_PTYPE_SCHOOL.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_SCHOOL/non_mandatory_tour_frequency_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_SCHOOL/non_mandatory_tour_frequency_interaction_expression_values.parquet\n", + "Loading EDB for PTYPE_PRESCHOOL segment\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_PRESCHOOL/non_mandatory_tour_frequency_coefficients_PTYPE_PRESCHOOL.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_PRESCHOOL/non_mandatory_tour_frequency_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_PRESCHOOL/non_mandatory_tour_frequency_interaction_expression_values.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_FULL/non_mandatory_tour_frequency_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/PTYPE_FULL/non_mandatory_tour_frequency_alternatives.csv\n", + "Creating larch model for PTYPE_FULL\n", + "Creating larch model for PTYPE_PART\n", + "Creating larch model for PTYPE_UNIVERSITY\n", + "Creating larch model for PTYPE_NONWORK\n", + "Creating larch model for PTYPE_RETIRED\n", + "Creating larch model for PTYPE_DRIVING\n", + "Creating larch model for PTYPE_SCHOOL\n", + "Creating larch model for PTYPE_PRESCHOOL\n" + ] + } + ], "source": [ "modelname = \"nonmand_tour_freq\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True, condense_parameters=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/non_mandatory_tour_frequency/\",\n", + " return_data=True,\n", + " condense_parameters=True,\n", + ")" ] }, { @@ -383,20 +472,20 @@ " \n", " \n", " 0\n", - " 72241\n", + " 72355\n", " 0\n", " 0\n", - " 72241\n", - " 56\n", - " 1\n", + " 72355\n", + " 52\n", " 1\n", + " 2\n", " 1\n", " 3\n", " 1\n", " ...\n", " False\n", " False\n", - " 0\n", + " 1\n", " 0\n", " 0\n", " 0\n", @@ -407,13 +496,13 @@ " \n", " \n", " 1\n", - " 72441\n", + " 72384\n", " 0\n", " 0\n", - " 72441\n", - " 49\n", - " 1\n", + " 72384\n", + " 28\n", " 1\n", + " 2\n", " 1\n", " 3\n", " 1\n", @@ -431,11 +520,11 @@ " \n", " \n", " 2\n", - " 73144\n", - " 0\n", + " 72407\n", + " 1\n", " 0\n", - " 73144\n", - " 31\n", + " 72407\n", + " 52\n", " 1\n", " 2\n", " 1\n", @@ -443,8 +532,8 @@ " 1\n", " ...\n", " False\n", - " True\n", - " -1\n", + " False\n", + " 0\n", " 0\n", " 0\n", " 0\n", @@ -455,20 +544,20 @@ " \n", " \n", " 3\n", - " 73493\n", + " 72459\n", " 0\n", " 0\n", - " 73493\n", - " 31\n", + " 72459\n", + " 38\n", + " 1\n", " 1\n", - " 2\n", " 1\n", " 3\n", " 1\n", " ...\n", " False\n", - " False\n", - " 0\n", + " True\n", + " -1\n", " 0\n", " 0\n", " 0\n", @@ -479,11 +568,11 @@ " \n", " \n", " 4\n", - " 73706\n", - " 0\n", - " 0\n", - " 73706\n", - " 26\n", + " 72569\n", + " 1\n", + " 20\n", + " 72569\n", + " 49\n", " 1\n", " 1\n", " 1\n", @@ -491,14 +580,14 @@ " 1\n", " ...\n", " False\n", - " False\n", + " True\n", + " -1\n", " 0\n", " 0\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 1\n", " 0\n", " \n", " \n", @@ -526,14 +615,14 @@ " ...\n", " \n", " \n", - " 1759\n", - " 7512288\n", - " 5\n", - " 5\n", - " 2820953\n", - " 28\n", - " 1\n", + " 19354\n", + " 7538573\n", + " 0\n", + " 0\n", + " 2847238\n", + " 67\n", " 1\n", + " 2\n", " 1\n", " 3\n", " 1\n", @@ -546,18 +635,18 @@ " 0\n", " 0\n", " 0\n", - " 0\n", + " 1\n", " 0\n", " \n", " \n", - " 1760\n", - " 7512469\n", + " 19355\n", + " 7538990\n", " 1\n", + " 19\n", + " 2847655\n", + " 72\n", " 1\n", - " 2821134\n", - " 34\n", " 1\n", - " 2\n", " 1\n", " 3\n", " 1\n", @@ -570,16 +659,16 @@ " 0\n", " 0\n", " 0\n", - " 1\n", + " 0\n", " 0\n", " \n", " \n", - " 1761\n", - " 7513117\n", + " 19356\n", + " 7539071\n", " 0\n", " 0\n", - " 2821782\n", - " 16\n", + " 2847736\n", + " 70\n", " 1\n", " 1\n", " 1\n", @@ -587,8 +676,8 @@ " 1\n", " ...\n", " False\n", - " True\n", - " -1\n", + " False\n", + " 1\n", " 0\n", " 0\n", " 0\n", @@ -598,12 +687,12 @@ " 0\n", " \n", " \n", - " 1762\n", - " 7513996\n", + " 19357\n", + " 7539203\n", " 0\n", " 0\n", - " 2822661\n", - " 24\n", + " 2847868\n", + " 87\n", " 1\n", " 1\n", " 1\n", @@ -622,21 +711,21 @@ " 0\n", " \n", " \n", - " 1763\n", - " 7514404\n", + " 19358\n", + " 7539317\n", " 0\n", " 0\n", - " 2823069\n", - " 30\n", + " 2847982\n", + " 70\n", + " 1\n", " 1\n", - " 2\n", " 1\n", " 3\n", " 1\n", " ...\n", " False\n", - " True\n", - " -1\n", + " False\n", + " 0\n", " 0\n", " 0\n", " 0\n", @@ -647,76 +736,76 @@ " \n", " \n", "\n", - "

1764 rows × 142 columns

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+       "  * person_id                                                                    (person_id) int64 155kB ...\n",
+       "  * alt_id                                                                       (alt_id) int64 768B ...\n",
+       "Data variables: (12/353)\n",
+       "    index                                                                        (person_id, alt_id) int64 15MB ...\n",
+       "    util_escorting_tour                                                          (person_id, alt_id) int64 15MB ...\n",
+       "    util_discretionary_tour                                                      (person_id, alt_id) int64 15MB ...\n",
+       "    util_shopping_tour                                                           (person_id, alt_id) int64 15MB ...\n",
+       "    util_maintenance_tour                                                        (person_id, alt_id) int64 15MB ...\n",
+       "    util_visiting_or_social_tour                                                 (person_id, alt_id) int64 15MB ...\n",
+       "    ...                                                                           ...\n",
+       "    num_hh_joint_eatout_tours                                                    (person_id) int8 19kB ...\n",
+       "    num_hh_joint_maint_tours                                                     (person_id) int8 19kB ...\n",
+       "    num_hh_joint_social_tours                                                    (person_id) int8 19kB ...\n",
+       "    num_hh_joint_othdiscr_tours                                                  (person_id) int8 19kB ...\n",
+       "    has_mandatory_tour                                                           (person_id) int64 155kB ...\n",
+       "    has_joint_tour                                                               (person_id) int64 155kB ...\n",
+       "Attributes:\n",
+       "    _caseid_:  person_id\n",
+       "    _altid_:   alt_id
" + ], + "text/plain": [ + " Size: 2GB\n", + "Dimensions: (\n", + " person_id: 19359,\n", + " alt_id: 96)\n", + "Coordinates:\n", + " * person_id (person_id) int64 155kB ...\n", + " * alt_id (alt_id) int64 768B ...\n", + "Data variables: (12/353)\n", + " index (person_id, alt_id) int64 15MB ...\n", + " util_escorting_tour (person_id, alt_id) int64 15MB ...\n", + " util_discretionary_tour (person_id, alt_id) int64 15MB ...\n", + " util_shopping_tour (person_id, alt_id) int64 15MB ...\n", + " util_maintenance_tour (person_id, alt_id) int64 15MB ...\n", + " util_visiting_or_social_tour (person_id, alt_id) int64 15MB ...\n", + " ... ...\n", + " num_hh_joint_eatout_tours (person_id) int8 19kB ...\n", + " num_hh_joint_maint_tours (person_id) int8 19kB ...\n", + " num_hh_joint_social_tours (person_id) int8 19kB ...\n", + " num_hh_joint_othdiscr_tours (person_id) int8 19kB ...\n", + " has_mandatory_tour (person_id) int64 155kB ...\n", + " has_joint_tour (person_id) int64 155kB ...\n", + "Attributes:\n", + " _caseid_: person_id\n", + " _altid_: alt_id" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model['PTYPE_FULL'].datatree.root_dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -768,27 +2747,29 @@ "source": [ "For future estimation work, parameters can be intelligently named and applied to match the model developer's desired structure (by using the same named parameter for multiple rows of the spec file). If this is done, the \"short cut\" should be disabled by setting `condense_parameters=False` in the loading step above.\n", "\n", - "Larch has a built-in estimation methods including BHHH, and also offers access to more advanced general purpose non-linear optimizers in the `scipy` package, including SLSQP, which allows for bounds and constraints on parameters. BHHH is the default and typically runs faster, but does not follow constraints on parameters." + "Larch has a built-in estimation methods including BHHH, and also offers access to more advanced general purpose non-linear optimizers in the `scipy` package, including SLSQP, which allows for bounds and constraints on parameters. BHHH is the default and typically runs faster, but does not follow constraints on parameters.\n", + "\n", + "For this model, we will sequentially estimate the models by person type and then save and clear the results, to avoid running out of memory, as the models are large and use a lot of resources. " ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": { "scrolled": false }, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "Model PTYPE_FULL\n" ] }, { "data": { "text/html": [ - "

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" ], "text/plain": [ "" @@ -800,7 +2781,7 @@ { "data": { "text/html": [ - "

Best LL = -1831.0744991680774

" + "

Best LL = -19916.199393036724

" ], "text/plain": [ "" @@ -831,70 +2812,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_0_auto_household_and_escorting_tour\n", " -2.000000\n", + " -2.000000\n", " -2.0000\n", - " 0.0\n", " -2.0\n", " -2.0\n", + " 0.0\n", " 1\n", - " \n", - " -2.000000\n", " \n", " \n", " coef_1_escort_tour_constant\n", - " 0.319037\n", + " -0.065728\n", + " -0.065728\n", " 0.0298\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.319037\n", " \n", " \n", " coef_1_plus_eating_out_tours_constant\n", - " -1.012856\n", + " 0.047768\n", + " 0.047768\n", " 0.0097\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.012856\n", " \n", " \n", " coef_1_plus_maintenance_tours_constant\n", - " -2.842643\n", + " 0.079776\n", + " 0.079776\n", " 0.1202\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.842643\n", " \n", " \n", " coef_1_plus_other_discretionary_tours_constant\n", - " 10.543979\n", + " 0.733799\n", + " 0.733799\n", " 0.7412\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 10.543979\n", " \n", " \n", " ...\n", @@ -905,122 +2890,120 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", " coef_walk_access_to_retail_and_discretionary\n", - " 0.160520\n", + " 0.060958\n", + " 0.060958\n", " 0.0567\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.160520\n", " \n", " \n", " coef_walk_access_to_retail_and_eating_out\n", - " 0.211289\n", + " 0.156964\n", + " 0.156964\n", " 0.1450\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.211289\n", " \n", " \n", " coef_walk_access_to_retail_and_escorting\n", - " -0.105285\n", + " 0.066031\n", + " 0.066031\n", " 0.0451\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.105285\n", " \n", " \n", " coef_walk_access_to_retail_and_shopping\n", - " 0.030182\n", + " 0.031695\n", + " 0.031695\n", " 0.0330\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.030182\n", " \n", " \n", " coef_zero_car_ownership_and_tour_frequency_is_5_plus\n", - " -0.227492\n", + " -0.239893\n", + " -0.239893\n", " -0.3486\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.227492\n", " \n", " \n", "\n", - "

72 rows × 8 columns

\n", + "

72 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_0_auto_household_and_escorting_tour -2.000000 -2.0000 \n", - "coef_1_escort_tour_constant 0.319037 0.0298 \n", - "coef_1_plus_eating_out_tours_constant -1.012856 0.0097 \n", - "coef_1_plus_maintenance_tours_constant -2.842643 0.1202 \n", - "coef_1_plus_other_discretionary_tours_constant 10.543979 0.7412 \n", - "... ... ... \n", - "coef_walk_access_to_retail_and_discretionary 0.160520 0.0567 \n", - "coef_walk_access_to_retail_and_eating_out 0.211289 0.1450 \n", - "coef_walk_access_to_retail_and_escorting -0.105285 0.0451 \n", - "coef_walk_access_to_retail_and_shopping 0.030182 0.0330 \n", - "coef_zero_car_ownership_and_tour_frequency_is_5... -0.227492 -0.3486 \n", + " value best \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.000000 \n", + "coef_1_escort_tour_constant -0.065728 -0.065728 \n", + "coef_1_plus_eating_out_tours_constant 0.047768 0.047768 \n", + "coef_1_plus_maintenance_tours_constant 0.079776 0.079776 \n", + "coef_1_plus_other_discretionary_tours_constant 0.733799 0.733799 \n", + "... ... ... \n", + "coef_walk_access_to_retail_and_discretionary 0.060958 0.060958 \n", + "coef_walk_access_to_retail_and_eating_out 0.156964 0.156964 \n", + "coef_walk_access_to_retail_and_escorting 0.066031 0.066031 \n", + "coef_walk_access_to_retail_and_shopping 0.031695 0.031695 \n", + "coef_zero_car_ownership_and_tour_frequency_is_5... -0.239893 -0.239893 \n", "\n", - " nullvalue minimum \\\n", - "coef_0_auto_household_and_escorting_tour 0.0 -2.0 \n", - "coef_1_escort_tour_constant 0.0 NaN \n", - "coef_1_plus_eating_out_tours_constant 0.0 NaN \n", - "coef_1_plus_maintenance_tours_constant 0.0 NaN \n", - "coef_1_plus_other_discretionary_tours_constant 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0000 -2.0 \n", + "coef_1_escort_tour_constant 0.0298 -20.0 \n", + "coef_1_plus_eating_out_tours_constant 0.0097 -20.0 \n", + "coef_1_plus_maintenance_tours_constant 0.1202 -20.0 \n", + "coef_1_plus_other_discretionary_tours_constant 0.7412 -20.0 \n", "... ... ... \n", - "coef_walk_access_to_retail_and_discretionary 0.0 NaN \n", - "coef_walk_access_to_retail_and_eating_out 0.0 NaN \n", - "coef_walk_access_to_retail_and_escorting 0.0 NaN \n", - "coef_walk_access_to_retail_and_shopping 0.0 NaN \n", - "coef_zero_car_ownership_and_tour_frequency_is_5... 0.0 NaN \n", + "coef_walk_access_to_retail_and_discretionary 0.0567 -20.0 \n", + "coef_walk_access_to_retail_and_eating_out 0.1450 -20.0 \n", + "coef_walk_access_to_retail_and_escorting 0.0451 -20.0 \n", + "coef_walk_access_to_retail_and_shopping 0.0330 -20.0 \n", + "coef_zero_car_ownership_and_tour_frequency_is_5... -0.3486 -20.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_0_auto_household_and_escorting_tour -2.0 1 \n", - "coef_1_escort_tour_constant NaN 0 \n", - "coef_1_plus_eating_out_tours_constant NaN 0 \n", - "coef_1_plus_maintenance_tours_constant NaN 0 \n", - "coef_1_plus_other_discretionary_tours_constant NaN 0 \n", - "... ... ... ... \n", - "coef_walk_access_to_retail_and_discretionary NaN 0 \n", - "coef_walk_access_to_retail_and_eating_out NaN 0 \n", - "coef_walk_access_to_retail_and_escorting NaN 0 \n", - "coef_walk_access_to_retail_and_shopping NaN 0 \n", - "coef_zero_car_ownership_and_tour_frequency_is_5... NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0 0.0 \n", + "coef_1_escort_tour_constant 20.0 0.0 \n", + "coef_1_plus_eating_out_tours_constant 20.0 0.0 \n", + "coef_1_plus_maintenance_tours_constant 20.0 0.0 \n", + "coef_1_plus_other_discretionary_tours_constant 20.0 0.0 \n", + "... ... ... \n", + "coef_walk_access_to_retail_and_discretionary 20.0 0.0 \n", + "coef_walk_access_to_retail_and_eating_out 20.0 0.0 \n", + "coef_walk_access_to_retail_and_escorting 20.0 0.0 \n", + "coef_walk_access_to_retail_and_shopping 20.0 0.0 \n", + "coef_zero_car_ownership_and_tour_frequency_is_5... 20.0 0.0 \n", "\n", - " best \n", - "coef_0_auto_household_and_escorting_tour -2.000000 \n", - "coef_1_escort_tour_constant 0.319037 \n", - "coef_1_plus_eating_out_tours_constant -1.012856 \n", - "coef_1_plus_maintenance_tours_constant -2.842643 \n", - "coef_1_plus_other_discretionary_tours_constant 10.543979 \n", - "... ... \n", - "coef_walk_access_to_retail_and_discretionary 0.160520 \n", - "coef_walk_access_to_retail_and_eating_out 0.211289 \n", - "coef_walk_access_to_retail_and_escorting -0.105285 \n", - "coef_walk_access_to_retail_and_shopping 0.030182 \n", - "coef_zero_car_ownership_and_tour_frequency_is_5... -0.227492 \n", + " holdfast \n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 1 \n", + "coef_1_escort_tour_constant 0 \n", + "coef_1_plus_eating_out_tours_constant 0 \n", + "coef_1_plus_maintenance_tours_constant 0 \n", + "coef_1_plus_other_discretionary_tours_constant 0 \n", + "... ... \n", + "coef_walk_access_to_retail_and_discretionary 0 \n", + "coef_walk_access_to_retail_and_eating_out 0 \n", + "coef_walk_access_to_retail_and_escorting 0 \n", + "coef_walk_access_to_retail_and_shopping 0 \n", + "coef_zero_car_ownership_and_tour_frequency_is_5... 0 \n", "\n", - "[72 rows x 8 columns]" + "[72 rows x 7 columns]" ] }, "metadata": {}, @@ -1030,24 +3013,717 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " m.estimate(method='SLSQP')\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/linalg/__init__.py:18: UserWarning: minimum eig 5.456681257677148e-07 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model seems to have 3 parameter estimators with negative variance\n", - "- coef_1_escort_tour_constant\n", - "- coef_2_plus_escort_tours_constant\n", - "- coef_urban_and_escorting_tour\n", - " m.estimate(method='SLSQP')\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: RuntimeWarning: invalid value encountered in sqrt\n", - " m.estimate(method='SLSQP')\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { "data": { "text/html": [ - "

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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_0_auto_household_and_escorting_tour-2.00 0.00 NA 0.00fixed value
coef_1_escort_tour_constant-0.0657 49.6-0.00 0.00
coef_1_plus_eating_out_tours_constant 0.0478 49.6 0.00 0.00
coef_1_plus_maintenance_tours_constant 0.0798 49.6 0.00 0.00
coef_1_plus_other_discretionary_tours_constant 0.734 49.6 0.01 0.00
coef_1_plus_shopping_tours_constant 0.360 49.6 0.01 0.00
coef_1_plus_visting_tours_constant-0.0190 49.6-0.00 0.00
coef_2_plus_escort_tours_constant 0.688 99.2 0.01 0.00
coef_at_home_pre_driving_school_kid_and_escorting_tour-0.471 0.160-2.94** 0.00
coef_at_home_pre_school_kid_and_discretionary_tour-0.223 0.186-1.20 0.00
coef_at_home_pre_school_kid_and_escorting_tour-1.53 0.227-6.75*** 0.00
coef_auto_access_to_retail_and_discretionary 0.0857 0.0630 1.36 0.00
coef_auto_access_to_retail_and_maintenance 0.0843 0.0587 1.44 0.00
coef_auto_access_to_retail_and_shopping 0.103 0.0604 1.71 0.00
coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus 0.120 0.0470 2.55* 0.00
coef_female_and_escorting_tour 0.177 0.0645 2.74** 0.00
coef_female_and_tour_frequency_is_1-0.0844 0.0430-1.96* 0.00
coef_female_and_tour_frequency_is_2-0.0975 0.0857-1.14 0.00
coef_female_and_tour_frequency_is_5-0.446 0.180-2.47* 0.00
coef_high_income_group_and_discretionary_tour 0.213 0.0780 2.74** 0.00
coef_high_income_group_and_eating_out_tour 0.384 0.0963 3.99*** 0.00
coef_high_income_group_and_tour_frequency_is_1 0.355 0.114 3.12** 0.00
coef_high_income_group_and_tour_frequency_is_2 0.990 0.240 4.12*** 0.00
coef_high_income_group_and_tour_frequency_is_5_plus 1.29 0.555 2.32* 0.00
coef_high_income_group_and_visiting_tour-0.228 0.122-1.87 0.00
coef_logged_maximum_residual_window_tour_frequency_is_1 1.28 0.0731 17.53*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_2 1.45 0.0918 15.83*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_5_plus 1.43 0.142 10.06*** 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_1 0.376 0.110 3.42*** 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_2 0.794 0.235 3.38*** 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_5_plus 1.03 0.548 1.88 0.00
coef_number_of_joint_eating_out_tours-0.618 0.529-1.17 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_2-1.07 0.158-6.75*** 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus-2.50 0.307-8.15*** 0.00
coef_presence_of_driving_school_kid_and_discretionary_tour-0.364 0.128-2.84** 0.00
coef_presence_of_driving_school_kid_and_escorting_tour 0.429 0.0738 5.81*** 0.00
coef_presence_of_full_time_worker_and_discretionary_tour-0.601 0.0679-8.86*** 0.00
coef_presence_of_full_time_worker_and_eating_out_tour-0.280 0.0777-3.60*** 0.00
coef_presence_of_full_time_worker_and_maintenance_tour-0.264 0.0767-3.45*** 0.00
coef_presence_of_full_time_worker_and_shopping_tour-0.175 0.0618-2.83** 0.00
coef_presence_of_non_worker_and_discretionary_tour-0.484 0.0844-5.73*** 0.00
coef_presence_of_non_worker_and_eating_out_tour-0.172 0.0913-1.88 0.00
coef_presence_of_non_worker_and_escorting_tour-0.476 0.0747-6.37*** 0.00
coef_presence_of_non_worker_and_maintenance_tour-0.279 0.0939-2.97** 0.00
coef_presence_of_non_worker_and_shopping_tour-0.419 0.0783-5.35*** 0.00
coef_presence_of_part_time_worker_and_discretionary_tour-0.252 0.0806-3.13** 0.00
coef_presence_of_part_time_worker_and_maintenance_tour-0.0951 0.0856-1.11 0.00
coef_presence_of_part_time_worker_and_shopping_tour-0.150 0.0686-2.19* 0.00
coef_presence_of_pre_driving_school_kid_and_discretionary_tour-0.401 0.0837-4.79*** 0.00
coef_presence_of_pre_driving_school_kid_and_escorting_tour 1.38 0.0611 22.52*** 0.00
coef_presence_of_pre_school_kid_and_discretionary_tour-0.509 0.100-5.09*** 0.00
coef_presence_of_pre_school_kid_and_eating_out_tour-0.481 0.108-4.44*** 0.00
coef_presence_of_pre_school_kid_and_escorting_tour 0.654 0.0634 10.32*** 0.00
coef_presence_of_pre_school_kid_and_shopping_tour-0.0802 0.0795-1.01 0.00
coef_presence_of_retiree_and_discretionary_tour-1.05 0.154-6.82*** 0.00
coef_presence_of_retiree_and_eating_out_tour-0.430 0.147-2.92** 0.00
coef_presence_of_retiree_and_escorting_tour-0.694 0.143-4.86*** 0.00
coef_presence_of_university_student_and_discretionary_tour-0.532 0.114-4.67*** 0.00
coef_total_number_of_tours_is_1-7.26 49.6-0.15 0.00
coef_total_number_of_tours_is_2-10.7 99.2-0.11 0.00
coef_total_number_of_tours_is_3-13.4 149.-0.09 0.00
coef_total_number_of_tours_is_4-16.5 198.-0.08 0.00
coef_total_number_of_tours_is_5-19.7 248.-0.08 0.00
coef_total_number_of_tours_is_6_plus-999. 0.00 NA 0.00fixed value
coef_transit_access_to_retail_and_tour_frequency_is_5_plus 0.0132 0.0114 1.15 0.00
coef_urban_and_discretionary_tour 0.00 0.00 NA 0.00fixed value
coef_urban_and_escorting_tour-0.486 0.0782-6.21*** 0.00
coef_walk_access_to_retail_and_discretionary 0.0610 0.0251 2.42* 0.00
coef_walk_access_to_retail_and_eating_out 0.157 0.0243 6.47*** 0.00
coef_walk_access_to_retail_and_escorting 0.0660 0.0200 3.30*** 0.00
coef_walk_access_to_retail_and_shopping 0.0317 0.0241 1.31 0.00
coef_zero_car_ownership_and_tour_frequency_is_5_plus-0.240 0.109-2.19* 0.00
\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model PTYPE_PART\n" + ] + }, + { + "data": { + "text/html": [ + "

Iteration 060 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1059,7 +3735,7 @@ { "data": { "text/html": [ - "

Best LL = -856.8595081667797

" + "

Best LL = -9327.08229602112

" ], "text/plain": [ "" @@ -1090,793 +3766,755 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_0_auto_household_and_escorting_tour\n", " -2.000000\n", - " -2.0000\n", - " 0.0\n", + " -2.000000\n", + " -2.000000\n", " -2.0\n", " -2.0\n", + " 0.0\n", " 1\n", - " \n", - " -2.000000\n", " \n", " \n", " coef_1_escort_tour_constant\n", - " 0.777927\n", - " 0.5272\n", + " 0.430423\n", + " 0.430423\n", + " 0.527200\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.777927\n", " \n", " \n", " coef_1_plus_eating_out_tours_constant\n", - " 1.665075\n", - " 0.6914\n", + " 0.732307\n", + " 0.732307\n", + " 0.691400\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.665075\n", " \n", " \n", " coef_1_plus_maintenance_tours_constant\n", - " 1.214734\n", - " 0.5533\n", + " 0.480847\n", + " 0.480847\n", + " 0.553300\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.214734\n", " \n", " \n", " coef_1_plus_other_discretionary_tours_constant\n", - " 1.783871\n", - " 0.7989\n", + " 0.900550\n", + " 0.900550\n", + " 0.798900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.783871\n", " \n", " \n", " coef_1_plus_shopping_tours_constant\n", - " 1.521613\n", - " 0.7569\n", + " 0.731723\n", + " 0.731723\n", + " 0.756900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.521613\n", " \n", " \n", " coef_1_plus_visting_tours_constant\n", - " 1.045482\n", - " 0.1405\n", + " 0.250360\n", + " 0.250360\n", + " 0.140500\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.045482\n", " \n", " \n", " coef_2_plus_escort_tours_constant\n", - " 1.882661\n", - " 1.5987\n", + " 1.457716\n", + " 1.457716\n", + " 1.598700\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.882661\n", " \n", " \n", " coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus\n", - " 0.049232\n", - " -0.5498\n", + " -0.400969\n", + " -0.400969\n", + " -0.549800\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.049232\n", " \n", " \n", " coef_female_and_discretionary_tour\n", - " 0.439252\n", - " 0.3072\n", + " 0.316191\n", + " 0.316191\n", + " 0.307200\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.439252\n", " \n", " \n", " coef_female_and_shopping_tour\n", - " 0.753133\n", - " 0.4524\n", + " 0.352178\n", + " 0.352178\n", + " 0.452400\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.753133\n", " \n", " \n", " coef_high_income_group_and_discretionary_tour\n", - " 0.236506\n", - " 0.2960\n", + " 0.245706\n", + " 0.245706\n", + " 0.296000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.236506\n", " \n", " \n", " coef_high_income_group_and_maintenance_tour\n", - " 1.385100\n", - " 0.6763\n", + " 0.828693\n", + " 0.828693\n", + " 0.676300\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.385100\n", " \n", " \n", " coef_high_income_group_and_shopping_tour\n", - " 0.819417\n", - " 0.7066\n", + " 0.846024\n", + " 0.846024\n", + " 0.706600\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.819417\n", " \n", " \n", " coef_high_income_group_and_tour_frequency_is_1\n", - " 1.145715\n", - " 0.8682\n", + " 0.809721\n", + " 0.809721\n", + " 0.868200\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.145715\n", " \n", " \n", " coef_high_income_group_and_tour_frequency_is_2\n", - " 1.347519\n", - " 1.5362\n", + " 1.223360\n", + " 1.223360\n", + " 1.536200\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.347519\n", " \n", " \n", " coef_high_income_group_and_tour_frequency_is_5_plus\n", - " 1.498903\n", - " 1.9331\n", + " 1.571734\n", + " 1.571734\n", + " 1.933100\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.498903\n", " \n", " \n", " coef_high_income_group_and_visiting_tour\n", - " -0.517316\n", - " -0.6868\n", + " -0.714757\n", + " -0.714757\n", + " -0.686800\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.517316\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_1\n", - " 0.768519\n", - " 1.5748\n", + " 1.659306\n", + " 1.659306\n", + " 1.574800\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.768519\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_5_plus\n", - " 1.243995\n", - " 2.0026\n", + " 1.957087\n", + " 1.957087\n", + " 2.002600\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.243995\n", " \n", " \n", " coef_mediumhigh_income_group_and_shopping_tour\n", - " 0.605047\n", - " 0.4421\n", + " 0.573217\n", + " 0.573217\n", + " 0.442100\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.605047\n", " \n", " \n", " coef_mediumlow_income_group_and_tour_frequency_is_1\n", - " 0.784377\n", - " 0.5981\n", + " 0.685180\n", + " 0.685180\n", + " 0.598100\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.784377\n", " \n", " \n", " coef_mediumlow_income_group_and_tour_frequency_is_2\n", - " 0.776466\n", - " 0.9178\n", + " 0.592898\n", + " 0.592898\n", + " 0.917800\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.776466\n", " \n", " \n", " coef_mediumlow_income_group_and_tour_frequency_is_5_plus\n", - " 0.850898\n", - " 1.7539\n", + " 1.597675\n", + " 1.597675\n", + " 1.753900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.850898\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_4\n", - " -1.347657\n", - " -1.1986\n", + " -0.760824\n", + " -0.760824\n", + " -1.198600\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.347657\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_5_plus\n", " -999.000000\n", - " -999.0000\n", - " 0.0\n", + " -999.000000\n", + " -999.000000\n", " -999.0\n", " -999.0\n", + " 0.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_1\n", - " -0.989069\n", - " -0.2390\n", + " -0.358322\n", + " -0.358322\n", + " -0.239000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.989069\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_2\n", - " -2.829794\n", - " -1.8208\n", + " -1.622848\n", + " -1.622848\n", + " -1.820800\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.829794\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus\n", - " -2.785677\n", - " -2.5923\n", + " -2.631492\n", + " -2.631492\n", + " -2.592300\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.785677\n", " \n", " \n", " coef_presence_of_driving_school_kid_and_escorting_tour\n", - " 1.029447\n", - " 0.4164\n", + " 0.367517\n", + " 0.367517\n", + " 0.416400\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.029447\n", " \n", " \n", " coef_presence_of_full_time_worker_and_maintenance_tour\n", - " -0.484999\n", - " -0.3131\n", + " -0.254950\n", + " -0.254950\n", + " -0.313100\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.484999\n", " \n", " \n", " coef_presence_of_non_worker_and_discretionary_tour\n", - " -0.556803\n", - " -1.0371\n", + " -0.828046\n", + " -0.828046\n", + " -1.037100\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.556803\n", " \n", " \n", " coef_presence_of_non_worker_and_eating_out_tour\n", - " -0.231608\n", - " -0.6545\n", + " -0.660344\n", + " -0.660344\n", + " -0.654500\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.231608\n", " \n", " \n", " coef_presence_of_non_worker_and_escorting_tour\n", - " -0.617113\n", - " -0.5263\n", + " -0.530905\n", + " -0.530905\n", + " -0.526300\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.617113\n", " \n", " \n", " coef_presence_of_part_time_worker_and_maintenance_tour\n", - " -1.034909\n", - " -0.5621\n", + " -0.576071\n", + " -0.576071\n", + " -0.562100\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.034909\n", " \n", " \n", " coef_presence_of_pre_driving_school_kid_and_escorting_tour\n", - " 1.808890\n", - " 1.5795\n", + " 1.756066\n", + " 1.756066\n", + " 1.579500\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.808890\n", " \n", " \n", " coef_presence_of_pre_school_kid_and_escorting_tour\n", - " 0.291702\n", - " 0.5414\n", + " 0.549515\n", + " 0.549515\n", + " 0.541400\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.291702\n", " \n", " \n", " coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1\n", - " 0.308611\n", - " -0.1559\n", + " -0.340060\n", + " -0.340060\n", + " -0.155900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.308611\n", " \n", " \n", " coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5\n", - " -0.530685\n", - " -0.5681\n", + " -0.650421\n", + " -0.650421\n", + " -0.568100\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.530685\n", " \n", " \n", " coef_presence_of_retiree_and_eating_out_tour\n", - " 0.109209\n", - " -1.3890\n", + " -1.202708\n", + " -1.202708\n", + " -1.389000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.109209\n", " \n", " \n", " coef_presence_of_retiree_and_escorting_tour\n", - " -0.461150\n", - " -0.7516\n", + " -0.801304\n", + " -0.801304\n", + " -0.751600\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.461150\n", " \n", " \n", " coef_presence_of_university_student_and_eating_out_tour\n", - " -1.759323\n", - " -1.4318\n", + " -1.695822\n", + " -1.695822\n", + " -1.431800\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.759323\n", " \n", " \n", " coef_total_number_of_tours_is_1\n", - " -6.812615\n", - " -7.6391\n", + " -7.835780\n", + " -7.835780\n", + " -7.639100\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -6.812615\n", " \n", " \n", " coef_total_number_of_tours_is_2\n", - " -9.848060\n", - " -10.4557\n", + " -10.277923\n", + " -10.277923\n", + " -10.455700\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -9.848060\n", " \n", " \n", " coef_total_number_of_tours_is_3\n", - " -12.828277\n", - " -14.0176\n", + " -14.048815\n", + " -14.048815\n", + " -14.017600\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -12.828277\n", " \n", " \n", " coef_total_number_of_tours_is_4\n", - " -17.097027\n", - " -16.9717\n", + " -17.043997\n", + " -17.043997\n", + " -16.971701\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -17.097027\n", " \n", " \n", " coef_urban_and_discretionary_tour\n", " 0.000000\n", - " 0.0000\n", + " 0.000000\n", + " 0.000000\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_urban_and_escorting_tour\n", - " 0.425750\n", - " -0.3929\n", + " -0.503217\n", + " -0.503217\n", + " -0.392900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.425750\n", " \n", " \n", " coef_walk_access_to_retail_and_tour_frequency_is_1\n", - " 0.080140\n", - " 0.0899\n", + " 0.108136\n", + " 0.108136\n", + " 0.089900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.080140\n", " \n", " \n", " coef_walk_access_to_retail_and_tour_frequency_is_2\n", - " 0.103820\n", - " 0.1447\n", + " 0.128901\n", + " 0.128901\n", + " 0.144700\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.103820\n", " \n", " \n", " coef_walk_access_to_retail_and_tour_frequency_is_5_plus\n", - " 0.050631\n", - " 0.3479\n", + " 0.385133\n", + " 0.385133\n", + " 0.347900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.050631\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_0_auto_household_and_escorting_tour -2.000000 -2.0000 \n", - "coef_1_escort_tour_constant 0.777927 0.5272 \n", - "coef_1_plus_eating_out_tours_constant 1.665075 0.6914 \n", - "coef_1_plus_maintenance_tours_constant 1.214734 0.5533 \n", - "coef_1_plus_other_discretionary_tours_constant 1.783871 0.7989 \n", - "coef_1_plus_shopping_tours_constant 1.521613 0.7569 \n", - "coef_1_plus_visting_tours_constant 1.045482 0.1405 \n", - "coef_2_plus_escort_tours_constant 1.882661 1.5987 \n", - "coef_car_shortage_vs_workers_and_tour_frequency... 0.049232 -0.5498 \n", - "coef_female_and_discretionary_tour 0.439252 0.3072 \n", - "coef_female_and_shopping_tour 0.753133 0.4524 \n", - "coef_high_income_group_and_discretionary_tour 0.236506 0.2960 \n", - "coef_high_income_group_and_maintenance_tour 1.385100 0.6763 \n", - "coef_high_income_group_and_shopping_tour 0.819417 0.7066 \n", - "coef_high_income_group_and_tour_frequency_is_1 1.145715 0.8682 \n", - "coef_high_income_group_and_tour_frequency_is_2 1.347519 1.5362 \n", - "coef_high_income_group_and_tour_frequency_is_5_... 1.498903 1.9331 \n", - "coef_high_income_group_and_visiting_tour -0.517316 -0.6868 \n", - "coef_logged_maximum_residual_window_tour_freque... 0.768519 1.5748 \n", - "coef_logged_maximum_residual_window_tour_freque... 1.243995 2.0026 \n", - "coef_mediumhigh_income_group_and_shopping_tour 0.605047 0.4421 \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.784377 0.5981 \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.776466 0.9178 \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.850898 1.7539 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_4 -1.347657 -1.1986 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.0000 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -0.989069 -0.2390 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -2.829794 -1.8208 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -2.785677 -2.5923 \n", - "coef_presence_of_driving_school_kid_and_escorti... 1.029447 0.4164 \n", - "coef_presence_of_full_time_worker_and_maintenan... -0.484999 -0.3131 \n", - "coef_presence_of_non_worker_and_discretionary_tour -0.556803 -1.0371 \n", - "coef_presence_of_non_worker_and_eating_out_tour -0.231608 -0.6545 \n", - "coef_presence_of_non_worker_and_escorting_tour -0.617113 -0.5263 \n", - "coef_presence_of_part_time_worker_and_maintenan... -1.034909 -0.5621 \n", - "coef_presence_of_pre_driving_school_kid_and_esc... 1.808890 1.5795 \n", - "coef_presence_of_pre_school_kid_and_escorting_tour 0.291702 0.5414 \n", - "coef_presence_of_preschool_kid_in_household_and... 0.308611 -0.1559 \n", - "coef_presence_of_preschool_kid_in_household_and... -0.530685 -0.5681 \n", - "coef_presence_of_retiree_and_eating_out_tour 0.109209 -1.3890 \n", - "coef_presence_of_retiree_and_escorting_tour -0.461150 -0.7516 \n", - "coef_presence_of_university_student_and_eating_... -1.759323 -1.4318 \n", - "coef_total_number_of_tours_is_1 -6.812615 -7.6391 \n", - "coef_total_number_of_tours_is_2 -9.848060 -10.4557 \n", - "coef_total_number_of_tours_is_3 -12.828277 -14.0176 \n", - "coef_total_number_of_tours_is_4 -17.097027 -16.9717 \n", - "coef_urban_and_discretionary_tour 0.000000 0.0000 \n", - "coef_urban_and_escorting_tour 0.425750 -0.3929 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_1 0.080140 0.0899 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_2 0.103820 0.1447 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... 0.050631 0.3479 \n", + " value best \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.000000 \n", + "coef_1_escort_tour_constant 0.430423 0.430423 \n", + "coef_1_plus_eating_out_tours_constant 0.732307 0.732307 \n", + "coef_1_plus_maintenance_tours_constant 0.480847 0.480847 \n", + "coef_1_plus_other_discretionary_tours_constant 0.900550 0.900550 \n", + "coef_1_plus_shopping_tours_constant 0.731723 0.731723 \n", + "coef_1_plus_visting_tours_constant 0.250360 0.250360 \n", + "coef_2_plus_escort_tours_constant 1.457716 1.457716 \n", + "coef_car_shortage_vs_workers_and_tour_frequency... -0.400969 -0.400969 \n", + "coef_female_and_discretionary_tour 0.316191 0.316191 \n", + "coef_female_and_shopping_tour 0.352178 0.352178 \n", + "coef_high_income_group_and_discretionary_tour 0.245706 0.245706 \n", + "coef_high_income_group_and_maintenance_tour 0.828693 0.828693 \n", + "coef_high_income_group_and_shopping_tour 0.846024 0.846024 \n", + "coef_high_income_group_and_tour_frequency_is_1 0.809721 0.809721 \n", + "coef_high_income_group_and_tour_frequency_is_2 1.223360 1.223360 \n", + "coef_high_income_group_and_tour_frequency_is_5_... 1.571734 1.571734 \n", + "coef_high_income_group_and_visiting_tour -0.714757 -0.714757 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.659306 1.659306 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.957087 1.957087 \n", + "coef_mediumhigh_income_group_and_shopping_tour 0.573217 0.573217 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 0.685180 0.685180 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 0.592898 0.592898 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 1.597675 1.597675 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_4 -0.760824 -0.760824 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.000000 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -0.358322 -0.358322 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -1.622848 -1.622848 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -2.631492 -2.631492 \n", + "coef_presence_of_driving_school_kid_and_escorti... 0.367517 0.367517 \n", + "coef_presence_of_full_time_worker_and_maintenan... -0.254950 -0.254950 \n", + "coef_presence_of_non_worker_and_discretionary_tour -0.828046 -0.828046 \n", + "coef_presence_of_non_worker_and_eating_out_tour -0.660344 -0.660344 \n", + "coef_presence_of_non_worker_and_escorting_tour -0.530905 -0.530905 \n", + "coef_presence_of_part_time_worker_and_maintenan... -0.576071 -0.576071 \n", + "coef_presence_of_pre_driving_school_kid_and_esc... 1.756066 1.756066 \n", + "coef_presence_of_pre_school_kid_and_escorting_tour 0.549515 0.549515 \n", + "coef_presence_of_preschool_kid_in_household_and... -0.340060 -0.340060 \n", + "coef_presence_of_preschool_kid_in_household_and... -0.650421 -0.650421 \n", + "coef_presence_of_retiree_and_eating_out_tour -1.202708 -1.202708 \n", + "coef_presence_of_retiree_and_escorting_tour -0.801304 -0.801304 \n", + "coef_presence_of_university_student_and_eating_... -1.695822 -1.695822 \n", + "coef_total_number_of_tours_is_1 -7.835780 -7.835780 \n", + "coef_total_number_of_tours_is_2 -10.277923 -10.277923 \n", + "coef_total_number_of_tours_is_3 -14.048815 -14.048815 \n", + "coef_total_number_of_tours_is_4 -17.043997 -17.043997 \n", + "coef_urban_and_discretionary_tour 0.000000 0.000000 \n", + "coef_urban_and_escorting_tour -0.503217 -0.503217 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_1 0.108136 0.108136 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_2 0.128901 0.128901 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 0.385133 0.385133 \n", "\n", - " nullvalue minimum \\\n", - "coef_0_auto_household_and_escorting_tour 0.0 -2.0 \n", - "coef_1_escort_tour_constant 0.0 NaN \n", - "coef_1_plus_eating_out_tours_constant 0.0 NaN \n", - "coef_1_plus_maintenance_tours_constant 0.0 NaN \n", - "coef_1_plus_other_discretionary_tours_constant 0.0 NaN \n", - "coef_1_plus_shopping_tours_constant 0.0 NaN \n", - "coef_1_plus_visting_tours_constant 0.0 NaN \n", - "coef_2_plus_escort_tours_constant 0.0 NaN \n", - "coef_car_shortage_vs_workers_and_tour_frequency... 0.0 NaN \n", - "coef_female_and_discretionary_tour 0.0 NaN \n", - "coef_female_and_shopping_tour 0.0 NaN \n", - "coef_high_income_group_and_discretionary_tour 0.0 NaN \n", - "coef_high_income_group_and_maintenance_tour 0.0 NaN \n", - "coef_high_income_group_and_shopping_tour 0.0 NaN \n", - "coef_high_income_group_and_tour_frequency_is_1 0.0 NaN \n", - "coef_high_income_group_and_tour_frequency_is_2 0.0 NaN \n", - "coef_high_income_group_and_tour_frequency_is_5_... 0.0 NaN \n", - "coef_high_income_group_and_visiting_tour 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_mediumhigh_income_group_and_shopping_tour 0.0 NaN \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.0 NaN \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.0 NaN \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_is_4 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_i... 0.0 -999.0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_presence_of_driving_school_kid_and_escorti... 0.0 NaN \n", - "coef_presence_of_full_time_worker_and_maintenan... 0.0 NaN \n", - "coef_presence_of_non_worker_and_discretionary_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_eating_out_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_escorting_tour 0.0 NaN \n", - "coef_presence_of_part_time_worker_and_maintenan... 0.0 NaN \n", - "coef_presence_of_pre_driving_school_kid_and_esc... 0.0 NaN \n", - "coef_presence_of_pre_school_kid_and_escorting_tour 0.0 NaN \n", - "coef_presence_of_preschool_kid_in_household_and... 0.0 NaN \n", - "coef_presence_of_preschool_kid_in_household_and... 0.0 NaN \n", - "coef_presence_of_retiree_and_eating_out_tour 0.0 NaN \n", - "coef_presence_of_retiree_and_escorting_tour 0.0 NaN \n", - "coef_presence_of_university_student_and_eating_... 0.0 NaN \n", - "coef_total_number_of_tours_is_1 0.0 NaN \n", - "coef_total_number_of_tours_is_2 0.0 NaN \n", - "coef_total_number_of_tours_is_3 0.0 NaN \n", - "coef_total_number_of_tours_is_4 0.0 NaN \n", - "coef_urban_and_discretionary_tour 0.0 0.0 \n", - "coef_urban_and_escorting_tour 0.0 NaN \n", - "coef_walk_access_to_retail_and_tour_frequency_is_1 0.0 NaN \n", - "coef_walk_access_to_retail_and_tour_frequency_is_2 0.0 NaN \n", - "coef_walk_access_to_retail_and_tour_frequency_i... 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.0 \n", + "coef_1_escort_tour_constant 0.527200 -20.0 \n", + "coef_1_plus_eating_out_tours_constant 0.691400 -20.0 \n", + "coef_1_plus_maintenance_tours_constant 0.553300 -20.0 \n", + "coef_1_plus_other_discretionary_tours_constant 0.798900 -20.0 \n", + "coef_1_plus_shopping_tours_constant 0.756900 -20.0 \n", + "coef_1_plus_visting_tours_constant 0.140500 -20.0 \n", + "coef_2_plus_escort_tours_constant 1.598700 -20.0 \n", + "coef_car_shortage_vs_workers_and_tour_frequency... -0.549800 -20.0 \n", + "coef_female_and_discretionary_tour 0.307200 -20.0 \n", + "coef_female_and_shopping_tour 0.452400 -20.0 \n", + "coef_high_income_group_and_discretionary_tour 0.296000 -20.0 \n", + "coef_high_income_group_and_maintenance_tour 0.676300 -20.0 \n", + "coef_high_income_group_and_shopping_tour 0.706600 -20.0 \n", + "coef_high_income_group_and_tour_frequency_is_1 0.868200 -20.0 \n", + "coef_high_income_group_and_tour_frequency_is_2 1.536200 -20.0 \n", + "coef_high_income_group_and_tour_frequency_is_5_... 1.933100 -20.0 \n", + "coef_high_income_group_and_visiting_tour -0.686800 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.574800 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 2.002600 -20.0 \n", + "coef_mediumhigh_income_group_and_shopping_tour 0.442100 -20.0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 0.598100 -20.0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 0.917800 -20.0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 1.753900 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_4 -1.198600 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -0.239000 -20.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -1.820800 -20.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -2.592300 -20.0 \n", + "coef_presence_of_driving_school_kid_and_escorti... 0.416400 -20.0 \n", + "coef_presence_of_full_time_worker_and_maintenan... -0.313100 -20.0 \n", + "coef_presence_of_non_worker_and_discretionary_tour -1.037100 -20.0 \n", + "coef_presence_of_non_worker_and_eating_out_tour -0.654500 -20.0 \n", + "coef_presence_of_non_worker_and_escorting_tour -0.526300 -20.0 \n", + "coef_presence_of_part_time_worker_and_maintenan... -0.562100 -20.0 \n", + "coef_presence_of_pre_driving_school_kid_and_esc... 1.579500 -20.0 \n", + "coef_presence_of_pre_school_kid_and_escorting_tour 0.541400 -20.0 \n", + "coef_presence_of_preschool_kid_in_household_and... -0.155900 -20.0 \n", + "coef_presence_of_preschool_kid_in_household_and... -0.568100 -20.0 \n", + "coef_presence_of_retiree_and_eating_out_tour -1.389000 -20.0 \n", + "coef_presence_of_retiree_and_escorting_tour -0.751600 -20.0 \n", + "coef_presence_of_university_student_and_eating_... -1.431800 -20.0 \n", + "coef_total_number_of_tours_is_1 -7.639100 -20.0 \n", + "coef_total_number_of_tours_is_2 -10.455700 -20.0 \n", + "coef_total_number_of_tours_is_3 -14.017600 -20.0 \n", + "coef_total_number_of_tours_is_4 -16.971701 -20.0 \n", + "coef_urban_and_discretionary_tour 0.000000 0.0 \n", + "coef_urban_and_escorting_tour -0.392900 -20.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_1 0.089900 -20.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_2 0.144700 -20.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 0.347900 -20.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_0_auto_household_and_escorting_tour -2.0 1 \n", - "coef_1_escort_tour_constant NaN 0 \n", - "coef_1_plus_eating_out_tours_constant NaN 0 \n", - "coef_1_plus_maintenance_tours_constant NaN 0 \n", - "coef_1_plus_other_discretionary_tours_constant NaN 0 \n", - "coef_1_plus_shopping_tours_constant NaN 0 \n", - "coef_1_plus_visting_tours_constant NaN 0 \n", - "coef_2_plus_escort_tours_constant NaN 0 \n", - "coef_car_shortage_vs_workers_and_tour_frequency... NaN 0 \n", - "coef_female_and_discretionary_tour NaN 0 \n", - "coef_female_and_shopping_tour NaN 0 \n", - "coef_high_income_group_and_discretionary_tour NaN 0 \n", - "coef_high_income_group_and_maintenance_tour NaN 0 \n", - "coef_high_income_group_and_shopping_tour NaN 0 \n", - "coef_high_income_group_and_tour_frequency_is_1 NaN 0 \n", - "coef_high_income_group_and_tour_frequency_is_2 NaN 0 \n", - "coef_high_income_group_and_tour_frequency_is_5_... NaN 0 \n", - "coef_high_income_group_and_visiting_tour NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_mediumhigh_income_group_and_shopping_tour NaN 0 \n", - "coef_mediumlow_income_group_and_tour_frequency_... NaN 0 \n", - "coef_mediumlow_income_group_and_tour_frequency_... NaN 0 \n", - "coef_mediumlow_income_group_and_tour_frequency_... NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_4 NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.0 1 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_presence_of_driving_school_kid_and_escorti... NaN 0 \n", - "coef_presence_of_full_time_worker_and_maintenan... NaN 0 \n", - "coef_presence_of_non_worker_and_discretionary_tour NaN 0 \n", - "coef_presence_of_non_worker_and_eating_out_tour NaN 0 \n", - "coef_presence_of_non_worker_and_escorting_tour NaN 0 \n", - "coef_presence_of_part_time_worker_and_maintenan... NaN 0 \n", - "coef_presence_of_pre_driving_school_kid_and_esc... NaN 0 \n", - "coef_presence_of_pre_school_kid_and_escorting_tour NaN 0 \n", - "coef_presence_of_preschool_kid_in_household_and... NaN 0 \n", - "coef_presence_of_preschool_kid_in_household_and... NaN 0 \n", - "coef_presence_of_retiree_and_eating_out_tour NaN 0 \n", - "coef_presence_of_retiree_and_escorting_tour NaN 0 \n", - "coef_presence_of_university_student_and_eating_... NaN 0 \n", - "coef_total_number_of_tours_is_1 NaN 0 \n", - "coef_total_number_of_tours_is_2 NaN 0 \n", - "coef_total_number_of_tours_is_3 NaN 0 \n", - "coef_total_number_of_tours_is_4 NaN 0 \n", - "coef_urban_and_discretionary_tour 0.0 1 \n", - "coef_urban_and_escorting_tour NaN 0 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_1 NaN 0 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_2 NaN 0 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0 0.0 \n", + "coef_1_escort_tour_constant 20.0 0.0 \n", + "coef_1_plus_eating_out_tours_constant 20.0 0.0 \n", + "coef_1_plus_maintenance_tours_constant 20.0 0.0 \n", + "coef_1_plus_other_discretionary_tours_constant 20.0 0.0 \n", + "coef_1_plus_shopping_tours_constant 20.0 0.0 \n", + "coef_1_plus_visting_tours_constant 20.0 0.0 \n", + "coef_2_plus_escort_tours_constant 20.0 0.0 \n", + "coef_car_shortage_vs_workers_and_tour_frequency... 20.0 0.0 \n", + "coef_female_and_discretionary_tour 20.0 0.0 \n", + "coef_female_and_shopping_tour 20.0 0.0 \n", + "coef_high_income_group_and_discretionary_tour 20.0 0.0 \n", + "coef_high_income_group_and_maintenance_tour 20.0 0.0 \n", + "coef_high_income_group_and_shopping_tour 20.0 0.0 \n", + "coef_high_income_group_and_tour_frequency_is_1 20.0 0.0 \n", + "coef_high_income_group_and_tour_frequency_is_2 20.0 0.0 \n", + "coef_high_income_group_and_tour_frequency_is_5_... 20.0 0.0 \n", + "coef_high_income_group_and_visiting_tour 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_mediumhigh_income_group_and_shopping_tour 20.0 0.0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 20.0 0.0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 20.0 0.0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_4 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_presence_of_driving_school_kid_and_escorti... 20.0 0.0 \n", + "coef_presence_of_full_time_worker_and_maintenan... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_discretionary_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_escorting_tour 20.0 0.0 \n", + "coef_presence_of_part_time_worker_and_maintenan... 20.0 0.0 \n", + "coef_presence_of_pre_driving_school_kid_and_esc... 20.0 0.0 \n", + "coef_presence_of_pre_school_kid_and_escorting_tour 20.0 0.0 \n", + "coef_presence_of_preschool_kid_in_household_and... 20.0 0.0 \n", + "coef_presence_of_preschool_kid_in_household_and... 20.0 0.0 \n", + "coef_presence_of_retiree_and_eating_out_tour 20.0 0.0 \n", + "coef_presence_of_retiree_and_escorting_tour 20.0 0.0 \n", + "coef_presence_of_university_student_and_eating_... 20.0 0.0 \n", + "coef_total_number_of_tours_is_1 20.0 0.0 \n", + "coef_total_number_of_tours_is_2 20.0 0.0 \n", + "coef_total_number_of_tours_is_3 20.0 0.0 \n", + "coef_total_number_of_tours_is_4 20.0 0.0 \n", + "coef_urban_and_discretionary_tour 0.0 0.0 \n", + "coef_urban_and_escorting_tour 20.0 0.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_1 20.0 0.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_2 20.0 0.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 20.0 0.0 \n", "\n", - " best \n", - "coef_0_auto_household_and_escorting_tour -2.000000 \n", - "coef_1_escort_tour_constant 0.777927 \n", - "coef_1_plus_eating_out_tours_constant 1.665075 \n", - "coef_1_plus_maintenance_tours_constant 1.214734 \n", - "coef_1_plus_other_discretionary_tours_constant 1.783871 \n", - "coef_1_plus_shopping_tours_constant 1.521613 \n", - "coef_1_plus_visting_tours_constant 1.045482 \n", - "coef_2_plus_escort_tours_constant 1.882661 \n", - "coef_car_shortage_vs_workers_and_tour_frequency... 0.049232 \n", - "coef_female_and_discretionary_tour 0.439252 \n", - "coef_female_and_shopping_tour 0.753133 \n", - "coef_high_income_group_and_discretionary_tour 0.236506 \n", - "coef_high_income_group_and_maintenance_tour 1.385100 \n", - "coef_high_income_group_and_shopping_tour 0.819417 \n", - "coef_high_income_group_and_tour_frequency_is_1 1.145715 \n", - "coef_high_income_group_and_tour_frequency_is_2 1.347519 \n", - "coef_high_income_group_and_tour_frequency_is_5_... 1.498903 \n", - "coef_high_income_group_and_visiting_tour -0.517316 \n", - "coef_logged_maximum_residual_window_tour_freque... 0.768519 \n", - "coef_logged_maximum_residual_window_tour_freque... 1.243995 \n", - "coef_mediumhigh_income_group_and_shopping_tour 0.605047 \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.784377 \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.776466 \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.850898 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_4 -1.347657 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -0.989069 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -2.829794 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -2.785677 \n", - "coef_presence_of_driving_school_kid_and_escorti... 1.029447 \n", - "coef_presence_of_full_time_worker_and_maintenan... -0.484999 \n", - "coef_presence_of_non_worker_and_discretionary_tour -0.556803 \n", - "coef_presence_of_non_worker_and_eating_out_tour -0.231608 \n", - "coef_presence_of_non_worker_and_escorting_tour -0.617113 \n", - "coef_presence_of_part_time_worker_and_maintenan... -1.034909 \n", - "coef_presence_of_pre_driving_school_kid_and_esc... 1.808890 \n", - "coef_presence_of_pre_school_kid_and_escorting_tour 0.291702 \n", - "coef_presence_of_preschool_kid_in_household_and... 0.308611 \n", - "coef_presence_of_preschool_kid_in_household_and... -0.530685 \n", - "coef_presence_of_retiree_and_eating_out_tour 0.109209 \n", - "coef_presence_of_retiree_and_escorting_tour -0.461150 \n", - "coef_presence_of_university_student_and_eating_... -1.759323 \n", - "coef_total_number_of_tours_is_1 -6.812615 \n", - "coef_total_number_of_tours_is_2 -9.848060 \n", - "coef_total_number_of_tours_is_3 -12.828277 \n", - "coef_total_number_of_tours_is_4 -17.097027 \n", - "coef_urban_and_discretionary_tour 0.000000 \n", - "coef_urban_and_escorting_tour 0.425750 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_1 0.080140 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_2 0.103820 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... 0.050631 " + " holdfast \n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 1 \n", + "coef_1_escort_tour_constant 0 \n", + "coef_1_plus_eating_out_tours_constant 0 \n", + "coef_1_plus_maintenance_tours_constant 0 \n", + "coef_1_plus_other_discretionary_tours_constant 0 \n", + "coef_1_plus_shopping_tours_constant 0 \n", + "coef_1_plus_visting_tours_constant 0 \n", + "coef_2_plus_escort_tours_constant 0 \n", + "coef_car_shortage_vs_workers_and_tour_frequency... 0 \n", + "coef_female_and_discretionary_tour 0 \n", + "coef_female_and_shopping_tour 0 \n", + "coef_high_income_group_and_discretionary_tour 0 \n", + "coef_high_income_group_and_maintenance_tour 0 \n", + "coef_high_income_group_and_shopping_tour 0 \n", + "coef_high_income_group_and_tour_frequency_is_1 0 \n", + "coef_high_income_group_and_tour_frequency_is_2 0 \n", + "coef_high_income_group_and_tour_frequency_is_5_... 0 \n", + "coef_high_income_group_and_visiting_tour 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_mediumhigh_income_group_and_shopping_tour 0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_4 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... 1 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_presence_of_driving_school_kid_and_escorti... 0 \n", + "coef_presence_of_full_time_worker_and_maintenan... 0 \n", + "coef_presence_of_non_worker_and_discretionary_tour 0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 0 \n", + "coef_presence_of_non_worker_and_escorting_tour 0 \n", + "coef_presence_of_part_time_worker_and_maintenan... 0 \n", + "coef_presence_of_pre_driving_school_kid_and_esc... 0 \n", + "coef_presence_of_pre_school_kid_and_escorting_tour 0 \n", + "coef_presence_of_preschool_kid_in_household_and... 0 \n", + "coef_presence_of_preschool_kid_in_household_and... 0 \n", + "coef_presence_of_retiree_and_eating_out_tour 0 \n", + "coef_presence_of_retiree_and_escorting_tour 0 \n", + "coef_presence_of_university_student_and_eating_... 0 \n", + "coef_total_number_of_tours_is_1 0 \n", + "coef_total_number_of_tours_is_2 0 \n", + "coef_total_number_of_tours_is_3 0 \n", + "coef_total_number_of_tours_is_4 0 \n", + "coef_urban_and_discretionary_tour 1 \n", + "coef_urban_and_escorting_tour 0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_1 0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_2 0 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 0 " ] }, "metadata": {}, @@ -1886,23 +4524,528 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " m.estimate(method='SLSQP')\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.818666298527715e-07 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model seems to have 2 parameter estimators with negative variance\n", - "- coef_1_escort_tour_constant\n", - "- coef_2_plus_escort_tours_constant\n", - " m.estimate(method='SLSQP')\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: RuntimeWarning: invalid value encountered in sqrt\n", - " m.estimate(method='SLSQP')\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { "data": { "text/html": [ - 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Iteration 076 [Optimization terminated successfully]

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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_0_auto_household_and_escorting_tour-2.00 0.00 NA 0.00fixed value
coef_1_escort_tour_constant 0.430 NA NA 0.00
coef_1_plus_eating_out_tours_constant 0.732 NA NA 0.00
coef_1_plus_maintenance_tours_constant 0.481 NA NA 0.00
coef_1_plus_other_discretionary_tours_constant 0.901 NA NA 0.00
coef_1_plus_shopping_tours_constant 0.732 NA NA 0.00
coef_1_plus_visting_tours_constant 0.250 NA NA 0.00
coef_2_plus_escort_tours_constant 1.46 NA NA 0.00
coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus-0.401 0.0883-4.54*** 0.00
coef_female_and_discretionary_tour 0.316 0.0881 3.59*** 0.00
coef_female_and_shopping_tour 0.352 0.0792 4.45*** 0.00
coef_high_income_group_and_discretionary_tour 0.246 0.163 1.50 0.00
coef_high_income_group_and_maintenance_tour 0.829 0.195 4.25*** 0.00
coef_high_income_group_and_shopping_tour 0.846 0.170 4.98*** 0.00
coef_high_income_group_and_tour_frequency_is_1 0.810 0.162 5.00*** 0.00
coef_high_income_group_and_tour_frequency_is_2 1.22 0.228 5.37*** 0.00
coef_high_income_group_and_tour_frequency_is_5_plus 1.57 0.350 4.49*** 0.00
coef_high_income_group_and_visiting_tour-0.715 0.204-3.50*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_1 1.66 0.131 12.64*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_5_plus 1.96 0.141 13.90*** 0.00
coef_mediumhigh_income_group_and_shopping_tour 0.573 0.164 3.49*** 0.00
coef_mediumlow_income_group_and_tour_frequency_is_1 0.685 0.171 4.01*** 0.00
coef_mediumlow_income_group_and_tour_frequency_is_2 0.593 0.242 2.45* 0.00
coef_mediumlow_income_group_and_tour_frequency_is_5_plus 1.60 0.362 4.41*** 0.00
coef_number_of_joint_tours_and_tour_frequency_is_4-0.761 0.227-3.36*** 0.00
coef_number_of_joint_tours_and_tour_frequency_is_5_plus-999. 0.00 NA 0.00fixed value
coef_number_of_mandatory_tours_and_tour_frequency_is_1-0.358 0.150-2.39* 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_2-1.62 0.237-6.86*** 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus-2.63 0.260-10.11*** 0.00
coef_presence_of_driving_school_kid_and_escorting_tour 0.368 0.0942 3.90*** 0.00
coef_presence_of_full_time_worker_and_maintenance_tour-0.255 0.0976-2.61** 0.00
coef_presence_of_non_worker_and_discretionary_tour-0.828 0.122-6.79*** 0.00
coef_presence_of_non_worker_and_eating_out_tour-0.660 0.155-4.26*** 0.00
coef_presence_of_non_worker_and_escorting_tour-0.531 0.0850-6.24*** 0.00
coef_presence_of_part_time_worker_and_maintenance_tour-0.576 0.109-5.30*** 0.00
coef_presence_of_pre_driving_school_kid_and_escorting_tour 1.76 0.0737 23.84*** 0.00
coef_presence_of_pre_school_kid_and_escorting_tour 0.550 0.0912 6.02*** 0.00
coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1-0.340 0.112-3.02** 0.00
coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5-0.650 0.151-4.31*** 0.00
coef_presence_of_retiree_and_eating_out_tour-1.20 0.245-4.90*** 0.00
coef_presence_of_retiree_and_escorting_tour-0.801 0.136-5.90*** 0.00
coef_presence_of_university_student_and_eating_out_tour-1.70 0.334-5.08*** 0.00
coef_total_number_of_tours_is_1-7.84 NA NA 0.00
coef_total_number_of_tours_is_2-10.3 NA NA 0.00
coef_total_number_of_tours_is_3-14.0 NA NA 0.00
coef_total_number_of_tours_is_4-17.0 NA NA 0.00
coef_urban_and_discretionary_tour 0.00 0.00 NA 0.00fixed value
coef_urban_and_escorting_tour-0.503 0.0816-6.17*** 0.00
coef_walk_access_to_retail_and_tour_frequency_is_1 0.108 0.0253 4.28*** 0.00
coef_walk_access_to_retail_and_tour_frequency_is_2 0.129 0.0303 4.25*** 0.00
coef_walk_access_to_retail_and_tour_frequency_is_5_plus 0.385 0.0468 8.23*** 0.00
\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model PTYPE_UNIVERSITY\n" + ] + }, + { + "data": { + "text/html": [ + "

Iteration 074 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1914,7 +5057,7 @@ { "data": { "text/html": [ - "

Best LL = -324.8584172756779

" + "

Best LL = -3512.6973954855457

" ], "text/plain": [ "" @@ -1945,70 +5088,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_0_auto_household_and_escorting_tour\n", " -2.000000\n", + " -2.000000\n", " -2.0000\n", - " 0.0\n", " -2.0\n", " -2.0\n", + " 0.0\n", " 1\n", - " \n", - " -2.000000\n", " \n", " \n", " coef_1_escort_tour_constant\n", - " 1.851506\n", + " 1.761998\n", + " 1.761998\n", " 1.7028\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.851506\n", " \n", " \n", " coef_1_plus_eating_out_tours_constant\n", - " -13.970901\n", + " 2.214614\n", + " 2.214614\n", " 2.0723\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -13.970901\n", " \n", " \n", " coef_1_plus_maintenance_tours_constant\n", - " -0.338031\n", + " 0.085206\n", + " 0.085206\n", " 0.3348\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.338031\n", " \n", " \n", " coef_1_plus_other_discretionary_tours_constant\n", - " -1.473992\n", + " 1.308003\n", + " 1.308003\n", " 1.3389\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.473992\n", " \n", " \n", " ...\n", @@ -2019,109 +5166,106 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", " coef_urban_and_shopping_tour\n", - " 0.711573\n", + " 0.637185\n", + " 0.637185\n", " 0.5330\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.711573\n", " \n", " \n", " coef_urban_and_tour_frequency_is_1\n", - " -3.537340\n", + " -0.924987\n", + " -0.924987\n", " -1.1648\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -3.537340\n", " \n", " \n", " coef_urban_and_tour_frequency_is_2\n", - " -4.729195\n", + " -2.118276\n", + " -2.118276\n", " -2.3177\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.729195\n", " \n", " \n", " coef_urban_and_tour_frequency_is_5_plus\n", - " -6.020888\n", + " -2.502952\n", + " -2.502952\n", " -2.5027\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -6.020888\n", " \n", " \n", " coef_walk_access_to_retail_and_shopping\n", - " 0.102379\n", + " 0.072376\n", + " 0.072376\n", " 0.0972\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.102379\n", " \n", " \n", "\n", - "

70 rows × 8 columns

\n", + "

70 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_0_auto_household_and_escorting_tour -2.000000 -2.0000 \n", - "coef_1_escort_tour_constant 1.851506 1.7028 \n", - "coef_1_plus_eating_out_tours_constant -13.970901 2.0723 \n", - "coef_1_plus_maintenance_tours_constant -0.338031 0.3348 \n", - "coef_1_plus_other_discretionary_tours_constant -1.473992 1.3389 \n", - "... ... ... \n", - "coef_urban_and_shopping_tour 0.711573 0.5330 \n", - "coef_urban_and_tour_frequency_is_1 -3.537340 -1.1648 \n", - "coef_urban_and_tour_frequency_is_2 -4.729195 -2.3177 \n", - "coef_urban_and_tour_frequency_is_5_plus -6.020888 -2.5027 \n", - "coef_walk_access_to_retail_and_shopping 0.102379 0.0972 \n", + " value best initvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.000000 -2.0000 \n", + "coef_1_escort_tour_constant 1.761998 1.761998 1.7028 \n", + "coef_1_plus_eating_out_tours_constant 2.214614 2.214614 2.0723 \n", + "coef_1_plus_maintenance_tours_constant 0.085206 0.085206 0.3348 \n", + "coef_1_plus_other_discretionary_tours_constant 1.308003 1.308003 1.3389 \n", + "... ... ... ... \n", + "coef_urban_and_shopping_tour 0.637185 0.637185 0.5330 \n", + "coef_urban_and_tour_frequency_is_1 -0.924987 -0.924987 -1.1648 \n", + "coef_urban_and_tour_frequency_is_2 -2.118276 -2.118276 -2.3177 \n", + "coef_urban_and_tour_frequency_is_5_plus -2.502952 -2.502952 -2.5027 \n", + "coef_walk_access_to_retail_and_shopping 0.072376 0.072376 0.0972 \n", "\n", - " nullvalue minimum maximum \\\n", - "coef_0_auto_household_and_escorting_tour 0.0 -2.0 -2.0 \n", - "coef_1_escort_tour_constant 0.0 NaN NaN \n", - "coef_1_plus_eating_out_tours_constant 0.0 NaN NaN \n", - "coef_1_plus_maintenance_tours_constant 0.0 NaN NaN \n", - "coef_1_plus_other_discretionary_tours_constant 0.0 NaN NaN \n", - "... ... ... ... \n", - "coef_urban_and_shopping_tour 0.0 NaN NaN \n", - "coef_urban_and_tour_frequency_is_1 0.0 NaN NaN \n", - "coef_urban_and_tour_frequency_is_2 0.0 NaN NaN \n", - "coef_urban_and_tour_frequency_is_5_plus 0.0 NaN NaN \n", - "coef_walk_access_to_retail_and_shopping 0.0 NaN NaN \n", + " minimum maximum nullvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0 -2.0 0.0 \n", + "coef_1_escort_tour_constant -20.0 20.0 0.0 \n", + "coef_1_plus_eating_out_tours_constant -20.0 20.0 0.0 \n", + "coef_1_plus_maintenance_tours_constant -20.0 20.0 0.0 \n", + "coef_1_plus_other_discretionary_tours_constant -20.0 20.0 0.0 \n", + "... ... ... ... \n", + "coef_urban_and_shopping_tour -20.0 20.0 0.0 \n", + "coef_urban_and_tour_frequency_is_1 -20.0 20.0 0.0 \n", + "coef_urban_and_tour_frequency_is_2 -20.0 20.0 0.0 \n", + "coef_urban_and_tour_frequency_is_5_plus -20.0 20.0 0.0 \n", + "coef_walk_access_to_retail_and_shopping -20.0 20.0 0.0 \n", "\n", - " holdfast note best \n", - "coef_0_auto_household_and_escorting_tour 1 -2.000000 \n", - "coef_1_escort_tour_constant 0 1.851506 \n", - "coef_1_plus_eating_out_tours_constant 0 -13.970901 \n", - "coef_1_plus_maintenance_tours_constant 0 -0.338031 \n", - "coef_1_plus_other_discretionary_tours_constant 0 -1.473992 \n", - "... ... ... ... \n", - "coef_urban_and_shopping_tour 0 0.711573 \n", - "coef_urban_and_tour_frequency_is_1 0 -3.537340 \n", - "coef_urban_and_tour_frequency_is_2 0 -4.729195 \n", - "coef_urban_and_tour_frequency_is_5_plus 0 -6.020888 \n", - "coef_walk_access_to_retail_and_shopping 0 0.102379 \n", + " holdfast \n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 1 \n", + "coef_1_escort_tour_constant 0 \n", + "coef_1_plus_eating_out_tours_constant 0 \n", + "coef_1_plus_maintenance_tours_constant 0 \n", + "coef_1_plus_other_discretionary_tours_constant 0 \n", + "... ... \n", + "coef_urban_and_shopping_tour 0 \n", + "coef_urban_and_tour_frequency_is_1 0 \n", + "coef_urban_and_tour_frequency_is_2 0 \n", + "coef_urban_and_tour_frequency_is_5_plus 0 \n", + "coef_walk_access_to_retail_and_shopping 0 \n", "\n", - "[70 rows x 8 columns]" + "[70 rows x 7 columns]" ] }, "metadata": {}, @@ -2131,26 +5275,699 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " m.estimate(method='SLSQP')\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.8717456834857003e-13 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model seems to have 13 parameter estimators with negative variance\n", - "- coef_1_plus_eating_out_tours_constant\n", - "- coef_1_plus_shopping_tours_constant\n", - "- coef_1_plus_visting_tours_constant\n", - "- coef_logged_maximum_residual_window_tour_frequency_is_0\n", - "- and 9 more\n", - " m.estimate(method='SLSQP')\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: RuntimeWarning: invalid value encountered in sqrt\n", - " m.estimate(method='SLSQP')\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { "data": { "text/html": [ - "

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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_0_auto_household_and_escorting_tour-2.00 0.00 NA 0.00fixed value
coef_1_escort_tour_constant 1.76 185. 0.01 0.00
coef_1_plus_eating_out_tours_constant 2.21 185. 0.01 0.00
coef_1_plus_maintenance_tours_constant 0.0852 185. 0.00 0.00
coef_1_plus_other_discretionary_tours_constant 1.31 185. 0.01 0.00
coef_1_plus_shopping_tours_constant 1.84 185. 0.01 0.00
coef_1_plus_visting_tours_constant 1.17 185. 0.01 0.00
coef_2_plus_escort_tours_constant 3.01 371. 0.01 0.00
coef_auto_access_to_retail_and_discretionary 0.0900 0.138 0.65 0.00
coef_auto_access_to_retail_and_eating_out 0.0731 0.147 0.50 0.00
coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus-0.790 0.187-4.23*** 0.00
coef_female_and_discretionary_tour-0.393 0.156-2.52* 0.00
coef_female_and_eatingout_tour-0.727 0.176-4.14*** 0.00
coef_female_and_tour_frequency_is_1-0.0110 0.151-0.07 0.00
coef_female_and_tour_frequency_is_2 0.140 0.188 0.74 0.00
coef_female_and_tour_frequency_is_5 1.41 0.250 5.62*** 0.00
coef_high_income_group_and_eating_out_tour-0.130 0.215-0.60 0.00
coef_high_income_group_and_shopping_tour 0.648 0.180 3.60*** 0.00
coef_high_income_group_and_tour_frequency_is_1 0.192 0.180 1.07 0.00
coef_high_income_group_and_tour_frequency_is_2 0.658 0.215 3.07** 0.00
coef_high_income_group_and_tour_frequency_is_5_plus 0.540 0.282 1.92 0.00
coef_high_income_group_and_visiting_tour-0.536 0.215-2.50* 0.00
coef_logged_maximum_residual_window_tour_frequency_is_0 1.14 NA NA 0.00
coef_logged_maximum_residual_window_tour_frequency_is_5_plus 1.53 NA NA 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_1-0.0200 0.180-0.11 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_2 0.0675 0.226 0.30 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_5_plus 0.530 0.268 1.98* 0.00
coef_number_of_joint_discretionary_tours 1.21 0.353 3.43*** 0.00
coef_number_of_joint_shopping_tours-0.600 0.791-0.76 0.00
coef_number_of_joint_tours_and_tour_frequency_is_2-0.543 0.347-1.57 0.00
coef_number_of_joint_tours_and_tour_frequency_is_3-0.800 0.423-1.89 0.00
coef_number_of_joint_tours_and_tour_frequency_is_5_plus-999. 0.00 NA 0.00fixed value
coef_number_of_mandatory_tours_and_tour_frequency_is_1-0.0978 0.170-0.58 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_2-0.496 0.194-2.55* 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_3-1.55 0.250-6.21*** 0.00
coef_presence_of_full_time_worker_and_discretionary_tour-0.576 0.145-3.98*** 0.00
coef_presence_of_full_time_worker_and_eating_out_tour-0.770 0.198-3.89*** 0.00
coef_presence_of_full_time_worker_and_shopping_tour-0.732 0.158-4.63*** 0.00
coef_presence_of_non_worker_and_discretionary_tour 1.12 0.179 6.23*** 0.00
coef_presence_of_non_worker_and_tour_frequency_is_1-0.653 0.180-3.64*** 0.00
coef_presence_of_non_worker_and_tour_frequency_is_5-1.46 0.214-6.82*** 0.00
coef_presence_of_part_time_worker_and_eating_out_tour-2.81 0.388-7.24*** 0.00
coef_presence_of_part_time_worker_and_escorting_tour-1.59 0.172-9.21*** 0.00
coef_presence_of_part_time_worker_and_shopping_tour-0.486 0.156-3.11** 0.00
coef_presence_of_pre_driving_school_kid_and_escorting_tour 0.992 0.114 8.69*** 0.00
coef_presence_of_pre_driving_school_kid_and_maintenance_tour 0.880 0.221 3.98*** 0.00
coef_presence_of_pre_school_kid_and_escorting_tour 1.88 0.216 8.71*** 0.00
coef_presence_of_pre_school_kid_and_maintenance_tour 0.753 0.317 2.38* 0.00
coef_presence_of_pre_school_kid_and_shopping_tour 1.06 0.245 4.32*** 0.00
coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1-1.00 0.269-3.71*** 0.00
coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2-1.76 0.389-4.53*** 0.00
coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5-2.20 0.521-4.23*** 0.00
coef_presence_of_university_student_and_discretionary_tour-0.735 0.169-4.35*** 0.00
coef_presence_of_university_student_and_eating_out_tour-0.545 0.227-2.41* 0.00
coef_total_number_of_tours_is_1-6.46 185.-0.03 0.00
coef_total_number_of_tours_is_2-9.07 371.-0.02 0.00
coef_total_number_of_tours_is_3-12.0 556.-0.02 0.00
coef_total_number_of_tours_is_4-15.8 741.-0.02 0.00
coef_transit_access_to_retail_and_discretionary 0.00 0.00 NA 0.00fixed value
coef_transit_access_to_retail_and_maintenance 0.100 0.0621 1.61 0.00
coef_transit_access_to_retail_and_tour_frequency_is_5_plus 0.0272 0.0421 0.65 0.00
coef_urban_and_discretionary_tour 1.25 0.258 4.83*** 0.00
coef_urban_and_eatingout_tour 0.594 0.274 2.17* 0.00
coef_urban_and_escorting_tour 0.778 0.233 3.35*** 0.00
coef_urban_and_maintenance_tour 0.853 0.339 2.52* 0.00
coef_urban_and_shopping_tour 0.637 0.262 2.43* 0.00
coef_urban_and_tour_frequency_is_1-0.925 0.280-3.30*** 0.00
coef_urban_and_tour_frequency_is_2-2.12 0.455-4.66*** 0.00
coef_urban_and_tour_frequency_is_5_plus-2.50 0.659-3.80*** 0.00
coef_walk_access_to_retail_and_shopping 0.0724 0.0523 1.38 0.00
\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model PTYPE_NONWORK\n" + ] + }, + { + "data": { + "text/html": [ + "

Iteration 152 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -2162,7 +5979,7 @@ { "data": { "text/html": [ - "

Best LL = -1038.9605658891858

" + "

Best LL = -15004.401530353549

" ], "text/plain": [ "" @@ -2193,70 +6010,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_0_auto_household_and_escorting_tour\n", " -2.000000\n", + " -2.000000\n", " -2.0000\n", - " 0.0\n", " -2.0\n", " -2.0\n", + " 0.0\n", " 1\n", - " \n", - " -2.000000\n", " \n", " \n", " coef_1_escort_tour_constant\n", - " -4.317862\n", + " -0.539501\n", + " -0.539501\n", " -0.0629\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.317862\n", " \n", " \n", " coef_1_plus_eating_out_tours_constant\n", - " -4.459267\n", + " -0.520038\n", + " -0.520038\n", " -0.1429\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.459267\n", " \n", " \n", " coef_1_plus_maintenance_tours_constant\n", - " -9.609591\n", + " -0.627098\n", + " -0.627098\n", " -0.0653\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -9.609591\n", " \n", " \n", " coef_1_plus_other_discretionary_tours_constant\n", - " -4.488178\n", + " -0.154697\n", + " -0.154697\n", " 0.3334\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.488178\n", " \n", " \n", " ...\n", @@ -2267,122 +6088,120 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", " coef_walk_access_to_retail_and_discretionary\n", - " 0.214072\n", + " 0.089664\n", + " 0.089664\n", " 0.0772\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.214072\n", " \n", " \n", " coef_walk_access_to_retail_and_shopping\n", - " 0.039849\n", + " 0.080837\n", + " 0.080837\n", " 0.0598\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.039849\n", " \n", " \n", " coef_walk_access_to_retail_and_tour_frequency_is_1\n", - " -0.507092\n", + " 0.126334\n", + " 0.126334\n", " 0.0713\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.507092\n", " \n", " \n", " coef_walk_access_to_retail_and_tour_frequency_is_2\n", - " -0.403984\n", + " 0.186292\n", + " 0.186292\n", " 0.1256\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.403984\n", " \n", " \n", " coef_walk_access_to_retail_and_tour_frequency_is_5_plus\n", - " -0.260693\n", + " 0.163397\n", + " 0.163397\n", " 0.1508\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.260693\n", " \n", " \n", "\n", - "

77 rows × 8 columns

\n", + "

77 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_0_auto_household_and_escorting_tour -2.000000 -2.0000 \n", - "coef_1_escort_tour_constant -4.317862 -0.0629 \n", - "coef_1_plus_eating_out_tours_constant -4.459267 -0.1429 \n", - "coef_1_plus_maintenance_tours_constant -9.609591 -0.0653 \n", - "coef_1_plus_other_discretionary_tours_constant -4.488178 0.3334 \n", - "... ... ... \n", - "coef_walk_access_to_retail_and_discretionary 0.214072 0.0772 \n", - "coef_walk_access_to_retail_and_shopping 0.039849 0.0598 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_1 -0.507092 0.0713 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_2 -0.403984 0.1256 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... -0.260693 0.1508 \n", + " value best \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.000000 \n", + "coef_1_escort_tour_constant -0.539501 -0.539501 \n", + "coef_1_plus_eating_out_tours_constant -0.520038 -0.520038 \n", + "coef_1_plus_maintenance_tours_constant -0.627098 -0.627098 \n", + "coef_1_plus_other_discretionary_tours_constant -0.154697 -0.154697 \n", + "... ... ... \n", + "coef_walk_access_to_retail_and_discretionary 0.089664 0.089664 \n", + "coef_walk_access_to_retail_and_shopping 0.080837 0.080837 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_1 0.126334 0.126334 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_2 0.186292 0.186292 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 0.163397 0.163397 \n", "\n", - " nullvalue minimum \\\n", - "coef_0_auto_household_and_escorting_tour 0.0 -2.0 \n", - "coef_1_escort_tour_constant 0.0 NaN \n", - "coef_1_plus_eating_out_tours_constant 0.0 NaN \n", - "coef_1_plus_maintenance_tours_constant 0.0 NaN \n", - "coef_1_plus_other_discretionary_tours_constant 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0000 -2.0 \n", + "coef_1_escort_tour_constant -0.0629 -20.0 \n", + "coef_1_plus_eating_out_tours_constant -0.1429 -20.0 \n", + "coef_1_plus_maintenance_tours_constant -0.0653 -20.0 \n", + "coef_1_plus_other_discretionary_tours_constant 0.3334 -20.0 \n", "... ... ... \n", - "coef_walk_access_to_retail_and_discretionary 0.0 NaN \n", - "coef_walk_access_to_retail_and_shopping 0.0 NaN \n", - "coef_walk_access_to_retail_and_tour_frequency_is_1 0.0 NaN \n", - "coef_walk_access_to_retail_and_tour_frequency_is_2 0.0 NaN \n", - "coef_walk_access_to_retail_and_tour_frequency_i... 0.0 NaN \n", + "coef_walk_access_to_retail_and_discretionary 0.0772 -20.0 \n", + "coef_walk_access_to_retail_and_shopping 0.0598 -20.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_1 0.0713 -20.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_2 0.1256 -20.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 0.1508 -20.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_0_auto_household_and_escorting_tour -2.0 1 \n", - "coef_1_escort_tour_constant NaN 0 \n", - "coef_1_plus_eating_out_tours_constant NaN 0 \n", - "coef_1_plus_maintenance_tours_constant NaN 0 \n", - "coef_1_plus_other_discretionary_tours_constant NaN 0 \n", - "... ... ... ... \n", - "coef_walk_access_to_retail_and_discretionary NaN 0 \n", - "coef_walk_access_to_retail_and_shopping NaN 0 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_1 NaN 0 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_2 NaN 0 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0 0.0 \n", + "coef_1_escort_tour_constant 20.0 0.0 \n", + "coef_1_plus_eating_out_tours_constant 20.0 0.0 \n", + "coef_1_plus_maintenance_tours_constant 20.0 0.0 \n", + "coef_1_plus_other_discretionary_tours_constant 20.0 0.0 \n", + "... ... ... \n", + "coef_walk_access_to_retail_and_discretionary 20.0 0.0 \n", + "coef_walk_access_to_retail_and_shopping 20.0 0.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_1 20.0 0.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_2 20.0 0.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 20.0 0.0 \n", "\n", - " best \n", - "coef_0_auto_household_and_escorting_tour -2.000000 \n", - "coef_1_escort_tour_constant -4.317862 \n", - "coef_1_plus_eating_out_tours_constant -4.459267 \n", - "coef_1_plus_maintenance_tours_constant -9.609591 \n", - "coef_1_plus_other_discretionary_tours_constant -4.488178 \n", + " holdfast \n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 1 \n", + "coef_1_escort_tour_constant 0 \n", + "coef_1_plus_eating_out_tours_constant 0 \n", + "coef_1_plus_maintenance_tours_constant 0 \n", + "coef_1_plus_other_discretionary_tours_constant 0 \n", "... ... \n", - "coef_walk_access_to_retail_and_discretionary 0.214072 \n", - "coef_walk_access_to_retail_and_shopping 0.039849 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_1 -0.507092 \n", - "coef_walk_access_to_retail_and_tour_frequency_is_2 -0.403984 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... -0.260693 \n", + "coef_walk_access_to_retail_and_discretionary 0 \n", + "coef_walk_access_to_retail_and_shopping 0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_1 0 \n", + "coef_walk_access_to_retail_and_tour_frequency_is_2 0 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 0 \n", "\n", - "[77 rows x 8 columns]" + "[77 rows x 7 columns]" ] }, "metadata": {}, @@ -2392,26 +6211,762 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " m.estimate(method='SLSQP')\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.673077519570165e-16 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model seems to have 21 parameter estimators with negative variance\n", - "- coef_1_escort_tour_constant\n", - "- coef_1_plus_eating_out_tours_constant\n", - "- coef_1_plus_maintenance_tours_constant\n", - "- coef_1_plus_other_discretionary_tours_constant\n", - "- and 17 more\n", - " m.estimate(method='SLSQP')\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: RuntimeWarning: invalid value encountered in sqrt\n", - " m.estimate(method='SLSQP')\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { "data": { "text/html": [ - "

Iteration 074 [Optimization terminated successfully]

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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_0_auto_household_and_escorting_tour-2.00 0.00 NA 0.00fixed value
coef_1_escort_tour_constant-0.540 102.-0.01 0.00
coef_1_plus_eating_out_tours_constant-0.520 102.-0.01 0.00
coef_1_plus_maintenance_tours_constant-0.627 102.-0.01 0.00
coef_1_plus_other_discretionary_tours_constant-0.155 102.-0.00 0.00
coef_1_plus_shopping_tours_constant-0.0544 102.-0.00 0.00
coef_1_plus_visting_tours_constant-0.452 102.-0.00 0.00
coef_2_plus_escort_tours_constant-0.0628 203.-0.00 0.00
coef_at_home_pre_driving_school_kid_and_escorting_tour-1.18 0.154-7.67*** 0.00
coef_at_home_pre_school_kid_and_eating_out_tour-0.368 0.216-1.70 0.00
coef_at_home_pre_school_kid_and_escorting_tour-0.332 0.105-3.18** 0.00
coef_auto_access_to_retail_and_maintenance 0.108 0.0554 1.94 0.00
coef_car_shortage_vs_workers_and_tour_frequency_is_1-0.160 0.414-0.39 0.00
coef_car_shortage_vs_workers_and_tour_frequency_is_2-1.15 0.428-2.70** 0.00
coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus-1.52 0.484-3.14** 0.00
coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus 0.878 0.240 3.65*** 0.00
coef_female_and_maintenance_tour-0.350 0.0674-5.19*** 0.00
coef_female_and_tour_frequency_is_1 0.509 0.192 2.65** 0.00
coef_female_and_tour_frequency_is_2 0.461 0.198 2.33* 0.00
coef_female_and_tour_frequency_is_3 0.637 0.220 2.89** 0.00
coef_female_and_tour_frequency_is_5 0.996 0.304 3.28** 0.00
coef_high_income_group_and_discretionary_tour 0.831 0.107 7.78*** 0.00
coef_high_income_group_and_eating_out_tour 0.589 0.153 3.86*** 0.00
coef_high_income_group_and_shopping_tour 0.913 0.0932 9.79*** 0.00
coef_high_income_group_and_tour_frequency_is_2 1.24 0.312 3.99*** 0.00
coef_high_income_group_and_tour_frequency_is_3 1.94 0.340 5.71*** 0.00
coef_high_income_group_and_tour_frequency_is_5_plus 2.71 0.384 7.04*** 0.00
coef_high_income_group_and_visiting_tour-1.12 0.169-6.63*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_1 3.58 0.342 10.47*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_5_plus 2.85 0.387 7.37*** 0.00
coef_mediumhigh_income_group_and_discretionary_tour 0.511 0.103 4.96*** 0.00
coef_mediumhigh_income_group_and_eating_out_tour 0.441 0.147 3.00** 0.00
coef_mediumhigh_income_group_and_shopping_tour 0.942 0.0888 10.61*** 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_1 0.690 0.282 2.44* 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_2 0.681 0.291 2.34* 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_5_plus 0.625 0.314 1.99* 0.00
coef_mediumhigh_income_group_and_visiting_tour-0.429 0.112-3.83*** 0.00
coef_mediumlow_income_group_and_discretionary_tour 0.141 0.101 1.40 0.00
coef_mediumlow_income_group_and_eating_out_tour 0.125 0.142 0.88 0.00
coef_mediumlow_income_group_and_shopping_tour 0.698 0.0888 7.86*** 0.00
coef_mediumlow_income_group_and_tour_frequency_is_1 0.934 0.288 3.24** 0.00
coef_mediumlow_income_group_and_tour_frequency_is_5_plus 1.11 0.296 3.77*** 0.00
coef_number_of_joint_eating_out_tours-0.263 0.580-0.45 0.00
coef_number_of_joint_shopping_tours-0.612 0.233-2.62** 0.00
coef_number_of_joint_tours_and_tour_frequency_is_1-3.09 1.93-1.60 0.00
coef_number_of_joint_tours_and_tour_frequency_is_2-1.35 1.65-0.81 0.00
coef_number_of_joint_tours_and_tour_frequency_is_3-1.20 1.65-0.73 0.00
coef_number_of_joint_tours_and_tour_frequency_is_5_plus-1.39 1.67-0.83 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_1-0.677 1.06e-09-BIG*** 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_3-1.05 1.80e-09-BIG*** 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus-999. 0.00 NA 0.00fixed value
coef_presence_of_full_time_worker_and_eating_out_tour-0.429 0.109-3.93*** 0.00
coef_presence_of_full_time_worker_and_escorting_tour 0.436 0.0527 8.26*** 0.00
coef_presence_of_non_worker_and_eating_out_tour-0.413 0.107-3.86*** 0.00
coef_presence_of_non_worker_and_tour_frequency_is_1-0.162 0.185-0.87 0.00
coef_presence_of_non_worker_and_tour_frequency_is_2-0.633 0.192-3.30*** 0.00
coef_presence_of_non_worker_and_tour_frequency_is_5-1.03 0.212-4.86*** 0.00
coef_presence_of_part_time_worker_and_discretionary_tour-0.381 0.0565-6.74*** 0.00
coef_presence_of_part_time_worker_and_escorting_tour-0.642 0.0637-10.08*** 0.00
coef_presence_of_pre_driving_school_kid_and_escorting_tour 1.35 0.0589 22.99*** 0.00
coef_presence_of_pre_school_kid_and_escorting_tour 0.820 0.0530 15.45*** 0.00
coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1 0.0317 0.189 0.17 0.00
coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5 0.573 0.200 2.86** 0.00
coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5-0.739 0.186-3.98*** 0.00
coef_presence_of_retiree_and_eating_out_tour-0.778 0.186-4.19*** 0.00
coef_presence_of_retiree_and_tour_frequency_is_1-0.223 0.223-1.00 0.00
coef_presence_of_retiree_and_tour_frequency_is_5-0.225 0.230-0.98 0.00
coef_total_number_of_tours_is_1-10.6 102.-0.10 0.00
coef_total_number_of_tours_is_2-13.0 203.-0.06 0.00
coef_total_number_of_tours_is_3-15.2 305.-0.05 0.00
coef_total_number_of_tours_is_4-17.7 407.-0.04 0.00
coef_urban_and_discretionary_tour 0.00 0.00 NA 0.00fixed value
coef_walk_access_to_retail_and_discretionary 0.0897 0.0225 3.98*** 0.00
coef_walk_access_to_retail_and_shopping 0.0808 0.0199 4.07*** 0.00
coef_walk_access_to_retail_and_tour_frequency_is_1 0.126 0.0653 1.93 0.00
coef_walk_access_to_retail_and_tour_frequency_is_2 0.186 0.0679 2.74** 0.00
coef_walk_access_to_retail_and_tour_frequency_is_5_plus 0.163 0.0735 2.22* 0.00
\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model PTYPE_RETIRED\n" + ] + }, + { + "data": { + "text/html": [ + "

Iteration 076 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -2423,7 +6978,7 @@ { "data": { "text/html": [ - "

Best LL = -787.4000431560225

" + "

Best LL = -7936.229778686792

" ], "text/plain": [ "" @@ -2454,823 +7009,783 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_0_auto_household_and_escorting_tour\n", " -2.000000\n", + " -2.000000\n", " -2.0000\n", - " 0.0\n", " -2.0\n", " -2.0\n", + " 0.0\n", " 1\n", - " \n", - " -2.000000\n", " \n", " \n", " coef_1_escort_tour_constant\n", - " -2.730596\n", + " -0.420225\n", + " -0.420225\n", " -0.3992\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.730596\n", " \n", " \n", " coef_1_plus_eating_out_tours_constant\n", - " -2.583305\n", + " -0.040375\n", + " -0.040375\n", " 0.0245\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.583305\n", " \n", " \n", " coef_1_plus_maintenance_tours_constant\n", - " -2.299219\n", + " 0.008956\n", + " 0.008956\n", " 0.1046\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.299219\n", " \n", " \n", " coef_1_plus_other_discretionary_tours_constant\n", - " -2.243196\n", + " 0.373522\n", + " 0.373522\n", " 0.4282\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.243196\n", " \n", " \n", " coef_1_plus_shopping_tours_constant\n", - " -1.916643\n", + " 0.512414\n", + " 0.512414\n", " 0.5947\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.916643\n", " \n", " \n", " coef_1_plus_visting_tours_constant\n", - " -2.344018\n", + " 0.079465\n", + " 0.079465\n", " 0.2789\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.344018\n", " \n", " \n", " coef_2_plus_escort_tours_constant\n", - " -4.935937\n", + " 0.307462\n", + " 0.307462\n", " 0.5175\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.935937\n", " \n", " \n", " coef_car_surplus_vs_workers_and_tour_frequency_is_1\n", - " 3.094754\n", + " 1.243116\n", + " 1.243116\n", " 0.7965\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 3.094754\n", " \n", " \n", " coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus\n", - " 3.475854\n", + " 2.463002\n", + " 2.463002\n", " 2.1302\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 3.475854\n", " \n", " \n", " coef_female_and_discretionary_tour\n", - " 0.541528\n", + " 0.503760\n", + " 0.503760\n", " 0.4954\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.541528\n", " \n", " \n", " coef_female_and_maintenance_tour\n", - " 0.708328\n", + " 0.726465\n", + " 0.726465\n", " 0.7424\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.708328\n", " \n", " \n", " coef_female_and_shopping_tour\n", - " 0.609316\n", + " 0.951849\n", + " 0.951849\n", " 0.9688\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.609316\n", " \n", " \n", " coef_female_and_tour_frequency_is_1\n", - " -2.519155\n", + " -0.637595\n", + " -0.637595\n", " -0.9348\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.519155\n", " \n", " \n", " coef_female_and_tour_frequency_is_2\n", - " -2.727169\n", + " -0.922030\n", + " -0.922030\n", " -1.3028\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.727169\n", " \n", " \n", " coef_female_and_tour_frequency_is_5\n", - " -4.160203\n", + " -1.995909\n", + " -1.995909\n", " -2.2660\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.160203\n", " \n", " \n", " coef_high_income_group_and_discretionary_tour\n", - " 0.925884\n", + " 0.912572\n", + " 0.912572\n", " 1.0095\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.925884\n", " \n", " \n", " coef_high_income_group_and_eating_out_tour\n", - " 1.624493\n", + " 1.333766\n", + " 1.333766\n", " 1.4842\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.624493\n", " \n", " \n", " coef_high_income_group_and_maintenance_tour\n", - " 1.006105\n", + " 1.269533\n", + " 1.269533\n", " 1.3795\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.006105\n", " \n", " \n", " coef_high_income_group_and_shopping_tour\n", - " 1.105171\n", + " 0.999823\n", + " 0.999823\n", " 1.0949\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.105171\n", " \n", " \n", " coef_high_income_group_and_visiting_tour\n", - " -0.656664\n", + " -0.187117\n", + " -0.187117\n", " -0.5137\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.656664\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_1\n", - " 2.966557\n", + " 2.036712\n", + " 2.036712\n", " 1.8357\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2.966557\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_2\n", - " 5.581416\n", + " 2.413288\n", + " 2.413288\n", " 2.2707\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 5.581416\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_5_plus\n", - " 31.909531\n", + " 4.720353\n", + " 4.720353\n", " 4.4023\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 31.909531\n", " \n", " \n", " coef_mediumhigh_income_group_and_eating_out_tour\n", - " 0.964279\n", + " 0.944127\n", + " 0.944127\n", " 1.1810\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.964279\n", " \n", " \n", " coef_mediumhigh_income_group_and_maintenance_tour\n", - " 0.465351\n", + " 0.688701\n", + " 0.688701\n", " 0.7648\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.465351\n", " \n", " \n", " coef_mediumhigh_income_group_and_visiting_tour\n", - " -0.478169\n", + " -0.370854\n", + " -0.370854\n", " -0.4368\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.478169\n", " \n", " \n", " coef_mediumlow_income_group_and_eating_out_tour\n", - " 0.877486\n", + " 0.937822\n", + " 0.937822\n", " 0.9769\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.877486\n", " \n", " \n", " coef_number_of_joint_shopping_tours\n", - " -0.290998\n", + " -1.313333\n", + " -1.313333\n", " -0.8072\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.290998\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_2\n", - " -6.327143\n", + " -1.010634\n", + " -1.010634\n", " -0.9500\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -6.327143\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_3\n", - " -85.627389\n", + " -7.212476\n", + " -7.212476\n", " -7.1430\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -85.627389\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_5_plus\n", " -999.000000\n", + " -999.000000\n", " -999.0000\n", - " 0.0\n", " -999.0\n", " -999.0\n", + " 0.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_3\n", " -5.019600\n", + " -5.019600\n", " -5.0196\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -5.019600\n", " \n", " \n", " coef_presence_of_full_time_worker_and_discretionary_tour\n", - " -0.331984\n", + " -0.657085\n", + " -0.657085\n", " -0.4835\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.331984\n", " \n", " \n", " coef_presence_of_full_time_worker_and_shopping_tour\n", - " -0.207325\n", + " -0.421774\n", + " -0.421774\n", " -0.3609\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.207325\n", " \n", " \n", " coef_presence_of_non_worker_and_discretionary_tour\n", - " -0.084104\n", + " -0.575662\n", + " -0.575662\n", " -0.5603\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.084104\n", " \n", " \n", " coef_presence_of_non_worker_and_eating_out_tour\n", - " -0.701536\n", + " -0.905311\n", + " -0.905311\n", " -0.7880\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.701536\n", " \n", " \n", " coef_presence_of_non_worker_and_tour_frequency_is_1\n", - " 1.190681\n", + " -0.017018\n", + " -0.017018\n", " 0.2240\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.190681\n", " \n", " \n", " coef_presence_of_non_worker_and_tour_frequency_is_2\n", - " 1.374195\n", + " 0.067997\n", + " 0.067997\n", " 0.2436\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.374195\n", " \n", " \n", " coef_presence_of_non_worker_and_tour_frequency_is_3\n", - " 2.156822\n", + " 0.258114\n", + " 0.258114\n", " 0.6200\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 2.156822\n", " \n", " \n", " coef_presence_of_non_worker_and_tour_frequency_is_5\n", - " 3.694303\n", + " 3.203479\n", + " 3.203479\n", " 3.3742\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 3.694303\n", " \n", " \n", " coef_presence_of_pre_driving_school_kid_and_escorting_tour\n", - " 1.682880\n", + " 1.424066\n", + " 1.424066\n", " 1.4903\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.682880\n", " \n", " \n", " coef_presence_of_pre_school_kid_and_escorting_tour\n", - " 0.641813\n", + " 0.393961\n", + " 0.393961\n", " 0.5027\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.641813\n", " \n", " \n", " coef_presence_of_retiree_and_eating_out_tour\n", - " -0.944680\n", + " -0.793588\n", + " -0.793588\n", " -0.9282\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.944680\n", " \n", " \n", " coef_presence_of_retiree_and_tour_frequency_is_1\n", - " 0.321424\n", + " -0.721457\n", + " -0.721457\n", " -0.4458\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.321424\n", " \n", " \n", " coef_presence_of_retiree_and_tour_frequency_is_5\n", - " -0.051242\n", + " -0.751932\n", + " -0.751932\n", " -0.5315\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.051242\n", " \n", " \n", " coef_total_number_of_tours_is_1\n", - " -14.532345\n", + " -8.702153\n", + " -8.702153\n", " -8.5684\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -14.532345\n", " \n", " \n", " coef_total_number_of_tours_is_2\n", - " -15.267480\n", + " -12.664662\n", + " -12.664662\n", " -12.7416\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -15.267480\n", " \n", " \n", " coef_total_number_of_tours_is_3\n", - " -15.029318\n", + " -14.734677\n", + " -14.734677\n", " -15.0978\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -15.029318\n", " \n", " \n", " coef_total_number_of_tours_is_4\n", - " -14.905140\n", + " -19.432621\n", + " -19.432621\n", " -19.5439\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -14.905140\n", " \n", " \n", " coef_total_number_of_tours_is_5\n", - " -27.549766\n", + " -19.999982\n", + " -19.999982\n", " -20.7897\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -27.549766\n", " \n", " \n", " coef_urban_and_discretionary_tour\n", " 0.000000\n", + " 0.000000\n", " 0.0000\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_walk_access_to_retail_and_tour_frequency_is_5_plus\n", - " 0.691082\n", + " -0.010167\n", + " -0.010167\n", " 0.0616\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.691082\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_0_auto_household_and_escorting_tour -2.000000 -2.0000 \n", - "coef_1_escort_tour_constant -2.730596 -0.3992 \n", - "coef_1_plus_eating_out_tours_constant -2.583305 0.0245 \n", - "coef_1_plus_maintenance_tours_constant -2.299219 0.1046 \n", - "coef_1_plus_other_discretionary_tours_constant -2.243196 0.4282 \n", - "coef_1_plus_shopping_tours_constant -1.916643 0.5947 \n", - "coef_1_plus_visting_tours_constant -2.344018 0.2789 \n", - "coef_2_plus_escort_tours_constant -4.935937 0.5175 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 3.094754 0.7965 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 3.475854 2.1302 \n", - "coef_female_and_discretionary_tour 0.541528 0.4954 \n", - "coef_female_and_maintenance_tour 0.708328 0.7424 \n", - "coef_female_and_shopping_tour 0.609316 0.9688 \n", - "coef_female_and_tour_frequency_is_1 -2.519155 -0.9348 \n", - "coef_female_and_tour_frequency_is_2 -2.727169 -1.3028 \n", - "coef_female_and_tour_frequency_is_5 -4.160203 -2.2660 \n", - "coef_high_income_group_and_discretionary_tour 0.925884 1.0095 \n", - "coef_high_income_group_and_eating_out_tour 1.624493 1.4842 \n", - "coef_high_income_group_and_maintenance_tour 1.006105 1.3795 \n", - "coef_high_income_group_and_shopping_tour 1.105171 1.0949 \n", - "coef_high_income_group_and_visiting_tour -0.656664 -0.5137 \n", - "coef_logged_maximum_residual_window_tour_freque... 2.966557 1.8357 \n", - "coef_logged_maximum_residual_window_tour_freque... 5.581416 2.2707 \n", - "coef_logged_maximum_residual_window_tour_freque... 31.909531 4.4023 \n", - "coef_mediumhigh_income_group_and_eating_out_tour 0.964279 1.1810 \n", - "coef_mediumhigh_income_group_and_maintenance_tour 0.465351 0.7648 \n", - "coef_mediumhigh_income_group_and_visiting_tour -0.478169 -0.4368 \n", - "coef_mediumlow_income_group_and_eating_out_tour 0.877486 0.9769 \n", - "coef_number_of_joint_shopping_tours -0.290998 -0.8072 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 -6.327143 -0.9500 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_3 -85.627389 -7.1430 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.0000 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -5.019600 -5.0196 \n", - "coef_presence_of_full_time_worker_and_discretio... -0.331984 -0.4835 \n", - "coef_presence_of_full_time_worker_and_shopping_... -0.207325 -0.3609 \n", - "coef_presence_of_non_worker_and_discretionary_tour -0.084104 -0.5603 \n", - "coef_presence_of_non_worker_and_eating_out_tour -0.701536 -0.7880 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 1.190681 0.2240 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 1.374195 0.2436 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 2.156822 0.6200 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 3.694303 3.3742 \n", - "coef_presence_of_pre_driving_school_kid_and_esc... 1.682880 1.4903 \n", - "coef_presence_of_pre_school_kid_and_escorting_tour 0.641813 0.5027 \n", - "coef_presence_of_retiree_and_eating_out_tour -0.944680 -0.9282 \n", - "coef_presence_of_retiree_and_tour_frequency_is_1 0.321424 -0.4458 \n", - "coef_presence_of_retiree_and_tour_frequency_is_5 -0.051242 -0.5315 \n", - "coef_total_number_of_tours_is_1 -14.532345 -8.5684 \n", - "coef_total_number_of_tours_is_2 -15.267480 -12.7416 \n", - "coef_total_number_of_tours_is_3 -15.029318 -15.0978 \n", - "coef_total_number_of_tours_is_4 -14.905140 -19.5439 \n", - "coef_total_number_of_tours_is_5 -27.549766 -20.7897 \n", - "coef_urban_and_discretionary_tour 0.000000 0.0000 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... 0.691082 0.0616 \n", + " value best \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.000000 \n", + "coef_1_escort_tour_constant -0.420225 -0.420225 \n", + "coef_1_plus_eating_out_tours_constant -0.040375 -0.040375 \n", + "coef_1_plus_maintenance_tours_constant 0.008956 0.008956 \n", + "coef_1_plus_other_discretionary_tours_constant 0.373522 0.373522 \n", + "coef_1_plus_shopping_tours_constant 0.512414 0.512414 \n", + "coef_1_plus_visting_tours_constant 0.079465 0.079465 \n", + "coef_2_plus_escort_tours_constant 0.307462 0.307462 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 1.243116 1.243116 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 2.463002 2.463002 \n", + "coef_female_and_discretionary_tour 0.503760 0.503760 \n", + "coef_female_and_maintenance_tour 0.726465 0.726465 \n", + "coef_female_and_shopping_tour 0.951849 0.951849 \n", + "coef_female_and_tour_frequency_is_1 -0.637595 -0.637595 \n", + "coef_female_and_tour_frequency_is_2 -0.922030 -0.922030 \n", + "coef_female_and_tour_frequency_is_5 -1.995909 -1.995909 \n", + "coef_high_income_group_and_discretionary_tour 0.912572 0.912572 \n", + "coef_high_income_group_and_eating_out_tour 1.333766 1.333766 \n", + "coef_high_income_group_and_maintenance_tour 1.269533 1.269533 \n", + "coef_high_income_group_and_shopping_tour 0.999823 0.999823 \n", + "coef_high_income_group_and_visiting_tour -0.187117 -0.187117 \n", + "coef_logged_maximum_residual_window_tour_freque... 2.036712 2.036712 \n", + "coef_logged_maximum_residual_window_tour_freque... 2.413288 2.413288 \n", + "coef_logged_maximum_residual_window_tour_freque... 4.720353 4.720353 \n", + "coef_mediumhigh_income_group_and_eating_out_tour 0.944127 0.944127 \n", + "coef_mediumhigh_income_group_and_maintenance_tour 0.688701 0.688701 \n", + "coef_mediumhigh_income_group_and_visiting_tour -0.370854 -0.370854 \n", + "coef_mediumlow_income_group_and_eating_out_tour 0.937822 0.937822 \n", + "coef_number_of_joint_shopping_tours -1.313333 -1.313333 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 -1.010634 -1.010634 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_3 -7.212476 -7.212476 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.000000 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -5.019600 -5.019600 \n", + "coef_presence_of_full_time_worker_and_discretio... -0.657085 -0.657085 \n", + "coef_presence_of_full_time_worker_and_shopping_... -0.421774 -0.421774 \n", + "coef_presence_of_non_worker_and_discretionary_tour -0.575662 -0.575662 \n", + "coef_presence_of_non_worker_and_eating_out_tour -0.905311 -0.905311 \n", + "coef_presence_of_non_worker_and_tour_frequency_... -0.017018 -0.017018 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0.067997 0.067997 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0.258114 0.258114 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 3.203479 3.203479 \n", + "coef_presence_of_pre_driving_school_kid_and_esc... 1.424066 1.424066 \n", + "coef_presence_of_pre_school_kid_and_escorting_tour 0.393961 0.393961 \n", + "coef_presence_of_retiree_and_eating_out_tour -0.793588 -0.793588 \n", + "coef_presence_of_retiree_and_tour_frequency_is_1 -0.721457 -0.721457 \n", + "coef_presence_of_retiree_and_tour_frequency_is_5 -0.751932 -0.751932 \n", + "coef_total_number_of_tours_is_1 -8.702153 -8.702153 \n", + "coef_total_number_of_tours_is_2 -12.664662 -12.664662 \n", + "coef_total_number_of_tours_is_3 -14.734677 -14.734677 \n", + "coef_total_number_of_tours_is_4 -19.432621 -19.432621 \n", + "coef_total_number_of_tours_is_5 -19.999982 -19.999982 \n", + "coef_urban_and_discretionary_tour 0.000000 0.000000 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... -0.010167 -0.010167 \n", "\n", - " nullvalue minimum \\\n", - "coef_0_auto_household_and_escorting_tour 0.0 -2.0 \n", - "coef_1_escort_tour_constant 0.0 NaN \n", - "coef_1_plus_eating_out_tours_constant 0.0 NaN \n", - "coef_1_plus_maintenance_tours_constant 0.0 NaN \n", - "coef_1_plus_other_discretionary_tours_constant 0.0 NaN \n", - "coef_1_plus_shopping_tours_constant 0.0 NaN \n", - "coef_1_plus_visting_tours_constant 0.0 NaN \n", - "coef_2_plus_escort_tours_constant 0.0 NaN \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 0.0 NaN \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 0.0 NaN \n", - "coef_female_and_discretionary_tour 0.0 NaN \n", - "coef_female_and_maintenance_tour 0.0 NaN \n", - "coef_female_and_shopping_tour 0.0 NaN \n", - "coef_female_and_tour_frequency_is_1 0.0 NaN \n", - "coef_female_and_tour_frequency_is_2 0.0 NaN \n", - "coef_female_and_tour_frequency_is_5 0.0 NaN \n", - "coef_high_income_group_and_discretionary_tour 0.0 NaN \n", - "coef_high_income_group_and_eating_out_tour 0.0 NaN \n", - "coef_high_income_group_and_maintenance_tour 0.0 NaN \n", - "coef_high_income_group_and_shopping_tour 0.0 NaN \n", - "coef_high_income_group_and_visiting_tour 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_mediumhigh_income_group_and_eating_out_tour 0.0 NaN \n", - "coef_mediumhigh_income_group_and_maintenance_tour 0.0 NaN \n", - "coef_mediumhigh_income_group_and_visiting_tour 0.0 NaN \n", - "coef_mediumlow_income_group_and_eating_out_tour 0.0 NaN \n", - "coef_number_of_joint_shopping_tours 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_is_3 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_i... 0.0 -999.0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_presence_of_full_time_worker_and_discretio... 0.0 NaN \n", - "coef_presence_of_full_time_worker_and_shopping_... 0.0 NaN \n", - "coef_presence_of_non_worker_and_discretionary_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_eating_out_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_tour_frequency_... 0.0 NaN \n", - "coef_presence_of_non_worker_and_tour_frequency_... 0.0 NaN \n", - "coef_presence_of_non_worker_and_tour_frequency_... 0.0 NaN \n", - "coef_presence_of_non_worker_and_tour_frequency_... 0.0 NaN \n", - "coef_presence_of_pre_driving_school_kid_and_esc... 0.0 NaN \n", - "coef_presence_of_pre_school_kid_and_escorting_tour 0.0 NaN \n", - "coef_presence_of_retiree_and_eating_out_tour 0.0 NaN \n", - "coef_presence_of_retiree_and_tour_frequency_is_1 0.0 NaN \n", - "coef_presence_of_retiree_and_tour_frequency_is_5 0.0 NaN \n", - "coef_total_number_of_tours_is_1 0.0 NaN \n", - "coef_total_number_of_tours_is_2 0.0 NaN \n", - "coef_total_number_of_tours_is_3 0.0 NaN \n", - "coef_total_number_of_tours_is_4 0.0 NaN \n", - "coef_total_number_of_tours_is_5 0.0 NaN \n", - "coef_urban_and_discretionary_tour 0.0 0.0 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0000 -2.0 \n", + "coef_1_escort_tour_constant -0.3992 -20.0 \n", + "coef_1_plus_eating_out_tours_constant 0.0245 -20.0 \n", + "coef_1_plus_maintenance_tours_constant 0.1046 -20.0 \n", + "coef_1_plus_other_discretionary_tours_constant 0.4282 -20.0 \n", + "coef_1_plus_shopping_tours_constant 0.5947 -20.0 \n", + "coef_1_plus_visting_tours_constant 0.2789 -20.0 \n", + "coef_2_plus_escort_tours_constant 0.5175 -20.0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 0.7965 -20.0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 2.1302 -20.0 \n", + "coef_female_and_discretionary_tour 0.4954 -20.0 \n", + "coef_female_and_maintenance_tour 0.7424 -20.0 \n", + "coef_female_and_shopping_tour 0.9688 -20.0 \n", + "coef_female_and_tour_frequency_is_1 -0.9348 -20.0 \n", + "coef_female_and_tour_frequency_is_2 -1.3028 -20.0 \n", + "coef_female_and_tour_frequency_is_5 -2.2660 -20.0 \n", + "coef_high_income_group_and_discretionary_tour 1.0095 -20.0 \n", + "coef_high_income_group_and_eating_out_tour 1.4842 -20.0 \n", + "coef_high_income_group_and_maintenance_tour 1.3795 -20.0 \n", + "coef_high_income_group_and_shopping_tour 1.0949 -20.0 \n", + "coef_high_income_group_and_visiting_tour -0.5137 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.8357 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 2.2707 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 4.4023 -20.0 \n", + "coef_mediumhigh_income_group_and_eating_out_tour 1.1810 -20.0 \n", + "coef_mediumhigh_income_group_and_maintenance_tour 0.7648 -20.0 \n", + "coef_mediumhigh_income_group_and_visiting_tour -0.4368 -20.0 \n", + "coef_mediumlow_income_group_and_eating_out_tour 0.9769 -20.0 \n", + "coef_number_of_joint_shopping_tours -0.8072 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 -0.9500 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_3 -7.1430 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.0000 -999.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -5.0196 -20.0 \n", + "coef_presence_of_full_time_worker_and_discretio... -0.4835 -20.0 \n", + "coef_presence_of_full_time_worker_and_shopping_... -0.3609 -20.0 \n", + "coef_presence_of_non_worker_and_discretionary_tour -0.5603 -20.0 \n", + "coef_presence_of_non_worker_and_eating_out_tour -0.7880 -20.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0.2240 -20.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0.2436 -20.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0.6200 -20.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 3.3742 -20.0 \n", + "coef_presence_of_pre_driving_school_kid_and_esc... 1.4903 -20.0 \n", + "coef_presence_of_pre_school_kid_and_escorting_tour 0.5027 -20.0 \n", + "coef_presence_of_retiree_and_eating_out_tour -0.9282 -20.0 \n", + "coef_presence_of_retiree_and_tour_frequency_is_1 -0.4458 -20.0 \n", + "coef_presence_of_retiree_and_tour_frequency_is_5 -0.5315 -20.0 \n", + "coef_total_number_of_tours_is_1 -8.5684 -20.0 \n", + "coef_total_number_of_tours_is_2 -12.7416 -20.0 \n", + "coef_total_number_of_tours_is_3 -15.0978 -20.0 \n", + "coef_total_number_of_tours_is_4 -19.5439 -20.0 \n", + "coef_total_number_of_tours_is_5 -20.7897 -20.0 \n", + "coef_urban_and_discretionary_tour 0.0000 0.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 0.0616 -20.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_0_auto_household_and_escorting_tour -2.0 1 \n", - "coef_1_escort_tour_constant NaN 0 \n", - "coef_1_plus_eating_out_tours_constant NaN 0 \n", - "coef_1_plus_maintenance_tours_constant NaN 0 \n", - "coef_1_plus_other_discretionary_tours_constant NaN 0 \n", - "coef_1_plus_shopping_tours_constant NaN 0 \n", - "coef_1_plus_visting_tours_constant NaN 0 \n", - "coef_2_plus_escort_tours_constant NaN 0 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... NaN 0 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... NaN 0 \n", - "coef_female_and_discretionary_tour NaN 0 \n", - "coef_female_and_maintenance_tour NaN 0 \n", - "coef_female_and_shopping_tour NaN 0 \n", - "coef_female_and_tour_frequency_is_1 NaN 0 \n", - "coef_female_and_tour_frequency_is_2 NaN 0 \n", - "coef_female_and_tour_frequency_is_5 NaN 0 \n", - "coef_high_income_group_and_discretionary_tour NaN 0 \n", - "coef_high_income_group_and_eating_out_tour NaN 0 \n", - "coef_high_income_group_and_maintenance_tour NaN 0 \n", - "coef_high_income_group_and_shopping_tour NaN 0 \n", - "coef_high_income_group_and_visiting_tour NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_mediumhigh_income_group_and_eating_out_tour NaN 0 \n", - "coef_mediumhigh_income_group_and_maintenance_tour NaN 0 \n", - "coef_mediumhigh_income_group_and_visiting_tour NaN 0 \n", - "coef_mediumlow_income_group_and_eating_out_tour NaN 0 \n", - "coef_number_of_joint_shopping_tours NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_3 NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.0 1 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_presence_of_full_time_worker_and_discretio... NaN 0 \n", - "coef_presence_of_full_time_worker_and_shopping_... NaN 0 \n", - "coef_presence_of_non_worker_and_discretionary_tour NaN 0 \n", - "coef_presence_of_non_worker_and_eating_out_tour NaN 0 \n", - "coef_presence_of_non_worker_and_tour_frequency_... NaN 0 \n", - "coef_presence_of_non_worker_and_tour_frequency_... NaN 0 \n", - "coef_presence_of_non_worker_and_tour_frequency_... NaN 0 \n", - "coef_presence_of_non_worker_and_tour_frequency_... NaN 0 \n", - "coef_presence_of_pre_driving_school_kid_and_esc... NaN 0 \n", - "coef_presence_of_pre_school_kid_and_escorting_tour NaN 0 \n", - "coef_presence_of_retiree_and_eating_out_tour NaN 0 \n", - "coef_presence_of_retiree_and_tour_frequency_is_1 NaN 0 \n", - "coef_presence_of_retiree_and_tour_frequency_is_5 NaN 0 \n", - "coef_total_number_of_tours_is_1 NaN 0 \n", - "coef_total_number_of_tours_is_2 NaN 0 \n", - "coef_total_number_of_tours_is_3 NaN 0 \n", - "coef_total_number_of_tours_is_4 NaN 0 \n", - "coef_total_number_of_tours_is_5 NaN 0 \n", - "coef_urban_and_discretionary_tour 0.0 1 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0 0.0 \n", + "coef_1_escort_tour_constant 20.0 0.0 \n", + "coef_1_plus_eating_out_tours_constant 20.0 0.0 \n", + "coef_1_plus_maintenance_tours_constant 20.0 0.0 \n", + "coef_1_plus_other_discretionary_tours_constant 20.0 0.0 \n", + "coef_1_plus_shopping_tours_constant 20.0 0.0 \n", + "coef_1_plus_visting_tours_constant 20.0 0.0 \n", + "coef_2_plus_escort_tours_constant 20.0 0.0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 20.0 0.0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 20.0 0.0 \n", + "coef_female_and_discretionary_tour 20.0 0.0 \n", + "coef_female_and_maintenance_tour 20.0 0.0 \n", + "coef_female_and_shopping_tour 20.0 0.0 \n", + "coef_female_and_tour_frequency_is_1 20.0 0.0 \n", + "coef_female_and_tour_frequency_is_2 20.0 0.0 \n", + "coef_female_and_tour_frequency_is_5 20.0 0.0 \n", + "coef_high_income_group_and_discretionary_tour 20.0 0.0 \n", + "coef_high_income_group_and_eating_out_tour 20.0 0.0 \n", + "coef_high_income_group_and_maintenance_tour 20.0 0.0 \n", + "coef_high_income_group_and_shopping_tour 20.0 0.0 \n", + "coef_high_income_group_and_visiting_tour 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_mediumhigh_income_group_and_eating_out_tour 20.0 0.0 \n", + "coef_mediumhigh_income_group_and_maintenance_tour 20.0 0.0 \n", + "coef_mediumhigh_income_group_and_visiting_tour 20.0 0.0 \n", + "coef_mediumlow_income_group_and_eating_out_tour 20.0 0.0 \n", + "coef_number_of_joint_shopping_tours 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_3 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_presence_of_full_time_worker_and_discretio... 20.0 0.0 \n", + "coef_presence_of_full_time_worker_and_shopping_... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_discretionary_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 20.0 0.0 \n", + "coef_presence_of_pre_driving_school_kid_and_esc... 20.0 0.0 \n", + "coef_presence_of_pre_school_kid_and_escorting_tour 20.0 0.0 \n", + "coef_presence_of_retiree_and_eating_out_tour 20.0 0.0 \n", + "coef_presence_of_retiree_and_tour_frequency_is_1 20.0 0.0 \n", + "coef_presence_of_retiree_and_tour_frequency_is_5 20.0 0.0 \n", + "coef_total_number_of_tours_is_1 20.0 0.0 \n", + "coef_total_number_of_tours_is_2 20.0 0.0 \n", + "coef_total_number_of_tours_is_3 20.0 0.0 \n", + "coef_total_number_of_tours_is_4 20.0 0.0 \n", + "coef_total_number_of_tours_is_5 20.0 0.0 \n", + "coef_urban_and_discretionary_tour 0.0 0.0 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 20.0 0.0 \n", "\n", - " best \n", - "coef_0_auto_household_and_escorting_tour -2.000000 \n", - "coef_1_escort_tour_constant -2.730596 \n", - "coef_1_plus_eating_out_tours_constant -2.583305 \n", - "coef_1_plus_maintenance_tours_constant -2.299219 \n", - "coef_1_plus_other_discretionary_tours_constant -2.243196 \n", - "coef_1_plus_shopping_tours_constant -1.916643 \n", - "coef_1_plus_visting_tours_constant -2.344018 \n", - "coef_2_plus_escort_tours_constant -4.935937 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 3.094754 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 3.475854 \n", - "coef_female_and_discretionary_tour 0.541528 \n", - "coef_female_and_maintenance_tour 0.708328 \n", - "coef_female_and_shopping_tour 0.609316 \n", - "coef_female_and_tour_frequency_is_1 -2.519155 \n", - "coef_female_and_tour_frequency_is_2 -2.727169 \n", - "coef_female_and_tour_frequency_is_5 -4.160203 \n", - "coef_high_income_group_and_discretionary_tour 0.925884 \n", - "coef_high_income_group_and_eating_out_tour 1.624493 \n", - "coef_high_income_group_and_maintenance_tour 1.006105 \n", - "coef_high_income_group_and_shopping_tour 1.105171 \n", - "coef_high_income_group_and_visiting_tour -0.656664 \n", - "coef_logged_maximum_residual_window_tour_freque... 2.966557 \n", - "coef_logged_maximum_residual_window_tour_freque... 5.581416 \n", - "coef_logged_maximum_residual_window_tour_freque... 31.909531 \n", - "coef_mediumhigh_income_group_and_eating_out_tour 0.964279 \n", - "coef_mediumhigh_income_group_and_maintenance_tour 0.465351 \n", - "coef_mediumhigh_income_group_and_visiting_tour -0.478169 \n", - "coef_mediumlow_income_group_and_eating_out_tour 0.877486 \n", - "coef_number_of_joint_shopping_tours -0.290998 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 -6.327143 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_3 -85.627389 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -5.019600 \n", - "coef_presence_of_full_time_worker_and_discretio... -0.331984 \n", - "coef_presence_of_full_time_worker_and_shopping_... -0.207325 \n", - "coef_presence_of_non_worker_and_discretionary_tour -0.084104 \n", - "coef_presence_of_non_worker_and_eating_out_tour -0.701536 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 1.190681 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 1.374195 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 2.156822 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 3.694303 \n", - "coef_presence_of_pre_driving_school_kid_and_esc... 1.682880 \n", - "coef_presence_of_pre_school_kid_and_escorting_tour 0.641813 \n", - "coef_presence_of_retiree_and_eating_out_tour -0.944680 \n", - "coef_presence_of_retiree_and_tour_frequency_is_1 0.321424 \n", - "coef_presence_of_retiree_and_tour_frequency_is_5 -0.051242 \n", - "coef_total_number_of_tours_is_1 -14.532345 \n", - "coef_total_number_of_tours_is_2 -15.267480 \n", - "coef_total_number_of_tours_is_3 -15.029318 \n", - "coef_total_number_of_tours_is_4 -14.905140 \n", - "coef_total_number_of_tours_is_5 -27.549766 \n", - "coef_urban_and_discretionary_tour 0.000000 \n", - "coef_walk_access_to_retail_and_tour_frequency_i... 0.691082 " + " holdfast \n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 1 \n", + "coef_1_escort_tour_constant 0 \n", + "coef_1_plus_eating_out_tours_constant 0 \n", + "coef_1_plus_maintenance_tours_constant 0 \n", + "coef_1_plus_other_discretionary_tours_constant 0 \n", + "coef_1_plus_shopping_tours_constant 0 \n", + "coef_1_plus_visting_tours_constant 0 \n", + "coef_2_plus_escort_tours_constant 0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 0 \n", + "coef_female_and_discretionary_tour 0 \n", + "coef_female_and_maintenance_tour 0 \n", + "coef_female_and_shopping_tour 0 \n", + "coef_female_and_tour_frequency_is_1 0 \n", + "coef_female_and_tour_frequency_is_2 0 \n", + "coef_female_and_tour_frequency_is_5 0 \n", + "coef_high_income_group_and_discretionary_tour 0 \n", + "coef_high_income_group_and_eating_out_tour 0 \n", + "coef_high_income_group_and_maintenance_tour 0 \n", + "coef_high_income_group_and_shopping_tour 0 \n", + "coef_high_income_group_and_visiting_tour 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_mediumhigh_income_group_and_eating_out_tour 0 \n", + "coef_mediumhigh_income_group_and_maintenance_tour 0 \n", + "coef_mediumhigh_income_group_and_visiting_tour 0 \n", + "coef_mediumlow_income_group_and_eating_out_tour 0 \n", + "coef_number_of_joint_shopping_tours 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_3 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... 1 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_presence_of_full_time_worker_and_discretio... 0 \n", + "coef_presence_of_full_time_worker_and_shopping_... 0 \n", + "coef_presence_of_non_worker_and_discretionary_tour 0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0 \n", + "coef_presence_of_pre_driving_school_kid_and_esc... 0 \n", + "coef_presence_of_pre_school_kid_and_escorting_tour 0 \n", + "coef_presence_of_retiree_and_eating_out_tour 0 \n", + "coef_presence_of_retiree_and_tour_frequency_is_1 0 \n", + "coef_presence_of_retiree_and_tour_frequency_is_5 0 \n", + "coef_total_number_of_tours_is_1 0 \n", + "coef_total_number_of_tours_is_2 0 \n", + "coef_total_number_of_tours_is_3 0 \n", + "coef_total_number_of_tours_is_4 0 \n", + "coef_total_number_of_tours_is_5 0 \n", + "coef_urban_and_discretionary_tour 1 \n", + "coef_walk_access_to_retail_and_tour_frequency_i... 0 " ] }, "metadata": {}, @@ -3280,26 +7795,546 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " m.estimate(method='SLSQP')\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.7375419460797773e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model seems to have 11 parameter estimators with negative variance\n", - "- coef_1_escort_tour_constant\n", - "- coef_1_plus_eating_out_tours_constant\n", - "- coef_1_plus_maintenance_tours_constant\n", - "- coef_1_plus_other_discretionary_tours_constant\n", - "- and 7 more\n", - " m.estimate(method='SLSQP')\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: RuntimeWarning: invalid value encountered in sqrt\n", - 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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_0_auto_household_and_escorting_tour-2.00 0.00 NA 0.00fixed value
coef_1_escort_tour_constant-0.420 NA NA 0.00
coef_1_plus_eating_out_tours_constant-0.0404 NA NA 0.00
coef_1_plus_maintenance_tours_constant 0.00896 NA NA 0.00
coef_1_plus_other_discretionary_tours_constant 0.374 NA NA 0.00
coef_1_plus_shopping_tours_constant 0.512 NA NA 0.00
coef_1_plus_visting_tours_constant 0.0795 NA NA 0.00
coef_2_plus_escort_tours_constant 0.307 NA NA 0.00
coef_car_surplus_vs_workers_and_tour_frequency_is_1 1.24 0.325 3.82*** 0.00
coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus 2.46 0.352 7.00*** 0.00
coef_female_and_discretionary_tour 0.504 0.0998 5.05*** 0.00
coef_female_and_maintenance_tour 0.726 0.101 7.19*** 0.00
coef_female_and_shopping_tour 0.952 0.0924 10.30*** 0.00
coef_female_and_tour_frequency_is_1-0.638 0.212-3.00** 0.00
coef_female_and_tour_frequency_is_2-0.922 0.243-3.79*** 0.00
coef_female_and_tour_frequency_is_5-2.00 0.299-6.67*** 0.00
coef_high_income_group_and_discretionary_tour 0.913 0.110 8.32*** 0.00
coef_high_income_group_and_eating_out_tour 1.33 0.218 6.13*** 0.00
coef_high_income_group_and_maintenance_tour 1.27 0.137 9.27*** 0.00
coef_high_income_group_and_shopping_tour 1.00 0.102 9.82*** 0.00
coef_high_income_group_and_visiting_tour-0.187 0.184-1.02 0.00
coef_logged_maximum_residual_window_tour_frequency_is_1 2.04 0.397 5.13*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_2 2.41 0.555 4.35*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_5_plus 4.72 1.20 3.94*** 0.00
coef_mediumhigh_income_group_and_eating_out_tour 0.944 0.193 4.88*** 0.00
coef_mediumhigh_income_group_and_maintenance_tour 0.689 0.112 6.16*** 0.00
coef_mediumhigh_income_group_and_visiting_tour-0.371 0.155-2.40* 0.00
coef_mediumlow_income_group_and_eating_out_tour 0.938 0.162 5.79*** 0.00
coef_number_of_joint_shopping_tours-1.31 0.343-3.83*** 0.00
coef_number_of_joint_tours_and_tour_frequency_is_2-1.01 1.37-0.74 0.00
coef_number_of_joint_tours_and_tour_frequency_is_3-7.21 3.36-2.15* 0.00
coef_number_of_joint_tours_and_tour_frequency_is_5_plus-999. 0.00 NA 0.00fixed value
coef_number_of_mandatory_tours_and_tour_frequency_is_3-5.02 1.36e-09-BIG*** 0.00
coef_presence_of_full_time_worker_and_discretionary_tour-0.657 0.104-6.31*** 0.00
coef_presence_of_full_time_worker_and_shopping_tour-0.422 0.0891-4.73*** 0.00
coef_presence_of_non_worker_and_discretionary_tour-0.576 0.128-4.50*** 0.00
coef_presence_of_non_worker_and_eating_out_tour-0.905 0.113-8.00*** 0.00
coef_presence_of_non_worker_and_tour_frequency_is_1-0.0170 0.239-0.07 0.00
coef_presence_of_non_worker_and_tour_frequency_is_2 0.0680 0.262 0.26 0.00
coef_presence_of_non_worker_and_tour_frequency_is_3 0.258 0.330 0.78 0.00
coef_presence_of_non_worker_and_tour_frequency_is_5 3.20 0.707 4.53*** 0.00
coef_presence_of_pre_driving_school_kid_and_escorting_tour 1.42 0.127 11.20*** 0.00
coef_presence_of_pre_school_kid_and_escorting_tour 0.394 0.177 2.22* 0.00
coef_presence_of_retiree_and_eating_out_tour-0.794 0.140-5.65*** 0.00
coef_presence_of_retiree_and_tour_frequency_is_1-0.721 0.238-3.03** 0.00
coef_presence_of_retiree_and_tour_frequency_is_5-0.752 0.248-3.03** 0.00
coef_total_number_of_tours_is_1-8.70 NA NA 0.00
coef_total_number_of_tours_is_2-12.7 NA NA 0.00
coef_total_number_of_tours_is_3-14.7 NA NA 0.00
coef_total_number_of_tours_is_4-19.4 NA NA 0.00
coef_total_number_of_tours_is_5-20.0 NA NA 0.00
coef_urban_and_discretionary_tour 0.00 0.00 NA 0.00fixed value
coef_walk_access_to_retail_and_tour_frequency_is_5_plus-0.0102 0.0639-0.16 0.00
\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model PTYPE_DRIVING\n" ] }, { "data": { "text/html": [ - "

Iteration 078 [Optimization terminated successfully]

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Iteration 111 [Optimization terminated successfully]

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Best LL = -13.427352167831913

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Best LL = -1410.7703396627119

" ], "text/plain": [ "" @@ -3342,673 +8377,643 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_0_auto_household_and_escorting_tour\n", - " -289.819438\n", + " -2.355904\n", + " -2.355904\n", " -2.0000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -289.819438\n", " \n", " \n", " coef_1_escort_tour_constant\n", - " -6434.961317\n", + " -0.591707\n", + " -0.591707\n", " -0.4934\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -6434.961317\n", " \n", " \n", " coef_1_plus_eating_out_tours_constant\n", - " -3885.411913\n", + " -0.530705\n", + " -0.530705\n", " -0.0242\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -3885.411913\n", " \n", " \n", " coef_1_plus_maintenance_tours_constant\n", - " -1195.807014\n", + " -0.478676\n", + " -0.478676\n", " -0.4344\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1195.807014\n", " \n", " \n", " coef_1_plus_other_discretionary_tours_constant\n", - " -2406.806121\n", + " 0.075144\n", + " 0.075144\n", " -0.2602\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2406.806121\n", " \n", " \n", " coef_1_plus_shopping_tours_constant\n", - " -2389.305945\n", + " 0.278338\n", + " 0.278338\n", " 0.5320\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2389.305945\n", " \n", " \n", " coef_1_plus_visting_tours_constant\n", - " -2389.305996\n", + " 0.074734\n", + " 0.074734\n", " 0.2367\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2389.305996\n", " \n", " \n", " coef_2_plus_escort_tours_constant\n", - " -5667.685401\n", + " 0.538812\n", + " 0.538812\n", " 1.4155\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -5667.685401\n", " \n", " \n", " coef_auto_access_to_retail_and_tour_frequency_is_5_plus\n", - " -44.188373\n", + " 0.120695\n", + " 0.120695\n", " 0.1004\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -44.188373\n", " \n", " \n", " coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus\n", - " -17232.832071\n", + " -0.895829\n", + " -0.895829\n", " -0.6369\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -17232.832071\n", " \n", " \n", " coef_car_surplus_vs_workers_and_tour_frequency_is_1\n", - " -4035.619542\n", + " 0.384556\n", + " 0.384556\n", " 0.2902\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4035.619542\n", " \n", " \n", " coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus\n", - " 15225.992542\n", + " 1.915045\n", + " 1.915045\n", " 2.0352\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 15225.992542\n", " \n", " \n", " coef_high_income_group_and_discretionary_tour\n", - " 4481.084393\n", + " 1.973678\n", + " 1.973678\n", " 2.3270\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4481.084393\n", " \n", " \n", " coef_high_income_group_and_eating_out_tour\n", - " -3157.273834\n", + " 1.115882\n", + " 1.115882\n", " 0.4916\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -3157.273834\n", " \n", " \n", " coef_high_income_group_and_maintenance_tour\n", - " 4461.484862\n", + " 0.535657\n", + " 0.535657\n", " 0.3982\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4461.484862\n", " \n", " \n", " coef_high_income_group_and_shopping_tour\n", - " 4461.390803\n", + " 0.297949\n", + " 0.297949\n", " 0.2443\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4461.390803\n", " \n", " \n", " coef_high_income_group_and_visiting_tour\n", - " 4461.390852\n", + " 0.657170\n", + " 0.657170\n", " 0.2858\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4461.390852\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_1\n", - " 16.594329\n", + " 1.842413\n", + " 1.842413\n", " 1.3298\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 16.594329\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_2\n", - " -19742.937757\n", + " 2.746659\n", + " 2.746659\n", " 1.3759\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -19742.937757\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_5_plus\n", - " -11491.665678\n", + " 3.207837\n", + " 3.207837\n", " 3.2808\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -11491.665678\n", " \n", " \n", " coef_mediumhigh_income_group_and_discretionary_tour\n", - " 572.847509\n", + " 0.785646\n", + " 0.785646\n", " 1.4050\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 572.847509\n", " \n", " \n", " coef_mediumlow_income_group_and_discretionary_tour\n", - " -4429.942211\n", + " 0.715806\n", + " 0.715806\n", " 0.9169\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4429.942211\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_1\n", - " -4180.353968\n", + " -0.076456\n", + " -0.076456\n", " -0.2162\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4180.353968\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_2\n", - " -1606.502880\n", + " -2.349128\n", + " -2.349128\n", " -0.3587\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1606.502880\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_3\n", - " -109.819329\n", + " -4.951681\n", + " -4.951681\n", " -4.2701\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -109.819329\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_5_plus\n", " -999.000000\n", + " -999.000000\n", " -999.0000\n", - " 0.0\n", " -999.0\n", " -999.0\n", + " 0.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_1\n", - " -16877.023970\n", + " -0.717100\n", + " -0.717100\n", " -0.2340\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -16877.023970\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_2\n", - " 12620.764595\n", + " -2.894440\n", + " -2.894440\n", " -0.9231\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 12620.764595\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_3\n", - " -4861.997912\n", + " -6.487708\n", + " -6.487708\n", " -6.5835\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4861.997912\n", " \n", " \n", " coef_presence_of_driving_school_kid_and_discretionary_tour\n", - " -578.872073\n", + " -0.825813\n", + " -0.825813\n", " -0.9202\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -578.872073\n", " \n", " \n", " coef_presence_of_driving_school_kid_and_eating_out_tour\n", - " 6.381728\n", + " -0.605776\n", + " -0.605776\n", " -0.6377\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 6.381728\n", " \n", " \n", " coef_presence_of_non_worker_and_tour_frequency_is_2\n", - " 878.008827\n", + " -0.268732\n", + " -0.268732\n", " -0.6571\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 878.008827\n", " \n", " \n", " coef_presence_of_non_worker_and_tour_frequency_is_5\n", - " -1944.922644\n", + " -3.177667\n", + " -3.177667\n", " -1.4044\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1944.922644\n", " \n", " \n", " coef_presence_of_pre_driving_school_kid_and_eating_out_tour\n", - " -164.906255\n", + " -1.449331\n", + " -1.449331\n", " -1.5698\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -164.906255\n", " \n", " \n", " coef_presence_of_pre_school_kid_and_eating_out_tour\n", - " 313.476309\n", + " -1.804988\n", + " -1.804988\n", " -0.2987\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 313.476309\n", " \n", " \n", " coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1\n", - " 4033.566871\n", + " -0.395397\n", + " -0.395397\n", " -0.3219\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 4033.566871\n", " \n", " \n", " coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5\n", - " 10149.331976\n", + " -1.985303\n", + " -1.985303\n", " -1.0874\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 10149.331976\n", " \n", " \n", " coef_presence_of_university_student_and_discretionary_tour\n", - " 3906.378403\n", + " -1.663216\n", + " -1.663216\n", " -1.2834\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 3906.378403\n", " \n", " \n", " coef_total_number_of_tours_is_1\n", - " 15200.662337\n", + " -7.917385\n", + " -7.917385\n", " -7.1506\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 15200.662337\n", " \n", " \n", " coef_total_number_of_tours_is_2\n", - " -1638.556186\n", + " -11.926451\n", + " -11.926451\n", " -11.1214\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1638.556186\n", " \n", " \n", " coef_total_number_of_tours_is_3\n", - " -14010.608324\n", + " -13.210287\n", + " -13.210287\n", " -13.1750\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -14010.608324\n", " \n", " \n", " coef_urban_and_discretionary_tour\n", " 0.000000\n", + " 0.000000\n", " 0.0000\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_urban_and_maintenance_tour\n", - " -1194.333214\n", + " 1.131129\n", + " 1.131129\n", " 1.0394\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1194.333214\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_0_auto_household_and_escorting_tour -289.819438 -2.0000 \n", - "coef_1_escort_tour_constant -6434.961317 -0.4934 \n", - "coef_1_plus_eating_out_tours_constant -3885.411913 -0.0242 \n", - "coef_1_plus_maintenance_tours_constant -1195.807014 -0.4344 \n", - "coef_1_plus_other_discretionary_tours_constant -2406.806121 -0.2602 \n", - "coef_1_plus_shopping_tours_constant -2389.305945 0.5320 \n", - "coef_1_plus_visting_tours_constant -2389.305996 0.2367 \n", - "coef_2_plus_escort_tours_constant -5667.685401 1.4155 \n", - "coef_auto_access_to_retail_and_tour_frequency_i... -44.188373 0.1004 \n", - "coef_car_shortage_vs_workers_and_tour_frequency... -17232.832071 -0.6369 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... -4035.619542 0.2902 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 15225.992542 2.0352 \n", - "coef_high_income_group_and_discretionary_tour 4481.084393 2.3270 \n", - "coef_high_income_group_and_eating_out_tour -3157.273834 0.4916 \n", - "coef_high_income_group_and_maintenance_tour 4461.484862 0.3982 \n", - "coef_high_income_group_and_shopping_tour 4461.390803 0.2443 \n", - "coef_high_income_group_and_visiting_tour 4461.390852 0.2858 \n", - "coef_logged_maximum_residual_window_tour_freque... 16.594329 1.3298 \n", - "coef_logged_maximum_residual_window_tour_freque... -19742.937757 1.3759 \n", - "coef_logged_maximum_residual_window_tour_freque... -11491.665678 3.2808 \n", - "coef_mediumhigh_income_group_and_discretionary_... 572.847509 1.4050 \n", - "coef_mediumlow_income_group_and_discretionary_tour -4429.942211 0.9169 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_1 -4180.353968 -0.2162 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 -1606.502880 -0.3587 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_3 -109.819329 -4.2701 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.0000 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -16877.023970 -0.2340 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 12620.764595 -0.9231 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -4861.997912 -6.5835 \n", - "coef_presence_of_driving_school_kid_and_discret... -578.872073 -0.9202 \n", - "coef_presence_of_driving_school_kid_and_eating_... 6.381728 -0.6377 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 878.008827 -0.6571 \n", - "coef_presence_of_non_worker_and_tour_frequency_... -1944.922644 -1.4044 \n", - "coef_presence_of_pre_driving_school_kid_and_eat... -164.906255 -1.5698 \n", - "coef_presence_of_pre_school_kid_and_eating_out_... 313.476309 -0.2987 \n", - "coef_presence_of_predriving_school_kid_in_house... 4033.566871 -0.3219 \n", - "coef_presence_of_predriving_school_kid_in_house... 10149.331976 -1.0874 \n", - "coef_presence_of_university_student_and_discret... 3906.378403 -1.2834 \n", - "coef_total_number_of_tours_is_1 15200.662337 -7.1506 \n", - "coef_total_number_of_tours_is_2 -1638.556186 -11.1214 \n", - "coef_total_number_of_tours_is_3 -14010.608324 -13.1750 \n", - "coef_urban_and_discretionary_tour 0.000000 0.0000 \n", - "coef_urban_and_maintenance_tour -1194.333214 1.0394 \n", + " value best \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.355904 -2.355904 \n", + "coef_1_escort_tour_constant -0.591707 -0.591707 \n", + "coef_1_plus_eating_out_tours_constant -0.530705 -0.530705 \n", + "coef_1_plus_maintenance_tours_constant -0.478676 -0.478676 \n", + "coef_1_plus_other_discretionary_tours_constant 0.075144 0.075144 \n", + "coef_1_plus_shopping_tours_constant 0.278338 0.278338 \n", + "coef_1_plus_visting_tours_constant 0.074734 0.074734 \n", + "coef_2_plus_escort_tours_constant 0.538812 0.538812 \n", + "coef_auto_access_to_retail_and_tour_frequency_i... 0.120695 0.120695 \n", + "coef_car_shortage_vs_workers_and_tour_frequency... -0.895829 -0.895829 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 0.384556 0.384556 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 1.915045 1.915045 \n", + "coef_high_income_group_and_discretionary_tour 1.973678 1.973678 \n", + "coef_high_income_group_and_eating_out_tour 1.115882 1.115882 \n", + "coef_high_income_group_and_maintenance_tour 0.535657 0.535657 \n", + "coef_high_income_group_and_shopping_tour 0.297949 0.297949 \n", + "coef_high_income_group_and_visiting_tour 0.657170 0.657170 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.842413 1.842413 \n", + "coef_logged_maximum_residual_window_tour_freque... 2.746659 2.746659 \n", + "coef_logged_maximum_residual_window_tour_freque... 3.207837 3.207837 \n", + "coef_mediumhigh_income_group_and_discretionary_... 0.785646 0.785646 \n", + "coef_mediumlow_income_group_and_discretionary_tour 0.715806 0.715806 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_1 -0.076456 -0.076456 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 -2.349128 -2.349128 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_3 -4.951681 -4.951681 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.000000 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -0.717100 -0.717100 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -2.894440 -2.894440 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -6.487708 -6.487708 \n", + "coef_presence_of_driving_school_kid_and_discret... -0.825813 -0.825813 \n", + "coef_presence_of_driving_school_kid_and_eating_... -0.605776 -0.605776 \n", + "coef_presence_of_non_worker_and_tour_frequency_... -0.268732 -0.268732 \n", + "coef_presence_of_non_worker_and_tour_frequency_... -3.177667 -3.177667 \n", + "coef_presence_of_pre_driving_school_kid_and_eat... -1.449331 -1.449331 \n", + "coef_presence_of_pre_school_kid_and_eating_out_... -1.804988 -1.804988 \n", + "coef_presence_of_predriving_school_kid_in_house... -0.395397 -0.395397 \n", + "coef_presence_of_predriving_school_kid_in_house... -1.985303 -1.985303 \n", + "coef_presence_of_university_student_and_discret... -1.663216 -1.663216 \n", + "coef_total_number_of_tours_is_1 -7.917385 -7.917385 \n", + "coef_total_number_of_tours_is_2 -11.926451 -11.926451 \n", + "coef_total_number_of_tours_is_3 -13.210287 -13.210287 \n", + "coef_urban_and_discretionary_tour 0.000000 0.000000 \n", + "coef_urban_and_maintenance_tour 1.131129 1.131129 \n", "\n", - " nullvalue minimum \\\n", - "coef_0_auto_household_and_escorting_tour 0.0 NaN \n", - "coef_1_escort_tour_constant 0.0 NaN \n", - "coef_1_plus_eating_out_tours_constant 0.0 NaN \n", - "coef_1_plus_maintenance_tours_constant 0.0 NaN \n", - "coef_1_plus_other_discretionary_tours_constant 0.0 NaN \n", - "coef_1_plus_shopping_tours_constant 0.0 NaN \n", - "coef_1_plus_visting_tours_constant 0.0 NaN \n", - "coef_2_plus_escort_tours_constant 0.0 NaN \n", - "coef_auto_access_to_retail_and_tour_frequency_i... 0.0 NaN \n", - "coef_car_shortage_vs_workers_and_tour_frequency... 0.0 NaN \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 0.0 NaN \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 0.0 NaN \n", - "coef_high_income_group_and_discretionary_tour 0.0 NaN \n", - "coef_high_income_group_and_eating_out_tour 0.0 NaN \n", - "coef_high_income_group_and_maintenance_tour 0.0 NaN \n", - "coef_high_income_group_and_shopping_tour 0.0 NaN \n", - "coef_high_income_group_and_visiting_tour 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_mediumhigh_income_group_and_discretionary_... 0.0 NaN \n", - "coef_mediumlow_income_group_and_discretionary_tour 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_is_1 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_is_3 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_i... 0.0 -999.0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_presence_of_driving_school_kid_and_discret... 0.0 NaN \n", - "coef_presence_of_driving_school_kid_and_eating_... 0.0 NaN \n", - "coef_presence_of_non_worker_and_tour_frequency_... 0.0 NaN \n", - "coef_presence_of_non_worker_and_tour_frequency_... 0.0 NaN \n", - "coef_presence_of_pre_driving_school_kid_and_eat... 0.0 NaN \n", - "coef_presence_of_pre_school_kid_and_eating_out_... 0.0 NaN \n", - "coef_presence_of_predriving_school_kid_in_house... 0.0 NaN \n", - "coef_presence_of_predriving_school_kid_in_house... 0.0 NaN \n", - "coef_presence_of_university_student_and_discret... 0.0 NaN \n", - "coef_total_number_of_tours_is_1 0.0 NaN \n", - "coef_total_number_of_tours_is_2 0.0 NaN \n", - "coef_total_number_of_tours_is_3 0.0 NaN \n", - "coef_urban_and_discretionary_tour 0.0 0.0 \n", - "coef_urban_and_maintenance_tour 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0000 -20.0 \n", + "coef_1_escort_tour_constant -0.4934 -20.0 \n", + "coef_1_plus_eating_out_tours_constant -0.0242 -20.0 \n", + "coef_1_plus_maintenance_tours_constant -0.4344 -20.0 \n", + "coef_1_plus_other_discretionary_tours_constant -0.2602 -20.0 \n", + "coef_1_plus_shopping_tours_constant 0.5320 -20.0 \n", + "coef_1_plus_visting_tours_constant 0.2367 -20.0 \n", + "coef_2_plus_escort_tours_constant 1.4155 -20.0 \n", + "coef_auto_access_to_retail_and_tour_frequency_i... 0.1004 -20.0 \n", + "coef_car_shortage_vs_workers_and_tour_frequency... -0.6369 -20.0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 0.2902 -20.0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 2.0352 -20.0 \n", + "coef_high_income_group_and_discretionary_tour 2.3270 -20.0 \n", + "coef_high_income_group_and_eating_out_tour 0.4916 -20.0 \n", + "coef_high_income_group_and_maintenance_tour 0.3982 -20.0 \n", + "coef_high_income_group_and_shopping_tour 0.2443 -20.0 \n", + "coef_high_income_group_and_visiting_tour 0.2858 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.3298 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.3759 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 3.2808 -20.0 \n", + "coef_mediumhigh_income_group_and_discretionary_... 1.4050 -20.0 \n", + "coef_mediumlow_income_group_and_discretionary_tour 0.9169 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_1 -0.2162 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 -0.3587 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_3 -4.2701 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.0000 -999.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -0.2340 -20.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -0.9231 -20.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -6.5835 -20.0 \n", + "coef_presence_of_driving_school_kid_and_discret... -0.9202 -20.0 \n", + "coef_presence_of_driving_school_kid_and_eating_... -0.6377 -20.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... -0.6571 -20.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... -1.4044 -20.0 \n", + "coef_presence_of_pre_driving_school_kid_and_eat... -1.5698 -20.0 \n", + "coef_presence_of_pre_school_kid_and_eating_out_... -0.2987 -20.0 \n", + "coef_presence_of_predriving_school_kid_in_house... -0.3219 -20.0 \n", + "coef_presence_of_predriving_school_kid_in_house... -1.0874 -20.0 \n", + "coef_presence_of_university_student_and_discret... -1.2834 -20.0 \n", + "coef_total_number_of_tours_is_1 -7.1506 -20.0 \n", + "coef_total_number_of_tours_is_2 -11.1214 -20.0 \n", + "coef_total_number_of_tours_is_3 -13.1750 -20.0 \n", + "coef_urban_and_discretionary_tour 0.0000 0.0 \n", + "coef_urban_and_maintenance_tour 1.0394 -20.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_0_auto_household_and_escorting_tour NaN 0 \n", - "coef_1_escort_tour_constant NaN 0 \n", - "coef_1_plus_eating_out_tours_constant NaN 0 \n", - "coef_1_plus_maintenance_tours_constant NaN 0 \n", - "coef_1_plus_other_discretionary_tours_constant NaN 0 \n", - "coef_1_plus_shopping_tours_constant NaN 0 \n", - "coef_1_plus_visting_tours_constant NaN 0 \n", - "coef_2_plus_escort_tours_constant NaN 0 \n", - "coef_auto_access_to_retail_and_tour_frequency_i... NaN 0 \n", - "coef_car_shortage_vs_workers_and_tour_frequency... NaN 0 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... NaN 0 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... NaN 0 \n", - "coef_high_income_group_and_discretionary_tour NaN 0 \n", - "coef_high_income_group_and_eating_out_tour NaN 0 \n", - "coef_high_income_group_and_maintenance_tour NaN 0 \n", - "coef_high_income_group_and_shopping_tour NaN 0 \n", - "coef_high_income_group_and_visiting_tour NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_mediumhigh_income_group_and_discretionary_... NaN 0 \n", - "coef_mediumlow_income_group_and_discretionary_tour NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_1 NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_3 NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.0 1 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_presence_of_driving_school_kid_and_discret... NaN 0 \n", - "coef_presence_of_driving_school_kid_and_eating_... NaN 0 \n", - "coef_presence_of_non_worker_and_tour_frequency_... NaN 0 \n", - "coef_presence_of_non_worker_and_tour_frequency_... NaN 0 \n", - "coef_presence_of_pre_driving_school_kid_and_eat... NaN 0 \n", - "coef_presence_of_pre_school_kid_and_eating_out_... NaN 0 \n", - "coef_presence_of_predriving_school_kid_in_house... NaN 0 \n", - "coef_presence_of_predriving_school_kid_in_house... NaN 0 \n", - "coef_presence_of_university_student_and_discret... NaN 0 \n", - "coef_total_number_of_tours_is_1 NaN 0 \n", - "coef_total_number_of_tours_is_2 NaN 0 \n", - "coef_total_number_of_tours_is_3 NaN 0 \n", - "coef_urban_and_discretionary_tour 0.0 1 \n", - "coef_urban_and_maintenance_tour NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 20.0 0.0 \n", + "coef_1_escort_tour_constant 20.0 0.0 \n", + "coef_1_plus_eating_out_tours_constant 20.0 0.0 \n", + "coef_1_plus_maintenance_tours_constant 20.0 0.0 \n", + "coef_1_plus_other_discretionary_tours_constant 20.0 0.0 \n", + "coef_1_plus_shopping_tours_constant 20.0 0.0 \n", + "coef_1_plus_visting_tours_constant 20.0 0.0 \n", + "coef_2_plus_escort_tours_constant 20.0 0.0 \n", + "coef_auto_access_to_retail_and_tour_frequency_i... 20.0 0.0 \n", + "coef_car_shortage_vs_workers_and_tour_frequency... 20.0 0.0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 20.0 0.0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 20.0 0.0 \n", + "coef_high_income_group_and_discretionary_tour 20.0 0.0 \n", + "coef_high_income_group_and_eating_out_tour 20.0 0.0 \n", + "coef_high_income_group_and_maintenance_tour 20.0 0.0 \n", + "coef_high_income_group_and_shopping_tour 20.0 0.0 \n", + "coef_high_income_group_and_visiting_tour 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_mediumhigh_income_group_and_discretionary_... 20.0 0.0 \n", + "coef_mediumlow_income_group_and_discretionary_tour 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_1 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_3 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_presence_of_driving_school_kid_and_discret... 20.0 0.0 \n", + "coef_presence_of_driving_school_kid_and_eating_... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 20.0 0.0 \n", + "coef_presence_of_pre_driving_school_kid_and_eat... 20.0 0.0 \n", + "coef_presence_of_pre_school_kid_and_eating_out_... 20.0 0.0 \n", + "coef_presence_of_predriving_school_kid_in_house... 20.0 0.0 \n", + "coef_presence_of_predriving_school_kid_in_house... 20.0 0.0 \n", + "coef_presence_of_university_student_and_discret... 20.0 0.0 \n", + "coef_total_number_of_tours_is_1 20.0 0.0 \n", + "coef_total_number_of_tours_is_2 20.0 0.0 \n", + "coef_total_number_of_tours_is_3 20.0 0.0 \n", + "coef_urban_and_discretionary_tour 0.0 0.0 \n", + "coef_urban_and_maintenance_tour 20.0 0.0 \n", "\n", - " best \n", - "coef_0_auto_household_and_escorting_tour -289.819438 \n", - "coef_1_escort_tour_constant -6434.961317 \n", - "coef_1_plus_eating_out_tours_constant -3885.411913 \n", - "coef_1_plus_maintenance_tours_constant -1195.807014 \n", - "coef_1_plus_other_discretionary_tours_constant -2406.806121 \n", - "coef_1_plus_shopping_tours_constant -2389.305945 \n", - "coef_1_plus_visting_tours_constant -2389.305996 \n", - "coef_2_plus_escort_tours_constant -5667.685401 \n", - "coef_auto_access_to_retail_and_tour_frequency_i... -44.188373 \n", - "coef_car_shortage_vs_workers_and_tour_frequency... -17232.832071 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... -4035.619542 \n", - "coef_car_surplus_vs_workers_and_tour_frequency_... 15225.992542 \n", - "coef_high_income_group_and_discretionary_tour 4481.084393 \n", - "coef_high_income_group_and_eating_out_tour -3157.273834 \n", - "coef_high_income_group_and_maintenance_tour 4461.484862 \n", - "coef_high_income_group_and_shopping_tour 4461.390803 \n", - "coef_high_income_group_and_visiting_tour 4461.390852 \n", - "coef_logged_maximum_residual_window_tour_freque... 16.594329 \n", - "coef_logged_maximum_residual_window_tour_freque... -19742.937757 \n", - "coef_logged_maximum_residual_window_tour_freque... -11491.665678 \n", - "coef_mediumhigh_income_group_and_discretionary_... 572.847509 \n", - "coef_mediumlow_income_group_and_discretionary_tour -4429.942211 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_1 -4180.353968 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 -1606.502880 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_3 -109.819329 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -16877.023970 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 12620.764595 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -4861.997912 \n", - "coef_presence_of_driving_school_kid_and_discret... -578.872073 \n", - "coef_presence_of_driving_school_kid_and_eating_... 6.381728 \n", - "coef_presence_of_non_worker_and_tour_frequency_... 878.008827 \n", - "coef_presence_of_non_worker_and_tour_frequency_... -1944.922644 \n", - "coef_presence_of_pre_driving_school_kid_and_eat... -164.906255 \n", - "coef_presence_of_pre_school_kid_and_eating_out_... 313.476309 \n", - "coef_presence_of_predriving_school_kid_in_house... 4033.566871 \n", - "coef_presence_of_predriving_school_kid_in_house... 10149.331976 \n", - "coef_presence_of_university_student_and_discret... 3906.378403 \n", - "coef_total_number_of_tours_is_1 15200.662337 \n", - "coef_total_number_of_tours_is_2 -1638.556186 \n", - "coef_total_number_of_tours_is_3 -14010.608324 \n", - "coef_urban_and_discretionary_tour 0.000000 \n", - "coef_urban_and_maintenance_tour -1194.333214 " + " holdfast \n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 0 \n", + "coef_1_escort_tour_constant 0 \n", + "coef_1_plus_eating_out_tours_constant 0 \n", + "coef_1_plus_maintenance_tours_constant 0 \n", + "coef_1_plus_other_discretionary_tours_constant 0 \n", + "coef_1_plus_shopping_tours_constant 0 \n", + "coef_1_plus_visting_tours_constant 0 \n", + "coef_2_plus_escort_tours_constant 0 \n", + "coef_auto_access_to_retail_and_tour_frequency_i... 0 \n", + "coef_car_shortage_vs_workers_and_tour_frequency... 0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 0 \n", + "coef_car_surplus_vs_workers_and_tour_frequency_... 0 \n", + "coef_high_income_group_and_discretionary_tour 0 \n", + "coef_high_income_group_and_eating_out_tour 0 \n", + "coef_high_income_group_and_maintenance_tour 0 \n", + "coef_high_income_group_and_shopping_tour 0 \n", + "coef_high_income_group_and_visiting_tour 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_mediumhigh_income_group_and_discretionary_... 0 \n", + "coef_mediumlow_income_group_and_discretionary_tour 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_1 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_3 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... 1 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_presence_of_driving_school_kid_and_discret... 0 \n", + "coef_presence_of_driving_school_kid_and_eating_... 0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0 \n", + "coef_presence_of_pre_driving_school_kid_and_eat... 0 \n", + "coef_presence_of_pre_school_kid_and_eating_out_... 0 \n", + "coef_presence_of_predriving_school_kid_in_house... 0 \n", + "coef_presence_of_predriving_school_kid_in_house... 0 \n", + "coef_presence_of_university_student_and_discret... 0 \n", + "coef_total_number_of_tours_is_1 0 \n", + "coef_total_number_of_tours_is_2 0 \n", + "coef_total_number_of_tours_is_3 0 \n", + "coef_urban_and_discretionary_tour 1 \n", + "coef_urban_and_maintenance_tour 0 " ] }, "metadata": {}, @@ -4018,26 +9023,456 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " m.estimate(method='SLSQP')\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/linalg/__init__.py:18: UserWarning: minimum eig 0.0 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model seems to have 14 parameter estimators with negative variance\n", - "- coef_1_plus_maintenance_tours_constant\n", - "- coef_1_plus_other_discretionary_tours_constant\n", - "- coef_1_plus_shopping_tours_constant\n", - "- coef_1_plus_visting_tours_constant\n", - "- and 10 more\n", - " m.estimate(method='SLSQP')\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: RuntimeWarning: invalid value encountered in sqrt\n", - 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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_0_auto_household_and_escorting_tour-2.36 3.76-0.63 0.00
coef_1_escort_tour_constant-0.592 NA NA 0.00
coef_1_plus_eating_out_tours_constant-0.531 NA NA 0.00
coef_1_plus_maintenance_tours_constant-0.479 NA NA 0.00
coef_1_plus_other_discretionary_tours_constant 0.0751 NA NA 0.00
coef_1_plus_shopping_tours_constant 0.278 NA NA 0.00
coef_1_plus_visting_tours_constant 0.0747 NA NA 0.00
coef_2_plus_escort_tours_constant 0.539 NA NA 0.00
coef_auto_access_to_retail_and_tour_frequency_is_5_plus 0.121 0.110 1.10 0.00
coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus-0.896 0.225-3.98*** 0.00
coef_car_surplus_vs_workers_and_tour_frequency_is_1 0.385 0.160 2.40* 0.00
coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus 1.92 0.421 4.55*** 0.00
coef_high_income_group_and_discretionary_tour 1.97 0.433 4.56*** 0.00
coef_high_income_group_and_eating_out_tour 1.12 0.412 2.71** 0.00
coef_high_income_group_and_maintenance_tour 0.536 0.283 1.89 0.00
coef_high_income_group_and_shopping_tour 0.298 0.256 1.17 0.00
coef_high_income_group_and_visiting_tour 0.657 0.266 2.47* 0.00
coef_logged_maximum_residual_window_tour_frequency_is_1 1.84 0.280 6.58*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_2 2.75 0.544 5.05*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_5_plus 3.21 3.57 0.90 0.00
coef_mediumhigh_income_group_and_discretionary_tour 0.786 0.459 1.71 0.00
coef_mediumlow_income_group_and_discretionary_tour 0.716 0.472 1.52 0.00
coef_number_of_joint_tours_and_tour_frequency_is_1-0.0765 0.227-0.34 0.00
coef_number_of_joint_tours_and_tour_frequency_is_2-2.35 1.41-1.66 0.00
coef_number_of_joint_tours_and_tour_frequency_is_3-4.95 10.5-0.47 0.00
coef_number_of_joint_tours_and_tour_frequency_is_5_plus-999. 0.00 NA 0.00fixed value
coef_number_of_mandatory_tours_and_tour_frequency_is_1-0.717 0.256-2.80** 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_2-2.89 1.19-2.44* 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_3-6.49 8.76-0.74 0.00
coef_presence_of_driving_school_kid_and_discretionary_tour-0.826 0.330-2.50* 0.00
coef_presence_of_driving_school_kid_and_eating_out_tour-0.606 0.545-1.11 0.00
coef_presence_of_non_worker_and_tour_frequency_is_2-0.269 0.382-0.70 0.00
coef_presence_of_non_worker_and_tour_frequency_is_5-3.18 2.64-1.21 0.00
coef_presence_of_pre_driving_school_kid_and_eating_out_tour-1.45 0.500-2.90** 0.00
coef_presence_of_pre_school_kid_and_eating_out_tour-1.80 1.09-1.65 0.00
coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1-0.395 0.149-2.65** 0.00
coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5-1.99 0.501-3.96*** 0.00
coef_presence_of_university_student_and_discretionary_tour-1.66 0.377-4.42*** 0.00
coef_total_number_of_tours_is_1-7.92 NA NA 0.00
coef_total_number_of_tours_is_2-11.9 NA NA 0.00
coef_total_number_of_tours_is_3-13.2 NA NA 0.00
coef_urban_and_discretionary_tour 0.00 0.00 NA 0.00fixed value
coef_urban_and_maintenance_tour 1.13 0.259 4.36*** 0.00
\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model PTYPE_SCHOOL\n" ] }, { "data": { "text/html": [ - "

Iteration 037 [Optimization terminated successfully]

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Iteration 055 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -4049,7 +9484,7 @@ { "data": { "text/html": [ - "

Best LL = -256.78783276592117

" + "

Best LL = -5118.870584262372

" ], "text/plain": [ "" @@ -4080,538 +9515,517 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_0_auto_household_and_escorting_tour\n", " -2.000000\n", + " -2.000000\n", " -2.0000\n", - " 0.0\n", " -2.0\n", " -2.0\n", + " 0.0\n", " 1\n", - " \n", - " -2.000000\n", " \n", " \n", " coef_1_escort_tour_constant\n", - " -1.572081\n", + " -0.710427\n", + " -0.710427\n", " -0.7551\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.572081\n", " \n", " \n", " coef_1_plus_eating_out_tours_constant\n", - " -2.222210\n", + " 1.267594\n", + " 1.267594\n", " 1.1145\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.222210\n", " \n", " \n", " coef_1_plus_maintenance_tours_constant\n", - " -1.497135\n", + " -0.580534\n", + " -0.580534\n", " -0.5060\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.497135\n", " \n", " \n", " coef_1_plus_other_discretionary_tours_constant\n", - " 0.090818\n", + " 0.614538\n", + " 0.614538\n", " 0.4634\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.090818\n", " \n", " \n", " coef_1_plus_shopping_tours_constant\n", - " 1.474688\n", + " 1.037830\n", + " 1.037830\n", " 0.4783\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.474688\n", " \n", " \n", " coef_1_plus_visting_tours_constant\n", - " -1.792608\n", + " -0.445905\n", + " -0.445905\n", " -0.4006\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.792608\n", " \n", " \n", " coef_2_plus_escort_tours_constant\n", - " -2.059623\n", + " -0.076053\n", + " -0.076053\n", " -0.0086\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -2.059623\n", " \n", " \n", " coef_auto_access_to_retail_and_escorting\n", - " 0.555108\n", + " 0.063236\n", + " 0.063236\n", " 0.0629\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.555108\n", " \n", " \n", " coef_high_income_group_and_eating_out_tour\n", - " -1.361980\n", + " -0.810212\n", + " -0.810212\n", " -0.7010\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.361980\n", " \n", " \n", " coef_high_income_group_and_shopping_tour\n", - " -3.736670\n", + " -0.945693\n", + " -0.945693\n", " -0.6506\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -3.736670\n", " \n", " \n", " coef_high_income_group_and_tour_frequency_is_5_plus\n", - " 16.017262\n", + " 2.304674\n", + " 2.304674\n", " 2.0175\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 16.017262\n", " \n", " \n", " coef_logged_maximum_residual_window_tour_frequency_is_5_plus\n", - " 1.526025\n", + " 1.353636\n", + " 1.353636\n", " 1.5603\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.526025\n", " \n", " \n", " coef_mediumhigh_income_group_and_tour_frequency_is_5_plus\n", - " 15.096814\n", + " 1.811428\n", + " 1.811428\n", " 1.5197\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 15.096814\n", " \n", " \n", " coef_mediumlow_income_group_and_tour_frequency_is_5_plus\n", - " 14.227759\n", + " 1.143302\n", + " 1.143302\n", " 1.0873\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 14.227759\n", " \n", " \n", " coef_number_of_joint_maintenance_tours\n", " -1.347600\n", + " -1.347600\n", " -1.3476\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.347600\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_2\n", - " -1.197115\n", + " -0.540183\n", + " -0.540183\n", " -0.6149\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.197115\n", " \n", " \n", " coef_number_of_joint_tours_and_tour_frequency_is_5_plus\n", " -999.000000\n", + " -999.000000\n", " -999.0000\n", - " 0.0\n", " -999.0\n", " -999.0\n", + " 0.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_1\n", - " -9.889679\n", + " -1.256737\n", + " -1.256737\n", " -1.0331\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -9.889679\n", " \n", " \n", " coef_number_of_mandatory_tours_and_tour_frequency_is_3\n", - " -10.675107\n", + " -3.162364\n", + " -3.162364\n", " -2.7445\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -10.675107\n", " \n", " \n", " coef_presence_of_full_time_worker_and_discretionary_tour\n", - " 0.167217\n", + " 0.646457\n", + " 0.646457\n", " 0.7526\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.167217\n", " \n", " \n", " coef_presence_of_non_worker_and_eating_out_tour\n", - " -1.295662\n", + " -1.533575\n", + " -1.533575\n", " -1.3074\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.295662\n", " \n", " \n", " coef_presence_of_non_worker_and_shopping_tour\n", - " -1.353670\n", + " -0.760303\n", + " -0.760303\n", " -0.6450\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.353670\n", " \n", " \n", " coef_presence_of_non_worker_and_tour_frequency_is_5\n", - " -0.434686\n", + " 0.353557\n", + " 0.353557\n", " 0.2177\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.434686\n", " \n", " \n", " coef_presence_of_part_time_worker_and_discretionary_tour\n", - " -0.342155\n", + " 0.436183\n", + " 0.436183\n", " 0.3721\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.342155\n", " \n", " \n", " coef_presence_of_pre_driving_school_kid_and_shopping_tour\n", - " 1.415379\n", + " 0.745895\n", + " 0.745895\n", " 0.9365\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.415379\n", " \n", " \n", " coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5\n", - " 0.290181\n", + " -0.086497\n", + " -0.086497\n", " -0.2264\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.290181\n", " \n", " \n", " coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5\n", - " 0.328944\n", + " -0.357691\n", + " -0.357691\n", " -0.4439\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.328944\n", " \n", " \n", " coef_total_number_of_tours_is_1\n", - " -11.291182\n", + " -7.203758\n", + " -7.203758\n", " -7.4863\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -11.291182\n", " \n", " \n", " coef_total_number_of_tours_is_2\n", - " -13.228339\n", + " -10.489540\n", + " -10.489540\n", " -10.7180\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -13.228339\n", " \n", " \n", " coef_total_number_of_tours_is_3\n", - " -14.184905\n", + " -13.816990\n", + " -13.816990\n", " -13.7884\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -14.184905\n", " \n", " \n", " coef_urban_and_discretionary_tour\n", " 0.000000\n", + " 0.000000\n", " 0.0000\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_urban_and_escorting_tour\n", - " -4.483827\n", + " 0.728596\n", + " 0.728596\n", " 0.4352\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.483827\n", " \n", " \n", " coef_walk_access_to_retail_and_eating_out\n", - " 0.400103\n", + " 0.099568\n", + " 0.099568\n", " 0.0738\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.400103\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_0_auto_household_and_escorting_tour -2.000000 -2.0000 \n", - "coef_1_escort_tour_constant -1.572081 -0.7551 \n", - "coef_1_plus_eating_out_tours_constant -2.222210 1.1145 \n", - "coef_1_plus_maintenance_tours_constant -1.497135 -0.5060 \n", - "coef_1_plus_other_discretionary_tours_constant 0.090818 0.4634 \n", - "coef_1_plus_shopping_tours_constant 1.474688 0.4783 \n", - "coef_1_plus_visting_tours_constant -1.792608 -0.4006 \n", - "coef_2_plus_escort_tours_constant -2.059623 -0.0086 \n", - "coef_auto_access_to_retail_and_escorting 0.555108 0.0629 \n", - "coef_high_income_group_and_eating_out_tour -1.361980 -0.7010 \n", - "coef_high_income_group_and_shopping_tour -3.736670 -0.6506 \n", - "coef_high_income_group_and_tour_frequency_is_5_... 16.017262 2.0175 \n", - "coef_logged_maximum_residual_window_tour_freque... 1.526025 1.5603 \n", - "coef_mediumhigh_income_group_and_tour_frequency... 15.096814 1.5197 \n", - "coef_mediumlow_income_group_and_tour_frequency_... 14.227759 1.0873 \n", - "coef_number_of_joint_maintenance_tours -1.347600 -1.3476 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 -1.197115 -0.6149 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.0000 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -9.889679 -1.0331 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -10.675107 -2.7445 \n", - "coef_presence_of_full_time_worker_and_discretio... 0.167217 0.7526 \n", - "coef_presence_of_non_worker_and_eating_out_tour -1.295662 -1.3074 \n", - "coef_presence_of_non_worker_and_shopping_tour -1.353670 -0.6450 \n", - "coef_presence_of_non_worker_and_tour_frequency_... -0.434686 0.2177 \n", - "coef_presence_of_part_time_worker_and_discretio... -0.342155 0.3721 \n", - "coef_presence_of_pre_driving_school_kid_and_sho... 1.415379 0.9365 \n", - "coef_presence_of_predriving_school_kid_in_house... 0.290181 -0.2264 \n", - "coef_presence_of_preschool_kid_in_household_and... 0.328944 -0.4439 \n", - "coef_total_number_of_tours_is_1 -11.291182 -7.4863 \n", - "coef_total_number_of_tours_is_2 -13.228339 -10.7180 \n", - "coef_total_number_of_tours_is_3 -14.184905 -13.7884 \n", - "coef_urban_and_discretionary_tour 0.000000 0.0000 \n", - "coef_urban_and_escorting_tour -4.483827 0.4352 \n", - "coef_walk_access_to_retail_and_eating_out 0.400103 0.0738 \n", + " value best \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.000000 \n", + "coef_1_escort_tour_constant -0.710427 -0.710427 \n", + "coef_1_plus_eating_out_tours_constant 1.267594 1.267594 \n", + "coef_1_plus_maintenance_tours_constant -0.580534 -0.580534 \n", + "coef_1_plus_other_discretionary_tours_constant 0.614538 0.614538 \n", + "coef_1_plus_shopping_tours_constant 1.037830 1.037830 \n", + "coef_1_plus_visting_tours_constant -0.445905 -0.445905 \n", + "coef_2_plus_escort_tours_constant -0.076053 -0.076053 \n", + "coef_auto_access_to_retail_and_escorting 0.063236 0.063236 \n", + "coef_high_income_group_and_eating_out_tour -0.810212 -0.810212 \n", + "coef_high_income_group_and_shopping_tour -0.945693 -0.945693 \n", + "coef_high_income_group_and_tour_frequency_is_5_... 2.304674 2.304674 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.353636 1.353636 \n", + "coef_mediumhigh_income_group_and_tour_frequency... 1.811428 1.811428 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 1.143302 1.143302 \n", + "coef_number_of_joint_maintenance_tours -1.347600 -1.347600 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 -0.540183 -0.540183 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 -999.000000 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -1.256737 -1.256737 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -3.162364 -3.162364 \n", + "coef_presence_of_full_time_worker_and_discretio... 0.646457 0.646457 \n", + "coef_presence_of_non_worker_and_eating_out_tour -1.533575 -1.533575 \n", + "coef_presence_of_non_worker_and_shopping_tour -0.760303 -0.760303 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0.353557 0.353557 \n", + "coef_presence_of_part_time_worker_and_discretio... 0.436183 0.436183 \n", + "coef_presence_of_pre_driving_school_kid_and_sho... 0.745895 0.745895 \n", + "coef_presence_of_predriving_school_kid_in_house... -0.086497 -0.086497 \n", + "coef_presence_of_preschool_kid_in_household_and... -0.357691 -0.357691 \n", + "coef_total_number_of_tours_is_1 -7.203758 -7.203758 \n", + "coef_total_number_of_tours_is_2 -10.489540 -10.489540 \n", + "coef_total_number_of_tours_is_3 -13.816990 -13.816990 \n", + "coef_urban_and_discretionary_tour 0.000000 0.000000 \n", + "coef_urban_and_escorting_tour 0.728596 0.728596 \n", + "coef_walk_access_to_retail_and_eating_out 0.099568 0.099568 \n", "\n", - " nullvalue minimum \\\n", - "coef_0_auto_household_and_escorting_tour 0.0 -2.0 \n", - "coef_1_escort_tour_constant 0.0 NaN \n", - "coef_1_plus_eating_out_tours_constant 0.0 NaN \n", - "coef_1_plus_maintenance_tours_constant 0.0 NaN \n", - "coef_1_plus_other_discretionary_tours_constant 0.0 NaN \n", - "coef_1_plus_shopping_tours_constant 0.0 NaN \n", - "coef_1_plus_visting_tours_constant 0.0 NaN \n", - "coef_2_plus_escort_tours_constant 0.0 NaN \n", - "coef_auto_access_to_retail_and_escorting 0.0 NaN \n", - "coef_high_income_group_and_eating_out_tour 0.0 NaN \n", - "coef_high_income_group_and_shopping_tour 0.0 NaN \n", - "coef_high_income_group_and_tour_frequency_is_5_... 0.0 NaN \n", - "coef_logged_maximum_residual_window_tour_freque... 0.0 NaN \n", - "coef_mediumhigh_income_group_and_tour_frequency... 0.0 NaN \n", - "coef_mediumlow_income_group_and_tour_frequency_... 0.0 NaN \n", - "coef_number_of_joint_maintenance_tours 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 0.0 NaN \n", - "coef_number_of_joint_tours_and_tour_frequency_i... 0.0 -999.0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_number_of_mandatory_tours_and_tour_frequen... 0.0 NaN \n", - "coef_presence_of_full_time_worker_and_discretio... 0.0 NaN \n", - "coef_presence_of_non_worker_and_eating_out_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_shopping_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_tour_frequency_... 0.0 NaN \n", - "coef_presence_of_part_time_worker_and_discretio... 0.0 NaN \n", - "coef_presence_of_pre_driving_school_kid_and_sho... 0.0 NaN \n", - "coef_presence_of_predriving_school_kid_in_house... 0.0 NaN \n", - "coef_presence_of_preschool_kid_in_household_and... 0.0 NaN \n", - "coef_total_number_of_tours_is_1 0.0 NaN \n", - "coef_total_number_of_tours_is_2 0.0 NaN \n", - "coef_total_number_of_tours_is_3 0.0 NaN \n", - "coef_urban_and_discretionary_tour 0.0 0.0 \n", - "coef_urban_and_escorting_tour 0.0 NaN \n", - "coef_walk_access_to_retail_and_eating_out 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0000 -2.0 \n", + "coef_1_escort_tour_constant -0.7551 -20.0 \n", + "coef_1_plus_eating_out_tours_constant 1.1145 -20.0 \n", + "coef_1_plus_maintenance_tours_constant -0.5060 -20.0 \n", + "coef_1_plus_other_discretionary_tours_constant 0.4634 -20.0 \n", + "coef_1_plus_shopping_tours_constant 0.4783 -20.0 \n", + "coef_1_plus_visting_tours_constant -0.4006 -20.0 \n", + "coef_2_plus_escort_tours_constant -0.0086 -20.0 \n", + "coef_auto_access_to_retail_and_escorting 0.0629 -20.0 \n", + "coef_high_income_group_and_eating_out_tour -0.7010 -20.0 \n", + "coef_high_income_group_and_shopping_tour -0.6506 -20.0 \n", + "coef_high_income_group_and_tour_frequency_is_5_... 2.0175 -20.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 1.5603 -20.0 \n", + "coef_mediumhigh_income_group_and_tour_frequency... 1.5197 -20.0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 1.0873 -20.0 \n", + "coef_number_of_joint_maintenance_tours -1.3476 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 -0.6149 -20.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.0000 -999.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -1.0331 -20.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... -2.7445 -20.0 \n", + "coef_presence_of_full_time_worker_and_discretio... 0.7526 -20.0 \n", + "coef_presence_of_non_worker_and_eating_out_tour -1.3074 -20.0 \n", + "coef_presence_of_non_worker_and_shopping_tour -0.6450 -20.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0.2177 -20.0 \n", + "coef_presence_of_part_time_worker_and_discretio... 0.3721 -20.0 \n", + "coef_presence_of_pre_driving_school_kid_and_sho... 0.9365 -20.0 \n", + "coef_presence_of_predriving_school_kid_in_house... -0.2264 -20.0 \n", + "coef_presence_of_preschool_kid_in_household_and... -0.4439 -20.0 \n", + "coef_total_number_of_tours_is_1 -7.4863 -20.0 \n", + "coef_total_number_of_tours_is_2 -10.7180 -20.0 \n", + "coef_total_number_of_tours_is_3 -13.7884 -20.0 \n", + "coef_urban_and_discretionary_tour 0.0000 0.0 \n", + "coef_urban_and_escorting_tour 0.4352 -20.0 \n", + "coef_walk_access_to_retail_and_eating_out 0.0738 -20.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_0_auto_household_and_escorting_tour -2.0 1 \n", - "coef_1_escort_tour_constant NaN 0 \n", - "coef_1_plus_eating_out_tours_constant NaN 0 \n", - "coef_1_plus_maintenance_tours_constant NaN 0 \n", - "coef_1_plus_other_discretionary_tours_constant NaN 0 \n", - "coef_1_plus_shopping_tours_constant NaN 0 \n", - "coef_1_plus_visting_tours_constant NaN 0 \n", - "coef_2_plus_escort_tours_constant NaN 0 \n", - "coef_auto_access_to_retail_and_escorting NaN 0 \n", - "coef_high_income_group_and_eating_out_tour NaN 0 \n", - "coef_high_income_group_and_shopping_tour NaN 0 \n", - "coef_high_income_group_and_tour_frequency_is_5_... NaN 0 \n", - "coef_logged_maximum_residual_window_tour_freque... NaN 0 \n", - "coef_mediumhigh_income_group_and_tour_frequency... NaN 0 \n", - "coef_mediumlow_income_group_and_tour_frequency_... NaN 0 \n", - "coef_number_of_joint_maintenance_tours NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 NaN 0 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.0 1 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... NaN 0 \n", - "coef_presence_of_full_time_worker_and_discretio... NaN 0 \n", - "coef_presence_of_non_worker_and_eating_out_tour NaN 0 \n", - "coef_presence_of_non_worker_and_shopping_tour NaN 0 \n", - "coef_presence_of_non_worker_and_tour_frequency_... NaN 0 \n", - "coef_presence_of_part_time_worker_and_discretio... NaN 0 \n", - "coef_presence_of_pre_driving_school_kid_and_sho... NaN 0 \n", - "coef_presence_of_predriving_school_kid_in_house... NaN 0 \n", - "coef_presence_of_preschool_kid_in_household_and... NaN 0 \n", - "coef_total_number_of_tours_is_1 NaN 0 \n", - "coef_total_number_of_tours_is_2 NaN 0 \n", - "coef_total_number_of_tours_is_3 NaN 0 \n", - "coef_urban_and_discretionary_tour 0.0 1 \n", - "coef_urban_and_escorting_tour NaN 0 \n", - "coef_walk_access_to_retail_and_eating_out NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0 0.0 \n", + "coef_1_escort_tour_constant 20.0 0.0 \n", + "coef_1_plus_eating_out_tours_constant 20.0 0.0 \n", + "coef_1_plus_maintenance_tours_constant 20.0 0.0 \n", + "coef_1_plus_other_discretionary_tours_constant 20.0 0.0 \n", + "coef_1_plus_shopping_tours_constant 20.0 0.0 \n", + "coef_1_plus_visting_tours_constant 20.0 0.0 \n", + "coef_2_plus_escort_tours_constant 20.0 0.0 \n", + "coef_auto_access_to_retail_and_escorting 20.0 0.0 \n", + "coef_high_income_group_and_eating_out_tour 20.0 0.0 \n", + "coef_high_income_group_and_shopping_tour 20.0 0.0 \n", + "coef_high_income_group_and_tour_frequency_is_5_... 20.0 0.0 \n", + "coef_logged_maximum_residual_window_tour_freque... 20.0 0.0 \n", + "coef_mediumhigh_income_group_and_tour_frequency... 20.0 0.0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 20.0 0.0 \n", + "coef_number_of_joint_maintenance_tours 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 20.0 0.0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... -999.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 20.0 0.0 \n", + "coef_presence_of_full_time_worker_and_discretio... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_shopping_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 20.0 0.0 \n", + "coef_presence_of_part_time_worker_and_discretio... 20.0 0.0 \n", + "coef_presence_of_pre_driving_school_kid_and_sho... 20.0 0.0 \n", + "coef_presence_of_predriving_school_kid_in_house... 20.0 0.0 \n", + "coef_presence_of_preschool_kid_in_household_and... 20.0 0.0 \n", + "coef_total_number_of_tours_is_1 20.0 0.0 \n", + "coef_total_number_of_tours_is_2 20.0 0.0 \n", + "coef_total_number_of_tours_is_3 20.0 0.0 \n", + "coef_urban_and_discretionary_tour 0.0 0.0 \n", + "coef_urban_and_escorting_tour 20.0 0.0 \n", + "coef_walk_access_to_retail_and_eating_out 20.0 0.0 \n", "\n", - " best \n", - "coef_0_auto_household_and_escorting_tour -2.000000 \n", - "coef_1_escort_tour_constant -1.572081 \n", - "coef_1_plus_eating_out_tours_constant -2.222210 \n", - "coef_1_plus_maintenance_tours_constant -1.497135 \n", - "coef_1_plus_other_discretionary_tours_constant 0.090818 \n", - "coef_1_plus_shopping_tours_constant 1.474688 \n", - "coef_1_plus_visting_tours_constant -1.792608 \n", - "coef_2_plus_escort_tours_constant -2.059623 \n", - "coef_auto_access_to_retail_and_escorting 0.555108 \n", - "coef_high_income_group_and_eating_out_tour -1.361980 \n", - "coef_high_income_group_and_shopping_tour -3.736670 \n", - "coef_high_income_group_and_tour_frequency_is_5_... 16.017262 \n", - "coef_logged_maximum_residual_window_tour_freque... 1.526025 \n", - "coef_mediumhigh_income_group_and_tour_frequency... 15.096814 \n", - "coef_mediumlow_income_group_and_tour_frequency_... 14.227759 \n", - "coef_number_of_joint_maintenance_tours -1.347600 \n", - "coef_number_of_joint_tours_and_tour_frequency_is_2 -1.197115 \n", - "coef_number_of_joint_tours_and_tour_frequency_i... -999.000000 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -9.889679 \n", - "coef_number_of_mandatory_tours_and_tour_frequen... -10.675107 \n", - "coef_presence_of_full_time_worker_and_discretio... 0.167217 \n", - "coef_presence_of_non_worker_and_eating_out_tour -1.295662 \n", - "coef_presence_of_non_worker_and_shopping_tour -1.353670 \n", - "coef_presence_of_non_worker_and_tour_frequency_... -0.434686 \n", - "coef_presence_of_part_time_worker_and_discretio... -0.342155 \n", - "coef_presence_of_pre_driving_school_kid_and_sho... 1.415379 \n", - "coef_presence_of_predriving_school_kid_in_house... 0.290181 \n", - "coef_presence_of_preschool_kid_in_household_and... 0.328944 \n", - "coef_total_number_of_tours_is_1 -11.291182 \n", - "coef_total_number_of_tours_is_2 -13.228339 \n", - "coef_total_number_of_tours_is_3 -14.184905 \n", - "coef_urban_and_discretionary_tour 0.000000 \n", - "coef_urban_and_escorting_tour -4.483827 \n", - "coef_walk_access_to_retail_and_eating_out 0.400103 " + " holdfast \n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 1 \n", + "coef_1_escort_tour_constant 0 \n", + "coef_1_plus_eating_out_tours_constant 0 \n", + "coef_1_plus_maintenance_tours_constant 0 \n", + "coef_1_plus_other_discretionary_tours_constant 0 \n", + "coef_1_plus_shopping_tours_constant 0 \n", + "coef_1_plus_visting_tours_constant 0 \n", + "coef_2_plus_escort_tours_constant 0 \n", + "coef_auto_access_to_retail_and_escorting 0 \n", + "coef_high_income_group_and_eating_out_tour 0 \n", + "coef_high_income_group_and_shopping_tour 0 \n", + "coef_high_income_group_and_tour_frequency_is_5_... 0 \n", + "coef_logged_maximum_residual_window_tour_freque... 0 \n", + "coef_mediumhigh_income_group_and_tour_frequency... 0 \n", + "coef_mediumlow_income_group_and_tour_frequency_... 0 \n", + "coef_number_of_joint_maintenance_tours 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_is_2 0 \n", + "coef_number_of_joint_tours_and_tour_frequency_i... 1 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_number_of_mandatory_tours_and_tour_frequen... 0 \n", + "coef_presence_of_full_time_worker_and_discretio... 0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 0 \n", + "coef_presence_of_non_worker_and_shopping_tour 0 \n", + "coef_presence_of_non_worker_and_tour_frequency_... 0 \n", + "coef_presence_of_part_time_worker_and_discretio... 0 \n", + "coef_presence_of_pre_driving_school_kid_and_sho... 0 \n", + "coef_presence_of_predriving_school_kid_in_house... 0 \n", + "coef_presence_of_preschool_kid_in_household_and... 0 \n", + "coef_total_number_of_tours_is_1 0 \n", + "coef_total_number_of_tours_is_2 0 \n", + "coef_total_number_of_tours_is_3 0 \n", + "coef_urban_and_discretionary_tour 1 \n", + "coef_urban_and_escorting_tour 0 \n", + "coef_walk_access_to_retail_and_eating_out 0 " ] }, "metadata": {}, @@ -4621,24 +10035,375 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " m.estimate(method='SLSQP')\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.064162929131762e-17 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model seems to have 3 parameter estimators with negative variance\n", - "- coef_1_escort_tour_constant\n", - "- coef_2_plus_escort_tours_constant\n", - "- coef_urban_and_escorting_tour\n", - " m.estimate(method='SLSQP')\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: RuntimeWarning: invalid value encountered in sqrt\n", - " m.estimate(method='SLSQP')\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_0_auto_household_and_escorting_tour-2.00 0.00 NA 0.00fixed value
coef_1_escort_tour_constant-0.710 191.-0.00 0.00
coef_1_plus_eating_out_tours_constant 1.27 191. 0.01 0.00
coef_1_plus_maintenance_tours_constant-0.581 191.-0.00 0.00
coef_1_plus_other_discretionary_tours_constant 0.615 191. 0.00 0.00
coef_1_plus_shopping_tours_constant 1.04 191. 0.01 0.00
coef_1_plus_visting_tours_constant-0.446 191.-0.00 0.00
coef_2_plus_escort_tours_constant-0.0761 382.-0.00 0.00
coef_auto_access_to_retail_and_escorting 0.0632 0.112 0.56 0.00
coef_high_income_group_and_eating_out_tour-0.810 0.242-3.35*** 0.00
coef_high_income_group_and_shopping_tour-0.946 0.239-3.95*** 0.00
coef_high_income_group_and_tour_frequency_is_5_plus 2.30 0.217 10.62*** 0.00
coef_logged_maximum_residual_window_tour_frequency_is_5_plus 1.35 0.147 9.23*** 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_5_plus 1.81 0.217 8.33*** 0.00
coef_mediumlow_income_group_and_tour_frequency_is_5_plus 1.14 0.225 5.08*** 0.00
coef_number_of_joint_maintenance_tours-1.35 NA NA 0.00
coef_number_of_joint_tours_and_tour_frequency_is_2-0.540 0.138-3.92*** 0.00
coef_number_of_joint_tours_and_tour_frequency_is_5_plus-999. 0.00 NA 0.00fixed value
coef_number_of_mandatory_tours_and_tour_frequency_is_1-1.26 0.206-6.10*** 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_3-3.16 0.312-10.14*** 0.00
coef_presence_of_full_time_worker_and_discretionary_tour 0.646 0.148 4.36*** 0.00
coef_presence_of_non_worker_and_eating_out_tour-1.53 0.168-9.11*** 0.00
coef_presence_of_non_worker_and_shopping_tour-0.760 0.151-5.05*** 0.00
coef_presence_of_non_worker_and_tour_frequency_is_5 0.354 0.0883 4.01*** 0.00
coef_presence_of_part_time_worker_and_discretionary_tour 0.436 0.0926 4.71*** 0.00
coef_presence_of_pre_driving_school_kid_and_shopping_tour 0.746 0.150 4.98*** 0.00
coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5-0.0865 0.0791-1.09 0.00
coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5-0.358 0.0910-3.93*** 0.00
coef_total_number_of_tours_is_1-7.20 191.-0.04 0.00
coef_total_number_of_tours_is_2-10.5 382.-0.03 0.00
coef_total_number_of_tours_is_3-13.8 574.-0.02 0.00
coef_urban_and_discretionary_tour 0.00 0.00 NA 0.00fixed value
coef_urban_and_escorting_tour 0.729 0.147 4.97*** 0.00
coef_walk_access_to_retail_and_eating_out 0.0996 0.0402 2.47* 0.00
\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model PTYPE_PRESCHOOL\n" ] }, { "data": { "text/html": [ - "

Iteration 030 [Optimization terminated successfully]

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Iteration 074 [Optimization terminated successfully]

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Best LL = -225.00971520122772

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Best LL = -3515.750312068413

" ], "text/plain": [ "" @@ -4681,403 +10446,391 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_0_auto_household_and_escorting_tour\n", " -2.000000\n", - " -2.0000\n", - " 0.0\n", + " -2.000000\n", + " -2.000000\n", " -2.0\n", " -2.0\n", + " 0.0\n", " 1\n", - " \n", - " -2.000000\n", " \n", " \n", " coef_1_escort_tour_constant\n", - " 0.179651\n", - " 0.3622\n", + " 0.274841\n", + " 0.274841\n", + " 0.362200\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.179651\n", " \n", " \n", " coef_1_plus_eating_out_tours_constant\n", - " 0.204827\n", - " 0.9612\n", + " -0.253387\n", + " -0.253387\n", + " 0.961200\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.204827\n", " \n", " \n", " coef_1_plus_maintenance_tours_constant\n", - " 0.073169\n", - " 0.6788\n", + " 0.316648\n", + " 0.316648\n", + " 0.678800\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.073169\n", " \n", " \n", " coef_1_plus_other_discretionary_tours_constant\n", - " 1.133662\n", - " 1.4935\n", + " 1.168896\n", + " 1.168896\n", + " 1.493500\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.133662\n", " \n", " \n", " coef_1_plus_shopping_tours_constant\n", - " 0.785367\n", - " 1.6919\n", + " 1.139680\n", + " 1.139680\n", + " 1.691900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.785367\n", " \n", " \n", " coef_1_plus_visting_tours_constant\n", - " -0.011286\n", - " 0.4424\n", + " 0.059049\n", + " 0.059049\n", + " 0.442400\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.011286\n", " \n", " \n", " coef_2_plus_escort_tours_constant\n", - " 1.744429\n", - " 2.2219\n", + " 1.941139\n", + " 1.941139\n", + " 2.221900\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.744429\n", " \n", " \n", " coef_discretionary_tour\n", - " 0.543162\n", - " 0.9030\n", + " 0.578396\n", + " 0.578396\n", + " 0.903000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.543162\n", " \n", " \n", " coef_escorting_tour\n", - " 1.353509\n", - " 2.4910\n", + " 1.842119\n", + " 1.842119\n", + " 2.491000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.353509\n", " \n", " \n", " coef_maintenance_tour\n", - " 0.416369\n", - " 1.0220\n", + " 0.659848\n", + " 0.659848\n", + " 1.022000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.416369\n", " \n", " \n", " coef_presence_of_full_time_worker_and_escorting_tour\n", - " -0.613492\n", - " -0.8930\n", + " -0.928522\n", + " -0.928522\n", + " -0.893000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.613492\n", " \n", " \n", " coef_presence_of_non_worker_and_discretionary_tour\n", - " 0.013879\n", - " 0.7910\n", + " 0.693868\n", + " 0.693868\n", + " 0.791000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.013879\n", " \n", " \n", " coef_presence_of_non_worker_and_eating_out_tour\n", - " 1.115052\n", - " 1.1570\n", + " 1.549677\n", + " 1.549677\n", + " 1.157000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.115052\n", " \n", " \n", " coef_presence_of_non_worker_and_escorting_tour\n", - " 0.890993\n", - " 0.8900\n", + " 0.960167\n", + " 0.960167\n", + " 0.890000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.890993\n", " \n", " \n", " coef_presence_of_non_worker_and_shopping_tour\n", - " 0.231053\n", - " 0.8080\n", + " 0.669579\n", + " 0.669579\n", + " 0.808000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.231053\n", " \n", " \n", " coef_presence_of_part_time_worker_and_eating_out_tour\n", - " 1.392675\n", - " 1.0370\n", + " 1.135686\n", + " 1.135686\n", + " 1.037000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.392675\n", " \n", " \n", " coef_presence_of_part_time_worker_and_shopping_tour\n", - " 1.044044\n", - " 1.1550\n", + " 1.013348\n", + " 1.013348\n", + " 1.155000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.044044\n", " \n", " \n", " coef_total_number_of_tours_is_1\n", - " -4.436747\n", - " -5.7590\n", + " -4.911268\n", + " -4.911268\n", + " -5.759000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -4.436747\n", " \n", " \n", " coef_total_number_of_tours_is_2\n", - " -9.039558\n", - " -11.5170\n", + " -9.965345\n", + " -9.965345\n", + " -11.517000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -9.039558\n", " \n", " \n", " coef_total_number_of_tours_is_3\n", - " -12.714429\n", - " -17.2760\n", + " -15.118161\n", + " -15.118161\n", + " -17.275999\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -12.714429\n", " \n", " \n", " coef_total_number_of_tours_is_4\n", - " -29.080351\n", - " -23.0350\n", + " -19.999999\n", + " -19.999999\n", + " -23.035000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -29.080351\n", " \n", " \n", " coef_total_number_of_tours_is_6_plus\n", " -999.000000\n", - " -999.0000\n", - " 0.0\n", + " -999.000000\n", + " -999.000000\n", " -999.0\n", " -999.0\n", + " 0.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_urban_and_discretionary_tour\n", " 0.000000\n", - " 0.0000\n", + " 0.000000\n", + " 0.000000\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_visiting_or_social_tour\n", - " 0.315314\n", - " 0.7690\n", + " 0.385649\n", + " 0.385649\n", + " 0.769000\n", + " -20.0\n", + " 20.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.315314\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_0_auto_household_and_escorting_tour -2.000000 -2.0000 \n", - "coef_1_escort_tour_constant 0.179651 0.3622 \n", - "coef_1_plus_eating_out_tours_constant 0.204827 0.9612 \n", - "coef_1_plus_maintenance_tours_constant 0.073169 0.6788 \n", - "coef_1_plus_other_discretionary_tours_constant 1.133662 1.4935 \n", - "coef_1_plus_shopping_tours_constant 0.785367 1.6919 \n", - "coef_1_plus_visting_tours_constant -0.011286 0.4424 \n", - "coef_2_plus_escort_tours_constant 1.744429 2.2219 \n", - "coef_discretionary_tour 0.543162 0.9030 \n", - "coef_escorting_tour 1.353509 2.4910 \n", - "coef_maintenance_tour 0.416369 1.0220 \n", - "coef_presence_of_full_time_worker_and_escorting... -0.613492 -0.8930 \n", - "coef_presence_of_non_worker_and_discretionary_tour 0.013879 0.7910 \n", - "coef_presence_of_non_worker_and_eating_out_tour 1.115052 1.1570 \n", - "coef_presence_of_non_worker_and_escorting_tour 0.890993 0.8900 \n", - "coef_presence_of_non_worker_and_shopping_tour 0.231053 0.8080 \n", - "coef_presence_of_part_time_worker_and_eating_ou... 1.392675 1.0370 \n", - "coef_presence_of_part_time_worker_and_shopping_... 1.044044 1.1550 \n", - "coef_total_number_of_tours_is_1 -4.436747 -5.7590 \n", - "coef_total_number_of_tours_is_2 -9.039558 -11.5170 \n", - "coef_total_number_of_tours_is_3 -12.714429 -17.2760 \n", - "coef_total_number_of_tours_is_4 -29.080351 -23.0350 \n", - "coef_total_number_of_tours_is_6_plus -999.000000 -999.0000 \n", - "coef_urban_and_discretionary_tour 0.000000 0.0000 \n", - "coef_visiting_or_social_tour 0.315314 0.7690 \n", + " value best \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.000000 \n", + "coef_1_escort_tour_constant 0.274841 0.274841 \n", + "coef_1_plus_eating_out_tours_constant -0.253387 -0.253387 \n", + "coef_1_plus_maintenance_tours_constant 0.316648 0.316648 \n", + "coef_1_plus_other_discretionary_tours_constant 1.168896 1.168896 \n", + "coef_1_plus_shopping_tours_constant 1.139680 1.139680 \n", + "coef_1_plus_visting_tours_constant 0.059049 0.059049 \n", + "coef_2_plus_escort_tours_constant 1.941139 1.941139 \n", + "coef_discretionary_tour 0.578396 0.578396 \n", + "coef_escorting_tour 1.842119 1.842119 \n", + "coef_maintenance_tour 0.659848 0.659848 \n", + "coef_presence_of_full_time_worker_and_escorting... -0.928522 -0.928522 \n", + "coef_presence_of_non_worker_and_discretionary_tour 0.693868 0.693868 \n", + "coef_presence_of_non_worker_and_eating_out_tour 1.549677 1.549677 \n", + "coef_presence_of_non_worker_and_escorting_tour 0.960167 0.960167 \n", + "coef_presence_of_non_worker_and_shopping_tour 0.669579 0.669579 \n", + "coef_presence_of_part_time_worker_and_eating_ou... 1.135686 1.135686 \n", + "coef_presence_of_part_time_worker_and_shopping_... 1.013348 1.013348 \n", + "coef_total_number_of_tours_is_1 -4.911268 -4.911268 \n", + "coef_total_number_of_tours_is_2 -9.965345 -9.965345 \n", + "coef_total_number_of_tours_is_3 -15.118161 -15.118161 \n", + "coef_total_number_of_tours_is_4 -19.999999 -19.999999 \n", + "coef_total_number_of_tours_is_6_plus -999.000000 -999.000000 \n", + "coef_urban_and_discretionary_tour 0.000000 0.000000 \n", + "coef_visiting_or_social_tour 0.385649 0.385649 \n", "\n", - " nullvalue minimum \\\n", - "coef_0_auto_household_and_escorting_tour 0.0 -2.0 \n", - "coef_1_escort_tour_constant 0.0 NaN \n", - "coef_1_plus_eating_out_tours_constant 0.0 NaN \n", - "coef_1_plus_maintenance_tours_constant 0.0 NaN \n", - "coef_1_plus_other_discretionary_tours_constant 0.0 NaN \n", - "coef_1_plus_shopping_tours_constant 0.0 NaN \n", - "coef_1_plus_visting_tours_constant 0.0 NaN \n", - "coef_2_plus_escort_tours_constant 0.0 NaN \n", - "coef_discretionary_tour 0.0 NaN \n", - "coef_escorting_tour 0.0 NaN \n", - "coef_maintenance_tour 0.0 NaN \n", - "coef_presence_of_full_time_worker_and_escorting... 0.0 NaN \n", - "coef_presence_of_non_worker_and_discretionary_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_eating_out_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_escorting_tour 0.0 NaN \n", - "coef_presence_of_non_worker_and_shopping_tour 0.0 NaN \n", - "coef_presence_of_part_time_worker_and_eating_ou... 0.0 NaN \n", - "coef_presence_of_part_time_worker_and_shopping_... 0.0 NaN \n", - "coef_total_number_of_tours_is_1 0.0 NaN \n", - "coef_total_number_of_tours_is_2 0.0 NaN \n", - "coef_total_number_of_tours_is_3 0.0 NaN \n", - "coef_total_number_of_tours_is_4 0.0 NaN \n", - "coef_total_number_of_tours_is_6_plus 0.0 -999.0 \n", - "coef_urban_and_discretionary_tour 0.0 0.0 \n", - "coef_visiting_or_social_tour 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.000000 -2.0 \n", + "coef_1_escort_tour_constant 0.362200 -20.0 \n", + "coef_1_plus_eating_out_tours_constant 0.961200 -20.0 \n", + "coef_1_plus_maintenance_tours_constant 0.678800 -20.0 \n", + "coef_1_plus_other_discretionary_tours_constant 1.493500 -20.0 \n", + "coef_1_plus_shopping_tours_constant 1.691900 -20.0 \n", + "coef_1_plus_visting_tours_constant 0.442400 -20.0 \n", + "coef_2_plus_escort_tours_constant 2.221900 -20.0 \n", + "coef_discretionary_tour 0.903000 -20.0 \n", + "coef_escorting_tour 2.491000 -20.0 \n", + "coef_maintenance_tour 1.022000 -20.0 \n", + "coef_presence_of_full_time_worker_and_escorting... -0.893000 -20.0 \n", + "coef_presence_of_non_worker_and_discretionary_tour 0.791000 -20.0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 1.157000 -20.0 \n", + "coef_presence_of_non_worker_and_escorting_tour 0.890000 -20.0 \n", + "coef_presence_of_non_worker_and_shopping_tour 0.808000 -20.0 \n", + "coef_presence_of_part_time_worker_and_eating_ou... 1.037000 -20.0 \n", + "coef_presence_of_part_time_worker_and_shopping_... 1.155000 -20.0 \n", + "coef_total_number_of_tours_is_1 -5.759000 -20.0 \n", + "coef_total_number_of_tours_is_2 -11.517000 -20.0 \n", + "coef_total_number_of_tours_is_3 -17.275999 -20.0 \n", + "coef_total_number_of_tours_is_4 -23.035000 -20.0 \n", + "coef_total_number_of_tours_is_6_plus -999.000000 -999.0 \n", + "coef_urban_and_discretionary_tour 0.000000 0.0 \n", + "coef_visiting_or_social_tour 0.769000 -20.0 \n", "\n", - " maximum holdfast note \\\n", - "coef_0_auto_household_and_escorting_tour -2.0 1 \n", - "coef_1_escort_tour_constant NaN 0 \n", - "coef_1_plus_eating_out_tours_constant NaN 0 \n", - "coef_1_plus_maintenance_tours_constant NaN 0 \n", - "coef_1_plus_other_discretionary_tours_constant NaN 0 \n", - "coef_1_plus_shopping_tours_constant NaN 0 \n", - "coef_1_plus_visting_tours_constant NaN 0 \n", - "coef_2_plus_escort_tours_constant NaN 0 \n", - "coef_discretionary_tour NaN 0 \n", - "coef_escorting_tour NaN 0 \n", - "coef_maintenance_tour NaN 0 \n", - "coef_presence_of_full_time_worker_and_escorting... NaN 0 \n", - "coef_presence_of_non_worker_and_discretionary_tour NaN 0 \n", - "coef_presence_of_non_worker_and_eating_out_tour NaN 0 \n", - "coef_presence_of_non_worker_and_escorting_tour NaN 0 \n", - "coef_presence_of_non_worker_and_shopping_tour NaN 0 \n", - "coef_presence_of_part_time_worker_and_eating_ou... NaN 0 \n", - "coef_presence_of_part_time_worker_and_shopping_... NaN 0 \n", - "coef_total_number_of_tours_is_1 NaN 0 \n", - "coef_total_number_of_tours_is_2 NaN 0 \n", - "coef_total_number_of_tours_is_3 NaN 0 \n", - "coef_total_number_of_tours_is_4 NaN 0 \n", - "coef_total_number_of_tours_is_6_plus -999.0 1 \n", - "coef_urban_and_discretionary_tour 0.0 1 \n", - "coef_visiting_or_social_tour NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour -2.0 0.0 \n", + "coef_1_escort_tour_constant 20.0 0.0 \n", + "coef_1_plus_eating_out_tours_constant 20.0 0.0 \n", + "coef_1_plus_maintenance_tours_constant 20.0 0.0 \n", + "coef_1_plus_other_discretionary_tours_constant 20.0 0.0 \n", + "coef_1_plus_shopping_tours_constant 20.0 0.0 \n", + "coef_1_plus_visting_tours_constant 20.0 0.0 \n", + "coef_2_plus_escort_tours_constant 20.0 0.0 \n", + "coef_discretionary_tour 20.0 0.0 \n", + "coef_escorting_tour 20.0 0.0 \n", + "coef_maintenance_tour 20.0 0.0 \n", + "coef_presence_of_full_time_worker_and_escorting... 20.0 0.0 \n", + "coef_presence_of_non_worker_and_discretionary_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_escorting_tour 20.0 0.0 \n", + "coef_presence_of_non_worker_and_shopping_tour 20.0 0.0 \n", + "coef_presence_of_part_time_worker_and_eating_ou... 20.0 0.0 \n", + "coef_presence_of_part_time_worker_and_shopping_... 20.0 0.0 \n", + "coef_total_number_of_tours_is_1 20.0 0.0 \n", + "coef_total_number_of_tours_is_2 20.0 0.0 \n", + "coef_total_number_of_tours_is_3 20.0 0.0 \n", + "coef_total_number_of_tours_is_4 20.0 0.0 \n", + "coef_total_number_of_tours_is_6_plus -999.0 0.0 \n", + "coef_urban_and_discretionary_tour 0.0 0.0 \n", + "coef_visiting_or_social_tour 20.0 0.0 \n", "\n", - " best \n", - "coef_0_auto_household_and_escorting_tour -2.000000 \n", - "coef_1_escort_tour_constant 0.179651 \n", - "coef_1_plus_eating_out_tours_constant 0.204827 \n", - "coef_1_plus_maintenance_tours_constant 0.073169 \n", - "coef_1_plus_other_discretionary_tours_constant 1.133662 \n", - "coef_1_plus_shopping_tours_constant 0.785367 \n", - "coef_1_plus_visting_tours_constant -0.011286 \n", - "coef_2_plus_escort_tours_constant 1.744429 \n", - "coef_discretionary_tour 0.543162 \n", - "coef_escorting_tour 1.353509 \n", - "coef_maintenance_tour 0.416369 \n", - "coef_presence_of_full_time_worker_and_escorting... -0.613492 \n", - "coef_presence_of_non_worker_and_discretionary_tour 0.013879 \n", - "coef_presence_of_non_worker_and_eating_out_tour 1.115052 \n", - "coef_presence_of_non_worker_and_escorting_tour 0.890993 \n", - "coef_presence_of_non_worker_and_shopping_tour 0.231053 \n", - "coef_presence_of_part_time_worker_and_eating_ou... 1.392675 \n", - "coef_presence_of_part_time_worker_and_shopping_... 1.044044 \n", - "coef_total_number_of_tours_is_1 -4.436747 \n", - "coef_total_number_of_tours_is_2 -9.039558 \n", - "coef_total_number_of_tours_is_3 -12.714429 \n", - "coef_total_number_of_tours_is_4 -29.080351 \n", - "coef_total_number_of_tours_is_6_plus -999.000000 \n", - "coef_urban_and_discretionary_tour 0.000000 \n", - "coef_visiting_or_social_tour 0.315314 " + " holdfast \n", + "param_name \n", + "coef_0_auto_household_and_escorting_tour 1 \n", + "coef_1_escort_tour_constant 0 \n", + "coef_1_plus_eating_out_tours_constant 0 \n", + "coef_1_plus_maintenance_tours_constant 0 \n", + "coef_1_plus_other_discretionary_tours_constant 0 \n", + "coef_1_plus_shopping_tours_constant 0 \n", + "coef_1_plus_visting_tours_constant 0 \n", + "coef_2_plus_escort_tours_constant 0 \n", + "coef_discretionary_tour 0 \n", + "coef_escorting_tour 0 \n", + "coef_maintenance_tour 0 \n", + "coef_presence_of_full_time_worker_and_escorting... 0 \n", + "coef_presence_of_non_worker_and_discretionary_tour 0 \n", + "coef_presence_of_non_worker_and_eating_out_tour 0 \n", + "coef_presence_of_non_worker_and_escorting_tour 0 \n", + "coef_presence_of_non_worker_and_shopping_tour 0 \n", + "coef_presence_of_part_time_worker_and_eating_ou... 0 \n", + "coef_presence_of_part_time_worker_and_shopping_... 0 \n", + "coef_total_number_of_tours_is_1 0 \n", + "coef_total_number_of_tours_is_2 0 \n", + "coef_total_number_of_tours_is_3 0 \n", + "coef_total_number_of_tours_is_4 0 \n", + "coef_total_number_of_tours_is_6_plus 1 \n", + "coef_urban_and_discretionary_tour 1 \n", + "coef_visiting_or_social_tour 0 " ] }, "metadata": {}, @@ -5087,873 +10840,307 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " m.estimate(method='SLSQP')\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/linalg/__init__.py:18: UserWarning: minimum eig 2.8528068249273466e-08 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: PossibleOverspecification: WARNING: Model seems to have 14 parameter estimators with negative variance\n", - "- coef_1_escort_tour_constant\n", - "- coef_1_plus_eating_out_tours_constant\n", - "- coef_1_plus_maintenance_tours_constant\n", - "- coef_1_plus_shopping_tours_constant\n", - "- and 10 more\n", - " m.estimate(method='SLSQP')\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_48972/89088409.py:2: RuntimeWarning: invalid value encountered in sqrt\n", - " m.estimate(method='SLSQP')\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] - } - ], - "source": [ - "for k, m in model.items():\n", - " m.estimate(method='SLSQP')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Estimated coefficients" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ + }, { "data": { "text/html": [ "\n", - "\n", + "
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 ValueStd Errt StatSignifLike RatioNull ValueConstrainedValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_0_auto_household_and_escorting_tour-2.00 NA NA NA 0.00fixed value
coef_1_escort_tour_constant 0.319 NA NA[*] 2.36 0.00
coef_1_plus_eating_out_tours_constant-1.01 124.-0.01 NA 0.00
coef_1_plus_maintenance_tours_constant-2.84 124.-0.02 NA 0.00
coef_1_plus_other_discretionary_tours_constant 10.5 123. 0.09 NA 0.00
coef_1_plus_shopping_tours_constant 7.18 124. 0.06 NA 0.00
coef_1_plus_visting_tours_constant-0.321 124.-0.00 NA 0.00
coef_2_plus_escort_tours_constant 0.607 NA NA[] 0.97 0.00
coef_at_home_pre_driving_school_kid_and_escorting_tour-0.926 1.05-0.89 NA 0.00
coef_at_home_pre_school_kid_and_discretionary_tour-0.656 0.743-0.88 NA 0.00
coef_at_home_pre_school_kid_and_escorting_tour-0.793 0.821-0.97 NA 0.00
coef_auto_access_to_retail_and_discretionary-1.05 0.957-1.10 NA 0.00
coef_auto_access_to_retail_and_maintenance 0.279 0.886 0.31 NA 0.00
coef_auto_access_to_retail_and_shopping-0.631 0.855-0.74 NA 0.00
coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus 0.168 0.233 0.72 NA 0.00
coef_female_and_escorting_tour 0.601 0.266 2.26* NA 0.00
coef_female_and_tour_frequency_is_1-0.316 0.137-2.31* NA 0.00
coef_female_and_tour_frequency_is_2-0.583 0.277-2.11* NA 0.00
coef_female_and_tour_frequency_is_5 0.0227 0.671 0.03 NA 0.00
coef_high_income_group_and_discretionary_tour-0.0604 0.241-0.25 NA 0.00
coef_high_income_group_and_eating_out_tour 0.726 0.282 2.58** NA 0.00
coef_high_income_group_and_tour_frequency_is_1 1.14 0.408 2.79** NA 0.00
coef_high_income_group_and_tour_frequency_is_2 2.22 0.869 2.55* NA 0.00
coef_high_income_group_and_tour_frequency_is_5_plus 0.105 1.42 0.07 NA 0.00
coef_high_income_group_and_visiting_tour-0.863 0.350-2.46* NA 0.00
coef_logged_maximum_residual_window_tour_frequency_is_1 1.34 0.232 5.76*** NA 0.00
coef_logged_maximum_residual_window_tour_frequency_is_2 1.43 0.289 4.94*** NA 0.00
coef_logged_maximum_residual_window_tour_frequency_is_5_plus 0.640 1.09 0.59 NA 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_1 1.09 0.394 2.77** NA 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_2 1.81 0.850 2.13* NA 0.00
coef_mediumhigh_income_group_and_tour_frequency_is_5_plus 1.04 1.25 0.83 NA 0.00
coef_number_of_joint_eating_out_tours-9.98 147.-0.07 NA 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_2-1.43 0.489-2.93** NA 0.00
coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus-1.64 2.28-0.72 NA 0.00
coef_presence_of_driving_school_kid_and_discretionary_tour 0.384 0.452 0.85 NA 0.00
coef_presence_of_driving_school_kid_and_escorting_tour-0.211 0.529-0.40 NA 0.00
coef_presence_of_full_time_worker_and_discretionary_tour-0.783 0.222-3.53*** NA 0.00
coef_presence_of_full_time_worker_and_eating_out_tour-0.748 0.221-3.38*** NA 0.00
coef_presence_of_full_time_worker_and_maintenance_tour-0.342 0.271-1.27 NA 0.00
coef_presence_of_full_time_worker_and_shopping_tour-0.631 0.190-3.32*** NA 0.00
coef_presence_of_non_worker_and_discretionary_tour-1.27 0.384-3.30*** NA 0.00
coef_presence_of_non_worker_and_eating_out_tour-0.445 0.327-1.36 NA 0.00
coef_presence_of_non_worker_and_escorting_tour-0.854 0.404-2.11* NA 0.00
coef_presence_of_non_worker_and_maintenance_tour-0.209 0.364-0.58 NA 0.00
coef_presence_of_non_worker_and_shopping_tour-0.844 0.301-2.80** NA 0.00
coef_presence_of_part_time_worker_and_discretionary_tour-0.0412 0.265-0.16 NA 0.00
coef_presence_of_part_time_worker_and_maintenance_tour-0.183 0.328-0.56 NA 0.00
coef_presence_of_part_time_worker_and_shopping_tour-0.149 0.224-0.66 NA 0.00
coef_presence_of_pre_driving_school_kid_and_discretionary_tour-0.126 0.314-0.40 NA 0.00
coef_presence_of_pre_driving_school_kid_and_escorting_tour 1.40 0.268 5.23*** NA 0.00
coef_presence_of_pre_school_kid_and_discretionary_tour-0.0171 0.349-0.05 NA 0.00
coef_presence_of_pre_school_kid_and_eating_out_tour-0.845 0.421-2.01* NA 0.00
coef_presence_of_pre_school_kid_and_escorting_tour 0.748 0.309 2.42* NA 0.00
coef_presence_of_pre_school_kid_and_shopping_tour-0.00614 0.294-0.02 NA 0.00
coef_presence_of_retiree_and_discretionary_tour-0.597 0.461-1.29 NA 0.00
coef_presence_of_retiree_and_eating_out_tour-1.29 0.618-2.08* NA 0.00
coef_presence_of_retiree_and_escorting_tour-12.9 250.-0.05 NA 0.00
coef_presence_of_university_student_and_discretionary_tour-0.407 0.376-1.08 NA 0.00
coef_total_number_of_tours_is_1-7.52 124.-0.06 NA 0.00
coef_total_number_of_tours_is_2-10.1 247.-0.04 NA 0.00
coef_total_number_of_tours_is_3-11.1 371.-0.03 NA 0.00
coef_total_number_of_tours_is_4-12.8 494.-0.03 NA 0.00
coef_total_number_of_tours_is_5-21.8 623.-0.03 NA 0.00
coef_total_number_of_tours_is_6_plus-999. NA NA NA 0.00fixed value
coef_transit_access_to_retail_and_tour_frequency_is_5_plus 0.0745 0.114 0.65 NA 0.00
coef_urban_and_discretionary_tour 0.00 NA NA NA 0.00fixed value
coef_urban_and_escorting_tour-0.409 NA NA[***] 6.54 0.00
coef_walk_access_to_retail_and_discretionary 0.161 0.169 0.95 NA 0.00
coef_walk_access_to_retail_and_eating_out 0.211 0.128 1.65 NA 0.00
coef_walk_access_to_retail_and_escorting-0.105 0.147-0.72 NA 0.00
coef_walk_access_to_retail_and_shopping 0.0302 0.146 0.21 NA 0.00
coef_zero_car_ownership_and_tour_frequency_is_5_plus-0.227 0.175-1.30 NA 0.00coef_0_auto_household_and_escorting_tour-2.00 0.00 NA 0.00fixed value
coef_1_escort_tour_constant 0.275 211. 0.00 0.00
coef_1_plus_eating_out_tours_constant-0.253 0.215-1.18 0.00
coef_1_plus_maintenance_tours_constant 0.317 9.89e+13 0.00 0.00
coef_1_plus_other_discretionary_tours_constant 1.17 2.63e+06 0.00 0.00
coef_1_plus_shopping_tours_constant 1.14 0.0702 16.23*** 0.00
coef_1_plus_visting_tours_constant 0.0590 NA NA 0.00
coef_2_plus_escort_tours_constant 1.94 421. 0.00 0.00
coef_discretionary_tour 0.578 NA NA 0.00
coef_escorting_tour 1.84 212. 0.01 0.00
coef_maintenance_tour 0.660 9.89e+13 0.00 0.00
coef_presence_of_full_time_worker_and_escorting_tour-0.929 0.105-8.82*** 0.00
coef_presence_of_non_worker_and_discretionary_tour 0.694 0.129 5.36*** 0.00
coef_presence_of_non_worker_and_eating_out_tour 1.55 0.222 6.97*** 0.00
coef_presence_of_non_worker_and_escorting_tour 0.960 0.127 7.56*** 0.00
coef_presence_of_non_worker_and_shopping_tour 0.670 0.151 4.44*** 0.00
coef_presence_of_part_time_worker_and_eating_out_tour 1.14 0.195 5.81*** 0.00
coef_presence_of_part_time_worker_and_shopping_tour 1.01 0.142 7.12*** 0.00
coef_total_number_of_tours_is_1-4.91 NA NA 0.00
coef_total_number_of_tours_is_2-9.97 NA NA 0.00
coef_total_number_of_tours_is_3-15.1 0.239-63.27*** 0.00
coef_total_number_of_tours_is_4-20.0 0.00 NA 0.00coef_total_number_of_tours_is_4 ≥ -20.0
coef_total_number_of_tours_is_6_plus-999. 0.00 NA 0.00fixed value
coef_urban_and_discretionary_tour 0.00 0.00 NA 0.00fixed value
coef_visiting_or_social_tour 0.386 NA NA 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 11, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], - "source": [ - "model['PTYPE_FULL'].parameter_summary()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "colab_type": "text", - "id": "TojXWivZsx7M" - }, - "source": [ - "# Output Estimation Results" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], "source": [ "from activitysim.estimation.larch import update_coefficients\n", + "\n", "for k, m in model.items():\n", + " print(f\"Model {k}\")\n", + " m.set_cap(20)\n", + " m.estimate(method='SLSQP', maxiter=900)\n", + "\n", + " display(m.parameter_summary())\n", + "\n", " result_dir = data.edb_directory/k/\"estimated\"\n", " update_coefficients(\n", " m, data.coefficients[k], result_dir,\n", " output_file=f\"{modelname}_{k}_coefficients_revised.csv\",\n", " relabel_coef=data.relabel_coef.get(k),\n", - " );" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Write the model estimation report, including coefficient t-statistic and log likelihood" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/util/excel.py:523: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/util/excel.py:523: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/util/excel.py:523: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/util/excel.py:523: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/util/excel.py:523: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/util/excel.py:523: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/util/excel.py:523: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n", - "/Users/jeffnewman/LocalGit/asim-larch/activitysim-larch/conda-environments/AL-ENV/lib/python3.9/site-packages/larch/util/excel.py:523: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n" - ] - } - ], - "source": [ - "for k, m in model.items():\n", - " result_dir = data.edb_directory/k/\"estimated\"\n", + " )\n", + "\n", " m.to_xlsx(\n", " result_dir/f\"{modelname}_{k}_model_estimation.xlsx\", \n", " data_statistics=False,\n", - " )" + " )\n", + "\n", + " m.release_memory()\n" ] }, { @@ -5967,7 +11154,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -6036,25 +11223,25 @@ " \n", " 205\n", " coef_1_plus_maintenance_tours_constant\n", - " -2.842643\n", + " 0.079776\n", " F\n", " \n", " \n", " 206\n", " coef_1_plus_eating_out_tours_constant\n", - " -1.012856\n", + " 0.047768\n", " F\n", " \n", " \n", " 207\n", " coef_1_plus_visting_tours_constant\n", - " -0.320820\n", + " -0.019022\n", " F\n", " \n", " \n", " 208\n", " coef_1_plus_other_discretionary_tours_constant\n", - " 10.543979\n", + " 0.733799\n", " F\n", " \n", " \n", @@ -6069,23 +11256,23 @@ "" ], "text/plain": [ - " coefficient_name value constrain\n", - "0 coef_escorting_tour 0.000000 T\n", - "1 coef_discretionary_tour 0.000000 T\n", - "2 coef_shopping_tour 0.000000 T\n", - "3 coef_maintenance_tour 0.000000 T\n", - "4 coef_visiting_or_social_tour 0.000000 T\n", - ".. ... ... ...\n", - "205 coef_1_plus_maintenance_tours_constant -2.842643 F\n", - "206 coef_1_plus_eating_out_tours_constant -1.012856 F\n", - "207 coef_1_plus_visting_tours_constant -0.320820 F\n", - "208 coef_1_plus_other_discretionary_tours_constant 10.543979 F\n", - "209 coef_0_auto_household_and_escorting_tour -2.000000 T\n", + " coefficient_name value constrain\n", + "0 coef_escorting_tour 0.000000 T\n", + "1 coef_discretionary_tour 0.000000 T\n", + "2 coef_shopping_tour 0.000000 T\n", + "3 coef_maintenance_tour 0.000000 T\n", + "4 coef_visiting_or_social_tour 0.000000 T\n", + ".. ... ... ...\n", + "205 coef_1_plus_maintenance_tours_constant 0.079776 F\n", + "206 coef_1_plus_eating_out_tours_constant 0.047768 F\n", + "207 coef_1_plus_visting_tours_constant -0.019022 F\n", + "208 coef_1_plus_other_discretionary_tours_constant 0.733799 F\n", + "209 coef_0_auto_household_and_escorting_tour -2.000000 T\n", "\n", "[210 rows x 3 columns]" ] }, - "execution_count": 14, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -6103,7 +11290,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -6117,7 +11304,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.10.15" }, "toc": { "base_numbering": 1, @@ -6135,4 +11322,4 @@ }, "nbformat": 4, "nbformat_minor": 1 -} \ No newline at end of file +} diff --git a/activitysim/examples/example_estimation/notebooks/16_nonmand_tour_scheduling.ipynb b/activitysim/examples/example_estimation/notebooks/16_nonmand_tour_scheduling.ipynb index 3d7a8214f7..522ff71ca3 100644 --- a/activitysim/examples/example_estimation/notebooks/16_nonmand_tour_scheduling.ipynb +++ b/activitysim/examples/example_estimation/notebooks/16_nonmand_tour_scheduling.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +115,28 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_scheduling/tour_scheduling_nonmandatory_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_scheduling/non_mandatory_tour_scheduling_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_scheduling/non_mandatory_tour_scheduling_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/non_mandatory_tour_scheduling/non_mandatory_tour_scheduling_choosers_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"non_mandatory_tour_scheduling\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -256,38 +319,38 @@ " \n", " \n", " \n", - " 0\n", + " 5\n", " util_subsequent_tour_must_start_after_previous...\n", " Subsequent tour must start after previous tour...\n", " (start < end_previous) & (tour_type_num > 1)\n", " coef_subsequent_tour_must_start_after_previous...\n", " \n", " \n", - " 1\n", + " 6\n", " util_free_flow_round_trip_auto_time_shift_effe...\n", " Free-flow round trip auto time shift effects -...\n", " roundtrip_auto_time_to_work * duration\n", " coef_free_flow_round_trip_auto_time_shift_effe...\n", " \n", " \n", - " 2\n", + " 7\n", " util_shopping_tour_departure_shift_effects\n", " Shopping tour - departure shift effects\n", - " (tour_type == 'shopping') * start\n", + " @(_is_shopping) * df.start\n", " coef_shopping_tour_departure_shift_effects\n", " \n", " \n", - " 3\n", + " 8\n", " util_shopping_tour_duration_shift_effects\n", " Shopping tour - duration shift effects\n", - " (tour_type == 'shopping') * duration\n", + " @(_is_shopping) * df.duration\n", " coef_shopping_tour_duration_shift_effects\n", " \n", " \n", - " 4\n", + " 9\n", " util_maintenance_tour_departure_shift_effects\n", " Maintenance tour - departure shift effects\n", - " (tour_type == 'othmaint') * start\n", + " @(_is_othmaint) * df.start\n", " coef_maintenance_tour_departure_shift_effects\n", " \n", " \n", @@ -298,38 +361,38 @@ " ...\n", " \n", " \n", - " 86\n", + " 91\n", " util_escort_tour_duration_constants_4_to_5_hours\n", " Escort Tour Duration Constants -- 4 to 5 hours\n", - " (tour_type == 'escort') & (duration > 3) & (du...\n", + " @(_is_escort) * (df.duration > 3) * (df.durati...\n", " coef_escort_tour_duration_constants_4_to_5_hours\n", " \n", " \n", - " 87\n", + " 92\n", " util_escort_tour_duration_constants_6_to_7_hours\n", " Escort Tour Duration Constants -- 6 to 7 hours\n", - " (tour_type == 'escort') & (duration > 5) & (du...\n", + " @(_is_escort) * (df.duration > 5) * (df.durati...\n", " coef_escort_tour_duration_constants_6_to_7_hours\n", " \n", " \n", - " 88\n", + " 93\n", " util_escort_tour_duration_constants_8_to_10_hours\n", " Escort Tour Duration Constants -- 8 to 10 hours\n", - " (tour_type == 'escort') & (duration > 7) & (du...\n", + " @(_is_escort) * (df.duration > 7) * (df.durati...\n", " coef_escort_tour_duration_constants_8_to_10_hours\n", " \n", " \n", - " 89\n", + " 94\n", " util_escort_tour_duration_constants_11_to_13_h...\n", " Escort Tour Duration Constants -- 11 to 13 hours\n", - " (tour_type == 'escort') & (duration > 10) & (d...\n", + " @(_is_escort) * (df.duration > 10) * (df.durat...\n", " coef_escort_tour_duration_constants_11_to_13_h...\n", " \n", " \n", - " 90\n", + " 95\n", " util_escort_tour_duration_constants_14_to_18_h...\n", " Escort Tour Duration Constants -- 14 to 18 hours\n", - " (tour_type == 'escort') & (duration > 13) & (d...\n", + " @(_is_escort) * (df.duration > 13) * (df.durat...\n", " coef_escort_tour_duration_constants_14_to_18_h...\n", " \n", " \n", @@ -339,56 +402,56 @@ ], "text/plain": [ " Label \\\n", - "0 util_subsequent_tour_must_start_after_previous... \n", - "1 util_free_flow_round_trip_auto_time_shift_effe... \n", - "2 util_shopping_tour_departure_shift_effects \n", - "3 util_shopping_tour_duration_shift_effects \n", - "4 util_maintenance_tour_departure_shift_effects \n", + "5 util_subsequent_tour_must_start_after_previous... \n", + "6 util_free_flow_round_trip_auto_time_shift_effe... \n", + "7 util_shopping_tour_departure_shift_effects \n", + "8 util_shopping_tour_duration_shift_effects \n", + "9 util_maintenance_tour_departure_shift_effects \n", ".. ... \n", - "86 util_escort_tour_duration_constants_4_to_5_hours \n", - "87 util_escort_tour_duration_constants_6_to_7_hours \n", - "88 util_escort_tour_duration_constants_8_to_10_hours \n", - "89 util_escort_tour_duration_constants_11_to_13_h... \n", - "90 util_escort_tour_duration_constants_14_to_18_h... \n", + "91 util_escort_tour_duration_constants_4_to_5_hours \n", + "92 util_escort_tour_duration_constants_6_to_7_hours \n", + "93 util_escort_tour_duration_constants_8_to_10_hours \n", + "94 util_escort_tour_duration_constants_11_to_13_h... \n", + "95 util_escort_tour_duration_constants_14_to_18_h... \n", "\n", " Description \\\n", - "0 Subsequent tour must start after previous tour... \n", - "1 Free-flow round trip auto time shift effects -... \n", - "2 Shopping tour - departure shift effects \n", - "3 Shopping tour - duration shift effects \n", - "4 Maintenance tour - departure shift effects \n", + "5 Subsequent tour must start after previous tour... \n", + "6 Free-flow round trip auto time shift effects -... \n", + "7 Shopping tour - departure shift effects \n", + "8 Shopping tour - duration shift effects \n", + "9 Maintenance tour - departure shift effects \n", ".. ... \n", - "86 Escort Tour Duration Constants -- 4 to 5 hours \n", - "87 Escort Tour Duration Constants -- 6 to 7 hours \n", - "88 Escort Tour Duration Constants -- 8 to 10 hours \n", - "89 Escort Tour Duration Constants -- 11 to 13 hours \n", - "90 Escort Tour Duration Constants -- 14 to 18 hours \n", + "91 Escort Tour Duration Constants -- 4 to 5 hours \n", + "92 Escort Tour Duration Constants -- 6 to 7 hours \n", + "93 Escort Tour Duration Constants -- 8 to 10 hours \n", + "94 Escort Tour Duration Constants -- 11 to 13 hours \n", + "95 Escort Tour Duration Constants -- 14 to 18 hours \n", "\n", " Expression \\\n", - "0 (start < end_previous) & (tour_type_num > 1) \n", - "1 roundtrip_auto_time_to_work * duration \n", - "2 (tour_type == 'shopping') * start \n", - "3 (tour_type == 'shopping') * duration \n", - "4 (tour_type == 'othmaint') * start \n", + "5 (start < end_previous) & (tour_type_num > 1) \n", + "6 roundtrip_auto_time_to_work * duration \n", + "7 @(_is_shopping) * df.start \n", + "8 @(_is_shopping) * df.duration \n", + "9 @(_is_othmaint) * df.start \n", ".. ... \n", - "86 (tour_type == 'escort') & (duration > 3) & (du... \n", - "87 (tour_type == 'escort') & (duration > 5) & (du... \n", - "88 (tour_type == 'escort') & (duration > 7) & (du... \n", - "89 (tour_type == 'escort') & (duration > 10) & (d... \n", - "90 (tour_type == 'escort') & (duration > 13) & (d... \n", + "91 @(_is_escort) * (df.duration > 3) * (df.durati... \n", + "92 @(_is_escort) * (df.duration > 5) * (df.durati... \n", + "93 @(_is_escort) * (df.duration > 7) * (df.durati... \n", + "94 @(_is_escort) * (df.duration > 10) * (df.durat... \n", + "95 @(_is_escort) * (df.duration > 13) * (df.durat... \n", "\n", " Coefficient \n", - "0 coef_subsequent_tour_must_start_after_previous... \n", - "1 coef_free_flow_round_trip_auto_time_shift_effe... \n", - "2 coef_shopping_tour_departure_shift_effects \n", - "3 coef_shopping_tour_duration_shift_effects \n", - "4 coef_maintenance_tour_departure_shift_effects \n", + "5 coef_subsequent_tour_must_start_after_previous... \n", + "6 coef_free_flow_round_trip_auto_time_shift_effe... \n", + "7 coef_shopping_tour_departure_shift_effects \n", + "8 coef_shopping_tour_duration_shift_effects \n", + "9 coef_maintenance_tour_departure_shift_effects \n", ".. ... \n", - "86 coef_escort_tour_duration_constants_4_to_5_hours \n", - "87 coef_escort_tour_duration_constants_6_to_7_hours \n", - "88 coef_escort_tour_duration_constants_8_to_10_hours \n", - "89 coef_escort_tour_duration_constants_11_to_13_h... \n", - "90 coef_escort_tour_duration_constants_14_to_18_h... \n", + "91 coef_escort_tour_duration_constants_4_to_5_hours \n", + "92 coef_escort_tour_duration_constants_6_to_7_hours \n", + "93 coef_escort_tour_duration_constants_8_to_10_hours \n", + "94 coef_escort_tour_duration_constants_11_to_13_h... \n", + "95 coef_escort_tour_duration_constants_14_to_18_h... \n", "\n", "[89 rows x 4 columns]" ] @@ -461,11 +524,11 @@ " \n", " \n", " 0\n", - " 6812\n", - " 118\n", - " 118\n", - " 166\n", - " eatout\n", + " 1870\n", + " 73\n", + " 137\n", + " 45\n", + " othdiscr\n", " 1\n", " 1\n", " 1\n", @@ -485,11 +548,11 @@ " \n", " \n", " 1\n", - " 8110\n", - " 112\n", - " 112\n", - " 197\n", - " shopping\n", + " 20468\n", + " 99\n", + " 124\n", + " 499\n", + " escort\n", " 1\n", " 1\n", " 1\n", @@ -501,23 +564,23 @@ " 0\n", " 0.0\n", " 0\n", - " 0\n", " 1\n", + " 0\n", " True\n", " 5\n", " 5\n", " \n", " \n", " 2\n", - " 11013\n", - " 169\n", + " 27055\n", + " 146\n", " 169\n", - " 268\n", - " othdiscr\n", + " 659\n", + " social\n", + " 1\n", + " 1\n", " 1\n", " 1\n", - " 2\n", - " 2\n", " non_mandatory\n", " ...\n", " 0\n", @@ -526,18 +589,18 @@ " 0.0\n", " 0\n", " 0\n", - " 2\n", + " 1\n", " True\n", - " 12\n", - " 15\n", + " 5\n", + " 5\n", " \n", " \n", " 3\n", - " 11016\n", - " 115\n", - " 115\n", - " 268\n", - " othmaint\n", + " 38877\n", + " 37\n", + " 125\n", + " 948\n", + " escort\n", " 1\n", " 1\n", " 1\n", @@ -549,23 +612,23 @@ " 0\n", " 0.0\n", " 0\n", - " 0\n", - " 2\n", + " 1\n", + " 1\n", " True\n", " 5\n", " 5\n", " \n", " \n", " 4\n", - " 15403\n", - " 99\n", - " 99\n", - " 375\n", - " othmaint\n", - " 1\n", - " 1\n", + " 38904\n", + " 95\n", + " 172\n", + " 948\n", + " social\n", " 1\n", " 1\n", + " 2\n", + " 2\n", " non_mandatory\n", " ...\n", " 0\n", @@ -573,11 +636,11 @@ " 0\n", " 0.0\n", " 0\n", - " 0\n", + " 1\n", " 1\n", " True\n", - " 5\n", - " 5\n", + " 7\n", + " 7\n", " \n", " \n", " ...\n", @@ -604,16 +667,16 @@ " ...\n", " \n", " \n", - " 2485\n", - " 309760814\n", - " 71\n", - " 71\n", - " 7555141\n", + " 29664\n", + " 310197956\n", + " 125\n", + " 127\n", + " 7565803\n", " shopping\n", - " 2\n", " 1\n", " 1\n", - " 3\n", + " 1\n", + " 1\n", " non_mandatory\n", " ...\n", " 0\n", @@ -622,22 +685,22 @@ " 0.0\n", " 0\n", " 0\n", - " 3\n", + " 1\n", " True\n", " 5\n", " 5\n", " \n", " \n", - " 2486\n", - " 309760815\n", - " 137\n", - " 137\n", - " 7555141\n", - " shopping\n", - " 2\n", + " 29665\n", + " 310202376\n", + " 126\n", + " 5\n", + " 7565911\n", + " othdiscr\n", + " 1\n", + " 1\n", " 2\n", " 2\n", - " 3\n", " non_mandatory\n", " ...\n", " 0\n", @@ -646,22 +709,22 @@ " 0.0\n", " 0\n", " 0\n", - " 3\n", + " 2\n", " True\n", - " 9\n", - " 10\n", + " 15\n", + " 19\n", " \n", " \n", - " 2487\n", - " 309790009\n", - " 109\n", - " 109\n", - " 7555853\n", - " social\n", - " 1\n", + " 29666\n", + " 310202384\n", + " 149\n", + " 129\n", + " 7565911\n", + " shopping\n", " 1\n", " 1\n", " 1\n", + " 2\n", " non_mandatory\n", " ...\n", " 0\n", @@ -670,22 +733,22 @@ " 0.0\n", " 0\n", " 0\n", - " 1\n", + " 2\n", " True\n", " 5\n", " 5\n", " \n", " \n", - " 2488\n", - " 309796968\n", - " 146\n", + " 29667\n", + " 310212634\n", + " 86\n", " 146\n", - " 7556023\n", - " othdiscr\n", - " 2\n", + " 7566161\n", + " shopping\n", + " 1\n", + " 1\n", " 1\n", " 1\n", - " 2\n", " non_mandatory\n", " ...\n", " 0\n", @@ -694,22 +757,22 @@ " 0.0\n", " 0\n", " 0\n", - " 2\n", + " 1\n", " True\n", " 5\n", " 5\n", " \n", " \n", - " 2489\n", - " 309796969\n", - " 180\n", - " 180\n", - " 7556023\n", - " othdiscr\n", - " 2\n", - " 2\n", - " 2\n", - " 2\n", + " 29668\n", + " 310220296\n", + " 74\n", + " 126\n", + " 7566348\n", + " othmaint\n", + " 1\n", + " 1\n", + " 1\n", + " 1\n", " non_mandatory\n", " ...\n", " 0\n", @@ -718,83 +781,83 @@ " 0.0\n", " 0\n", " 0\n", - " 2\n", + " 1\n", " True\n", - " 15\n", - " 16\n", + " 5\n", + " 5\n", " \n", " \n", "\n", - "

2490 rows × 31 columns

\n", + "

29669 rows × 31 columns

\n", "" ], "text/plain": [ - " tour_id model_choice override_choice person_id tour_type \\\n", - "0 6812 118 118 166 eatout \n", - "1 8110 112 112 197 shopping \n", - "2 11013 169 169 268 othdiscr \n", - "3 11016 115 115 268 othmaint \n", - "4 15403 99 99 375 othmaint \n", - "... ... ... ... ... ... \n", - "2485 309760814 71 71 7555141 shopping \n", - "2486 309760815 137 137 7555141 shopping \n", - "2487 309790009 109 109 7555853 social \n", - "2488 309796968 146 146 7556023 othdiscr \n", - "2489 309796969 180 180 7556023 othdiscr \n", + " tour_id model_choice override_choice person_id tour_type \\\n", + "0 1870 73 137 45 othdiscr \n", + "1 20468 99 124 499 escort \n", + "2 27055 146 169 659 social \n", + "3 38877 37 125 948 escort \n", + "4 38904 95 172 948 social \n", + "... ... ... ... ... ... \n", + "29664 310197956 125 127 7565803 shopping \n", + "29665 310202376 126 5 7565911 othdiscr \n", + "29666 310202384 149 129 7565911 shopping \n", + "29667 310212634 86 146 7566161 shopping \n", + "29668 310220296 74 126 7566348 othmaint \n", "\n", - " tour_type_count tour_type_num tour_num tour_count tour_category \\\n", - "0 1 1 1 1 non_mandatory \n", - "1 1 1 1 1 non_mandatory \n", - "2 1 1 2 2 non_mandatory \n", - "3 1 1 1 2 non_mandatory \n", - "4 1 1 1 1 non_mandatory \n", - "... ... ... ... ... ... \n", - "2485 2 1 1 3 non_mandatory \n", - "2486 2 2 2 3 non_mandatory \n", - "2487 1 1 1 1 non_mandatory \n", - "2488 2 1 1 2 non_mandatory \n", - "2489 2 2 2 2 non_mandatory \n", + " tour_type_count tour_type_num tour_num tour_count tour_category \\\n", + "0 1 1 1 1 non_mandatory \n", + "1 1 1 1 1 non_mandatory \n", + "2 1 1 1 1 non_mandatory \n", + "3 1 1 1 2 non_mandatory \n", + "4 1 1 2 2 non_mandatory \n", + "... ... ... ... ... ... \n", + "29664 1 1 1 1 non_mandatory \n", + "29665 1 1 2 2 non_mandatory \n", + "29666 1 1 1 2 non_mandatory \n", + "29667 1 1 1 1 non_mandatory \n", + "29668 1 1 1 1 non_mandatory \n", "\n", - " ... num_person_joint_tours ptype num_children \\\n", - "0 ... 0 4 0 \n", - "1 ... 0 4 0 \n", - "2 ... 0 4 0 \n", - "3 ... 0 4 0 \n", - "4 ... 0 4 0 \n", - "... ... ... ... ... \n", - "2485 ... 0 5 0 \n", - "2486 ... 0 5 0 \n", - "2487 ... 0 5 0 \n", - "2488 ... 0 5 0 \n", - "2489 ... 0 5 0 \n", + " ... num_person_joint_tours ptype num_children \\\n", + "0 ... 0 4 0 \n", + "1 ... 0 4 0 \n", + "2 ... 0 4 0 \n", + "3 ... 0 4 0 \n", + "4 ... 0 4 0 \n", + "... ... ... ... ... \n", + "29664 ... 0 5 0 \n", + "29665 ... 0 5 0 \n", + "29666 ... 0 5 0 \n", + "29667 ... 0 5 0 \n", + "29668 ... 0 5 0 \n", "\n", - " roundtrip_auto_time_to_work num_mand num_escort_tours \\\n", - "0 0.0 0 0 \n", - "1 0.0 0 0 \n", - "2 0.0 0 0 \n", - "3 0.0 0 0 \n", - "4 0.0 0 0 \n", - "... ... ... ... \n", - "2485 0.0 0 0 \n", - "2486 0.0 0 0 \n", - "2487 0.0 0 0 \n", - "2488 0.0 0 0 \n", - "2489 0.0 0 0 \n", + " roundtrip_auto_time_to_work num_mand num_escort_tours \\\n", + "0 0.0 0 0 \n", + "1 0.0 0 1 \n", + "2 0.0 0 0 \n", + "3 0.0 0 1 \n", + "4 0.0 0 1 \n", + "... ... ... ... \n", + "29664 0.0 0 0 \n", + "29665 0.0 0 0 \n", + "29666 0.0 0 0 \n", + "29667 0.0 0 0 \n", + "29668 0.0 0 0 \n", "\n", - " num_non_escort_tours adult start_previous end_previous \n", - "0 1 True 5 5 \n", - "1 1 True 5 5 \n", - "2 2 True 12 15 \n", - "3 2 True 5 5 \n", - "4 1 True 5 5 \n", - "... ... ... ... ... \n", - "2485 3 True 5 5 \n", - "2486 3 True 9 10 \n", - "2487 1 True 5 5 \n", - "2488 2 True 5 5 \n", - "2489 2 True 15 16 \n", + " num_non_escort_tours adult start_previous end_previous \n", + "0 1 True 5 5 \n", + "1 0 True 5 5 \n", + "2 1 True 5 5 \n", + "3 1 True 5 5 \n", + "4 1 True 7 7 \n", + "... ... ... ... ... \n", + "29664 1 True 5 5 \n", + "29665 2 True 15 19 \n", + "29666 2 True 5 5 \n", + "29667 1 True 5 5 \n", + "29668 1 True 5 5 \n", "\n", - "[2490 rows x 31 columns]" + "[29669 rows x 31 columns]" ] }, "execution_count": 6, @@ -840,129 +903,114 @@ " \n", " \n", " tour_id\n", - " variable\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", + " start\n", + " end\n", + " duration\n", + " tdd\n", + " mode_choice_logsum\n", + " util_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends\n", + " util_free_flow_round_trip_auto_time_shift_effects_duration\n", + " util_shopping_tour_departure_shift_effects\n", + " util_shopping_tour_duration_shift_effects\n", " ...\n", - " 180\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", + " util_escort_tour_arrival_constants_pm_peak_4\n", + " util_escort_tour_arrival_constants_evening\n", + " util_escort_tour_arrival_constants_late\n", + " util_escort_tour_duration_constants_0_to_1_hours\n", + " util_escort_tour_duration_constants_2_to_3_hours\n", + " util_escort_tour_duration_constants_4_to_5_hours\n", + " util_escort_tour_duration_constants_6_to_7_hours\n", + " util_escort_tour_duration_constants_8_to_10_hours\n", + " util_escort_tour_duration_constants_11_to_13_hours\n", + " util_escort_tour_duration_constants_14_to_18_hours\n", " \n", " \n", " \n", " \n", " 0\n", - " 6812\n", - " duration\n", + " 1870\n", + " 5\n", + " 5\n", + " 0\n", + " 0\n", + " 0\n", + " False\n", " 0.0\n", - " 1.0\n", - " 2.0\n", - " 3.0\n", - " 4.0\n", - " 5.0\n", - " 6.0\n", - " 7.0\n", + " 0\n", + " 0\n", " ...\n", - " 0.0\n", - " 1.0\n", - " 2.0\n", - " 3.0\n", - " 0.0\n", - " 1.0\n", - " 2.0\n", - " 0.0\n", - " 1.0\n", - " 0.0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 1\n", - " 6812\n", - " end\n", - " 5.0\n", - " 6.0\n", - " 7.0\n", - " 8.0\n", - " 9.0\n", - " 10.0\n", - " 11.0\n", - " 12.0\n", - " ...\n", - " 20.0\n", - " 21.0\n", - " 22.0\n", - " 23.0\n", - " 21.0\n", - " 22.0\n", - " 23.0\n", - " 22.0\n", - " 23.0\n", - " 23.0\n", + " 1870\n", + " 5\n", + " 6\n", + " 1\n", + " 1\n", + " 0\n", + " False\n", + " 0.0\n", + " 0\n", + " 0\n", + " ...\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 2\n", - " 6812\n", - " mode_choice_logsum\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 1870\n", + " 5\n", + " 7\n", + " 2\n", + " 2\n", + " 0\n", + " False\n", " 0.0\n", + " 0\n", + " 0\n", " ...\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 3\n", - " 6812\n", - " start\n", - " 5.0\n", - " 5.0\n", - " 5.0\n", - " 5.0\n", - " 5.0\n", - " 5.0\n", - " 5.0\n", - " 5.0\n", - " ...\n", - " 20.0\n", - " 20.0\n", - " 20.0\n", - " 20.0\n", - " 21.0\n", - " 21.0\n", - " 21.0\n", - " 22.0\n", - " 22.0\n", - " 23.0\n", - " \n", - " \n", - " 4\n", - " 6812\n", - " util_adjacent_window_exists_after_this_arrival...\n", + " 1870\n", + " 5\n", + " 8\n", + " 3\n", + " 3\n", + " 0\n", + " False\n", + " 0.0\n", + " 0\n", + " 0\n", + " ...\n", " False\n", " False\n", " False\n", @@ -971,6 +1019,21 @@ " False\n", " False\n", " False\n", + " False\n", + " False\n", + " \n", + " \n", + " 4\n", + " 1870\n", + " 5\n", + " 9\n", + " 4\n", + " 4\n", + " 0\n", + " False\n", + " 0.0\n", + " 0\n", + " 0\n", " ...\n", " False\n", " False\n", @@ -1008,41 +1071,17 @@ " ...\n", " \n", " \n", - " 231565\n", - " 309796969\n", - " util_subsequent_of_2_plus_tours_for_same_purpo...\n", - " 0\n", + " 3632342\n", + " 310220296\n", + " 21\n", + " 22\n", " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", - " ...\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", + " 185\n", " 0\n", - " 1\n", - " 2\n", + " False\n", + " 0.0\n", " 0\n", - " 1\n", " 0\n", - " \n", - " \n", - " 231566\n", - " 309796969\n", - " util_subsequent_tour_must_start_after_previous...\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", - " True\n", " ...\n", " False\n", " False\n", @@ -1056,9 +1095,21 @@ " False\n", " \n", " \n", - " 231567\n", - " 309796969\n", - " util_university_student_arrive_after_22\n", + " 3632343\n", + " 310220296\n", + " 21\n", + " 23\n", + " 2\n", + " 186\n", + " 0\n", + " False\n", + " 0.0\n", + " 0\n", + " 0\n", + " ...\n", + " False\n", + " False\n", + " False\n", " False\n", " False\n", " False\n", @@ -1066,7 +1117,19 @@ " False\n", " False\n", " False\n", + " \n", + " \n", + " 3632344\n", + " 310220296\n", + " 22\n", + " 22\n", + " 0\n", + " 187\n", + " 0\n", " False\n", + " 0.0\n", + " 0\n", + " 0\n", " ...\n", " False\n", " False\n", @@ -1080,99 +1143,255 @@ " False\n", " \n", " \n", - " 231568\n", - " 309796969\n", - " util_visit_tour_departure_shift_effects_start\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 3632345\n", + " 310220296\n", + " 22\n", + " 23\n", + " 1\n", + " 188\n", " 0\n", + " False\n", + " 0.0\n", " 0\n", " 0\n", " ...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", - " 231569\n", - " 309796969\n", - " util_visit_tour_duration_shift_effects_duration\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 3632346\n", + " 310220296\n", + " 23\n", + " 23\n", " 0\n", + " 189\n", " 0\n", + " False\n", + " 0.0\n", " 0\n", " 0\n", " ...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", "\n", - "

231570 rows × 192 columns

\n", + "

3632347 rows × 95 columns

\n", "" ], "text/plain": [ - " tour_id variable 0 \\\n", - "0 6812 duration 0.0 \n", - "1 6812 end 5.0 \n", - "2 6812 mode_choice_logsum 0.0 \n", - "3 6812 start 5.0 \n", - "4 6812 util_adjacent_window_exists_after_this_arrival... False \n", - "... ... ... ... \n", - "231565 309796969 util_subsequent_of_2_plus_tours_for_same_purpo... 0 \n", - "231566 309796969 util_subsequent_tour_must_start_after_previous... True \n", - "231567 309796969 util_university_student_arrive_after_22 False \n", - "231568 309796969 util_visit_tour_departure_shift_effects_start 0 \n", - "231569 309796969 util_visit_tour_duration_shift_effects_duration 0 \n", + " tour_id start end duration tdd mode_choice_logsum \\\n", + "0 1870 5 5 0 0 0 \n", + "1 1870 5 6 1 1 0 \n", + "2 1870 5 7 2 2 0 \n", + "3 1870 5 8 3 3 0 \n", + "4 1870 5 9 4 4 0 \n", + "... ... ... ... ... ... ... \n", + "3632342 310220296 21 22 1 185 0 \n", + "3632343 310220296 21 23 2 186 0 \n", + "3632344 310220296 22 22 0 187 0 \n", + "3632345 310220296 22 23 1 188 0 \n", + "3632346 310220296 23 23 0 189 0 \n", + "\n", + " util_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "3632342 False \n", + "3632343 False \n", + "3632344 False \n", + "3632345 False \n", + "3632346 False \n", "\n", - " 1 2 3 4 5 6 7 ... 180 181 \\\n", - "0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 ... 0.0 1.0 \n", - "1 6.0 7.0 8.0 9.0 10.0 11.0 12.0 ... 20.0 21.0 \n", - "2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 \n", - "3 5.0 5.0 5.0 5.0 5.0 5.0 5.0 ... 20.0 20.0 \n", - "4 False False False False False False False ... 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False False \n", - "231568 0 0 0 0 0 0 0 ... 0 0 \n", - "231569 0 0 0 0 0 0 0 ... 0 0 \n", + " util_free_flow_round_trip_auto_time_shift_effects_duration \\\n", + "0 0.0 \n", + "1 0.0 \n", + "2 0.0 \n", + "3 0.0 \n", + "4 0.0 \n", + "... ... \n", + "3632342 0.0 \n", + "3632343 0.0 \n", + "3632344 0.0 \n", + "3632345 0.0 \n", + "3632346 0.0 \n", "\n", - " 182 183 184 185 186 187 188 189 \n", - "0 2.0 3.0 0.0 1.0 2.0 0.0 1.0 0.0 \n", - "1 22.0 23.0 21.0 22.0 23.0 22.0 23.0 23.0 \n", - "2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n", - "3 20.0 20.0 21.0 21.0 21.0 22.0 22.0 23.0 \n", - "4 False False False False False False False False \n", - "... ... ... ... ... ... ... ... ... \n", - "231565 2 3 0 1 2 0 1 0 \n", - "231566 False False False False False False False False \n", - "231567 False False False False False False False False \n", - "231568 0 0 0 0 0 0 0 0 \n", - "231569 0 0 0 0 0 0 0 0 \n", + " util_shopping_tour_departure_shift_effects \\\n", + "0 0 \n", + "1 0 \n", + "2 0 \n", + "3 0 \n", + "4 0 \n", + "... ... \n", + "3632342 0 \n", + "3632343 0 \n", + "3632344 0 \n", + "3632345 0 \n", + "3632346 0 \n", "\n", - 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"req_data does not request avail_ca or avail_co but it is set and being provided\n" + "problem: chosen_but_not_available has (149 issues)\n" ] }, + { + "data": { + "text/plain": [ + "(,\n", + " ┣ chosen_but_not_available: altid n example rows\n", + " ┃ 0 2 1 26680\n", + " ┃ 1 7 1 15549\n", + " ┃ 2 8 1 2727\n", + " ┃ 3 12 1 18739\n", + " ┃ 4 20 5 9872, 15764, 22362\n", + " ┃ .. ... .. ...\n", + " ┃ 144 183 12 4208, 14096, 15246\n", + " ┃ 145 184 5 1829, 8653, 13517\n", + " ┃ 146 185 10 626, 5650, 9208\n", + " ┃ 147 186 9 4563, 8308, 8746\n", + " ┃ 148 187 7 8216, 13933, 19491\n", + " ┃ \n", + " ┃ [149 rows x 3 columns])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.doctor(repair_ch_av=\"-\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ { "data": { "text/html": [ - "

Iteration 079 [Optimization terminated successfully]

" + "

Iteration 121 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1220,7 +1473,7 @@ { "data": { "text/html": [ - "

Best LL = -9499.39971608494

" + "

Best LL = -103688.04725680027

" ], "text/plain": [ "" @@ -1251,70 +1504,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction\n", - " -0.127954\n", + " 0.126593\n", + " 0.126593\n", " -0.025700\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.127954\n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction\n", - " 0.093954\n", + " -0.610258\n", + " -0.610258\n", " -0.027340\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.093954\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction\n", - " 0.253749\n", + " 0.113506\n", + " 0.113506\n", " 0.008442\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.253749\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction\n", - " -0.198343\n", + " 0.386575\n", + " 0.386575\n", " -0.059300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.198343\n", " \n", " \n", " coef_adult_with_children_in_hh_arrive_19_21\n", - " 0.309424\n", + " 0.281164\n", + " 0.281164\n", " 0.336000\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.309424\n", " \n", " \n", " ...\n", @@ -1325,135 +1582,125 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", " coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect\n", - " -0.115107\n", + " -0.281272\n", + " -0.281272\n", " -0.173100\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.115107\n", " \n", " \n", " coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends\n", " -999.000000\n", " -999.000000\n", + " -999.000000\n", + " -999.0\n", + " -999.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " coef_university_student_arrive_after_22\n", - " -0.537299\n", + " 0.609651\n", + " 0.609651\n", " 0.546600\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.537299\n", " \n", " \n", " coef_visit_tour_departure_shift_effects\n", - " 0.169598\n", + " 0.080406\n", + " 0.080406\n", " 0.096880\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.169598\n", " \n", " \n", " coef_visit_tour_duration_shift_effects\n", - " 0.155783\n", + " 0.140532\n", + " 0.140532\n", " 0.163800\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.155783\n", " \n", " \n", "\n", - "

89 rows × 8 columns

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89 rows × 7 columns

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"[89 rows x 8 columns]" + "[89 rows x 7 columns]" ] }, "metadata": {}, "output_type": "display_data" }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jeffnewman/opt/anaconda3/envs/garage38/lib/python3.8/site-packages/scipy/optimize/optimize.py:282: RuntimeWarning: Values in x were outside bounds during a minimize step, clipping to bounds\n", - " warnings.warn(\"Values in x were outside bounds during a \"\n" - ] - }, { "data": { "text/html": [ @@ -1467,31 +1714,31 @@ " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction\n", - " -0.127954\n", + " 0.126593\n", " \n", " \n", " coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction\n", - " 0.093954\n", + " -0.610258\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction\n", - " 0.253749\n", + " 0.113506\n", " \n", " \n", " coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction\n", - " -0.198343\n", + " 0.386575\n", " \n", " \n", " coef_adult_with_children_in_hh_arrive_19_21\n", - " 0.309424\n", + " 0.281164\n", " \n", " \n", " coef_arrival_constants_am_peak\n", - " 0.423382\n", + " -1.621626\n", " \n", " \n", " coef_arrival_constants_early\n", - " 2.912542\n", + " 0.006167\n", " \n", " \n", " coef_arrival_constants_evening\n", @@ -1499,67 +1746,67 @@ " \n", " \n", " coef_arrival_constants_late\n", - " -1.191037\n", + " -0.817500\n", " \n", " \n", " coef_arrival_constants_midday_1\n", - " 1.483808\n", + " 0.050461\n", " \n", " \n", " coef_arrival_constants_midday_2\n", - " 1.574014\n", + " 0.512472\n", " \n", " \n", " coef_arrival_constants_pm_peak_1\n", - " 1.409632\n", + " 0.637774\n", " \n", " \n", " coef_arrival_constants_pm_peak_2\n", - " 1.601585\n", + " 0.623529\n", " \n", " \n", " coef_arrival_constants_pm_peak_3\n", - " 1.110412\n", + " 0.299165\n", " \n", " \n", " coef_arrival_constants_pm_peak_4\n", - " 0.718971\n", + " 0.085991\n", " \n", " \n", " coef_departure_constants_am_peak_1\n", - " -0.462981\n", + " -0.564262\n", " \n", " \n", " coef_departure_constants_am_peak_2\n", - " 1.259376\n", + " 0.617882\n", " \n", " \n", " coef_departure_constants_am_peak_3\n", - " 1.496731\n", + " 1.077085\n", " \n", " \n", " coef_departure_constants_am_peak_4\n", - " 1.574361\n", + " 0.967759\n", " \n", " \n", " coef_departure_constants_early\n", - " -1.029511\n", + " -1.393229\n", " \n", " \n", " coef_departure_constants_evening\n", - " -1.905774\n", + " -1.688698\n", " \n", " \n", " coef_departure_constants_late\n", - " -5.863097\n", + " -4.308508\n", " \n", " \n", " coef_departure_constants_midday_1\n", - " 1.406032\n", + " 0.803175\n", " \n", " \n", " coef_departure_constants_midday_2\n", - " 0.672976\n", + " 0.328097\n", " \n", " \n", " coef_departure_constants_pm_peak\n", @@ -1567,11 +1814,11 @@ " \n", " \n", " coef_destination_in_cbd_duration_shift_effects\n", - " 0.116120\n", + " 0.110221\n", " \n", " \n", " coef_discretionary_tour_duration_lt_2_hours\n", - " -0.263935\n", + " -0.712606\n", " \n", " \n", " coef_duration_constants_0_to_1_hours\n", @@ -1579,31 +1826,31 @@ " \n", " \n", " coef_duration_constants_11_to_13_hours\n", - " -0.877324\n", + " -1.002178\n", " \n", " \n", " coef_duration_constants_14_to_18_hours\n", - " -2.821298\n", + " -1.203201\n", " \n", " \n", " coef_duration_constants_2_to_3_hours\n", - " 0.435394\n", + " -0.064944\n", " \n", " \n", " coef_duration_constants_4_to_5_hours\n", - " -0.223601\n", + " -0.717940\n", " \n", " \n", " coef_duration_constants_6_to_7_hours\n", - " -0.584059\n", + " -1.110132\n", " \n", " \n", " coef_duration_constants_8_to_10_hours\n", - " -0.527906\n", + " -0.954018\n", " \n", " \n", " coef_eat_out_tour_departure_shift_effects\n", - " 0.105657\n", + " 0.065095\n", " \n", " \n", " coef_escort_tour_arrival_constants_am_peak\n", @@ -1615,11 +1862,11 @@ " \n", " \n", " coef_escort_tour_arrival_constants_evening\n", - " -0.878853\n", + " -0.305413\n", " \n", " \n", " coef_escort_tour_arrival_constants_late\n", - " -1.254415\n", + " -0.704974\n", " \n", " \n", " coef_escort_tour_arrival_constants_midday_1\n", @@ -1647,35 +1894,35 @@ " \n", " \n", " coef_escort_tour_departure_constants_am_peak_1\n", - " 0.704309\n", + " -0.874537\n", " \n", " \n", " coef_escort_tour_departure_constants_am_peak_2\n", - " 2.276345\n", + " 1.002187\n", " \n", " \n", " coef_escort_tour_departure_constants_am_peak_3\n", - " 2.300896\n", + " 1.431663\n", " \n", " \n", " coef_escort_tour_departure_constants_am_peak_4\n", - " 0.493137\n", + " -0.076284\n", " \n", " \n", " coef_escort_tour_departure_constants_early\n", - " -0.493910\n", + " -1.237400\n", " \n", " \n", " coef_escort_tour_departure_constants_evening\n", - " -4.802269\n", + " -3.664017\n", " \n", " \n", " coef_escort_tour_departure_constants_late\n", - " -6.857486\n", + " -7.398170\n", " \n", " \n", " coef_escort_tour_departure_constants_midday_1\n", - " 0.746447\n", + " 0.185749\n", " \n", " \n", " coef_escort_tour_departure_constants_midday_2\n", @@ -1683,7 +1930,7 @@ " \n", " \n", " coef_escort_tour_departure_constants_pm_peak\n", - " -1.823360\n", + " -1.171787\n", " \n", " \n", " coef_escort_tour_duration_constants_0_to_1_hours\n", @@ -1691,138 +1938,138 @@ " \n", " \n", " coef_escort_tour_duration_constants_11_to_13_hours\n", - " -6.393148\n", + " -2.821199\n", " \n", " \n", " coef_escort_tour_duration_constants_14_to_18_hours\n", - " -9.419793\n", + " -2.493843\n", " \n", " \n", " coef_escort_tour_duration_constants_2_to_3_hours\n", - " -2.595592\n", + " -2.026673\n", " \n", " \n", " coef_escort_tour_duration_constants_4_to_5_hours\n", - " -3.522889\n", + " -2.941739\n", " \n", " \n", " coef_escort_tour_duration_constants_6_to_7_hours\n", - " -3.979277\n", + " -3.103903\n", " \n", " \n", " coef_escort_tour_duration_constants_8_to_10_hours\n", - " -5.158316\n", + " -3.097454\n", " \n", " \n", " coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect\n", - " -0.285201\n", + " -0.272458\n", " \n", " \n", " coef_free_flow_round_trip_auto_time_shift_effects_duration\n", - " 0.004992\n", + " 0.004326\n", " \n", " \n", " coef_maintenance_tour_depart_before_7\n", - " 0.041997\n", + " -0.819334\n", " \n", " \n", " coef_maintenance_tour_departure_shift_effects\n", - " -0.036636\n", + " -0.140265\n", " \n", " \n", " coef_maintenance_tour_duration_shift_effects\n", - " -0.115944\n", + " -0.068132\n", " \n", " \n", " coef_number_of_escort_tours_departure_shift_effects\n", - " 0.115214\n", + " 0.055565\n", " \n", " \n", " coef_number_of_individual_non_mandatory_tours_excluding_escort_departure_shift_effects\n", - " 0.104375\n", + " 0.054223\n", " \n", " \n", " coef_number_of_joint_tours_departure_shift_effects\n", - " 0.121920\n", + " 0.029269\n", " \n", " \n", " coef_number_of_mandatory_tours_departure_shift_effects\n", - " 0.170817\n", + " 0.031273\n", " \n", " \n", " coef_ratio_of_individual_non_mandatory_tours_to_be_scheduled_to_number_of_unscheduled_hours\n", - " 5.643619\n", + " -13.624709\n", " \n", " \n", " coef_school_child_age_16_plus_departure_shift_effects\n", - " 0.000283\n", + " 0.086050\n", " \n", " \n", " coef_school_child_age_16_plus_duration_shift_effects\n", - " 0.306122\n", + " 0.250586\n", " \n", " \n", " coef_school_child_age_under_16_departure_shift_effects\n", - " 0.110796\n", + " 0.053201\n", " \n", " \n", " coef_school_child_age_under_16_duration_shift_effects\n", - " 0.338212\n", + " 0.312477\n", " \n", " \n", " coef_school_child_under_16_arrive_after_22\n", - " -0.402410\n", + " -1.096083\n", " \n", " \n", " coef_shopping_tour_arrive_after_22\n", - " -2.545226\n", + " -0.583411\n", " \n", " \n", " coef_shopping_tour_depart_before_8\n", - " -0.787100\n", + " -1.172034\n", " \n", " \n", " coef_shopping_tour_departure_shift_effects\n", - " 0.015067\n", + " -0.061028\n", " \n", " \n", " coef_shopping_tour_duration_lt_2_hours\n", - " 0.943420\n", + " 0.405721\n", " \n", " \n", " coef_shopping_tour_duration_shift_effects\n", - " -0.075331\n", + " -0.113223\n", " \n", " \n", " coef_some_previously_scheduled_tour_begins_in_this_arrival_hour\n", - " -0.054385\n", + " -0.260255\n", " \n", " \n", " coef_some_previously_scheduled_tour_ends_in_this_departure_hour\n", - " -0.345727\n", + " -0.317129\n", " \n", " \n", " coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect\n", - " -0.115107\n", + " -0.281272\n", " \n", " \n", " coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends\n", - " -25.000000\n", + " -999.000000\n", " \n", " \n", " coef_university_student_arrive_after_22\n", - " -0.537299\n", + " 0.609651\n", " \n", " \n", " coef_visit_tour_departure_shift_effects\n", - " 0.169598\n", + " 0.080406\n", " \n", " \n", " coef_visit_tour_duration_shift_effects\n", - " 0.155783\n", + " 0.140532\n", " \n", " \n", - "loglike-9499.39971608494d_loglike\n", + "
logloss3.8088398507438663d_logloss\n", " \n", " \n", " \n", @@ -1832,409 +2079,409 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - "
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction0.0001143.438973e-05
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction-0.0003853.037850e-05
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction0.000097-6.894273e-05
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction-0.0002052.343581e-05
coef_adult_with_children_in_hh_arrive_19_210.0002946.653629e-05
coef_arrival_constants_am_peak0.0000379.439405e-07
coef_arrival_constants_early0.000111-8.901383e-06
coef_arrival_constants_evening0.0000000.000000e+00
coef_arrival_constants_late0.000194-6.165299e-05
coef_arrival_constants_midday_1-0.001155-3.871814e-05
coef_arrival_constants_midday_2-0.0007143.424832e-05
coef_arrival_constants_pm_peak_1-0.0000882.789318e-05
coef_arrival_constants_pm_peak_2-0.0003175.620495e-05
coef_arrival_constants_pm_peak_3-0.0000917.993874e-05
coef_arrival_constants_pm_peak_40.0007294.315887e-05
coef_departure_constants_am_peak_10.000352-8.495800e-05
coef_departure_constants_am_peak_2-0.000454-1.392003e-05
coef_departure_constants_am_peak_30.0002356.548727e-06
coef_departure_constants_am_peak_4-0.0003863.101496e-05
coef_departure_constants_early-0.000155-4.598593e-05
coef_departure_constants_evening0.0008867.934172e-05
coef_departure_constants_late0.000080-3.695844e-05
coef_departure_constants_midday_1-0.000777-5.887180e-05
coef_departure_constants_midday_20.0000792.120332e-05
coef_departure_constants_pm_peak0.0000000.000000e+00
coef_destination_in_cbd_duration_shift_effects0.002269-5.090224e-04
coef_discretionary_tour_duration_lt_2_hours-0.0004347.164386e-05
coef_duration_constants_0_to_1_hours0.0000000.000000e+00
coef_duration_constants_11_to_13_hours-0.000100-7.457357e-05
coef_duration_constants_14_to_18_hours-0.000201-6.196472e-06
coef_duration_constants_2_to_3_hours0.0007523.359402e-06
coef_duration_constants_4_to_5_hours0.000035-1.152395e-04
coef_duration_constants_6_to_7_hours0.0002578.557322e-05
coef_duration_constants_8_to_10_hours0.0000551.199127e-04
coef_eat_out_tour_departure_shift_effects-0.0008649.487469e-05
coef_escort_tour_arrival_constants_am_peak0.0000000.000000e+00
coef_escort_tour_arrival_constants_early0.0000000.000000e+00
coef_escort_tour_arrival_constants_evening0.000050-2.421029e-06
coef_escort_tour_arrival_constants_late-0.000165-2.218474e-05
coef_escort_tour_arrival_constants_midday_10.0000000.000000e+00
coef_escort_tour_arrival_constants_midday_20.0000000.000000e+00
coef_escort_tour_arrival_constants_pm_peak_10.0000000.000000e+00
coef_escort_tour_arrival_constants_pm_peak_20.0000000.000000e+00
coef_escort_tour_arrival_constants_pm_peak_30.0000000.000000e+00
coef_escort_tour_arrival_constants_pm_peak_40.0000000.000000e+00
coef_escort_tour_departure_constants_am_peak_10.000085-4.267869e-05
coef_escort_tour_departure_constants_am_peak_2-0.0000066.901890e-05
coef_escort_tour_departure_constants_am_peak_30.0001894.201443e-05
coef_escort_tour_departure_constants_am_peak_4-0.0003224.405139e-05
coef_escort_tour_departure_constants_early-0.0001185.739071e-05
coef_escort_tour_departure_constants_evening0.000116-1.563838e-05
coef_escort_tour_departure_constants_late-0.0000661.808622e-04
coef_escort_tour_departure_constants_midday_10.000073-5.212731e-06
coef_escort_tour_departure_constants_midday_20.0000000.000000e+00
coef_escort_tour_departure_constants_pm_peak0.000128-3.144269e-05
coef_escort_tour_duration_constants_0_to_1_hours0.0000000.000000e+00
coef_escort_tour_duration_constants_11_to_13_hours0.0004584.885945e-05
coef_escort_tour_duration_constants_14_to_18_hours-0.000124-6.674129e-06
coef_escort_tour_duration_constants_2_to_3_hours-0.0002188.004432e-05
coef_escort_tour_duration_constants_4_to_5_hours0.0000737.200311e-06
coef_escort_tour_duration_constants_6_to_7_hours0.0000929.728923e-06
coef_escort_tour_duration_constants_8_to_10_hours0.0000133.329902e-06
coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect0.0083783.750465e-05
coef_free_flow_round_trip_auto_time_shift_effects_duration-0.0392021.926232e-04
coef_maintenance_tour_depart_before_70.000197-7.804297e-06
coef_maintenance_tour_departure_shift_effects-0.0042501.482773e-04
coef_maintenance_tour_duration_shift_effects0.0011253.493923e-04
coef_number_of_escort_tours_departure_shift_effects0.0076461.304873e-05
coef_number_of_individual_non_mandatory_tours_excluding_escort_departure_shift_effects0.015415-1.378737e-05
coef_number_of_joint_tours_departure_shift_effects0.000633-9.589696e-05
coef_number_of_mandatory_tours_departure_shift_effects0.003775-4.122044e-05
coef_ratio_of_individual_non_mandatory_tours_to_be_scheduled_to_number_of_unscheduled_hours0.0000442.048882e-05
coef_school_child_age_16_plus_departure_shift_effects-0.000324-1.242593e-05
coef_school_child_age_16_plus_duration_shift_effects0.000284-1.367621e-05
coef_school_child_age_under_16_departure_shift_effects0.000075-4.089013e-05
coef_school_child_age_under_16_duration_shift_effects0.001635-2.174936e-05
coef_school_child_under_16_arrive_after_22-0.0001867.030245e-07
coef_shopping_tour_arrive_after_22-0.0000441.001740e-06
coef_shopping_tour_depart_before_8-0.0003601.716270e-05
coef_shopping_tour_departure_shift_effects0.0175473.564338e-05
coef_shopping_tour_duration_lt_2_hours-0.000129-4.343344e-05
coef_shopping_tour_duration_shift_effects0.0037181.135557e-04
coef_some_previously_scheduled_tour_begins_in_this_arrival_hour-0.0000754.711918e-06
coef_some_previously_scheduled_tour_ends_in_this_departure_hour-0.000476-5.226511e-05
coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect0.0005837.117498e-05
coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends0.0000000.000000e+00
coef_university_student_arrive_after_22-0.000256-8.028019e-06
coef_visit_tour_departure_shift_effects-0.000785-8.601128e-05
coef_visit_tour_duration_shift_effects-0.001139-1.064345e-04
nit79nfev236njev79status0message'Optimization terminated successfully'successTrueelapsed_time0:00:18.828322method'slsqp'n_cases2490iteration_number79logloss3.8150199662991726" + "nit121nfev130njev121status0message'Optimization terminated successfully'successTrueelapsed_time0:01:35.575519method'slsqp'n_cases29669iteration_number121loglike-103688.04725680027" ], "text/plain": [ - "┣ x: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction -0.127954\n", - "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction 0.093954\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.253749\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction -0.198343\n", - "┃ coef_adult_with_children_in_hh_arrive_19_21 0.309424\n", - "┃ ... \n", - "┃ coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect -0.115107\n", - "┃ coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends -25.000000\n", - "┃ coef_university_student_arrive_after_22 -0.537299\n", - "┃ coef_visit_tour_departure_shift_effects 0.169598\n", - "┃ coef_visit_tour_duration_shift_effects 0.155783\n", + "┣ x: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.126593\n", + "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction -0.610258\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.113506\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction 0.386575\n", + "┃ coef_adult_with_children_in_hh_arrive_19_21 0.281164\n", + "┃ ... \n", + "┃ coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect -0.281272\n", + "┃ coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends -999.000000\n", + "┃ coef_university_student_arrive_after_22 0.609651\n", + "┃ coef_visit_tour_departure_shift_effects 0.080406\n", + "┃ coef_visit_tour_duration_shift_effects 0.140532\n", "┃ Length: 89, dtype: float64\n", - "┣ loglike: -9499.39971608494\n", - "┣ d_loglike: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.000114\n", - "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction -0.000385\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.000097\n", - "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction -0.000205\n", - "┃ coef_adult_with_children_in_hh_arrive_19_21 0.000294\n", + "┣ logloss: 3.8088398507438663\n", + "┣ d_logloss: coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.000034\n", + "┃ coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction 0.000030\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction -0.000069\n", + "┃ coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction 0.000023\n", + "┃ coef_adult_with_children_in_hh_arrive_19_21 0.000067\n", "┃ ... \n", - "┃ coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect 0.000583\n", + "┃ coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect 0.000071\n", "┃ coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends 0.000000\n", - "┃ coef_university_student_arrive_after_22 -0.000256\n", - "┃ coef_visit_tour_departure_shift_effects -0.000785\n", - "┃ coef_visit_tour_duration_shift_effects -0.001139\n", + "┃ coef_university_student_arrive_after_22 -0.000008\n", + "┃ coef_visit_tour_departure_shift_effects -0.000086\n", + "┃ coef_visit_tour_duration_shift_effects -0.000106\n", "┃ Length: 89, dtype: float64\n", - "┣ nit: 79\n", - "┣ nfev: 236\n", - "┣ njev: 79\n", + "┣ nit: 121\n", + "┣ nfev: 130\n", + "┣ njev: 121\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=18, microseconds=828322)\n", + "┣ elapsed_time: datetime.timedelta(seconds=95, microseconds=575519)\n", "┣ method: 'slsqp'\n", - "┣ n_cases: 2490\n", - "┣ iteration_number: 79\n", - "┣ logloss: 3.8150199662991726" + "┣ n_cases: 29669\n", + "┣ iteration_number: 121\n", + "┣ loglike: -103688.04725680027" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.estimate()" + "model.estimate(maxiter=900)" ] }, { @@ -2246,830 +2493,856 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Null Value Constrained
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction-0.128 0.141-0.91 0.00
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction 0.0940 0.137 0.69 0.00
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.254 0.148 1.72 0.00
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction-0.198 0.140-1.42 0.00
coef_adult_with_children_in_hh_arrive_19_21 0.309 0.136 2.27* 0.00
coef_arrival_constants_am_peak 0.423 0.303 1.40 0.00
coef_arrival_constants_early 2.91 0.429 6.78*** 0.00
coef_arrival_constants_evening 0.00 NA NA 0.00fixed value
coef_arrival_constants_late-1.19 0.133-8.96*** 0.00
coef_arrival_constants_midday_1 1.48 0.220 6.75*** 0.00
coef_arrival_constants_midday_2 1.57 0.174 9.05*** 0.00
coef_arrival_constants_pm_peak_1 1.41 0.160 8.80*** 0.00
coef_arrival_constants_pm_peak_2 1.60 0.132 12.14*** 0.00
coef_arrival_constants_pm_peak_3 1.11 0.118 9.40*** 0.00
coef_arrival_constants_pm_peak_4 0.719 0.108 6.69*** 0.00
coef_departure_constants_am_peak_1-0.463 0.384-1.21 0.00
coef_departure_constants_am_peak_2 1.26 0.276 4.56*** 0.00
coef_departure_constants_am_peak_3 1.50 0.246 6.10*** 0.00
coef_departure_constants_am_peak_4 1.57 0.223 7.06*** 0.00
coef_departure_constants_early-1.03 0.420-2.45* 0.00
coef_departure_constants_evening-1.91 0.136-14.03*** 0.00
coef_departure_constants_late-5.86 0.728-8.05*** 0.00
coef_departure_constants_midday_1 1.41 0.171 8.23*** 0.00
coef_departure_constants_midday_2 0.673 0.113 5.98*** 0.00
coef_departure_constants_pm_peak 0.00 NA NA 0.00fixed value
coef_destination_in_cbd_duration_shift_effects 0.116 0.0186 6.26*** 0.00
coef_discretionary_tour_duration_lt_2_hours-0.264 0.136-1.93 0.00
coef_duration_constants_0_to_1_hours 0.00 NA NA 0.00fixed value
coef_duration_constants_11_to_13_hours-0.877 0.352-2.49* 0.00
coef_duration_constants_14_to_18_hours-2.82 0.771-3.66*** 0.00
coef_duration_constants_2_to_3_hours 0.435 0.0972 4.48*** 0.00
coef_duration_constants_4_to_5_hours-0.224 0.139-1.60 0.00
coef_duration_constants_6_to_7_hours-0.584 0.192-3.04** 0.00
coef_duration_constants_8_to_10_hours-0.528 0.249-2.12* 0.00
coef_eat_out_tour_departure_shift_effects 0.106 0.0224 4.71*** 0.00
coef_escort_tour_arrival_constants_am_peak 0.00 NA NA 0.00fixed value
coef_escort_tour_arrival_constants_early 0.00 NA NA 0.00fixed value
coef_escort_tour_arrival_constants_evening-0.879 0.304-2.89** 0.00
coef_escort_tour_arrival_constants_late-1.25 0.579-2.17* 0.00
coef_escort_tour_arrival_constants_midday_1 0.00 NA NA 0.00fixed value
coef_escort_tour_arrival_constants_midday_2 0.00 NA NA 0.00fixed value
coef_escort_tour_arrival_constants_pm_peak_1 0.00 NA NA 0.00fixed value
coef_escort_tour_arrival_constants_pm_peak_2 0.00 NA NA 0.00fixed value
coef_escort_tour_arrival_constants_pm_peak_3 0.00 NA NA 0.00fixed value
coef_escort_tour_arrival_constants_pm_peak_4 0.00 NA NA 0.00fixed value
coef_escort_tour_departure_constants_am_peak_1 0.704 0.317 2.22* 0.00
coef_escort_tour_departure_constants_am_peak_2 2.28 0.192 11.84*** 0.00
coef_escort_tour_departure_constants_am_peak_3 2.30 0.187 12.28*** 0.00
coef_escort_tour_departure_constants_am_peak_4 0.493 0.316 1.56 0.00
coef_escort_tour_departure_constants_early-0.494 0.566-0.87 0.00
coef_escort_tour_departure_constants_evening-4.80 0.503-9.55*** 0.00
coef_escort_tour_departure_constants_late-6.86 1.10-6.23*** 0.00
coef_escort_tour_departure_constants_midday_1 0.746 0.165 4.53*** 0.00
coef_escort_tour_departure_constants_midday_2 0.00 NA NA 0.00fixed value
coef_escort_tour_departure_constants_pm_peak-1.82 0.210-8.67*** 0.00
coef_escort_tour_duration_constants_0_to_1_hours 0.00 NA NA 0.00fixed value
coef_escort_tour_duration_constants_11_to_13_hours-6.39 0.808-7.92*** 0.00
coef_escort_tour_duration_constants_14_to_18_hours-9.42 1.63-5.78*** 0.00
coef_escort_tour_duration_constants_2_to_3_hours-2.60 0.212-12.27*** 0.00
coef_escort_tour_duration_constants_4_to_5_hours-3.52 0.319-11.05*** 0.00
coef_escort_tour_duration_constants_6_to_7_hours-3.98 0.379-10.49*** 0.00
coef_escort_tour_duration_constants_8_to_10_hours-5.16 0.492-10.47*** 0.00
coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect-0.285 0.0225-12.67*** 0.00
coef_free_flow_round_trip_auto_time_shift_effects_duration 0.00499 0.000948 5.27*** 0.00
coef_maintenance_tour_depart_before_7 0.0420 0.359 0.12 0.00
coef_maintenance_tour_departure_shift_effects-0.0366 0.0193-1.90 0.00
coef_maintenance_tour_duration_shift_effects-0.116 0.0298-3.89*** 0.00
coef_number_of_escort_tours_departure_shift_effects 0.115 0.00964 11.95*** 0.00
coef_number_of_individual_non_mandatory_tours_excluding_escort_departure_shift_effects 0.104 0.00667 15.64*** 0.00
coef_number_of_joint_tours_departure_shift_effects 0.122 0.0296 4.12*** 0.00
coef_number_of_mandatory_tours_departure_shift_effects 0.171 0.0125 13.63*** 0.00
coef_ratio_of_individual_non_mandatory_tours_to_be_scheduled_to_number_of_unscheduled_hours 5.64 0.804 7.02*** 0.00
coef_school_child_age_16_plus_departure_shift_effects 0.000283 0.112 0.00 0.00
coef_school_child_age_16_plus_duration_shift_effects 0.306 0.0952 3.22** 0.00
coef_school_child_age_under_16_departure_shift_effects 0.111 0.0367 3.02** 0.00
coef_school_child_age_under_16_duration_shift_effects 0.338 0.0418 8.10*** 0.00
coef_school_child_under_16_arrive_after_22-0.402 0.480-0.84 0.00
coef_shopping_tour_arrive_after_22-2.55 1.01-2.52* 0.00
coef_shopping_tour_depart_before_8-0.787 0.254-3.10** 0.00
coef_shopping_tour_departure_shift_effects 0.0151 0.0182 0.83 0.00
coef_shopping_tour_duration_lt_2_hours 0.943 0.144 6.55*** 0.00
coef_shopping_tour_duration_shift_effects-0.0753 0.0296-2.55* 0.00
coef_some_previously_scheduled_tour_begins_in_this_arrival_hour-0.0544 0.0946-0.58 0.00
coef_some_previously_scheduled_tour_ends_in_this_departure_hour-0.346 0.0763-4.53*** 0.00
coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect-0.115 0.0570-2.02* 0.00
coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends-999. NA NA 0.00fixed value
coef_university_student_arrive_after_22-0.537 0.853-0.63 0.00
coef_visit_tour_departure_shift_effects 0.170 0.0312 5.44*** 0.00
coef_visit_tour_duration_shift_effects 0.156 0.0369 4.22*** 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_adjacent_window_exists_after_this_arrival_hour_first_tour_interaction 0.127 0.0994 1.27 0.00
coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction-0.610 0.0968-6.30*** 0.00
coef_adjacent_window_exists_before_this_departure_hour_first_tour_interaction 0.114 0.0850 1.34 0.00
coef_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interaction 0.387 0.0868 4.45*** 0.00
coef_adult_with_children_in_hh_arrive_19_21 0.281 0.0376 7.47*** 0.00
coef_arrival_constants_am_peak-1.62 0.104-15.66*** 0.00
coef_arrival_constants_early 0.00617 0.146 0.04 0.00
coef_arrival_constants_evening 0.00 0.00 NA 0.00fixed value
coef_arrival_constants_late-0.817 0.0418-19.58*** 0.00
coef_arrival_constants_midday_1 0.0505 0.0730 0.69 0.00
coef_arrival_constants_midday_2 0.512 0.0562 9.12*** 0.00
coef_arrival_constants_pm_peak_1 0.638 0.0500 12.74*** 0.00
coef_arrival_constants_pm_peak_2 0.624 0.0421 14.82*** 0.00
coef_arrival_constants_pm_peak_3 0.299 0.0377 7.95*** 0.00
coef_arrival_constants_pm_peak_4 0.0860 0.0339 2.53* 0.00
coef_departure_constants_am_peak_1-0.564 0.115-4.91*** 0.00
coef_departure_constants_am_peak_2 0.618 0.0862 7.17*** 0.00
coef_departure_constants_am_peak_3 1.08 0.0750 14.36*** 0.00
coef_departure_constants_am_peak_4 0.968 0.0684 14.16*** 0.00
coef_departure_constants_early-1.39 0.133-10.46*** 0.00
coef_departure_constants_evening-1.69 0.0406-41.61*** 0.00
coef_departure_constants_late-4.31 0.172-25.06*** 0.00
coef_departure_constants_midday_1 0.803 0.0524 15.33*** 0.00
coef_departure_constants_midday_2 0.328 0.0342 9.58*** 0.00
coef_departure_constants_pm_peak 0.00 0.00 NA 0.00fixed value
coef_destination_in_cbd_duration_shift_effects 0.110 0.00846 13.02*** 0.00
coef_discretionary_tour_duration_lt_2_hours-0.713 0.0444-16.04*** 0.00
coef_duration_constants_0_to_1_hours 0.00 0.00 NA 0.00fixed value
coef_duration_constants_11_to_13_hours-1.00 0.115-8.70*** 0.00
coef_duration_constants_14_to_18_hours-1.20 0.192-6.28*** 0.00
coef_duration_constants_2_to_3_hours-0.0649 0.0325-2.00* 0.00
coef_duration_constants_4_to_5_hours-0.718 0.0457-15.71*** 0.00
coef_duration_constants_6_to_7_hours-1.11 0.0630-17.62*** 0.00
coef_duration_constants_8_to_10_hours-0.954 0.0817-11.68*** 0.00
coef_eat_out_tour_departure_shift_effects 0.0651 0.00756 8.61*** 0.00
coef_escort_tour_arrival_constants_am_peak 0.00 0.00 NA 0.00fixed value
coef_escort_tour_arrival_constants_early 0.00 0.00 NA 0.00fixed value
coef_escort_tour_arrival_constants_evening-0.305 0.0678-4.51*** 0.00
coef_escort_tour_arrival_constants_late-0.705 0.132-5.34*** 0.00
coef_escort_tour_arrival_constants_midday_1 0.00 0.00 NA 0.00fixed value
coef_escort_tour_arrival_constants_midday_2 0.00 0.00 NA 0.00fixed value
coef_escort_tour_arrival_constants_pm_peak_1 0.00 0.00 NA 0.00fixed value
coef_escort_tour_arrival_constants_pm_peak_2 0.00 0.00 NA 0.00fixed value
coef_escort_tour_arrival_constants_pm_peak_3 0.00 0.00 NA 0.00fixed value
coef_escort_tour_arrival_constants_pm_peak_4 0.00 0.00 NA 0.00fixed value
coef_escort_tour_departure_constants_am_peak_1-0.875 0.0968-9.04*** 0.00
coef_escort_tour_departure_constants_am_peak_2 1.00 0.0627 15.99*** 0.00
coef_escort_tour_departure_constants_am_peak_3 1.43 0.0560 25.58*** 0.00
coef_escort_tour_departure_constants_am_peak_4-0.0763 0.0774-0.99 0.00
coef_escort_tour_departure_constants_early-1.24 0.114-10.89*** 0.00
coef_escort_tour_departure_constants_evening-3.66 0.115-31.78*** 0.00
coef_escort_tour_departure_constants_late-7.40 0.594-12.45*** 0.00
coef_escort_tour_departure_constants_midday_1 0.186 0.0464 4.00*** 0.00
coef_escort_tour_departure_constants_midday_2 0.00 0.00 NA 0.00fixed value
coef_escort_tour_departure_constants_pm_peak-1.17 0.0525-22.33*** 0.00
coef_escort_tour_duration_constants_0_to_1_hours 0.00 0.00 NA 0.00fixed value
coef_escort_tour_duration_constants_11_to_13_hours-2.82 0.160-17.67*** 0.00
coef_escort_tour_duration_constants_14_to_18_hours-2.49 0.263-9.48*** 0.00
coef_escort_tour_duration_constants_2_to_3_hours-2.03 0.0487-41.65*** 0.00
coef_escort_tour_duration_constants_4_to_5_hours-2.94 0.0862-34.13*** 0.00
coef_escort_tour_duration_constants_6_to_7_hours-3.10 0.108-28.63*** 0.00
coef_escort_tour_duration_constants_8_to_10_hours-3.10 0.116-26.68*** 0.00
coef_first_of_2_plus_tours_for_same_purpose_departure_shift_effect-0.272 0.00757-36.01*** 0.00
coef_free_flow_round_trip_auto_time_shift_effects_duration 0.00433 0.000116 37.30*** 0.00
coef_maintenance_tour_depart_before_7-0.819 0.121-6.78*** 0.00
coef_maintenance_tour_departure_shift_effects-0.140 0.00739-18.98*** 0.00
coef_maintenance_tour_duration_shift_effects-0.0681 0.00931-7.32*** 0.00
coef_number_of_escort_tours_departure_shift_effects 0.0556 0.00378 14.70*** 0.00
coef_number_of_individual_non_mandatory_tours_excluding_escort_departure_shift_effects 0.0542 0.00268 20.25*** 0.00
coef_number_of_joint_tours_departure_shift_effects 0.0293 0.00871 3.36*** 0.00
coef_number_of_mandatory_tours_departure_shift_effects 0.0313 0.00474 6.60*** 0.00
coef_ratio_of_individual_non_mandatory_tours_to_be_scheduled_to_number_of_unscheduled_hours-13.6 0.746-18.26*** 0.00
coef_school_child_age_16_plus_departure_shift_effects 0.0860 0.0191 4.51*** 0.00
coef_school_child_age_16_plus_duration_shift_effects 0.251 0.0205 12.25*** 0.00
coef_school_child_age_under_16_departure_shift_effects 0.0532 0.00949 5.60*** 0.00
coef_school_child_age_under_16_duration_shift_effects 0.312 0.0106 29.41*** 0.00
coef_school_child_under_16_arrive_after_22-1.10 0.170-6.44*** 0.00
coef_shopping_tour_arrive_after_22-0.583 0.148-3.95*** 0.00
coef_shopping_tour_depart_before_8-1.17 0.0899-13.03*** 0.00
coef_shopping_tour_departure_shift_effects-0.0610 0.00644-9.48*** 0.00
coef_shopping_tour_duration_lt_2_hours 0.406 0.0459 8.83*** 0.00
coef_shopping_tour_duration_shift_effects-0.113 0.00985-11.49*** 0.00
coef_some_previously_scheduled_tour_begins_in_this_arrival_hour-0.260 0.0337-7.71*** 0.00
coef_some_previously_scheduled_tour_ends_in_this_departure_hour-0.317 0.0252-12.58*** 0.00
coef_subsequent_of_2_plus_tours_for_same_purpose_duration_shift_effect-0.281 0.0193-14.55*** 0.00
coef_subsequent_tour_must_start_after_previous_tour_for_this_purpose_ends-999. 0.00 NA 0.00fixed value
coef_university_student_arrive_after_22 0.610 0.171 3.57*** 0.00
coef_visit_tour_departure_shift_effects 0.0804 0.00979 8.21*** 0.00
coef_visit_tour_duration_shift_effects 0.141 0.0115 12.20*** 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -3090,7 +3363,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -3111,20 +3384,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -3143,7 +3405,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -3188,19 +3450,19 @@ " \n", " 2\n", " coef_free_flow_round_trip_auto_time_shift_effe...\n", - " 0.004992\n", + " 0.004326\n", " F\n", " \n", " \n", " 3\n", " coef_shopping_tour_departure_shift_effects\n", - " 0.015067\n", + " -0.061028\n", " F\n", " \n", " \n", " 4\n", " coef_shopping_tour_duration_shift_effects\n", - " -0.075331\n", + " -0.113223\n", " F\n", " \n", " \n", @@ -3212,31 +3474,31 @@ " \n", " 85\n", " coef_escort_tour_duration_constants_4_to_5_hours\n", - " -3.522889\n", + " -2.941739\n", " F\n", " \n", " \n", " 86\n", " coef_escort_tour_duration_constants_6_to_7_hours\n", - " -3.979277\n", + " -3.103903\n", " F\n", " \n", " \n", " 87\n", " coef_escort_tour_duration_constants_8_to_10_hours\n", - " -5.158316\n", + " -3.097454\n", " F\n", " \n", " \n", " 88\n", " coef_escort_tour_duration_constants_11_to_13_h...\n", - " -6.393148\n", + " -2.821199\n", " F\n", " \n", " \n", " 89\n", " coef_escort_tour_duration_constants_14_to_18_h...\n", - " -9.419793\n", + " -2.493843\n", " F\n", " \n", " \n", @@ -3248,20 +3510,20 @@ " coefficient_name value constrain\n", "0 coef_dummy 1.000000 T\n", "1 coef_subsequent_tour_must_start_after_previous... -999.000000 T\n", - "2 coef_free_flow_round_trip_auto_time_shift_effe... 0.004992 F\n", - "3 coef_shopping_tour_departure_shift_effects 0.015067 F\n", - "4 coef_shopping_tour_duration_shift_effects -0.075331 F\n", + "2 coef_free_flow_round_trip_auto_time_shift_effe... 0.004326 F\n", + "3 coef_shopping_tour_departure_shift_effects -0.061028 F\n", + "4 coef_shopping_tour_duration_shift_effects -0.113223 F\n", ".. ... ... ...\n", - "85 coef_escort_tour_duration_constants_4_to_5_hours -3.522889 F\n", - "86 coef_escort_tour_duration_constants_6_to_7_hours -3.979277 F\n", - "87 coef_escort_tour_duration_constants_8_to_10_hours -5.158316 F\n", - "88 coef_escort_tour_duration_constants_11_to_13_h... -6.393148 F\n", - "89 coef_escort_tour_duration_constants_14_to_18_h... -9.419793 F\n", + "85 coef_escort_tour_duration_constants_4_to_5_hours -2.941739 F\n", + "86 coef_escort_tour_duration_constants_6_to_7_hours -3.103903 F\n", + "87 coef_escort_tour_duration_constants_8_to_10_hours -3.097454 F\n", + "88 coef_escort_tour_duration_constants_11_to_13_h... -2.821199 F\n", + "89 coef_escort_tour_duration_constants_14_to_18_h... -2.493843 F\n", "\n", "[90 rows x 3 columns]" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -3278,7 +3540,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -3292,7 +3554,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb b/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb index e502d50ff8..766538fa48 100644 --- a/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb +++ b/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +115,28 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_coefficients_template.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_values_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"tour_mode_choice\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -88,9 +151,24 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_mode_choice/tour_mode_choice_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_mode_choice/atwork_subtour_mode_choice_coefficients_template.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/atwork_subtour_mode_choice/atwork_subtour_mode_choice_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_mode_choice/atwork_subtour_mode_choice_values_combined.parquet\n" + ] + } + ], "source": [ - "model2, data2 = component_model(\"atwork_subtour_mode_choice\", return_data=True)" + "model2, data2 = component_model(\n", + " \"atwork_subtour_mode_choice\", \n", + " edb_directory=\"output-est-mode/estimation_data_bundle/atwork_subtour_mode_choice\",\n", + " return_data=True,\n", + " )" ] }, { @@ -715,6 +793,7 @@ " util_DRIVEALONEFREE_Terminal_time\n", " util_DRIVEALONEFREE_Operating_cost\n", " ...\n", + " walk_lrf_available\n", " walk_ferry_available\n", " drive_local_available\n", " drive_commuter_available\n", @@ -723,7 +802,6 @@ " drive_lrf_available\n", " drive_ferry_available\n", " destination_in_cbd\n", - " tour_id.1\n", " override_choice_code\n", " \n", " \n", @@ -753,91 +831,92 @@ " \n", " \n", " \n", - " 6812\n", - " WALK\n", - " WALK\n", + " 1870\n", + " SHARED3FREE\n", + " SHARED3FREE\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 5.480000\n", - " 15.45016\n", - " 2.156258\n", + " 0.0\n", + " 20.830002\n", + " 21.26572\n", + " 6.293324\n", " ...\n", " False\n", " False\n", + " True\n", + " True\n", " False\n", - " False\n", - " False\n", + " True\n", " False\n", " False\n", " 1\n", - " 6812\n", - " 7\n", + " 5\n", " \n", " \n", - " 8110\n", - " WALK\n", - " WALK\n", + " 20468\n", + " SHARED3FREE\n", + " TNC_SINGLE\n", + " 0.0\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 8.860000\n", - " 34.19784\n", - " 17.722496\n", + " 9.440000\n", + " 13.24624\n", + " 14.917349\n", " ...\n", " False\n", " False\n", + " True\n", + " True\n", " False\n", - " False\n", - " False\n", + " True\n", " False\n", " False\n", " 0\n", - " 8110\n", - " 7\n", + " 20\n", " \n", " \n", - " 11013\n", - " DRIVEALONEFREE\n", - " DRIVEALONEFREE\n", + " 27055\n", + " SHARED3FREE\n", + " SHARED3FREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 20.689999\n", - " 18.17320\n", - " 15.097005\n", + " 13.160000\n", + " 8.53068\n", + " 25.088453\n", " ...\n", " False\n", + " False\n", " True\n", " True\n", " False\n", " True\n", " False\n", " False\n", - " 1\n", - " 11013\n", - " 1\n", + " 0\n", + " 5\n", " \n", " \n", - " 11016\n", - " DRIVEALONEFREE\n", - " DRIVEALONEFREE\n", + " 38877\n", + " SHARED2FREE\n", + " SHARED3FREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 14.710000\n", - " 12.85052\n", - " 10.971117\n", + " 6.730000\n", + " 11.04132\n", + " 11.040045\n", " ...\n", " False\n", + " False\n", " True\n", " True\n", " False\n", @@ -845,32 +924,31 @@ " False\n", " False\n", " 0\n", - " 11016\n", - " 1\n", + " 5\n", " \n", " \n", - " 15403\n", - " DRIVEALONEFREE\n", - " DRIVEALONEFREE\n", + " 38904\n", + " SHARED2FREE\n", + " SHARED2FREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 15.160000\n", - " 10.64808\n", - " 26.092745\n", + " 22.410000\n", + " 17.29320\n", + " 46.920191\n", " ...\n", + " True\n", " False\n", " True\n", " True\n", " False\n", " True\n", - " False\n", + " True\n", " False\n", " 0\n", - " 15403\n", - " 1\n", + " 3\n", " \n", " \n", " ...\n", @@ -897,7 +975,7 @@ " ...\n", " \n", " \n", - " 309760814\n", + " 310197956\n", " DRIVEALONEFREE\n", " DRIVEALONEFREE\n", " 0.0\n", @@ -905,95 +983,95 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 24.510000\n", - " 11.41364\n", - " 27.217999\n", + " 29.900002\n", + " 4.21092\n", + " 69.245528\n", " ...\n", " False\n", - " True\n", - " True\n", " False\n", - " True\n", + " False\n", + " False\n", + " False\n", + " False\n", " False\n", " False\n", " 0\n", - " 309760814\n", " 1\n", " \n", " \n", - " 309760815\n", - " SHARED2FREE\n", - " SHARED2FREE\n", + " 310202376\n", + " DRIVEALONEFREE\n", + " BIKE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 19.349998\n", - " 16.96372\n", - " 14.591494\n", + " 5.480000\n", + " 3.82392\n", + " 19.277738\n", " ...\n", " False\n", - " True\n", - " True\n", " False\n", - " True\n", " False\n", " False\n", - " 1\n", - " 309760815\n", - " 3\n", + " False\n", + " False\n", + " False\n", + " False\n", + " 0\n", + " 8\n", " \n", " \n", - " 309790009\n", - " BIKE\n", - " BIKE\n", + " 310202384\n", + " DRIVEALONEFREE\n", + " DRIVEALONEFREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 21.410000\n", - " 19.44384\n", - " 84.280323\n", + " 5.480000\n", + " 3.82392\n", + " 19.277738\n", " ...\n", " False\n", - " True\n", - " True\n", " False\n", - " True\n", " False\n", " False\n", + " False\n", + " False\n", + " False\n", + " False\n", + " 0\n", " 1\n", - " 309790009\n", - " 8\n", " \n", " \n", - " 309796968\n", - " SHARED3FREE\n", - " SHARED3FREE\n", + " 310212634\n", + " DRIVEALONEFREE\n", + " DRIVEALONEFREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 17.340000\n", - " 13.66872\n", - " 30.549632\n", + " 12.840000\n", + " 5.32256\n", + " 5.457677\n", " ...\n", " False\n", + " False\n", + " False\n", " True\n", " True\n", " False\n", - " True\n", " False\n", " False\n", " 0\n", - " 309796968\n", - " 5\n", + " 1\n", " \n", " \n", - " 309796969\n", + " 310220296\n", " DRIVEALONEFREE\n", " DRIVEALONEFREE\n", " 0.0\n", @@ -1001,196 +1079,196 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 8.000000\n", - " 10.00692\n", - " 18.758547\n", + " 13.590000\n", + " 8.05768\n", + " 15.684208\n", " ...\n", " False\n", - " True\n", - " True\n", + " False\n", + " False\n", " False\n", " True\n", " False\n", " False\n", + " False\n", " 0\n", - " 309796969\n", " 1\n", " \n", " \n", "\n", - "

5314 rows × 535 columns

\n", + "

63935 rows × 536 columns

\n", "" ], "text/plain": [ " model_choice override_choice util_DRIVEALONEFREE_Unavailable \\\n", "tour_id \n", - "6812 WALK WALK 0.0 \n", - "8110 WALK WALK 0.0 \n", - "11013 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", - "11016 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", - "15403 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", + "1870 SHARED3FREE SHARED3FREE 0.0 \n", + "20468 SHARED3FREE TNC_SINGLE 0.0 \n", + "27055 SHARED3FREE SHARED3FREE 0.0 \n", + "38877 SHARED2FREE SHARED3FREE 0.0 \n", + "38904 SHARED2FREE SHARED2FREE 0.0 \n", "... ... ... ... \n", - "309760814 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", - "309760815 SHARED2FREE SHARED2FREE 0.0 \n", - "309790009 BIKE BIKE 0.0 \n", - "309796968 SHARED3FREE SHARED3FREE 0.0 \n", - "309796969 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", + "310197956 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", + "310202376 DRIVEALONEFREE BIKE 0.0 \n", + "310202384 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", + "310212634 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", + "310220296 DRIVEALONEFREE DRIVEALONEFREE 0.0 \n", "\n", " util_DRIVEALONEFREE_Unavailable_for_zero_auto_households \\\n", "tour_id \n", - "6812 1.0 \n", - "8110 1.0 \n", - "11013 0.0 \n", - "11016 0.0 \n", - "15403 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", + "38877 0.0 \n", + "38904 0.0 \n", "... ... \n", - "309760814 0.0 \n", - "309760815 0.0 \n", - "309790009 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", + "310197956 0.0 \n", + "310202376 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_Unavailable_for_persons_less_than_16 \\\n", "tour_id \n", - "6812 0.0 \n", - "8110 0.0 \n", - "11013 0.0 \n", - "11016 0.0 \n", - "15403 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", + "38877 0.0 \n", + "38904 0.0 \n", "... ... \n", - "309760814 0.0 \n", - "309760815 0.0 \n", - "309790009 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", + "310197956 0.0 \n", + "310202376 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_Unavailable_for_joint_tours \\\n", "tour_id \n", - "6812 0.0 \n", - "8110 0.0 \n", - "11013 0.0 \n", - "11016 0.0 \n", - "15403 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", + "38877 0.0 \n", + "38904 0.0 \n", "... ... \n", - "309760814 0.0 \n", - "309760815 0.0 \n", - "309790009 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", + "310197956 0.0 \n", + "310202376 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_Unavailable_if_didnt_drive_to_work \\\n", "tour_id \n", - "6812 0.0 \n", - "8110 0.0 \n", - "11013 0.0 \n", - "11016 0.0 \n", - "15403 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", + "38877 0.0 \n", + "38904 0.0 \n", "... ... \n", - "309760814 0.0 \n", - "309760815 0.0 \n", - "309790009 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", + "310197956 0.0 \n", + "310202376 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_In_vehicle_time \\\n", "tour_id \n", - "6812 5.480000 \n", - "8110 8.860000 \n", - "11013 20.689999 \n", - "11016 14.710000 \n", - "15403 15.160000 \n", + "1870 20.830002 \n", + "20468 9.440000 \n", + "27055 13.160000 \n", + "38877 6.730000 \n", + "38904 22.410000 \n", "... ... \n", - "309760814 24.510000 \n", - "309760815 19.349998 \n", - "309790009 21.410000 \n", - "309796968 17.340000 \n", - "309796969 8.000000 \n", + "310197956 29.900002 \n", + "310202376 5.480000 \n", + "310202384 5.480000 \n", + "310212634 12.840000 \n", + "310220296 13.590000 \n", "\n", " util_DRIVEALONEFREE_Terminal_time \\\n", "tour_id \n", - "6812 15.45016 \n", - "8110 34.19784 \n", - "11013 18.17320 \n", - "11016 12.85052 \n", - "15403 10.64808 \n", + "1870 21.26572 \n", + "20468 13.24624 \n", + "27055 8.53068 \n", + "38877 11.04132 \n", + "38904 17.29320 \n", "... ... \n", - "309760814 11.41364 \n", - "309760815 16.96372 \n", - "309790009 19.44384 \n", - "309796968 13.66872 \n", - "309796969 10.00692 \n", + "310197956 4.21092 \n", + "310202376 3.82392 \n", + "310202384 3.82392 \n", + "310212634 5.32256 \n", + "310220296 8.05768 \n", "\n", - " util_DRIVEALONEFREE_Operating_cost ... walk_ferry_available \\\n", - "tour_id ... \n", - "6812 2.156258 ... False \n", - "8110 17.722496 ... False \n", - "11013 15.097005 ... False \n", - "11016 10.971117 ... False \n", - "15403 26.092745 ... False \n", - "... ... ... ... \n", - "309760814 27.217999 ... False \n", - "309760815 14.591494 ... False \n", - "309790009 84.280323 ... False \n", - "309796968 30.549632 ... False \n", - "309796969 18.758547 ... False \n", + " util_DRIVEALONEFREE_Operating_cost ... walk_lrf_available \\\n", + "tour_id ... \n", + "1870 6.293324 ... False \n", + "20468 14.917349 ... False \n", + "27055 25.088453 ... False \n", + "38877 11.040045 ... False \n", + "38904 46.920191 ... True \n", + "... ... ... ... \n", + "310197956 69.245528 ... False \n", + "310202376 19.277738 ... False \n", + "310202384 19.277738 ... False \n", + "310212634 5.457677 ... False \n", + "310220296 15.684208 ... False \n", "\n", - " drive_local_available drive_commuter_available \\\n", - "tour_id \n", - "6812 False False \n", - "8110 False False \n", - "11013 True True \n", - "11016 True True \n", - "15403 True True \n", - "... ... ... \n", - "309760814 True True \n", - "309760815 True True \n", - "309790009 True True \n", - "309796968 True True \n", - "309796969 True True \n", + " walk_ferry_available drive_local_available \\\n", + "tour_id \n", + "1870 False True \n", + "20468 False True \n", + "27055 False True \n", + "38877 False True \n", + "38904 False True \n", + "... ... ... \n", + "310197956 False False \n", + "310202376 False False \n", + "310202384 False False \n", + "310212634 False False \n", + "310220296 False False \n", "\n", - " drive_express_available drive_heavyrail_available \\\n", - "tour_id \n", - "6812 False False \n", - "8110 False False \n", - "11013 False True \n", - "11016 False True \n", - "15403 False True \n", - "... ... ... \n", - "309760814 False True \n", - "309760815 False True \n", - "309790009 False True \n", - "309796968 False True \n", - "309796969 False True \n", + " drive_commuter_available drive_express_available \\\n", + "tour_id \n", + "1870 True False \n", + "20468 True False \n", + "27055 True False \n", + "38877 True False \n", + "38904 True False \n", + "... ... ... \n", + "310197956 False False \n", + "310202376 False False \n", + "310202384 False False \n", + "310212634 True True \n", + "310220296 False True \n", "\n", - " drive_lrf_available drive_ferry_available destination_in_cbd \\\n", - "tour_id \n", - "6812 False False 1 \n", - "8110 False False 0 \n", - "11013 False False 1 \n", - "11016 False False 0 \n", - "15403 False False 0 \n", - "... ... ... ... \n", - "309760814 False False 0 \n", - "309760815 False False 1 \n", - "309790009 False False 1 \n", - "309796968 False False 0 \n", - "309796969 False False 0 \n", + " drive_heavyrail_available drive_lrf_available \\\n", + "tour_id \n", + "1870 True False \n", + "20468 True False \n", + "27055 True False \n", + "38877 True False \n", + "38904 True True \n", + "... ... ... \n", + "310197956 False False \n", + "310202376 False False \n", + "310202384 False False \n", + "310212634 False False \n", + "310220296 False False \n", "\n", - " tour_id.1 override_choice_code \n", - "tour_id \n", - "6812 6812 7 \n", - "8110 8110 7 \n", - "11013 11013 1 \n", - "11016 11016 1 \n", - "15403 15403 1 \n", - "... ... ... \n", - "309760814 309760814 1 \n", - "309760815 309760815 3 \n", - "309790009 309790009 8 \n", - "309796968 309796968 5 \n", - "309796969 309796969 1 \n", + " drive_ferry_available destination_in_cbd override_choice_code \n", + "tour_id \n", + "1870 False 1 5 \n", + "20468 False 0 20 \n", + "27055 False 0 5 \n", + "38877 False 0 5 \n", + "38904 False 0 3 \n", + "... ... ... ... \n", + "310197956 False 0 1 \n", + "310202376 False 0 8 \n", + "310202384 False 0 1 \n", + "310212634 False 0 1 \n", + "310220296 False 0 1 \n", "\n", - "[5314 rows x 535 columns]" + "[63935 rows x 536 columns]" ] }, "execution_count": 8, @@ -1216,88 +1294,20 @@ "execution_count": 9, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "problem: chosen-but-not-available (1 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (1 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: low-variance-data-co (1 issues)\n" - ] - }, { "data": { "text/plain": [ - "[(,\n", - " ┣ chosen_but_not_available: n example rows\n", - " ┃ 12 2 45, 312\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 58 util_BIKE_Unavailable_if_didnt_bike_to_work, u...),\n", - " (,\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 87 util_BIKE_Unavailable_if_didnt_bike_to_work, u...),\n", - " (,\n", - " ┣ chosen_but_not_available: n example rows\n", - " ┃ 10 4 66, 184, 222\n", - " ┃ 12 3 205, 394, 560\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 56 util_BIKE_Unavailable_if_didnt_bike_to_work, u...),\n", - " (,\n", - " ┣ chosen_but_not_available: n example rows\n", - " ┃ 10 4 25, 73, 98\n", - " ┃ 12 2 129, 320\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 57 util_BIKE_Unavailable_if_didnt_bike_to_work, u...),\n", - " (,\n", - " ┣ chosen_but_not_available: n example rows\n", - " ┃ 10 25 3, 108, 145\n", - " ┃ 12 5 10, 23, 135\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 88 util_BIKE_Unavailable_if_didnt_bike_to_work, u...),\n", - " (,\n", - " ┣ chosen_but_not_available: n example rows\n", - " ┃ 10 5 118, 300, 303\n", - " ┃ 12 1 252\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 54 util_BIKE_Unavailable_if_didnt_bike_to_work, u...),\n", - " (,\n", - " ┣ chosen_but_not_available: n example rows\n", - " ┃ 10 3 71, 163, 170\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 65 util_BIKE_Unavailable_if_didnt_bike_to_work, u...),\n", - " (, dictx()),\n", - " (,\n", - " ┣ chosen_but_not_available: n example rows\n", - " ┃ 10 36 21, 23, 95\n", - " ┃ 12 15 46, 243, 449\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 108 util_BIKE_Unavailable_if_didnt_bike_to_work, u...),\n", - " (,\n", - " ┣ low_variance_data_co: n example cols\n", - " ┃ low_variance_co 106 util_Commuter_Rail, util_DRIVEALONEFREE_Unavai...)]" + "(,\n", + " [(, dictx()),\n", + " (, dictx()),\n", + " (, dictx()),\n", + " (, dictx()),\n", + " (, dictx()),\n", + " (, dictx()),\n", + " (, dictx()),\n", + " (, dictx()),\n", + " (, dictx()),\n", + " (, dictx())])" ] }, "execution_count": 9, @@ -1306,7 +1316,6 @@ } ], "source": [ - "model.load_data()\n", "model.doctor(repair_ch_av=\"-\")" ] }, @@ -1318,7 +1327,7 @@ { "data": { "text/html": [ - "

Iteration 168 [Optimization terminated successfully]

" + "

Iteration 186 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1330,7 +1339,7 @@ { "data": { "text/html": [ - "

Best LL = -6324.409943103907

" + "

Best LL = -76504.13129817661

" ], "text/plain": [ "" @@ -1361,13 +1370,22 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -1375,56 +1393,51 @@ " -999\n", " -999.000000\n", " -999.000000\n", + " -999.000000\n", " -999.0\n", " -999.0\n", - " -999.0\n", + " 0.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " 1\n", " 1.000000\n", " 1.000000\n", + " 1.000000\n", " 1.0\n", " 1.0\n", - " 1.0\n", + " 0.0\n", " 1\n", - " \n", - " 1.000000\n", " \n", " \n", - " bike_ASC_auto_deficient_eatout\n", - " -95.051842\n", - " -1.569111\n", + " bike_ASC_auto_deficient_atwork\n", + " -0.997746\n", + " -0.997746\n", + " -0.807408\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -95.051842\n", " \n", " \n", - " bike_ASC_auto_sufficient_eatout\n", - " -1.464118\n", - " -1.200347\n", + " bike_ASC_auto_deficient_eatout\n", + " -1.673695\n", + " -1.673695\n", + " -1.569111\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.464118\n", " \n", " \n", - " bike_ASC_no_auto_eatout\n", - " 7.201849\n", - " 0.868071\n", + " bike_ASC_auto_deficient_escort\n", + " -4.147119\n", + " -4.147119\n", + " -4.527928\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 7.201849\n", " \n", " \n", " ...\n", @@ -1435,113 +1448,133 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", - " walk_ASC_no_auto_atwork\n", - " 12.824109\n", - " 6.669213\n", + " walk_transit_ASC_no_auto_work\n", + " 4.665799\n", + " 4.665799\n", + " 5.035417\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 12.824109\n", " \n", " \n", - " walk_transit_ASC_auto_deficient_atwork\n", - " 8.985177\n", - " -2.998829\n", + " walk_transit_CBD_ASC_atwork\n", + " 1.146544\n", + " 1.146544\n", + " 0.564000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 8.985177\n", " \n", " \n", - " walk_transit_ASC_auto_sufficient_atwork\n", - " 9.127996\n", - " -3.401027\n", + " walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social\n", + " 1.074027\n", + " 1.074027\n", + " 0.525000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 9.127996\n", " \n", " \n", - " walk_transit_ASC_no_auto_atwork\n", - " 21.234896\n", - " 2.704188\n", + " walk_transit_CBD_ASC_school_univ\n", + " 0.818861\n", + " 0.818861\n", + " 0.672000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 21.234896\n", " \n", " \n", - " walk_transit_CBD_ASC_atwork\n", - " 0.351949\n", - " 0.564000\n", + " walk_transit_CBD_ASC_work\n", + " 1.158108\n", + " 1.158108\n", + " 0.804000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.351949\n", " \n", " \n", "\n", - "

301 rows × 8 columns

\n", + "

301 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue nullvalue \\\n", - "-999 -999.000000 -999.000000 -999.0 \n", - "1 1.000000 1.000000 1.0 \n", - "bike_ASC_auto_deficient_eatout -95.051842 -1.569111 0.0 \n", - "bike_ASC_auto_sufficient_eatout -1.464118 -1.200347 0.0 \n", - "bike_ASC_no_auto_eatout 7.201849 0.868071 0.0 \n", - "... ... ... ... \n", - "walk_ASC_no_auto_atwork 12.824109 6.669213 0.0 \n", - "walk_transit_ASC_auto_deficient_atwork 8.985177 -2.998829 0.0 \n", - "walk_transit_ASC_auto_sufficient_atwork 9.127996 -3.401027 0.0 \n", - "walk_transit_ASC_no_auto_atwork 21.234896 2.704188 0.0 \n", - "walk_transit_CBD_ASC_atwork 0.351949 0.564000 0.0 \n", + " value best \\\n", + "param_name \n", + "-999 -999.000000 -999.000000 \n", + "1 1.000000 1.000000 \n", + "bike_ASC_auto_deficient_atwork -0.997746 -0.997746 \n", + "bike_ASC_auto_deficient_eatout -1.673695 -1.673695 \n", + "bike_ASC_auto_deficient_escort -4.147119 -4.147119 \n", + "... ... ... \n", + "walk_transit_ASC_no_auto_work 4.665799 4.665799 \n", + "walk_transit_CBD_ASC_atwork 1.146544 1.146544 \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth... 1.074027 1.074027 \n", + "walk_transit_CBD_ASC_school_univ 0.818861 0.818861 \n", + "walk_transit_CBD_ASC_work 1.158108 1.158108 \n", "\n", - " minimum maximum holdfast note \\\n", - "-999 -999.0 -999.0 1 \n", - "1 1.0 1.0 1 \n", - "bike_ASC_auto_deficient_eatout NaN NaN 0 \n", - "bike_ASC_auto_sufficient_eatout NaN NaN 0 \n", - "bike_ASC_no_auto_eatout NaN NaN 0 \n", - "... ... ... ... ... \n", - "walk_ASC_no_auto_atwork NaN NaN 0 \n", - "walk_transit_ASC_auto_deficient_atwork NaN NaN 0 \n", - "walk_transit_ASC_auto_sufficient_atwork NaN NaN 0 \n", - "walk_transit_ASC_no_auto_atwork NaN NaN 0 \n", - "walk_transit_CBD_ASC_atwork NaN NaN 0 \n", + " initvalue minimum \\\n", + "param_name \n", + "-999 -999.000000 -999.0 \n", + "1 1.000000 1.0 \n", + "bike_ASC_auto_deficient_atwork -0.807408 -inf \n", + "bike_ASC_auto_deficient_eatout -1.569111 -inf \n", + "bike_ASC_auto_deficient_escort -4.527928 -inf \n", + "... ... ... \n", + "walk_transit_ASC_no_auto_work 5.035417 -inf \n", + "walk_transit_CBD_ASC_atwork 0.564000 -inf \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth... 0.525000 -inf \n", + "walk_transit_CBD_ASC_school_univ 0.672000 -inf \n", + "walk_transit_CBD_ASC_work 0.804000 -inf \n", "\n", - " best \n", - "-999 -999.000000 \n", - "1 1.000000 \n", - "bike_ASC_auto_deficient_eatout -95.051842 \n", - "bike_ASC_auto_sufficient_eatout -1.464118 \n", - "bike_ASC_no_auto_eatout 7.201849 \n", - "... ... \n", - "walk_ASC_no_auto_atwork 12.824109 \n", - "walk_transit_ASC_auto_deficient_atwork 8.985177 \n", - "walk_transit_ASC_auto_sufficient_atwork 9.127996 \n", - "walk_transit_ASC_no_auto_atwork 21.234896 \n", - "walk_transit_CBD_ASC_atwork 0.351949 \n", + " maximum nullvalue \\\n", + "param_name \n", + "-999 -999.0 0.0 \n", + "1 1.0 0.0 \n", + "bike_ASC_auto_deficient_atwork inf 0.0 \n", + "bike_ASC_auto_deficient_eatout inf 0.0 \n", + "bike_ASC_auto_deficient_escort inf 0.0 \n", + "... ... ... \n", + "walk_transit_ASC_no_auto_work inf 0.0 \n", + "walk_transit_CBD_ASC_atwork inf 0.0 \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth... inf 0.0 \n", + "walk_transit_CBD_ASC_school_univ inf 0.0 \n", + "walk_transit_CBD_ASC_work inf 0.0 \n", "\n", - "[301 rows x 8 columns]" + " holdfast \n", + "param_name \n", + "-999 1 \n", + "1 1 \n", + "bike_ASC_auto_deficient_atwork 0 \n", + "bike_ASC_auto_deficient_eatout 0 \n", + "bike_ASC_auto_deficient_escort 0 \n", + "... ... \n", + "walk_transit_ASC_no_auto_work 0 \n", + "walk_transit_CBD_ASC_atwork 0 \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth... 0 \n", + "walk_transit_CBD_ASC_school_univ 0 \n", + "walk_transit_CBD_ASC_work 0 \n", + "\n", + "[301 rows x 7 columns]" ] }, "metadata": {}, "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/jpn/Git/est-mode/larch/src/larch/model/optimization.py:338: UserWarning: SLSQP may not play nicely with unbounded parameters\n", + "if you get poor results, consider setting global bounds with model.set_cap()\n", + " warnings.warn( # infinite bounds # )\n" + ] } ], "source": [ @@ -1557,18 +1590,120 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_92897/3375301916.py:1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.calculate_parameter_covariance()\n", - "/Users/jeffnewman/LocalGit/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 1.1755327986150339e-46 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - "/var/folders/js/bk_dt9015j79_f6bxnc44dsr0000gp/T/ipykernel_92897/3375301916.py:1: PossibleOverspecification: WARNING: Model seems to have 58 parameter estimators with negative variance\n", - "- commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", - "- drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", - "- drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", - "- drive_transit_ASC_no_auto_all\n", - "- and 54 more\n", + "/var/folders/l1/yt63lf3n60b1dc25d_y2d1q80000gn/T/ipykernel_30646/3375301916.py:1: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", " model.calculate_parameter_covariance()\n" ] + }, + { + "data": { + "text/plain": [ + "(array([0.00000000e+00, 0.00000000e+00, 3.35905128e-01, 4.03997542e-01,\n", + " 3.98391399e-01, 2.04116538e-01, 3.43847113e-01, 3.05273022e-01,\n", + " 2.20308907e-01, 3.19155920e-01, 3.56339406e-02, 7.75126393e-02,\n", + " 4.36635034e+02, 1.46654623e-01, 3.88297006e-01, 9.37023760e-02,\n", + " 1.79285943e-01, 1.04219523e-01, 1.29302923e-01, 2.01485594e-01,\n", + " 1.57876345e-02, 6.56232000e-02, 7.82486553e+01, 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" \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", - " \n", - "
 ValueStd Errt StatSignifLike RatioNull ValueValueStd Errt StatSignifNull Value
Parameter     
-999-999. 0.00 NA NA-999.00
1 1.00 0.00 NA NA 1.00
bike_ASC_auto_deficient_eatout-95.1 0.00 NA[**] 3.97 0.00
bike_ASC_auto_sufficient_eatout-1.46 0.459-3.19** NA 0.00
bike_ASC_no_auto_eatout 7.20 0.740 9.73*** NA 0.00
coef_age010_trn_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work 0.720 0.387 1.86 NA 0.00
coef_age1619_da_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work-0.0191 0.214-0.09 NA 0.00
coef_age16p_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social-1.14 0.276-4.13*** NA 0.00
coef_hhsize1_sr_multiplier_eatout_escort_othdiscr_othmaint_school_shopping_social_univ_atwork 0.0210 0.0998 0.21 NA 0.00
coef_hhsize2_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork-0.00393 0.0708-0.06 NA 0.00
coef_ivt_eatout_escort_othdiscr_othmaint_shopping_social-0.0169 0.000785-21.58*** NA 0.00
coef_nest_AUTO 0.720 0.00 NA NA 1.00
coef_nest_AUTO_DRIVEALONE 0.350 0.00 NA NA 1.00
coef_nest_AUTO_SHAREDRIDE2 0.350 0.00 NA NA 1.00
coef_nest_AUTO_SHAREDRIDE3 0.350 0.00 NA NA 1.00
coef_nest_NONMOTORIZED 0.720 0.00 NA NA 1.00
coef_nest_RIDEHAIL 0.360 0.00 NA NA 1.00
coef_nest_TRANSIT 0.720 0.00 NA NA 1.00
coef_nest_TRANSIT_DRIVEACCESS 0.500 0.00 NA NA 1.00
coef_nest_TRANSIT_WALKACCESS 0.500 0.00 NA NA 1.00
commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-38.8 NA NA[***] BIG 0.00
drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork 0.940 NA NA[] 0.00 0.00
drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-25.9 NA NA[***] 94.74 0.00
drive_transit_ASC_auto_deficient_eatout 14.7 1.77 8.30*** NA 0.00
drive_transit_ASC_auto_sufficient_eatout 12.1 1.88 6.45*** NA 0.00
drive_transit_ASC_no_auto_all 0.00 NA NA[] 0.00 0.00
drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social 0.553 0.813 0.68 NA 0.00
express_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-61.5 NA NA[***] 94.10 0.00
heavy_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-11.3 1.64-6.91*** NA 0.00
joint_bike_ASC_auto_deficient_all-155. NA NA[***] 49.72 0.00
joint_bike_ASC_auto_sufficient_all-108. NA NA[***] 89.09 0.00
joint_bike_ASC_no_auto_all-47.7 NA NA[] 1.65 0.00
joint_drive_transit_ASC_auto_deficient_all-36.1 NA NA[] 0.00 0.00
joint_drive_transit_ASC_auto_sufficient_all-24.1 NA NA[] 0.00 0.00
joint_drive_transit_ASC_no_auto_all 0.00 0.00 NA NA 0.00
joint_sr2_ASC_auto_deficient_all 0.00 0.00 NA NA 0.00
joint_sr2_ASC_auto_sufficient_all 0.00 0.00 NA NA 0.00
joint_sr2_ASC_no_auto_all 0.00 0.00 NA NA 0.00
joint_sr3p_ASC_auto_deficient_all-5.34 1.92-2.79** NA 0.00
joint_sr3p_ASC_auto_sufficient_all-3.33 0.983-3.39*** NA 0.00
joint_sr3p_ASC_no_auto_all 0.977 0.798 1.22 NA 0.00
joint_taxi_ASC_auto_deficient_all-45.5 NA NA[***] 31.66 0.00
joint_taxi_ASC_auto_sufficient_all-11.7 0.00 NA NA 0.00
joint_taxi_ASC_no_auto_all-12.8 841.-0.02 NA 0.00
joint_tnc_shared_ASC_auto_deficient_all-37.8 NA NA[***] 42.60 0.00
joint_tnc_shared_ASC_auto_sufficient_all-13.2 0.00 NA NA 0.00
joint_tnc_shared_ASC_no_auto_all-24.5 NA NA[] 1.15 0.00
joint_tnc_single_ASC_auto_deficient_all-51.7 NA NA[***] 36.10 0.00
joint_tnc_single_ASC_auto_sufficient_all-14.0 0.00 NA NA 0.00
joint_tnc_single_ASC_no_auto_all-16.7 NA NA[] 0.72 0.00
joint_walk_ASC_auto_deficient_all-1.31 1.43-0.92 NA 0.00
joint_walk_ASC_auto_sufficient_all-3.63 1.11-3.27** NA 0.00
joint_walk_ASC_no_auto_all 0.968 1.21 0.80 NA 0.00
joint_walk_transit_ASC_auto_deficient_all 4.48 2.40 1.87 NA 0.00
joint_walk_transit_ASC_auto_sufficient_all-18.3 NA NA[] 0.00 0.00
joint_walk_transit_ASC_no_auto_all 13.6 1.87 7.24*** NA 0.00
local_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-12.6 1.64-7.68*** NA 0.00
sr2_ASC_auto_deficient_eatout 0.235 0.415 0.57 NA 0.00
sr2_ASC_auto_sufficient_eatout 0.457 0.318 1.44 NA 0.00
sr2_ASC_no_auto_all 5.30 0.368 14.42*** NA 0.00
sr3p_ASC_auto_deficient_eatout-0.0844 0.448-0.19 NA 0.00
sr3p_ASC_auto_sufficient_eatout 0.502 0.313 1.60 NA 0.00
sr3p_ASC_no_auto_eatout 5.80 0.782 7.42*** NA 0.00
taxi_ASC_auto_deficient_eatout_othdiscr_social-34.3 NA NA[***] 10.47 0.00
taxi_ASC_auto_sufficient_eatout_othdiscr_social-2.38 0.505-4.71*** NA 0.00
taxi_ASC_no_auto_eatout_othdiscr_social-25.8 NA NA[] 0.00 0.00
tnc_shared_ASC_auto_deficient_eatout_othdiscr_social-2.92 1.01-2.89** NA 0.00
tnc_shared_ASC_auto_sufficient_eatout_othdiscr_social-3.47 0.610-5.69*** NA 0.00
tnc_shared_ASC_no_auto_eatout_othdiscr_social 5.50 0.507 10.85*** NA 0.00
tnc_single_ASC_auto_deficient_eatout_othdiscr_social-30.0 NA NA[***] 15.06 0.00
tnc_single_ASC_auto_sufficient_eatout_othdiscr_social-2.09 0.375-5.57*** NA 0.00
tnc_single_ASC_no_auto_eatout_othdiscr_social 6.70 0.465 14.39*** NA 0.00
walk_ASC_auto_deficient_eatout 2.96 0.472 6.27*** NA 0.00
walk_ASC_auto_sufficient_eatout 0.804 0.390 2.06* NA 0.00
walk_ASC_no_auto_eatout 10.2 0.673 15.17*** NA 0.00
walk_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork 0.940 NA NA[] 0.00 0.00
walk_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-11.6 1.64-7.06*** NA 0.00
walk_transit_ASC_auto_deficient_eatout 12.3 1.69 7.30*** NA 0.00
walk_transit_ASC_auto_sufficient_eatout 10.8 1.67 6.43*** NA 0.00
walk_transit_ASC_no_auto_eatout 20.5 1.50 13.66*** NA 0.00
walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social 0.691 0.157 4.40*** NA 0.00
bike_ASC_auto_deficient_escort-80.8 NA NA[***] 15.70 0.00
bike_ASC_auto_sufficient_escort-4.23 0.746-5.68*** NA 0.00
bike_ASC_no_auto_escort-82.6 NA NA[] 0.00 0.00
drive_transit_ASC_auto_deficient_escort 12.0 1.93 6.23*** NA 0.00
drive_transit_ASC_auto_sufficient_escort-38.4 NA NA[] 0.00 0.00
sr2_ASC_auto_deficient_escort-0.0289 0.415-0.07 NA 0.00
sr2_ASC_auto_sufficient_escort-0.446 0.436-1.02 NA 0.00
sr3p_ASC_auto_deficient_escort-0.242 0.420-0.58 NA 0.00
sr3p_ASC_auto_sufficient_escort-0.573 0.437-1.31 NA 0.00
sr3p_ASC_no_auto_escort-48.6 NA NA[] 0.00 0.00
taxi_ASC_auto_deficient_escort_othmaint_shopping 0.221 0.304 0.73 NA 0.00
taxi_ASC_auto_sufficient_escort_othmaint_shopping-1.87 0.295-6.35*** NA 0.00
taxi_ASC_no_auto_escort_othmaint_shopping 7.36 0.451 16.30*** NA 0.00
tnc_shared_ASC_auto_deficient_escort_othmaint_shopping-0.244 0.228-1.07 NA 0.00
tnc_shared_ASC_auto_sufficient_escort_othmaint_shopping-2.71 0.286-9.46*** NA 0.00
tnc_shared_ASC_no_auto_escort_othmaint_shopping 6.66 0.440 15.13*** NA 0.00
tnc_single_ASC_auto_deficient_escort_othmaint_shopping 0.896 0.219 4.09*** NA 0.00
tnc_single_ASC_auto_sufficient_escort_othmaint_shopping-1.75 0.263-6.64*** NA 0.00
tnc_single_ASC_no_auto_escort_othmaint_shopping 7.44 0.437 17.05*** NA 0.00
walk_ASC_auto_deficient_escort-103. NA NA[*] 1.98 0.00
walk_ASC_auto_sufficient_escort-2.20 0.773-2.84** NA 0.00
walk_ASC_no_auto_escort 7.37 1.26 5.87*** NA 0.00
walk_transit_ASC_auto_deficient_escort 8.76 1.87 4.70*** NA 0.00
walk_transit_ASC_auto_sufficient_escort 7.57 1.77 4.29*** NA 0.00
walk_transit_ASC_no_auto_escort-44.3 NA NA[] 0.00 0.00
bike_ASC_auto_deficient_othdiscr 0.229 0.469 0.49 NA 0.00
bike_ASC_auto_sufficient_othdiscr-1.92 0.393-4.87*** NA 0.00
bike_ASC_no_auto_othdiscr 5.46 0.640 8.52*** NA 0.00
drive_transit_ASC_auto_deficient_othdiscr-61.4 NA NA[] 0.00 0.00
drive_transit_ASC_auto_sufficient_othdiscr 11.3 1.94 5.85*** NA 0.00
sr2_ASC_auto_deficient_othdiscr 0.739 0.378 1.96 NA 0.00
sr2_ASC_auto_sufficient_othdiscr 0.123 0.299 0.41 NA 0.00
sr3p_ASC_auto_deficient_othdiscr 0.935 0.364 2.57* NA 0.00
sr3p_ASC_auto_sufficient_othdiscr 0.246 0.295 0.83 NA 0.00
sr3p_ASC_no_auto_othdiscr 6.41 0.497 12.89*** NA 0.00
walk_ASC_auto_deficient_othdiscr 1.63 0.545 2.98** NA 0.00
walk_ASC_auto_sufficient_othdiscr 1.09 0.261 4.20*** NA 0.00
walk_ASC_no_auto_othdiscr 8.77 0.545 16.09*** NA 0.00
walk_transit_ASC_auto_deficient_othdiscr 13.3 1.67 7.97*** NA 0.00
walk_transit_ASC_auto_sufficient_othdiscr 11.3 1.65 6.84*** NA 0.00
walk_transit_ASC_no_auto_othdiscr 20.4 1.44 14.14*** NA 0.00
bike_ASC_auto_deficient_othmaint-1.55 0.792-1.96 NA 0.00
bike_ASC_auto_sufficient_othmaint-2.48 0.551-4.51*** NA 0.00
bike_ASC_no_auto_othmaint 7.09 0.520 13.63*** NA 0.00
drive_transit_ASC_auto_deficient_othmaint-65.9 NA NA[] 0.00 0.00
drive_transit_ASC_auto_sufficient_othmaint-32.2 NA NA[] 0.00 0.00
sr2_ASC_auto_deficient_othmaint-0.174 0.421-0.41 NA 0.00
sr2_ASC_auto_sufficient_othmaint 0.222 0.306 0.72 NA 0.00
sr3p_ASC_auto_deficient_othmaint-1.77 0.796-2.22* NA 0.00
sr3p_ASC_auto_sufficient_othmaint-0.251 0.322-0.78 NA 0.00
sr3p_ASC_no_auto_othmaint 4.59 0.844 5.44*** NA 0.00
walk_ASC_auto_deficient_othmaint 1.83 0.694 2.64** NA 0.00
walk_ASC_auto_sufficient_othmaint 0.890 0.354 2.51* NA 0.00
walk_ASC_no_auto_othmaint 6.29 0.883 7.13*** NA 0.00
walk_transit_ASC_auto_deficient_othmaint 9.41 1.92 4.90*** NA 0.00
walk_transit_ASC_auto_sufficient_othmaint 11.0 1.66 6.59*** NA 0.00
walk_transit_ASC_no_auto_othmaint 20.6 1.45 14.26*** NA 0.00
bike_ASC_auto_deficient_school-0.418 1.07-0.39 NA 0.00
bike_ASC_auto_sufficient_school-3.51 0.742-4.72*** NA 0.00
bike_ASC_no_auto_school-28.7 NA NA[] 0.00 0.00
coef_age010_trn_multiplier_school_univ-1.11 0.279-3.98*** NA 0.00
coef_age1619_da_multiplier_school_univ-1.60 0.496-3.22** NA 0.00
coef_age16p_sr_multiplier_school_univ_work_atwork-0.721 0.357-2.02* NA 0.00
coef_hhsize2_sr_multiplier_school_univ-0.534 0.528-1.01 NA 0.00
coef_ivt_school_univ-0.0212 0.00207-10.25*** NA 0.00
commuter_rail_ASC_school_univ-32.4 NA NA[***] 230.28 0.00
drive_ferry_ASC_school_univ 2.02 NA NA[] 0.00 0.00
drive_light_rail_ASC_school_univ-19.1 0.0154-BIG*** NA 0.00
drive_transit_ASC_auto_deficient_school-96.0 NA NA[***] BIG 0.00
drive_transit_ASC_auto_sufficient_school-46.2 153.-0.30 NA 0.00
drive_transit_CBD_ASC_school_univ 62.5 153. 0.41 NA 0.00
express_bus_ASC_school_univ 0.325 NA NA[] 0.00 0.00
heavy_rail_ASC_school_univ-12.4 305.-0.04 NA 0.00
local_bus_ASC_school_univ-13.9 305.-0.05 NA 0.00
sr2_ASC_auto_deficient_school 0.116 0.860 0.14 NA 0.00
sr2_ASC_auto_sufficient_school-1.65 0.362-4.55*** NA 0.00
sr3p_ASC_auto_deficient_school 0.721 0.848 0.85 NA 0.00
sr3p_ASC_auto_sufficient_school-1.19 0.353-3.36*** NA 0.00
sr3p_ASC_no_auto_school-6.02 NA NA[] 0.00 0.00
taxi_ASC_auto_deficient_school 1.59 0.932 1.71 NA 0.00
taxi_ASC_auto_sufficient_school-1.63 0.602-2.71** NA 0.00
taxi_ASC_no_auto_school_univ-7.00 0.00 NA NA 0.00
tnc_shared_ASC_auto_deficient_school 0.968 0.905 1.07 NA 0.00
tnc_shared_ASC_auto_sufficient_school-2.77 0.626-4.43*** NA 0.00
tnc_shared_ASC_no_auto_school-7.00 0.00 NA NA 0.00
tnc_single_ASC_auto_deficient_school-3.36 113.-0.03 NA 0.00
tnc_single_ASC_auto_sufficient_school-2.37 0.650-3.65*** NA 0.00
tnc_single_ASC_no_auto_school-7.00 0.00 NA NA 0.00
walk_ASC_auto_deficient_school 3.23 0.931 3.47*** NA 0.00
walk_ASC_auto_sufficient_school 0.692 0.421 1.64 NA 0.00
walk_ASC_no_auto_school 31.9 NA NA[***] 241.14 0.00
walk_ferry_ASC_school_univ 2.02 NA NA[] 0.00 0.00
walk_light_rail_ASC_school_univ-12.1 305.-0.04 NA 0.00
walk_transit_ASC_auto_deficient_school 17.1 305. 0.06 NA 0.00
walk_transit_ASC_auto_sufficient_school 14.2 305. 0.05 NA 0.00
walk_transit_ASC_no_auto_school 48.7 NA NA[***] BIG 0.00
walk_transit_CBD_ASC_school_univ 0.788 0.260 3.03** NA 0.00
bike_ASC_auto_deficient_shopping-0.982 0.499-1.97* NA 0.00
bike_ASC_auto_sufficient_shopping-4.77 0.991-4.81*** NA 0.00
bike_ASC_no_auto_shopping 6.35 0.481 13.21*** NA 0.00
drive_transit_ASC_auto_deficient_shopping-69.1 NA NA[] 0.00 0.00
drive_transit_ASC_auto_sufficient_shopping-74.4 NA NA[] 0.00 0.00
sr2_ASC_auto_deficient_shopping 0.341 0.336 1.01 NA 0.00
sr2_ASC_auto_sufficient_shopping 0.145 0.293 0.49 NA 0.00
sr3p_ASC_auto_deficient_shopping-0.262 0.376-0.70 NA 0.00
sr3p_ASC_auto_sufficient_shopping-0.296 0.301-0.98 NA 0.00
sr3p_ASC_no_auto_shopping 5.65 0.463 12.20*** NA 0.00
walk_ASC_auto_deficient_shopping 2.80 0.360 7.78*** NA 0.00
walk_ASC_auto_sufficient_shopping 0.473 0.249 1.90 NA 0.00
walk_ASC_no_auto_shopping 8.22 0.493 16.65*** NA 0.00
walk_transit_ASC_auto_deficient_shopping 11.3 1.67 6.73*** NA 0.00
walk_transit_ASC_auto_sufficient_shopping 9.75 1.66 5.86*** NA 0.00
walk_transit_ASC_no_auto_shopping 19.7 1.43 13.75*** NA 0.00
bike_ASC_auto_deficient_social-0.269 1.04-0.26 NA 0.00
bike_ASC_auto_sufficient_social-0.854 0.716-1.19 NA 0.00
bike_ASC_no_auto_social 5.51 0.583 9.46*** NA 0.00
drive_transit_ASC_auto_deficient_social-52.8 NA NA[] 0.00 0.00
drive_transit_ASC_auto_sufficient_social-48.0 NA NA[] 0.00 0.00
sr2_ASC_auto_deficient_social 1.43 0.463 3.08** NA 0.00
sr2_ASC_auto_sufficient_social 0.977 0.351 2.78** NA 0.00
sr3p_ASC_auto_deficient_social 0.676 0.546 1.24 NA 0.00
sr3p_ASC_auto_sufficient_social 0.757 0.362 2.09* NA 0.00
sr3p_ASC_no_auto_social 3.97 0.820 4.84*** NA 0.00
walk_ASC_auto_deficient_social 3.17 0.911 3.48*** NA 0.00
walk_ASC_auto_sufficient_social 2.66 0.491 5.42*** NA 0.00
walk_ASC_no_auto_social 6.44 0.683 9.43*** NA 0.00
walk_transit_ASC_auto_deficient_social 12.9 1.75 7.36*** NA 0.00
walk_transit_ASC_auto_sufficient_social 12.6 1.67 7.54*** NA 0.00
walk_transit_ASC_no_auto_social 19.0 1.46 13.02*** NA 0.00
bike_ASC_auto_deficient_univ-0.669 NA NA[] 0.00 0.00
bike_ASC_auto_sufficient_univ-1.94 NA NA[] 0.00 0.00
bike_ASC_no_auto_univ 4.29 NA NA[] 0.00 0.00
drive_transit_ASC_auto_deficient_univ 1.85 NA NA[] 0.00 0.00
drive_transit_ASC_auto_sufficient_univ 1.36 NA NA[] 0.00 0.00
sr2_ASC_auto_deficient_univ-1.69 NA NA[] 0.00 0.00
sr2_ASC_auto_sufficient_univ-1.86 NA NA[] 0.00 0.00
sr3p_ASC_auto_deficient_univ-1.73 NA NA[] 0.00 0.00
sr3p_ASC_auto_sufficient_univ-1.90 4.83e-14-BIG*** NA 0.00
sr3p_ASC_no_auto_univ-6.06 2.85e-18-BIG*** NA 0.00
taxi_ASC_auto_deficient_univ 4.25 0.00 NA[] 0.00 0.00
taxi_ASC_auto_sufficient_univ-0.313 0.00 NA[] 0.00 0.00
tnc_shared_ASC_auto_deficient_univ 3.25 0.00 NA[] 0.00 0.00
tnc_shared_ASC_auto_sufficient_univ-0.907 0.00 NA[] 0.00 0.00
tnc_shared_ASC_no_auto_univ-5.81 0.00 NA[] 0.00 0.00
tnc_single_ASC_auto_deficient_univ 1.02 0.00 NA[] 0.00 0.00
tnc_single_ASC_auto_sufficient_univ 0.209 0.00 NA[] 0.00 0.00
tnc_single_ASC_no_auto_univ-2.52 0.00 NA[] 0.00 0.00
walk_ASC_auto_deficient_univ 4.51 0.00 NA[] 0.00 0.00
walk_ASC_auto_sufficient_univ 1.06 0.00 NA[] 0.00 0.00
walk_ASC_no_auto_univ 6.41 0.00 NA[] 0.00 0.00
walk_transit_ASC_auto_deficient_univ 3.14 0.00 NA[] 0.00 0.00
walk_transit_ASC_auto_sufficient_univ 0.473 0.00 NA[] 0.00 0.00
walk_transit_ASC_no_auto_univ 8.79 0.00 NA[] 0.00 0.00
bike_ASC_auto_deficient_work 0.109 0.159 0.69 NA 0.00
bike_ASC_auto_sufficient_work-1.71 0.201-8.54*** NA 0.00
bike_ASC_no_auto_work 7.92 0.643 12.31*** NA 0.00
coef_hhsize1_sr_multiplier_work-0.679 0.174-3.90*** NA 0.00
coef_ivt_work-0.0131 0.000672-19.44*** NA 0.00
commuter_rail_ASC_work 12.1 0.561 21.60*** NA 0.00
drive_ferry_ASC_work 0.933 0.00 NA[] 0.00 0.00
drive_light_rail_ASC_work-36.0 NA NA[] 0.00 0.00
drive_transit_ASC_auto_deficient_work-10.8 0.493-21.96*** NA 0.00
drive_transit_ASC_auto_sufficient_work-11.9 0.496-24.03*** NA 0.00
drive_transit_CBD_ASC_work 1.43 0.593 2.41* NA 0.00
express_bus_ASC_work-54.6 NA NA[] 0.00 0.00
heavy_rail_ASC_work 11.0 0.185 59.50*** NA 0.00
local_bus_ASC_work 10.3 0.173 59.60*** NA 0.00
sr2_ASC_auto_deficient_work 0.463 0.367 1.26 NA 0.00
sr2_ASC_auto_sufficient_work-0.391 0.369-1.06 NA 0.00
sr3p_ASC_auto_deficient_work-0.0501 0.372-0.13 NA 0.00
sr3p_ASC_auto_sufficient_work-0.716 0.373-1.92 NA 0.00
sr3p_ASC_no_auto_work 5.29 0.646 8.18*** NA 0.00
taxi_ASC_auto_deficient_work-1.36 0.326-4.16*** NA 0.00
taxi_ASC_auto_sufficient_work-56.0 NA NA[***] 89.02 0.00
taxi_ASC_no_auto_work 9.43 0.651 14.50*** NA 0.00
tnc_shared_ASC_auto_deficient_work-2.43 0.420-5.80*** NA 0.00
tnc_shared_ASC_auto_sufficient_work-63.4 NA NA[***] 180.49 0.00
tnc_shared_ASC_no_auto_work-47.3 NA NA[] 0.00 0.00
tnc_single_ASC_auto_deficient_work-0.788 0.211-3.73*** NA 0.00
tnc_single_ASC_auto_sufficient_work-4.88 1.00-4.86*** NA 0.00
tnc_single_ASC_no_auto_work 10.3 0.630 16.35*** NA 0.00
walk_ASC_auto_deficient_work 2.13 0.200 10.62*** NA 0.00
walk_ASC_auto_sufficient_work 0.176 0.215 0.82 NA 0.00
walk_ASC_no_auto_work 10.4 0.654 15.83*** NA 0.00
walk_ferry_ASC_work 0.933 0.00 NA[] 0.00 0.00
walk_light_rail_ASC_work 11.2 0.178 62.93*** NA 0.00
walk_transit_ASC_auto_deficient_work-9.77 0.182-53.62*** NA 0.00
walk_transit_ASC_auto_sufficient_work-11.3 0.187-60.43*** NA 0.00
walk_transit_ASC_no_auto_work-0.818 0.576-1.42 NA 0.00
walk_transit_CBD_ASC_work 0.977 0.121 8.07*** NA 0.00
bike_ASC_auto_deficient_atwork-1.38 0.914-1.51 NA 0.00
bike_ASC_auto_sufficient_atwork 15.7 726. 0.02 NA 0.00
bike_ASC_no_auto_atwork-28.4 NA NA[] 0.00 0.00
coef_age010_trn_multiplier_atwork 0.000722 0.00 NA[] 0.00 0.00
coef_age1619_da_multiplier_atwork-0.807 1.03-0.79 NA 0.00
coef_ivt_atwork-0.0210 0.00255-8.26*** NA 0.00
drive_transit_ASC_auto_deficient_atwork-999. 0.00 NA[] 0.00 0.00
drive_transit_ASC_auto_sufficient_atwork-999. 0.00 NA[] 0.00 0.00
drive_transit_CBD_ASC_atwork 0.564 0.00 NA[] 0.00 0.00
sr2_ASC_auto_deficient_atwork-1.89 0.573-3.31*** NA 0.00
sr2_ASC_auto_sufficient_atwork-0.652 0.398-1.64 NA 0.00
sr3p_ASC_auto_deficient_atwork-2.38 0.580-4.11*** NA 0.00
sr3p_ASC_auto_sufficient_atwork-0.822 0.401-2.05* NA 0.00
sr3p_ASC_no_auto_atwork 6.24 0.790 7.90*** NA 0.00
taxi_ASC_auto_deficient_atwork-28.5 NA NA[***] 64.57 0.00
taxi_ASC_auto_sufficient_atwork-28.6 NA NA[***] 38.13 0.00
taxi_ASC_no_auto_atwork 10.2 0.970 10.52*** NA 0.00
tnc_shared_ASC_auto_deficient_atwork-3.91 0.639-6.12*** NA 0.00
tnc_shared_ASC_auto_sufficient_atwork-2.69 0.496-5.42*** NA 0.00
tnc_shared_ASC_no_auto_atwork 9.06 0.890 10.18*** NA 0.00
tnc_single_ASC_auto_deficient_atwork-3.11 0.611-5.09*** NA 0.00
tnc_single_ASC_auto_sufficient_atwork-2.63 0.529-4.97*** NA 0.00
tnc_single_ASC_no_auto_atwork 10.5 0.917 11.43*** NA 0.00
walk_ASC_auto_deficient_atwork 1.82 0.671 2.72** NA 0.00
walk_ASC_auto_sufficient_atwork 1.43 0.379 3.77*** NA 0.00
walk_ASC_no_auto_atwork 12.8 1.04 12.31*** NA 0.00
walk_transit_ASC_auto_deficient_atwork 8.99 1.76 5.10*** NA 0.00
walk_transit_ASC_auto_sufficient_atwork 9.13 1.81 5.04*** NA 0.00
walk_transit_ASC_no_auto_atwork 21.2 1.66 12.81*** NA 0.00
walk_transit_CBD_ASC_atwork 0.352 0.549 0.64 NA 0.00-999-999. 0.00 NA 0.00
\n" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.parameter_summary()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "colab_type": "text", - "id": "TojXWivZsx7M" - }, - "source": [ - "# Output Estimation Results" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "from activitysim.estimation.larch import update_coefficients\n", - "result_dir = data.edb_directory/\"estimated\"\n", - "update_coefficients(\n", - " model, data, result_dir,\n", - " output_file=f\"{modelname}_coefficients_revised.csv\",\n", - ");" + " \n", + " 1\n", + "  1.00\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_atwork\n", + " -0.998\n", + "  0.336\n", + " -2.97\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_eatout\n", + " -1.67\n", + "  0.404\n", + " -4.14\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_escort\n", + " -4.15\n", + "  0.398\n", + " -10.41\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_othdiscr\n", + " -1.11\n", + "  0.204\n", + " -5.42\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_othmaint\n", + " -2.34\n", + "  0.344\n", + " -6.81\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_school\n", + " -1.44\n", + "  0.305\n", + " -4.71\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_shopping\n", + " -1.92\n", + "  0.220\n", + " -8.74\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_social\n", + "  0.185\n", + "  0.319\n", + "  0.58\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_univ\n", + " -0.669\n", + "  0.0356\n", + " -18.78\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_deficient_work\n", + " -0.335\n", + "  0.0775\n", + " -4.33\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_atwork\n", + "  15.7\n", + "  437.\n", + "  0.04\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_eatout\n", + " -1.88\n", + "  0.147\n", + " -12.80\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_escort\n", + " -6.00\n", + "  0.388\n", + " -15.46\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_othdiscr\n", + " -1.97\n", + "  0.0937\n", + " -21.00\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_othmaint\n", + " -3.17\n", + "  0.179\n", + " -17.71\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_school\n", + " -2.70\n", + "  0.104\n", + " -25.91\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_shopping\n", + " -3.22\n", + "  0.129\n", + " -24.92\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_social\n", + " -2.25\n", + "  0.201\n", + " -11.15\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_univ\n", + " -1.94\n", + "  0.0158\n", + " -122.87\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_auto_sufficient_work\n", + " -2.04\n", + "  0.0656\n", + " -31.15\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_atwork\n", + " -0.909\n", + "  78.2\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_eatout\n", + "  0.420\n", + "  77.7\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_escort\n", + " -0.754\n", + "  77.7\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_othdiscr\n", + " -0.514\n", + "  77.7\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_othmaint\n", + "  1.48\n", + "  77.7\n", + "  0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_school\n", + "  13.3\n", + "  106.\n", + "  0.13\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_shopping\n", + "  0.955\n", + "  77.7\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_social\n", + "  0.352\n", + "  77.7\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_univ\n", + "  4.29\n", + "  0.0225\n", + "  190.79\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " bike_ASC_no_auto_work\n", + "  3.46\n", + "  77.7\n", + "  0.04\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_age010_trn_multiplier_atwork\n", + "  0.000722\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_age010_trn_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work\n", + "  0.277\n", + "  0.177\n", + "  1.56\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_age010_trn_multiplier_school_univ\n", + " -0.884\n", + "  0.0900\n", + " -9.82\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_age1619_da_multiplier_atwork\n", + " -0.184\n", + "  0.205\n", + " -0.90\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_age1619_da_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work\n", + "  0.0300\n", + "  0.0425\n", + "  0.71\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_age1619_da_multiplier_school_univ\n", + " -1.63\n", + "  0.0746\n", + " -21.80\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_age16p_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social\n", + " -1.42\n", + "  0.0807\n", + " -17.61\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_age16p_sr_multiplier_school_univ_work_atwork\n", + " -0.663\n", + "  0.0682\n", + " -9.72\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_hhsize1_sr_multiplier_eatout_escort_othdiscr_othmaint_school_shopping_social_univ_atwork\n", + " -0.0800\n", + "  0.0313\n", + " -2.56\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " coef_hhsize1_sr_multiplier_work\n", + " -0.839\n", + "  0.0576\n", + " -14.56\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_hhsize2_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork\n", + " -0.00550\n", + "  0.0178\n", + " -0.31\n", + " \n", + " 0.00\n", + " \n", + " \n", + " coef_hhsize2_sr_multiplier_school_univ\n", + " -0.733\n", + "  0.0909\n", + " -8.06\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_ivt_atwork\n", + " -0.0112\n", + "  0.000480\n", + " -23.42\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_ivt_eatout_escort_othdiscr_othmaint_shopping_social\n", + " -0.00688\n", + "  0.000144\n", + " -47.63\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_ivt_school_univ\n", + " -0.0106\n", + "  0.000322\n", + " -33.03\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_ivt_work\n", + " -0.00787\n", + "  0.000147\n", + " -53.42\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " coef_nest_AUTO\n", + "  0.720\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " coef_nest_AUTO_DRIVEALONE\n", + "  0.350\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " coef_nest_AUTO_SHAREDRIDE2\n", + "  0.350\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " coef_nest_AUTO_SHAREDRIDE3\n", + "  0.350\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " coef_nest_NONMOTORIZED\n", + "  0.720\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " coef_nest_RIDEHAIL\n", + "  0.360\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " coef_nest_TRANSIT\n", + "  0.720\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " coef_nest_TRANSIT_DRIVEACCESS\n", + "  0.500\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " coef_nest_TRANSIT_WALKACCESS\n", + "  0.500\n", + "  0.00\n", + "  NA\n", + " \n", + " 1.00\n", + " \n", + " \n", + " commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", + " -1.08\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " commuter_rail_ASC_school_univ\n", + " -0.338\n", + "  527.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " commuter_rail_ASC_work\n", + "  0.168\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", + " -0.764\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_ferry_ASC_school_univ\n", + "  1.41\n", + "  527.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_ferry_ASC_work\n", + "  0.187\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", + " -0.402\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_light_rail_ASC_school_univ\n", + "  0.615\n", + "  527.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_light_rail_ASC_work\n", + "  0.520\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_atwork\n", + " -999.\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_eatout\n", + " -0.277\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_escort\n", + " -2.24\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_othdiscr\n", + " -0.968\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_othmaint\n", + " -1.43\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_school\n", + "  1.63\n", + "  527.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_shopping\n", + " -1.68\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_social\n", + "  0.629\n", + "  266.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_univ\n", + "  1.85\n", + "  0.00197\n", + "  939.88\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_deficient_work\n", + " -0.896\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_atwork\n", + " -999.\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_eatout\n", + " -1.75\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_escort\n", + " -5.32\n", + "  266.\n", + " -0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_othdiscr\n", + " -1.27\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_othmaint\n", + " -2.85\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_school\n", + " -0.182\n", + "  527.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_shopping\n", + " -4.23\n", + "  266.\n", + " -0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_social\n", + " -1.47\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_univ\n", + "  1.36\n", + "  0.000573\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_auto_sufficient_work\n", + " -1.81\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_ASC_no_auto_all\n", + "  0.00\n", + "  0.000507\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " drive_transit_CBD_ASC_atwork\n", + "  0.564\n", + "  0.000881\n", + "  639.86\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social\n", + "  1.41\n", + "  0.142\n", + "  9.88\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " drive_transit_CBD_ASC_school_univ\n", + "  1.18\n", + "  0.250\n", + "  4.72\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " drive_transit_CBD_ASC_work\n", + "  1.65\n", + "  0.0699\n", + "  23.57\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " express_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", + " -0.396\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " express_bus_ASC_school_univ\n", + " -0.568\n", + "  527.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " express_bus_ASC_work\n", + " -0.917\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " heavy_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", + " -0.251\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " heavy_rail_ASC_school_univ\n", + " -0.00300\n", + "  527.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " heavy_rail_ASC_work\n", + "  0.495\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_bike_ASC_auto_deficient_all\n", + " -6.18\n", + "  1.39\n", + " -4.45\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " joint_bike_ASC_auto_sufficient_all\n", + " -7.13\n", + "  0.506\n", + " -14.09\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " joint_bike_ASC_no_auto_all\n", + " -2.70\n", + "  1.11\n", + " -2.43\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " joint_drive_transit_ASC_auto_deficient_all\n", + " -6.03\n", + "  266.\n", + " -0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_drive_transit_ASC_auto_sufficient_all\n", + " -7.80\n", + "  266.\n", + " -0.03\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_drive_transit_ASC_no_auto_all\n", + "  0.00\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_sr2_ASC_auto_deficient_all\n", + "  0.00\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_sr2_ASC_auto_sufficient_all\n", + "  0.00\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_sr2_ASC_no_auto_all\n", + "  0.00\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_sr3p_ASC_auto_deficient_all\n", + " -1.55\n", + "  0.265\n", + " -5.85\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " joint_sr3p_ASC_auto_sufficient_all\n", + " -2.28\n", + "  0.133\n", + " -17.16\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " joint_sr3p_ASC_no_auto_all\n", + "  0.656\n", + "  0.458\n", + "  1.43\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_taxi_ASC_auto_deficient_all\n", + " -9.82\n", + "  8.47\n", + " -1.16\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_taxi_ASC_auto_sufficient_all\n", + " -11.7\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_taxi_ASC_no_auto_all\n", + " -4.58\n", + "  4.30\n", + " -1.07\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_tnc_shared_ASC_auto_deficient_all\n", + " -11.2\n", + "  17.8\n", + " -0.63\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_tnc_shared_ASC_auto_sufficient_all\n", + " -13.2\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_tnc_shared_ASC_no_auto_all\n", + " -4.69\n", + "  2.26\n", + " -2.07\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " joint_tnc_single_ASC_auto_deficient_all\n", + " -9.90\n", + "  7.49\n", + " -1.32\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_tnc_single_ASC_auto_sufficient_all\n", + " -14.0\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_tnc_single_ASC_no_auto_all\n", + " -3.91\n", + "  2.15\n", + " -1.82\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_walk_ASC_auto_deficient_all\n", + " -2.24\n", + "  0.387\n", + " -5.78\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " joint_walk_ASC_auto_sufficient_all\n", + " -4.23\n", + "  0.246\n", + " -17.23\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " joint_walk_ASC_no_auto_all\n", + " -0.402\n", + "  0.729\n", + " -0.55\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_walk_transit_ASC_auto_deficient_all\n", + " -5.28\n", + "  266.\n", + " -0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_walk_transit_ASC_auto_sufficient_all\n", + " -18.3\n", + "  777.\n", + " -0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " joint_walk_transit_ASC_no_auto_all\n", + "  0.489\n", + "  266.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " local_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", + " -1.24\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " local_bus_ASC_school_univ\n", + " -0.934\n", + "  527.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " local_bus_ASC_work\n", + " -0.196\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_atwork\n", + " -1.58\n", + "  0.134\n", + " -11.80\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_eatout\n", + "  0.592\n", + "  0.145\n", + "  4.07\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_escort\n", + " -0.0768\n", + "  0.151\n", + " -0.51\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_othdiscr\n", + "  0.821\n", + "  0.119\n", + "  6.92\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_othmaint\n", + "  0.318\n", + "  0.135\n", + "  2.35\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_school\n", + "  0.162\n", + "  0.175\n", + "  0.93\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_shopping\n", + "  0.283\n", + "  0.115\n", + "  2.46\n", + " *\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_social\n", + "  1.99\n", + "  0.203\n", + "  9.83\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_univ\n", + " -1.69\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_deficient_work\n", + "  0.325\n", + "  0.0744\n", + "  4.36\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_atwork\n", + " -0.800\n", + "  0.0784\n", + " -10.21\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_eatout\n", + "  0.925\n", + "  0.0894\n", + "  10.35\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_escort\n", + "  0.188\n", + "  0.117\n", + "  1.61\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_othdiscr\n", + "  0.596\n", + "  0.0846\n", + "  7.05\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_othmaint\n", + "  0.416\n", + "  0.0870\n", + "  4.79\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_school\n", + " -1.23\n", + "  0.0803\n", + " -15.34\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_shopping\n", + "  0.292\n", + "  0.0841\n", + "  3.48\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_social\n", + "  0.641\n", + "  0.0953\n", + "  6.72\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_univ\n", + " -1.86\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_auto_sufficient_work\n", + " -0.396\n", + "  0.0705\n", + " -5.62\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr2_ASC_no_auto_all\n", + "  1.10\n", + "  77.7\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_atwork\n", + " -1.90\n", + "  0.138\n", + " -13.76\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_eatout\n", + " -0.120\n", + "  0.182\n", + " -0.66\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_escort\n", + " -0.301\n", + "  0.154\n", + " -1.96\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_othdiscr\n", + "  1.18\n", + "  0.112\n", + "  10.56\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_othmaint\n", + " -0.936\n", + "  0.225\n", + " -4.16\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_school\n", + "  0.708\n", + "  0.170\n", + "  4.16\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_shopping\n", + " -0.0640\n", + "  0.126\n", + " -0.51\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_social\n", + "  1.72\n", + "  0.212\n", + "  8.14\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_univ\n", + " -1.73\n", + "  0.000100\n", + " -BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_deficient_work\n", + " -0.219\n", + "  0.0779\n", + " -2.81\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_atwork\n", + " -0.984\n", + "  0.0796\n", + " -12.35\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_eatout\n", + "  0.898\n", + "  0.0894\n", + "  10.04\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_escort\n", + "  0.162\n", + "  0.117\n", + "  1.38\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_othdiscr\n", + "  0.697\n", + "  0.0841\n", + "  8.29\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_othmaint\n", + "  0.0330\n", + "  0.0899\n", + "  0.37\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_school\n", + " -0.663\n", + "  0.0792\n", + " -8.37\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_shopping\n", + "  0.0515\n", + "  0.0851\n", + "  0.61\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_social\n", + "  0.642\n", + "  0.0951\n", + "  6.75\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_univ\n", + " -1.90\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_auto_sufficient_work\n", + " -0.763\n", + "  0.0714\n", + " -10.68\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_atwork\n", + "  1.45\n", + "  77.7\n", + "  0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_eatout\n", + "  1.56\n", + "  77.7\n", + "  0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_escort\n", + " -1.86\n", + "  77.7\n", + " -0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_othdiscr\n", + "  1.27\n", + "  77.7\n", + "  0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_othmaint\n", + "  0.243\n", + "  77.7\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_school\n", + " -6.02\n", + "  102.\n", + " -0.06\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_shopping\n", + "  0.711\n", + "  77.7\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_social\n", + " -1.16\n", + "  77.7\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_univ\n", + " -6.06\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " sr3p_ASC_no_auto_work\n", + "  0.560\n", + "  77.7\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_deficient_atwork\n", + " -4.54\n", + "  0.419\n", + " -10.84\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_deficient_eatout_othdiscr_social\n", + " -3.37\n", + "  0.476\n", + " -7.09\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_deficient_escort_othmaint_shopping\n", + " -1.10\n", + "  0.109\n", + " -10.15\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_deficient_school\n", + "  0.626\n", + "  0.205\n", + "  3.05\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_deficient_univ\n", + "  4.25\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_deficient_work\n", + " -2.11\n", + "  0.191\n", + " -11.04\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_sufficient_atwork\n", + " -3.35\n", + "  0.151\n", + " -22.19\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_sufficient_eatout_othdiscr_social\n", + " -4.24\n", + "  0.278\n", + " -15.26\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_sufficient_escort_othmaint_shopping\n", + " -2.90\n", + "  0.0839\n", + " -34.57\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_sufficient_school\n", + " -2.68\n", + "  0.128\n", + " -20.89\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_sufficient_univ\n", + " -0.313\n", + "  2.26e-05\n", + " -BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_auto_sufficient_work\n", + " -5.12\n", + "  0.363\n", + " -14.09\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_no_auto_atwork\n", + "  3.64\n", + "  77.7\n", + "  0.05\n", + " \n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_no_auto_eatout_othdiscr_social\n", + " -0.558\n", + "  77.7\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_no_auto_escort_othmaint_shopping\n", + "  1.46\n", + "  77.7\n", + "  0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_no_auto_school_univ\n", + " -7.00\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " taxi_ASC_no_auto_work\n", + "  3.94\n", + "  77.7\n", + "  0.05\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_deficient_atwork\n", + " -5.10\n", + "  0.397\n", + " -12.85\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_deficient_eatout_othdiscr_social\n", + " -4.48\n", + "  0.814\n", + " -5.51\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_deficient_escort_othmaint_shopping\n", + " -1.38\n", + "  0.0981\n", + " -14.08\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_deficient_school\n", + "  0.0328\n", + "  0.199\n", + "  0.17\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_deficient_univ\n", + "  3.25\n", + "  1.81e-05\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_deficient_work\n", + " -3.60\n", + "  0.218\n", + " -16.52\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_sufficient_atwork\n", + " -4.09\n", + "  0.166\n", + " -24.61\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_sufficient_eatout_othdiscr_social\n", + " -4.53\n", + "  0.201\n", + " -22.49\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_sufficient_escort_othmaint_shopping\n", + " -3.38\n", + "  0.0779\n", + " -43.43\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_sufficient_school\n", + " -4.04\n", + "  0.158\n", + " -25.50\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_sufficient_univ\n", + " -0.907\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_auto_sufficient_work\n", + " -6.73\n", + "  0.417\n", + " -16.13\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_no_auto_atwork\n", + "  3.04\n", + "  77.7\n", + "  0.04\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_no_auto_eatout_othdiscr_social\n", + " -0.0561\n", + "  77.7\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_no_auto_escort_othmaint_shopping\n", + "  0.675\n", + "  77.7\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_no_auto_school\n", + " -7.00\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_no_auto_univ\n", + " -5.81\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_shared_ASC_no_auto_work\n", + "  2.26\n", + "  77.7\n", + "  0.03\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_deficient_atwork\n", + " -4.20\n", + "  0.308\n", + " -13.65\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_deficient_eatout_othdiscr_social\n", + " -3.40\n", + "  0.433\n", + " -7.84\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_deficient_escort_othmaint_shopping\n", + " -0.493\n", + "  0.0900\n", + " -5.48\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_deficient_school\n", + " -0.235\n", + "  0.239\n", + " -0.98\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_deficient_univ\n", + "  1.02\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_deficient_work\n", + " -1.42\n", + "  0.106\n", + " -13.40\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_sufficient_atwork\n", + " -3.14\n", + "  0.126\n", + " -25.00\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_sufficient_eatout_othdiscr_social\n", + " -3.44\n", + "  0.147\n", + " -23.37\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_sufficient_escort_othmaint_shopping\n", + " -2.31\n", + "  0.0677\n", + " -34.09\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_sufficient_school\n", + " -2.47\n", + "  0.110\n", + " -22.48\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_sufficient_univ\n", + "  0.209\n", + "  1.24e-05\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_auto_sufficient_work\n", + " -4.30\n", + "  0.174\n", + " -24.71\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_no_auto_atwork\n", + "  4.25\n", + "  77.7\n", + "  0.05\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_no_auto_eatout_othdiscr_social\n", + "  0.988\n", + "  77.7\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_no_auto_escort_othmaint_shopping\n", + "  1.61\n", + "  77.7\n", + "  0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_no_auto_school\n", + " -7.00\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_no_auto_univ\n", + " -2.52\n", + "  1.04e-05\n", + " -BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " tnc_single_ASC_no_auto_work\n", + "  5.36\n", + "  77.7\n", + "  0.07\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_atwork\n", + "  0.179\n", + "  0.125\n", + "  1.44\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_eatout\n", + "  1.97\n", + "  0.189\n", + "  10.38\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_escort\n", + " -2.25\n", + "  0.269\n", + " -8.35\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_othdiscr\n", + "  1.07\n", + "  0.146\n", + "  7.33\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_othmaint\n", + " -0.0496\n", + "  0.206\n", + " -0.24\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_school\n", + "  2.31\n", + "  0.190\n", + "  12.13\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_shopping\n", + "  0.790\n", + "  0.128\n", + "  6.18\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_social\n", + "  2.06\n", + "  0.291\n", + "  7.09\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_univ\n", + "  4.51\n", + "  9.40e-06\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_deficient_work\n", + "  1.60\n", + "  0.0818\n", + "  19.57\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_atwork\n", + "  0.0778\n", + "  0.0580\n", + "  1.34\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_eatout\n", + "  0.530\n", + "  0.0933\n", + "  5.68\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_escort\n", + " -1.81\n", + "  0.106\n", + " -17.07\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_othdiscr\n", + "  0.218\n", + "  0.0663\n", + "  3.28\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_othmaint\n", + " -0.244\n", + "  0.0814\n", + " -2.99\n", + " **\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_school\n", + " -0.101\n", + "  0.0864\n", + " -1.17\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_shopping\n", + " -0.368\n", + "  0.0638\n", + " -5.76\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_social\n", + "  0.469\n", + "  0.107\n", + "  4.39\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_univ\n", + "  1.06\n", + "  3.73e-07\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_auto_sufficient_work\n", + " -0.393\n", + "  0.0617\n", + " -6.37\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_atwork\n", + "  6.64\n", + "  77.7\n", + "  0.09\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_eatout\n", + "  4.42\n", + "  77.7\n", + "  0.06\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_escort\n", + "  2.50\n", + "  77.7\n", + "  0.03\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_othdiscr\n", + "  2.90\n", + "  77.7\n", + "  0.04\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_othmaint\n", + "  0.919\n", + "  77.7\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_school\n", + "  17.8\n", + "  106.\n", + "  0.17\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_shopping\n", + "  2.17\n", + "  77.7\n", + "  0.03\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_social\n", + "  1.71\n", + "  77.7\n", + "  0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_univ\n", + "  6.41\n", + "  1.10e-07\n", + "  BIG\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_ASC_no_auto_work\n", + "  5.32\n", + "  77.7\n", + "  0.07\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", + " -0.371\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ferry_ASC_school_univ\n", + "  0.875\n", + "  527.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_ferry_ASC_work\n", + "  0.153\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork\n", + " -0.197\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_light_rail_ASC_school_univ\n", + "  0.611\n", + "  527.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_light_rail_ASC_work\n", + "  0.753\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_atwork\n", + " -2.55\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_eatout\n", + " -0.608\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_escort\n", + " -4.51\n", + "  266.\n", + " -0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_othdiscr\n", + "  0.823\n", + "  266.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_othmaint\n", + " -3.04\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_school\n", + "  2.82\n", + "  527.\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_shopping\n", + " -1.17\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_social\n", + "  1.30\n", + "  266.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_univ\n", + "  3.14\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_deficient_work\n", + "  0.0872\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_atwork\n", + " -3.57\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_eatout\n", + " -1.34\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_escort\n", + " -4.99\n", + "  266.\n", + " -0.02\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_othdiscr\n", + " -0.924\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_othmaint\n", + " -1.71\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_school\n", + "  0.156\n", + "  527.\n", + "  0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_shopping\n", + " -2.38\n", + "  266.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_social\n", + " -0.668\n", + "  266.\n", + " -0.00\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_univ\n", + "  0.473\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_auto_sufficient_work\n", + " -1.43\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_atwork\n", + "  3.19\n", + "  280.\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_eatout\n", + "  3.02\n", + "  280.\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_escort\n", + " -2.25\n", + "  280.\n", + " -0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_othdiscr\n", + "  2.90\n", + "  280.\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_othmaint\n", + "  2.65\n", + "  280.\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_school\n", + "  20.6\n", + "  524.\n", + "  0.04\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_shopping\n", + "  2.45\n", + "  280.\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_social\n", + "  2.11\n", + "  280.\n", + "  0.01\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_univ\n", + "  8.79\n", + "  0.00\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_ASC_no_auto_work\n", + "  4.67\n", + "  NA\n", + "  NA\n", + " \n", + " 0.00\n", + " \n", + " \n", + " walk_transit_CBD_ASC_atwork\n", + "  1.15\n", + "  0.283\n", + "  4.05\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social\n", + "  1.07\n", + "  0.0756\n", + "  14.20\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_transit_CBD_ASC_school_univ\n", + "  0.819\n", + "  0.114\n", + "  7.16\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + " walk_transit_CBD_ASC_work\n", + "  1.16\n", + "  0.0539\n", + "  21.50\n", + " ***\n", + " 0.00\n", + " \n", + " \n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.parameter_summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "TojXWivZsx7M" + }, + "source": [ + "# Output Estimation Results" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "from activitysim.estimation.larch import update_coefficients\n", + "result_dir = data.edb_directory/\"estimated\"\n", + "update_coefficients(\n", + " model, data, result_dir,\n", + " output_file=f\"{modelname}_coefficients_revised.csv\",\n", + ");" ] }, { @@ -4376,16 +4217,7 @@ "cell_type": "code", "execution_count": 14, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jeffnewman/LocalGit/larch/larch/util/excel.py:521: FutureWarning: Use of **kwargs is deprecated, use engine_kwargs instead.\n", - " xl = ExcelWriter(filename, engine='xlsxwriter_larch', model=model, **kwargs)\n" - ] - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -4473,25 +4305,25 @@ " \n", " 302\n", " walk_transit_CBD_ASC_atwork\n", - " 0.351950\n", + " 1.146544\n", " F\n", " \n", " \n", " 303\n", " drive_transit_CBD_ASC_eatout_escort_othdiscr_o...\n", - " 0.553404\n", + " 1.407306\n", " F\n", " \n", " \n", " 304\n", " drive_transit_CBD_ASC_school_univ\n", - " 62.459413\n", + " 1.179871\n", " F\n", " \n", " \n", " 305\n", " drive_transit_CBD_ASC_work\n", - " 1.432631\n", + " 1.648397\n", " F\n", " \n", " \n", @@ -4506,18 +4338,18 @@ "" ], "text/plain": [ - " coefficient_name value constrain\n", - "0 coef_one 1.000000 T\n", - "1 coef_nest_root 1.000000 T\n", - "2 coef_nest_AUTO 0.720000 T\n", - "3 coef_nest_AUTO_DRIVEALONE 0.350000 T\n", - "4 coef_nest_AUTO_SHAREDRIDE2 0.350000 T\n", - ".. ... ... ...\n", - "302 walk_transit_CBD_ASC_atwork 0.351950 F\n", - "303 drive_transit_CBD_ASC_eatout_escort_othdiscr_o... 0.553404 F\n", - "304 drive_transit_CBD_ASC_school_univ 62.459413 F\n", - "305 drive_transit_CBD_ASC_work 1.432631 F\n", - "306 drive_transit_CBD_ASC_atwork 0.564000 F\n", + " coefficient_name value constrain\n", + "0 coef_one 1.000000 T\n", + "1 coef_nest_root 1.000000 T\n", + "2 coef_nest_AUTO 0.720000 T\n", + "3 coef_nest_AUTO_DRIVEALONE 0.350000 T\n", + "4 coef_nest_AUTO_SHAREDRIDE2 0.350000 T\n", + ".. ... ... ...\n", + "302 walk_transit_CBD_ASC_atwork 1.146544 F\n", + "303 drive_transit_CBD_ASC_eatout_escort_othdiscr_o... 1.407306 F\n", + "304 drive_transit_CBD_ASC_school_univ 1.179871 F\n", + "305 drive_transit_CBD_ASC_work 1.648397 F\n", + "306 drive_transit_CBD_ASC_atwork 0.564000 F\n", "\n", "[307 rows x 3 columns]" ] @@ -4539,7 +4371,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -4553,7 +4385,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/18_atwork_subtour_freq.ipynb b/activitysim/examples/example_estimation/notebooks/18_atwork_subtour_freq.ipynb index 4bd5cd1f3e..9d92886e00 100644 --- a/activitysim/examples/example_estimation/notebooks/18_atwork_subtour_freq.ipynb +++ b/activitysim/examples/example_estimation/notebooks/18_atwork_subtour_freq.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -68,12 +115,27 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_frequency/atwork_subtour_frequency_coefficients.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/atwork_subtour_frequency/atwork_subtour_frequency_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_frequency/atwork_subtour_frequency_values_combined.parquet\n" + ] + } + ], "source": [ "modelname = \"atwork_subtour_frequency\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -752,11 +814,11 @@ " util_individual_discretionary_tours_made_by_full_time_worker\n", " util_individual_discretionary_tours_made_by_part_time_worker\n", " ...\n", - " TERMINAL\n", - " household_density\n", - " employment_density\n", - " density_index\n", - " is_cbd\n", + " trPkTotal\n", + " trOpRetail\n", + " trOpTotal\n", + " nmRetail\n", + " nmTotal\n", " num_maint_shop_escort\n", " num_joint_discr\n", " num_joint_maint_shop_eat\n", @@ -790,31 +852,31 @@ " \n", " \n", " \n", - " 2998943\n", - " maint\n", - " maint\n", + " 2966594\n", + " no_subtours\n", + " eat\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 2.48345\n", - " 26.073171\n", - " 8.048780\n", - " 6.150212\n", - " False\n", + " 9.119016\n", + " 6.446184\n", + " 9.035333\n", + " 5.256966\n", + " 6.831275\n", " 0\n", " 0\n", " 0\n", " False\n", - " 3\n", + " 1\n", " \n", " \n", - " 3060361\n", + " 3046667\n", " eat\n", " eat\n", " 1.0\n", @@ -826,45 +888,45 @@ " 0.0\n", " 0.0\n", " ...\n", - " 2.09035\n", - " 20.666667\n", - " 4.107527\n", - " 3.426505\n", - " False\n", + " 7.771767\n", + " 5.298242\n", + " 7.602426\n", + " 6.443514\n", + " 7.965548\n", " 0\n", " 0\n", " 0\n", - " True\n", + " False\n", " 1\n", " \n", " \n", - " 4422914\n", - " eat\n", + " 3048143\n", + " no_subtours\n", " eat\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 5.35435\n", - " 139.333333\n", - " 418.518519\n", - " 104.532377\n", - " False\n", + " 7.771767\n", + " 5.298242\n", + " 7.602426\n", + " 6.443514\n", + " 7.965548\n", " 0\n", " 0\n", " 0\n", - " False\n", + " True\n", " 1\n", " \n", " \n", - " 4440298\n", - " maint\n", - " maint\n", + " 3177498\n", + " no_subtours\n", + " eat\n", " 1.0\n", " 0.0\n", " 0.0\n", @@ -874,39 +936,39 @@ " 0.0\n", " 0.0\n", " ...\n", - " 5.22542\n", - " 97.634722\n", - " 550.205552\n", - " 82.920387\n", - " False\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " 0\n", " 0\n", " 0\n", - " False\n", - " 3\n", + " True\n", + " 1\n", " \n", " \n", - " 4496796\n", - " maint\n", + " 3191848\n", + " eat\n", " maint\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 4.73802\n", - " 117.769796\n", - " 246.205869\n", - " 79.663609\n", - " False\n", + " 3.278544\n", + " 1.239060\n", + " 3.280429\n", + " 4.284159\n", + " 6.249753\n", " 0\n", " 0\n", " 0\n", - " False\n", + " True\n", " 3\n", " \n", " \n", @@ -934,258 +996,258 @@ " ...\n", " \n", " \n", - " 302923742\n", - " maint\n", - " maint\n", + " 308156039\n", + " no_subtours\n", + " eat\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 2.37546\n", - " 19.153846\n", - " 5.907692\n", - " 4.515087\n", - " False\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 3.086628\n", + " 5.647842\n", " 0\n", " 0\n", " 0\n", - " True\n", - " 3\n", + " False\n", + " 1\n", " \n", " \n", - " 302942602\n", - " eat\n", - " eat\n", + " 308227666\n", + " no_subtours\n", + " maint\n", + " 0.0\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 2.81406\n", - " 16.068376\n", - " 21.136752\n", - " 9.128669\n", - " False\n", + " 7.890189\n", + " 4.493279\n", + " 7.643024\n", + " 5.529241\n", + " 8.876000\n", " 0\n", " 0\n", " 0\n", " True\n", - " 1\n", + " 3\n", " \n", " \n", - " 302942643\n", - " maint\n", - " maint\n", + " 308260138\n", + " no_subtours\n", + " eat\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 2.81406\n", - " 16.068376\n", - " 21.136752\n", - " 9.128669\n", - " False\n", + " 7.614481\n", + " 3.838266\n", + " 7.011926\n", + " 5.169891\n", + " 8.595128\n", " 0\n", " 0\n", " 0\n", " False\n", - " 3\n", + " 1\n", " \n", " \n", - " 305120481\n", - " maint\n", - " maint\n", + " 309080753\n", + " no_subtours\n", + " eat\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 8.54946\n", - " 55.606634\n", - " 142.984438\n", - " 40.036459\n", - " False\n", + " 9.892019\n", + " 6.979741\n", + " 9.773601\n", + " 6.557982\n", + " 8.518901\n", " 0\n", " 0\n", " 0\n", " False\n", - " 3\n", + " 1\n", " \n", " \n", - " 308000690\n", - " maint\n", + " 309112036\n", " maint\n", - " 0.0\n", + " eat\n", " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.0\n", + " 0.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 4.64648\n", - " 196.395950\n", - " 178.779465\n", - " 93.587057\n", - " False\n", + " 0.222696\n", + " 0.016077\n", + " 0.153189\n", + " 0.000000\n", + " 0.000000\n", " 0\n", " 0\n", " 0\n", - " False\n", - " 3\n", + " True\n", + " 1\n", " \n", " \n", "\n", - "

460 rows × 182 columns

\n", + "

5947 rows × 182 columns

\n", "" ], "text/plain": [ " model_choice override_choice util_dummy_for_full_time_worker \\\n", "tour_id \n", - "2998943 maint maint 1.0 \n", - "3060361 eat eat 1.0 \n", - "4422914 eat eat 1.0 \n", - "4440298 maint maint 1.0 \n", - "4496796 maint maint 1.0 \n", + "2966594 no_subtours eat 1.0 \n", + "3046667 eat eat 1.0 \n", + "3048143 no_subtours eat 1.0 \n", + "3177498 no_subtours eat 1.0 \n", + "3191848 eat maint 1.0 \n", "... ... ... ... \n", - "302923742 maint maint 1.0 \n", - "302942602 eat eat 1.0 \n", - "302942643 maint maint 1.0 \n", - "305120481 maint maint 1.0 \n", - "308000690 maint maint 0.0 \n", + "308156039 no_subtours eat 1.0 \n", + "308227666 no_subtours maint 0.0 \n", + "308260138 no_subtours eat 1.0 \n", + "309080753 no_subtours eat 1.0 \n", + "309112036 maint eat 1.0 \n", "\n", " util_dummy_for_non_full_time_worker util_dummy_for_non_workers \\\n", "tour_id \n", - "2998943 0.0 0.0 \n", - "3060361 0.0 0.0 \n", - "4422914 0.0 0.0 \n", - "4440298 0.0 0.0 \n", - "4496796 0.0 0.0 \n", + "2966594 0.0 0.0 \n", + "3046667 0.0 0.0 \n", + "3048143 0.0 0.0 \n", + "3177498 0.0 0.0 \n", + "3191848 0.0 0.0 \n", "... ... ... \n", - "302923742 0.0 0.0 \n", - "302942602 0.0 0.0 \n", - "302942643 0.0 0.0 \n", - "305120481 0.0 0.0 \n", - "308000690 1.0 0.0 \n", + "308156039 0.0 0.0 \n", + "308227666 1.0 0.0 \n", + "308260138 0.0 0.0 \n", + "309080753 0.0 0.0 \n", + "309112036 0.0 0.0 \n", "\n", " util_medium_hh_income_dummy util_high_hh_income_dummy \\\n", "tour_id \n", - "2998943 0.0 0.0 \n", - "3060361 0.0 0.0 \n", - "4422914 0.0 0.0 \n", - "4440298 0.0 0.0 \n", - "4496796 0.0 0.0 \n", + "2966594 0.0 0.0 \n", + "3046667 0.0 0.0 \n", + "3048143 0.0 0.0 \n", + "3177498 0.0 0.0 \n", + "3191848 0.0 0.0 \n", "... ... ... \n", - "302923742 0.0 1.0 \n", - "302942602 0.0 1.0 \n", - "302942643 0.0 1.0 \n", - "305120481 0.0 1.0 \n", - "308000690 0.0 0.0 \n", + "308156039 0.0 0.0 \n", + "308227666 0.0 0.0 \n", + "308260138 0.0 0.0 \n", + "309080753 0.0 0.0 \n", + "309112036 0.0 0.0 \n", "\n", " util_zero_cars_owned_by_hh_dummy \\\n", "tour_id \n", - "2998943 1.0 \n", - "3060361 0.0 \n", - "4422914 1.0 \n", - "4440298 0.0 \n", - "4496796 1.0 \n", + "2966594 0.0 \n", + "3046667 0.0 \n", + "3048143 0.0 \n", + "3177498 0.0 \n", + "3191848 0.0 \n", "... ... \n", - "302923742 0.0 \n", - "302942602 0.0 \n", - "302942643 0.0 \n", - "305120481 0.0 \n", - "308000690 1.0 \n", + "308156039 0.0 \n", + "308227666 0.0 \n", + "308260138 0.0 \n", + "309080753 1.0 \n", + "309112036 0.0 \n", "\n", " util_individual_discretionary_tours_made_by_full_time_worker \\\n", "tour_id \n", - "2998943 0.0 \n", - "3060361 0.0 \n", - "4422914 0.0 \n", - "4440298 0.0 \n", - "4496796 0.0 \n", + "2966594 0.0 \n", + "3046667 0.0 \n", + "3048143 0.0 \n", + "3177498 0.0 \n", + "3191848 0.0 \n", "... ... \n", - "302923742 0.0 \n", - "302942602 0.0 \n", - "302942643 0.0 \n", - "305120481 0.0 \n", - "308000690 0.0 \n", + "308156039 0.0 \n", + "308227666 0.0 \n", + "308260138 0.0 \n", + "309080753 0.0 \n", + "309112036 0.0 \n", "\n", " util_individual_discretionary_tours_made_by_part_time_worker ... \\\n", "tour_id ... \n", - "2998943 0.0 ... \n", - "3060361 0.0 ... \n", - "4422914 0.0 ... \n", - "4440298 0.0 ... \n", - "4496796 0.0 ... \n", + "2966594 0.0 ... \n", + "3046667 0.0 ... \n", + "3048143 0.0 ... \n", + "3177498 0.0 ... \n", + "3191848 0.0 ... \n", "... ... ... \n", - "302923742 0.0 ... \n", - "302942602 0.0 ... \n", - "302942643 0.0 ... \n", - "305120481 0.0 ... \n", - "308000690 0.0 ... \n", + "308156039 0.0 ... \n", + "308227666 0.0 ... \n", + "308260138 0.0 ... \n", + "309080753 0.0 ... \n", + "309112036 0.0 ... \n", "\n", - " TERMINAL household_density employment_density density_index \\\n", - "tour_id \n", - "2998943 2.48345 26.073171 8.048780 6.150212 \n", - "3060361 2.09035 20.666667 4.107527 3.426505 \n", - "4422914 5.35435 139.333333 418.518519 104.532377 \n", - "4440298 5.22542 97.634722 550.205552 82.920387 \n", - "4496796 4.73802 117.769796 246.205869 79.663609 \n", - "... ... ... ... ... \n", - "302923742 2.37546 19.153846 5.907692 4.515087 \n", - "302942602 2.81406 16.068376 21.136752 9.128669 \n", - "302942643 2.81406 16.068376 21.136752 9.128669 \n", - "305120481 8.54946 55.606634 142.984438 40.036459 \n", - "308000690 4.64648 196.395950 178.779465 93.587057 \n", + " trPkTotal trOpRetail trOpTotal nmRetail nmTotal \\\n", + "tour_id \n", + "2966594 9.119016 6.446184 9.035333 5.256966 6.831275 \n", + "3046667 7.771767 5.298242 7.602426 6.443514 7.965548 \n", + "3048143 7.771767 5.298242 7.602426 6.443514 7.965548 \n", + "3177498 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "3191848 3.278544 1.239060 3.280429 4.284159 6.249753 \n", + "... ... ... ... ... ... \n", + "308156039 0.000000 0.000000 0.000000 3.086628 5.647842 \n", + "308227666 7.890189 4.493279 7.643024 5.529241 8.876000 \n", + "308260138 7.614481 3.838266 7.011926 5.169891 8.595128 \n", + "309080753 9.892019 6.979741 9.773601 6.557982 8.518901 \n", + "309112036 0.222696 0.016077 0.153189 0.000000 0.000000 \n", "\n", - " is_cbd num_maint_shop_escort num_joint_discr \\\n", - "tour_id \n", - "2998943 False 0 0 \n", - "3060361 False 0 0 \n", - "4422914 False 0 0 \n", - "4440298 False 0 0 \n", - "4496796 False 0 0 \n", - "... ... ... ... \n", - "302923742 False 0 0 \n", - "302942602 False 0 0 \n", - "302942643 False 0 0 \n", - "305120481 False 0 0 \n", - "308000690 False 0 0 \n", + " num_maint_shop_escort num_joint_discr num_joint_maint_shop_eat \\\n", + "tour_id \n", + "2966594 0 0 0 \n", + "3046667 0 0 0 \n", + "3048143 0 0 0 \n", + "3177498 0 0 0 \n", + "3191848 0 0 0 \n", + "... ... ... ... \n", + "308156039 0 0 0 \n", + "308227666 0 0 0 \n", + "308260138 0 0 0 \n", + "309080753 0 0 0 \n", + "309112036 0 0 0 \n", "\n", - " num_joint_maint_shop_eat work_tour_is_SOV override_choice_code \n", - "tour_id \n", - "2998943 0 False 3 \n", - "3060361 0 True 1 \n", - "4422914 0 False 1 \n", - "4440298 0 False 3 \n", - "4496796 0 False 3 \n", - "... ... ... ... \n", - "302923742 0 True 3 \n", - "302942602 0 True 1 \n", - "302942643 0 False 3 \n", - "305120481 0 False 3 \n", - "308000690 0 False 3 \n", + " work_tour_is_SOV override_choice_code \n", + "tour_id \n", + "2966594 False 1 \n", + "3046667 False 1 \n", + "3048143 True 1 \n", + "3177498 True 1 \n", + "3191848 True 3 \n", + "... ... ... \n", + "308156039 False 1 \n", + "308227666 True 3 \n", + "308260138 False 1 \n", + "309080753 False 1 \n", + "309112036 True 1 \n", "\n", - "[460 rows x 182 columns]" + "[5947 rows x 182 columns]" ] }, "execution_count": 6, @@ -1211,17 +1273,10 @@ "execution_count": 7, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

Iteration 075 [Optimization terminated successfully]

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Iteration 100 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1233,7 +1288,7 @@ { "data": { "text/html": [ - "

Best LL = -311.0816324383027

" + "

Best LL = -4832.223778692503

" ], "text/plain": [ "" @@ -1264,70 +1319,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coefficient_at_work_sub_tour_asc_business1\n", - " 1.421407\n", + " -0.350395\n", + " -0.350395\n", " -0.5372\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 1.421407\n", " \n", " \n", " coefficient_at_work_sub_tour_asc_business2\n", - " -0.130778\n", + " -2.211281\n", + " -2.211281\n", " -2.1337\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.130778\n", " \n", " \n", " coefficient_at_work_sub_tour_asc_eat\n", - " 5.809056\n", + " 0.440311\n", + " 0.440311\n", " 0.8576\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 5.809056\n", " \n", " \n", " coefficient_at_work_sub_tour_asc_eat_business\n", - " -23.415363\n", + " -0.860366\n", + " -0.860366\n", " -0.9721\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -23.415363\n", " \n", " \n", " coefficient_at_work_sub_tour_asc_maint\n", - " 12.910479\n", + " -0.423469\n", + " -0.423469\n", " -0.6198\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 12.910479\n", " \n", " \n", " ...\n", @@ -1338,122 +1397,120 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_business1\n", - " -0.526876\n", + " -0.633755\n", + " -0.633755\n", " -0.3391\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.526876\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_business2\n", " 0.000000\n", + " 0.000000\n", " 0.0000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_eat\n", " 0.000000\n", + " 0.000000\n", " 0.0000\n", " 0.0\n", - " NaN\n", - " NaN\n", + " 0.0\n", + " 0.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_eat_business\n", - " -19.116288\n", + " -0.847707\n", + " -0.847707\n", " -0.3391\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -19.116288\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_maint\n", - " 0.559350\n", + " -0.020836\n", + " -0.020836\n", " 0.1762\n", + " -50.0\n", + " 50.0\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.559350\n", " \n", " \n", "\n", - "

110 rows × 8 columns

\n", + "

110 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coefficient_at_work_sub_tour_asc_business1 1.421407 -0.5372 \n", - "coefficient_at_work_sub_tour_asc_business2 -0.130778 -2.1337 \n", - "coefficient_at_work_sub_tour_asc_eat 5.809056 0.8576 \n", - "coefficient_at_work_sub_tour_asc_eat_business -23.415363 -0.9721 \n", - "coefficient_at_work_sub_tour_asc_maint 12.910479 -0.6198 \n", - "... ... ... \n", - "coefficient_zero_cars_owned_by_hh_dummy_business1 -0.526876 -0.3391 \n", - "coefficient_zero_cars_owned_by_hh_dummy_business2 0.000000 0.0000 \n", - "coefficient_zero_cars_owned_by_hh_dummy_eat 0.000000 0.0000 \n", - "coefficient_zero_cars_owned_by_hh_dummy_eat_bus... -19.116288 -0.3391 \n", - "coefficient_zero_cars_owned_by_hh_dummy_maint 0.559350 0.1762 \n", + " value best \\\n", + "param_name \n", + "coefficient_at_work_sub_tour_asc_business1 -0.350395 -0.350395 \n", + "coefficient_at_work_sub_tour_asc_business2 -2.211281 -2.211281 \n", + "coefficient_at_work_sub_tour_asc_eat 0.440311 0.440311 \n", + "coefficient_at_work_sub_tour_asc_eat_business -0.860366 -0.860366 \n", + "coefficient_at_work_sub_tour_asc_maint -0.423469 -0.423469 \n", + "... ... ... \n", + "coefficient_zero_cars_owned_by_hh_dummy_business1 -0.633755 -0.633755 \n", + "coefficient_zero_cars_owned_by_hh_dummy_business2 0.000000 0.000000 \n", + "coefficient_zero_cars_owned_by_hh_dummy_eat 0.000000 0.000000 \n", + "coefficient_zero_cars_owned_by_hh_dummy_eat_bus... -0.847707 -0.847707 \n", + "coefficient_zero_cars_owned_by_hh_dummy_maint -0.020836 -0.020836 \n", "\n", - " nullvalue minimum \\\n", - "coefficient_at_work_sub_tour_asc_business1 0.0 NaN \n", - "coefficient_at_work_sub_tour_asc_business2 0.0 NaN \n", - "coefficient_at_work_sub_tour_asc_eat 0.0 NaN \n", - "coefficient_at_work_sub_tour_asc_eat_business 0.0 NaN \n", - "coefficient_at_work_sub_tour_asc_maint 0.0 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coefficient_at_work_sub_tour_asc_business1 -0.5372 -50.0 \n", + "coefficient_at_work_sub_tour_asc_business2 -2.1337 -50.0 \n", + "coefficient_at_work_sub_tour_asc_eat 0.8576 -50.0 \n", + "coefficient_at_work_sub_tour_asc_eat_business -0.9721 -50.0 \n", + "coefficient_at_work_sub_tour_asc_maint -0.6198 -50.0 \n", "... ... ... \n", - "coefficient_zero_cars_owned_by_hh_dummy_business1 0.0 NaN \n", - "coefficient_zero_cars_owned_by_hh_dummy_business2 0.0 NaN \n", - "coefficient_zero_cars_owned_by_hh_dummy_eat 0.0 NaN \n", - "coefficient_zero_cars_owned_by_hh_dummy_eat_bus... 0.0 NaN \n", - "coefficient_zero_cars_owned_by_hh_dummy_maint 0.0 NaN \n", + "coefficient_zero_cars_owned_by_hh_dummy_business1 -0.3391 -50.0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_business2 0.0000 0.0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_eat 0.0000 0.0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_eat_bus... -0.3391 -50.0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_maint 0.1762 -50.0 \n", "\n", - " maximum holdfast note \\\n", - "coefficient_at_work_sub_tour_asc_business1 NaN 0 \n", - "coefficient_at_work_sub_tour_asc_business2 NaN 0 \n", - "coefficient_at_work_sub_tour_asc_eat NaN 0 \n", - "coefficient_at_work_sub_tour_asc_eat_business NaN 0 \n", - "coefficient_at_work_sub_tour_asc_maint NaN 0 \n", - "... ... ... ... \n", - "coefficient_zero_cars_owned_by_hh_dummy_business1 NaN 0 \n", - "coefficient_zero_cars_owned_by_hh_dummy_business2 NaN 1 \n", - "coefficient_zero_cars_owned_by_hh_dummy_eat NaN 1 \n", - "coefficient_zero_cars_owned_by_hh_dummy_eat_bus... NaN 0 \n", - "coefficient_zero_cars_owned_by_hh_dummy_maint NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coefficient_at_work_sub_tour_asc_business1 50.0 0.0 \n", + "coefficient_at_work_sub_tour_asc_business2 50.0 0.0 \n", + "coefficient_at_work_sub_tour_asc_eat 50.0 0.0 \n", + "coefficient_at_work_sub_tour_asc_eat_business 50.0 0.0 \n", + "coefficient_at_work_sub_tour_asc_maint 50.0 0.0 \n", + "... ... ... \n", + "coefficient_zero_cars_owned_by_hh_dummy_business1 50.0 0.0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_business2 0.0 0.0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_eat 0.0 0.0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_eat_bus... 50.0 0.0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_maint 50.0 0.0 \n", "\n", - " best \n", - "coefficient_at_work_sub_tour_asc_business1 1.421407 \n", - "coefficient_at_work_sub_tour_asc_business2 -0.130778 \n", - "coefficient_at_work_sub_tour_asc_eat 5.809056 \n", - "coefficient_at_work_sub_tour_asc_eat_business -23.415363 \n", - "coefficient_at_work_sub_tour_asc_maint 12.910479 \n", - "... ... \n", - "coefficient_zero_cars_owned_by_hh_dummy_business1 -0.526876 \n", - "coefficient_zero_cars_owned_by_hh_dummy_business2 0.000000 \n", - "coefficient_zero_cars_owned_by_hh_dummy_eat 0.000000 \n", - "coefficient_zero_cars_owned_by_hh_dummy_eat_bus... -19.116288 \n", - "coefficient_zero_cars_owned_by_hh_dummy_maint 0.559350 \n", + " holdfast \n", + "param_name \n", + "coefficient_at_work_sub_tour_asc_business1 0 \n", + "coefficient_at_work_sub_tour_asc_business2 0 \n", + "coefficient_at_work_sub_tour_asc_eat 0 \n", + "coefficient_at_work_sub_tour_asc_eat_business 0 \n", + "coefficient_at_work_sub_tour_asc_maint 0 \n", + "... ... \n", + "coefficient_zero_cars_owned_by_hh_dummy_business1 0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_business2 1 \n", + "coefficient_zero_cars_owned_by_hh_dummy_eat 1 \n", + "coefficient_zero_cars_owned_by_hh_dummy_eat_bus... 0 \n", + "coefficient_zero_cars_owned_by_hh_dummy_maint 0 \n", "\n", - "[110 rows x 8 columns]" + "[110 rows x 7 columns]" ] }, "metadata": {}, @@ -1463,12 +1520,8 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate(method='SLSQP')\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 5.5647113087279e-33 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - ":1: RuntimeWarning: invalid value encountered in sqrt\n", - " model.estimate(method='SLSQP')\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { @@ -1484,446 +1537,446 @@ " \n", " \n", " coefficient_at_work_sub_tour_asc_business1\n", - " 1.421407e+00\n", + " -0.350395\n", " \n", " \n", " coefficient_at_work_sub_tour_asc_business2\n", - " -1.307783e-01\n", + " -2.211281\n", " \n", " \n", " coefficient_at_work_sub_tour_asc_eat\n", - " 5.809056e+00\n", + " 0.440311\n", " \n", " \n", " coefficient_at_work_sub_tour_asc_eat_business\n", - " -2.341536e+01\n", + " -0.860366\n", " \n", " \n", " coefficient_at_work_sub_tour_asc_maint\n", - " 1.291048e+01\n", + " -0.423469\n", " \n", " \n", " coefficient_auto_accessibility_to_retail_for_work_taz_business1\n", - " -2.350832e-01\n", + " 0.078156\n", " \n", " \n", " coefficient_auto_accessibility_to_retail_for_work_taz_business2\n", - " 2.951134e+00\n", + " 0.295708\n", " \n", " \n", " coefficient_auto_accessibility_to_retail_for_work_taz_eat\n", - " -7.610481e-01\n", + " 0.137215\n", " \n", " \n", " coefficient_auto_accessibility_to_retail_for_work_taz_eat_business\n", - " 1.515548e+00\n", + " -0.262951\n", " \n", " \n", " coefficient_auto_accessibility_to_retail_for_work_taz_maint\n", - " -3.200651e+00\n", + " 0.021772\n", " \n", " \n", " coefficient_dummy_for_drive_alone_mode_for_work_tour_business1\n", - " 3.943802e+00\n", + " 0.949692\n", " \n", " \n", " coefficient_dummy_for_drive_alone_mode_for_work_tour_business2\n", - " -7.285121e+00\n", + " 1.745346\n", " \n", " \n", " coefficient_dummy_for_drive_alone_mode_for_work_tour_eat\n", - " 3.216240e+00\n", + " 0.488173\n", " \n", " \n", " coefficient_dummy_for_drive_alone_mode_for_work_tour_eat_business\n", - " 2.333483e+00\n", + " 1.784643\n", " \n", " \n", " coefficient_dummy_for_drive_alone_mode_for_work_tour_maint\n", - " 3.865797e+00\n", + " 1.106347\n", " \n", " \n", " coefficient_dummy_for_full_time_worker_business1\n", - " -1.136529e+01\n", + " -7.402415\n", " \n", " \n", " coefficient_dummy_for_full_time_worker_business2\n", - " -1.383392e+01\n", + " -13.824988\n", " \n", " \n", " coefficient_dummy_for_full_time_worker_eat\n", - " -9.545916e+00\n", + " -7.551797\n", " \n", " \n", " coefficient_dummy_for_full_time_worker_eat_business\n", - " -1.119217e+01\n", + " -14.974823\n", " \n", " \n", " coefficient_dummy_for_full_time_worker_maint\n", - " -5.880704e+00\n", + " -8.063977\n", " \n", " \n", " coefficient_dummy_for_non_full_time_worker_business1\n", - " -2.370101e+00\n", + " -8.104781\n", " \n", " \n", " coefficient_dummy_for_non_full_time_worker_business2\n", - " -1.272316e+01\n", + " -14.812593\n", " \n", " \n", " coefficient_dummy_for_non_full_time_worker_eat\n", - " -1.386629e+00\n", + " -8.749492\n", " \n", " \n", " coefficient_dummy_for_non_full_time_worker_eat_business\n", - " -4.083109e+01\n", + " -14.493442\n", " \n", " \n", " coefficient_dummy_for_non_full_time_worker_maint\n", - " 3.103983e+00\n", + " -8.046692\n", " \n", " \n", " coefficient_dummy_for_non_workers_business1\n", - " -5.000000e+00\n", + " -5.000000\n", " \n", " \n", " coefficient_dummy_for_non_workers_business2\n", - " -5.000000e+00\n", + " -5.000000\n", " \n", " \n", " coefficient_dummy_for_non_workers_eat\n", - " -3.678488e-14\n", + " 0.000000\n", " \n", " \n", " coefficient_dummy_for_non_workers_eat_business\n", - " -5.000000e+00\n", + " -5.000000\n", " \n", " \n", " coefficient_dummy_for_non_workers_maint\n", - " -5.000000e+00\n", + " -5.000000\n", " \n", " \n", " coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business1\n", - " 5.542765e-14\n", + " 0.000000\n", " \n", " \n", " coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business2\n", - " -6.800386e-14\n", + " 0.000000\n", " \n", " \n", " coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat\n", - " -7.803277e-15\n", + " 0.000000\n", " \n", " \n", " coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat_business\n", - " 9.964378e-15\n", + " 0.000000\n", " \n", " \n", " coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_maint\n", - " -4.465435e-01\n", + " -0.857652\n", " \n", " \n", " coefficient_high_hh_income_dummy_business1\n", - " -5.699484e+00\n", + " 1.051824\n", " \n", " \n", " coefficient_high_hh_income_dummy_business2\n", - " 1.817758e+01\n", + " 1.775205\n", " \n", " \n", " coefficient_high_hh_income_dummy_eat\n", - " -5.360138e+00\n", + " 0.987000\n", " \n", " \n", " coefficient_high_hh_income_dummy_eat_business\n", - " 5.949348e+00\n", + " 2.165299\n", " \n", " \n", " coefficient_high_hh_income_dummy_maint\n", - " -6.899602e+00\n", + " 0.188372\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_full_time_worker_business1\n", - " -1.423867e+00\n", + " 0.746021\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_full_time_worker_business2\n", - " 1.949725e+01\n", + " 0.764494\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_full_time_worker_eat\n", - " -1.457980e+00\n", + " 0.315100\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_full_time_worker_eat_business\n", - " -1.111294e+01\n", + " 1.303968\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_full_time_worker_maint\n", - " -1.711559e+00\n", + " 0.661317\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_part_time_worker_business1\n", - " 1.701675e+00\n", + " 0.057399\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_part_time_worker_business2\n", - " 1.531338e+00\n", + " 2.149968\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_part_time_worker_eat\n", - " 9.815649e-01\n", + " 0.034146\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_part_time_worker_eat_business\n", - " 2.152744e-01\n", + " 1.416263\n", " \n", " \n", " coefficient_individual_discretionary_tours_made_by_part_time_worker_maint\n", - " 2.494477e-01\n", + " 1.021525\n", " \n", " \n", " coefficient_individual_eating_out_tours_made_by_person_business1\n", - " 4.249081e-01\n", + " 0.263548\n", " \n", " \n", " coefficient_individual_eating_out_tours_made_by_person_business2\n", - " 1.688422e+01\n", + " 1.149846\n", " \n", " \n", " coefficient_individual_eating_out_tours_made_by_person_eat\n", - " -2.110385e-01\n", + " 0.231645\n", " \n", " \n", " coefficient_individual_eating_out_tours_made_by_person_eat_business\n", - " -1.375749e+01\n", + " 1.418076\n", " \n", " \n", " coefficient_individual_eating_out_tours_made_by_person_maint\n", - " 8.477993e-01\n", + " 1.125285\n", " \n", " \n", " coefficient_log_of_the_work_tour_duration_business1\n", - " 1.079743e+01\n", + " 1.007122\n", " \n", " \n", " coefficient_log_of_the_work_tour_duration_business2\n", - " -4.104113e+01\n", + " 1.771287\n", " \n", " \n", " coefficient_log_of_the_work_tour_duration_eat\n", - " 9.912072e+00\n", + " 1.458489\n", " \n", " \n", " coefficient_log_of_the_work_tour_duration_eat_business\n", - " 1.921602e+01\n", + " 3.447598\n", " \n", " \n", " coefficient_log_of_the_work_tour_duration_maint\n", - " 1.044261e+01\n", + " 1.642504\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business1\n", - " 5.245200e+00\n", + " -0.181697\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business2\n", - " -5.957409e+00\n", + " -0.328201\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat\n", - " 5.734339e+00\n", + " -0.013286\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat_business\n", - " -1.136555e+01\n", + " -0.788124\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_full_time_worker_maint\n", - " 5.726820e+00\n", + " 0.694707\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business1\n", - " -1.437920e+01\n", + " -0.005852\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business2\n", - " 1.824373e-01\n", + " -0.444998\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat\n", - " 6.645087e+00\n", + " -0.120943\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat_business\n", - " -4.922608e-01\n", + " -1.170010\n", " \n", " \n", " coefficient_main_shop_escort_tours_allocated_to_part_time_worker_maint\n", - " 6.390638e+00\n", + " 0.088504\n", " \n", " \n", " coefficient_medium_hh_income_dummy_business1\n", - " -3.286293e+00\n", + " 0.374955\n", " \n", " \n", " coefficient_medium_hh_income_dummy_business2\n", - " 2.006070e+00\n", + " 1.384595\n", " \n", " \n", " coefficient_medium_hh_income_dummy_eat\n", - " -2.530097e+00\n", + " 0.467235\n", " \n", " \n", " coefficient_medium_hh_income_dummy_eat_business\n", - " 1.050098e+01\n", + " 1.373736\n", " \n", " \n", " coefficient_medium_hh_income_dummy_maint\n", - " -3.095965e+00\n", + " -0.005820\n", " \n", " \n", " coefficient_participation_in_joint_discretionary_tours_business1\n", - " 8.878328e-01\n", + " 0.075698\n", " \n", " \n", " coefficient_participation_in_joint_discretionary_tours_business2\n", - " -4.199835e-01\n", + " -0.191769\n", " \n", " \n", " coefficient_participation_in_joint_discretionary_tours_eat\n", - " -2.448175e-01\n", + " 0.454516\n", " \n", " \n", " coefficient_participation_in_joint_discretionary_tours_eat_business\n", - " -2.723876e+00\n", + " -0.681551\n", " \n", " \n", " coefficient_participation_in_joint_discretionary_tours_maint\n", - " 2.745844e+00\n", + " 0.588105\n", " \n", " \n", " coefficient_participation_in_joint_shop_main_eat_tours_business1\n", - " 3.561155e+00\n", + " 0.151268\n", " \n", " \n", " coefficient_participation_in_joint_shop_main_eat_tours_business2\n", - " -2.800502e-01\n", + " 0.232018\n", " \n", " \n", " coefficient_participation_in_joint_shop_main_eat_tours_eat\n", - " 1.988637e+00\n", + " -0.054088\n", " \n", " \n", " coefficient_participation_in_joint_shop_main_eat_tours_eat_business\n", - " -6.545173e+00\n", + " 0.928998\n", " \n", " \n", " coefficient_participation_in_joint_shop_main_eat_tours_maint\n", - " 2.179332e+00\n", + " -0.354297\n", " \n", " \n", " coefficient_two_work_tours_by_person_business1\n", - " 3.694023e+00\n", + " 0.343052\n", " \n", " \n", " coefficient_two_work_tours_by_person_business2\n", - " -4.104683e+00\n", + " 0.672564\n", " \n", " \n", " coefficient_two_work_tours_by_person_eat\n", - " 1.927236e+00\n", + " -0.903976\n", " \n", " \n", " coefficient_two_work_tours_by_person_eat_business\n", - " -5.424974e+00\n", + " -1.029881\n", " \n", " \n", " coefficient_two_work_tours_by_person_maint\n", - " 3.205997e+00\n", + " 0.215840\n", " \n", " \n", " coefficient_walk_accessibility_to_retail_for_work_taz_business1\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coefficient_walk_accessibility_to_retail_for_work_taz_business2\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coefficient_walk_accessibility_to_retail_for_work_taz_eat\n", - " 5.329379e-02\n", + " 0.054262\n", " \n", " \n", " coefficient_walk_accessibility_to_retail_for_work_taz_eat_business\n", - " -4.690165e-01\n", + " 0.248444\n", " \n", " \n", " coefficient_walk_accessibility_to_retail_for_work_taz_maint\n", - " 3.930491e-01\n", + " 0.051297\n", " \n", " \n", " coefficient_workplace_suburban_area_dummy_business1\n", - " -1.102000e-01\n", + " -0.077046\n", " \n", " \n", " coefficient_workplace_suburban_area_dummy_business2\n", - " -2.204000e-01\n", + " -0.214908\n", " \n", " \n", " coefficient_workplace_suburban_area_dummy_eat\n", - " -2.916000e-01\n", + " -0.497064\n", " \n", " \n", " coefficient_workplace_suburban_area_dummy_eat_business\n", - " -4.018000e-01\n", + " -0.496303\n", " \n", " \n", " coefficient_workplace_suburban_area_dummy_maint\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coefficient_workplace_urban_area_dummy_business1\n", - " 1.735107e+00\n", + " -0.069849\n", " \n", " \n", " coefficient_workplace_urban_area_dummy_business2\n", - " 1.555922e+00\n", + " -0.530073\n", " \n", " \n", " coefficient_workplace_urban_area_dummy_eat\n", - " 4.533256e+00\n", + " -0.630025\n", " \n", " \n", " coefficient_workplace_urban_area_dummy_eat_business\n", - " -2.308496e+01\n", + " -0.435462\n", " \n", " \n", " coefficient_workplace_urban_area_dummy_maint\n", - " 1.338238e+01\n", + " -0.212890\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_business1\n", - " -5.268759e-01\n", + " -0.633755\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_business2\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_eat\n", - " 0.000000e+00\n", + " 0.000000\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_eat_business\n", - " -1.911629e+01\n", + " -0.847707\n", " \n", " \n", " coefficient_zero_cars_owned_by_hh_dummy_maint\n", - " 5.593497e-01\n", + " -0.020836\n", " \n", " \n", - "loglike-311.0816324383027d_loglike\n", + "
logloss0.8125481383373976d_logloss\n", " \n", " \n", " \n", @@ -1933,103 +1986,103 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2069,227 +2122,227 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2301,31 +2354,31 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2333,27 +2386,27 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2365,52 +2418,52 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - "
coefficient_at_work_sub_tour_asc_business1-1.481164e-04-2.181632e-05
coefficient_at_work_sub_tour_asc_business2-2.230083e-05-7.974611e-06
coefficient_at_work_sub_tour_asc_eat1.390294e-046.885959e-05
coefficient_at_work_sub_tour_asc_eat_business1.539374e-04-5.704460e-06
coefficient_at_work_sub_tour_asc_maint-1.225496e-04-3.336420e-05
coefficient_auto_accessibility_to_retail_for_work_taz_business1-1.603725e-031.678059e-05
coefficient_auto_accessibility_to_retail_for_work_taz_business2-2.219798e-04-7.241747e-05
coefficient_auto_accessibility_to_retail_for_work_taz_eat1.752293e-03-6.082835e-05
coefficient_auto_accessibility_to_retail_for_work_taz_eat_business1.320801e-038.064174e-05
coefficient_auto_accessibility_to_retail_for_work_taz_maint-1.247389e-033.582349e-05
coefficient_dummy_for_drive_alone_mode_for_work_tour_business1-9.593191e-05-4.107213e-05
coefficient_dummy_for_drive_alone_mode_for_work_tour_business2-1.354692e-055.986918e-05
coefficient_dummy_for_drive_alone_mode_for_work_tour_eat-2.279001e-047.033209e-05
coefficient_dummy_for_drive_alone_mode_for_work_tour_eat_business4.011519e-04-9.447444e-06
coefficient_dummy_for_drive_alone_mode_for_work_tour_maint-6.377298e-05-7.968169e-05
coefficient_dummy_for_full_time_worker_business1-1.605243e-042.817589e-05
coefficient_dummy_for_full_time_worker_business2-2.230083e-053.226183e-05
coefficient_dummy_for_full_time_worker_eat7.303158e-051.003712e-04
coefficient_dummy_for_full_time_worker_eat_business1.539374e-041.549190e-05
coefficient_dummy_for_full_time_worker_maint-4.414386e-05-1.763008e-04
coefficient_dummy_for_non_full_time_worker_business11.240794e-05-4.999221e-05
coefficient_dummy_for_non_full_time_worker_business2-7.261864e-17-4.023644e-05
coefficient_dummy_for_non_full_time_worker_eat6.599780e-05-3.151158e-05
coefficient_dummy_for_non_full_time_worker_eat_business-1.086362e-18-2.119636e-05
coefficient_dummy_for_non_full_time_worker_maint-7.840574e-051.429366e-04
coefficient_dummy_for_non_workers_business1
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_maint-9.311590e-05-1.714819e-04
coefficient_high_hh_income_dummy_business1-1.000616e-04-1.191730e-05
coefficient_high_hh_income_dummy_business2-8.753913e-06-7.059313e-05
coefficient_high_hh_income_dummy_eat-2.221195e-06-5.126677e-05
coefficient_high_hh_income_dummy_eat_business2.213370e-048.255506e-05
coefficient_high_hh_income_dummy_maint-1.103003e-045.122214e-05
coefficient_individual_discretionary_tours_made_by_full_time_worker_business1-7.053640e-05-1.226983e-05
coefficient_individual_discretionary_tours_made_by_full_time_worker_business2-2.791062e-057.360525e-05
coefficient_individual_discretionary_tours_made_by_full_time_worker_eat1.818022e-04-3.188124e-05
coefficient_individual_discretionary_tours_made_by_full_time_worker_eat_business-2.707632e-066.305075e-07
coefficient_individual_discretionary_tours_made_by_full_time_worker_maint-8.064758e-05-3.008468e-05
coefficient_individual_discretionary_tours_made_by_part_time_worker_business1-9.603037e-06-2.903966e-05
coefficient_individual_discretionary_tours_made_by_part_time_worker_business2-1.629515e-19-1.376988e-05
coefficient_individual_discretionary_tours_made_by_part_time_worker_eat-3.348668e-072.058728e-05
coefficient_individual_discretionary_tours_made_by_part_time_worker_eat_business-1.124861e-22-3.015319e-05
coefficient_individual_discretionary_tours_made_by_part_time_worker_maint9.937904e-065.237545e-05
coefficient_individual_eating_out_tours_made_by_person_business1-7.862028e-05-1.667468e-04
coefficient_individual_eating_out_tours_made_by_person_business2-8.753608e-06-3.264570e-05
coefficient_individual_eating_out_tours_made_by_person_eat3.564089e-052.212368e-05
coefficient_individual_eating_out_tours_made_by_person_eat_business-1.309491e-079.515601e-06
coefficient_individual_eating_out_tours_made_by_person_maint5.186395e-051.677532e-04
coefficient_log_of_the_work_tour_duration_business1-3.971369e-041.043468e-04
coefficient_log_of_the_work_tour_duration_business2-2.991023e-058.913429e-06
coefficient_log_of_the_work_tour_duration_eat3.149096e-041.295254e-05
coefficient_log_of_the_work_tour_duration_eat_business3.910540e-04-1.066273e-04
coefficient_log_of_the_work_tour_duration_maint-2.789165e-04-1.958540e-05
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business18.932382e-064.643980e-05
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business2-1.299699e-05-2.188999e-05
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat-8.667554e-051.650779e-04
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat_business-1.119625e-084.743178e-05
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_maint9.075134e-05-2.370595e-04
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business1-4.914227e-102.357735e-05
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business2-2.173636e-16-1.188907e-05
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat-2.658044e-067.570065e-05
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat_business-7.964540e-24-3.983432e-05
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_maint2.658536e-06-4.755461e-05
coefficient_medium_hh_income_dummy_business1-5.984683e-053.482667e-05
coefficient_medium_hh_income_dummy_business2-8.619829e-275.769942e-05
coefficient_medium_hh_income_dummy_eat1.446985e-04-5.137537e-06
coefficient_medium_hh_income_dummy_eat_business-6.509501e-05-5.711674e-05
coefficient_medium_hh_income_dummy_maint-1.975668e-05-3.027181e-05
coefficient_participation_in_joint_discretionary_tours_business11.633148e-05-5.693164e-05
coefficient_participation_in_joint_discretionary_tours_business2-3.971146e-267.289406e-05
coefficient_participation_in_joint_discretionary_tours_eat8.138286e-051.061065e-04
coefficient_participation_in_joint_discretionary_tours_eat_business-5.416119e-05-9.568225e-05
coefficient_participation_in_joint_discretionary_tours_maint-4.355316e-05-2.638670e-05
coefficient_participation_in_joint_shop_main_eat_tours_business1-1.005486e-044.632880e-05
coefficient_participation_in_joint_shop_main_eat_tours_business2-1.490847e-157.216085e-07
coefficient_participation_in_joint_shop_main_eat_tours_eat1.024581e-04-6.996621e-05
coefficient_participation_in_joint_shop_main_eat_tours_eat_business-8.904994e-071.708229e-06
coefficient_participation_in_joint_shop_main_eat_tours_maint-1.018973e-062.120756e-05
coefficient_two_work_tours_by_person_business17.076435e-059.533131e-05
coefficient_two_work_tours_by_person_business2-3.049929e-10-7.711784e-06
coefficient_two_work_tours_by_person_eat1.336457e-05-5.696558e-06
coefficient_two_work_tours_by_person_eat_business-1.430779e-06-5.510631e-05
coefficient_two_work_tours_by_person_maint-8.269783e-05-2.681666e-05
coefficient_walk_accessibility_to_retail_for_work_taz_business1
coefficient_walk_accessibility_to_retail_for_work_taz_eat2.395850e-038.877549e-05
coefficient_walk_accessibility_to_retail_for_work_taz_eat_business-5.362286e-045.191476e-05
coefficient_walk_accessibility_to_retail_for_work_taz_maint-6.315696e-04-3.267917e-05
coefficient_workplace_suburban_area_dummy_business10.000000e+00-2.911572e-05
coefficient_workplace_suburban_area_dummy_business20.000000e+00-3.969147e-06
coefficient_workplace_suburban_area_dummy_eat0.000000e+002.978185e-05
coefficient_workplace_suburban_area_dummy_eat_business0.000000e+00-8.309287e-06
coefficient_workplace_suburban_area_dummy_maint
coefficient_workplace_urban_area_dummy_business1-1.481164e-047.299400e-06
coefficient_workplace_urban_area_dummy_business2-2.230083e-05-4.005464e-06
coefficient_workplace_urban_area_dummy_eat1.390294e-043.907774e-05
coefficient_workplace_urban_area_dummy_eat_business1.539374e-042.604827e-06
coefficient_workplace_urban_area_dummy_maint-1.225496e-04-4.497650e-05
coefficient_zero_cars_owned_by_hh_dummy_business1-2.241883e-04-1.324894e-05
coefficient_zero_cars_owned_by_hh_dummy_business2
coefficient_zero_cars_owned_by_hh_dummy_eat_business-4.538836e-09-8.057484e-05
coefficient_zero_cars_owned_by_hh_dummy_maint-3.467043e-05-2.405112e-05
nit75nfev115njev75status0message'Optimization terminated successfully'successTrueelapsed_time0:00:01.501390method'SLSQP'n_cases460iteration_number75logloss0.6762644183441363" + "nit100nfev104njev100status0message'Optimization terminated successfully'successTrueelapsed_time0:00:00.874759method'SLSQP'n_cases5947iteration_number100loglike-4832.223778692503" ], "text/plain": [ - "┣ x: coefficient_at_work_sub_tour_asc_business1 1.421407\n", - "┃ coefficient_at_work_sub_tour_asc_business2 -0.130778\n", - "┃ coefficient_at_work_sub_tour_asc_eat 5.809056\n", - "┃ coefficient_at_work_sub_tour_asc_eat_business -23.415363\n", - "┃ coefficient_at_work_sub_tour_asc_maint 12.910479\n", - "┃ ... \n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_business1 -0.526876\n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_business2 0.000000\n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_eat 0.000000\n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_eat_business -19.116288\n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_maint 0.559350\n", + "┣ x: coefficient_at_work_sub_tour_asc_business1 -0.350395\n", + "┃ coefficient_at_work_sub_tour_asc_business2 -2.211281\n", + "┃ coefficient_at_work_sub_tour_asc_eat 0.440311\n", + "┃ coefficient_at_work_sub_tour_asc_eat_business -0.860366\n", + "┃ coefficient_at_work_sub_tour_asc_maint -0.423469\n", + "┃ ... \n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_business1 -0.633755\n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_business2 0.000000\n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_eat 0.000000\n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_eat_business -0.847707\n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_maint -0.020836\n", "┃ Length: 110, dtype: float64\n", - "┣ loglike: -311.0816324383027\n", - "┣ d_loglike: coefficient_at_work_sub_tour_asc_business1 -1.481164e-04\n", - "┃ coefficient_at_work_sub_tour_asc_business2 -2.230083e-05\n", - "┃ coefficient_at_work_sub_tour_asc_eat 1.390294e-04\n", - "┃ coefficient_at_work_sub_tour_asc_eat_business 1.539374e-04\n", - "┃ coefficient_at_work_sub_tour_asc_maint -1.225496e-04\n", - "┃ ... \n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_business1 -2.241883e-04\n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_business2 0.000000e+00\n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_eat 0.000000e+00\n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_eat_business -4.538836e-09\n", - "┃ coefficient_zero_cars_owned_by_hh_dummy_maint -3.467043e-05\n", + "┣ logloss: 0.8125481383373976\n", + "┣ d_logloss: coefficient_at_work_sub_tour_asc_business1 -0.000022\n", + "┃ coefficient_at_work_sub_tour_asc_business2 -0.000008\n", + "┃ coefficient_at_work_sub_tour_asc_eat 0.000069\n", + "┃ coefficient_at_work_sub_tour_asc_eat_business -0.000006\n", + "┃ coefficient_at_work_sub_tour_asc_maint -0.000033\n", + "┃ ... \n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_business1 -0.000013\n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_business2 0.000000\n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_eat 0.000000\n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_eat_business -0.000081\n", + "┃ coefficient_zero_cars_owned_by_hh_dummy_maint -0.000024\n", "┃ Length: 110, dtype: float64\n", - "┣ nit: 75\n", - "┣ nfev: 115\n", - "┣ njev: 75\n", + "┣ nit: 100\n", + "┣ nfev: 104\n", + "┣ njev: 100\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=1, microseconds=501390)\n", + "┣ elapsed_time: datetime.timedelta(microseconds=874759)\n", "┣ method: 'SLSQP'\n", - "┣ n_cases: 460\n", - "┣ iteration_number: 75\n", - "┣ logloss: 0.6762644183441363" + "┣ n_cases: 5947\n", + "┣ iteration_number: 100\n", + "┣ loglike: -4832.223778692503" ] }, "execution_count": 7, @@ -2419,7 +2472,7 @@ } ], "source": [ - "model.estimate(method='SLSQP')" + "model.estimate(method='SLSQP', maxiter=900)" ] }, { @@ -2437,1120 +2490,1036 @@ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
coefficient_at_work_sub_tour_asc_business1 1.42 NA NA[***] 29.59 0.00
coefficient_at_work_sub_tour_asc_business2-0.131 1.51e+04-0.00 NA 0.00
coefficient_at_work_sub_tour_asc_eat 5.81 484. 0.01 NA 0.00
coefficient_at_work_sub_tour_asc_eat_business-23.4 NA NA[***] BIG 0.00
coefficient_at_work_sub_tour_asc_maint 12.9 523. 0.02 NA 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_business1-0.235 NA NA[***] 181.30 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_business2 2.95 2.55e+03 0.00 NA 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_eat-0.761 NA NA[***] 714.04 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_eat_business 1.52 NA NA[***] 41.92 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_maint-3.20 NA NA[***] BIG 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_business1 3.94 NA NA[***] 77.39 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_business2-7.29 NA NA[] 0.02 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_eat 3.22 NA NA[***] 201.21 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_eat_business 2.33 NA NA[] 1.40 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_maint 3.87 NA NA[***] 79.47 0.00
coefficient_dummy_for_full_time_worker_business1-11.4 NA NA[***] BIG 0.00
coefficient_dummy_for_full_time_worker_business2-13.8 NA NA[**] 5.21 0.00
coefficient_dummy_for_full_time_worker_eat-9.55 NA NA[***] 827.25 0.00
coefficient_dummy_for_full_time_worker_eat_business-11.2 NA NA[***] BIG 0.00
coefficient_dummy_for_full_time_worker_maint-5.88 260.-0.02 NA 0.00
coefficient_dummy_for_non_full_time_worker_business1-2.37 1.09e+03-0.00 NA 0.00
coefficient_dummy_for_non_full_time_worker_business2-12.7 NA NA[] 0.00 0.00
coefficient_dummy_for_non_full_time_worker_eat-1.39 1.96e+03-0.00 NA 0.00
coefficient_dummy_for_non_full_time_worker_eat_business-40.8 NA NA[] 1.24 0.00
coefficient_dummy_for_non_full_time_worker_maint 3.10 2.40e+03 0.00 NA 0.00
coefficient_dummy_for_non_workers_business1-5.00 NA NA NA 0.00fixed value
coefficient_dummy_for_non_workers_business2-5.00 NA NA NA 0.00fixed value
coefficient_dummy_for_non_workers_eat 0.00 NA NA NA 0.00fixed value
coefficient_dummy_for_non_workers_eat_business-5.00 NA NA NA 0.00fixed value
coefficient_dummy_for_non_workers_maint-5.00 NA NA NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business1 0.00 NA NA NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business2 0.00 NA NA NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat 0.00 NA NA NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat_business 0.00 NA NA NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_maint-0.447 0.821-0.54 NA 0.00
coefficient_high_hh_income_dummy_business1-5.70 NA NA[***] 900.87 0.00
coefficient_high_hh_income_dummy_business2 18.2 NA NA[***] 5.91 0.00
coefficient_high_hh_income_dummy_eat-5.36 NA NA[***] 296.55 0.00
coefficient_high_hh_income_dummy_eat_business 5.95 430. 0.01 NA 0.00
coefficient_high_hh_income_dummy_maint-6.90 NA NA[***] BIG 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_business1-1.42 540.-0.00 NA 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_business2 19.5 4.34e+03 0.00 NA 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_eat-1.46 540.-0.00 NA 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_eat_business-11.1 806.-0.01 NA 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_maint-1.71 540.-0.00 NA 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_business1 1.70 NA NA[] 0.74 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_business2 1.53 0.000562 BIG*** NA 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_eat 0.982 NA NA[] 0.40 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_eat_business 0.215 0.000123 BIG*** NA 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_maint 0.249 NA NA[] 0.02 0.00
coefficient_individual_eating_out_tours_made_by_person_business1 0.425 NA NA[] 0.26 0.00
coefficient_individual_eating_out_tours_made_by_person_business2 16.9 NA NA[**] 4.62 0.00
coefficient_individual_eating_out_tours_made_by_person_eat-0.211 NA NA[] 0.12 0.00
coefficient_individual_eating_out_tours_made_by_person_eat_business-13.8 2.41e+03-0.01 NA 0.00
coefficient_individual_eating_out_tours_made_by_person_maint 0.848 NA NA[] 1.11 0.00
coefficient_log_of_the_work_tour_duration_business1 10.8 NA NA[***] BIG 0.00
coefficient_log_of_the_work_tour_duration_business2-41.0 4.06e+03-0.01 NA 0.00
coefficient_log_of_the_work_tour_duration_eat 9.91 NA NA[***] BIG 0.00
coefficient_log_of_the_work_tour_duration_eat_business 19.2 NA NA[***] 151.19 0.00
coefficient_log_of_the_work_tour_duration_maint 10.4 NA NA[***] BIG 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business1 5.25 NA NA[***] 17.02 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business2-5.96 1.41e+04-0.00 NA 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat 5.73 NA NA[***] 170.02 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat_business-11.4 7.01e+03-0.00 NA 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_maint 5.73 NA NA[***] 19.07 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business1-14.4 NA NA[] 0.00 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business2 0.182 NA NA[] 0.00 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat 6.65 5.15e+03 0.00 NA 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat_business-0.492 NA NA[] 0.00 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_maint 6.39 5.15e+03 0.00 NA 0.00
coefficient_medium_hh_income_dummy_business1-3.29 1.13e+03-0.00 NA 0.00
coefficient_medium_hh_income_dummy_business2 2.01 NA NA[] 0.00 0.00
coefficient_medium_hh_income_dummy_eat-2.53 1.13e+03-0.00 NA 0.00
coefficient_medium_hh_income_dummy_eat_business 10.5 1.27e+03 0.01 NA 0.00
coefficient_medium_hh_income_dummy_maint-3.10 1.13e+03-0.00 NA 0.00
coefficient_participation_in_joint_discretionary_tours_business1 0.888 NA NA[] 0.23 0.00
coefficient_participation_in_joint_discretionary_tours_business2-0.420 NA NA[] 0.00 0.00
coefficient_participation_in_joint_discretionary_tours_eat-0.245 NA NA[] 0.02 0.00
coefficient_participation_in_joint_discretionary_tours_eat_business-2.72 NA NA[] 0.00 0.00
coefficient_participation_in_joint_discretionary_tours_maint 2.75 NA NA[*] 2.92 0.00
coefficient_participation_in_joint_shop_main_eat_tours_business1 3.56 1.13e+03 0.00 NA 0.00
coefficient_participation_in_joint_shop_main_eat_tours_business2-0.280 NA NA[] 0.00 0.00
coefficient_participation_in_joint_shop_main_eat_tours_eat 1.99 1.13e+03 0.00 NA 0.00
coefficient_participation_in_joint_shop_main_eat_tours_eat_business-6.55 1.38e+03-0.00 NA 0.00
coefficient_participation_in_joint_shop_main_eat_tours_maint 2.18 1.13e+03 0.00 NA 0.00
coefficient_two_work_tours_by_person_business1 3.69 NA NA[**] 5.16 0.00
coefficient_two_work_tours_by_person_business2-4.10 2.72e+03-0.00 NA 0.00
coefficient_two_work_tours_by_person_eat 1.93 NA NA[**] 4.09 0.00
coefficient_two_work_tours_by_person_eat_business-5.42 NA NA[] 0.00 0.00
coefficient_two_work_tours_by_person_maint 3.21 NA NA[**] 4.07 0.00
coefficient_walk_accessibility_to_retail_for_work_taz_business1 0.00 NA NA NA 0.00fixed value
coefficient_walk_accessibility_to_retail_for_work_taz_business2 0.00 NA NA NA 0.00fixed value
coefficient_walk_accessibility_to_retail_for_work_taz_eat 0.0533 0.234 0.23 NA 0.00
coefficient_walk_accessibility_to_retail_for_work_taz_eat_business-0.469 0.669-0.70 NA 0.00
coefficient_walk_accessibility_to_retail_for_work_taz_maint 0.393 0.308 1.28 NA 0.00
coefficient_workplace_suburban_area_dummy_business1-0.110 0.00 NA[] 0.00 0.00
coefficient_workplace_suburban_area_dummy_business2-0.220 0.00 NA[] 0.00 0.00
coefficient_workplace_suburban_area_dummy_eat-0.292 0.00 NA[] 0.00 0.00
coefficient_workplace_suburban_area_dummy_eat_business-0.402 0.00 NA[] 0.00 0.00
coefficient_workplace_suburban_area_dummy_maint 0.00 NA NA NA 0.00fixed value
coefficient_workplace_urban_area_dummy_business1 1.74 NA NA[***] 41.10 0.00
coefficient_workplace_urban_area_dummy_business2 1.56 NA NA[]-0.00 0.00
coefficient_workplace_urban_area_dummy_eat 4.53 NA NA[***] 890.88 0.00
coefficient_workplace_urban_area_dummy_eat_business-23.1 NA NA[***] BIG 0.00
coefficient_workplace_urban_area_dummy_maint 13.4 579. 0.02 NA 0.00
coefficient_zero_cars_owned_by_hh_dummy_business1-0.527 0.582-0.90 NA 0.00
coefficient_zero_cars_owned_by_hh_dummy_business2 0.00 NA NA NA 0.00fixed value
coefficient_zero_cars_owned_by_hh_dummy_eat 0.00 NA NA NA 0.00fixed value
coefficient_zero_cars_owned_by_hh_dummy_eat_business-19.1 1.36e+04-0.00 NA 0.00
coefficient_zero_cars_owned_by_hh_dummy_maint 0.559 0.426 1.31 NA 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coefficient_at_work_sub_tour_asc_business1-0.350 1.10e+03-0.00 0.00
coefficient_at_work_sub_tour_asc_business2-2.21 2.21e+03-0.00 0.00
coefficient_at_work_sub_tour_asc_eat 0.440 NA NA 0.00
coefficient_at_work_sub_tour_asc_eat_business-0.860 495.-0.00 0.00
coefficient_at_work_sub_tour_asc_maint-0.423 NA NA 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_business1 0.0782 NA NA 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_business2 0.296 NA NA 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_eat 0.137 NA NA 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_eat_business-0.263 NA NA 0.00
coefficient_auto_accessibility_to_retail_for_work_taz_maint 0.0218 NA NA 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_business1 0.950 NA NA 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_business2 1.75 NA NA 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_eat 0.488 NA NA 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_eat_business 1.78 NA NA 0.00
coefficient_dummy_for_drive_alone_mode_for_work_tour_maint 1.11 NA NA 0.00
coefficient_dummy_for_full_time_worker_business1-7.40 552.-0.01 0.00
coefficient_dummy_for_full_time_worker_business2-13.8 1.67e+03-0.01 0.00
coefficient_dummy_for_full_time_worker_eat-7.55 1.25e+03-0.01 0.00
coefficient_dummy_for_full_time_worker_eat_business-15.0 2.70e+03-0.01 0.00
coefficient_dummy_for_full_time_worker_maint-8.06 1.60e+03-0.01 0.00
coefficient_dummy_for_non_full_time_worker_business1-8.10 687.-0.01 0.00
coefficient_dummy_for_non_full_time_worker_business2-14.8 1.52e+03-0.01 0.00
coefficient_dummy_for_non_full_time_worker_eat-8.75 1.58e+03-0.01 0.00
coefficient_dummy_for_non_full_time_worker_eat_business-14.5 2.34e+03-0.01 0.00
coefficient_dummy_for_non_full_time_worker_maint-8.05 2.29e+03-0.00 0.00
coefficient_dummy_for_non_workers_business1-5.00 0.00 NA 0.00fixed value
coefficient_dummy_for_non_workers_business2-5.00 0.00 NA 0.00fixed value
coefficient_dummy_for_non_workers_eat 0.00 0.00 NA 0.00fixed value
coefficient_dummy_for_non_workers_eat_business-5.00 0.00 NA 0.00fixed value
coefficient_dummy_for_non_workers_maint-5.00 0.00 NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business1 0.00 0.00 NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business2 0.00 0.00 NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat 0.00 0.00 NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat_business 0.00 0.00 NA 0.00fixed value
coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_maint-0.858 0.324-2.64** 0.00
coefficient_high_hh_income_dummy_business1 1.05 733. 0.00 0.00
coefficient_high_hh_income_dummy_business2 1.78 733. 0.00 0.00
coefficient_high_hh_income_dummy_eat 0.987 733. 0.00 0.00
coefficient_high_hh_income_dummy_eat_business 2.17 733. 0.00 0.00
coefficient_high_hh_income_dummy_maint 0.188 733. 0.00 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_business1 0.746 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_business2 0.764 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_eat 0.315 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_eat_business 1.30 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_full_time_worker_maint 0.661 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_business1 0.0574 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_business2 2.15 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_eat 0.0341 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_eat_business 1.42 NA NA 0.00
coefficient_individual_discretionary_tours_made_by_part_time_worker_maint 1.02 NA NA 0.00
coefficient_individual_eating_out_tours_made_by_person_business1 0.264 NA NA 0.00
coefficient_individual_eating_out_tours_made_by_person_business2 1.15 NA NA 0.00
coefficient_individual_eating_out_tours_made_by_person_eat 0.232 NA NA 0.00
coefficient_individual_eating_out_tours_made_by_person_eat_business 1.42 NA NA 0.00
coefficient_individual_eating_out_tours_made_by_person_maint 1.13 NA NA 0.00
coefficient_log_of_the_work_tour_duration_business1 1.01 288. 0.00 0.00
coefficient_log_of_the_work_tour_duration_business2 1.77 288. 0.01 0.00
coefficient_log_of_the_work_tour_duration_eat 1.46 288. 0.01 0.00
coefficient_log_of_the_work_tour_duration_eat_business 3.45 288. 0.01 0.00
coefficient_log_of_the_work_tour_duration_maint 1.64 288. 0.01 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business1-0.182 NA NA 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business2-0.328 NA NA 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat-0.0133 NA NA 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat_business-0.788 NA NA 0.00
coefficient_main_shop_escort_tours_allocated_to_full_time_worker_maint 0.695 NA NA 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business1-0.00585 1.19e+03-0.00 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business2-0.445 1.19e+03-0.00 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat-0.121 1.19e+03-0.00 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat_business-1.17 1.19e+03-0.00 0.00
coefficient_main_shop_escort_tours_allocated_to_part_time_worker_maint 0.0885 1.19e+03 0.00 0.00
coefficient_medium_hh_income_dummy_business1 0.375 772. 0.00 0.00
coefficient_medium_hh_income_dummy_business2 1.38 772. 0.00 0.00
coefficient_medium_hh_income_dummy_eat 0.467 772. 0.00 0.00
coefficient_medium_hh_income_dummy_eat_business 1.37 772. 0.00 0.00
coefficient_medium_hh_income_dummy_maint-0.00582 772.-0.00 0.00
coefficient_participation_in_joint_discretionary_tours_business1 0.0757 3.02e+03 0.00 0.00
coefficient_participation_in_joint_discretionary_tours_business2-0.192 3.02e+03-0.00 0.00
coefficient_participation_in_joint_discretionary_tours_eat 0.455 3.02e+03 0.00 0.00
coefficient_participation_in_joint_discretionary_tours_eat_business-0.682 3.02e+03-0.00 0.00
coefficient_participation_in_joint_discretionary_tours_maint 0.588 3.02e+03 0.00 0.00
coefficient_participation_in_joint_shop_main_eat_tours_business1 0.151 1.04e+03 0.00 0.00
coefficient_participation_in_joint_shop_main_eat_tours_business2 0.232 1.04e+03 0.00 0.00
coefficient_participation_in_joint_shop_main_eat_tours_eat-0.0541 1.04e+03-0.00 0.00
coefficient_participation_in_joint_shop_main_eat_tours_eat_business 0.929 1.04e+03 0.00 0.00
coefficient_participation_in_joint_shop_main_eat_tours_maint-0.354 1.04e+03-0.00 0.00
coefficient_two_work_tours_by_person_business1 0.343 NA NA 0.00
coefficient_two_work_tours_by_person_business2 0.673 NA NA 0.00
coefficient_two_work_tours_by_person_eat-0.904 NA NA 0.00
coefficient_two_work_tours_by_person_eat_business-1.03 NA NA 0.00
coefficient_two_work_tours_by_person_maint 0.216 NA NA 0.00
coefficient_walk_accessibility_to_retail_for_work_taz_business1 0.00 0.00 NA 0.00fixed value
coefficient_walk_accessibility_to_retail_for_work_taz_business2 0.00 0.00 NA 0.00fixed value
coefficient_walk_accessibility_to_retail_for_work_taz_eat 0.0543 0.0307 1.77 0.00
coefficient_walk_accessibility_to_retail_for_work_taz_eat_business 0.248 0.125 1.98* 0.00
coefficient_walk_accessibility_to_retail_for_work_taz_maint 0.0513 0.0415 1.24 0.00
coefficient_workplace_suburban_area_dummy_business1-0.0770 695.-0.00 0.00
coefficient_workplace_suburban_area_dummy_business2-0.215 1.23e+03-0.00 0.00
coefficient_workplace_suburban_area_dummy_eat-0.497 235.-0.00 0.00
coefficient_workplace_suburban_area_dummy_eat_business-0.496 5.05e+03-0.00 0.00
coefficient_workplace_suburban_area_dummy_maint 0.00 0.00 NA 0.00fixed value
coefficient_workplace_urban_area_dummy_business1-0.0698 NA NA 0.00
coefficient_workplace_urban_area_dummy_business2-0.530 1.18e+03-0.00 0.00
coefficient_workplace_urban_area_dummy_eat-0.630 NA NA 0.00
coefficient_workplace_urban_area_dummy_eat_business-0.435 5.37e+03-0.00 0.00
coefficient_workplace_urban_area_dummy_maint-0.213 305.-0.00 0.00
coefficient_zero_cars_owned_by_hh_dummy_business1-0.634 0.312-2.03* 0.00
coefficient_zero_cars_owned_by_hh_dummy_business2 0.00 0.00 NA 0.00fixed value
coefficient_zero_cars_owned_by_hh_dummy_eat 0.00 0.00 NA 0.00fixed value
coefficient_zero_cars_owned_by_hh_dummy_eat_business-0.848 1.51-0.56 0.00
coefficient_zero_cars_owned_by_hh_dummy_maint-0.0208 0.253-0.08 0.00
\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 8, @@ -3597,18 +3566,7 @@ "cell_type": "code", "execution_count": 10, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -3660,31 +3618,31 @@ " \n", " 0\n", " coefficient_dummy_for_full_time_worker_business1\n", - " -11.365293\n", + " -7.402415\n", " F\n", " \n", " \n", " 1\n", " coefficient_dummy_for_full_time_worker_business2\n", - " -13.833915\n", + " -13.824988\n", " F\n", " \n", " \n", " 2\n", " coefficient_dummy_for_full_time_worker_eat\n", - " -9.545916\n", + " -7.551797\n", " F\n", " \n", " \n", " 3\n", " coefficient_dummy_for_full_time_worker_eat_bus...\n", - " -11.192172\n", + " -14.974823\n", " F\n", " \n", " \n", " 4\n", " coefficient_dummy_for_full_time_worker_maint\n", - " -5.880704\n", + " -8.063977\n", " F\n", " \n", " \n", @@ -3696,25 +3654,25 @@ " \n", " 127\n", " coefficient_at_work_sub_tour_asc_business2\n", - " -0.130778\n", + " -2.211281\n", " F\n", " \n", " \n", " 128\n", " coefficient_at_work_sub_tour_asc_eat\n", - " 5.809056\n", + " 0.440311\n", " F\n", " \n", " \n", " 129\n", " coefficient_at_work_sub_tour_asc_eat_business\n", - " -23.415363\n", + " -0.860366\n", " F\n", " \n", " \n", " 130\n", " coefficient_at_work_sub_tour_asc_maint\n", - " 12.910479\n", + " -0.423469\n", " F\n", " \n", " \n", @@ -3730,16 +3688,16 @@ ], "text/plain": [ " coefficient_name value constrain\n", - "0 coefficient_dummy_for_full_time_worker_business1 -11.365293 F\n", - "1 coefficient_dummy_for_full_time_worker_business2 -13.833915 F\n", - "2 coefficient_dummy_for_full_time_worker_eat -9.545916 F\n", - "3 coefficient_dummy_for_full_time_worker_eat_bus... -11.192172 F\n", - "4 coefficient_dummy_for_full_time_worker_maint -5.880704 F\n", + "0 coefficient_dummy_for_full_time_worker_business1 -7.402415 F\n", + "1 coefficient_dummy_for_full_time_worker_business2 -13.824988 F\n", + "2 coefficient_dummy_for_full_time_worker_eat -7.551797 F\n", + "3 coefficient_dummy_for_full_time_worker_eat_bus... -14.974823 F\n", + "4 coefficient_dummy_for_full_time_worker_maint -8.063977 F\n", ".. ... ... ...\n", - "127 coefficient_at_work_sub_tour_asc_business2 -0.130778 F\n", - "128 coefficient_at_work_sub_tour_asc_eat 5.809056 F\n", - "129 coefficient_at_work_sub_tour_asc_eat_business -23.415363 F\n", - "130 coefficient_at_work_sub_tour_asc_maint 12.910479 F\n", + "127 coefficient_at_work_sub_tour_asc_business2 -2.211281 F\n", + "128 coefficient_at_work_sub_tour_asc_eat 0.440311 F\n", + "129 coefficient_at_work_sub_tour_asc_eat_business -0.860366 F\n", + "130 coefficient_at_work_sub_tour_asc_maint -0.423469 F\n", "131 coefficient_at_work_sub_tour_asc_no_subtours 0.000000 T\n", "\n", "[132 rows x 3 columns]" @@ -3762,7 +3720,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -3776,7 +3734,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/19_atwork_subtour_dest.ipynb b/activitysim/examples/example_estimation/notebooks/19_atwork_subtour_dest.ipynb index a340efca73..5219560f6c 100644 --- a/activitysim/examples/example_estimation/notebooks/19_atwork_subtour_dest.ipynb +++ b/activitysim/examples/example_estimation/notebooks/19_atwork_subtour_dest.ipynb @@ -26,30 +26,74 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import larch # !conda install larch #for estimation\n", + "import larch as lx\n", "import pandas as pd\n", - "import numpy as np\n", - "import yaml \n", - "import larch.util.excel\n", - "import os" + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -72,10 +116,27 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_destination/atwork_subtour_destination_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_destination/atwork_subtour_destination_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_destination/atwork_subtour_destination_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_destination/atwork_subtour_destination_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_destination/atwork_subtour_destination_landuse.csv\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_destination/atwork_subtour_destination_size_terms.csv\n" + ] + } + ], "source": [ "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -236,148 +297,88 @@ " \n", " \n", " tour_id\n", - " variable\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", - " 8\n", - " ...\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", - " 190\n", + " alt_dest\n", + " util_distance_piecewise_linear_from_0_to_1_miles\n", + " util_distance_piecewise_linear_from_1_to_2_miles\n", + " util_distance_piecewise_linear_from_2_to_5_miles\n", + " util_distance_piecewise_linear_from_5_to_15_miles\n", + " util_distance_piecewise_linear_for_15_plus_miles\n", + " util_size_variable_atwork\n", + " util_no_attractions_atwork_size_variable_is_0\n", + " util_mode_choice_logsum\n", + " util_sample_of_alternatives_correction_factor\n", " \n", " \n", " \n", " \n", " 0\n", - " 2998927\n", - " util_distance_piecewise_linear_for_15_plus_miles\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ...\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 2966559\n", + " 4\n", + " 0.99\n", + " 0.00\n", + " 0.00\n", " 0.0\n", " 0.0\n", + " 7.026095\n", + " False\n", + " 14.641064\n", + " 3.669233\n", " \n", " \n", " 1\n", - " 2998927\n", - " util_distance_piecewise_linear_from_0_to_1_miles\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " ...\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", + " 2966559\n", + " 9\n", + " 1.00\n", + " 0.98\n", + " 0.00\n", + " 0.0\n", + " 0.0\n", + " 7.841204\n", + " False\n", + " 13.896585\n", + " 4.331944\n", " \n", " \n", " 2\n", - " 2998927\n", - " util_distance_piecewise_linear_from_1_to_2_miles\n", - " 1.0\n", - " 0.9299999475479126\n", - " 0.7599999904632568\n", - " 0.7699999809265137\n", - " 0.4700000286102295\n", - " 0.2799999713897705\n", - " 0.12000000476837158\n", - " 0.25999999046325684\n", - " ...\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", + " 2966559\n", + " 11\n", + " 1.00\n", + " 0.35\n", + " 0.00\n", + " 0.0\n", + " 0.0\n", + " 7.778631\n", + " False\n", + " 14.171065\n", + " 3.202032\n", " \n", " \n", " 3\n", - " 2998927\n", - " util_distance_piecewise_linear_from_2_to_5_miles\n", - " 0.029999971389770508\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 2966559\n", + " 12\n", + " 0.89\n", + " 0.00\n", + " 0.00\n", " 0.0\n", " 0.0\n", - " ...\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", - " 2.9600000381469727\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", - " 3.0\n", + " 7.385584\n", + " False\n", + " 14.520744\n", + " 4.616777\n", " \n", " \n", " 4\n", - " 2998927\n", - " util_distance_piecewise_linear_from_5_to_15_miles\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 2966559\n", + " 14\n", + " 0.87\n", + " 0.00\n", + " 0.00\n", " 0.0\n", - " ...\n", - " 0.8899998664855957\n", - " 1.8000001907348633\n", - " 1.3299999237060547\n", - " 0.48999977111816406\n", " 0.0\n", - " 1.0799999237060547\n", - " 0.9899997711181641\n", - " 1.070000171661377\n", - " 1.929999828338623\n", - " 2.130000114440918\n", + " 6.755056\n", + " False\n", + " 14.588424\n", + " 4.538306\n", " \n", " \n", " ...\n", @@ -392,235 +393,188 @@ " ...\n", " ...\n", " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", " \n", " \n", - " 4171\n", - " 308000674\n", - " util_distance_piecewise_linear_from_5_to_15_miles\n", - " 1.4200000762939453\n", - " 1.3600001335144043\n", - " 1.2899999618530273\n", - " 1.1700000762939453\n", - " 0.9699997901916504\n", - " 0.9699997901916504\n", - " 0.809999942779541\n", - " 0.6100001335144043\n", - " ...\n", - " 0.75\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 125546\n", + " 309112001\n", + " 1375\n", + " 1.00\n", + " 1.00\n", + " 1.38\n", " 0.0\n", " 0.0\n", + " 5.398090\n", + " False\n", + " 12.614690\n", + " 4.169279\n", + " \n", + " \n", + " 125547\n", + " 309112001\n", + " 1376\n", + " 1.00\n", + " 1.00\n", + " 0.95\n", " 0.0\n", " 0.0\n", + " 5.786087\n", + " False\n", + " 12.938050\n", + " 3.557811\n", + " \n", + " \n", + " 125548\n", + " 309112001\n", + " 1378\n", + " 1.00\n", + " 1.00\n", + " 0.76\n", " 0.0\n", " 0.0\n", + " 5.680807\n", + " False\n", + " 13.080930\n", + " 3.564348\n", " \n", " \n", - " 4172\n", - " 308000674\n", - " util_mode_choice_logsum\n", - " 1.743683315365601\n", - " 1.8090398438241646\n", - " 1.9187317689932244\n", - " 1.845763258455972\n", - " 1.9118565509402088\n", - " 2.070472775294134\n", - " 2.0749647025662954\n", - " 2.0765252832944836\n", - " ...\n", - " 1.4896400525368332\n", - " 1.9120295717956781\n", - " 1.9541420210552534\n", - " 1.9566568956436885\n", - " 2.1147517922008467\n", - " 2.110613932849587\n", - " 2.36614159716225\n", - " 2.675175002962727\n", - " 2.45867106695333\n", - " 2.161156410360593\n", - " \n", - " \n", - " 4173\n", - " 308000674\n", - " util_no_attractions_atwork_size_variable_is_0\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " ...\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 125549\n", + " 309112001\n", + " 1380\n", + " 1.00\n", + " 1.00\n", + " 0.67\n", + " 0.0\n", + " 0.0\n", + " 6.972544\n", " False\n", + " 13.148609\n", + " 3.835276\n", " \n", " \n", - " 4174\n", - " 308000674\n", - " util_sample_of_alternatives_correction_factor\n", - " 5.621843324877587\n", - " 4.892390701697378\n", - " 6.41959006998515\n", - " 5.121864578661301\n", - " 4.0943304970661645\n", - " 5.6640922965207166\n", - " 4.849601771676099\n", - " 5.493466028204648\n", - " ...\n", - " 7.195735435552638\n", - " 6.66177523532048\n", - " 5.775893570617849\n", - " 5.627447629966182\n", - " 5.316640911769303\n", - " 5.484197717810032\n", - " 5.248188568415137\n", - " 3.3386531188982147\n", - " 7.377276636224848\n", - " 5.8249441461146\n", - " \n", - " \n", - " 4175\n", - " 308000674\n", - " util_size_variable_atwork\n", - " 6.577240859271166\n", - " 7.294423493874009\n", - " 5.752909090156044\n", - " 7.026094604325162\n", - " 8.012728626482545\n", - " 6.442966827027993\n", - " 7.224737382332969\n", - " 6.539973163879868\n", - " ...\n", - " 4.866333729879064\n", - " 5.1845549872093715\n", - " 5.945708525269778\n", - " 6.047381635266343\n", - " 6.06715626447492\n", - " 5.987948372605412\n", - " 5.730242629913322\n", - " 7.343549119396827\n", - " 3.6375335267623483\n", - " 5.304200029706192\n", + " 125550\n", + " 309112001\n", + " 1381\n", + " 1.00\n", + " 0.02\n", + " 0.00\n", + " 0.0\n", + " 0.0\n", + " 6.198092\n", + " False\n", + " 14.389409\n", + " 3.261637\n", " \n", " \n", "\n", - "

4176 rows × 192 columns

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125551 rows × 11 columns

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464 rows × 6 columns

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6036 rows × 6 columns

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" income_segment \n", - "0 1 \n", - "1 1 \n", - "2 1 \n", - "3 1 \n", - "4 1 \n", - ".. ... \n", - "459 4 \n", - "460 4 \n", - "461 4 \n", - "462 4 \n", - "463 1 \n", + " income_segment \n", + "0 1 \n", + "1 1 \n", + "2 1 \n", + "3 1 \n", + "4 1 \n", + "... ... \n", + "6031 1 \n", + "6032 1 \n", + "6033 1 \n", + "6034 1 \n", + "6035 1 \n", "\n", - "[464 rows x 6 columns]" + "[6036 rows x 6 columns]" ] }, "execution_count": 7, @@ -912,9 +866,9 @@ " 7\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 3\n", " 5.89564\n", " 2.875000\n", @@ -936,9 +890,9 @@ " 19\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.84871\n", " 5.195214\n", @@ -960,9 +914,9 @@ " 38\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.53231\n", " 80.470405\n", @@ -984,9 +938,9 @@ " 20\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 2\n", " 5.64330\n", " 7.947368\n", @@ -1008,9 +962,9 @@ " 86\n", " ...\n", " 0\n", - 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190 rows × 28 columns

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LabelDescriptionExpressionatwork
0util_distance_piecewise_linear_from_0_to_1_milesDistance, piecewise linear from 0 to 1 miles@skims['DIST'].clip(0,1)coef_distance_piecewise_linear_from_0_to_1_miles
1util_distance_piecewise_linear_from_1_to_2_milesDistance, piecewise linear from 1 to 2 miles@(skims['DIST']-1).clip(0,1)coef_distance_piecewise_linear_from_1_to_2_miles
2util_distance_piecewise_linear_from_2_to_5_milesDistance, piecewise linear from 2 to 5 miles@(skims['DIST']-2).clip(0,3)coef_distance_piecewise_linear_from_2_to_5_miles
3util_distance_piecewise_linear_from_5_to_15_milesDistance, piecewise linear from 5 to 15 miles@(skims['DIST']-5).clip(0,10)coef_distance_piecewise_linear_from_5_to_15_miles
4util_distance_piecewise_linear_for_15_plus_milesDistance, piecewise linear for 15+ miles@(skims['DIST']-15.0).clip(0)coef_distance_piecewise_linear_for_15_plus_miles
5util_no_attractions_atwork_size_variable_is_0No attractions, atwork size_term variable is 0size_term==0coef_no_attractions_atwork_size_variable_is_0
6util_mode_choice_logsumMode choice logsummode_choice_logsumcoef_mode_choice_logsum
7util_sample_of_alternatives_correction_factorSample of alternatives correction factor@np.minimum(np.log(df.pick_count/df.prob), 60)coef_sample_of_alternatives_correction_factor
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Iteration 006 [Optimization terminated successfully]

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x\n", " \n", " \n", " \n", @@ -1738,7 +1865,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1746,27 +1873,27 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1777,38 +1904,37 @@ " \n", " \n", " \n", - "
atwork_HEREMPN-1.707324-1.371795
atwork_RETEMPN
coef_distance_piecewise_linear_for_15_plus_miles-0.204500-0.326384
coef_distance_piecewise_linear_from_0_to_1_miles-1.364154-0.840401
coef_distance_piecewise_linear_from_1_to_2_miles-0.739532-0.905173
coef_distance_piecewise_linear_from_2_to_5_miles-0.504526-0.577554
coef_distance_piecewise_linear_from_5_to_15_miles-0.073403-0.193532
coef_mode_choice_logsum0.5032710.403737
coef_no_attractions_atwork_size_variable_is_01.000000
tolerance8.076677745948512e-06
stepsarray([1., 1., 1., 1., 1., 1., 1., 1.])
message'Optimization terminated successfully.'
elapsed_time0:00:00.121814
method'BHHH'
n_cases464
iteration_number8
logloss5.021271650749392
" + "
tolerance8.315604351559683e-06stepsarray([1., 1., 1., 1., 1., 1.])message'Optimization terminated successfully'elapsed_time0:00:00.285360method'bhhh'n_cases6036iteration_number6
" ], "text/plain": [ - "┣ loglike: -2329.8700459477177\n", - "┣ x: atwork_HEREMPN -1.707324\n", + "┣ loglike: -12720.40641937967\n", + "┣ x: atwork_HEREMPN -1.371795\n", "┃ atwork_RETEMPN -0.298406\n", - "┃ coef_distance_piecewise_linear_for_15_plus_miles -0.204500\n", - "┃ coef_distance_piecewise_linear_from_0_to_1_miles -1.364154\n", - "┃ coef_distance_piecewise_linear_from_1_to_2_miles -0.739532\n", - "┃ coef_distance_piecewise_linear_from_2_to_5_miles -0.504526\n", - "┃ coef_distance_piecewise_linear_from_5_to_15_miles -0.073403\n", - "┃ coef_mode_choice_logsum 0.503271\n", + "┃ coef_distance_piecewise_linear_for_15_plus_miles -0.326384\n", + "┃ coef_distance_piecewise_linear_from_0_to_1_miles -0.840401\n", + "┃ coef_distance_piecewise_linear_from_1_to_2_miles -0.905173\n", + "┃ coef_distance_piecewise_linear_from_2_to_5_miles -0.577554\n", + "┃ coef_distance_piecewise_linear_from_5_to_15_miles -0.193532\n", + "┃ coef_mode_choice_logsum 0.403737\n", "┃ coef_no_attractions_atwork_size_variable_is_0 -999.000000\n", "┃ coef_sample_of_alternatives_correction_factor 1.000000\n", "┃ dtype: float64\n", - "┣ tolerance: 8.076677745948512e-06\n", - "┣ steps: array([1., 1., 1., 1., 1., 1., 1., 1.])\n", - "┣ message: 'Optimization terminated successfully.'\n", - "┣ elapsed_time: datetime.timedelta(microseconds=121814)\n", - "┣ method: 'BHHH'\n", - "┣ n_cases: 464\n", - "┣ iteration_number: 8\n", - "┣ logloss: 5.021271650749392" + "┣ tolerance: 8.315604351559683e-06\n", + "┣ steps: array([1., 1., 1., 1., 1., 1.])\n", + "┣ message: 'Optimization terminated successfully'\n", + "┣ elapsed_time: datetime.timedelta(microseconds=285360)\n", + "┣ method: 'bhhh'\n", + "┣ n_cases: 6036\n", + "┣ iteration_number: 6" ] }, - "execution_count": 11, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.estimate(method='BHHH', options={'maxiter':1000})" + "model.estimate(method='bhhh', options={'maxiter':1000})" ] }, { @@ -1820,119 +1946,145 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Value Std Err t Stat Signif Null Value Constrained
atwork_HEREMPN-1.71 0.203-8.39*** 0.00
atwork_RETEMPN-0.298 NA NA 0.00fixed value
coef_distance_piecewise_linear_for_15_plus_miles-0.205 1.79e-14-BIG*** 0.00
coef_distance_piecewise_linear_from_0_to_1_miles-1.36 0.402-3.39*** 0.00
coef_distance_piecewise_linear_from_1_to_2_miles-0.740 0.222-3.33*** 0.00
coef_distance_piecewise_linear_from_2_to_5_miles-0.505 0.0702-7.19*** 0.00
coef_distance_piecewise_linear_from_5_to_15_miles-0.0734 0.0897-0.82 0.00
coef_mode_choice_logsum 0.503 0.0702 7.17*** 0.00
coef_no_attractions_atwork_size_variable_is_0-999. NA NA 0.00fixed value
coef_sample_of_alternatives_correction_factor 1.00 NA NA 0.00fixed value
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
atwork_HEREMPN-1.37 0.0710-19.32*** 0.00
atwork_RETEMPN-0.298 0.00 NA 0.00fixed value
coef_distance_piecewise_linear_for_15_plus_miles-0.326 0.0607-5.38*** 0.00
coef_distance_piecewise_linear_from_0_to_1_miles-0.840 0.0954-8.81*** 0.00
coef_distance_piecewise_linear_from_1_to_2_miles-0.905 0.0554-16.34*** 0.00
coef_distance_piecewise_linear_from_2_to_5_miles-0.578 0.0278-20.77*** 0.00
coef_distance_piecewise_linear_from_5_to_15_miles-0.194 0.0173-11.20*** 0.00
coef_mode_choice_logsum 0.404 0.0244 16.54*** 0.00
coef_no_attractions_atwork_size_variable_is_0-999. 0.00 NA 0.00fixed value
coef_sample_of_alternatives_correction_factor 1.00 0.00 NA 0.00fixed value
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 12, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -1953,7 +2105,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -1970,7 +2122,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -1989,7 +2141,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -2242,9 +2394,9 @@ " atwork\n", " atwork\n", " 0.000000\n", - " 0.803595\n", + " 0.745241\n", " 0.000000\n", - " 0.196405\n", + " 0.254759\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -2400,7 +2552,7 @@ "10 othmaint non_mandatory 0.000000 0.482000 0.000000 0.518000 \n", "11 social non_mandatory 0.000000 0.522000 0.000000 0.478000 \n", "12 othdiscr non_mandatory 0.252252 0.212212 0.000000 0.272272 \n", - "13 atwork atwork 0.000000 0.803595 0.000000 0.196405 \n", + "13 atwork atwork 0.000000 0.745241 0.000000 0.254759 \n", "14 work trip 0.000000 0.166667 0.166667 0.166667 \n", "15 escort trip 0.001000 0.225000 0.000000 0.144000 \n", "16 shopping trip 0.001000 0.999000 0.000000 0.000000 \n", @@ -2435,7 +2587,7 @@ "21 0.000000 0.000000 0.000000 0.000 0.000000 0.591409 0.407592 " ] }, - "execution_count": 15, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -2456,7 +2608,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -2480,7 +2632,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -2513,31 +2665,31 @@ " \n", " 0\n", " coef_distance_piecewise_linear_from_0_to_1_miles\n", - " -1.364154\n", + " -0.840401\n", " F\n", " \n", " \n", " 1\n", " coef_distance_piecewise_linear_from_1_to_2_miles\n", - " -0.739532\n", + " -0.905173\n", " F\n", " \n", " \n", " 2\n", " coef_distance_piecewise_linear_from_2_to_5_miles\n", - " -0.504526\n", + " -0.577554\n", " F\n", " \n", " \n", " 3\n", " coef_distance_piecewise_linear_from_5_to_15_miles\n", - " -0.073403\n", + " -0.193532\n", " F\n", " \n", " \n", " 4\n", " coef_distance_piecewise_linear_for_15_plus_miles\n", - " -0.204500\n", + " -0.326384\n", " F\n", " \n", " \n", @@ -2555,7 +2707,7 @@ " \n", " 7\n", " coef_mode_choice_logsum\n", - " 0.503271\n", + " 0.403737\n", " F\n", " \n", " \n", @@ -2570,18 +2722,18 @@ ], "text/plain": [ " coefficient_name value constrain\n", - "0 coef_distance_piecewise_linear_from_0_to_1_miles -1.364154 F\n", - "1 coef_distance_piecewise_linear_from_1_to_2_miles -0.739532 F\n", - "2 coef_distance_piecewise_linear_from_2_to_5_miles -0.504526 F\n", - "3 coef_distance_piecewise_linear_from_5_to_15_miles -0.073403 F\n", - "4 coef_distance_piecewise_linear_for_15_plus_miles -0.204500 F\n", + "0 coef_distance_piecewise_linear_from_0_to_1_miles -0.840401 F\n", + "1 coef_distance_piecewise_linear_from_1_to_2_miles -0.905173 F\n", + "2 coef_distance_piecewise_linear_from_2_to_5_miles -0.577554 F\n", + "3 coef_distance_piecewise_linear_from_5_to_15_miles -0.193532 F\n", + "4 coef_distance_piecewise_linear_for_15_plus_miles -0.326384 F\n", "5 coef_size_variable_atwork 1.000000 T\n", "6 coef_no_attractions_atwork_size_variable_is_0 -999.000000 T\n", - "7 coef_mode_choice_logsum 0.503271 F\n", + "7 coef_mode_choice_logsum 0.403737 F\n", "8 coef_sample_of_alternatives_correction_factor 1.000000 T" ] }, - "execution_count": 17, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -2592,7 +2744,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -2860,9 +3012,9 @@ " atwork\n", " atwork\n", " 0.000000\n", - " 0.803595\n", + " 0.745241\n", " 0.000000\n", - " 0.196405\n", + " 0.254759\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -3026,7 +3178,7 @@ "10 10 othmaint non_mandatory 0.000000 0.482000 0.000000 \n", "11 11 social non_mandatory 0.000000 0.522000 0.000000 \n", "12 12 othdiscr non_mandatory 0.252252 0.212212 0.000000 \n", - "13 13 atwork atwork 0.000000 0.803595 0.000000 \n", + "13 13 atwork atwork 0.000000 0.745241 0.000000 \n", "14 14 work trip 0.000000 0.166667 0.166667 \n", "15 15 escort trip 0.001000 0.225000 0.000000 \n", "16 16 shopping trip 0.001000 0.999000 0.000000 \n", @@ -3050,7 +3202,7 @@ "10 0.518000 0.000000 0.000000 0.000000 0.000 0.000000 0.000000 \n", "11 0.478000 0.000000 0.000000 0.000000 0.000 0.000000 0.000000 \n", "12 0.272272 0.165165 0.000000 0.000000 0.000 0.098098 0.000000 \n", - "13 0.196405 0.000000 0.000000 0.000000 0.000 0.000000 0.000000 \n", + "13 0.254759 0.000000 0.000000 0.000000 0.000 0.000000 0.000000 \n", "14 0.166667 0.166667 0.166667 0.166667 0.000 0.000000 0.000000 \n", "15 0.144000 0.000000 0.000000 0.000000 0.464 0.166000 0.000000 \n", "16 0.000000 0.000000 0.000000 0.000000 0.000 0.000000 0.000000 \n", @@ -3085,7 +3237,7 @@ "21 0.407592 " ] }, - "execution_count": 18, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -3102,7 +3254,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -3116,7 +3268,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/20_atwork_subtour_scheduling.ipynb b/activitysim/examples/example_estimation/notebooks/20_atwork_subtour_scheduling.ipynb index ae20d36942..1de74014a3 100644 --- a/activitysim/examples/example_estimation/notebooks/20_atwork_subtour_scheduling.ipynb +++ b/activitysim/examples/example_estimation/notebooks/20_atwork_subtour_scheduling.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -70,11 +117,13 @@ "metadata": {}, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/activitysim/activitysim/estimation/larch/__init__.py:18: DtypeWarning: Columns (15,16,17,18,19,20,33,34,35,36,37,38,50,51,52,53,54,55,66,67,68,69,70,71,81,82,83,84,85,86,95,96,97,98,99,100,108,109,110,111,112,113,120,121,122,123,124,125,131,132,133,134,135,136,141,142,143,144,145,146,150,151,152,153,154,155,158,159,160,161,162,163,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191) have mixed types.Specify dtype option on import or set low_memory=False.\n", - " return m(*args, **kwargs)\n" + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_scheduling/tour_scheduling_atwork_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_scheduling/atwork_subtour_scheduling_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_scheduling/atwork_subtour_scheduling_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/atwork_subtour_scheduling/atwork_subtour_scheduling_choosers_combined.parquet\n" ] } ], @@ -82,7 +131,12 @@ "modelname = \"atwork_subtour_scheduling\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -1095,14 +1149,14 @@ " tour_count\n", " tour_category\n", " ...\n", - " COLLFTE\n", - " COLLPTE\n", - " TOPOLOGY\n", - " TERMINAL\n", - " household_density\n", - " employment_density\n", - " density_index\n", - " is_cbd\n", + " auOpRetail\n", + " auOpTotal\n", + " trPkRetail\n", + " trPkTotal\n", + " trOpRetail\n", + " trOpTotal\n", + " nmRetail\n", + " nmTotal\n", " start_previous\n", " end_previous\n", " \n", @@ -1110,34 +1164,34 @@ " \n", " \n", " 0\n", - " 2998927\n", - " 114\n", - " 114\n", - " 73144\n", - " maint\n", + " 2966559\n", + " 86\n", + " 113\n", + " 72355\n", + " eat\n", " 1\n", " 1\n", " 1\n", " 1\n", " atwork\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 2.48345\n", - " 26.073171\n", - " 8.048780\n", - " 6.150212\n", - " False\n", + " 9.915345\n", + " 12.430580\n", + " 6.550726\n", + " 9.119016\n", + " 6.446184\n", + " 9.035333\n", + " 5.256966\n", + " 6.831275\n", " 5\n", " 5\n", " \n", " \n", " 1\n", - " 3060326\n", - " 85\n", - " 85\n", - " 74642\n", + " 3046632\n", + " 145\n", + " 90\n", + " 74308\n", " eat\n", " 1\n", " 1\n", @@ -1145,23 +1199,23 @@ " 1\n", " atwork\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 2.09035\n", - " 20.666667\n", - " 4.107527\n", - " 3.426505\n", - " False\n", + " 10.259606\n", + " 12.727344\n", + " 5.452325\n", + " 7.771767\n", + " 5.298242\n", + " 7.602426\n", + " 6.443514\n", + " 7.965548\n", " 5\n", " 5\n", " \n", " \n", " 2\n", - " 4422879\n", - " 124\n", + " 3048108\n", + " 85\n", " 124\n", - " 107875\n", + " 74344\n", " eat\n", " 1\n", " 1\n", @@ -1169,47 +1223,47 @@ " 1\n", " atwork\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 5.35435\n", - " 139.333333\n", - " 418.518519\n", - " 104.532377\n", - " False\n", + " 10.259606\n", + " 12.727344\n", + " 5.452325\n", + " 7.771767\n", + " 5.298242\n", + " 7.602426\n", + " 6.443514\n", + " 7.965548\n", " 5\n", " 5\n", " \n", " \n", " 3\n", - " 4440282\n", - " 154\n", - " 154\n", - " 108299\n", - " maint\n", + " 3177463\n", + " 99\n", + " 55\n", + " 77499\n", + " eat\n", " 1\n", " 1\n", " 1\n", " 1\n", " atwork\n", " ...\n", - " 2035.58118\n", - " 20.60887\n", - " 2\n", - " 5.22542\n", - " 97.634722\n", - " 550.205552\n", - " 82.920387\n", - " False\n", + " 7.714071\n", + " 10.313852\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " 5\n", " 5\n", " \n", " \n", " 4\n", - " 4496780\n", - " 89\n", - " 89\n", - " 109677\n", + " 3191832\n", + " 99\n", + " 145\n", + " 77849\n", " maint\n", " 1\n", " 1\n", @@ -1217,14 +1271,14 @@ " 1\n", " atwork\n", " ...\n", - " 690.54974\n", - " 0.00000\n", - " 3\n", - " 4.73802\n", - " 117.769796\n", - " 246.205869\n", - " 79.663609\n", - " False\n", + " 9.763398\n", + " 12.307147\n", + " 1.228620\n", + " 3.278544\n", + " 1.239060\n", + " 3.280429\n", + " 4.284159\n", + " 6.249753\n", " 5\n", " 5\n", " \n", @@ -1253,184 +1307,184 @@ " ...\n", " \n", " \n", - " 459\n", - " 302923726\n", - " 145\n", - " 145\n", - " 7388383\n", - " maint\n", + " 6031\n", + " 308156004\n", + " 99\n", + " 124\n", + " 7516000\n", + " eat\n", " 1\n", " 1\n", " 1\n", " 1\n", " atwork\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 2.37546\n", - " 19.153846\n", - " 5.907692\n", - " 4.515087\n", - " False\n", + " 9.566058\n", + " 12.139587\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 3.086628\n", + " 5.647842\n", " 5\n", " 5\n", " \n", " \n", - " 460\n", - " 302942567\n", - " 85\n", - " 85\n", - " 7388843\n", - " eat\n", + " 6032\n", + " 308227650\n", + " 155\n", + " 88\n", + " 7517747\n", + " maint\n", " 1\n", " 1\n", " 1\n", " 1\n", " atwork\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 2.81406\n", - " 16.068376\n", - " 21.136752\n", - " 9.128669\n", - " False\n", + " 10.260330\n", + " 12.748307\n", + " 4.719610\n", + " 7.890189\n", + " 4.493279\n", + " 7.643024\n", + " 5.529241\n", + " 8.876000\n", " 5\n", " 5\n", " \n", " \n", - " 461\n", - " 302942627\n", - " 135\n", - " 135\n", - " 7388844\n", - " maint\n", + " 6033\n", + " 308260103\n", + " 102\n", + " 113\n", + " 7518539\n", + " eat\n", " 1\n", " 1\n", " 1\n", " 1\n", " atwork\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 2.81406\n", - " 16.068376\n", - " 21.136752\n", - " 9.128669\n", - " False\n", + " 10.294354\n", + " 12.880095\n", + " 4.408064\n", + " 7.614481\n", + " 3.838266\n", + " 7.011926\n", + " 5.169891\n", + " 8.595128\n", " 5\n", " 5\n", " \n", " \n", - " 462\n", - " 305120465\n", - " 112\n", - " 112\n", - " 7441962\n", - " maint\n", + " 6034\n", + " 309080718\n", + " 55\n", + " 113\n", + " 7538554\n", + " eat\n", " 1\n", " 1\n", " 1\n", " 1\n", " atwork\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 1\n", - " 8.54946\n", - " 55.606634\n", - " 142.984438\n", - " 40.036459\n", - " False\n", + " 10.345456\n", + " 12.953264\n", + " 7.103743\n", + " 9.892019\n", + " 6.979741\n", + " 9.773601\n", + " 6.557982\n", + " 8.518901\n", " 5\n", " 5\n", " \n", " \n", - " 463\n", - " 308000674\n", - " 124\n", - " 124\n", - " 7512211\n", - " maint\n", + " 6035\n", + " 309112001\n", + " 125\n", + " 113\n", + " 7539317\n", + " eat\n", " 1\n", " 1\n", " 1\n", " 1\n", " atwork\n", " ...\n", - " 0.00000\n", - " 0.00000\n", - " 2\n", - " 4.64648\n", - " 196.395950\n", - " 178.779465\n", - " 93.587057\n", - " False\n", + " 6.494711\n", + " 8.713819\n", + " 0.019735\n", + " 0.222696\n", + " 0.016077\n", + " 0.153189\n", + " 0.000000\n", + " 0.000000\n", " 5\n", " 5\n", " \n", " \n", "\n", - "

464 rows × 162 columns

\n", + "

6036 rows × 162 columns

\n", "" ], "text/plain": [ - " tour_id model_choice override_choice person_id tour_type \\\n", - "0 2998927 114 114 73144 maint \n", - "1 3060326 85 85 74642 eat \n", - "2 4422879 124 124 107875 eat \n", - "3 4440282 154 154 108299 maint \n", - "4 4496780 89 89 109677 maint \n", - ".. ... ... ... ... ... \n", - "459 302923726 145 145 7388383 maint \n", - "460 302942567 85 85 7388843 eat \n", - "461 302942627 135 135 7388844 maint \n", - "462 305120465 112 112 7441962 maint \n", - "463 308000674 124 124 7512211 maint \n", + " tour_id model_choice override_choice person_id tour_type \\\n", + "0 2966559 86 113 72355 eat \n", + "1 3046632 145 90 74308 eat \n", + "2 3048108 85 124 74344 eat \n", + "3 3177463 99 55 77499 eat \n", + "4 3191832 99 145 77849 maint \n", + "... ... ... ... ... ... \n", + "6031 308156004 99 124 7516000 eat \n", + "6032 308227650 155 88 7517747 maint \n", + "6033 308260103 102 113 7518539 eat \n", + "6034 309080718 55 113 7538554 eat \n", + "6035 309112001 125 113 7539317 eat \n", "\n", - " tour_type_count tour_type_num tour_num tour_count tour_category ... \\\n", - "0 1 1 1 1 atwork ... \n", - "1 1 1 1 1 atwork ... \n", - "2 1 1 1 1 atwork ... \n", - "3 1 1 1 1 atwork ... \n", - "4 1 1 1 1 atwork ... \n", - ".. ... ... ... ... ... ... \n", - "459 1 1 1 1 atwork ... \n", - "460 1 1 1 1 atwork ... \n", - "461 1 1 1 1 atwork ... \n", - "462 1 1 1 1 atwork ... \n", - "463 1 1 1 1 atwork ... \n", + " tour_type_count tour_type_num tour_num tour_count tour_category ... \\\n", + "0 1 1 1 1 atwork ... \n", + "1 1 1 1 1 atwork ... \n", + "2 1 1 1 1 atwork ... \n", + "3 1 1 1 1 atwork ... \n", + "4 1 1 1 1 atwork ... \n", + "... ... ... ... ... ... ... \n", + "6031 1 1 1 1 atwork ... \n", + "6032 1 1 1 1 atwork ... \n", + "6033 1 1 1 1 atwork ... \n", + "6034 1 1 1 1 atwork ... \n", + "6035 1 1 1 1 atwork ... \n", "\n", - " COLLFTE COLLPTE TOPOLOGY TERMINAL household_density \\\n", - "0 0.00000 0.00000 1 2.48345 26.073171 \n", - "1 0.00000 0.00000 1 2.09035 20.666667 \n", - "2 0.00000 0.00000 1 5.35435 139.333333 \n", - "3 2035.58118 20.60887 2 5.22542 97.634722 \n", - "4 690.54974 0.00000 3 4.73802 117.769796 \n", - ".. ... ... ... ... ... \n", - "459 0.00000 0.00000 1 2.37546 19.153846 \n", - "460 0.00000 0.00000 1 2.81406 16.068376 \n", - "461 0.00000 0.00000 1 2.81406 16.068376 \n", - "462 0.00000 0.00000 1 8.54946 55.606634 \n", - "463 0.00000 0.00000 2 4.64648 196.395950 \n", + " auOpRetail auOpTotal trPkRetail trPkTotal trOpRetail trOpTotal \\\n", + "0 9.915345 12.430580 6.550726 9.119016 6.446184 9.035333 \n", + "1 10.259606 12.727344 5.452325 7.771767 5.298242 7.602426 \n", + "2 10.259606 12.727344 5.452325 7.771767 5.298242 7.602426 \n", + "3 7.714071 10.313852 0.000000 0.000000 0.000000 0.000000 \n", + "4 9.763398 12.307147 1.228620 3.278544 1.239060 3.280429 \n", + "... ... ... ... ... ... ... \n", + "6031 9.566058 12.139587 0.000000 0.000000 0.000000 0.000000 \n", + "6032 10.260330 12.748307 4.719610 7.890189 4.493279 7.643024 \n", + "6033 10.294354 12.880095 4.408064 7.614481 3.838266 7.011926 \n", + "6034 10.345456 12.953264 7.103743 9.892019 6.979741 9.773601 \n", + "6035 6.494711 8.713819 0.019735 0.222696 0.016077 0.153189 \n", "\n", - " employment_density density_index is_cbd start_previous end_previous \n", - "0 8.048780 6.150212 False 5 5 \n", - "1 4.107527 3.426505 False 5 5 \n", - "2 418.518519 104.532377 False 5 5 \n", - "3 550.205552 82.920387 False 5 5 \n", - "4 246.205869 79.663609 False 5 5 \n", - ".. ... ... ... ... ... \n", - "459 5.907692 4.515087 False 5 5 \n", - "460 21.136752 9.128669 False 5 5 \n", - "461 21.136752 9.128669 False 5 5 \n", - "462 142.984438 40.036459 False 5 5 \n", - "463 178.779465 93.587057 False 5 5 \n", + " nmRetail nmTotal start_previous end_previous \n", + "0 5.256966 6.831275 5 5 \n", + "1 6.443514 7.965548 5 5 \n", + "2 6.443514 7.965548 5 5 \n", + "3 0.000000 0.000000 5 5 \n", + "4 4.284159 6.249753 5 5 \n", + "... ... ... ... ... \n", + "6031 3.086628 5.647842 5 5 \n", + "6032 5.529241 8.876000 5 5 \n", + "6033 5.169891 8.595128 5 5 \n", + "6034 6.557982 8.518901 5 5 \n", + "6035 0.000000 0.000000 5 5 \n", "\n", - "[464 rows x 162 columns]" + "[6036 rows x 162 columns]" ] }, "execution_count": 6, @@ -1476,148 +1530,148 @@ " \n", " \n", " tour_id\n", - " variable\n", - " 0\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", + " start\n", + " end\n", + " duration\n", + " tdd\n", + " mode_choice_logsum\n", + " util_early_start_at_5\n", + " util_am_peak_start_at_6\n", + " util_am_peak_start_at_7\n", + " util_am_peak_start_at_8\n", " ...\n", - " 180\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", + " util_duration_shift_for_number_of_mandatory_tours\n", + " util_start_shift_for_number_of_joint_tours\n", + " util_duration_shift_for_number_of_joint_tours\n", + " util_start_shift_for_number_of_individual_nonmandatory_tours\n", + " util_duration_shift_for_number_of_individual_nonmandatory_tours\n", + " util_dummy_for_business_related_purpose_and_duration_from_0_to_1\n", + " util_dummy_for_eating_out_purpose_and_duration_of_1_hour\n", + " util_dummy_for_eating_out_purpose_and_departure_at_11\n", + " util_dummy_for_eating_out_purpose_and_departure_at_12\n", + " util_dummy_for_eating_out_purpose_and_departure_at_13\n", " \n", " \n", " \n", " \n", " 0\n", - " 2998927\n", - " duration\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 2966559\n", + " 10\n", + " 10\n", " 0\n", + " 85\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", " ...\n", " 0\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 1\n", - " 2998927\n", - " end\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 2966559\n", + " 10\n", + " 11\n", + " 1\n", + " 86\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", " ...\n", + " 1\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 2\n", - " 2998927\n", - " mode_choice_logsum\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 2966559\n", + " 10\n", + " 12\n", + " 2\n", + " 87\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", " ...\n", + " 2\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 3\n", - " 2998927\n", - " start\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 2966559\n", + " 10\n", + " 13\n", + " 3\n", + " 88\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", " ...\n", + " 3\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " 4\n", - " 2998927\n", - " util_am_peak_end\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 2966559\n", + " 10\n", + " 14\n", + " 4\n", + " 89\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", " ...\n", + " 4\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", " ...\n", @@ -1644,197 +1698,301 @@ " ...\n", " \n", " \n", - " 24587\n", - " 308000674\n", - " util_start_shift_for_number_of_individual_nonm...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 457514\n", + " 309112001\n", + " 21\n", + " 22\n", + " 1\n", + " 185\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", " ...\n", + " 1\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", - " 24588\n", - " 308000674\n", - " util_start_shift_for_number_of_joint_tours\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " ...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 457515\n", + " 309112001\n", + " 21\n", + " 23\n", + " 2\n", + " 186\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " ...\n", + " 2\n", " 0\n", " 0\n", " 0\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", - " 24589\n", - " 308000674\n", - " util_start_shift_for_number_of_mandatory_tours\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " ...\n", - " 0\n", - " 0\n", - " 0\n", + " 457516\n", + " 309112001\n", + " 22\n", + " 22\n", " 0\n", + " 187\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " ...\n", " 0\n", " 0\n", " 0\n", " 0\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", - " 24590\n", - " 308000674\n", - " util_start_shift_for_outbound_auto_travel_time...\n", - " 60.10000228881836\n", - " 60.10000228881836\n", - " 60.10000228881836\n", - " 60.10000228881836\n", - " 60.10000228881836\n", - " 60.10000228881836\n", - " 60.10000228881836\n", - " 60.10000228881836\n", - " ...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 457517\n", + " 309112001\n", + " 22\n", + " 23\n", + " 1\n", + " 188\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " ...\n", + " 1\n", " 0\n", " 0\n", " 0\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", - " 24591\n", - " 308000674\n", - " util_start_shift_for_subsequent_sub_tour_of_sa...\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 457518\n", + " 309112001\n", + " 23\n", + " 23\n", " 0\n", + " 189\n", " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", " ...\n", " 0\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " False\n", + " False\n", + " False\n", + " False\n", + " False\n", " \n", " \n", "\n", - "

24592 rows × 192 columns

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457519 rows × 55 columns

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"[24592 rows x 192 columns]" + " util_dummy_for_eating_out_purpose_and_departure_at_11 \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "457514 False \n", + "457515 False \n", + "457516 False \n", + "457517 False \n", + "457518 False \n", + "\n", + " util_dummy_for_eating_out_purpose_and_departure_at_12 \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "457514 False \n", + "457515 False \n", + "457516 False \n", + "457517 False \n", + "457518 False \n", + "\n", + " util_dummy_for_eating_out_purpose_and_departure_at_13 \n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "457514 False \n", + "457515 False \n", + "457516 False \n", + "457517 False \n", + "457518 False \n", + "\n", + "[457519 rows x 55 columns]" ] }, "execution_count": 7, @@ -1864,9 +2022,44 @@ "name": "stderr", "output_type": "stream", "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" + "problem: nan_utility has (190 issues)\n", + "problem: chosen_but_not_available has (12 issues)\n" ] }, + { + "data": { + "text/plain": [ + "(,\n", + " ┣ chosen_but_not_available: altid n example rows\n", + " ┃ 0 88 1 5445\n", + " ┃ 1 100 2 1344, 5240\n", + " ┃ 2 102 1 4696\n", + " ┃ 3 103 1 3099\n", + " ┃ 4 107 1 2364\n", + " ┃ 5 113 2 3454, 4647\n", + " ┃ 6 114 4 1537, 2506, 2800\n", + " ┃ 7 115 1 1791\n", + " ┃ 8 116 1 4089\n", + " ┃ 9 120 1 2595\n", + " ┃ 10 125 3 797, 1766, 2716\n", + " ┃ 11 138 1 2003)" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.doctor(repair_nan_utility=True)\n", + "model.doctor(repair_ch_av=\"-\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ { "data": { "text/html": [ @@ -1882,7 +2075,7 @@ { "data": { "text/html": [ - "

Best LL = -1401.9305368056416

" + "

Best LL = -17373.947698365682

" ], "text/plain": [ "" @@ -1913,778 +2106,732 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " coef_am_peak_end\n", - " -1.373169\n", + " -2.543876\n", + " -2.543876\n", " -2.928312\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.373169\n", " \n", " \n", " coef_am_peak_start_at_6\n", - " -20.592814\n", + " -5.790935\n", + " -5.790935\n", " -6.156718\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -20.592814\n", " \n", " \n", " coef_am_peak_start_at_7\n", - " -2.826984\n", + " -4.238642\n", + " -4.238642\n", " -4.061708\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.826984\n", " \n", " \n", " coef_am_peak_start_at_8\n", - " -1.196528\n", + " -2.371798\n", + " -2.371798\n", " -2.330535\n", - 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" -2.204068\n", " \n", " \n", " coef_evening_end_at_19_20_21\n", - " -4.521037\n", + " -2.460690\n", + " -2.460690\n", " -2.319982\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -4.521037\n", " \n", " \n", " coef_evening_start_at_19_20_21\n", - " -0.325741\n", + " -0.786571\n", + " -0.786571\n", " -1.015090\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.325741\n", " \n", " \n", " coef_late_end_at_22_23\n", - " -11.516565\n", + " -2.391664\n", + " -2.391664\n", " -2.319982\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -11.516565\n", " \n", " \n", " coef_late_start_at_22_23\n", - " -5.142925\n", + " -0.890587\n", + " -0.890587\n", " -0.737570\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -5.142925\n", " \n", " \n", " coef_midday_end_at_10_11_12\n", - " -1.305196\n", + " -2.145575\n", + " -2.145575\n", " -2.297264\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.305196\n", " \n", " \n", " coef_midday_end_at_13_14\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_midday_start_at_10_11_12\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.0\n", + " 0.0\n", " 0.0\n", - " -25.0\n", - " 25.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", " coef_midday_start_at_13_14_15\n", - " -1.051562\n", + " -0.665045\n", + " -0.665045\n", " -0.775022\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.051562\n", " \n", " \n", " coef_pm_peak_end_at_15\n", - " -1.432981\n", + " -0.586475\n", + " -0.586475\n", " -0.578344\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -1.432981\n", " \n", " \n", " coef_pm_peak_end_at_16\n", - " -2.055109\n", + " -1.337297\n", + " -1.337297\n", " -1.094087\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.055109\n", " \n", " \n", " coef_pm_peak_end_at_17\n", - " -2.404252\n", + " -1.432487\n", + " -1.432487\n", " -1.165847\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -2.404252\n", " \n", " \n", " coef_pm_peak_end_at_18\n", - " -3.500372\n", + " -1.702240\n", + " -1.702240\n", " -1.496131\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -3.500372\n", " \n", " \n", " coef_pm_peak_start_at_16_17_18\n", - " -0.798588\n", + " -0.000431\n", + " -0.000431\n", " -0.227528\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.798588\n", " \n", " \n", " coef_start_shift_for_business_related_\n", - " -0.083357\n", + " -0.071618\n", + " -0.071618\n", " -0.111300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.083357\n", " \n", " \n", " coef_start_shift_for_first_sub_tour_of_same_work_tour\n", - " -0.168324\n", + " -0.458549\n", + " -0.458549\n", " -0.543300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.168324\n", " \n", " \n", " coef_start_shift_for_inbound_auto_travel_time_off_peak\n", - " -0.099019\n", + " -0.011025\n", + " -0.011025\n", " 0.000650\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.099019\n", " \n", " \n", " coef_start_shift_for_number_of_individual_nonmandatory_tours\n", - " 0.026777\n", + " -0.019137\n", + " -0.019137\n", " -0.012800\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.026777\n", " \n", " \n", " coef_start_shift_for_number_of_joint_tours\n", - " -0.019722\n", + " 0.025502\n", + " 0.025502\n", " -0.020600\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.019722\n", " \n", " \n", " coef_start_shift_for_number_of_mandatory_tours\n", - " 0.059018\n", + " -0.067479\n", + " -0.067479\n", " -0.019300\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.059018\n", " \n", " \n", " coef_start_shift_for_outbound_auto_travel_time_off_peak\n", - " 0.100349\n", + " 0.010616\n", + " 0.010616\n", " 0.000650\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " 0.100349\n", " \n", " \n", " coef_start_shift_for_subsequent_sub_tour_of_same_work_tour\n", - " -0.360206\n", + " -0.117673\n", + " -0.117673\n", " -0.184400\n", - " 0.0\n", " -25.0\n", " 25.0\n", + " 0.0\n", " 0\n", - " \n", - " -0.360206\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue \\\n", - "coef_am_peak_end -1.373169 -2.928312 \n", - "coef_am_peak_start_at_6 -20.592814 -6.156718 \n", - "coef_am_peak_start_at_7 -2.826984 -4.061708 \n", - "coef_am_peak_start_at_8 -1.196528 -2.330535 \n", - "coef_am_peak_start_at_9 -1.619897 -1.881593 \n", - "coef_dummy_for_business_related_purpose_and_dur... -0.663129 -1.543000 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 1.151827 1.511000 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 2.625436 2.721000 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 2.360981 2.122000 \n", - "coef_dummy_for_eating_out_purpose_and_duration_... 0.310405 0.399900 \n", - "coef_duration_of_0_hours 9.959985 -0.906682 \n", - "coef_duration_of_11_to_13_hours -0.374055 0.300000 \n", - "coef_duration_of_14_to_18_hours 0.000000 0.000000 \n", - "coef_duration_of_1_hour 0.000000 0.000000 \n", - "coef_duration_of_2_to_3_hours 9.181283 -1.362176 \n", - "coef_duration_of_4_to_5_hours -0.483141 -0.819618 \n", - "coef_duration_of_6_to_7_hours 10.535613 1.088111 \n", - "coef_duration_of_8_to_10_hours 10.402183 1.734039 \n", - "coef_duration_shift_for_business_related_ 0.600044 0.264600 \n", - "coef_duration_shift_for_first_sub_tour_of_same_... 0.319885 -0.399200 \n", - "coef_duration_shift_for_inbound_auto_travel_tim... -0.118575 0.009810 \n", - "coef_duration_shift_for_number_of_individual_no... 0.009894 -0.042200 \n", - "coef_duration_shift_for_number_of_joint_tours -0.577681 -0.249700 \n", - "coef_duration_shift_for_number_of_mandatory_tours -1.058788 -0.770200 \n", - "coef_duration_shift_for_outbound_auto_travel_ti... 0.145324 0.009810 \n", - "coef_duration_shift_for_subsequent_sub_tour_of_... -10.333603 -0.184400 \n", - "coef_early_end_at_5_6 -25.000000 -2.928312 \n", - "coef_early_start_at_5 -2.204068 -7.765548 \n", - "coef_evening_end_at_19_20_21 -4.521037 -2.319982 \n", - "coef_evening_start_at_19_20_21 -0.325741 -1.015090 \n", - "coef_late_end_at_22_23 -11.516565 -2.319982 \n", - "coef_late_start_at_22_23 -5.142925 -0.737570 \n", - "coef_midday_end_at_10_11_12 -1.305196 -2.297264 \n", - "coef_midday_end_at_13_14 0.000000 0.000000 \n", - "coef_midday_start_at_10_11_12 0.000000 0.000000 \n", - "coef_midday_start_at_13_14_15 -1.051562 -0.775022 \n", - "coef_pm_peak_end_at_15 -1.432981 -0.578344 \n", - "coef_pm_peak_end_at_16 -2.055109 -1.094087 \n", - "coef_pm_peak_end_at_17 -2.404252 -1.165847 \n", - "coef_pm_peak_end_at_18 -3.500372 -1.496131 \n", - "coef_pm_peak_start_at_16_17_18 -0.798588 -0.227528 \n", - "coef_start_shift_for_business_related_ -0.083357 -0.111300 \n", - "coef_start_shift_for_first_sub_tour_of_same_wor... -0.168324 -0.543300 \n", - "coef_start_shift_for_inbound_auto_travel_time_o... -0.099019 0.000650 \n", - "coef_start_shift_for_number_of_individual_nonma... 0.026777 -0.012800 \n", - "coef_start_shift_for_number_of_joint_tours -0.019722 -0.020600 \n", - "coef_start_shift_for_number_of_mandatory_tours 0.059018 -0.019300 \n", - "coef_start_shift_for_outbound_auto_travel_time_... 0.100349 0.000650 \n", - "coef_start_shift_for_subsequent_sub_tour_of_sam... -0.360206 -0.184400 \n", + " value best \\\n", + "param_name \n", + "coef_am_peak_end -2.543876 -2.543876 \n", + "coef_am_peak_start_at_6 -5.790935 -5.790935 \n", + "coef_am_peak_start_at_7 -4.238642 -4.238642 \n", + "coef_am_peak_start_at_8 -2.371798 -2.371798 \n", + "coef_am_peak_start_at_9 -2.106247 -2.106247 \n", + "coef_dummy_for_business_related_purpose_and_dur... -1.656086 -1.656086 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 1.371453 1.371453 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 2.454861 2.454861 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 1.832150 1.832150 \n", + "coef_dummy_for_eating_out_purpose_and_duration_... 0.534786 0.534786 \n", + "coef_duration_of_0_hours -1.056506 -1.056506 \n", + "coef_duration_of_11_to_13_hours 0.292100 0.292100 \n", + "coef_duration_of_14_to_18_hours 0.000000 0.000000 \n", + "coef_duration_of_1_hour 0.000000 0.000000 \n", + "coef_duration_of_2_to_3_hours -1.478463 -1.478463 \n", + "coef_duration_of_4_to_5_hours -1.032651 -1.032651 \n", + "coef_duration_of_6_to_7_hours 1.074781 1.074781 \n", + "coef_duration_of_8_to_10_hours 1.476278 1.476278 \n", + "coef_duration_shift_for_business_related_ 0.237322 0.237322 \n", + "coef_duration_shift_for_first_sub_tour_of_same_... -0.199899 -0.199899 \n", + "coef_duration_shift_for_inbound_auto_travel_tim... 0.022979 0.022979 \n", + "coef_duration_shift_for_number_of_individual_no... -0.075913 -0.075913 \n", + "coef_duration_shift_for_number_of_joint_tours -0.234618 -0.234618 \n", + "coef_duration_shift_for_number_of_mandatory_tours -0.909117 -0.909117 \n", + "coef_duration_shift_for_outbound_auto_travel_ti... -0.002863 -0.002863 \n", + "coef_duration_shift_for_subsequent_sub_tour_of_... -0.371148 -0.371148 \n", + "coef_early_end_at_5_6 -2.693000 -2.693000 \n", + "coef_early_start_at_5 -7.645209 -7.645209 \n", + "coef_evening_end_at_19_20_21 -2.460690 -2.460690 \n", + "coef_evening_start_at_19_20_21 -0.786571 -0.786571 \n", + "coef_late_end_at_22_23 -2.391664 -2.391664 \n", + "coef_late_start_at_22_23 -0.890587 -0.890587 \n", + "coef_midday_end_at_10_11_12 -2.145575 -2.145575 \n", + "coef_midday_end_at_13_14 0.000000 0.000000 \n", + "coef_midday_start_at_10_11_12 0.000000 0.000000 \n", + "coef_midday_start_at_13_14_15 -0.665045 -0.665045 \n", + "coef_pm_peak_end_at_15 -0.586475 -0.586475 \n", + "coef_pm_peak_end_at_16 -1.337297 -1.337297 \n", + "coef_pm_peak_end_at_17 -1.432487 -1.432487 \n", + "coef_pm_peak_end_at_18 -1.702240 -1.702240 \n", + "coef_pm_peak_start_at_16_17_18 -0.000431 -0.000431 \n", + "coef_start_shift_for_business_related_ -0.071618 -0.071618 \n", + "coef_start_shift_for_first_sub_tour_of_same_wor... -0.458549 -0.458549 \n", + "coef_start_shift_for_inbound_auto_travel_time_o... -0.011025 -0.011025 \n", + "coef_start_shift_for_number_of_individual_nonma... -0.019137 -0.019137 \n", + "coef_start_shift_for_number_of_joint_tours 0.025502 0.025502 \n", + "coef_start_shift_for_number_of_mandatory_tours -0.067479 -0.067479 \n", + "coef_start_shift_for_outbound_auto_travel_time_... 0.010616 0.010616 \n", + "coef_start_shift_for_subsequent_sub_tour_of_sam... -0.117673 -0.117673 \n", "\n", - " nullvalue minimum \\\n", - "coef_am_peak_end 0.0 -25.0 \n", - "coef_am_peak_start_at_6 0.0 -25.0 \n", - "coef_am_peak_start_at_7 0.0 -25.0 \n", - "coef_am_peak_start_at_8 0.0 -25.0 \n", - "coef_am_peak_start_at_9 0.0 -25.0 \n", - "coef_dummy_for_business_related_purpose_and_dur... 0.0 -25.0 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 0.0 -25.0 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 0.0 -25.0 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 0.0 -25.0 \n", - "coef_dummy_for_eating_out_purpose_and_duration_... 0.0 -25.0 \n", - "coef_duration_of_0_hours 0.0 -25.0 \n", - "coef_duration_of_11_to_13_hours 0.0 -25.0 \n", - "coef_duration_of_14_to_18_hours 0.0 -25.0 \n", - "coef_duration_of_1_hour 0.0 -25.0 \n", - "coef_duration_of_2_to_3_hours 0.0 -25.0 \n", - "coef_duration_of_4_to_5_hours 0.0 -25.0 \n", - "coef_duration_of_6_to_7_hours 0.0 -25.0 \n", - "coef_duration_of_8_to_10_hours 0.0 -25.0 \n", - "coef_duration_shift_for_business_related_ 0.0 -25.0 \n", - "coef_duration_shift_for_first_sub_tour_of_same_... 0.0 -25.0 \n", - "coef_duration_shift_for_inbound_auto_travel_tim... 0.0 -25.0 \n", - "coef_duration_shift_for_number_of_individual_no... 0.0 -25.0 \n", - "coef_duration_shift_for_number_of_joint_tours 0.0 -25.0 \n", - "coef_duration_shift_for_number_of_mandatory_tours 0.0 -25.0 \n", - "coef_duration_shift_for_outbound_auto_travel_ti... 0.0 -25.0 \n", - "coef_duration_shift_for_subsequent_sub_tour_of_... 0.0 -25.0 \n", - "coef_early_end_at_5_6 0.0 -25.0 \n", - "coef_early_start_at_5 0.0 -25.0 \n", - "coef_evening_end_at_19_20_21 0.0 -25.0 \n", - "coef_evening_start_at_19_20_21 0.0 -25.0 \n", - "coef_late_end_at_22_23 0.0 -25.0 \n", - "coef_late_start_at_22_23 0.0 -25.0 \n", - "coef_midday_end_at_10_11_12 0.0 -25.0 \n", - "coef_midday_end_at_13_14 0.0 -25.0 \n", - "coef_midday_start_at_10_11_12 0.0 -25.0 \n", - "coef_midday_start_at_13_14_15 0.0 -25.0 \n", - "coef_pm_peak_end_at_15 0.0 -25.0 \n", - "coef_pm_peak_end_at_16 0.0 -25.0 \n", - 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" maximum holdfast note \\\n", - "coef_am_peak_end 25.0 0 \n", - "coef_am_peak_start_at_6 25.0 0 \n", - "coef_am_peak_start_at_7 25.0 0 \n", - "coef_am_peak_start_at_8 25.0 0 \n", - "coef_am_peak_start_at_9 25.0 0 \n", - "coef_dummy_for_business_related_purpose_and_dur... 25.0 0 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 25.0 0 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 25.0 0 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 25.0 0 \n", - "coef_dummy_for_eating_out_purpose_and_duration_... 25.0 0 \n", - "coef_duration_of_0_hours 25.0 0 \n", - "coef_duration_of_11_to_13_hours 25.0 0 \n", - "coef_duration_of_14_to_18_hours 25.0 1 \n", - "coef_duration_of_1_hour 25.0 1 \n", - "coef_duration_of_2_to_3_hours 25.0 0 \n", - "coef_duration_of_4_to_5_hours 25.0 0 \n", - "coef_duration_of_6_to_7_hours 25.0 0 \n", - "coef_duration_of_8_to_10_hours 25.0 0 \n", - "coef_duration_shift_for_business_related_ 25.0 0 \n", - "coef_duration_shift_for_first_sub_tour_of_same_... 25.0 0 \n", - "coef_duration_shift_for_inbound_auto_travel_tim... 25.0 0 \n", - "coef_duration_shift_for_number_of_individual_no... 25.0 0 \n", - "coef_duration_shift_for_number_of_joint_tours 25.0 0 \n", - "coef_duration_shift_for_number_of_mandatory_tours 25.0 0 \n", - "coef_duration_shift_for_outbound_auto_travel_ti... 25.0 0 \n", - "coef_duration_shift_for_subsequent_sub_tour_of_... 25.0 0 \n", - "coef_early_end_at_5_6 25.0 0 \n", - "coef_early_start_at_5 25.0 0 \n", - "coef_evening_end_at_19_20_21 25.0 0 \n", - "coef_evening_start_at_19_20_21 25.0 0 \n", - "coef_late_end_at_22_23 25.0 0 \n", - "coef_late_start_at_22_23 25.0 0 \n", - "coef_midday_end_at_10_11_12 25.0 0 \n", - "coef_midday_end_at_13_14 25.0 1 \n", - "coef_midday_start_at_10_11_12 25.0 1 \n", - "coef_midday_start_at_13_14_15 25.0 0 \n", - "coef_pm_peak_end_at_15 25.0 0 \n", - "coef_pm_peak_end_at_16 25.0 0 \n", - "coef_pm_peak_end_at_17 25.0 0 \n", - "coef_pm_peak_end_at_18 25.0 0 \n", - "coef_pm_peak_start_at_16_17_18 25.0 0 \n", - "coef_start_shift_for_business_related_ 25.0 0 \n", - "coef_start_shift_for_first_sub_tour_of_same_wor... 25.0 0 \n", - "coef_start_shift_for_inbound_auto_travel_time_o... 25.0 0 \n", - "coef_start_shift_for_number_of_individual_nonma... 25.0 0 \n", - "coef_start_shift_for_number_of_joint_tours 25.0 0 \n", - "coef_start_shift_for_number_of_mandatory_tours 25.0 0 \n", - "coef_start_shift_for_outbound_auto_travel_time_... 25.0 0 \n", - "coef_start_shift_for_subsequent_sub_tour_of_sam... 25.0 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_am_peak_end 25.0 0.0 \n", + "coef_am_peak_start_at_6 25.0 0.0 \n", + "coef_am_peak_start_at_7 25.0 0.0 \n", + "coef_am_peak_start_at_8 25.0 0.0 \n", + "coef_am_peak_start_at_9 25.0 0.0 \n", + "coef_dummy_for_business_related_purpose_and_dur... 25.0 0.0 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 25.0 0.0 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 25.0 0.0 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 25.0 0.0 \n", + "coef_dummy_for_eating_out_purpose_and_duration_... 25.0 0.0 \n", + "coef_duration_of_0_hours 25.0 0.0 \n", + "coef_duration_of_11_to_13_hours 25.0 0.0 \n", + "coef_duration_of_14_to_18_hours 0.0 0.0 \n", + "coef_duration_of_1_hour 0.0 0.0 \n", + "coef_duration_of_2_to_3_hours 25.0 0.0 \n", + "coef_duration_of_4_to_5_hours 25.0 0.0 \n", + "coef_duration_of_6_to_7_hours 25.0 0.0 \n", + "coef_duration_of_8_to_10_hours 25.0 0.0 \n", + "coef_duration_shift_for_business_related_ 25.0 0.0 \n", + "coef_duration_shift_for_first_sub_tour_of_same_... 25.0 0.0 \n", + "coef_duration_shift_for_inbound_auto_travel_tim... 25.0 0.0 \n", + "coef_duration_shift_for_number_of_individual_no... 25.0 0.0 \n", + "coef_duration_shift_for_number_of_joint_tours 25.0 0.0 \n", + "coef_duration_shift_for_number_of_mandatory_tours 25.0 0.0 \n", + "coef_duration_shift_for_outbound_auto_travel_ti... 25.0 0.0 \n", + "coef_duration_shift_for_subsequent_sub_tour_of_... 25.0 0.0 \n", + "coef_early_end_at_5_6 25.0 0.0 \n", + "coef_early_start_at_5 25.0 0.0 \n", + "coef_evening_end_at_19_20_21 25.0 0.0 \n", + "coef_evening_start_at_19_20_21 25.0 0.0 \n", + "coef_late_end_at_22_23 25.0 0.0 \n", + "coef_late_start_at_22_23 25.0 0.0 \n", + "coef_midday_end_at_10_11_12 25.0 0.0 \n", + "coef_midday_end_at_13_14 0.0 0.0 \n", + "coef_midday_start_at_10_11_12 0.0 0.0 \n", + "coef_midday_start_at_13_14_15 25.0 0.0 \n", + "coef_pm_peak_end_at_15 25.0 0.0 \n", + "coef_pm_peak_end_at_16 25.0 0.0 \n", + "coef_pm_peak_end_at_17 25.0 0.0 \n", + "coef_pm_peak_end_at_18 25.0 0.0 \n", + "coef_pm_peak_start_at_16_17_18 25.0 0.0 \n", + "coef_start_shift_for_business_related_ 25.0 0.0 \n", + "coef_start_shift_for_first_sub_tour_of_same_wor... 25.0 0.0 \n", + "coef_start_shift_for_inbound_auto_travel_time_o... 25.0 0.0 \n", + "coef_start_shift_for_number_of_individual_nonma... 25.0 0.0 \n", + "coef_start_shift_for_number_of_joint_tours 25.0 0.0 \n", + "coef_start_shift_for_number_of_mandatory_tours 25.0 0.0 \n", + "coef_start_shift_for_outbound_auto_travel_time_... 25.0 0.0 \n", + "coef_start_shift_for_subsequent_sub_tour_of_sam... 25.0 0.0 \n", "\n", - " best \n", - "coef_am_peak_end -1.373169 \n", - "coef_am_peak_start_at_6 -20.592814 \n", - "coef_am_peak_start_at_7 -2.826984 \n", - "coef_am_peak_start_at_8 -1.196528 \n", - "coef_am_peak_start_at_9 -1.619897 \n", - "coef_dummy_for_business_related_purpose_and_dur... -0.663129 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 1.151827 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 2.625436 \n", - "coef_dummy_for_eating_out_purpose_and_departure... 2.360981 \n", - "coef_dummy_for_eating_out_purpose_and_duration_... 0.310405 \n", - "coef_duration_of_0_hours 9.959985 \n", - "coef_duration_of_11_to_13_hours -0.374055 \n", - "coef_duration_of_14_to_18_hours 0.000000 \n", - "coef_duration_of_1_hour 0.000000 \n", - "coef_duration_of_2_to_3_hours 9.181283 \n", - "coef_duration_of_4_to_5_hours -0.483141 \n", - "coef_duration_of_6_to_7_hours 10.535613 \n", - "coef_duration_of_8_to_10_hours 10.402183 \n", - "coef_duration_shift_for_business_related_ 0.600044 \n", - "coef_duration_shift_for_first_sub_tour_of_same_... 0.319885 \n", - "coef_duration_shift_for_inbound_auto_travel_tim... -0.118575 \n", - "coef_duration_shift_for_number_of_individual_no... 0.009894 \n", - "coef_duration_shift_for_number_of_joint_tours -0.577681 \n", - "coef_duration_shift_for_number_of_mandatory_tours -1.058788 \n", - "coef_duration_shift_for_outbound_auto_travel_ti... 0.145324 \n", - "coef_duration_shift_for_subsequent_sub_tour_of_... -10.333603 \n", - "coef_early_end_at_5_6 -25.000000 \n", - "coef_early_start_at_5 -2.204068 \n", - "coef_evening_end_at_19_20_21 -4.521037 \n", - "coef_evening_start_at_19_20_21 -0.325741 \n", - "coef_late_end_at_22_23 -11.516565 \n", - "coef_late_start_at_22_23 -5.142925 \n", - "coef_midday_end_at_10_11_12 -1.305196 \n", - "coef_midday_end_at_13_14 0.000000 \n", - "coef_midday_start_at_10_11_12 0.000000 \n", - "coef_midday_start_at_13_14_15 -1.051562 \n", - "coef_pm_peak_end_at_15 -1.432981 \n", - "coef_pm_peak_end_at_16 -2.055109 \n", - "coef_pm_peak_end_at_17 -2.404252 \n", - "coef_pm_peak_end_at_18 -3.500372 \n", - "coef_pm_peak_start_at_16_17_18 -0.798588 \n", - "coef_start_shift_for_business_related_ -0.083357 \n", - "coef_start_shift_for_first_sub_tour_of_same_wor... -0.168324 \n", - "coef_start_shift_for_inbound_auto_travel_time_o... -0.099019 \n", - "coef_start_shift_for_number_of_individual_nonma... 0.026777 \n", - "coef_start_shift_for_number_of_joint_tours -0.019722 \n", - "coef_start_shift_for_number_of_mandatory_tours 0.059018 \n", - "coef_start_shift_for_outbound_auto_travel_time_... 0.100349 \n", - "coef_start_shift_for_subsequent_sub_tour_of_sam... -0.360206 " + " holdfast \n", + "param_name \n", + "coef_am_peak_end 0 \n", + "coef_am_peak_start_at_6 0 \n", + "coef_am_peak_start_at_7 0 \n", + "coef_am_peak_start_at_8 0 \n", + "coef_am_peak_start_at_9 0 \n", + "coef_dummy_for_business_related_purpose_and_dur... 0 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 0 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 0 \n", + "coef_dummy_for_eating_out_purpose_and_departure... 0 \n", + "coef_dummy_for_eating_out_purpose_and_duration_... 0 \n", + "coef_duration_of_0_hours 0 \n", + "coef_duration_of_11_to_13_hours 0 \n", + "coef_duration_of_14_to_18_hours 1 \n", + "coef_duration_of_1_hour 1 \n", + "coef_duration_of_2_to_3_hours 0 \n", + "coef_duration_of_4_to_5_hours 0 \n", + "coef_duration_of_6_to_7_hours 0 \n", + "coef_duration_of_8_to_10_hours 0 \n", + "coef_duration_shift_for_business_related_ 0 \n", + "coef_duration_shift_for_first_sub_tour_of_same_... 0 \n", + "coef_duration_shift_for_inbound_auto_travel_tim... 0 \n", + "coef_duration_shift_for_number_of_individual_no... 0 \n", + "coef_duration_shift_for_number_of_joint_tours 0 \n", + "coef_duration_shift_for_number_of_mandatory_tours 0 \n", + "coef_duration_shift_for_outbound_auto_travel_ti... 0 \n", + "coef_duration_shift_for_subsequent_sub_tour_of_... 0 \n", + "coef_early_end_at_5_6 0 \n", + "coef_early_start_at_5 0 \n", + "coef_evening_end_at_19_20_21 0 \n", + "coef_evening_start_at_19_20_21 0 \n", + "coef_late_end_at_22_23 0 \n", + "coef_late_start_at_22_23 0 \n", + "coef_midday_end_at_10_11_12 0 \n", + "coef_midday_end_at_13_14 1 \n", + "coef_midday_start_at_10_11_12 1 \n", + "coef_midday_start_at_13_14_15 0 \n", + "coef_pm_peak_end_at_15 0 \n", + "coef_pm_peak_end_at_16 0 \n", + "coef_pm_peak_end_at_17 0 \n", + "coef_pm_peak_end_at_18 0 \n", + "coef_pm_peak_start_at_16_17_18 0 \n", + "coef_start_shift_for_business_related_ 0 \n", + "coef_start_shift_for_first_sub_tour_of_same_wor... 0 \n", + "coef_start_shift_for_inbound_auto_travel_time_o... 0 \n", + "coef_start_shift_for_number_of_individual_nonma... 0 \n", + "coef_start_shift_for_number_of_joint_tours 0 \n", + "coef_start_shift_for_number_of_mandatory_tours 0 \n", + "coef_start_shift_for_outbound_auto_travel_time_... 0 \n", + "coef_start_shift_for_subsequent_sub_tour_of_sam... 0 " ] }, "metadata": {}, "output_type": "display_data" }, - 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" 1.151827\n", + " 1.371453\n", " \n", " \n", " coef_dummy_for_eating_out_purpose_and_departure_at_12\n", - " 2.625436\n", + " 2.454861\n", " \n", " \n", " coef_dummy_for_eating_out_purpose_and_departure_at_13\n", - " 2.360981\n", + " 1.832150\n", " \n", " \n", " coef_dummy_for_eating_out_purpose_and_duration_of_1_hour\n", - " 0.310405\n", + " 0.534786\n", " \n", " \n", " coef_duration_of_0_hours\n", - " 9.959985\n", + " -1.056506\n", " \n", " \n", " coef_duration_of_11_to_13_hours\n", - " -0.374055\n", + " 0.292100\n", " \n", " \n", " coef_duration_of_14_to_18_hours\n", @@ -2754,79 +2901,79 @@ " \n", " \n", " coef_duration_of_2_to_3_hours\n", - " 9.181283\n", + " -1.478463\n", " \n", " \n", " coef_duration_of_4_to_5_hours\n", - " -0.483141\n", + " -1.032651\n", " \n", " \n", " coef_duration_of_6_to_7_hours\n", - " 10.535613\n", + " 1.074781\n", " \n", " \n", " coef_duration_of_8_to_10_hours\n", - " 10.402183\n", + " 1.476278\n", " \n", " \n", " coef_duration_shift_for_business_related_\n", - " 0.600044\n", + " 0.237322\n", " \n", " \n", " coef_duration_shift_for_first_sub_tour_of_same_work_tour\n", - " 0.319885\n", + " -0.199899\n", " \n", " \n", " coef_duration_shift_for_inbound_auto_travel_time_off_peak\n", - " -0.118575\n", + " 0.022979\n", " \n", " \n", " coef_duration_shift_for_number_of_individual_nonmandatory_tours\n", - " 0.009894\n", + " -0.075913\n", " \n", " \n", " coef_duration_shift_for_number_of_joint_tours\n", - " -0.577681\n", + " -0.234618\n", " \n", " \n", " coef_duration_shift_for_number_of_mandatory_tours\n", - " -1.058788\n", + " -0.909117\n", " \n", " \n", " coef_duration_shift_for_outbound_auto_travel_time_off_peak\n", - " 0.145324\n", + " -0.002863\n", " \n", " \n", " coef_duration_shift_for_subsequent_sub_tour_of_same_work_tour\n", - " -10.333603\n", + " -0.371148\n", " \n", " \n", " coef_early_end_at_5_6\n", - " -25.000000\n", + " -2.693000\n", " \n", " \n", " coef_early_start_at_5\n", - " -2.204068\n", + " -7.645209\n", " \n", " \n", " coef_evening_end_at_19_20_21\n", - " -4.521037\n", + " -2.460690\n", " \n", " \n", " coef_evening_start_at_19_20_21\n", - " -0.325741\n", + " -0.786571\n", " \n", " \n", " coef_late_end_at_22_23\n", - " -11.516565\n", + " -2.391664\n", " \n", " \n", " coef_late_start_at_22_23\n", - " -5.142925\n", + " -0.890587\n", " \n", " \n", " coef_midday_end_at_10_11_12\n", - " -1.305196\n", + " -2.145575\n", " \n", " \n", " coef_midday_end_at_13_14\n", @@ -2838,62 +2985,62 @@ " \n", " \n", " coef_midday_start_at_13_14_15\n", - " -1.051562\n", + " -0.665045\n", " \n", " \n", " coef_pm_peak_end_at_15\n", - " -1.432981\n", + " -0.586475\n", " \n", " \n", " coef_pm_peak_end_at_16\n", - " -2.055109\n", + " -1.337297\n", " \n", " \n", " coef_pm_peak_end_at_17\n", - " -2.404252\n", + " -1.432487\n", " \n", " \n", " coef_pm_peak_end_at_18\n", - " -3.500372\n", + " -1.702240\n", " \n", " \n", " coef_pm_peak_start_at_16_17_18\n", - " -0.798588\n", + " -0.000431\n", " \n", " \n", " coef_start_shift_for_business_related_\n", - " -0.083357\n", + " -0.071618\n", " \n", " \n", " coef_start_shift_for_first_sub_tour_of_same_work_tour\n", - " -0.168324\n", + " -0.458549\n", " \n", " \n", " coef_start_shift_for_inbound_auto_travel_time_off_peak\n", - " -0.099019\n", + " -0.011025\n", " \n", " \n", " coef_start_shift_for_number_of_individual_nonmandatory_tours\n", - " 0.026777\n", + " -0.019137\n", " \n", " \n", " coef_start_shift_for_number_of_joint_tours\n", - " -0.019722\n", + " 0.025502\n", " \n", " \n", " coef_start_shift_for_number_of_mandatory_tours\n", - " 0.059018\n", + " -0.067479\n", " \n", " \n", " coef_start_shift_for_outbound_auto_travel_time_off_peak\n", - " 0.100349\n", + " 0.010616\n", " \n", " \n", " coef_start_shift_for_subsequent_sub_tour_of_same_work_tour\n", - " -0.360206\n", + " -0.117673\n", " \n", " \n", - "loglike-1401.9305368056416d_loglike\n", + "
logloss2.887476765558531d_logloss\n", " \n", " \n", " \n", @@ -2903,51 +3050,51 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2959,79 +3106,79 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3043,185 +3190,185 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - "
coef_am_peak_end1.755671e-04-4.854218e-05
coef_am_peak_start_at_6-3.041241e-081.910552e-05
coef_am_peak_start_at_7-8.670115e-059.916948e-07
coef_am_peak_start_at_85.028242e-054.037261e-05
coef_am_peak_start_at_95.798423e-041.440668e-04
coef_dummy_for_business_related_purpose_and_duration_from_0_to_11.601202e-04-1.280892e-04
coef_dummy_for_eating_out_purpose_and_departure_at_11-3.475790e-051.803296e-04
coef_dummy_for_eating_out_purpose_and_departure_at_12-5.671365e-05-1.483346e-04
coef_dummy_for_eating_out_purpose_and_departure_at_13-2.578419e-051.713493e-04
coef_dummy_for_eating_out_purpose_and_duration_of_1_hour1.872976e-04-2.135625e-04
coef_duration_of_0_hours-1.158083e-038.415289e-05
coef_duration_of_11_to_13_hours-1.673798e-06-6.167370e-06
coef_duration_of_14_to_18_hours
coef_duration_of_2_to_3_hours9.972871e-04-1.347427e-04
coef_duration_of_4_to_5_hours1.179130e-041.170007e-05
coef_duration_of_6_to_7_hours-3.119839e-04-7.452797e-05
coef_duration_of_8_to_10_hours1.749841e-06-4.591330e-06
coef_duration_shift_for_business_related_-1.422810e-031.631608e-04
coef_duration_shift_for_first_sub_tour_of_same_work_tour-6.454765e-046.894456e-05
coef_duration_shift_for_inbound_auto_travel_time_off_peak8.510358e-03-1.645782e-04
coef_duration_shift_for_number_of_individual_nonmandatory_tours-1.352429e-03-1.965446e-04
coef_duration_shift_for_number_of_joint_tours1.961158e-042.409234e-04
coef_duration_shift_for_number_of_mandatory_tours-6.872100e-04-9.571494e-05
coef_duration_shift_for_outbound_auto_travel_time_off_peak7.485785e-035.935593e-05
coef_duration_shift_for_subsequent_sub_tour_of_same_work_tour-5.553217e-06-5.141939e-05
coef_early_end_at_5_6-4.444583e-111.627725e-05
coef_early_start_at_55.404961e-057.249674e-05
coef_evening_end_at_19_20_21-3.938375e-04-1.112621e-04
coef_evening_start_at_19_20_21-1.613864e-041.220311e-04
coef_late_end_at_22_23-3.810622e-04-5.597541e-05
coef_late_start_at_22_23-1.853500e-06-9.478339e-05
coef_midday_end_at_10_11_126.960928e-04-2.023533e-05
coef_midday_end_at_13_14
coef_midday_start_at_13_14_158.833428e-058.980809e-05
coef_pm_peak_end_at_15-2.278624e-04-2.232845e-04
coef_pm_peak_end_at_16-3.377131e-05-4.780466e-05
coef_pm_peak_end_at_17-4.096157e-043.154057e-04
coef_pm_peak_end_at_18-4.205497e-04-1.485193e-04
coef_pm_peak_start_at_16_17_18-8.339350e-04-3.850429e-05
coef_start_shift_for_business_related_1.194878e-04-2.801495e-06
coef_start_shift_for_first_sub_tour_of_same_work_tour-1.481936e-021.192141e-04
coef_start_shift_for_inbound_auto_travel_time_off_peak-1.201511e-017.248793e-05
coef_start_shift_for_number_of_individual_nonmandatory_tours-1.882400e-03-4.273167e-05
coef_start_shift_for_number_of_joint_tours-1.517039e-034.702349e-05
coef_start_shift_for_number_of_mandatory_tours-1.475028e-02-4.354135e-05
coef_start_shift_for_outbound_auto_travel_time_off_peak-1.163942e-01-4.170920e-05
coef_start_shift_for_subsequent_sub_tour_of_same_work_tour2.856907e-051.286129e-04
nit68nfev132njev68status0message'Optimization terminated successfully'successTrueelapsed_time0:00:01.774115method'slsqp'n_cases464iteration_number68logloss3.021402018977676" + "nit68nfev75njev68status0message'Optimization terminated successfully'successTrueelapsed_time0:00:05.198235method'slsqp'n_cases6036iteration_number68loglike-17373.947698365682" ], "text/plain": [ - "┣ x: coef_am_peak_end -1.373169\n", - "┃ coef_am_peak_start_at_6 -20.592814\n", - "┃ coef_am_peak_start_at_7 -2.826984\n", - "┃ coef_am_peak_start_at_8 -1.196528\n", - "┃ coef_am_peak_start_at_9 -1.619897\n", - "┃ coef_dummy_for_business_related_purpose_and_duration_from_0_to_1 -0.663129\n", - "┃ coef_dummy_for_eating_out_purpose_and_departure_at_11 1.151827\n", - "┃ coef_dummy_for_eating_out_purpose_and_departure_at_12 2.625436\n", - "┃ coef_dummy_for_eating_out_purpose_and_departure_at_13 2.360981\n", - "┃ coef_dummy_for_eating_out_purpose_and_duration_of_1_hour 0.310405\n", - "┃ coef_duration_of_0_hours 9.959985\n", - 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"┃ coef_evening_end_at_19_20_21 -4.521037\n", - "┃ coef_evening_start_at_19_20_21 -0.325741\n", - "┃ coef_late_end_at_22_23 -11.516565\n", - "┃ coef_late_start_at_22_23 -5.142925\n", - "┃ coef_midday_end_at_10_11_12 -1.305196\n", - "┃ coef_midday_end_at_13_14 0.000000\n", - "┃ coef_midday_start_at_10_11_12 0.000000\n", - "┃ coef_midday_start_at_13_14_15 -1.051562\n", - "┃ coef_pm_peak_end_at_15 -1.432981\n", - "┃ coef_pm_peak_end_at_16 -2.055109\n", - "┃ coef_pm_peak_end_at_17 -2.404252\n", - "┃ coef_pm_peak_end_at_18 -3.500372\n", - "┃ coef_pm_peak_start_at_16_17_18 -0.798588\n", - "┃ coef_start_shift_for_business_related_ -0.083357\n", - "┃ coef_start_shift_for_first_sub_tour_of_same_work_tour -0.168324\n", - "┃ coef_start_shift_for_inbound_auto_travel_time_off_peak -0.099019\n", - "┃ coef_start_shift_for_number_of_individual_nonmandatory_tours 0.026777\n", - "┃ coef_start_shift_for_number_of_joint_tours -0.019722\n", - "┃ coef_start_shift_for_number_of_mandatory_tours 0.059018\n", - 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"┃ coef_midday_start_at_13_14_15 8.833428e-05\n", - "┃ coef_pm_peak_end_at_15 -2.278624e-04\n", - "┃ coef_pm_peak_end_at_16 -3.377131e-05\n", - "┃ coef_pm_peak_end_at_17 -4.096157e-04\n", - "┃ coef_pm_peak_end_at_18 -4.205497e-04\n", - "┃ coef_pm_peak_start_at_16_17_18 -8.339350e-04\n", - "┃ coef_start_shift_for_business_related_ 1.194878e-04\n", - "┃ coef_start_shift_for_first_sub_tour_of_same_work_tour -1.481936e-02\n", - "┃ coef_start_shift_for_inbound_auto_travel_time_off_peak -1.201511e-01\n", - "┃ coef_start_shift_for_number_of_individual_nonmandatory_tours -1.882400e-03\n", - "┃ coef_start_shift_for_number_of_joint_tours -1.517039e-03\n", - "┃ coef_start_shift_for_number_of_mandatory_tours -1.475028e-02\n", - "┃ coef_start_shift_for_outbound_auto_travel_time_off_peak -1.163942e-01\n", - "┃ coef_start_shift_for_subsequent_sub_tour_of_same_work_tour 2.856907e-05\n", + "┃ coef_midday_start_at_13_14_15 8.980809e-05\n", + "┃ coef_pm_peak_end_at_15 -2.232845e-04\n", + "┃ coef_pm_peak_end_at_16 -4.780466e-05\n", + "┃ coef_pm_peak_end_at_17 3.154057e-04\n", + "┃ coef_pm_peak_end_at_18 -1.485193e-04\n", + "┃ coef_pm_peak_start_at_16_17_18 -3.850429e-05\n", + "┃ coef_start_shift_for_business_related_ -2.801495e-06\n", + "┃ coef_start_shift_for_first_sub_tour_of_same_work_tour 1.192141e-04\n", + "┃ coef_start_shift_for_inbound_auto_travel_time_off_peak 7.248793e-05\n", + "┃ coef_start_shift_for_number_of_individual_nonmandatory_tours -4.273167e-05\n", + "┃ coef_start_shift_for_number_of_joint_tours 4.702349e-05\n", + "┃ coef_start_shift_for_number_of_mandatory_tours -4.354135e-05\n", + "┃ coef_start_shift_for_outbound_auto_travel_time_off_peak -4.170920e-05\n", + "┃ coef_start_shift_for_subsequent_sub_tour_of_same_work_tour 1.286129e-04\n", "┃ dtype: float64\n", "┣ nit: 68\n", - "┣ nfev: 132\n", + "┣ nfev: 75\n", "┣ njev: 68\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=1, microseconds=774115)\n", + "┣ elapsed_time: datetime.timedelta(seconds=5, microseconds=198235)\n", "┣ method: 'slsqp'\n", - "┣ n_cases: 464\n", + "┣ n_cases: 6036\n", "┣ iteration_number: 68\n", - "┣ logloss: 3.021402018977676" + "┣ loglike: -17373.947698365682" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.estimate()" + "model.estimate(maxiter=900)" ] }, { @@ -3233,519 +3380,496 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
coef_am_peak_end-1.37 0.551-2.49* NA 0.00
coef_am_peak_start_at_6-20.6 7.33-2.81** NA 0.00
coef_am_peak_start_at_7-2.83 0.615-4.59*** NA 0.00
coef_am_peak_start_at_8-1.20 0.405-2.96** NA 0.00
coef_am_peak_start_at_9-1.62 0.372-4.35*** NA 0.00
coef_dummy_for_business_related_purpose_and_duration_from_0_to_1-0.663 0.597-1.11 NA 0.00
coef_dummy_for_eating_out_purpose_and_departure_at_11 1.15 0.559 2.06* NA 0.00
coef_dummy_for_eating_out_purpose_and_departure_at_12 2.63 0.598 4.39*** NA 0.00
coef_dummy_for_eating_out_purpose_and_departure_at_13 2.36 0.785 3.01** NA 0.00
coef_dummy_for_eating_out_purpose_and_duration_of_1_hour 0.310 0.516 0.60 NA 0.00
coef_duration_of_0_hours 9.96 1.24 8.06*** NA 0.00
coef_duration_of_11_to_13_hours-0.374 773.-0.00 NA 0.00
coef_duration_of_14_to_18_hours 0.00 NA NA NA 0.00fixed value
coef_duration_of_1_hour 0.00 NA NA NA 0.00fixed value
coef_duration_of_2_to_3_hours 9.18 1.26 7.27*** NA 0.00
coef_duration_of_4_to_5_hours-0.483 0.399-1.21 NA 0.00
coef_duration_of_6_to_7_hours 10.5 1.48 7.11*** NA 0.00
coef_duration_of_8_to_10_hours 10.4 1.83 5.70*** NA 0.00
coef_duration_shift_for_business_related_ 0.600 0.143 4.20*** NA 0.00
coef_duration_shift_for_first_sub_tour_of_same_work_tour 0.320 0.665 0.48 NA 0.00
coef_duration_shift_for_inbound_auto_travel_time_off_peak-0.119 0.0948-1.25 NA 0.00
coef_duration_shift_for_number_of_individual_nonmandatory_tours 0.00989 0.0574 0.17 NA 0.00
coef_duration_shift_for_number_of_joint_tours-0.578 0.294-1.96* NA 0.00
coef_duration_shift_for_number_of_mandatory_tours-1.06 0.652-1.62 NA 0.00
coef_duration_shift_for_outbound_auto_travel_time_off_peak 0.145 0.0956 1.52 NA 0.00
coef_duration_shift_for_subsequent_sub_tour_of_same_work_tour-10.3 424.-0.02 NA 0.00
coef_early_end_at_5_6-25.0 NA NA[*] 3.06 0.00coef_early_end_at_5_6 ≥ -25.0
coef_early_start_at_5-2.20 1.30-1.70 NA 0.00
coef_evening_end_at_19_20_21-4.52 1.26-3.59*** NA 0.00
coef_evening_start_at_19_20_21-0.326 1.53-0.21 NA 0.00
coef_late_end_at_22_23-11.5 51.4-0.22 NA 0.00
coef_late_start_at_22_23-5.14 736.-0.01 NA 0.00
coef_midday_end_at_10_11_12-1.31 0.238-5.49*** NA 0.00
coef_midday_end_at_13_14 0.00 NA NA NA 0.00fixed value
coef_midday_start_at_10_11_12 0.00 NA NA NA 0.00fixed value
coef_midday_start_at_13_14_15-1.05 0.239-4.41*** NA 0.00
coef_pm_peak_end_at_15-1.43 0.260-5.50*** NA 0.00
coef_pm_peak_end_at_16-2.06 0.451-4.56*** NA 0.00
coef_pm_peak_end_at_17-2.40 0.556-4.33*** NA 0.00
coef_pm_peak_end_at_18-3.50 0.738-4.74*** NA 0.00
coef_pm_peak_start_at_16_17_18-0.799 0.642-1.24 NA 0.00
coef_start_shift_for_business_related_-0.0834 0.144-0.58 NA 0.00
coef_start_shift_for_first_sub_tour_of_same_work_tour-0.168 0.135-1.25 NA 0.00
coef_start_shift_for_inbound_auto_travel_time_off_peak-0.0990 0.0641-1.54 NA 0.00
coef_start_shift_for_number_of_individual_nonmandatory_tours 0.0268 0.0292 0.92 NA 0.00
coef_start_shift_for_number_of_joint_tours-0.0197 0.122-0.16 NA 0.00
coef_start_shift_for_number_of_mandatory_tours 0.0590 0.0887 0.67 NA 0.00
coef_start_shift_for_outbound_auto_travel_time_off_peak 0.100 0.0650 1.54 NA 0.00
coef_start_shift_for_subsequent_sub_tour_of_same_work_tour-0.360 0.423-0.85 NA 0.00
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_am_peak_end-2.54 0.162-15.68*** 0.00
coef_am_peak_start_at_6-5.79 0.649-8.93*** 0.00
coef_am_peak_start_at_7-4.24 0.200-21.18*** 0.00
coef_am_peak_start_at_8-2.37 0.127-18.63*** 0.00
coef_am_peak_start_at_9-2.11 0.111-19.05*** 0.00
coef_dummy_for_business_related_purpose_and_duration_from_0_to_1-1.66 0.153-10.81*** 0.00
coef_dummy_for_eating_out_purpose_and_departure_at_11 1.37 0.130 10.56*** 0.00
coef_dummy_for_eating_out_purpose_and_departure_at_12 2.45 0.153 16.00*** 0.00
coef_dummy_for_eating_out_purpose_and_departure_at_13 1.83 0.204 8.98*** 0.00
coef_dummy_for_eating_out_purpose_and_duration_of_1_hour 0.535 0.128 4.17*** 0.00
coef_duration_of_0_hours-1.06 0.214-4.94*** 0.00
coef_duration_of_11_to_13_hours 0.292 5.22 0.06 0.00
coef_duration_of_14_to_18_hours 0.00 0.00 NA 0.00fixed value
coef_duration_of_1_hour 0.00 0.00 NA 0.00fixed value
coef_duration_of_2_to_3_hours-1.48 0.199-7.43*** 0.00
coef_duration_of_4_to_5_hours-1.03 0.160-6.46*** 0.00
coef_duration_of_6_to_7_hours 1.07 0.241 4.46*** 0.00
coef_duration_of_8_to_10_hours 1.48 0.409 3.61*** 0.00
coef_duration_shift_for_business_related_ 0.237 0.0416 5.71*** 0.00
coef_duration_shift_for_first_sub_tour_of_same_work_tour-0.200 0.159-1.26 0.00
coef_duration_shift_for_inbound_auto_travel_time_off_peak 0.0230 0.0131 1.76 0.00
coef_duration_shift_for_number_of_individual_nonmandatory_tours-0.0759 0.0200-3.79*** 0.00
coef_duration_shift_for_number_of_joint_tours-0.235 0.0632-3.71*** 0.00
coef_duration_shift_for_number_of_mandatory_tours-0.909 0.154-5.90*** 0.00
coef_duration_shift_for_outbound_auto_travel_time_off_peak-0.00286 0.0130-0.22 0.00
coef_duration_shift_for_subsequent_sub_tour_of_same_work_tour-0.371 0.303-1.22 0.00
coef_early_end_at_5_6-2.69 0.834-3.23** 0.00
coef_early_start_at_5-7.65 1.48-5.16*** 0.00
coef_evening_end_at_19_20_21-2.46 0.364-6.75*** 0.00
coef_evening_start_at_19_20_21-0.787 0.597-1.32 0.00
coef_late_end_at_22_23-2.39 1.21-1.98* 0.00
coef_late_start_at_22_23-0.891 1.85-0.48 0.00
coef_midday_end_at_10_11_12-2.15 0.0685-31.31*** 0.00
coef_midday_end_at_13_14 0.00 0.00 NA 0.00fixed value
coef_midday_start_at_10_11_12 0.00 0.00 NA 0.00fixed value
coef_midday_start_at_13_14_15-0.665 0.0663-10.04*** 0.00
coef_pm_peak_end_at_15-0.586 0.0676-8.68*** 0.00
coef_pm_peak_end_at_16-1.34 0.134-10.01*** 0.00
coef_pm_peak_end_at_17-1.43 0.165-8.68*** 0.00
coef_pm_peak_end_at_18-1.70 0.211-8.07*** 0.00
coef_pm_peak_start_at_16_17_18-0.000431 0.181-0.00 0.00
coef_start_shift_for_business_related_-0.0716 0.0540-1.33 0.00
coef_start_shift_for_first_sub_tour_of_same_work_tour-0.459 0.0714-6.42*** 0.00
coef_start_shift_for_inbound_auto_travel_time_off_peak-0.0110 0.0130-0.85 0.00
coef_start_shift_for_number_of_individual_nonmandatory_tours-0.0191 0.0140-1.37 0.00
coef_start_shift_for_number_of_joint_tours 0.0255 0.0364 0.70 0.00
coef_start_shift_for_number_of_mandatory_tours-0.0675 0.0648-1.04 0.00
coef_start_shift_for_outbound_auto_travel_time_off_peak 0.0106 0.0127 0.83 0.00
coef_start_shift_for_subsequent_sub_tour_of_same_work_tour-0.118 0.167-0.71 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -3766,7 +3890,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -3787,20 +3911,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model.to_xlsx(\n", " result_dir/f\"{modelname}_model_estimation.xlsx\", \n", @@ -3819,7 +3932,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -3852,31 +3965,31 @@ " \n", " 0\n", " coef_early_start_at_5\n", - " -2.204068\n", + " -7.645209\n", " F\n", " \n", " \n", " 1\n", " coef_am_peak_start_at_6\n", - " -20.592814\n", + " -5.790935\n", " F\n", " \n", " \n", " 2\n", " coef_am_peak_start_at_7\n", - " -2.826984\n", + " -4.238642\n", " F\n", " \n", " \n", " 3\n", " coef_am_peak_start_at_8\n", - " -1.196528\n", + " -2.371798\n", " F\n", " \n", " \n", " 4\n", " coef_am_peak_start_at_9\n", - " -1.619897\n", + " -2.106247\n", " F\n", " \n", " \n", @@ -3888,43 +4001,43 @@ " \n", " 6\n", " coef_midday_start_at_13_14_15\n", - " -1.051562\n", + " -0.665045\n", " F\n", " \n", " \n", " 7\n", " coef_pm_peak_start_at_16_17_18\n", - " -0.798588\n", + " -0.000431\n", " F\n", " \n", " \n", " 8\n", " coef_evening_start_at_19_20_21\n", - " -0.325741\n", + " -0.786571\n", " F\n", " \n", " \n", " 9\n", " coef_late_start_at_22_23\n", - " -5.142925\n", + " -0.890587\n", " F\n", " \n", " \n", " 10\n", " coef_early_end_at_5_6\n", - " -25.000000\n", + " -2.693000\n", " F\n", " \n", " \n", " 11\n", " coef_am_peak_end\n", - " -1.373169\n", + " -2.543876\n", " F\n", " \n", " \n", " 12\n", " coef_midday_end_at_10_11_12\n", - " -1.305196\n", + " -2.145575\n", " F\n", " \n", " \n", @@ -3936,43 +4049,43 @@ " \n", " 14\n", " coef_pm_peak_end_at_15\n", - " -1.432981\n", + " -0.586475\n", " F\n", " \n", " \n", " 15\n", " coef_pm_peak_end_at_16\n", - " -2.055109\n", + " -1.337297\n", " F\n", " \n", " \n", " 16\n", " coef_pm_peak_end_at_17\n", - " -2.404252\n", + " -1.432487\n", " F\n", " \n", " \n", " 17\n", " coef_pm_peak_end_at_18\n", - " -3.500372\n", + " -1.702240\n", " F\n", " \n", " \n", " 18\n", " coef_evening_end_at_19_20_21\n", - " -4.521037\n", + " -2.460690\n", " F\n", " \n", " \n", " 19\n", " coef_late_end_at_22_23\n", - " -11.516565\n", + " -2.391664\n", " F\n", " \n", " \n", " 20\n", " coef_duration_of_0_hours\n", - " 9.959985\n", + " -1.056506\n", " F\n", " \n", " \n", @@ -3984,31 +4097,31 @@ " \n", " 22\n", " coef_duration_of_2_to_3_hours\n", - " 9.181283\n", + " -1.478463\n", " F\n", " \n", " \n", " 23\n", " coef_duration_of_4_to_5_hours\n", - " -0.483141\n", + " -1.032651\n", " F\n", " \n", " \n", " 24\n", " coef_duration_of_6_to_7_hours\n", - " 10.535613\n", + " 1.074781\n", " F\n", " \n", " \n", " 25\n", " coef_duration_of_8_to_10_hours\n", - " 10.402183\n", + " 1.476278\n", " F\n", " \n", " \n", " 26\n", " coef_duration_of_11_to_13_hours\n", - " -0.374055\n", + " 0.292100\n", " F\n", " \n", " \n", @@ -4020,127 +4133,127 @@ " \n", " 28\n", " coef_start_shift_for_outbound_auto_travel_time...\n", - " 0.100349\n", + " 0.010616\n", " F\n", " \n", " \n", " 29\n", " coef_start_shift_for_inbound_auto_travel_time_...\n", - " -0.099019\n", + " -0.011025\n", " F\n", " \n", " \n", " 30\n", " coef_duration_shift_for_outbound_auto_travel_t...\n", - " 0.145324\n", + " -0.002863\n", " F\n", " \n", " \n", " 31\n", " coef_duration_shift_for_inbound_auto_travel_ti...\n", - " -0.118575\n", + " 0.022979\n", " F\n", " \n", " \n", " 32\n", " coef_start_shift_for_business_related_\n", - " -0.083357\n", + " -0.071618\n", " F\n", " \n", " \n", " 33\n", " coef_duration_shift_for_business_related_\n", - " 0.600044\n", + " 0.237322\n", " F\n", " \n", " \n", " 34\n", " coef_start_shift_for_first_sub_tour_of_same_wo...\n", - " -0.168324\n", + " -0.458549\n", " F\n", " \n", " \n", " 35\n", " coef_duration_shift_for_first_sub_tour_of_same...\n", - " 0.319885\n", + " -0.199899\n", " F\n", " \n", " \n", " 36\n", " coef_start_shift_for_subsequent_sub_tour_of_sa...\n", - " -0.360206\n", + " -0.117673\n", " F\n", " \n", " \n", " 37\n", " coef_duration_shift_for_subsequent_sub_tour_of...\n", - " -10.333603\n", + " -0.371148\n", " F\n", " \n", " \n", " 38\n", " coef_start_shift_for_number_of_mandatory_tours\n", - " 0.059018\n", + " -0.067479\n", " F\n", " \n", " \n", " 39\n", " coef_duration_shift_for_number_of_mandatory_tours\n", - " -1.058788\n", + " -0.909117\n", " F\n", " \n", " \n", " 40\n", " coef_start_shift_for_number_of_joint_tours\n", - " -0.019722\n", + " 0.025502\n", " F\n", " \n", " \n", " 41\n", " coef_duration_shift_for_number_of_joint_tours\n", - " -0.577681\n", + " -0.234618\n", " F\n", " \n", " \n", " 42\n", " coef_start_shift_for_number_of_individual_nonm...\n", - " 0.026777\n", + " -0.019137\n", " F\n", " \n", " \n", " 43\n", " coef_duration_shift_for_number_of_individual_n...\n", - " 0.009894\n", + " -0.075913\n", " F\n", " \n", " \n", " 44\n", " coef_dummy_for_business_related_purpose_and_du...\n", - " -0.663129\n", + " -1.656086\n", " F\n", " \n", " \n", " 45\n", " coef_dummy_for_eating_out_purpose_and_duration...\n", - " 0.310405\n", + " 0.534786\n", " F\n", " \n", " \n", " 46\n", " coef_dummy_for_eating_out_purpose_and_departur...\n", - " 1.151827\n", + " 1.371453\n", " F\n", " \n", " \n", " 47\n", " coef_dummy_for_eating_out_purpose_and_departur...\n", - " 2.625436\n", + " 2.454861\n", " F\n", " \n", " \n", " 48\n", " coef_dummy_for_eating_out_purpose_and_departur...\n", - " 2.360981\n", + " 1.832150\n", " F\n", " \n", " \n", @@ -4148,59 +4261,59 @@ "" ], "text/plain": [ - " coefficient_name value constrain\n", - "0 coef_early_start_at_5 -2.204068 F\n", - "1 coef_am_peak_start_at_6 -20.592814 F\n", - "2 coef_am_peak_start_at_7 -2.826984 F\n", - "3 coef_am_peak_start_at_8 -1.196528 F\n", - "4 coef_am_peak_start_at_9 -1.619897 F\n", - "5 coef_midday_start_at_10_11_12 0.000000 T\n", - "6 coef_midday_start_at_13_14_15 -1.051562 F\n", - "7 coef_pm_peak_start_at_16_17_18 -0.798588 F\n", - "8 coef_evening_start_at_19_20_21 -0.325741 F\n", - "9 coef_late_start_at_22_23 -5.142925 F\n", - "10 coef_early_end_at_5_6 -25.000000 F\n", - "11 coef_am_peak_end -1.373169 F\n", - "12 coef_midday_end_at_10_11_12 -1.305196 F\n", - "13 coef_midday_end_at_13_14 0.000000 T\n", - "14 coef_pm_peak_end_at_15 -1.432981 F\n", - "15 coef_pm_peak_end_at_16 -2.055109 F\n", - "16 coef_pm_peak_end_at_17 -2.404252 F\n", - "17 coef_pm_peak_end_at_18 -3.500372 F\n", - "18 coef_evening_end_at_19_20_21 -4.521037 F\n", - "19 coef_late_end_at_22_23 -11.516565 F\n", - "20 coef_duration_of_0_hours 9.959985 F\n", - "21 coef_duration_of_1_hour 0.000000 T\n", - "22 coef_duration_of_2_to_3_hours 9.181283 F\n", - "23 coef_duration_of_4_to_5_hours -0.483141 F\n", - "24 coef_duration_of_6_to_7_hours 10.535613 F\n", - "25 coef_duration_of_8_to_10_hours 10.402183 F\n", - "26 coef_duration_of_11_to_13_hours -0.374055 F\n", - "27 coef_duration_of_14_to_18_hours 0.000000 T\n", - "28 coef_start_shift_for_outbound_auto_travel_time... 0.100349 F\n", - "29 coef_start_shift_for_inbound_auto_travel_time_... -0.099019 F\n", - "30 coef_duration_shift_for_outbound_auto_travel_t... 0.145324 F\n", - "31 coef_duration_shift_for_inbound_auto_travel_ti... -0.118575 F\n", - "32 coef_start_shift_for_business_related_ -0.083357 F\n", - "33 coef_duration_shift_for_business_related_ 0.600044 F\n", - "34 coef_start_shift_for_first_sub_tour_of_same_wo... -0.168324 F\n", - "35 coef_duration_shift_for_first_sub_tour_of_same... 0.319885 F\n", - "36 coef_start_shift_for_subsequent_sub_tour_of_sa... -0.360206 F\n", - "37 coef_duration_shift_for_subsequent_sub_tour_of... -10.333603 F\n", - "38 coef_start_shift_for_number_of_mandatory_tours 0.059018 F\n", - "39 coef_duration_shift_for_number_of_mandatory_tours -1.058788 F\n", - "40 coef_start_shift_for_number_of_joint_tours -0.019722 F\n", - "41 coef_duration_shift_for_number_of_joint_tours -0.577681 F\n", - "42 coef_start_shift_for_number_of_individual_nonm... 0.026777 F\n", - "43 coef_duration_shift_for_number_of_individual_n... 0.009894 F\n", - "44 coef_dummy_for_business_related_purpose_and_du... -0.663129 F\n", - "45 coef_dummy_for_eating_out_purpose_and_duration... 0.310405 F\n", - "46 coef_dummy_for_eating_out_purpose_and_departur... 1.151827 F\n", - "47 coef_dummy_for_eating_out_purpose_and_departur... 2.625436 F\n", - "48 coef_dummy_for_eating_out_purpose_and_departur... 2.360981 F" + " coefficient_name value constrain\n", + "0 coef_early_start_at_5 -7.645209 F\n", + "1 coef_am_peak_start_at_6 -5.790935 F\n", + "2 coef_am_peak_start_at_7 -4.238642 F\n", + "3 coef_am_peak_start_at_8 -2.371798 F\n", + "4 coef_am_peak_start_at_9 -2.106247 F\n", + "5 coef_midday_start_at_10_11_12 0.000000 T\n", + "6 coef_midday_start_at_13_14_15 -0.665045 F\n", + "7 coef_pm_peak_start_at_16_17_18 -0.000431 F\n", + "8 coef_evening_start_at_19_20_21 -0.786571 F\n", + "9 coef_late_start_at_22_23 -0.890587 F\n", + "10 coef_early_end_at_5_6 -2.693000 F\n", + "11 coef_am_peak_end -2.543876 F\n", + "12 coef_midday_end_at_10_11_12 -2.145575 F\n", + "13 coef_midday_end_at_13_14 0.000000 T\n", + "14 coef_pm_peak_end_at_15 -0.586475 F\n", + "15 coef_pm_peak_end_at_16 -1.337297 F\n", + "16 coef_pm_peak_end_at_17 -1.432487 F\n", + "17 coef_pm_peak_end_at_18 -1.702240 F\n", + "18 coef_evening_end_at_19_20_21 -2.460690 F\n", + "19 coef_late_end_at_22_23 -2.391664 F\n", + "20 coef_duration_of_0_hours -1.056506 F\n", + "21 coef_duration_of_1_hour 0.000000 T\n", + "22 coef_duration_of_2_to_3_hours -1.478463 F\n", + "23 coef_duration_of_4_to_5_hours -1.032651 F\n", + "24 coef_duration_of_6_to_7_hours 1.074781 F\n", + "25 coef_duration_of_8_to_10_hours 1.476278 F\n", + "26 coef_duration_of_11_to_13_hours 0.292100 F\n", + "27 coef_duration_of_14_to_18_hours 0.000000 T\n", + "28 coef_start_shift_for_outbound_auto_travel_time... 0.010616 F\n", + "29 coef_start_shift_for_inbound_auto_travel_time_... -0.011025 F\n", + "30 coef_duration_shift_for_outbound_auto_travel_t... -0.002863 F\n", + "31 coef_duration_shift_for_inbound_auto_travel_ti... 0.022979 F\n", + "32 coef_start_shift_for_business_related_ -0.071618 F\n", + "33 coef_duration_shift_for_business_related_ 0.237322 F\n", + "34 coef_start_shift_for_first_sub_tour_of_same_wo... -0.458549 F\n", + "35 coef_duration_shift_for_first_sub_tour_of_same... -0.199899 F\n", + "36 coef_start_shift_for_subsequent_sub_tour_of_sa... -0.117673 F\n", + "37 coef_duration_shift_for_subsequent_sub_tour_of... -0.371148 F\n", + "38 coef_start_shift_for_number_of_mandatory_tours -0.067479 F\n", + "39 coef_duration_shift_for_number_of_mandatory_tours -0.909117 F\n", + "40 coef_start_shift_for_number_of_joint_tours 0.025502 F\n", + "41 coef_duration_shift_for_number_of_joint_tours -0.234618 F\n", + "42 coef_start_shift_for_number_of_individual_nonm... -0.019137 F\n", + "43 coef_duration_shift_for_number_of_individual_n... -0.075913 F\n", + "44 coef_dummy_for_business_related_purpose_and_du... -1.656086 F\n", + "45 coef_dummy_for_eating_out_purpose_and_duration... 0.534786 F\n", + "46 coef_dummy_for_eating_out_purpose_and_departur... 1.371453 F\n", + "47 coef_dummy_for_eating_out_purpose_and_departur... 2.454861 F\n", + "48 coef_dummy_for_eating_out_purpose_and_departur... 1.832150 F" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -4217,7 +4330,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -4231,7 +4344,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/21_stop_frequency.ipynb b/activitysim/examples/example_estimation/notebooks/21_stop_frequency.ipynb index 3de8e64272..ee1914bfd6 100644 --- a/activitysim/examples/example_estimation/notebooks/21_stop_frequency.ipynb +++ b/activitysim/examples/example_estimation/notebooks/21_stop_frequency.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -73,8 +120,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/activitysim/activitysim/estimation/larch/general.py:321: UserWarning: coefficient dataframe missing 'constrain' column, setting all to 'F'\n", - " warnings.warn(\"coefficient dataframe missing 'constrain' column, setting all to 'F'\")\n" + "/Users/jpn/Git/est-mode/activitysim/activitysim/estimation/larch/general.py:359: UserWarning: coefficient dataframe missing 'constrain' column, setting all to 'F'\n", + " warnings.warn(\n" ] } ], @@ -82,7 +129,12 @@ "modelname = \"stop_frequency\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "\n", + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -1195,10 +1247,10 @@ " coef_alternative_specific_constant_for_outboun...\n", " coef_alternative_specific_constant_for_outboun...\n", " coef_alternative_specific_constant_for_outboun...\n", - " -3.934\n", - " -3.934\n", - " -3.934\n", - " -3.934\n", + " coef_alternative_specific_constant_for_outboun...\n", + " coef_alternative_specific_constant_for_outboun...\n", + " coef_alternative_specific_constant_for_outboun...\n", + " coef_alternative_specific_constant_for_outboun...\n", " \n", " \n", " 40\n", @@ -1208,19 +1260,19 @@ " NaN\n", " coef_alternative_specific_constant_for_return_...\n", " coef_alternative_specific_constant_for_return_...\n", - " -2.139\n", + " coef_alternative_specific_constant_for_return_...\n", " NaN\n", " coef_alternative_specific_constant_for_return_...\n", " coef_alternative_specific_constant_for_return_...\n", - " -2.139\n", + " coef_alternative_specific_constant_for_return_...\n", " NaN\n", " coef_alternative_specific_constant_for_return_...\n", " coef_alternative_specific_constant_for_return_...\n", - " -2.139\n", + " coef_alternative_specific_constant_for_return_...\n", " NaN\n", " coef_alternative_specific_constant_for_return_...\n", " coef_alternative_specific_constant_for_return_...\n", - " -2.139\n", + " coef_alternative_specific_constant_for_return_...\n", " \n", " \n", " 41\n", @@ -1537,7 +1589,7 @@ "37 coef_dummy_for_distance_in_miles \n", "38 coef_no_stops_if_tour_mode_is_drivetransit \n", "39 NaN \n", - "40 -2.139 \n", + "40 coef_alternative_specific_constant_for_return_... \n", "41 coef_alternative_specific_constant_for_the_tot... \n", "42 coef_number_of_subtours_in_the_tour \n", "\n", @@ -1717,7 +1769,7 @@ "37 coef_dummy_for_distance_in_miles \n", "38 coef_no_stops_if_tour_mode_is_drivetransit \n", "39 coef_alternative_specific_constant_for_outboun... \n", - "40 -2.139 \n", + "40 coef_alternative_specific_constant_for_return_... \n", "41 coef_alternative_specific_constant_for_the_tot... \n", "42 coef_number_of_subtours_in_the_tour \n", "\n", @@ -1897,7 +1949,7 @@ "37 coef_dummy_for_distance_in_miles \n", "38 coef_no_stops_if_tour_mode_is_drivetransit \n", "39 coef_alternative_specific_constant_for_outboun... \n", - "40 -2.139 \n", + "40 coef_alternative_specific_constant_for_return_... \n", "41 coef_alternative_specific_constant_for_the_tot... \n", "42 coef_number_of_subtours_in_the_tour \n", "\n", @@ -1941,7 +1993,7 @@ "36 coef_dummy_for_distance_less_than_20_miles \n", "37 coef_dummy_for_distance_in_miles \n", "38 coef_no_stops_if_tour_mode_is_drivetransit \n", - "39 -3.934 \n", + "39 coef_alternative_specific_constant_for_outboun... \n", "40 NaN \n", "41 coef_alternative_specific_constant_for_the_tot... \n", "42 coef_number_of_subtours_in_the_tour \n", @@ -1986,7 +2038,7 @@ "36 coef_dummy_for_distance_less_than_20_miles \n", "37 coef_dummy_for_distance_in_miles \n", "38 coef_no_stops_if_tour_mode_is_drivetransit \n", - "39 -3.934 \n", + "39 coef_alternative_specific_constant_for_outboun... \n", "40 coef_alternative_specific_constant_for_return_... \n", "41 coef_alternative_specific_constant_for_the_tot... \n", "42 coef_number_of_subtours_in_the_tour \n", @@ -2031,7 +2083,7 @@ "36 coef_dummy_for_distance_less_than_20_miles \n", "37 coef_dummy_for_distance_in_miles \n", "38 coef_no_stops_if_tour_mode_is_drivetransit \n", - "39 -3.934 \n", + "39 coef_alternative_specific_constant_for_outboun... \n", "40 coef_alternative_specific_constant_for_return_... \n", "41 coef_alternative_specific_constant_for_the_tot... \n", "42 coef_number_of_subtours_in_the_tour \n", @@ -2076,8 +2128,8 @@ "36 coef_dummy_for_distance_less_than_20_miles \n", "37 coef_dummy_for_distance_in_miles \n", "38 coef_no_stops_if_tour_mode_is_drivetransit \n", - "39 -3.934 \n", - "40 -2.139 \n", + "39 coef_alternative_specific_constant_for_outboun... \n", + "40 coef_alternative_specific_constant_for_return_... \n", "41 coef_alternative_specific_constant_for_the_tot... \n", "42 coef_number_of_subtours_in_the_tour " ] @@ -2175,9 +2227,9 @@ " \n", " \n", " \n", - " 2961920\n", - " 0out_0in\n", - " 0out_0in\n", + " 2966594\n", + " 0out_1in\n", + " 0out_1in\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -2191,17 +2243,17 @@ " False\n", " 0\n", " 0\n", + " 1\n", " 0\n", " 0\n", - " 0\n", - " 6.859067\n", - " 7.751024\n", - " 0\n", + " 6.446184\n", + " 6.869385\n", + " 1\n", " \n", " \n", - " 2970120\n", - " 2out_1in\n", - " 2out_1in\n", + " 2967783\n", + " 0out_0in\n", + " 0out_0in\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -2218,12 +2270,12 @@ " 0\n", " 0\n", " 0\n", - " 0.000000\n", - " 0.000000\n", - " 1\n", + " 6.384615\n", + " 7.341247\n", + " 0\n", " \n", " \n", - " 2998943\n", + " 2968726\n", " 0out_0in\n", " 0out_0in\n", " 0.0\n", @@ -2236,19 +2288,19 @@ " 0.0\n", " ...\n", " False\n", - " False\n", + " True\n", " 0\n", " 0\n", - " 1\n", " 0\n", " 0\n", - " 6.024261\n", - " 7.519040\n", - " 2\n", + " 0\n", + " 5.447277\n", + " 6.565208\n", + " 1\n", " \n", " \n", - " 3013252\n", - " 0out_0in\n", + " 2970858\n", + " 1out_1in\n", " 0out_0in\n", " 0.0\n", " 0.0\n", @@ -2266,12 +2318,12 @@ " 0\n", " 0\n", " 0\n", - " 5.672122\n", - " 6.595380\n", + " 6.787018\n", + " 7.692237\n", " 1\n", " \n", " \n", - " 3015794\n", + " 2973728\n", " 0out_0in\n", " 0out_0in\n", " 0.0\n", @@ -2290,8 +2342,8 @@ " 0\n", " 0\n", " 0\n", - " 6.252582\n", - " 5.865708\n", + " 6.611336\n", + " 5.693881\n", " 3\n", " \n", " \n", @@ -2319,38 +2371,38 @@ " ...\n", " \n", " \n", - " 308070309\n", - " 0out_0in\n", + " 309081532\n", + " 2out_0in\n", " 0out_0in\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1.0\n", - " 0.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " ...\n", " False\n", - " True\n", - " 0\n", + " False\n", " 0\n", " 0\n", " 0\n", " 0\n", - " 8.181251\n", - " 8.326834\n", " 0\n", + " 4.619027\n", + " 6.475182\n", + " 3\n", " \n", " \n", - " 308073875\n", - " 1out_0in\n", - " 1out_0in\n", + " 309090634\n", + " 0out_1in\n", + " 0out_0in\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1.0\n", - " 1.0\n", + " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -2362,14 +2414,14 @@ " 0\n", " 0\n", " 0\n", - " 0.000000\n", - " 0.000000\n", - " 2\n", + " 4.800090\n", + " 6.198316\n", + " 1\n", " \n", " \n", - " 308090603\n", - " 0out_0in\n", + " 309101950\n", " 0out_0in\n", + " 1out_1in\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -2386,22 +2438,22 @@ " 0\n", " 0\n", " 0\n", - " 7.629996\n", - " 7.282405\n", + " 0.000000\n", + " 0.000000\n", " 1\n", " \n", " \n", - " 308105896\n", + " 309107362\n", " 0out_0in\n", " 0out_0in\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1.0\n", - " 0.0\n", " 1.0\n", " 0.0\n", " 0.0\n", + " 0.0\n", " ...\n", " False\n", " False\n", @@ -2410,181 +2462,181 @@ " 0\n", " 0\n", " 0\n", - " 7.149388\n", - " 6.679189\n", - " 2\n", + " 0.000000\n", + " 0.000000\n", + " 4\n", " \n", " \n", - " 308122624\n", + " 309112036\n", " 0out_0in\n", " 0out_0in\n", " 0.0\n", " 0.0\n", " 0.0\n", " 1.0\n", - " 0.0\n", " 1.0\n", " 0.0\n", " 0.0\n", + " 0.0\n", " ...\n", " False\n", " False\n", " 0\n", " 0\n", + " 1\n", " 0\n", " 0\n", - " 0\n", - " 5.117139\n", - " 7.355598\n", - " 0\n", + " 0.000000\n", + " 0.000000\n", + " 4\n", " \n", " \n", "\n", - "

2124 rows × 220 columns

\n", + "

22637 rows × 220 columns

\n", "" ], "text/plain": [ " model_choice override_choice util_middle_to_low_income_hh \\\n", "tour_id \n", - "2961920 0out_0in 0out_0in 0.0 \n", - "2970120 2out_1in 2out_1in 0.0 \n", - "2998943 0out_0in 0out_0in 0.0 \n", - "3013252 0out_0in 0out_0in 0.0 \n", - "3015794 0out_0in 0out_0in 0.0 \n", + "2966594 0out_1in 0out_1in 0.0 \n", + "2967783 0out_0in 0out_0in 0.0 \n", + "2968726 0out_0in 0out_0in 0.0 \n", + "2970858 1out_1in 0out_0in 0.0 \n", + "2973728 0out_0in 0out_0in 0.0 \n", "... ... ... ... \n", - "308070309 0out_0in 0out_0in 0.0 \n", - "308073875 1out_0in 1out_0in 0.0 \n", - "308090603 0out_0in 0out_0in 0.0 \n", - "308105896 0out_0in 0out_0in 0.0 \n", - "308122624 0out_0in 0out_0in 0.0 \n", + "309081532 2out_0in 0out_0in 0.0 \n", + "309090634 0out_1in 0out_0in 0.0 \n", + "309101950 0out_0in 1out_1in 0.0 \n", + "309107362 0out_0in 0out_0in 0.0 \n", + "309112036 0out_0in 0out_0in 0.0 \n", "\n", " util_mid_to_high_income_hh util_high_income_hh \\\n", "tour_id \n", - "2961920 0.0 0.0 \n", - "2970120 0.0 0.0 \n", - "2998943 0.0 0.0 \n", - "3013252 0.0 0.0 \n", - "3015794 0.0 0.0 \n", + "2966594 0.0 0.0 \n", + "2967783 0.0 0.0 \n", + "2968726 0.0 0.0 \n", + "2970858 0.0 0.0 \n", + "2973728 0.0 0.0 \n", "... ... ... \n", - "308070309 0.0 0.0 \n", - "308073875 0.0 0.0 \n", - "308090603 0.0 0.0 \n", - "308105896 0.0 0.0 \n", - "308122624 0.0 0.0 \n", + "309081532 0.0 0.0 \n", + "309090634 0.0 0.0 \n", + "309101950 0.0 0.0 \n", + "309107362 0.0 0.0 \n", + "309112036 0.0 0.0 \n", "\n", " util_number_of_hh_persons util_number_of_full_time_workers_in_hh \\\n", "tour_id \n", - "2961920 1.0 1.0 \n", - "2970120 1.0 1.0 \n", - "2998943 1.0 1.0 \n", - "3013252 1.0 1.0 \n", - "3015794 1.0 0.0 \n", + "2966594 1.0 1.0 \n", + "2967783 1.0 1.0 \n", + "2968726 1.0 1.0 \n", + "2970858 1.0 1.0 \n", + "2973728 1.0 0.0 \n", "... ... ... \n", - "308070309 1.0 0.0 \n", - "308073875 1.0 1.0 \n", - "308090603 1.0 1.0 \n", - "308105896 1.0 0.0 \n", - "308122624 1.0 0.0 \n", + "309081532 1.0 1.0 \n", + "309090634 1.0 0.0 \n", + "309101950 1.0 1.0 \n", + "309107362 1.0 1.0 \n", + "309112036 1.0 1.0 \n", "\n", " util_number_of_students_in_hh \\\n", "tour_id \n", - "2961920 0.0 \n", - "2970120 0.0 \n", - "2998943 0.0 \n", - "3013252 0.0 \n", - "3015794 0.0 \n", + "2966594 0.0 \n", + "2967783 0.0 \n", + "2968726 0.0 \n", + "2970858 0.0 \n", + "2973728 0.0 \n", "... ... \n", - "308070309 0.0 \n", - "308073875 0.0 \n", - "308090603 0.0 \n", - "308105896 1.0 \n", - "308122624 1.0 \n", + "309081532 0.0 \n", + "309090634 0.0 \n", + "309101950 0.0 \n", + "309107362 0.0 \n", + "309112036 0.0 \n", "\n", " util_num_kids_between_0_and_4_including_years_old \\\n", "tour_id \n", - "2961920 0.0 \n", - "2970120 0.0 \n", - "2998943 0.0 \n", - "3013252 0.0 \n", - "3015794 0.0 \n", + "2966594 0.0 \n", + "2967783 0.0 \n", + "2968726 0.0 \n", + "2970858 0.0 \n", + "2973728 0.0 \n", "... ... \n", - "308070309 0.0 \n", - "308073875 0.0 \n", - "308090603 0.0 \n", - "308105896 0.0 \n", - "308122624 0.0 \n", + "309081532 0.0 \n", + "309090634 0.0 \n", + "309101950 0.0 \n", + "309107362 0.0 \n", + "309112036 0.0 \n", "\n", " util_presence_of_kids_between_0_and_4_including_years_old ... \\\n", "tour_id ... \n", - "2961920 0.0 ... \n", - "2970120 0.0 ... \n", - "2998943 0.0 ... \n", - "3013252 0.0 ... \n", - "3015794 0.0 ... \n", + "2966594 0.0 ... \n", + "2967783 0.0 ... \n", + "2968726 0.0 ... \n", + "2970858 0.0 ... \n", + "2973728 0.0 ... \n", "... ... ... \n", - "308070309 0.0 ... \n", - "308073875 0.0 ... \n", - "308090603 0.0 ... \n", - "308105896 0.0 ... \n", - "308122624 0.0 ... \n", + "309081532 0.0 ... \n", + "309090634 0.0 ... \n", + "309101950 0.0 ... \n", + "309107362 0.0 ... \n", + "309112036 0.0 ... \n", "\n", " tour_mode_is_drive_transit tour_mode_is_non_motorized \\\n", "tour_id \n", - "2961920 False False \n", - "2970120 False False \n", - "2998943 False False \n", - "3013252 False False \n", - "3015794 False False \n", + "2966594 False False \n", + "2967783 False False \n", + "2968726 False True \n", + "2970858 False False \n", + "2973728 False False \n", "... ... ... \n", - "308070309 False True \n", - "308073875 False False \n", - "308090603 False False \n", - "308105896 False False \n", - "308122624 False False \n", + "309081532 False False \n", + "309090634 False False \n", + "309101950 False False \n", + "309107362 False False \n", + "309112036 False False \n", "\n", " num_school_tours num_univ_tours num_atwork_subtours \\\n", "tour_id \n", - "2961920 0 0 0 \n", - "2970120 0 0 0 \n", - "2998943 0 0 1 \n", - "3013252 0 0 0 \n", - "3015794 0 0 0 \n", + "2966594 0 0 1 \n", + "2967783 0 0 0 \n", + "2968726 0 0 0 \n", + "2970858 0 0 0 \n", + "2973728 0 0 0 \n", "... ... ... ... \n", - "308070309 0 0 0 \n", - "308073875 0 0 0 \n", - "308090603 0 0 0 \n", - "308105896 0 0 0 \n", - "308122624 0 0 0 \n", + "309081532 0 0 0 \n", + "309090634 0 0 0 \n", + "309101950 0 0 0 \n", + "309107362 0 0 0 \n", + "309112036 0 0 1 \n", "\n", " num_hh_shop_tours num_hh_maint_tours hhacc pracc \\\n", "tour_id \n", - "2961920 0 0 6.859067 7.751024 \n", - "2970120 0 0 0.000000 0.000000 \n", - "2998943 0 0 6.024261 7.519040 \n", - "3013252 0 0 5.672122 6.595380 \n", - "3015794 0 0 6.252582 5.865708 \n", + "2966594 0 0 6.446184 6.869385 \n", + "2967783 0 0 6.384615 7.341247 \n", + "2968726 0 0 5.447277 6.565208 \n", + "2970858 0 0 6.787018 7.692237 \n", + "2973728 0 0 6.611336 5.693881 \n", "... ... ... ... ... \n", - "308070309 0 0 8.181251 8.326834 \n", - "308073875 0 0 0.000000 0.000000 \n", - "308090603 0 0 7.629996 7.282405 \n", - "308105896 0 0 7.149388 6.679189 \n", - "308122624 0 0 5.117139 7.355598 \n", + "309081532 0 0 4.619027 6.475182 \n", + "309090634 0 0 4.800090 6.198316 \n", + "309101950 0 0 0.000000 0.000000 \n", + "309107362 0 0 0.000000 0.000000 \n", + "309112036 0 0 0.000000 0.000000 \n", "\n", " destination_area_type \n", "tour_id \n", - "2961920 0 \n", - "2970120 1 \n", - "2998943 2 \n", - "3013252 1 \n", - "3015794 3 \n", + "2966594 1 \n", + "2967783 0 \n", + "2968726 1 \n", + "2970858 1 \n", + "2973728 3 \n", "... ... \n", - "308070309 0 \n", - "308073875 2 \n", - "308090603 1 \n", - "308105896 2 \n", - "308122624 0 \n", + "309081532 3 \n", + "309090634 1 \n", + "309101950 1 \n", + "309107362 4 \n", + "309112036 4 \n", "\n", - "[2124 rows x 220 columns]" + "[22637 rows x 220 columns]" ] }, "execution_count": 7, @@ -2610,26 +2662,10 @@ "execution_count": 8, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ - "

Iteration 130 [Optimization terminated successfully]

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Iteration 081 [Optimization terminated successfully]

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Best LL = -6094.555918549999

" + "

Best LL = -78188.35046478933

" ], "text/plain": [ "" @@ -2672,70 +2708,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " -2.139\n", - " -2.139000\n", - " -2.139\n", - " -2.139\n", - " -2.139\n", - " -2.139\n", - " 1\n", - " \n", - " -2.139000\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in\n", + " -0.817659\n", + " -0.817659\n", + " -0.833\n", + " -inf\n", + " inf\n", + " 0.0\n", + " 0\n", " \n", " \n", - " -3.934\n", - " -3.934000\n", - " -3.934\n", - " -3.934\n", - " -3.934\n", - " -3.934\n", - " 1\n", - " \n", - " -3.934000\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_atwork\n", + " -3.857785\n", + " -3.857785\n", + " -3.896\n", + " -inf\n", + " inf\n", + " 0.0\n", + " 0\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in\n", - " -0.741225\n", - " -0.833\n", - " 0.000\n", - " NaN\n", - " NaN\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout\n", + " -2.243908\n", + " -2.243908\n", + " -2.190\n", + " -inf\n", + " inf\n", + " 0.0\n", " 0\n", - " \n", - " -0.741225\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_2out_0in\n", - " -2.594489\n", - " -2.613\n", - " 0.000\n", - " NaN\n", - " NaN\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort\n", + " -2.254734\n", + " -2.254734\n", + " -2.173\n", + " -inf\n", + " inf\n", + " 0.0\n", " 0\n", - " \n", - " -2.594489\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in\n", - " -0.447476\n", - " -0.445\n", - " 0.000\n", - " NaN\n", - " NaN\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr\n", + " -1.509245\n", + " -1.509245\n", + " -1.581\n", + " -inf\n", + " inf\n", + " 0.0\n", " 0\n", - " \n", - " -0.447476\n", " \n", " \n", " ...\n", @@ -2746,122 +2786,120 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", " coef_primary_destination_accessibility_log_of_it_\n", - " 0.170704\n", + " 0.191205\n", + " 0.191205\n", " 0.180\n", - " 0.000\n", - " NaN\n", - " NaN\n", + " -inf\n", + " inf\n", + " 0.0\n", " 0\n", - " \n", - " 0.170704\n", " \n", " \n", " coef_subtour_departure_less_than_or_equal_to_11am\n", - " 0.266339\n", + " 0.352247\n", + " 0.352247\n", " 0.310\n", - " 0.000\n", - " NaN\n", - " NaN\n", + " -inf\n", + " inf\n", + " 0.0\n", " 0\n", - " \n", - " 0.266339\n", " \n", " \n", " coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_\n", - " -0.152384\n", + " 0.023141\n", + " 0.023141\n", " 0.020\n", - " 0.000\n", - " NaN\n", - " NaN\n", + " -inf\n", + " inf\n", + " 0.0\n", " 0\n", - " \n", - " -0.152384\n", " \n", " \n", " coef_subtour_duration_in_hours_integer_\n", - " 0.681811\n", + " 0.555413\n", + " 0.555413\n", " 0.560\n", - " 0.000\n", - " NaN\n", - " NaN\n", + " -inf\n", + " inf\n", + " 0.0\n", " 0\n", - " \n", - " 0.681811\n", " \n", " \n", " coef_subtour_return_time_greater_or_equal_to_2pm\n", - " 1.549569\n", + " 0.206446\n", + " 0.206446\n", " 0.340\n", - " 0.000\n", - " NaN\n", - " NaN\n", + " -inf\n", + " inf\n", + " 0.0\n", " 0\n", - " \n", - " 1.549569\n", " \n", " \n", "\n", - "

188 rows × 8 columns

\n", + "

188 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue \\\n", - "-2.139 -2.139000 -2.139 \n", - "-3.934 -3.934000 -3.934 \n", - "coef_alternative_specific_constant_for_outbound... -0.741225 -0.833 \n", - "coef_alternative_specific_constant_for_outbound... -2.594489 -2.613 \n", - "coef_alternative_specific_constant_for_return_s... -0.447476 -0.445 \n", - "... ... ... \n", - "coef_primary_destination_accessibility_log_of_it_ 0.170704 0.180 \n", - "coef_subtour_departure_less_than_or_equal_to_11am 0.266339 0.310 \n", - "coef_subtour_distance_in_miles_from_tour_destin... -0.152384 0.020 \n", - "coef_subtour_duration_in_hours_integer_ 0.681811 0.560 \n", - "coef_subtour_return_time_greater_or_equal_to_2pm 1.549569 0.340 \n", + " value best \\\n", + "param_name \n", + "coef_alternative_specific_constant_for_outbound... -0.817659 -0.817659 \n", + "coef_alternative_specific_constant_for_outbound... -3.857785 -3.857785 \n", + "coef_alternative_specific_constant_for_outbound... -2.243908 -2.243908 \n", + "coef_alternative_specific_constant_for_outbound... -2.254734 -2.254734 \n", + "coef_alternative_specific_constant_for_outbound... -1.509245 -1.509245 \n", + "... ... ... \n", + "coef_primary_destination_accessibility_log_of_it_ 0.191205 0.191205 \n", + "coef_subtour_departure_less_than_or_equal_to_11am 0.352247 0.352247 \n", + "coef_subtour_distance_in_miles_from_tour_destin... 0.023141 0.023141 \n", + "coef_subtour_duration_in_hours_integer_ 0.555413 0.555413 \n", + "coef_subtour_return_time_greater_or_equal_to_2pm 0.206446 0.206446 \n", "\n", - " nullvalue minimum \\\n", - "-2.139 -2.139 -2.139 \n", - "-3.934 -3.934 -3.934 \n", - "coef_alternative_specific_constant_for_outbound... 0.000 NaN \n", - "coef_alternative_specific_constant_for_outbound... 0.000 NaN \n", - "coef_alternative_specific_constant_for_return_s... 0.000 NaN \n", + " initvalue minimum \\\n", + "param_name \n", + "coef_alternative_specific_constant_for_outbound... -0.833 -inf \n", + "coef_alternative_specific_constant_for_outbound... -3.896 -inf \n", + "coef_alternative_specific_constant_for_outbound... -2.190 -inf \n", + "coef_alternative_specific_constant_for_outbound... -2.173 -inf \n", + "coef_alternative_specific_constant_for_outbound... -1.581 -inf \n", "... ... ... \n", - "coef_primary_destination_accessibility_log_of_it_ 0.000 NaN \n", - "coef_subtour_departure_less_than_or_equal_to_11am 0.000 NaN \n", - "coef_subtour_distance_in_miles_from_tour_destin... 0.000 NaN \n", - "coef_subtour_duration_in_hours_integer_ 0.000 NaN \n", - "coef_subtour_return_time_greater_or_equal_to_2pm 0.000 NaN \n", + "coef_primary_destination_accessibility_log_of_it_ 0.180 -inf \n", + "coef_subtour_departure_less_than_or_equal_to_11am 0.310 -inf \n", + "coef_subtour_distance_in_miles_from_tour_destin... 0.020 -inf \n", + "coef_subtour_duration_in_hours_integer_ 0.560 -inf \n", + "coef_subtour_return_time_greater_or_equal_to_2pm 0.340 -inf \n", "\n", - " maximum holdfast note \\\n", - "-2.139 -2.139 1 \n", - "-3.934 -3.934 1 \n", - "coef_alternative_specific_constant_for_outbound... NaN 0 \n", - "coef_alternative_specific_constant_for_outbound... NaN 0 \n", - "coef_alternative_specific_constant_for_return_s... NaN 0 \n", - "... ... ... ... \n", - "coef_primary_destination_accessibility_log_of_it_ NaN 0 \n", - "coef_subtour_departure_less_than_or_equal_to_11am NaN 0 \n", - "coef_subtour_distance_in_miles_from_tour_destin... NaN 0 \n", - "coef_subtour_duration_in_hours_integer_ NaN 0 \n", - "coef_subtour_return_time_greater_or_equal_to_2pm NaN 0 \n", + " maximum nullvalue \\\n", + "param_name \n", + "coef_alternative_specific_constant_for_outbound... inf 0.0 \n", + "coef_alternative_specific_constant_for_outbound... inf 0.0 \n", + "coef_alternative_specific_constant_for_outbound... inf 0.0 \n", + "coef_alternative_specific_constant_for_outbound... inf 0.0 \n", + "coef_alternative_specific_constant_for_outbound... inf 0.0 \n", + "... ... ... \n", + "coef_primary_destination_accessibility_log_of_it_ inf 0.0 \n", + "coef_subtour_departure_less_than_or_equal_to_11am inf 0.0 \n", + "coef_subtour_distance_in_miles_from_tour_destin... inf 0.0 \n", + "coef_subtour_duration_in_hours_integer_ inf 0.0 \n", + "coef_subtour_return_time_greater_or_equal_to_2pm inf 0.0 \n", "\n", - " best \n", - "-2.139 -2.139000 \n", - "-3.934 -3.934000 \n", - "coef_alternative_specific_constant_for_outbound... -0.741225 \n", - "coef_alternative_specific_constant_for_outbound... -2.594489 \n", - "coef_alternative_specific_constant_for_return_s... -0.447476 \n", + " holdfast \n", + "param_name \n", + "coef_alternative_specific_constant_for_outbound... 0 \n", + "coef_alternative_specific_constant_for_outbound... 0 \n", + "coef_alternative_specific_constant_for_outbound... 0 \n", + "coef_alternative_specific_constant_for_outbound... 0 \n", + "coef_alternative_specific_constant_for_outbound... 0 \n", "... ... \n", - "coef_primary_destination_accessibility_log_of_it_ 0.170704 \n", - "coef_subtour_departure_less_than_or_equal_to_11am 0.266339 \n", - "coef_subtour_distance_in_miles_from_tour_destin... -0.152384 \n", - "coef_subtour_duration_in_hours_integer_ 0.681811 \n", - "coef_subtour_return_time_greater_or_equal_to_2pm 1.549569 \n", + "coef_primary_destination_accessibility_log_of_it_ 0 \n", + "coef_subtour_departure_less_than_or_equal_to_11am 0 \n", + "coef_subtour_distance_in_miles_from_tour_destin... 0 \n", + "coef_subtour_duration_in_hours_integer_ 0 \n", + "coef_subtour_return_time_greater_or_equal_to_2pm 0 \n", "\n", - "[188 rows x 8 columns]" + "[188 rows x 7 columns]" ] }, "metadata": {}, @@ -2871,10 +2909,9 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate(method='SLSQP', options={\"maxiter\": 1000})\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 3.0254868525048906e-31 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/optimization.py:338: UserWarning: SLSQP may not play nicely with unbounded parameters\n", + "if you get poor results, consider setting global bounds with model.set_cap()\n", + " warnings.warn( # infinite bounds # )\n" ] }, { @@ -2889,3290 +2926,3126 @@ " \n", " \n", " \n", - " -2.139\n", - " -2.139000\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in\n", + " -0.817659\n", " \n", " \n", - " -3.934\n", - " -3.934000\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_atwork\n", + " -3.857785\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in\n", - " -0.741225\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout\n", + " -2.243908\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_2out_0in\n", - " -2.594489\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort\n", + " -2.254734\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in\n", - " -0.447476\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr\n", + " -1.509245\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_2in\n", - " -1.657817\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_othmaint\n", + " -1.850181\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in\n", - " 0.039441\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_school\n", + " -2.103501\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in\n", - " 0.754748\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_shopping\n", + " -1.374719\n", " \n", " \n", - " coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours\n", - " -1.998832\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_social\n", + " -1.100007\n", " \n", " \n", - " coef_dummy_for_all_stops_made_by_transit\n", - " -0.672704\n", + " coef_alternative_specific_constant_for_outbound_stops_1out_0in_univ\n", + " -2.583745\n", " \n", " \n", - " coef_dummy_for_distance_in_miles\n", - " 0.043974\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in\n", + " -2.553493\n", " \n", " \n", - " coef_dummy_for_distance_less_than_20_miles\n", - " -0.588175\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_atwork\n", + " -5.670203\n", " \n", " \n", - " coef_dummy_for_female\n", - " 0.282632\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_eatout\n", + " -4.501523\n", " \n", " \n", - " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours\n", - " 0.713048\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_escort\n", + " -4.225203\n", " \n", " \n", - " coef_dummy_for_walking_to_all_stops\n", - " -1.491072\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_othdiscr\n", + " -3.357879\n", " \n", " \n", - " coef_evening_arrival_19_00_interacted_with_return_tours\n", - " 0.606441\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_othmaint\n", + " -3.532505\n", " \n", " \n", - " coef_high_income_hh\n", - " 0.240000\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_school\n", + " -3.932072\n", " \n", " \n", - " coef_mid_to_high_income_hh\n", - " 0.230000\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_shopping\n", + " -3.001964\n", " \n", " \n", - " coef_middle_to_low_income_hh\n", - " 0.170000\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_social\n", + " -2.787392\n", " \n", " \n", - " coef_no_stops_if_tour_mode_is_drivetransit\n", - " -999.000000\n", + " coef_alternative_specific_constant_for_outbound_stops_2out_0in_univ\n", + " -3.625877\n", " \n", " \n", - " coef_num_kids_between_5_and_15_including_years_old\n", - " 0.089718\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in\n", + " -3.914672\n", " \n", " \n", - " coef_number_of_adults_16_years_old_\n", - " 0.074203\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_atwork\n", + " -7.451244\n", " \n", " \n", - " coef_number_of_cars_number_of_workers\n", - " -0.065713\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_eatout\n", + " -5.213504\n", " \n", " \n", - " coef_number_of_escort_tours_tours_undertaken_by_the_person\n", - " 0.097792\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_escort\n", + " -4.713943\n", " \n", " \n", - " coef_number_of_hh_persons\n", - " -0.328159\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_othdiscr\n", + " -4.262005\n", " \n", " \n", - " coef_number_of_school_tours_tours_undertaken_by_the_person\n", - " 0.130473\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_othmaint\n", + " -5.370287\n", " \n", " \n", - " coef_number_of_shop_tours_undertaken_by_the_houshold\n", - " -0.328294\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_school\n", + " -5.865306\n", " \n", " \n", - " coef_number_of_students_in_hh\n", - " 0.315297\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_shopping\n", + " -4.443339\n", " \n", " \n", - " coef_number_of_subtours_in_the_tour\n", - " 0.337091\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_social\n", + " -4.476231\n", " \n", " \n", - " coef_number_of_university_tours_tours_undertaken_by_the_person\n", - " -0.480000\n", + " coef_alternative_specific_constant_for_outbound_stops_3out_0in_univ\n", + " -5.123628\n", " \n", " \n", - " coef_number_of_work_tours_undertaken_by_the_person\n", - " -0.174762\n", + " coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in\n", + " -1.861054\n", " \n", " \n", - " coef_presence_of_kids_between_0_and_4_including_years_old\n", - " 0.557476\n", + " coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in\n", + " -4.027317\n", " \n", " \n", - " coef_presence_of_kids_between_5_and_15_including_years_old\n", - " 0.117544\n", + " coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in\n", + " -5.079709\n", " \n", " \n", - " -2.672\n", - " -2.672000\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in\n", + " -0.422070\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in_school\n", - " -1.768772\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_atwork\n", + " -3.667812\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_2out_0in_school\n", - " -4.305875\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_eatout\n", + " -1.667177\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_3out_0in_school\n", - " -6.209404\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_escort\n", + " -0.883632\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in_school\n", - " -1.229114\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_othdiscr\n", + " -0.944455\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_3in_school\n", - " -3.185728\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_othmaint\n", + " -0.606891\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in\n", - " 1.573277\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_school\n", + " -1.203184\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_school\n", - " 2.178796\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_shopping\n", + " -1.155398\n", " \n", " \n", - " coef_arrival_later_than_17_00_\n", - " 1.373657\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_social\n", + " -1.262568\n", " \n", " \n", - " coef_dummy_for_distance_in_miles_school\n", - " 0.092023\n", + " coef_alternative_specific_constant_for_return_stops_0out_1in_univ\n", + " -1.892703\n", " \n", " \n", - " coef_dummy_for_female_school\n", - " 0.687687\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in\n", + " -1.737740\n", " \n", " \n", - " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_\n", - " 1.904120\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_atwork\n", + " -5.352597\n", " \n", " \n", - " coef_dummy_for_walking_to_all_stops_school\n", - " -1.525112\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_eatout\n", + " -3.384664\n", " \n", " \n", - " coef_number_of_cars_number_of_workers_school\n", - " 0.282408\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_escort\n", + " -2.356788\n", " \n", " \n", - " coef_number_of_escort_tours_tours_undertaken_by_the_person_school\n", - " 2.320226\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_othdiscr\n", + " -2.247941\n", " \n", " \n", - " coef_number_of_hh_persons_school\n", - " -0.602730\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_othmaint\n", + " -1.549591\n", " \n", " \n", - " coef_presence_of_kids_between_5_and_15_including_years_old_school\n", - " 0.021083\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_school\n", + " -2.618009\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in_univ\n", - " -2.211722\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_shopping\n", + " -2.252362\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_2out_0in_univ\n", - " -4.042853\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_social\n", + " -2.751879\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_3out_0in_univ\n", - " -4.641257\n", + " coef_alternative_specific_constant_for_return_stops_0out_2in_univ\n", + " -3.564173\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in_univ\n", - " -1.574239\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in\n", + " -2.056255\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_2in_univ\n", - " -3.434788\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in_atwork\n", + " -6.484627\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_3in_univ\n", - " -3.860338\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in_eatout\n", + " -4.733147\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_univ\n", - " 2.019764\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in_othdiscr\n", + " -2.820768\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_univ\n", - " 2.117237\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in_othmaint\n", + " -2.348697\n", " \n", " \n", - " coef_arrival_later_than_17_00__univ\n", - " 0.397767\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in_school\n", + " -3.360598\n", " \n", " \n", - " coef_dummy_for_female_univ\n", - " 0.527348\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in_shopping\n", + " -3.086157\n", " \n", " \n", - " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__univ\n", - " 1.086324\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in_social\n", + " -3.617917\n", " \n", " \n", - " coef_hh_accesibility_for_inbound_tours_interaction\n", - " 0.243672\n", + " coef_alternative_specific_constant_for_return_stops_0out_3in_univ\n", + " -3.549561\n", " \n", " \n", - " coef_number_of_escort_tours_tours_undertaken_by_the_person_univ\n", - " 1.858956\n", + " coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in\n", + " -1.349229\n", " \n", " \n", - " coef_number_of_hh_persons_univ\n", - " -0.326432\n", + " coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in\n", + " -3.006175\n", " \n", " \n", - " coef_number_of_vehicles\n", - " 0.265859\n", + " coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in\n", + " -3.092591\n", " \n", " \n", - " coef_presence_of_kids_between_5_and_15_including_years_old_univ\n", - " -0.061482\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in\n", + " -0.033904\n", " \n", " \n", - " -1.783\n", - " -1.783000\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in\n", + " 0.619994\n", " \n", " \n", - " -2.874\n", - " -2.874000\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_atwork\n", + " 2.196478\n", " \n", " \n", - " -3.379\n", - " -3.379000\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_eatout\n", + " 0.956558\n", " \n", " \n", - " 1.497\n", - " 1.497000\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othdiscr\n", + " 0.779563\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in_social\n", - " -1.292414\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othmaint\n", + " 0.525190\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_3out_0in_social\n", - " -42.649173\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_shopping\n", + " 0.518875\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in\n", - " -4.158467\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_social\n", + " 0.620383\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in\n", - " -28.920114\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_univ\n", + " 1.218010\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in_social\n", - " 0.474303\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in\n", + " 0.555526\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_2in_social\n", - " -2.400345\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_eatout\n", + " 1.979106\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_3in_social\n", - " -3.106704\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_escort\n", + " -1.796251\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in\n", - " -1.489538\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othdiscr\n", + " 1.148950\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in\n", - " -3.529456\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othmaint\n", + " 0.489201\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_social\n", - " 2.605627\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_school\n", + " 1.203689\n", + " \n", + " \n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_shopping\n", + " 0.411626\n", " \n", " \n", " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_social\n", - " -9.808088\n", + " 0.866347\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in\n", - " -0.168353\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_univ\n", + " 1.958267\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in\n", - " -26.078121\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in\n", + " -0.057283\n", " \n", " \n", - " coef_arrival_later_than_17_00__social\n", - " -0.470057\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in\n", + " 0.608179\n", " \n", " \n", - " coef_at_least_one_kid_and_one_adult_participate_in_the_tour\n", - " 2.116069\n", + " coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in\n", + " 1.429603\n", " \n", " \n", - " coef_dummy_for_a_return_visiting_tour\n", - " -1.746712\n", + " coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours\n", + " -1.913742\n", " \n", " \n", - " coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg\n", - " 0.344025\n", + " coef_arrival_later_than_17_00_\n", + " 1.839504\n", " \n", " \n", - " coef_dummy_for_an_outbound_visiting_tour\n", - " -0.742278\n", + " coef_arrival_later_than_17_00__othdiscr\n", + " -0.637546\n", " \n", " \n", - " coef_dummy_for_distance_in_miles_social\n", - " -0.078778\n", + " coef_arrival_later_than_17_00__social\n", + " -0.708359\n", " \n", " \n", - " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_\n", - " 1.141918\n", + " coef_arrival_later_than_17_00__univ\n", + " 0.352924\n", " \n", " \n", - " coef_dummy_for_walking_to_all_stops_social\n", - " -2.087075\n", + " coef_at_least_one_kid_and_one_adult_participate_in_the_tour\n", + " 0.598380\n", " \n", " \n", - " coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction\n", - " -0.027490\n", + " coef_dummy_for_a_return_visiting_tour\n", + " -0.542418\n", " \n", " \n", - " coef_number_of_shop_tours_undertaken_by_the_person\n", - " -0.177893\n", + " coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg\n", + " 0.637918\n", " \n", " \n", - " coef_number_of_vehicles_social\n", - " -0.154123\n", + " coef_dummy_for_all_stops_made_by_transit\n", + " -0.698140\n", " \n", " \n", - " coef_number_of_work_tours_undertaken_by_the_person_social\n", - " -0.010226\n", + " coef_dummy_for_an_outbound_visiting_tour\n", + " -0.547383\n", " \n", " \n", - " -3.024\n", - " -3.024000\n", + " coef_dummy_for_distance_in_miles\n", + " 0.008199\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in_shopping\n", - " -1.491871\n", + " coef_dummy_for_distance_in_miles_othdiscr\n", + " -0.016398\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_2out_0in_shopping\n", - " -3.340709\n", + " coef_dummy_for_distance_in_miles_othmaint\n", + " 0.024622\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_3out_0in_shopping\n", - " -4.537979\n", + " coef_dummy_for_distance_in_miles_school\n", + " 0.048727\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in_shopping\n", - " -1.234250\n", + " coef_dummy_for_distance_in_miles_shopping\n", + " 0.042050\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_2in_shopping\n", - " -2.580404\n", + " coef_dummy_for_distance_in_miles_social\n", + " -0.011161\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_shopping\n", - " 0.585255\n", + " coef_dummy_for_distance_less_than_10_miles_\n", + " 0.311571\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_shopping\n", - " -0.015580\n", + " coef_dummy_for_distance_less_than_20_miles\n", + " -0.209813\n", " \n", " \n", - " coef_dummy_for_distance_in_miles_shopping\n", - " 0.021405\n", + " coef_dummy_for_distance_less_than_20_miles_\n", + " -0.403250\n", " \n", " \n", " coef_dummy_for_distance_less_than_5_miles\n", - " 0.152609\n", + " 0.391002\n", " \n", " \n", - " coef_dummy_for_female_shopping\n", - " 0.339336\n", + " coef_dummy_for_distance_less_than_5_miles_escort\n", + " 0.287884\n", " \n", " \n", - " coef_dummy_for_only_adults_participate_in_the_tour\n", - " 1.542207\n", + " coef_dummy_for_female\n", + " 0.231116\n", " \n", " \n", - " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__shopping\n", - " 3.102092\n", + " coef_dummy_for_female_othmaint\n", + " 0.298798\n", " \n", " \n", - " coef_dummy_for_walking_to_all_stops_shopping\n", - " -1.883904\n", + " coef_dummy_for_female_school\n", + " 0.518603\n", " \n", " \n", - " coef_num_kids_between_5_and_15_including_years_old_shopping\n", - " -0.047846\n", + " coef_dummy_for_female_shopping\n", + " 0.199726\n", " \n", " \n", - " coef_number_of_hh_persons_shopping\n", - " -0.086986\n", + " coef_dummy_for_female_univ\n", + " 0.539334\n", " \n", " \n", - " coef_number_of_maintenace_tours_tours_undertaken_by_the_person\n", - " -0.325799\n", + " coef_dummy_for_only_adults_participate_in_the_tour\n", + " 0.241206\n", " \n", " \n", - " coef_number_of_shop_tours_undertaken_by_the_houshold_shopping\n", - " 0.147901\n", + " coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_\n", + " 0.270000\n", " \n", " \n", - " coef_number_of_university_tours_tours_undertaken_by_the_person_shopping\n", - " -0.670900\n", + " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours\n", + " 0.629566\n", " \n", " \n", - " coef_number_of_work_tours_undertaken_by_the_person_shopping\n", - " -0.437195\n", + " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_\n", + " 1.296845\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout\n", - " -1.879526\n", + " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_\n", + " 0.935859\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_2out_0in_eatout\n", - " -32.613372\n", + " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__escort\n", + " 0.468894\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_3out_0in_eatout\n", - " -3.738703\n", + " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othdiscr\n", + " 0.843539\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in_eatout\n", - " -1.687121\n", + " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othmaint\n", + " 0.103716\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_2in_eatout\n", - " -3.033355\n", + " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__shopping\n", + " 1.035541\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_3in_eatout\n", - " -4.837278\n", + " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__univ\n", + " 0.771998\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_eatout\n", - " -31.986519\n", + " coef_dummy_for_walking_to_all_stops\n", + " -1.590379\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_eatout\n", - " -30.916248\n", + " coef_dummy_for_walking_to_all_stops_escort\n", + " -2.041910\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort\n", - " -2.225477\n", + " coef_dummy_for_walking_to_all_stops_othdiscr\n", + " -2.338073\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_2out_0in_escort\n", - " -4.857476\n", + " coef_dummy_for_walking_to_all_stops_othmaint\n", + " -1.321421\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_3out_0in_escort\n", - " -4.792453\n", + " coef_dummy_for_walking_to_all_stops_school\n", + " -2.074837\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in_escort\n", - " -1.279087\n", + " coef_dummy_for_walking_to_all_stops_shopping\n", + " -1.462311\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_2in_escort\n", - " -2.459341\n", + " coef_dummy_for_walking_to_all_stops_social\n", + " -1.649814\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_escort\n", - " -12.346112\n", + " coef_evening_arrival_19_00_interacted_with_return_tours\n", + " 0.297829\n", " \n", " \n", - " coef_dummy_for_distance_less_than_5_miles_escort\n", - " 0.269808\n", + " coef_hh_accesibility_for_inbound_tours_interaction\n", + " 0.258426\n", " \n", " \n", 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coef_num_kids_between_5_and_15_including_years_old\n", + " 0.083356\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_1out_0in_othmaint\n", - " -2.122249\n", + " coef_num_kids_between_5_and_15_including_years_old_shopping\n", + " 0.033141\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_2out_0in_othmaint\n", - " -3.470020\n", + " coef_number_of_adults_16_years_old_\n", + " 0.006177\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_3out_0in_othmaint\n", - " -4.230867\n", + " coef_number_of_cars_number_of_workers\n", + " 0.195317\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_1in_othmaint\n", - " -0.833758\n", + " coef_number_of_cars_number_of_workers_school\n", + " 0.630311\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_2in_othmaint\n", - " -1.186628\n", + " coef_number_of_eating_tours_tours_undertaken_by_the_person\n", + " -0.424859\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othmaint\n", - " 0.315206\n", + " coef_number_of_escort_tours_tours_undertaken_by_the_person\n", + " 0.285502\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othmaint\n", - " -31.005508\n", + " coef_number_of_escort_tours_tours_undertaken_by_the_person_escort\n", + " -0.077934\n", " \n", " \n", - " coef_dummy_for_distance_in_miles_othmaint\n", - " 0.102023\n", + " coef_number_of_escort_tours_tours_undertaken_by_the_person_school\n", + " 1.290196\n", " \n", " \n", - " coef_dummy_for_distance_less_than_20_miles_\n", - " -0.621770\n", + " coef_number_of_escort_tours_tours_undertaken_by_the_person_univ\n", + " 0.984566\n", " \n", " \n", - " coef_dummy_for_female_othmaint\n", - " 0.281419\n", + " coef_number_of_hh_persons\n", + " -0.291501\n", " \n", " \n", - " coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othmaint\n", - " 0.168631\n", + " coef_number_of_hh_persons_escort\n", + " -0.289093\n", " \n", " \n", - " coef_dummy_for_walking_to_all_stops_othmaint\n", - " -2.298979\n", + " coef_number_of_hh_persons_school\n", + " -0.521641\n", " \n", " \n", - " coef_middle_to_low_income_hh_\n", - " 0.170000\n", + " coef_number_of_hh_persons_shopping\n", + " -0.164111\n", " \n", " \n", - " coef_number_of_maintenace_tours_undertaken_by_the_houshold\n", - " -0.264644\n", + " coef_number_of_hh_persons_univ\n", + " -0.296528\n", " \n", " \n", - " coef_number_of_persons_participating_in_the_tour_return_stops_interaction\n", - " 0.626322\n", + " coef_number_of_maintenace_tours_tours_undertaken_by_the_person\n", + " -0.281780\n", " \n", " \n", - " coef_number_of_shool_tours_tours_undertaken_by_the_person\n", - " -29.423035\n", + " coef_number_of_maintenace_tours_tours_undertaken_by_the_person_othdiscr\n", + " -0.273666\n", " \n", " \n", - " coef_number_of_shop_tours_undertaken_by_the_person_othmaint\n", - " 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coef_alternative_specific_constant_for_outbound_stops_2out_0in_othdiscr\n", - " -2.956642\n", + " coef_number_of_shop_tours_undertaken_by_the_houshold\n", + " 0.194165\n", " \n", " \n", - " coef_alternative_specific_constant_for_outbound_stops_3out_0in_othdiscr\n", - " -4.394706\n", + " coef_number_of_shop_tours_undertaken_by_the_houshold_shopping\n", + " -0.142075\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_2in_othdiscr\n", - " -2.518386\n", + " coef_number_of_shop_tours_undertaken_by_the_person\n", + " -0.303706\n", " \n", " \n", - " coef_alternative_specific_constant_for_return_stops_0out_3in_othdiscr\n", - " -3.024368\n", + " coef_number_of_shop_tours_undertaken_by_the_person_othdiscr\n", + " -0.641366\n", " \n", " \n", - " coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othdiscr\n", - " 1.088281\n", + " coef_number_of_shop_tours_undertaken_by_the_person_othmaint\n", + " -0.175208\n", " \n", " \n", - " 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0
coef_alternative_specific_constant_for_outbound_stops_1out_0in1.318164e-07
coef_alternative_specific_constant_for_outbound_stops_1out_0in_atwork-3.450424e-05
coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout-2.357602e-05
coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort7.327103e-06
coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr5.830160e-05
coef_alternative_specific_constant_for_outbound_stops_1out_0in_othmaint-1.687364e-05
coef_alternative_specific_constant_for_outbound_stops_1out_0in_school-1.669586e-05
coef_alternative_specific_constant_for_outbound_stops_1out_0in_shopping-1.179775e-08
coef_alternative_specific_constant_for_outbound_stops_1out_0in_social1.831328e-05
coef_alternative_specific_constant_for_outbound_stops_1out_0in_univ1.659316e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in3.044727e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in_atwork1.175946e-08
coef_alternative_specific_constant_for_outbound_stops_2out_0in_eatout1.022786e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in_escort1.105196e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in_othdiscr3.555996e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in_othmaint-1.893055e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in_school3.445422e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in_shopping3.263881e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in_social-2.496547e-05
coef_alternative_specific_constant_for_outbound_stops_2out_0in_univ1.438293e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in-1.071751e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in_atwork-1.888854e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in_eatout1.167128e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in_escort1.356432e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in_othdiscr-3.000084e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in_othmaint1.163413e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in_school-2.151305e-06
coef_alternative_specific_constant_for_outbound_stops_3out_0in_shopping-1.610268e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in_social1.204101e-05
coef_alternative_specific_constant_for_outbound_stops_3out_0in_univ-2.399461e-05
coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in1.866585e-05
coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in9.984701e-06
coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in-2.645255e-05
coef_alternative_specific_constant_for_return_stops_0out_1in-4.708365e-05
coef_alternative_specific_constant_for_return_stops_0out_1in_atwork5.651507e-06
coef_alternative_specific_constant_for_return_stops_0out_1in_eatout1.418406e-06
coef_alternative_specific_constant_for_return_stops_0out_1in_escort-1.108521e-04
coef_alternative_specific_constant_for_return_stops_0out_1in_othdiscr3.754350e-05
coef_alternative_specific_constant_for_return_stops_0out_1in_othmaint-5.058401e-05
coef_alternative_specific_constant_for_return_stops_0out_1in_school-1.317771e-05
coef_alternative_specific_constant_for_return_stops_0out_1in_shopping-1.353818e-05
coef_alternative_specific_constant_for_return_stops_0out_1in_social9.274282e-06
coef_alternative_specific_constant_for_return_stops_0out_1in_univ1.265812e-05
coef_alternative_specific_constant_for_return_stops_0out_2in-1.013444e-04
coef_alternative_specific_constant_for_return_stops_0out_2in_atwork-5.726811e-06
coef_alternative_specific_constant_for_return_stops_0out_2in_eatout2.119117e-06
coef_alternative_specific_constant_for_return_stops_0out_2in_escort7.074619e-05
coef_alternative_specific_constant_for_return_stops_0out_2in_othdiscr6.714927e-06
coef_alternative_specific_constant_for_return_stops_0out_2in_othmaint6.821290e-06
coef_alternative_specific_constant_for_return_stops_0out_2in_school2.925330e-05
coef_alternative_specific_constant_for_return_stops_0out_2in_shopping-4.080487e-05
coef_alternative_specific_constant_for_return_stops_0out_2in_social-4.285482e-05
coef_alternative_specific_constant_for_return_stops_0out_2in_univ3.661192e-05
coef_alternative_specific_constant_for_return_stops_0out_3in1.133758e-04
coef_alternative_specific_constant_for_return_stops_0out_3in_atwork9.086276e-06
coef_alternative_specific_constant_for_return_stops_0out_3in_eatout4.586623e-06
coef_alternative_specific_constant_for_return_stops_0out_3in_othdiscr2.426809e-05
coef_alternative_specific_constant_for_return_stops_0out_3in_othmaint-2.486703e-05
coef_alternative_specific_constant_for_return_stops_0out_3in_school-2.227797e-05
coef_alternative_specific_constant_for_return_stops_0out_3in_shopping2.495105e-05
coef_alternative_specific_constant_for_return_stops_0out_3in_social-6.029497e-05
coef_alternative_specific_constant_for_return_stops_0out_3in_univ1.155529e-05
coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in-3.870571e-06
coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in7.661858e-06
coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in-4.833521e-06
coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in6.276561e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in-3.395874e-06
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_atwork3.600197e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_eatout4.455986e-07
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othdiscr-2.367744e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othmaint-1.442248e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_shopping-8.406942e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_social1.283479e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_univ-1.771563e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in1.798862e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_eatout-2.174096e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_escort4.005556e-06
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othdiscr-8.102586e-06
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othmaint-7.835219e-06
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_school1.969169e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_shopping-1.891110e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_social-1.234210e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_univ1.908165e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in-1.399555e-07
coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in1.065266e-05
coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in-2.973298e-05
coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours4.011337e-05
coef_arrival_later_than_17_00_9.509009e-06
coef_arrival_later_than_17_00__othdiscr5.323204e-05
coef_arrival_later_than_17_00__social-3.236359e-05
coef_arrival_later_than_17_00__univ6.463924e-06
coef_at_least_one_kid_and_one_adult_participate_in_the_tour5.107909e-05
coef_dummy_for_a_return_visiting_tour3.250338e-05
coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg-2.201652e-05
coef_dummy_for_all_stops_made_by_transit2.881609e-05
coef_dummy_for_an_outbound_visiting_tour6.196096e-06
coef_dummy_for_distance_in_miles9.385043e-06
coef_dummy_for_distance_in_miles_othdiscr-7.834462e-06
coef_dummy_for_distance_in_miles_othmaint4.302748e-05
coef_dummy_for_distance_in_miles_school2.634834e-05
coef_dummy_for_distance_in_miles_shopping-3.883054e-06
coef_dummy_for_distance_in_miles_social-2.876791e-06
coef_dummy_for_distance_less_than_10_miles_8.995802e-05
coef_dummy_for_distance_less_than_20_miles-2.204602e-05
coef_dummy_for_distance_less_than_20_miles_-1.281965e-04
coef_dummy_for_distance_less_than_5_miles-1.119062e-05
coef_dummy_for_distance_less_than_5_miles_escort-1.207377e-05
coef_dummy_for_female-8.480269e-06
coef_dummy_for_female_othmaint-4.926674e-05
coef_dummy_for_female_school1.424463e-05
coef_dummy_for_female_shopping-4.273230e-05
coef_dummy_for_female_univ3.630606e-05
coef_dummy_for_only_adults_participate_in_the_tour1.089846e-05
coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_0.000000e+00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours-4.743285e-05
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_-9.652111e-05
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_1.664266e-05
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__escort-5.502657e-06
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othdiscr-3.421032e-06
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othmaint-2.300422e-05
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__shopping3.276266e-06
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__univ-1.959322e-05
coef_dummy_for_walking_to_all_stops6.006629e-06
coef_dummy_for_walking_to_all_stops_escort-3.338229e-05
coef_dummy_for_walking_to_all_stops_othdiscr3.003054e-06
coef_dummy_for_walking_to_all_stops_othmaint5.544972e-06
coef_dummy_for_walking_to_all_stops_school5.590612e-05
coef_dummy_for_walking_to_all_stops_shopping-6.986420e-06
coef_dummy_for_walking_to_all_stops_social-1.812323e-05
coef_evening_arrival_19_00_interacted_with_return_tours-1.075717e-04
coef_hh_accesibility_for_inbound_tours_interaction1.545214e-04
coef_high_income_hh0.000000e+00
coef_mid_to_high_income_hh0.000000e+00
coef_middle_to_low_income_hh0.000000e+00
coef_middle_to_low_income_hh_0.000000e+00
coef_middle_to_low_income_hh__atwork1.591693e-05
coef_no_stops_if_tour_mode_is_drivetransit0.000000e+00
coef_num_kids_between_5_and_15_including_years_old1.811798e-04
coef_num_kids_between_5_and_15_including_years_old_shopping-2.177398e-05
coef_number_of_adults_16_years_old_1.607333e-04
coef_number_of_cars_number_of_workers-5.548331e-05
coef_number_of_cars_number_of_workers_school-4.595882e-05
coef_number_of_eating_tours_tours_undertaken_by_the_person-1.221656e-05
coef_number_of_escort_tours_tours_undertaken_by_the_person3.915582e-05
coef_number_of_escort_tours_tours_undertaken_by_the_person_escort-4.632281e-05
coef_number_of_escort_tours_tours_undertaken_by_the_person_school-1.496317e-06
coef_number_of_escort_tours_tours_undertaken_by_the_person_univ5.820883e-06
coef_number_of_hh_persons-9.384152e-05
coef_number_of_hh_persons_escort4.408343e-05
coef_number_of_hh_persons_school-4.397796e-05
coef_number_of_hh_persons_shopping3.401635e-05
coef_number_of_hh_persons_univ-6.991701e-05
coef_number_of_maintenace_tours_tours_undertaken_by_the_person-1.812134e-05
coef_number_of_maintenace_tours_tours_undertaken_by_the_person_othdiscr-2.534184e-05
coef_number_of_maintenace_tours_undertaken_by_the_houshold2.050003e-06
coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction6.755108e-06
coef_number_of_persons_participating_in_the_tour_return_stops_interaction-5.553747e-05
coef_number_of_school_tours_tours_undertaken_by_the_person3.616606e-06
coef_number_of_shool_tours_tours_undertaken_by_the_person-4.217392e-05
coef_number_of_shool_tours_tours_undertaken_by_the_person_othdiscr7.289526e-06
coef_number_of_shop_tours_undertaken_by_the_houshold5.577565e-05
coef_number_of_shop_tours_undertaken_by_the_houshold_shopping1.055865e-05
coef_number_of_shop_tours_undertaken_by_the_person2.191567e-05
coef_number_of_shop_tours_undertaken_by_the_person_othdiscr1.735752e-05
coef_number_of_shop_tours_undertaken_by_the_person_othmaint-1.989246e-05
coef_number_of_students_in_hh-3.900317e-05
coef_number_of_students_in_hh_escort-8.924947e-05
coef_number_of_subtours_in_the_tour-1.634519e-05
coef_number_of_university_tours_tours_undertaken_by_the_person0.000000e+00
coef_number_of_university_tours_tours_undertaken_by_the_person_othmaint0.000000e+00
coef_number_of_university_tours_tours_undertaken_by_the_person_shopping0.000000e+00
coef_number_of_vehicles-6.107892e-05
coef_number_of_vehicles_social4.943979e-05
coef_number_of_work_tours_undertaken_by_the_person-4.194501e-05
coef_number_of_work_tours_undertaken_by_the_person_escort-9.605595e-07
coef_number_of_work_tours_undertaken_by_the_person_othdiscr3.079891e-05
coef_number_of_work_tours_undertaken_by_the_person_othmaint-2.034031e-05
coef_number_of_work_tours_undertaken_by_the_person_shopping-2.318647e-05
coef_number_of_work_tours_undertaken_by_the_person_social-4.019493e-05
coef_presence_of_kids_between_0_and_4_including_years_old-9.532148e-05
coef_presence_of_kids_between_5_and_15_including_years_old1.004783e-04
coef_presence_of_kids_between_5_and_15_including_years_old_school-1.763120e-05
coef_presence_of_kids_between_5_and_15_including_years_old_univ-4.857618e-06
coef_primary_destination_accessibility_log_of_it_0.170704-4.708946e-06
coef_subtour_departure_less_than_or_equal_to_11am0.266339-3.435878e-05
coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_-0.1523849.929553e-05
coef_subtour_duration_in_hours_integer_-1.478819e-04
coef_subtour_return_time_greater_or_equal_to_2pm-2.289188e-05
nit81nfev82njev81status0message'Optimization terminated successfully'successTrueelapsed_time0:00:17.187577method'SLSQP'n_cases69971iteration_number81loglike-78188.35046478933" + ], + "text/plain": [ + "┣ x: coef_alternative_specific_constant_for_outbound_stops_1out_0in -0.817659\n", + "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in_atwork -3.857785\n", + "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout -2.243908\n", + "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort -2.254734\n", + "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr -1.509245\n", + "┃ ... \n", + "┃ coef_primary_destination_accessibility_log_of_it_ 0.191205\n", + "┃ coef_subtour_departure_less_than_or_equal_to_11am 0.352247\n", + "┃ coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_ 0.023141\n", + "┃ coef_subtour_duration_in_hours_integer_ 0.555413\n", + "┃ coef_subtour_return_time_greater_or_equal_to_2pm 0.206446\n", + "┃ Length: 188, dtype: float64\n", + "┣ logloss: 1.1174393743806623\n", + "┣ d_logloss: coef_alternative_specific_constant_for_outbound_stops_1out_0in 1.318164e-07\n", + "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in_atwork -3.450424e-05\n", + "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout -2.357602e-05\n", + "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort 7.327103e-06\n", + "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr 5.830160e-05\n", + "┃ ... \n", + "┃ coef_primary_destination_accessibility_log_of_it_ -4.708946e-06\n", + "┃ coef_subtour_departure_less_than_or_equal_to_11am -3.435878e-05\n", + "┃ coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_ 9.929553e-05\n", + "┃ coef_subtour_duration_in_hours_integer_ -1.478819e-04\n", + "┃ coef_subtour_return_time_greater_or_equal_to_2pm -2.289188e-05\n", + "┃ Length: 188, dtype: float64\n", + "┣ nit: 81\n", + "┣ nfev: 82\n", + "┣ njev: 81\n", + "┣ status: 0\n", + "┣ message: 'Optimization terminated successfully'\n", + "┣ success: True\n", + "┣ elapsed_time: datetime.timedelta(seconds=17, microseconds=187577)\n", + "┣ method: 'SLSQP'\n", + "┣ n_cases: 69971\n", + "┣ iteration_number: 81\n", + "┣ loglike: -78188.35046478933" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.estimate(method='SLSQP', options={\"maxiter\": 1000})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Estimated coefficients" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - "
coef_subtour_duration_in_hours_integer_0.681811 ValueStd Errt StatSignifNull Value
coef_subtour_return_time_greater_or_equal_to_2pm1.549569
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0Parameter     
-2.1390.000000e+00coef_alternative_specific_constant_for_outbound_stops_1out_0in-0.818 0.0344-23.78*** 0.00
-3.9340.000000e+00coef_alternative_specific_constant_for_outbound_stops_1out_0in_atwork-3.86 0.249-15.49*** 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in-7.969702e-05coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout-2.24 0.102-22.05*** 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in-7.162521e-04coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort-2.25 0.0741-30.45*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in-6.335846e-05coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr-1.51 0.0658-22.93*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in9.540429e-05coef_alternative_specific_constant_for_outbound_stops_1out_0in_othmaint-1.85 0.0875-21.14*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in-5.140413e-04coef_alternative_specific_constant_for_outbound_stops_1out_0in_school-2.10 0.0714-29.46*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in-8.954661e-05coef_alternative_specific_constant_for_outbound_stops_1out_0in_shopping-1.37 0.0511-26.89*** 0.00
coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours-2.097418e-04coef_alternative_specific_constant_for_outbound_stops_1out_0in_social-1.10 0.565-1.95 0.00
coef_dummy_for_all_stops_made_by_transit5.963845e-05coef_alternative_specific_constant_for_outbound_stops_1out_0in_univ-2.58 0.148-17.51*** 0.00
coef_dummy_for_distance_in_miles-2.339326e-03coef_alternative_specific_constant_for_outbound_stops_2out_0in-2.55 0.0622-41.08*** 0.00
coef_dummy_for_distance_less_than_20_miles-4.727787e-04coef_alternative_specific_constant_for_outbound_stops_2out_0in_atwork-5.67 0.275-20.66*** 0.00
coef_dummy_for_female2.329415e-05coef_alternative_specific_constant_for_outbound_stops_2out_0in_eatout-4.50 0.236-19.10*** 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours-2.446071e-04coef_alternative_specific_constant_for_outbound_stops_2out_0in_escort-4.23 0.158-26.72*** 0.00
coef_dummy_for_walking_to_all_stops-2.009061e-04coef_alternative_specific_constant_for_outbound_stops_2out_0in_othdiscr-3.36 0.116-28.93*** 0.00
coef_evening_arrival_19_00_interacted_with_return_tours-2.608074e-04coef_alternative_specific_constant_for_outbound_stops_2out_0in_othmaint-3.53 0.157-22.55*** 0.00
coef_high_income_hh0.000000e+00coef_alternative_specific_constant_for_outbound_stops_2out_0in_school-3.93 0.122-32.36*** 0.00
coef_mid_to_high_income_hh0.000000e+00coef_alternative_specific_constant_for_outbound_stops_2out_0in_shopping-3.00 0.0869-34.53*** 0.00
coef_middle_to_low_income_hh0.000000e+00coef_alternative_specific_constant_for_outbound_stops_2out_0in_social-2.79 0.582-4.79*** 0.00
coef_no_stops_if_tour_mode_is_drivetransit0.000000e+00coef_alternative_specific_constant_for_outbound_stops_2out_0in_univ-3.63 0.193-18.79*** 0.00
coef_num_kids_between_5_and_15_including_years_old1.941456e-04coef_alternative_specific_constant_for_outbound_stops_3out_0in-3.91 0.0934-41.93*** 0.00
coef_number_of_adults_16_years_old_2.205314e-04coef_alternative_specific_constant_for_outbound_stops_3out_0in_atwork-7.45 0.358-20.80*** 0.00
coef_number_of_cars_number_of_workers5.994133e-04coef_alternative_specific_constant_for_outbound_stops_3out_0in_eatout-5.21 0.325-16.02*** 0.00
coef_number_of_escort_tours_tours_undertaken_by_the_person-5.224365e-05coef_alternative_specific_constant_for_outbound_stops_3out_0in_escort-4.71 0.202-23.35*** 0.00
coef_number_of_hh_persons1.586957e-03coef_alternative_specific_constant_for_outbound_stops_3out_0in_othdiscr-4.26 0.163-26.11*** 0.00
coef_number_of_school_tours_tours_undertaken_by_the_person-3.034153e-05coef_alternative_specific_constant_for_outbound_stops_3out_0in_othmaint-5.37 0.326-16.47*** 0.00
coef_number_of_shop_tours_undertaken_by_the_houshold1.116601e-04coef_alternative_specific_constant_for_outbound_stops_3out_0in_school-5.87 0.244-24.09*** 0.00
coef_number_of_students_in_hh1.126486e-04coef_alternative_specific_constant_for_outbound_stops_3out_0in_shopping-4.44 0.143-30.98*** 0.00
coef_number_of_subtours_in_the_tour-4.322246e-04coef_alternative_specific_constant_for_outbound_stops_3out_0in_social-4.48 0.653-6.86*** 0.00
coef_number_of_university_tours_tours_undertaken_by_the_person0.000000e+00coef_alternative_specific_constant_for_outbound_stops_3out_0in_univ-5.12 0.304-16.88*** 0.00
coef_number_of_work_tours_undertaken_by_the_person-3.832504e-04coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in-1.86 0.132-14.07*** 0.00
coef_presence_of_kids_between_0_and_4_including_years_old-2.811261e-04coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in-4.03 0.366-11.00*** 0.00
coef_presence_of_kids_between_5_and_15_including_years_old1.838518e-04coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in-5.08 0.509-9.97*** 0.00
-2.6720.000000e+00coef_alternative_specific_constant_for_return_stops_0out_1in-0.422 0.0376-11.23*** 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_school3.622369e-04coef_alternative_specific_constant_for_return_stops_0out_1in_atwork-3.67 0.250-14.69*** 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_school-1.073515e-04coef_alternative_specific_constant_for_return_stops_0out_1in_eatout-1.67 0.0960-17.36*** 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_school5.591613e-07coef_alternative_specific_constant_for_return_stops_0out_1in_escort-0.884 0.0729-12.12*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_school-4.218724e-04coef_alternative_specific_constant_for_return_stops_0out_1in_othdiscr-0.944 0.0691-13.68*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_school-1.172540e-04coef_alternative_specific_constant_for_return_stops_0out_1in_othmaint-0.607 0.0995-6.10*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in6.638463e-05coef_alternative_specific_constant_for_return_stops_0out_1in_school-1.20 0.0752-16.01*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_school-4.148872e-05coef_alternative_specific_constant_for_return_stops_0out_1in_shopping-1.16 0.0523-22.10*** 0.00
coef_arrival_later_than_17_00_3.242621e-05coef_alternative_specific_constant_for_return_stops_0out_1in_social-1.26 0.260-4.86*** 0.00
coef_dummy_for_distance_in_miles_school1.257368e-04coef_alternative_specific_constant_for_return_stops_0out_1in_univ-1.89 0.143-13.28*** 0.00
coef_dummy_for_female_school1.151809e-04coef_alternative_specific_constant_for_return_stops_0out_2in-1.74 0.0605-28.73*** 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_1.609739e-04coef_alternative_specific_constant_for_return_stops_0out_2in_atwork-5.35 0.270-19.83*** 0.00
coef_dummy_for_walking_to_all_stops_school-2.948826e-05coef_alternative_specific_constant_for_return_stops_0out_2in_eatout-3.38 0.161-21.08*** 0.00
coef_number_of_cars_number_of_workers_school-1.267875e-04coef_alternative_specific_constant_for_return_stops_0out_2in_escort-2.36 0.104-22.69*** 0.00
coef_number_of_escort_tours_tours_undertaken_by_the_person_school-1.086302e-04coef_alternative_specific_constant_for_return_stops_0out_2in_othdiscr-2.25 0.0973-23.10*** 0.00
coef_number_of_hh_persons_school-8.934922e-05coef_alternative_specific_constant_for_return_stops_0out_2in_othmaint-1.55 0.121-12.84*** 0.00
coef_presence_of_kids_between_5_and_15_including_years_old_school2.925349e-04coef_alternative_specific_constant_for_return_stops_0out_2in_school-2.62 0.101-25.83*** 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_univ2.297287e-04coef_alternative_specific_constant_for_return_stops_0out_2in_shopping-2.25 0.0774-29.09*** 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_univ-7.201840e-04coef_alternative_specific_constant_for_return_stops_0out_2in_social-2.75 0.290-9.48*** 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_univ3.180905e-04coef_alternative_specific_constant_for_return_stops_0out_2in_univ-3.56 0.199-17.95*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_univ-6.094370e-04coef_alternative_specific_constant_for_return_stops_0out_3in-2.06 0.0653-31.50*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_univ2.159121e-04coef_alternative_specific_constant_for_return_stops_0out_3in_atwork-6.48 0.304-21.31*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_univ-2.067752e-04coef_alternative_specific_constant_for_return_stops_0out_3in_eatout-4.73 0.275-17.24*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_univ-1.224656e-04coef_alternative_specific_constant_for_return_stops_0out_3in_othdiscr-2.82 0.121-23.37*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_univ1.115042e-04coef_alternative_specific_constant_for_return_stops_0out_3in_othmaint-2.35 0.149-15.81*** 0.00
coef_arrival_later_than_17_00__univ3.883451e-05coef_alternative_specific_constant_for_return_stops_0out_3in_school-3.36 0.124-27.19*** 0.00
coef_dummy_for_female_univ-2.006300e-04coef_alternative_specific_constant_for_return_stops_0out_3in_shopping-3.09 0.0889-34.71*** 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__univ1.801912e-05coef_alternative_specific_constant_for_return_stops_0out_3in_social-3.62 0.345-10.49*** 0.00
coef_hh_accesibility_for_inbound_tours_interaction1.451782e-04coef_alternative_specific_constant_for_return_stops_0out_3in_univ-3.55 0.207-17.16*** 0.00
coef_number_of_escort_tours_tours_undertaken_by_the_person_univ4.571784e-05coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in-1.35 0.109-12.40*** 0.00
coef_number_of_hh_persons_univ-9.257971e-05coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in-3.01 0.298-10.08*** 0.00
coef_number_of_vehicles-3.492440e-05coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in-3.09 0.319-9.71*** 0.00
coef_presence_of_kids_between_5_and_15_including_years_old_univ-1.005346e-04coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in-0.0339 0.0356-0.95 0.00
-1.7830.000000e+00coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in 0.620 0.180 3.44*** 0.00
-2.8740.000000e+00coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_atwork 2.20 0.379 5.79*** 0.00
-3.3790.000000e+00coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_eatout 0.957 0.397 2.41* 0.00
1.4970.000000e+00coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othdiscr 0.780 0.146 5.35*** 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_social-1.680088e-04coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othmaint 0.525 0.198 2.65** 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_social-1.534541e-16coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_shopping 0.519 0.123 4.22*** 0.00
coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in-1.142652e-04coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_social 0.620 0.318 1.95 0.00
coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in-2.817966e-11coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_univ 1.22 0.294 4.14*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_social2.375526e-04coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in 0.556 0.128 4.35*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_social-2.745402e-08coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_eatout 1.98 0.616 3.21** 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_social-8.463137e-05coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_escort-1.80 1.19-1.51 0.00
coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in6.231017e-04coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othdiscr 1.15 0.241 4.76*** 0.00
coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in8.245417e-05coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othmaint 0.489 0.418 1.17 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_social-1.206021e-04coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_school 1.20 0.317 3.80*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_social-1.513475e-06coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_shopping 0.412 0.245 1.68 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in-2.522694e-04coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_social 0.866 0.592 1.46 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in-3.539804e-12coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_univ 1.96 0.383 5.12*** 0.00
coef_arrival_later_than_17_00__social4.029635e-04coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in-0.0573 0.238-0.24 0.00
coef_at_least_one_kid_and_one_adult_participate_in_the_tour3.720282e-04coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in 0.608 0.463 1.31 0.00
coef_dummy_for_a_return_visiting_tour3.077125e-04coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in 1.43 0.759 1.88 0.00
coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg1.591081e-04coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours-1.91 0.0370-51.75*** 0.00
coef_dummy_for_an_outbound_visiting_tour9.181048e-05coef_arrival_later_than_17_00_ 1.84 0.0758 24.27*** 0.00
coef_dummy_for_distance_in_miles_social6.278670e-04coef_arrival_later_than_17_00__othdiscr-0.638 0.0589-10.83*** 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_5.519594e-04coef_arrival_later_than_17_00__social-0.708 0.0742-9.55*** 0.00
coef_dummy_for_walking_to_all_stops_social4.496402e-04coef_arrival_later_than_17_00__univ 0.353 0.112 3.14** 0.00
coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction5.942079e-07coef_at_least_one_kid_and_one_adult_participate_in_the_tour 0.598 0.257 2.33* 0.00
coef_number_of_shop_tours_undertaken_by_the_person1.577034e-04coef_dummy_for_a_return_visiting_tour-0.542 0.250-2.17* 0.00
coef_number_of_vehicles_social1.013531e-03coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg 0.638 0.173 3.69*** 0.00
coef_number_of_work_tours_undertaken_by_the_person_social7.685343e-04coef_dummy_for_all_stops_made_by_transit-0.698 0.0392-17.80*** 0.00
-3.0240.000000e+00coef_dummy_for_an_outbound_visiting_tour-0.547 0.560-0.98 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_shopping2.666344e-05coef_dummy_for_distance_in_miles 0.00820 0.00214 3.83*** 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_shopping6.780320e-05coef_dummy_for_distance_in_miles_othdiscr-0.0164 0.00521-3.15** 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_shopping-7.271615e-04coef_dummy_for_distance_in_miles_othmaint 0.0246 0.00536 4.59*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_shopping-9.635243e-06coef_dummy_for_distance_in_miles_school 0.0487 0.00546 8.92*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_shopping5.507170e-05coef_dummy_for_distance_in_miles_shopping 0.0421 0.00629 6.68*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_shopping-5.236271e-05coef_dummy_for_distance_in_miles_social-0.0112 0.00621-1.80 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_shopping-7.154384e-05coef_dummy_for_distance_less_than_10_miles_ 0.312 0.0676 4.61*** 0.00
coef_dummy_for_distance_in_miles_shopping2.523396e-04coef_dummy_for_distance_less_than_20_miles-0.210 0.0571-3.67*** 0.00
coef_dummy_for_distance_less_than_5_miles-2.476980e-05coef_dummy_for_distance_less_than_20_miles_-0.403 0.109-3.71*** 0.00
coef_dummy_for_female_shopping4.740709e-04coef_dummy_for_distance_less_than_5_miles 0.391 0.0569 6.87*** 0.00
coef_dummy_for_only_adults_participate_in_the_tour4.017317e-04coef_dummy_for_distance_less_than_5_miles_escort 0.288 0.0736 3.91*** 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__shopping-4.228203e-05coef_dummy_for_female 0.231 0.0317 7.29*** 0.00
coef_dummy_for_walking_to_all_stops_shopping-3.690879e-04coef_dummy_for_female_othmaint 0.299 0.0693 4.31*** 0.00
coef_num_kids_between_5_and_15_including_years_old_shopping-1.102340e-04coef_dummy_for_female_school 0.519 0.0577 9.00*** 0.00
coef_number_of_hh_persons_shopping2.463465e-04coef_dummy_for_female_shopping 0.200 0.0467 4.28*** 0.00
coef_number_of_maintenace_tours_tours_undertaken_by_the_person7.302562e-05coef_dummy_for_female_univ 0.539 0.111 4.84*** 0.00
coef_number_of_shop_tours_undertaken_by_the_houshold_shopping-2.407855e-05coef_dummy_for_only_adults_participate_in_the_tour 0.241 0.194 1.25 0.00
coef_number_of_university_tours_tours_undertaken_by_the_person_shopping0.000000e+00coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_ 0.270 NA NA 0.00
coef_number_of_work_tours_undertaken_by_the_person_shopping8.243323e-05coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours 0.630 0.0404 15.57*** 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout-3.755981e-04coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_ 1.30 0.0744 17.43*** 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_eatout-1.868019e-12coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ 0.936 0.0765 12.24*** 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_eatout4.022851e-04coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__escort 0.469 0.163 2.88** 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_eatout-1.344298e-04coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othdiscr 0.844 0.118 7.13*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_eatout-1.392861e-04coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othmaint 0.104 0.161 0.65 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_eatout1.106246e-04coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__shopping 1.04 0.156 6.66*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_eatout-1.796611e-14coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__univ 0.772 0.320 2.41* 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_eatout-1.259540e-14coef_dummy_for_walking_to_all_stops-1.59 0.0898-17.72*** 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort-4.940134e-04coef_dummy_for_walking_to_all_stops_escort-2.04 0.265-7.71*** 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_escort1.495955e-04coef_dummy_for_walking_to_all_stops_othdiscr-2.34 0.153-15.29*** 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_escort-3.241983e-04coef_dummy_for_walking_to_all_stops_othmaint-1.32 0.170-7.79*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_escort9.510081e-04coef_dummy_for_walking_to_all_stops_school-2.07 0.112-18.53*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_escort-2.900724e-04coef_dummy_for_walking_to_all_stops_shopping-1.46 0.109-13.36*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_escort-1.512127e-06coef_dummy_for_walking_to_all_stops_social-1.65 0.150-10.97*** 0.00
coef_dummy_for_distance_less_than_5_miles_escort2.673121e-05coef_evening_arrival_19_00_interacted_with_return_tours 0.298 0.0385 7.73*** 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__escort-3.600725e-05coef_hh_accesibility_for_inbound_tours_interaction 0.258 0.0256 10.09*** 0.00
coef_dummy_for_walking_to_all_stops_escort1.191655e-04coef_high_income_hh 0.240 NA NA 0.00
coef_number_of_escort_tours_tours_undertaken_by_the_person_escort-7.410121e-05coef_mid_to_high_income_hh 0.230 NA NA 0.00
coef_number_of_hh_persons_escort-3.140191e-04coef_middle_to_low_income_hh 0.170 2.03e-14 BIG*** 0.00
coef_number_of_students_in_hh_escort1.269734e-04coef_middle_to_low_income_hh_ 0.170 1.42e-14 BIG*** 0.00
coef_number_of_work_tours_undertaken_by_the_person_escort-2.773780e-05coef_middle_to_low_income_hh__atwork 0.369 0.262 1.41 0.00
-2.4620.000000e+00coef_no_stops_if_tour_mode_is_drivetransit-999. NA NA 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_othmaint1.221742e-04coef_num_kids_between_5_and_15_including_years_old 0.0834 0.0434 1.92 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_othmaint3.550288e-05coef_num_kids_between_5_and_15_including_years_old_shopping 0.0331 0.0347 0.95 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_othmaint-3.087708e-04coef_number_of_adults_16_years_old_ 0.00618 0.0229 0.27 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_othmaint4.516106e-04coef_number_of_cars_number_of_workers 0.195 0.0414 4.72*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_othmaint3.975618e-04coef_number_of_cars_number_of_workers_school 0.630 0.0881 7.16*** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othmaint-6.769433e-05coef_number_of_eating_tours_tours_undertaken_by_the_person-0.425 0.178-2.39* 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othmaint-4.805955e-14coef_number_of_escort_tours_tours_undertaken_by_the_person 0.286 0.0527 5.42*** 0.00
coef_dummy_for_distance_in_miles_othmaint-1.679261e-04coef_number_of_escort_tours_tours_undertaken_by_the_person_escort-0.0779 0.0376-2.07* 0.00
coef_dummy_for_distance_less_than_20_miles_3.465085e-05coef_number_of_escort_tours_tours_undertaken_by_the_person_school 1.29 0.133 9.72*** 0.00
coef_dummy_for_female_othmaint1.685909e-04coef_number_of_escort_tours_tours_undertaken_by_the_person_univ 0.985 0.191 5.15*** 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othmaint-1.142635e-04coef_number_of_hh_persons-0.292 0.0225-12.98*** 0.00
coef_dummy_for_walking_to_all_stops_othmaint-3.369012e-04coef_number_of_hh_persons_escort-0.289 0.0247-11.72*** 0.00
coef_middle_to_low_income_hh_0.000000e+00coef_number_of_hh_persons_school-0.522 0.0197-26.42*** 0.00
coef_number_of_maintenace_tours_undertaken_by_the_houshold1.869470e-04coef_number_of_hh_persons_shopping-0.164 0.0143-11.47*** 0.00
coef_number_of_persons_participating_in_the_tour_return_stops_interaction1.532520e-05coef_number_of_hh_persons_univ-0.297 0.0417-7.12*** 0.00
coef_number_of_shool_tours_tours_undertaken_by_the_person-9.850134e-13coef_number_of_maintenace_tours_tours_undertaken_by_the_person-0.282 0.0682-4.13*** 0.00
coef_number_of_shop_tours_undertaken_by_the_person_othmaint1.727916e-04coef_number_of_maintenace_tours_tours_undertaken_by_the_person_othdiscr-0.274 0.0896-3.05** 0.00
coef_number_of_university_tours_tours_undertaken_by_the_person_othmaint0.000000e+00coef_number_of_maintenace_tours_undertaken_by_the_houshold 0.280 0.157 1.78 0.00
coef_number_of_work_tours_undertaken_by_the_person_othmaint-1.965224e-04coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction-0.531 0.165-3.22** 0.00
-0.9210.000000e+00coef_number_of_persons_participating_in_the_tour_return_stops_interaction 0.488 0.0633 7.72*** 0.00
0.9390.000000e+00coef_number_of_school_tours_tours_undertaken_by_the_person-1.54 0.467-3.30*** 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr-3.506169e-04coef_number_of_shool_tours_tours_undertaken_by_the_person-1.56 0.258-6.05*** 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_othdiscr1.907176e-04coef_number_of_shool_tours_tours_undertaken_by_the_person_othdiscr-0.844 0.100-8.43*** 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_othdiscr3.189979e-04coef_number_of_shop_tours_undertaken_by_the_houshold 0.194 0.245 0.79 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_othdiscr2.028679e-04coef_number_of_shop_tours_undertaken_by_the_houshold_shopping-0.142 0.117-1.21 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_othdiscr1.562541e-05coef_number_of_shop_tours_undertaken_by_the_person-0.304 0.0956-3.18** 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othdiscr2.583440e-04coef_number_of_shop_tours_undertaken_by_the_person_othdiscr-0.641 0.0747-8.59*** 0.00
coef_arrival_later_than_17_00__othdiscr1.080590e-04coef_number_of_shop_tours_undertaken_by_the_person_othmaint-0.175 0.0767-2.28* 0.00
coef_dummy_for_distance_in_miles_othdiscr9.492548e-04coef_number_of_students_in_hh 0.206 0.0209 9.85*** 0.00
coef_dummy_for_distance_less_than_10_miles_1.588828e-04coef_number_of_students_in_hh_escort 0.217 0.0357 6.07*** 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othdiscr1.826016e-04coef_number_of_subtours_in_the_tour 0.185 0.0354 5.21*** 0.00
coef_dummy_for_walking_to_all_stops_othdiscr1.223109e-04coef_number_of_university_tours_tours_undertaken_by_the_person-0.480 NA NA 0.00
coef_number_of_maintenace_tours_tours_undertaken_by_the_person_othdiscr-7.663028e-04coef_number_of_university_tours_tours_undertaken_by_the_person_othmaint-0.625 4.04e-15-BIG*** 0.00
coef_number_of_shool_tours_tours_undertaken_by_the_person_othdiscr4.152763e-04coef_number_of_university_tours_tours_undertaken_by_the_person_shopping-0.671 7.34e-15-BIG*** 0.00
coef_number_of_shop_tours_undertaken_by_the_person_othdiscr3.120237e-04coef_number_of_vehicles 0.190 0.0605 3.14** 0.00
coef_number_of_work_tours_undertaken_by_the_person_othdiscr3.092441e-04coef_number_of_vehicles_social-0.158 0.0333-4.76*** 0.00
-3.6710.000000e+00coef_number_of_work_tours_undertaken_by_the_person-0.182 0.0552-3.30*** 0.00
-3.8960.000000e+00coef_number_of_work_tours_undertaken_by_the_person_escort-0.222 0.0707-3.15** 0.00
-7.36100000000000150.000000e+00coef_number_of_work_tours_undertaken_by_the_person_othdiscr-0.547 0.0742-7.36*** 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_atwork-3.052719e-04coef_number_of_work_tours_undertaken_by_the_person_othmaint-0.426 0.0859-4.96*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_atwork-1.668958e-04coef_number_of_work_tours_undertaken_by_the_person_shopping-0.599 0.0588-10.19*** 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_atwork2.048973e-04coef_number_of_work_tours_undertaken_by_the_person_social-0.198 0.0971-2.04* 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_atwork1.185991e-04coef_presence_of_kids_between_0_and_4_including_years_old 0.738 0.0493 14.98*** 0.00
coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_0.000000e+00coef_presence_of_kids_between_5_and_15_including_years_old 0.174 0.0692 2.52* 0.00
coef_middle_to_low_income_hh__atwork-1.187817e-03coef_presence_of_kids_between_5_and_15_including_years_old_school 0.258 0.0737 3.50*** 0.00
coef_number_of_eating_tours_tours_undertaken_by_the_person4.166759e-04coef_presence_of_kids_between_5_and_15_including_years_old_univ 0.755 0.165 4.58*** 0.00
coef_primary_destination_accessibility_log_of_it_-3.977574e-03coef_primary_destination_accessibility_log_of_it_ 0.191 0.0120 15.92*** 0.00
coef_subtour_departure_less_than_or_equal_to_11am-7.903092e-04coef_subtour_departure_less_than_or_equal_to_11am 0.352 0.0707 4.98*** 0.00
coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_-4.153043e-03coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_ 0.0231 0.0171 1.35 0.00
coef_subtour_duration_in_hours_integer_-2.149064e-03coef_subtour_duration_in_hours_integer_ 0.555 0.0253 21.94*** 0.00
coef_subtour_return_time_greater_or_equal_to_2pm1.538038e-04coef_subtour_return_time_greater_or_equal_to_2pm 0.206 0.209 0.99 0.00
nit130nfev327njev130status0message'Optimization terminated successfully'successTrueelapsed_time0:01:25.611724method'SLSQP'n_cases5778iteration_number130logloss1.0547864171945307" - ], - "text/plain": [ - "┣ x: -2.139 -2.139000\n", - "┃ -3.934 -3.934000\n", - "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in -0.741225\n", - "┃ coef_alternative_specific_constant_for_outbound_stops_2out_0in -2.594489\n", - "┃ coef_alternative_specific_constant_for_return_stops_0out_1in -0.447476\n", - "┃ ... \n", - "┃ coef_primary_destination_accessibility_log_of_it_ 0.170704\n", - "┃ coef_subtour_departure_less_than_or_equal_to_11am 0.266339\n", - "┃ coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_ -0.152384\n", - "┃ coef_subtour_duration_in_hours_integer_ 0.681811\n", - "┃ coef_subtour_return_time_greater_or_equal_to_2pm 1.549569\n", - "┃ Length: 188, dtype: float64\n", - "┣ loglike: -6094.555918549999\n", - "┣ d_loglike: -2.139 0.000000\n", - "┃ -3.934 0.000000\n", - "┃ coef_alternative_specific_constant_for_outbound_stops_1out_0in -0.000080\n", - "┃ coef_alternative_specific_constant_for_outbound_stops_2out_0in -0.000716\n", - "┃ coef_alternative_specific_constant_for_return_stops_0out_1in -0.000063\n", - "┃ ... \n", - "┃ coef_primary_destination_accessibility_log_of_it_ -0.003978\n", - "┃ coef_subtour_departure_less_than_or_equal_to_11am -0.000790\n", - "┃ coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_ -0.004153\n", - "┃ coef_subtour_duration_in_hours_integer_ -0.002149\n", - "┃ coef_subtour_return_time_greater_or_equal_to_2pm 0.000154\n", - "┃ Length: 188, dtype: float64\n", - "┣ nit: 130\n", - "┣ nfev: 327\n", - "┣ njev: 130\n", - "┣ status: 0\n", - "┣ message: 'Optimization terminated successfully'\n", - "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=85, microseconds=611724)\n", - "┣ method: 'SLSQP'\n", - "┣ n_cases: 5778\n", - "┣ iteration_number: 130\n", - "┣ logloss: 1.0547864171945307" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.estimate(method='SLSQP', options={\"maxiter\": 1000})" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Estimated coefficients" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value
-2.139-2.14 0.00 NA NA-2.14
-3.934-3.93 0.00 NA NA-3.93
coef_alternative_specific_constant_for_outbound_stops_1out_0in-0.741 0.0909-8.16*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in-2.59 0.167-15.51*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in-0.447 0.0942-4.75*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in-1.66 0.136-12.17*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in 0.0394 0.0697 0.57 NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in 0.755 0.335 2.25* NA 0.00
coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours-2.00 0.132-15.17*** NA 0.00
coef_dummy_for_all_stops_made_by_transit-0.673 0.0870-7.73*** NA 0.00
coef_dummy_for_distance_in_miles 0.0440 0.0256 1.72 NA 0.00
coef_dummy_for_distance_less_than_20_miles-0.588 0.310-1.90 NA 0.00
coef_dummy_for_female 0.283 0.108 2.63** NA 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours 0.713 0.139 5.13*** NA 0.00
coef_dummy_for_walking_to_all_stops-1.49 0.218-6.84*** NA 0.00
coef_evening_arrival_19_00_interacted_with_return_tours 0.606 0.127 4.78*** NA 0.00
coef_high_income_hh 0.240 1.15e-07 BIG*** NA 0.00
coef_mid_to_high_income_hh 0.230 3.09e-07 BIG*** NA 0.00
coef_middle_to_low_income_hh 0.170 1.05e-06 BIG*** NA 0.00
coef_no_stops_if_tour_mode_is_drivetransit-999. 9.87e-07-BIG*** NA 0.00
coef_num_kids_between_5_and_15_including_years_old 0.0897 0.206 0.44 NA 0.00
coef_number_of_adults_16_years_old_ 0.0742 0.0890 0.83 NA 0.00
coef_number_of_cars_number_of_workers-0.0657 0.116-0.57 NA 0.00
coef_number_of_escort_tours_tours_undertaken_by_the_person 0.0978 0.216 0.45 NA 0.00
coef_number_of_hh_persons-0.328 0.0857-3.83*** NA 0.00
coef_number_of_school_tours_tours_undertaken_by_the_person 0.130 1.43 0.09 NA 0.00
coef_number_of_shop_tours_undertaken_by_the_houshold-0.328 0.660-0.50 NA 0.00
coef_number_of_students_in_hh 0.315 0.0885 3.56*** NA 0.00
coef_number_of_subtours_in_the_tour 0.337 0.128 2.63** NA 0.00
coef_number_of_university_tours_tours_undertaken_by_the_person-0.480 8.22e-07-BIG*** NA 0.00
coef_number_of_work_tours_undertaken_by_the_person-0.175 0.201-0.87 NA 0.00
coef_presence_of_kids_between_0_and_4_including_years_old 0.557 0.200 2.78** NA 0.00
coef_presence_of_kids_between_5_and_15_including_years_old 0.118 0.306 0.38 NA 0.00
-2.672-2.67 0.00 NA NA-2.67
coef_alternative_specific_constant_for_outbound_stops_1out_0in_school-1.77 0.250-7.07*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_school-4.31 0.594-7.26*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_school-6.21 1.12-5.53*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_school-1.23 0.243-5.05*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_school-3.19 0.436-7.30*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in 1.57 0.577 2.72** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_school 2.18 1.22 1.78 NA 0.00
coef_arrival_later_than_17_00_ 1.37 0.387 3.55*** NA 0.00
coef_dummy_for_distance_in_miles_school 0.0920 0.0697 1.32 NA 0.00
coef_dummy_for_female_school 0.688 0.282 2.44* NA 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ 1.90 0.388 4.91*** NA 0.00
coef_dummy_for_walking_to_all_stops_school-1.53 0.539-2.83** NA 0.00
coef_number_of_cars_number_of_workers_school 0.282 0.300 0.94 NA 0.00
coef_number_of_escort_tours_tours_undertaken_by_the_person_school 2.32 0.591 3.93*** NA 0.00
coef_number_of_hh_persons_school-0.603 0.0890-6.78*** NA 0.00
coef_presence_of_kids_between_5_and_15_including_years_old_school 0.0211 0.346 0.06 NA 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_univ-2.21 0.395-5.59*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_univ-4.04 0.629-6.42*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_univ-4.64 0.752-6.17*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_univ-1.57 0.395-3.98*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_univ-3.43 0.560-6.13*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_univ-3.86 0.649-5.95*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_univ 2.02 0.718 2.81** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_univ 2.12 1.26 1.68 NA 0.00
coef_arrival_later_than_17_00__univ 0.398 0.350 1.14 NA 0.00
coef_dummy_for_female_univ 0.527 0.361 1.46 NA 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__univ 1.09 0.968 1.12 NA 0.00
coef_hh_accesibility_for_inbound_tours_interaction 0.244 0.0583 4.18*** NA 0.00
coef_number_of_escort_tours_tours_undertaken_by_the_person_univ 1.86 1.35 1.37 NA 0.00
coef_number_of_hh_persons_univ-0.326 0.139-2.35* NA 0.00
coef_number_of_vehicles 0.266 0.201 1.32 NA 0.00
coef_presence_of_kids_between_5_and_15_including_years_old_univ-0.0615 0.651-0.09 NA 0.00
-1.783-1.78 0.00 NA NA-1.78
-2.874-2.87 0.00 NA NA-2.87
-3.379-3.38 0.00 NA NA-3.38
1.497 1.50 0.00 NA NA 1.50
coef_alternative_specific_constant_for_outbound_stops_1out_0in_social-1.29 0.598-2.16* NA 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_social-42.6 8.43e-07-BIG*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in-4.16 1.09-3.82*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in-28.9 4.10e-07-BIG*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_social 0.474 1.29 0.37 NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_social-2.40 1.50-1.61 NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_social-3.11 1.65-1.88 NA 0.00
coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in-1.49 0.366-4.07*** NA 0.00
coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in-3.53 0.880-4.01*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_social 2.61 1.22 2.14* NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_social-9.81 921.-0.01 NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in-0.168 0.519-0.32 NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in-26.1 1.12e-07-BIG*** NA 0.00
coef_arrival_later_than_17_00__social-0.470 0.240-1.96 NA 0.00
coef_at_least_one_kid_and_one_adult_participate_in_the_tour 2.12 1.01 2.09* NA 0.00
coef_dummy_for_a_return_visiting_tour-1.75 1.28-1.36 NA 0.00
coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg 0.344 0.644 0.53 NA 0.00
coef_dummy_for_an_outbound_visiting_tour-0.742 0.617-1.20 NA 0.00
coef_dummy_for_distance_in_miles_social-0.0788 0.0646-1.22 NA 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_ 1.14 0.248 4.60*** NA 0.00
coef_dummy_for_walking_to_all_stops_social-2.09 0.423-4.94*** NA 0.00
coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction-0.0275 0.310-0.09 NA 0.00
coef_number_of_shop_tours_undertaken_by_the_person-0.178 0.302-0.59 NA 0.00
coef_number_of_vehicles_social-0.154 0.132-1.17 NA 0.00
coef_number_of_work_tours_undertaken_by_the_person_social-0.0102 0.288-0.04 NA 0.00
-3.024-3.02 0.00 NA NA-3.02
coef_alternative_specific_constant_for_outbound_stops_1out_0in_shopping-1.49 0.156-9.57*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_shopping-3.34 0.273-12.24*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_shopping-4.54 0.447-10.16*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_shopping-1.23 0.155-7.95*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_shopping-2.58 0.221-11.70*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_shopping 0.585 0.339 1.72 NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_shopping-0.0156 1.03-0.02 NA 0.00
coef_dummy_for_distance_in_miles_shopping 0.0214 0.0384 0.56 NA 0.00
coef_dummy_for_distance_less_than_5_miles 0.153 0.172 0.89 NA 0.00
coef_dummy_for_female_shopping 0.339 0.162 2.09* NA 0.00
coef_dummy_for_only_adults_participate_in_the_tour 1.54 0.764 2.02* NA 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__shopping 3.10 0.813 3.82*** NA 0.00
coef_dummy_for_walking_to_all_stops_shopping-1.88 0.331-5.69*** NA 0.00
coef_num_kids_between_5_and_15_including_years_old_shopping-0.0478 0.155-0.31 NA 0.00
coef_number_of_hh_persons_shopping-0.0870 0.0495-1.76 NA 0.00
coef_number_of_maintenace_tours_tours_undertaken_by_the_person-0.326 0.218-1.49 NA 0.00
coef_number_of_shop_tours_undertaken_by_the_houshold_shopping 0.148 0.276 0.54 NA 0.00
coef_number_of_university_tours_tours_undertaken_by_the_person_shopping-0.671 3.90e-07-BIG*** NA 0.00
coef_number_of_work_tours_undertaken_by_the_person_shopping-0.437 0.186-2.35* NA 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_eatout-1.88 0.316-5.94*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_eatout-32.6 1.42e-07-BIG*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_eatout-3.74 0.648-5.77*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_eatout-1.69 0.321-5.26*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_eatout-3.03 0.462-6.56*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_eatout-4.84 1.04-4.64*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_eatout-32.0 2.36e-07-BIG*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_eatout-30.9 2.73e-07-BIG*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_1out_0in_escort-2.23 0.253-8.78*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_escort-4.86 0.729-6.67*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_escort-4.79 0.731-6.56*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_escort-1.28 0.241-5.31*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_escort-2.46 0.315-7.81*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_escort-12.3 923.-0.01 NA 0.00
coef_dummy_for_distance_less_than_5_miles_escort 0.270 0.240 1.12 NA 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__escort 1.40 0.752 1.86 NA 0.00
coef_dummy_for_walking_to_all_stops_escort-0.341 0.889-0.38 NA 0.00
coef_number_of_escort_tours_tours_undertaken_by_the_person_escort-0.260 0.147-1.77 NA 0.00
coef_number_of_hh_persons_escort-0.179 0.0901-1.98* NA 0.00
coef_number_of_students_in_hh_escort 0.161 0.159 1.01 NA 0.00
coef_number_of_work_tours_undertaken_by_the_person_escort-0.158 0.289-0.55 NA 0.00
-2.462-2.46 0.00 NA NA-2.46
coef_alternative_specific_constant_for_outbound_stops_1out_0in_othmaint-2.12 0.292-7.26*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_othmaint-3.47 0.501-6.92*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_othmaint-4.23 0.775-5.46*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_1in_othmaint-0.834 0.287-2.91** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_othmaint-1.19 0.307-3.87*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othmaint 0.315 0.650 0.48 NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in_othmaint-31.0 8.73e-08-BIG*** NA 0.00
coef_dummy_for_distance_in_miles_othmaint 0.102 0.0656 1.55 NA 0.00
coef_dummy_for_distance_less_than_20_miles_-0.622 0.451-1.38 NA 0.00
coef_dummy_for_female_othmaint 0.281 0.254 1.11 NA 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othmaint 0.169 0.746 0.23 NA 0.00
coef_dummy_for_walking_to_all_stops_othmaint-2.30 0.751-3.06** NA 0.00
coef_middle_to_low_income_hh_ 0.170 1.58e-08 BIG*** NA 0.00
coef_number_of_maintenace_tours_undertaken_by_the_houshold-0.265 0.426-0.62 NA 0.00
coef_number_of_persons_participating_in_the_tour_return_stops_interaction 0.626 0.233 2.69** NA 0.00
coef_number_of_shool_tours_tours_undertaken_by_the_person-29.4 3.81e-08-BIG*** NA 0.00
coef_number_of_shop_tours_undertaken_by_the_person_othmaint-0.200 0.253-0.79 NA 0.00
coef_number_of_university_tours_tours_undertaken_by_the_person_othmaint-0.625 3.47e-08-BIG*** NA 0.00
coef_number_of_work_tours_undertaken_by_the_person_othmaint-0.358 0.317-1.13 NA 0.00
-0.921-0.921 0.00 NA NA-0.92
0.939 0.939 0.00 NA NA 0.94
coef_alternative_specific_constant_for_outbound_stops_1out_0in_othdiscr-1.39 0.171-8.11*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_2out_0in_othdiscr-2.96 0.290-10.20*** NA 0.00
coef_alternative_specific_constant_for_outbound_stops_3out_0in_othdiscr-4.39 0.503-8.73*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_othdiscr-2.52 0.258-9.77*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_othdiscr-3.02 0.316-9.58*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_othdiscr 1.09 0.410 2.65** NA 0.00
coef_arrival_later_than_17_00__othdiscr-0.367 0.208-1.76 NA 0.00
coef_dummy_for_distance_in_miles_othdiscr 0.0493 0.0477 1.03 NA 0.00
coef_dummy_for_distance_less_than_10_miles_-0.135 0.250-0.54 NA 0.00
coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours__othdiscr 0.254 0.398 0.64 NA 0.00
coef_dummy_for_walking_to_all_stops_othdiscr-2.06 0.429-4.81*** NA 0.00
coef_number_of_maintenace_tours_tours_undertaken_by_the_person_othdiscr-0.621 0.322-1.92 NA 0.00
coef_number_of_shool_tours_tours_undertaken_by_the_person_othdiscr-0.595 0.410-1.45 NA 0.00
coef_number_of_shop_tours_undertaken_by_the_person_othdiscr-0.607 0.236-2.57* NA 0.00
coef_number_of_work_tours_undertaken_by_the_person_othdiscr-0.475 0.243-1.96 NA 0.00
-3.671-3.67 0.00 NA NA-3.67
-3.896-3.90 0.00 NA NA-3.90
-7.3610000000000015-7.36 0.00 NA NA-7.36
coef_alternative_specific_constant_for_outbound_stops_2out_0in_atwork-5.61 0.354-15.85*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_2in_atwork-6.03 0.427-14.13*** NA 0.00
coef_alternative_specific_constant_for_return_stops_0out_3in_atwork-8.02 1.03-7.75*** NA 0.00
coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in_atwork 2.56 1.04 2.45* NA 0.00
coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_ 0.270 0.00 NA[] 0.00 0.00
coef_middle_to_low_income_hh__atwork 0.939 0.357 2.63** NA 0.00
coef_number_of_eating_tours_tours_undertaken_by_the_person-0.250 0.553-0.45 NA 0.00
coef_primary_destination_accessibility_log_of_it_ 0.171 0.0435 3.93*** NA 0.00
coef_subtour_departure_less_than_or_equal_to_11am 0.266 0.259 1.03 NA 0.00
coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_-0.152 0.0816-1.87 NA 0.00
coef_subtour_duration_in_hours_integer_ 0.682 0.0974 7.00*** NA 0.00
coef_subtour_return_time_greater_or_equal_to_2pm 1.55 0.707 2.19* NA 0.00
" + "\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 9, @@ -6295,67 +6168,67 @@ " 3\n", " coef_number_of_hh_persons\n", " Number of HH Persons\n", - " -0.328159\n", + " -0.291501\n", " \n", " \n", " 4\n", " coef_number_of_students_in_hh\n", " Number of Students in HH\n", - " 0.315297\n", + " 0.206028\n", " \n", " \n", " 5\n", " coef_presence_of_kids_between_0_and_4_includin...\n", " Presence of Kids between 0 and 4 (including) y...\n", - " 0.557476\n", + " 0.738257\n", " \n", " \n", " 6\n", " coef_num_kids_between_5_and_15_including_years...\n", " Num kids between 5 and 15 (including) years old\n", - " 0.089718\n", + " 0.083356\n", " \n", " \n", " 7\n", " coef_presence_of_kids_between_5_and_15_includi...\n", " Presence of kids between 5 and 15 (including) ...\n", - " 0.117544\n", + " 0.174006\n", " \n", " \n", " 8\n", " coef_number_of_adults_16_years_old_\n", " Number of Adults (>= 16 years old)\n", - " 0.074203\n", + " 0.006177\n", " \n", " \n", " 9\n", " coef_number_of_cars_number_of_workers\n", " Number of Cars > Number of Workers\n", - " -0.065713\n", + " 0.195317\n", " \n", " \n", " 10\n", " coef_dummy_for_female\n", " Dummy for female\n", - " 0.282632\n", + " 0.231116\n", " \n", " \n", " 11\n", " coef_dummy_for_all_stops_made_by_transit\n", " Dummy for all stops made by transit\n", - " -0.672704\n", + " -0.698140\n", " \n", " \n", " 12\n", " coef_dummy_for_walking_to_all_stops\n", " Dummy for walking to all stops\n", - " -1.491072\n", + " -1.590379\n", " \n", " \n", " 13\n", " coef_number_of_work_tours_undertaken_by_the_pe...\n", " Number of work tours undertaken by the person\n", - " -0.174762\n", + " -0.182288\n", " \n", " \n", " 14\n", @@ -6367,49 +6240,49 @@ " 15\n", " coef_number_of_school_tours_tours_undertaken_b...\n", " Number of school tours tours undertaken by the...\n", - " 0.130473\n", + " -1.539830\n", " \n", " \n", " 16\n", " coef_number_of_escort_tours_tours_undertaken_b...\n", " Number of escort tours tours undertaken by the...\n", - " 0.097792\n", + " 0.285502\n", " \n", " \n", " 17\n", " coef_number_of_shop_tours_undertaken_by_the_ho...\n", " Number of shop tours undertaken by the houshold\n", - " -0.328294\n", + " 0.194165\n", " \n", " \n", " 18\n", " coef_am_peak_departure_between_6am_and_7_am_in...\n", " AM Peak departure between 6AM and 7 AM (includ...\n", - " -1.998832\n", + " -1.913742\n", " \n", " \n", " 19\n", " coef_evening_arrival_19_00_interacted_with_ret...\n", " Evening Arrival (>=19:00) Interacted with retu...\n", - " 0.606441\n", + " 0.297829\n", " \n", " \n", " 20\n", " coef_dummy_for_the_duration_of_the_tour_being_...\n", " Dummy for the duration of the tour being equal...\n", - " 0.713048\n", + " 0.629566\n", " \n", " \n", " 21\n", " coef_dummy_for_distance_less_than_20_miles\n", " dummy for distance less than 20 Miles\n", - " -0.588175\n", + " -0.209813\n", " \n", " \n", " 22\n", " coef_dummy_for_distance_in_miles\n", " dummy for distance in miles\n", - " 0.043974\n", + " 0.008199\n", " \n", " \n", " 23\n", @@ -6421,55 +6294,55 @@ " 24\n", " coef_alternative_specific_constant_for_return_...\n", " Alternative specific constant for return stops\n", - " -0.447476\n", + " -0.422070\n", " \n", " \n", " 25\n", " coef_number_of_subtours_in_the_tour\n", " Number of subtours in the tour\n", - " 0.337091\n", + " 0.184545\n", " \n", " \n", " 26\n", " coef_alternative_specific_constant_for_return_...\n", " Alternative specific constant for return stops\n", - " -1.657817\n", + " -1.737740\n", " \n", " \n", " 27\n", " coef_alternative_specific_constant_for_the_tot...\n", " Alternative specific constant for the total nu...\n", - " 0.039441\n", + " -0.033904\n", " \n", " \n", " 28\n", " coef_alternative_specific_constant_for_return_...\n", " Alternative specific constant for return stops\n", - " -2.139000\n", + " -2.056255\n", " \n", " \n", " 29\n", " coef_alternative_specific_constant_for_outboun...\n", " Alternative specific constant for outbound stops\n", - " -0.741225\n", + " -0.817659\n", " \n", " \n", " 30\n", " coef_alternative_specific_constant_for_outboun...\n", " Alternative specific constant for outbound stops\n", - " -2.594489\n", + " -2.553493\n", " \n", " \n", " 31\n", " coef_alternative_specific_constant_for_the_tot...\n", " Alternative specific constant for the total nu...\n", - " 0.754748\n", + " 0.555526\n", " \n", " \n", " 32\n", " coef_alternative_specific_constant_for_outboun...\n", " Alternative specific constant for outbound stops\n", - " -3.934000\n", + " -3.914672\n", " \n", " \n", "\n", @@ -6515,36 +6388,36 @@ "0 Middle to Low Income HH 0.170000 \n", "1 Mid to High Income HH 0.230000 \n", "2 High Income HH 0.240000 \n", - "3 Number of HH Persons -0.328159 \n", - "4 Number of Students in HH 0.315297 \n", - "5 Presence of Kids between 0 and 4 (including) y... 0.557476 \n", - "6 Num kids between 5 and 15 (including) years old 0.089718 \n", - "7 Presence of kids between 5 and 15 (including) ... 0.117544 \n", - "8 Number of Adults (>= 16 years old) 0.074203 \n", - "9 Number of Cars > Number of Workers -0.065713 \n", - "10 Dummy for female 0.282632 \n", - "11 Dummy for all stops made by transit -0.672704 \n", - "12 Dummy for walking to all stops -1.491072 \n", - "13 Number of work tours undertaken by the person -0.174762 \n", + "3 Number of HH Persons -0.291501 \n", + "4 Number of Students in HH 0.206028 \n", + "5 Presence of Kids between 0 and 4 (including) y... 0.738257 \n", + "6 Num kids between 5 and 15 (including) years old 0.083356 \n", + "7 Presence of kids between 5 and 15 (including) ... 0.174006 \n", + "8 Number of Adults (>= 16 years old) 0.006177 \n", + "9 Number of Cars > Number of Workers 0.195317 \n", + "10 Dummy for female 0.231116 \n", + "11 Dummy for all stops made by transit -0.698140 \n", + "12 Dummy for walking to all stops -1.590379 \n", + "13 Number of work tours undertaken by the person -0.182288 \n", "14 Number of university tours tours undertaken by... -0.480000 \n", - "15 Number of school tours tours undertaken by the... 0.130473 \n", - "16 Number of escort tours tours undertaken by the... 0.097792 \n", - "17 Number of shop tours undertaken by the houshold -0.328294 \n", - "18 AM Peak departure between 6AM and 7 AM (includ... -1.998832 \n", - "19 Evening Arrival (>=19:00) Interacted with retu... 0.606441 \n", - "20 Dummy for the duration of the tour being equal... 0.713048 \n", - "21 dummy for distance less than 20 Miles -0.588175 \n", - "22 dummy for distance in miles 0.043974 \n", + "15 Number of school tours tours undertaken by the... -1.539830 \n", + "16 Number of escort tours tours undertaken by the... 0.285502 \n", + "17 Number of shop tours undertaken by the houshold 0.194165 \n", + "18 AM Peak departure between 6AM and 7 AM (includ... -1.913742 \n", + "19 Evening Arrival (>=19:00) Interacted with retu... 0.297829 \n", + "20 Dummy for the duration of the tour being equal... 0.629566 \n", + "21 dummy for distance less than 20 Miles -0.209813 \n", + "22 dummy for distance in miles 0.008199 \n", "23 No stops if tour mode is driveTransit -999.000000 \n", - "24 Alternative specific constant for return stops -0.447476 \n", - "25 Number of subtours in the tour 0.337091 \n", - "26 Alternative specific constant for return stops -1.657817 \n", - "27 Alternative specific constant for the total nu... 0.039441 \n", - "28 Alternative specific constant for return stops -2.139000 \n", - "29 Alternative specific constant for outbound stops -0.741225 \n", - "30 Alternative specific constant for outbound stops -2.594489 \n", - "31 Alternative specific constant for the total nu... 0.754748 \n", - "32 Alternative specific constant for outbound stops -3.934000 " + "24 Alternative specific constant for return stops -0.422070 \n", + "25 Number of subtours in the tour 0.184545 \n", + "26 Alternative specific constant for return stops -1.737740 \n", + "27 Alternative specific constant for the total nu... -0.033904 \n", + "28 Alternative specific constant for return stops -2.056255 \n", + "29 Alternative specific constant for outbound stops -0.817659 \n", + "30 Alternative specific constant for outbound stops -2.553493 \n", + "31 Alternative specific constant for the total nu... 0.555526 \n", + "32 Alternative specific constant for outbound stops -3.914672 " ] }, "execution_count": 12, @@ -6564,7 +6437,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -6578,7 +6451,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/22_trip_dest.ipynb b/activitysim/examples/example_estimation/notebooks/22_trip_dest.ipynb index 576e87bfe5..2965cb74f0 100644 --- a/activitysim/examples/example_estimation/notebooks/22_trip_dest.ipynb +++ b/activitysim/examples/example_estimation/notebooks/22_trip_dest.ipynb @@ -26,30 +26,74 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import larch # !conda install larch #for estimation\n", + "import larch as lx\n", "import pandas as pd\n", - "import numpy as np\n", - "import yaml \n", - "import larch.util.excel\n", - "import os" + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -72,10 +116,35 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/trip_destination/trip_destination_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/trip_destination/trip_destination_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/trip_destination/trip_destination_alternatives_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/trip_destination/trip_destination_choosers_combined.parquet\n", + "loading from output-est-mode/estimation_data_bundle/trip_destination/trip_destination_landuse.csv\n", + "loading from output-est-mode/estimation_data_bundle/trip_destination/trip_destination_size_terms.csv\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/jpn/Git/est-mode/activitysim/activitysim/estimation/larch/location_choice.py:548: UserWarning: Removed 5419 choosers with invalid (zero-sized) observed choice\n", + " return location_choice_model(\n" + ] + } + ], "source": [ "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -290,148 +359,118 @@ " \n", " \n", " trip_id\n", - " variable\n", - " 1\n", - " 2\n", - " 3\n", - " 4\n", - " 5\n", - " 6\n", - " 7\n", - " 8\n", - " ...\n", - " 181\n", - " 182\n", - " 183\n", - " 184\n", - " 185\n", - " 186\n", - " 187\n", - " 188\n", - " 189\n", - " 190\n", + " dest_taz\n", + " util_size_term\n", + " util_no_attractions\n", + " util_distance_inbound\n", + " util_distance_outbound\n", + " util_distance_joint\n", + " util_prox_home_outbound\n", + " util_prox_home_inbound\n", + " util_prox_dest_outbound\n", + " util_prox_dest_inbound\n", + " util_sample_of_alternatives_correction_factor\n", + " util_mode_choice_logsum_os\n", + " util_stop_not_accessible_by_this_tour_mode\n", + " util_mode_choice_logsum_sd\n", + " util_dest_not_accessible_by_this_tour_mode\n", " \n", " \n", " \n", " \n", " 0\n", - " 123229\n", - " util_dest_not_accessible_by_this_tour_mode\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " ...\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", + " 439241\n", + " 2\n", + " 6.117394\n", " False\n", + " 0.000000\n", + " 14.110000\n", + " 0.0\n", + " 6.89\n", + " 0.000000\n", + " 7.22\n", + " 0.00\n", + " 6.128602\n", + " -0.847005\n", " False\n", + " -0.633253\n", " False\n", " \n", " \n", " 1\n", - " 123229\n", - " util_distance_inbound\n", - " 6.390000343322754\n", - " 6.170000076293945\n", - " 5.920000076293945\n", - " 5.810000419616699\n", - " 5.299999713897705\n", - " 5.170000076293945\n", - " 4.840000152587891\n", - " 4.630000114440918\n", - " ...\n", - " 9.819999694824219\n", - " 11.25\n", - " 10.449999809265137\n", - " 8.970000267028809\n", - " 7.920000076293945\n", - " 9.600000381469727\n", - " 9.889999389648438\n", - " 10.079999923706055\n", - " 11.899999618530273\n", - " 12.170000076293945\n", + " 439241\n", + " 11\n", + " 7.726934\n", + " False\n", + " 0.000000\n", + " 12.280001\n", + " 0.0\n", + " 5.90\n", + " 0.000000\n", + " 6.38\n", + " 0.00\n", + " 3.637608\n", + " -0.558405\n", + " False\n", + " -0.497479\n", + " False\n", " \n", " \n", " 2\n", - " 123229\n", - " util_distance_joint\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ...\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 439241\n", + " 16\n", + " 7.935721\n", + " False\n", + " 0.000000\n", + " 14.280000\n", " 0.0\n", + " 6.81\n", + " 0.000000\n", + " 7.47\n", + " 0.00\n", + " 3.634621\n", + " -0.681632\n", + " False\n", + " -0.639591\n", + " False\n", " \n", " \n", " 3\n", - " 123229\n", - " util_distance_outbound\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ...\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", + " 439241\n", + " 21\n", + " 5.953480\n", + " False\n", + " 0.000000\n", + " 12.920000\n", " 0.0\n", + " 6.13\n", + " 0.000000\n", + " 6.79\n", + " 0.00\n", + " 5.476918\n", + " -0.536647\n", + " False\n", + " -0.524008\n", + " False\n", " \n", " \n", " 4\n", - " 123229\n", - " util_mode_choice_logsum_os\n", - " -1.1826465123669618\n", - " -1.1342039462845261\n", - " -1.0045888362609303\n", - " -0.9695035841251944\n", - " -0.9086842324484546\n", - " -0.7911335856893744\n", - " -1.0394341719374236\n", - " -0.735128183005223\n", - " ...\n", - " -0.5685844758479193\n", - " -0.7106540688185471\n", - " -0.6324772374186627\n", - " -0.5127860821542347\n", - " -0.427736842041275\n", - " -0.5989989879176718\n", - " -0.6352947097849363\n", - " -0.6732994275559964\n", - " -0.8319610659002946\n", - " -0.8302145411677482\n", + " 439241\n", + " 82\n", + " 5.890218\n", + " False\n", + " 0.000000\n", + " 9.790000\n", + " 0.0\n", + " 4.83\n", + " 0.000000\n", + " 4.96\n", + " 0.00\n", + " 5.218103\n", + " -0.383122\n", + " False\n", + " -0.265333\n", + " False\n", " \n", " \n", " ...\n", @@ -451,230 +490,213 @@ " ...\n", " ...\n", " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " \n", - " \n", - " 39139\n", - " 2478375757\n", - " util_prox_home_inbound\n", - " 5.659999847412109\n", - " 5.570000171661377\n", - " 5.5\n", - " 5.329999923706055\n", - " 5.119999885559082\n", - " 5.190000057220459\n", - " 5.019999980926514\n", - " 4.809999942779541\n", - " ...\n", - " 6.260000228881836\n", - " 5.440000057220459\n", - " 5.110000133514404\n", - " 4.889999866485596\n", - " 4.329999923706055\n", - " 4.5\n", - " 3.990000009536743\n", - " 3.4200000762939453\n", - " 4.159999847412109\n", - " 4.650000095367432\n", - " \n", - " \n", - " 39140\n", - " 2478375757\n", - " util_prox_home_outbound\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ...\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", " \n", " \n", - " 39141\n", - " 2478375757\n", - " util_sample_of_alternatives_correction_factor\n", - " 5.969689780743902\n", - " 5.229744858144034\n", - " 6.651885938411212\n", - " 5.457984599784746\n", - " 4.557500241901908\n", - " 5.683456777589848\n", - " 4.880351408439651\n", - " 5.056172176409885\n", - " ...\n", - " 6.167159960103807\n", - " 5.635222918217218\n", - " 4.9055149705471015\n", - " 5.197733187456251\n", - " 4.545857557157909\n", - " 5.146011961990624\n", - " 5.677734711636542\n", - " 4.0921031600858315\n", - " 5.525577058677637\n", - " 6.765177014979627\n", - " \n", - " \n", - " 39142\n", - " 2478375757\n", - " util_size_term\n", - " 5.8928092787280315\n", - " 6.61382841501164\n", - " 5.174023179275996\n", - " 6.331334576117736\n", - " 7.181350090272405\n", - " 6.062963941307298\n", - " 6.824432363972737\n", - " 6.596881001099327\n", - " ...\n", - " 5.988058753973149\n", - " 6.313073295919817\n", - " 6.959507591274848\n", - " 6.611773525937498\n", - " 7.122336273469753\n", - " 6.565080445969589\n", - " 5.957654370567811\n", - " 7.481461558469711\n", - " 6.2347224418357365\n", - " 5.096060413644514\n", - " \n", - " \n", - " 39143\n", - " 2478375757\n", - " util_stop_not_accessible_by_this_tour_mode\n", - " False\n", - " False\n", - " False\n", + " 854498\n", + " 2481262477\n", + " 1314\n", + " 6.565007\n", " False\n", + " 21.299999\n", + " 0.000000\n", + " 0.0\n", + " 0.00\n", + " 10.650000\n", + " 0.00\n", + " 10.65\n", + " 3.869640\n", + " -3.466365\n", " False\n", + " -3.466365\n", " False\n", + " \n", + " \n", + " 854499\n", + " 2481262477\n", + " 1315\n", + " 5.491167\n", " False\n", + " 14.500000\n", + " 0.000000\n", + " 0.0\n", + " 0.00\n", + " 7.250000\n", + " 0.00\n", + " 7.25\n", + " 2.986897\n", + " -2.475631\n", " False\n", - " ...\n", + " -2.476182\n", " False\n", + " \n", + " \n", + " 854500\n", + " 2481262477\n", + " 1318\n", + " 4.109496\n", " False\n", + " 35.799999\n", + " 0.000000\n", + " 0.0\n", + " 0.00\n", + " 17.900000\n", + " 0.00\n", + " 17.90\n", + " 7.056036\n", + " -6.066198\n", " False\n", + " -6.054759\n", " False\n", + " \n", + " \n", + " 854501\n", + " 2481262477\n", + " 1324\n", + " 5.586113\n", " False\n", + " 40.349998\n", + " 0.000000\n", + " 0.0\n", + " 0.00\n", + " 19.950001\n", + " 0.00\n", + " 20.40\n", + " 6.153502\n", + " -6.458255\n", " False\n", + " -6.443607\n", " False\n", + " \n", + " \n", + " 854502\n", + " 2481262477\n", + " 1361\n", + " 7.160701\n", " False\n", + " 60.360001\n", + " 0.000000\n", + " 0.0\n", + " 0.00\n", + " 30.180000\n", + " 0.00\n", + " 30.18\n", + " 7.103621\n", + " -9.888594\n", " False\n", + " -9.902823\n", " False\n", " \n", " \n", "\n", - "

39144 rows × 192 columns

\n", + "

854503 rows × 16 columns

\n", "" ], "text/plain": [ - " trip_id variable \\\n", - "0 123229 util_dest_not_accessible_by_this_tour_mode \n", - "1 123229 util_distance_inbound \n", - "2 123229 util_distance_joint \n", - "3 123229 util_distance_outbound \n", - "4 123229 util_mode_choice_logsum_os \n", - "... ... ... \n", - "39139 2478375757 util_prox_home_inbound \n", - "39140 2478375757 util_prox_home_outbound \n", - "39141 2478375757 util_sample_of_alternatives_correction_factor \n", - "39142 2478375757 util_size_term \n", - "39143 2478375757 util_stop_not_accessible_by_this_tour_mode \n", + " trip_id dest_taz util_size_term util_no_attractions \\\n", + "0 439241 2 6.117394 False \n", + "1 439241 11 7.726934 False \n", + "2 439241 16 7.935721 False \n", + "3 439241 21 5.953480 False \n", + "4 439241 82 5.890218 False \n", + "... ... ... ... ... \n", + "854498 2481262477 1314 6.565007 False \n", + "854499 2481262477 1315 5.491167 False \n", + "854500 2481262477 1318 4.109496 False \n", + "854501 2481262477 1324 5.586113 False \n", + "854502 2481262477 1361 7.160701 False \n", + "\n", + " util_distance_inbound util_distance_outbound util_distance_joint \\\n", + "0 0.000000 14.110000 0.0 \n", + "1 0.000000 12.280001 0.0 \n", + "2 0.000000 14.280000 0.0 \n", + "3 0.000000 12.920000 0.0 \n", + "4 0.000000 9.790000 0.0 \n", + "... ... ... ... \n", + "854498 21.299999 0.000000 0.0 \n", + "854499 14.500000 0.000000 0.0 \n", + "854500 35.799999 0.000000 0.0 \n", + "854501 40.349998 0.000000 0.0 \n", + "854502 60.360001 0.000000 0.0 \n", "\n", - " 1 2 3 \\\n", - "0 False False False \n", - "1 6.390000343322754 6.170000076293945 5.920000076293945 \n", - "2 0.0 0.0 0.0 \n", - "3 0.0 0.0 0.0 \n", - "4 -1.1826465123669618 -1.1342039462845261 -1.0045888362609303 \n", - "... ... ... ... \n", - "39139 5.659999847412109 5.570000171661377 5.5 \n", - "39140 0.0 0.0 0.0 \n", - "39141 5.969689780743902 5.229744858144034 6.651885938411212 \n", - "39142 5.8928092787280315 6.61382841501164 5.174023179275996 \n", - "39143 False False False \n", + " util_prox_home_outbound util_prox_home_inbound \\\n", + "0 6.89 0.000000 \n", + "1 5.90 0.000000 \n", + "2 6.81 0.000000 \n", + "3 6.13 0.000000 \n", + "4 4.83 0.000000 \n", + "... ... ... \n", + "854498 0.00 10.650000 \n", + "854499 0.00 7.250000 \n", + "854500 0.00 17.900000 \n", + "854501 0.00 19.950001 \n", + "854502 0.00 30.180000 \n", "\n", - " 4 5 6 \\\n", - "0 False False False \n", - "1 5.810000419616699 5.299999713897705 5.170000076293945 \n", - "2 0.0 0.0 0.0 \n", - "3 0.0 0.0 0.0 \n", - "4 -0.9695035841251944 -0.9086842324484546 -0.7911335856893744 \n", - "... ... ... ... \n", - "39139 5.329999923706055 5.119999885559082 5.190000057220459 \n", - "39140 0.0 0.0 0.0 \n", - "39141 5.457984599784746 4.557500241901908 5.683456777589848 \n", - "39142 6.331334576117736 7.181350090272405 6.062963941307298 \n", - "39143 False False False \n", + " util_prox_dest_outbound util_prox_dest_inbound \\\n", + "0 7.22 0.00 \n", + "1 6.38 0.00 \n", + "2 7.47 0.00 \n", + "3 6.79 0.00 \n", + "4 4.96 0.00 \n", + "... ... ... \n", + "854498 0.00 10.65 \n", + "854499 0.00 7.25 \n", + "854500 0.00 17.90 \n", + "854501 0.00 20.40 \n", + "854502 0.00 30.18 \n", "\n", - " 7 8 ... 181 \\\n", - "0 False False ... False \n", - "1 4.840000152587891 4.630000114440918 ... 9.819999694824219 \n", - "2 0.0 0.0 ... 0.0 \n", - "3 0.0 0.0 ... 0.0 \n", - "4 -1.0394341719374236 -0.735128183005223 ... -0.5685844758479193 \n", - "... ... ... ... ... \n", - "39139 5.019999980926514 4.809999942779541 ... 6.260000228881836 \n", - "39140 0.0 0.0 ... 0.0 \n", - "39141 4.880351408439651 5.056172176409885 ... 6.167159960103807 \n", - "39142 6.824432363972737 6.596881001099327 ... 5.988058753973149 \n", - "39143 False False ... False \n", + " util_sample_of_alternatives_correction_factor \\\n", + "0 6.128602 \n", + "1 3.637608 \n", + "2 3.634621 \n", + "3 5.476918 \n", + "4 5.218103 \n", + "... ... \n", + "854498 3.869640 \n", + "854499 2.986897 \n", + "854500 7.056036 \n", + "854501 6.153502 \n", + "854502 7.103621 \n", "\n", - " 182 183 184 \\\n", - "0 False False False \n", - "1 11.25 10.449999809265137 8.970000267028809 \n", - "2 0.0 0.0 0.0 \n", - "3 0.0 0.0 0.0 \n", - "4 -0.7106540688185471 -0.6324772374186627 -0.5127860821542347 \n", - "... ... ... ... \n", - "39139 5.440000057220459 5.110000133514404 4.889999866485596 \n", - "39140 0.0 0.0 0.0 \n", - "39141 5.635222918217218 4.9055149705471015 5.197733187456251 \n", - "39142 6.313073295919817 6.959507591274848 6.611773525937498 \n", - "39143 False False False \n", + " util_mode_choice_logsum_os \\\n", + "0 -0.847005 \n", + "1 -0.558405 \n", + "2 -0.681632 \n", + "3 -0.536647 \n", + "4 -0.383122 \n", + "... ... \n", + "854498 -3.466365 \n", + "854499 -2.475631 \n", + "854500 -6.066198 \n", + "854501 -6.458255 \n", + "854502 -9.888594 \n", "\n", - " 185 186 187 \\\n", - "0 False False False \n", - "1 7.920000076293945 9.600000381469727 9.889999389648438 \n", - "2 0.0 0.0 0.0 \n", - "3 0.0 0.0 0.0 \n", - "4 -0.427736842041275 -0.5989989879176718 -0.6352947097849363 \n", - "... ... ... ... \n", - "39139 4.329999923706055 4.5 3.990000009536743 \n", - "39140 0.0 0.0 0.0 \n", - "39141 4.545857557157909 5.146011961990624 5.677734711636542 \n", - "39142 7.122336273469753 6.565080445969589 5.957654370567811 \n", - "39143 False False False \n", + " util_stop_not_accessible_by_this_tour_mode \\\n", + "0 False \n", + "1 False \n", + "2 False \n", + "3 False \n", + "4 False \n", + "... ... \n", + "854498 False \n", + "854499 False \n", + "854500 False \n", + "854501 False \n", + "854502 False \n", "\n", - " 188 189 190 \n", - "0 False False False \n", - "1 10.079999923706055 11.899999618530273 12.170000076293945 \n", - "2 0.0 0.0 0.0 \n", - "3 0.0 0.0 0.0 \n", - "4 -0.6732994275559964 -0.8319610659002946 -0.8302145411677482 \n", - "... ... ... ... \n", - "39139 3.4200000762939453 4.159999847412109 4.650000095367432 \n", - "39140 0.0 0.0 0.0 \n", - "39141 4.0921031600858315 5.525577058677637 6.765177014979627 \n", - "39142 7.481461558469711 6.2347224418357365 5.096060413644514 \n", - "39143 False False False \n", + " util_mode_choice_logsum_sd util_dest_not_accessible_by_this_tour_mode \n", + "0 -0.633253 False \n", + "1 -0.497479 False \n", + "2 -0.639591 False \n", + "3 -0.524008 False \n", + "4 -0.265333 False \n", + "... ... ... \n", + "854498 -3.466365 False \n", + "854499 -2.476182 False \n", + "854500 -6.054759 False \n", + "854501 -6.443607 False \n", + "854502 -9.902823 False \n", "\n", - "[39144 rows x 192 columns]" + "[854503 rows x 16 columns]" ] }, "execution_count": 6, @@ -724,130 +746,142 @@ " override_choice\n", " person_id\n", " household_id\n", - " tour_id\n", " primary_purpose\n", " trip_num\n", " outbound\n", " trip_count\n", + " destination\n", + " ...\n", " purpose\n", " next_trip_id\n", - " destination\n", - " origin\n", - " failed\n", " tour_mode\n", " trip_period\n", " is_joint\n", + " tour_leg_dest\n", + " purpose_index_num\n", + " tour_mode_is_walk\n", + " tour_mode_is_bike\n", " destination_logsum\n", " \n", " \n", " \n", " \n", " 0\n", - " 123229\n", - " 7\n", - " 69\n", - " 375\n", - " 375\n", - " 15403\n", - " othmaint\n", + " 439241\n", + " 93\n", + " 178\n", + " 1339\n", + " 1339\n", + " eatout\n", " 1\n", - " False\n", - " 3\n", + " True\n", + " 2\n", + " 187\n", + " ...\n", " shopping\n", - " 123230\n", - " 105\n", - " 67\n", - " False\n", + " 439242\n", " DRIVEALONEFREE\n", - " MD\n", + " PM\n", + " False\n", + " 187.0\n", + " 2\n", + " False\n", " False\n", " NaN\n", " \n", " \n", " 1\n", - " 123230\n", - " 9\n", - " 106\n", - " 375\n", - " 375\n", - " 15403\n", - " othmaint\n", + " 497189\n", + " 169\n", + " 99\n", + " 1515\n", + " 1515\n", + " shopping\n", + " 1\n", + " False\n", " 2\n", + " 170\n", + " ...\n", + " othdiscr\n", + " 497190\n", + " DRIVEALONEFREE\n", + " EV\n", " False\n", - " 3\n", - " eatout\n", - " 123231\n", - " 105\n", - " 69\n", + " 170.0\n", + " 6\n", " False\n", - " DRIVEALONEFREE\n", - " MD\n", " False\n", " NaN\n", " \n", " \n", " 2\n", - " 206561\n", - " 7\n", - " 9\n", - " 629\n", - " 629\n", - " 25820\n", - " univ\n", + " 536181\n", + " 184\n", + " 177\n", + " 1634\n", + " 1634\n", + " othmaint\n", " 1\n", - " True\n", + " False\n", " 2\n", - " escort\n", - " 206562\n", - " 12\n", - " 131\n", + " 178\n", + " ...\n", + " othmaint\n", + " 536182\n", + " DRIVEALONEFREE\n", + " PM\n", + " False\n", + " 178.0\n", + " 4\n", " False\n", - " WALK_HVY\n", - " MD\n", " False\n", " NaN\n", " \n", " \n", " 3\n", - " 265617\n", - " 141\n", - " 141\n", - " 809\n", - " 809\n", - " 33202\n", - " shopping\n", + " 593909\n", + " 183\n", + " 136\n", + " 1810\n", + " 1810\n", + " othmaint\n", + " 1\n", + " False\n", + " 3\n", + " 183\n", + " ...\n", + " escort\n", + " 593910\n", + " SHARED2FREE\n", + " AM\n", + " False\n", + " 183.0\n", " 1\n", - " True\n", - " 2\n", - " shopping\n", - " 265618\n", - " 117\n", - " 138\n", " False\n", - " DRIVEALONEFREE\n", - " MD\n", " False\n", " NaN\n", " \n", " \n", " 4\n", - " 265621\n", - " 127\n", - " 127\n", - " 809\n", - " 809\n", - " 33202\n", - " shopping\n", - " 1\n", - " False\n", + " 593910\n", + " 89\n", + " 188\n", + " 1810\n", + " 1810\n", + " othmaint\n", " 2\n", + " False\n", + " 3\n", + " 183\n", + " ...\n", " othmaint\n", - " 265622\n", - " 138\n", - " 117\n", + " 593911\n", + " SHARED2FREE\n", + " AM\n", + " False\n", + " 183.0\n", + " 4\n", " False\n", - " DRIVEALONEFREE\n", - " MD\n", " False\n", " NaN\n", " \n", @@ -872,176 +906,201 @@ " ...\n", " ...\n", " ...\n", + " ...\n", + " ...\n", " \n", " \n", - " 2791\n", - " 2473349145\n", - " 7\n", - " 121\n", - " 7540698\n", - " 2849363\n", - " 309168643\n", + " 36442\n", + " 2480879045\n", + " 1304\n", + " 1306\n", + " 7563655\n", + " 2872320\n", " othdiscr\n", " 1\n", - " True\n", + " False\n", " 2\n", - " social\n", - " 2473349146\n", - " 56\n", - " 92\n", + " 1293\n", + " ...\n", + " othdiscr\n", + " 2480879046\n", + " DRIVEALONEFREE\n", + " MD\n", + " False\n", + " 1293.0\n", + " 6\n", " False\n", - " SHARED3FREE\n", - " PM\n", " False\n", " NaN\n", " \n", " \n", - " 2792\n", - " 2473471869\n", - " 25\n", - " 134\n", - " 7541072\n", - " 2849737\n", - " 309183983\n", - " univ\n", + " 36443\n", + " 2480879069\n", + " 1298\n", + " 1299\n", + " 7563655\n", + " 2872320\n", + " othmaint\n", " 1\n", " False\n", + " 4\n", + " 1293\n", + " ...\n", + " shopping\n", + " 2480879070\n", + " DRIVEALONEFREE\n", + " PM\n", + " False\n", + " 1293.0\n", " 2\n", - " escort\n", - " 2473471870\n", - " 117\n", - " 107\n", " False\n", - " TAXI\n", - " AM\n", " False\n", " NaN\n", " \n", " \n", - " 2793\n", - " 2477980533\n", - " 7\n", - " 117\n", - " 7554818\n", - " 2863483\n", - " 309747566\n", + " 36444\n", + " 2480879070\n", + " 1291\n", + " 1293\n", + " 7563655\n", + " 2872320\n", " othmaint\n", - " 1\n", - " False\n", " 2\n", - " shopping\n", - " 2477980534\n", - " 20\n", - " 177\n", " False\n", + " 4\n", + " 1293\n", + " ...\n", + " eatout\n", + " 2480879071\n", " DRIVEALONEFREE\n", " PM\n", " False\n", + " 1293.0\n", + " 3\n", + " False\n", + " False\n", " NaN\n", " \n", " \n", - " 2794\n", - " 2478086525\n", - " 7\n", - " 48\n", - " 7555141\n", - " 2863806\n", - " 309760815\n", - " shopping\n", - " 1\n", + " 36445\n", + " 2480879071\n", + " 1293\n", + " 1293\n", + " 7563655\n", + " 2872320\n", + " othmaint\n", + " 3\n", + " False\n", + " 4\n", + " 1293\n", + " ...\n", + " othdiscr\n", + " 2480879072\n", + " DRIVEALONEFREE\n", + " PM\n", " False\n", - " 2\n", - " shopping\n", - " 2478086526\n", - " 85\n", - " 41\n", + " 1293.0\n", + " 6\n", " False\n", - " SHARED2FREE\n", - " PM\n", " False\n", " NaN\n", " \n", " \n", - " 2795\n", - " 2478375757\n", - " 126\n", - " 127\n", - " 7556023\n", - " 2864688\n", - " 309796969\n", + " 36446\n", + " 2481262477\n", + " 1309\n", + " 1302\n", + " 7564824\n", + " 2873489\n", " othdiscr\n", " 1\n", " False\n", " 2\n", - " escort\n", - " 2478375758\n", - " 136\n", - " 128\n", - " False\n", + " 1310\n", + " ...\n", + " shopping\n", + " 2481262478\n", " DRIVEALONEFREE\n", - " EV\n", + " PM\n", + " False\n", + " 1310.0\n", + " 2\n", + " False\n", " False\n", " NaN\n", " \n", " \n", "\n", - "

2796 rows × 19 columns

\n", + "

36447 rows × 23 columns

\n", "" ], "text/plain": [ - " trip_id model_choice override_choice person_id household_id \\\n", - "0 123229 7 69 375 375 \n", - "1 123230 9 106 375 375 \n", - "2 206561 7 9 629 629 \n", - "3 265617 141 141 809 809 \n", - "4 265621 127 127 809 809 \n", - "... ... ... ... ... ... \n", - "2791 2473349145 7 121 7540698 2849363 \n", - "2792 2473471869 25 134 7541072 2849737 \n", - "2793 2477980533 7 117 7554818 2863483 \n", - "2794 2478086525 7 48 7555141 2863806 \n", - "2795 2478375757 126 127 7556023 2864688 \n", + " trip_id model_choice override_choice person_id household_id \\\n", + "0 439241 93 178 1339 1339 \n", + "1 497189 169 99 1515 1515 \n", + "2 536181 184 177 1634 1634 \n", + "3 593909 183 136 1810 1810 \n", + "4 593910 89 188 1810 1810 \n", + "... ... ... ... ... ... \n", + "36442 2480879045 1304 1306 7563655 2872320 \n", + "36443 2480879069 1298 1299 7563655 2872320 \n", + "36444 2480879070 1291 1293 7563655 2872320 \n", + "36445 2480879071 1293 1293 7563655 2872320 \n", + "36446 2481262477 1309 1302 7564824 2873489 \n", "\n", - " tour_id primary_purpose trip_num outbound trip_count purpose \\\n", - "0 15403 othmaint 1 False 3 shopping \n", - "1 15403 othmaint 2 False 3 eatout \n", - "2 25820 univ 1 True 2 escort \n", - "3 33202 shopping 1 True 2 shopping \n", - "4 33202 shopping 1 False 2 othmaint \n", - "... ... ... ... ... ... ... \n", - "2791 309168643 othdiscr 1 True 2 social \n", - "2792 309183983 univ 1 False 2 escort \n", - "2793 309747566 othmaint 1 False 2 shopping \n", - "2794 309760815 shopping 1 False 2 shopping \n", - "2795 309796969 othdiscr 1 False 2 escort \n", + " primary_purpose trip_num outbound trip_count destination ... \\\n", + "0 eatout 1 True 2 187 ... \n", + "1 shopping 1 False 2 170 ... \n", + "2 othmaint 1 False 2 178 ... \n", + "3 othmaint 1 False 3 183 ... \n", + "4 othmaint 2 False 3 183 ... \n", + "... ... ... ... ... ... ... \n", + "36442 othdiscr 1 False 2 1293 ... \n", + "36443 othmaint 1 False 4 1293 ... \n", + "36444 othmaint 2 False 4 1293 ... \n", + "36445 othmaint 3 False 4 1293 ... \n", + "36446 othdiscr 1 False 2 1310 ... \n", "\n", - " next_trip_id destination origin failed tour_mode trip_period \\\n", - "0 123230 105 67 False DRIVEALONEFREE MD \n", - "1 123231 105 69 False DRIVEALONEFREE MD \n", - "2 206562 12 131 False WALK_HVY MD \n", - "3 265618 117 138 False DRIVEALONEFREE MD \n", - "4 265622 138 117 False DRIVEALONEFREE MD \n", - "... ... ... ... ... ... ... \n", - "2791 2473349146 56 92 False SHARED3FREE PM \n", - "2792 2473471870 117 107 False TAXI AM \n", - "2793 2477980534 20 177 False DRIVEALONEFREE PM \n", - "2794 2478086526 85 41 False SHARED2FREE PM \n", - "2795 2478375758 136 128 False DRIVEALONEFREE EV \n", + " purpose next_trip_id tour_mode trip_period is_joint \\\n", + "0 shopping 439242 DRIVEALONEFREE PM False \n", + "1 othdiscr 497190 DRIVEALONEFREE EV False \n", + "2 othmaint 536182 DRIVEALONEFREE PM False \n", + "3 escort 593910 SHARED2FREE AM False \n", + "4 othmaint 593911 SHARED2FREE AM False \n", + "... ... ... ... ... ... \n", + "36442 othdiscr 2480879046 DRIVEALONEFREE MD False \n", + "36443 shopping 2480879070 DRIVEALONEFREE PM False \n", + "36444 eatout 2480879071 DRIVEALONEFREE PM False \n", + "36445 othdiscr 2480879072 DRIVEALONEFREE PM False \n", + "36446 shopping 2481262478 DRIVEALONEFREE PM False \n", "\n", - " is_joint destination_logsum \n", - "0 False NaN \n", - "1 False NaN \n", - "2 False NaN \n", - "3 False NaN \n", - "4 False NaN \n", - "... ... ... \n", - "2791 False NaN \n", - "2792 False NaN \n", - "2793 False NaN \n", - "2794 False NaN \n", - "2795 False NaN \n", + " tour_leg_dest purpose_index_num tour_mode_is_walk tour_mode_is_bike \\\n", + "0 187.0 2 False False \n", + "1 170.0 6 False False \n", + "2 178.0 4 False False \n", + "3 183.0 1 False False \n", + "4 183.0 4 False False \n", + "... ... ... ... ... \n", + "36442 1293.0 6 False False \n", + "36443 1293.0 2 False False \n", + "36444 1293.0 3 False False \n", + "36445 1293.0 6 False False \n", + "36446 1310.0 2 False False \n", "\n", - "[2796 rows x 19 columns]" + " destination_logsum \n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN \n", + "... ... \n", + "36442 NaN \n", + "36443 NaN \n", + "36444 NaN \n", + "36445 NaN \n", + "36446 NaN \n", + "\n", + "[36447 rows x 23 columns]" ] }, "execution_count": 7, @@ -1148,9 +1207,9 @@ " 7\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 3\n", " 5.89564\n", " 2.875000\n", @@ -1172,9 +1231,9 @@ " 19\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.84871\n", " 5.195214\n", @@ -1196,9 +1255,9 @@ " 38\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.53231\n", " 80.470405\n", @@ -1220,9 +1279,9 @@ " 20\n", " ...\n", " 0\n", + " 0.0\n", " 0.00000\n", - " 0.00000\n", - " 0.00000\n", + " 0.0\n", " 2\n", " 5.64330\n", " 7.947368\n", @@ -1244,9 +1303,9 @@ " 86\n", " ...\n", " 0\n", - " 0.00000\n", + " 0.0\n", " 72.14684\n", - " 0.00000\n", + " 0.0\n", " 1\n", " 5.52555\n", " 38.187500\n", @@ -1279,188 +1338,188 @@ " ...\n", " \n", " \n", - " 186\n", - " 4\n", - " 4\n", - " 1\n", - " 2779\n", - " 8062\n", - " 376.0\n", - " 172.0\n", - " 15.00000\n", - " 1760\n", - " 1178\n", + " 1450\n", + " 34\n", + " 34\n", + " 9\n", + " 2724\n", + " 6493\n", + " 1320.0\n", + " 630.0\n", + " 69.00000\n", + " 1046\n", + " 1013\n", " ...\n", - 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190 rows × 28 columns

\n", + "

1454 rows × 28 columns

\n", "" ], "text/plain": [ - " DISTRICT SD county_id TOTHH TOTPOP TOTACRE RESACRE CIACRE \\\n", - "zone_id \n", - "1 1 1 1 46 82 20.3 1.0 15.00000 \n", - "2 1 1 1 134 240 31.1 1.0 24.79297 \n", - "3 1 1 1 267 476 14.7 1.0 2.31799 \n", - "4 1 1 1 151 253 19.3 1.0 18.00000 \n", - "5 1 1 1 611 1069 52.7 1.0 15.00000 \n", - "... ... .. ... ... ... ... ... ... \n", - "186 4 4 1 2779 8062 376.0 172.0 15.00000 \n", - "187 4 4 1 1492 4139 214.0 116.0 10.00000 \n", - "188 4 4 1 753 4072 232.0 11.0 178.00000 \n", - "189 4 4 1 3546 8476 201.0 72.0 6.00000 \n", - "190 4 4 1 968 1647 1381.0 14.0 28.00000 \n", + " DISTRICT SD county_id TOTHH TOTPOP TOTACRE RESACRE CIACRE \\\n", + "zone_id \n", + "1 1 1 1 46 82 20.3 1.0 15.00000 \n", + "2 1 1 1 134 240 31.1 1.0 24.79297 \n", + "3 1 1 1 267 476 14.7 1.0 2.31799 \n", + "4 1 1 1 151 253 19.3 1.0 18.00000 \n", + "5 1 1 1 611 1069 52.7 1.0 15.00000 \n", + "... ... .. ... ... ... ... ... ... \n", + "1450 34 34 9 2724 6493 1320.0 630.0 69.00000 \n", + "1451 34 34 9 2016 4835 664.0 379.0 43.00000 \n", + "1452 34 34 9 2178 5055 1068.0 602.0 35.00000 \n", + "1453 34 34 9 298 779 14195.0 429.0 4.00000 \n", + "1454 34 34 9 1068 2337 10469.0 1114.0 27.00000 \n", "\n", - " TOTEMP AGE0519 ... area_type HSENROLL COLLFTE \\\n", - "zone_id ... \n", - "1 27318 7 ... 0 0.00000 0.00000 \n", - "2 42078 19 ... 0 0.00000 0.00000 \n", - "3 2445 38 ... 0 0.00000 0.00000 \n", - "4 22434 20 ... 0 0.00000 0.00000 \n", - "5 15662 86 ... 0 0.00000 72.14684 \n", - "... ... ... ... ... ... ... \n", - "186 1760 1178 ... 3 0.00000 0.00000 \n", - "187 808 603 ... 3 0.00000 0.00000 \n", - "188 4502 1117 ... 2 3961.04761 17397.79102 \n", - "189 226 1057 ... 2 0.00000 0.00000 \n", - "190 1010 114 ... 3 0.00000 0.00000 \n", + " TOTEMP AGE0519 ... area_type HSENROLL COLLFTE COLLPTE \\\n", + "zone_id ... \n", + "1 27318 7 ... 0 0.0 0.00000 0.0 \n", + "2 42078 19 ... 0 0.0 0.00000 0.0 \n", + "3 2445 38 ... 0 0.0 0.00000 0.0 \n", + "4 22434 20 ... 0 0.0 0.00000 0.0 \n", + "5 15662 86 ... 0 0.0 72.14684 0.0 \n", + "... ... ... ... ... ... ... ... \n", + "1450 1046 1013 ... 4 0.0 0.00000 0.0 \n", + "1451 757 757 ... 4 0.0 0.00000 0.0 \n", + "1452 2110 789 ... 4 0.0 0.00000 0.0 \n", + "1453 922 88 ... 5 0.0 0.00000 0.0 \n", + "1454 607 418 ... 5 0.0 0.00000 0.0 \n", "\n", - " COLLPTE TOPOLOGY TERMINAL household_density \\\n", - "zone_id \n", - "1 0.00000 3 5.89564 2.875000 \n", - "2 0.00000 1 5.84871 5.195214 \n", - "3 0.00000 1 5.53231 80.470405 \n", - "4 0.00000 2 5.64330 7.947368 \n", - "5 0.00000 1 5.52555 38.187500 \n", - "... ... ... ... ... \n", - "186 0.00000 1 2.04173 14.860963 \n", - "187 0.00000 2 1.73676 11.841270 \n", - "188 11152.93652 1 2.28992 3.984127 \n", - "189 0.00000 1 2.88773 45.461538 \n", - "190 0.00000 1 2.60309 23.047619 \n", + " TOPOLOGY TERMINAL household_density employment_density \\\n", + "zone_id \n", + "1 3 5.89564 2.875000 1707.375000 \n", + "2 1 5.84871 5.195214 1631.374751 \n", + "3 1 5.53231 80.470405 736.891913 \n", + "4 2 5.64330 7.947368 1180.736842 \n", + "5 1 5.52555 38.187500 978.875000 \n", + "... ... ... ... ... \n", + "1450 1 1.12116 3.896996 1.496423 \n", + "1451 1 1.17116 4.777251 1.793839 \n", + "1452 1 1.17587 3.419152 3.312402 \n", + "1453 1 1.01972 0.688222 2.129330 \n", + "1454 1 0.95542 0.936021 0.531989 \n", "\n", - " employment_density density_index is_cbd \n", - "zone_id \n", - "1 1707.375000 2.870167 False \n", - "2 1631.374751 5.178722 False \n", - "3 736.891913 72.547987 False \n", - "4 1180.736842 7.894233 False \n", - "5 978.875000 36.753679 False \n", - "... ... ... ... \n", - "186 9.411765 5.762347 False \n", - "187 6.412698 4.159890 False \n", - "188 23.820106 3.413233 False \n", - "189 2.897436 2.723836 False \n", - "190 24.047619 11.768501 False \n", + " density_index is_cbd \n", + "zone_id \n", + "1 2.870167 False \n", + "2 5.178722 False \n", + "3 72.547987 False \n", + "4 7.894233 False \n", + "5 36.753679 False \n", + "... ... ... \n", + "1450 1.081235 False \n", + "1451 1.304140 False \n", + "1452 1.682465 False \n", + "1453 0.520115 False \n", + "1454 0.339203 False \n", "\n", - "[190 rows x 28 columns]" + "[1454 rows x 28 columns]" ] }, "execution_count": 8, @@ -1541,7 +1600,7 @@ " 1\n", " util_no_attractions\n", " no attractions\n", - " @size_terms.get(df.dest_taz, df.purpose) == 0\n", + " @size_terms.get(df.dest_taz, df.purpose) == 0 ...\n", " coef_UNAVAILABLE\n", " coef_UNAVAILABLE\n", " coef_UNAVAILABLE\n", @@ -1784,7 +1843,7 @@ "\n", " Expression \\\n", "0 @np.log1p(size_terms.get(df.dest_taz, df.purpo... \n", - "1 @size_terms.get(df.dest_taz, df.purpose) == 0 \n", + "1 @size_terms.get(df.dest_taz, df.purpose) == 0 ... \n", "2 @(~df.is_joint & ~df.outbound) * (_od_DIST + _... \n", "3 @(~df.is_joint & df.outbound) * (_od_DIST + _d... \n", "4 @df.is_joint * (_od_DIST + _dp_DIST) \n", @@ -2112,13 +2171,6 @@ "execution_count": 11, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n" - ] - }, { "data": { "text/html": [ @@ -2134,7 +2186,7 @@ { "data": { "text/html": [ - "

Best LL = -12569.486099970745

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Best LL = -78919.86749443343

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" -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -2.099140\n", " \n", " \n", " escort_TOTHH\n", " -6.907755\n", " -6.907755\n", + " -6.907755\n", + " -6.907755\n", + " -6.907755\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -6.907755\n", " \n", " \n", " othdiscr_HEREMPN\n", - " -6.000000\n", + " -4.394168\n", + " -4.394168\n", " -1.301953\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " othdiscr_HSENROLL\n", - " -6.000000\n", + " -3.310820\n", + " -3.310820\n", " -2.322788\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " othdiscr_OTHEMPN\n", - " -4.741924\n", + " -2.825965\n", + " -2.825965\n", " -1.801810\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -4.741924\n", " \n", " \n", " othdiscr_RETEMPN\n", - " -0.420810\n", + " -2.884521\n", + " -2.884521\n", " -1.551169\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -0.420810\n", " \n", " \n", " othdiscr_TOTHH\n", " -1.378326\n", " -1.378326\n", + " -1.378326\n", + " -1.378326\n", + " -1.378326\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -1.378326\n", " \n", " \n", " othmaint_HEREMPN\n", - " -6.000000\n", + " -1.693356\n", + " -1.693356\n", " -0.657780\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " othmaint_RETEMPN\n", - " -4.468097\n", + " -0.351270\n", + " -0.351270\n", " -0.731888\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -4.468097\n", " \n", " \n", " othmaint_TOTHH\n", " -6.907755\n", " -6.907755\n", + " -6.907755\n", + " -6.907755\n", + " -6.907755\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -6.907755\n", " \n", " \n", " shopping_RETEMPN\n", " -6.000000\n", + " -6.000000\n", " -0.001001\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " shopping_TOTHH\n", " -6.907755\n", " -6.907755\n", + " -6.907755\n", + " -6.907755\n", + " -6.907755\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -6.907755\n", " \n", " \n", " social_HEREMPN\n", - " -6.000000\n", + " -1.516222\n", + " -1.516222\n", " -0.738145\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " social_RETEMPN\n", - " -3.463457\n", + " -0.098839\n", + " -0.098839\n", " -0.652005\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -3.463457\n", " \n", " \n", " social_TOTHH\n", " -6.907755\n", " -6.907755\n", + " -6.907755\n", + " -6.907755\n", + " -6.907755\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -6.907755\n", " \n", " \n", " univ_COLLFTE\n", " -6.000000\n", + " -6.000000\n", " -0.524249\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " univ_COLLPTE\n", " -6.000000\n", + " -6.000000\n", " -0.896488\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " univ_TOTHH\n", " -6.907755\n", " -6.907755\n", + " -6.907755\n", + " -6.907755\n", + " -6.907755\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " -6.907755\n", " \n", " \n", " work_AGREMPN\n", - " 1.145159\n", + " 0.122431\n", + " 0.122431\n", " 0.000000\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " 1.145159\n", " \n", " \n", " work_FPSEMPN\n", " -6.000000\n", + " -6.000000\n", " 0.000000\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " work_HEREMPN\n", - " -4.551520\n", + " -1.959508\n", + " -1.959508\n", " 0.000000\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -4.551520\n", " \n", " \n", " work_MWTEMPN\n", - " -6.000000\n", + " -5.322959\n", + " -5.322959\n", " 0.000000\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -6.000000\n", " \n", " \n", " work_OTHEMPN\n", - " -5.205310\n", + " -2.512682\n", + " -2.512682\n", " 0.000000\n", + " -6.000000\n", + " 6.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 0\n", - " \n", - " -5.205310\n", " \n", " \n", " work_RETEMPN\n", " 0.000000\n", " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " 0.0\n", - " -6.0\n", - " 6.0\n", " 1\n", - " \n", - " 0.000000\n", " \n", " \n", "\n", "" ], "text/plain": [ - " value initvalue nullvalue minimum \\\n", - "coef_UNAVAILABLE -999.000000 -999.000000 0.0 NaN \n", - "coef_distance_joint -0.376392 -0.123800 0.0 NaN \n", - "coef_mode_choice_logsum 0.163028 1.821000 0.0 NaN \n", - "coef_one 1.000000 1.000000 0.0 NaN \n", - "coef_prox_dest_outbound_work -0.359504 -0.260000 0.0 NaN \n", - "coef_prox_home_inbound_work -0.174104 -0.150000 0.0 NaN \n", - "coef_prox_home_outbound_work -0.522711 -0.380000 0.0 NaN \n", - "coef_util_distance_atwork -0.122335 -0.122335 0.0 NaN \n", - "coef_util_distance_eatout -0.366193 -0.102900 0.0 NaN \n", - "coef_util_distance_escort -0.337785 -0.149100 0.0 NaN \n", - "coef_util_distance_othdiscr -0.408787 -0.126172 0.0 NaN \n", - "coef_util_distance_othmaint -0.257971 -0.096200 0.0 NaN \n", - "coef_util_distance_school -0.105600 -0.105600 0.0 NaN \n", - "coef_util_distance_shopping -0.390483 -0.119200 0.0 NaN \n", - "coef_util_distance_social -0.338764 -0.132900 0.0 NaN \n", - "coef_util_distance_univ -0.186380 -0.061300 0.0 NaN \n", - "coef_util_distance_work_inbound -0.094761 0.147813 0.0 NaN \n", - "coef_util_distance_work_outbound -0.300511 -0.049726 0.0 NaN \n", - "eatout_HEREMPN -4.274182 -1.354796 0.0 -6.0 \n", - "eatout_RETEMPN -0.298406 -0.298406 0.0 -6.0 \n", - "escort_AGE0519 -1.513508 -0.767871 0.0 -6.0 \n", - "escort_HEREMPN -6.000000 -1.937942 0.0 -6.0 \n", - "escort_HSENROLL -3.172185 -1.795767 0.0 -6.0 \n", - "escort_RETEMPN -2.099140 -1.491655 0.0 -6.0 \n", - "escort_TOTHH -6.907755 -6.907755 0.0 -6.0 \n", - "othdiscr_HEREMPN -6.000000 -1.301953 0.0 -6.0 \n", - "othdiscr_HSENROLL -6.000000 -2.322788 0.0 -6.0 \n", - "othdiscr_OTHEMPN -4.741924 -1.801810 0.0 -6.0 \n", - "othdiscr_RETEMPN -0.420810 -1.551169 0.0 -6.0 \n", - "othdiscr_TOTHH -1.378326 -1.378326 0.0 -6.0 \n", - "othmaint_HEREMPN -6.000000 -0.657780 0.0 -6.0 \n", - "othmaint_RETEMPN -4.468097 -0.731888 0.0 -6.0 \n", - "othmaint_TOTHH -6.907755 -6.907755 0.0 -6.0 \n", - "shopping_RETEMPN -6.000000 -0.001001 0.0 -6.0 \n", - "shopping_TOTHH -6.907755 -6.907755 0.0 -6.0 \n", - "social_HEREMPN -6.000000 -0.738145 0.0 -6.0 \n", - "social_RETEMPN -3.463457 -0.652005 0.0 -6.0 \n", - "social_TOTHH -6.907755 -6.907755 0.0 -6.0 \n", - "univ_COLLFTE -6.000000 -0.524249 0.0 -6.0 \n", - "univ_COLLPTE -6.000000 -0.896488 0.0 -6.0 \n", - "univ_TOTHH -6.907755 -6.907755 0.0 -6.0 \n", - "work_AGREMPN 1.145159 0.000000 0.0 -6.0 \n", - "work_FPSEMPN -6.000000 0.000000 0.0 -6.0 \n", - "work_HEREMPN -4.551520 0.000000 0.0 -6.0 \n", - "work_MWTEMPN -6.000000 0.000000 0.0 -6.0 \n", - "work_OTHEMPN -5.205310 0.000000 0.0 -6.0 \n", - "work_RETEMPN 0.000000 0.000000 0.0 -6.0 \n", + " value best initvalue \\\n", + "param_name \n", + "coef_UNAVAILABLE -999.000000 -999.000000 -999.000000 \n", + "coef_distance_joint -0.222590 -0.222590 -0.123800 \n", + "coef_mode_choice_logsum 0.908189 0.908189 1.821000 \n", + "coef_one 1.000000 1.000000 1.000000 \n", + "coef_prox_dest_outbound_work -0.278949 -0.278949 -0.260000 \n", + "coef_prox_home_inbound_work -0.121975 -0.121975 -0.150000 \n", + "coef_prox_home_outbound_work -0.419012 -0.419012 -0.380000 \n", + "coef_util_distance_atwork -0.122335 -0.122335 -0.122335 \n", + "coef_util_distance_eatout -0.219723 -0.219723 -0.102900 \n", + "coef_util_distance_escort -0.235858 -0.235858 -0.149100 \n", + "coef_util_distance_othdiscr -0.241573 -0.241573 -0.126172 \n", + "coef_util_distance_othmaint -0.177610 -0.177610 -0.096200 \n", + "coef_util_distance_school -0.105600 -0.105600 -0.105600 \n", + "coef_util_distance_shopping -0.227090 -0.227090 -0.119200 \n", + "coef_util_distance_social -0.227558 -0.227558 -0.132900 \n", + "coef_util_distance_univ -0.139388 -0.139388 -0.061300 \n", + "coef_util_distance_work_inbound 0.089849 0.089849 0.147813 \n", + "coef_util_distance_work_outbound -0.138174 -0.138174 -0.049726 \n", + "eatout_HEREMPN -2.550718 -2.550718 -1.354796 \n", + "eatout_RETEMPN -0.298406 -0.298406 -0.298406 \n", + "escort_AGE0519 -0.039579 -0.039579 -0.767871 \n", + "escort_HEREMPN -2.848681 -2.848681 -1.937942 \n", + "escort_HSENROLL -2.260284 -2.260284 -1.795768 \n", + "escort_RETEMPN -0.886457 -0.886457 -1.491655 \n", + "escort_TOTHH -6.907755 -6.907755 -6.907755 \n", + "othdiscr_HEREMPN -4.394168 -4.394168 -1.301953 \n", + "othdiscr_HSENROLL -3.310820 -3.310820 -2.322788 \n", + "othdiscr_OTHEMPN -2.825965 -2.825965 -1.801810 \n", + "othdiscr_RETEMPN -2.884521 -2.884521 -1.551169 \n", + "othdiscr_TOTHH -1.378326 -1.378326 -1.378326 \n", + "othmaint_HEREMPN -1.693356 -1.693356 -0.657780 \n", + "othmaint_RETEMPN -0.351270 -0.351270 -0.731888 \n", + "othmaint_TOTHH -6.907755 -6.907755 -6.907755 \n", + "shopping_RETEMPN -6.000000 -6.000000 -0.001001 \n", + "shopping_TOTHH -6.907755 -6.907755 -6.907755 \n", + "social_HEREMPN -1.516222 -1.516222 -0.738145 \n", + "social_RETEMPN -0.098839 -0.098839 -0.652005 \n", + "social_TOTHH -6.907755 -6.907755 -6.907755 \n", + "univ_COLLFTE -6.000000 -6.000000 -0.524249 \n", + "univ_COLLPTE -6.000000 -6.000000 -0.896488 \n", + "univ_TOTHH -6.907755 -6.907755 -6.907755 \n", + "work_AGREMPN 0.122431 0.122431 0.000000 \n", + "work_FPSEMPN -6.000000 -6.000000 0.000000 \n", + "work_HEREMPN -1.959508 -1.959508 0.000000 \n", + "work_MWTEMPN -5.322959 -5.322959 0.000000 \n", + "work_OTHEMPN -2.512682 -2.512682 0.000000 \n", + "work_RETEMPN 0.000000 0.000000 0.000000 \n", "\n", - " maximum holdfast note best \n", - "coef_UNAVAILABLE NaN 1 -999.000000 \n", - "coef_distance_joint NaN 0 -0.376392 \n", - "coef_mode_choice_logsum NaN 0 0.163028 \n", - "coef_one NaN 1 1.000000 \n", - "coef_prox_dest_outbound_work NaN 0 -0.359504 \n", - "coef_prox_home_inbound_work NaN 0 -0.174104 \n", - "coef_prox_home_outbound_work NaN 0 -0.522711 \n", - "coef_util_distance_atwork NaN 0 -0.122335 \n", - "coef_util_distance_eatout NaN 0 -0.366193 \n", - "coef_util_distance_escort NaN 0 -0.337785 \n", - "coef_util_distance_othdiscr NaN 0 -0.408787 \n", - "coef_util_distance_othmaint NaN 0 -0.257971 \n", - "coef_util_distance_school NaN 0 -0.105600 \n", - "coef_util_distance_shopping NaN 0 -0.390483 \n", - "coef_util_distance_social NaN 0 -0.338764 \n", - "coef_util_distance_univ NaN 0 -0.186380 \n", - "coef_util_distance_work_inbound NaN 0 -0.094761 \n", - "coef_util_distance_work_outbound NaN 0 -0.300511 \n", - "eatout_HEREMPN 6.0 0 -4.274182 \n", - "eatout_RETEMPN 6.0 1 -0.298406 \n", - "escort_AGE0519 6.0 0 -1.513508 \n", - "escort_HEREMPN 6.0 0 -6.000000 \n", - "escort_HSENROLL 6.0 0 -3.172185 \n", - "escort_RETEMPN 6.0 0 -2.099140 \n", - "escort_TOTHH 6.0 1 -6.907755 \n", - "othdiscr_HEREMPN 6.0 0 -6.000000 \n", - "othdiscr_HSENROLL 6.0 0 -6.000000 \n", - "othdiscr_OTHEMPN 6.0 0 -4.741924 \n", - "othdiscr_RETEMPN 6.0 0 -0.420810 \n", - "othdiscr_TOTHH 6.0 1 -1.378326 \n", - "othmaint_HEREMPN 6.0 0 -6.000000 \n", - "othmaint_RETEMPN 6.0 0 -4.468097 \n", - "othmaint_TOTHH 6.0 1 -6.907755 \n", - "shopping_RETEMPN 6.0 0 -6.000000 \n", - "shopping_TOTHH 6.0 1 -6.907755 \n", - "social_HEREMPN 6.0 0 -6.000000 \n", - "social_RETEMPN 6.0 0 -3.463457 \n", - "social_TOTHH 6.0 1 -6.907755 \n", - "univ_COLLFTE 6.0 0 -6.000000 \n", - "univ_COLLPTE 6.0 0 -6.000000 \n", - "univ_TOTHH 6.0 1 -6.907755 \n", - "work_AGREMPN 6.0 0 1.145159 \n", - "work_FPSEMPN 6.0 0 -6.000000 \n", - "work_HEREMPN 6.0 0 -4.551520 \n", - "work_MWTEMPN 6.0 0 -6.000000 \n", - "work_OTHEMPN 6.0 0 -5.205310 \n", - "work_RETEMPN 6.0 1 0.000000 " + " minimum maximum nullvalue holdfast \n", + "param_name \n", + "coef_UNAVAILABLE -999.000000 -999.000000 0.0 1 \n", + "coef_distance_joint -25.000000 25.000000 0.0 0 \n", + "coef_mode_choice_logsum -25.000000 25.000000 0.0 0 \n", + "coef_one 1.000000 1.000000 0.0 1 \n", + "coef_prox_dest_outbound_work -25.000000 25.000000 0.0 0 \n", + "coef_prox_home_inbound_work -25.000000 25.000000 0.0 0 \n", + "coef_prox_home_outbound_work -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_atwork -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_eatout -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_escort -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_othdiscr -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_othmaint -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_school -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_shopping -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_social -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_univ -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_work_inbound -25.000000 25.000000 0.0 0 \n", + "coef_util_distance_work_outbound -25.000000 25.000000 0.0 0 \n", + "eatout_HEREMPN -6.000000 6.000000 0.0 0 \n", + "eatout_RETEMPN -0.298406 -0.298406 0.0 1 \n", + "escort_AGE0519 -6.000000 6.000000 0.0 0 \n", + "escort_HEREMPN -6.000000 6.000000 0.0 0 \n", + "escort_HSENROLL -6.000000 6.000000 0.0 0 \n", + "escort_RETEMPN -6.000000 6.000000 0.0 0 \n", + "escort_TOTHH -6.907755 -6.907755 0.0 1 \n", + "othdiscr_HEREMPN -6.000000 6.000000 0.0 0 \n", + "othdiscr_HSENROLL -6.000000 6.000000 0.0 0 \n", + "othdiscr_OTHEMPN -6.000000 6.000000 0.0 0 \n", + "othdiscr_RETEMPN -6.000000 6.000000 0.0 0 \n", + "othdiscr_TOTHH -1.378326 -1.378326 0.0 1 \n", + "othmaint_HEREMPN -6.000000 6.000000 0.0 0 \n", + "othmaint_RETEMPN -6.000000 6.000000 0.0 0 \n", + "othmaint_TOTHH -6.907755 -6.907755 0.0 1 \n", + "shopping_RETEMPN -6.000000 6.000000 0.0 0 \n", + "shopping_TOTHH -6.907755 -6.907755 0.0 1 \n", + "social_HEREMPN -6.000000 6.000000 0.0 0 \n", + "social_RETEMPN -6.000000 6.000000 0.0 0 \n", + "social_TOTHH -6.907755 -6.907755 0.0 1 \n", + "univ_COLLFTE -6.000000 6.000000 0.0 0 \n", + "univ_COLLPTE -6.000000 6.000000 0.0 0 \n", + "univ_TOTHH -6.907755 -6.907755 0.0 1 \n", + "work_AGREMPN -6.000000 6.000000 0.0 0 \n", + "work_FPSEMPN -6.000000 6.000000 0.0 0 \n", + "work_HEREMPN -6.000000 6.000000 0.0 0 \n", + "work_MWTEMPN -6.000000 6.000000 0.0 0 \n", + "work_OTHEMPN -6.000000 6.000000 0.0 0 \n", + "work_RETEMPN 0.000000 0.000000 0.0 1 " ] }, "metadata": {}, @@ -2803,12 +2819,8 @@ "name": "stderr", "output_type": "stream", "text": [ - ":1: PossibleOverspecification: WARNING: Model is possibly over-specified (hessian is nearly singular).\n", - " model.estimate(method='SLSQP', options={'maxiter':1000})\n", - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/larch/larch/linalg/__init__.py:18: UserWarning: minimum eig 8.29804005517378e-15 in general_inverse\n", - " warnings.warn(f\"minimum eig {min_eig} in general_inverse\")\n", - ":1: RuntimeWarning: invalid value encountered in sqrt\n", - " model.estimate(method='SLSQP', options={'maxiter':1000})\n" + "/Users/jpn/Git/est-mode/larch/src/larch/model/jaxmodel.py:1156: PossibleOverspecification: Model is possibly over-specified (hessian is nearly singular).\n", + " self.calculate_parameter_covariance()\n" ] }, { @@ -2828,11 +2840,11 @@ " \n", " \n", " coef_distance_joint\n", - " -0.376392\n", + " -0.222590\n", " \n", " \n", " coef_mode_choice_logsum\n", - " 0.163028\n", + " 0.908189\n", " \n", " \n", " coef_one\n", @@ -2840,15 +2852,15 @@ " \n", " \n", " coef_prox_dest_outbound_work\n", - " -0.359504\n", + " -0.278949\n", " \n", " \n", " coef_prox_home_inbound_work\n", - " -0.174104\n", + " -0.121975\n", " \n", " \n", " coef_prox_home_outbound_work\n", - " -0.522711\n", + " -0.419012\n", " \n", " \n", " coef_util_distance_atwork\n", @@ -2856,19 +2868,19 @@ " \n", " \n", " coef_util_distance_eatout\n", - " -0.366193\n", + " -0.219723\n", " \n", " \n", " coef_util_distance_escort\n", - " -0.337785\n", + " -0.235858\n", " \n", " \n", " coef_util_distance_othdiscr\n", - " -0.408787\n", + " -0.241573\n", " \n", " \n", " coef_util_distance_othmaint\n", - " -0.257971\n", + " -0.177610\n", " \n", " \n", " coef_util_distance_school\n", @@ -2876,27 +2888,27 @@ " \n", " \n", " coef_util_distance_shopping\n", - " -0.390483\n", + " -0.227090\n", " \n", " \n", " coef_util_distance_social\n", - " -0.338764\n", + " -0.227558\n", " \n", " \n", " coef_util_distance_univ\n", - " -0.186380\n", + " -0.139388\n", " \n", " \n", " coef_util_distance_work_inbound\n", - " -0.094761\n", + " 0.089849\n", " \n", " \n", " coef_util_distance_work_outbound\n", - " -0.300511\n", + " -0.138174\n", " \n", " \n", " eatout_HEREMPN\n", - " -4.274182\n", + " -2.550718\n", " \n", " \n", " eatout_RETEMPN\n", @@ -2904,39 +2916,39 @@ " \n", " \n", " escort_AGE0519\n", - " -1.513508\n", + " -0.039579\n", " \n", " \n", " escort_HEREMPN\n", - " -6.000000\n", + " -2.848681\n", " \n", " \n", " escort_HSENROLL\n", - " -3.172185\n", + " -2.260284\n", " \n", " \n", " escort_RETEMPN\n", - " -2.099140\n", + " -0.886457\n", " \n", " \n", " escort_TOTHH\n", - " -6.000000\n", + " -6.907755\n", " \n", " \n", " othdiscr_HEREMPN\n", - " -6.000000\n", + " -4.394168\n", " \n", " \n", " othdiscr_HSENROLL\n", - " -6.000000\n", + " -3.310820\n", " \n", " \n", " othdiscr_OTHEMPN\n", - " -4.741924\n", + " -2.825965\n", " \n", " \n", " othdiscr_RETEMPN\n", - " -0.420810\n", + " -2.884521\n", " \n", " \n", " othdiscr_TOTHH\n", @@ -2944,15 +2956,15 @@ " \n", " \n", " othmaint_HEREMPN\n", - " -6.000000\n", + " -1.693356\n", " \n", " \n", " othmaint_RETEMPN\n", - " -4.468097\n", + " -0.351270\n", " \n", " \n", " othmaint_TOTHH\n", - " -6.000000\n", + " -6.907755\n", " \n", " \n", " shopping_RETEMPN\n", @@ -2960,19 +2972,19 @@ " \n", " \n", " shopping_TOTHH\n", - " -6.000000\n", + " -6.907755\n", " \n", " \n", " social_HEREMPN\n", - " -6.000000\n", + " -1.516222\n", " \n", " \n", " social_RETEMPN\n", - " -3.463457\n", + " -0.098839\n", " \n", " \n", " social_TOTHH\n", - " -6.000000\n", + " -6.907755\n", " \n", " \n", " univ_COLLFTE\n", @@ -2984,11 +2996,11 @@ " \n", " \n", " univ_TOTHH\n", - " -6.000000\n", + " -6.907755\n", " \n", " \n", " work_AGREMPN\n", - " 1.145159\n", + " 0.122431\n", " \n", " \n", " work_FPSEMPN\n", @@ -2996,22 +3008,22 @@ " \n", " \n", " work_HEREMPN\n", - " -4.551520\n", + " -1.959508\n", " \n", " \n", " work_MWTEMPN\n", - " -6.000000\n", + " -5.322959\n", " \n", " \n", " work_OTHEMPN\n", - " -5.205310\n", + " -2.512682\n", " \n", " \n", " work_RETEMPN\n", " 0.000000\n", " \n", " \n", - "loglike-12569.486099970745d_loglike\n", + "
logloss2.543504818049292d_logloss\n", " \n", " \n", " \n", @@ -3025,11 +3037,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3037,15 +3049,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3053,19 +3065,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3073,27 +3085,27 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3101,19 +3113,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3121,19 +3133,19 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3141,11 +3153,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3153,7 +3165,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3161,11 +3173,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3173,11 +3185,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3185,140 +3197,140 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - "
coef_distance_joint-0.0015450.000054
coef_mode_choice_logsum-0.0371690.000028
coef_one
coef_prox_dest_outbound_work-0.004856-0.000016
coef_prox_home_inbound_work-0.0006900.000044
coef_prox_home_outbound_work0.006258-0.000010
coef_util_distance_atwork
coef_util_distance_eatout0.0009010.000017
coef_util_distance_escort0.0016000.000004
coef_util_distance_othdiscr-0.002904-0.000030
coef_util_distance_othmaint0.002059-0.000009
coef_util_distance_school
coef_util_distance_shopping-0.0016370.000006
coef_util_distance_social-0.000562-0.000076
coef_util_distance_univ-0.0014910.000026
coef_util_distance_work_inbound0.001402-0.000026
coef_util_distance_work_outbound0.0099840.000069
eatout_HEREMPN0.000060-0.000049
eatout_RETEMPN
escort_AGE0519-0.000103-0.000144
escort_HEREMPN-0.2823510.000048
escort_HSENROLL-0.0001000.000044
escort_RETEMPN0.0002190.000042
escort_TOTHH
othdiscr_HEREMPN-0.0837150.000056
othdiscr_HSENROLL-0.013300-0.000088
othdiscr_OTHEMPN-0.0001250.000216
othdiscr_RETEMPN-0.000008-0.000059
othdiscr_TOTHH
othmaint_HEREMPN-14.917882-0.000220
othmaint_RETEMPN0.000013-0.000006
othmaint_TOTHH
shopping_RETEMPN-6.303186-0.005801
shopping_TOTHH
social_HEREMPN-2.2981350.000007
social_RETEMPN-0.000206-0.000072
social_TOTHH
univ_COLLFTE-12.165359-0.003131
univ_COLLPTE-12.781555-0.002441
univ_TOTHH
work_AGREMPN0.000453-0.000051
work_FPSEMPN-0.905637-0.000190
work_HEREMPN0.0002220.000081
work_MWTEMPN-0.021745-0.000196
work_OTHEMPN-0.000419-0.000045
work_RETEMPN0.000000
nit87nfev147njev87status0message'Optimization terminated successfully'successTrueelapsed_time0:00:21.469689method'SLSQP'n_cases2490iteration_number87logloss5.04798638553042" + "nit87nfev92njev87status0message'Optimization terminated successfully'successTrueelapsed_time0:00:19.360953method'SLSQP'n_cases31028iteration_number87loglike-78919.86749443343" ], "text/plain": [ "┣ x: coef_UNAVAILABLE -999.000000\n", - "┃ coef_distance_joint -0.376392\n", - "┃ coef_mode_choice_logsum 0.163028\n", + "┃ coef_distance_joint -0.222590\n", + "┃ coef_mode_choice_logsum 0.908189\n", "┃ coef_one 1.000000\n", - "┃ coef_prox_dest_outbound_work -0.359504\n", - "┃ coef_prox_home_inbound_work -0.174104\n", - "┃ coef_prox_home_outbound_work -0.522711\n", + "┃ coef_prox_dest_outbound_work -0.278949\n", + "┃ coef_prox_home_inbound_work -0.121975\n", + "┃ coef_prox_home_outbound_work -0.419012\n", "┃ coef_util_distance_atwork -0.122335\n", - "┃ coef_util_distance_eatout -0.366193\n", - "┃ coef_util_distance_escort -0.337785\n", - "┃ coef_util_distance_othdiscr -0.408787\n", - "┃ coef_util_distance_othmaint -0.257971\n", + "┃ coef_util_distance_eatout -0.219723\n", + "┃ coef_util_distance_escort -0.235858\n", + "┃ coef_util_distance_othdiscr -0.241573\n", + "┃ coef_util_distance_othmaint -0.177610\n", "┃ coef_util_distance_school -0.105600\n", - "┃ coef_util_distance_shopping -0.390483\n", - "┃ coef_util_distance_social -0.338764\n", - "┃ coef_util_distance_univ -0.186380\n", - "┃ coef_util_distance_work_inbound -0.094761\n", - "┃ coef_util_distance_work_outbound -0.300511\n", - "┃ eatout_HEREMPN -4.274182\n", + "┃ coef_util_distance_shopping -0.227090\n", + "┃ coef_util_distance_social -0.227558\n", + "┃ coef_util_distance_univ -0.139388\n", + "┃ coef_util_distance_work_inbound 0.089849\n", + "┃ coef_util_distance_work_outbound -0.138174\n", + "┃ eatout_HEREMPN -2.550718\n", "┃ eatout_RETEMPN -0.298406\n", - "┃ escort_AGE0519 -1.513508\n", - "┃ escort_HEREMPN -6.000000\n", - "┃ escort_HSENROLL -3.172185\n", - "┃ escort_RETEMPN -2.099140\n", - "┃ escort_TOTHH -6.000000\n", - "┃ othdiscr_HEREMPN -6.000000\n", - "┃ othdiscr_HSENROLL -6.000000\n", - "┃ othdiscr_OTHEMPN -4.741924\n", - "┃ othdiscr_RETEMPN -0.420810\n", + "┃ escort_AGE0519 -0.039579\n", + "┃ escort_HEREMPN -2.848681\n", + "┃ escort_HSENROLL -2.260284\n", + "┃ escort_RETEMPN -0.886457\n", + "┃ escort_TOTHH -6.907755\n", + "┃ othdiscr_HEREMPN -4.394168\n", + "┃ othdiscr_HSENROLL -3.310820\n", + "┃ othdiscr_OTHEMPN -2.825965\n", + "┃ othdiscr_RETEMPN -2.884521\n", "┃ othdiscr_TOTHH -1.378326\n", - "┃ othmaint_HEREMPN -6.000000\n", - "┃ othmaint_RETEMPN -4.468097\n", - "┃ othmaint_TOTHH -6.000000\n", + "┃ othmaint_HEREMPN -1.693356\n", + "┃ othmaint_RETEMPN -0.351270\n", + "┃ othmaint_TOTHH -6.907755\n", "┃ shopping_RETEMPN -6.000000\n", - "┃ shopping_TOTHH -6.000000\n", - "┃ social_HEREMPN -6.000000\n", - "┃ social_RETEMPN -3.463457\n", - "┃ social_TOTHH -6.000000\n", + "┃ shopping_TOTHH -6.907755\n", + "┃ social_HEREMPN -1.516222\n", + "┃ social_RETEMPN -0.098839\n", + "┃ social_TOTHH -6.907755\n", "┃ univ_COLLFTE -6.000000\n", "┃ univ_COLLPTE -6.000000\n", - "┃ univ_TOTHH -6.000000\n", - "┃ work_AGREMPN 1.145159\n", + "┃ univ_TOTHH -6.907755\n", + "┃ work_AGREMPN 0.122431\n", "┃ work_FPSEMPN -6.000000\n", - "┃ work_HEREMPN -4.551520\n", - "┃ work_MWTEMPN -6.000000\n", - "┃ work_OTHEMPN -5.205310\n", + "┃ work_HEREMPN -1.959508\n", + "┃ work_MWTEMPN -5.322959\n", + "┃ work_OTHEMPN -2.512682\n", "┃ work_RETEMPN 0.000000\n", "┃ dtype: float64\n", - "┣ loglike: -12569.486099970745\n", - "┣ d_loglike: coef_UNAVAILABLE 0.000000\n", - "┃ coef_distance_joint -0.001545\n", - "┃ coef_mode_choice_logsum -0.037169\n", - "┃ coef_one 0.000000\n", - "┃ coef_prox_dest_outbound_work -0.004856\n", - "┃ coef_prox_home_inbound_work -0.000690\n", - "┃ coef_prox_home_outbound_work 0.006258\n", - "┃ coef_util_distance_atwork 0.000000\n", - "┃ coef_util_distance_eatout 0.000901\n", - "┃ coef_util_distance_escort 0.001600\n", - "┃ coef_util_distance_othdiscr -0.002904\n", - "┃ coef_util_distance_othmaint 0.002059\n", - "┃ coef_util_distance_school 0.000000\n", - "┃ coef_util_distance_shopping -0.001637\n", - "┃ coef_util_distance_social -0.000562\n", - "┃ coef_util_distance_univ -0.001491\n", - "┃ coef_util_distance_work_inbound 0.001402\n", - "┃ coef_util_distance_work_outbound 0.009984\n", - "┃ eatout_HEREMPN 0.000060\n", - "┃ eatout_RETEMPN 0.000000\n", - "┃ escort_AGE0519 -0.000103\n", - "┃ escort_HEREMPN -0.282351\n", - "┃ escort_HSENROLL -0.000100\n", - "┃ escort_RETEMPN 0.000219\n", - "┃ escort_TOTHH 0.000000\n", - "┃ othdiscr_HEREMPN -0.083715\n", - "┃ othdiscr_HSENROLL -0.013300\n", - "┃ othdiscr_OTHEMPN -0.000125\n", - "┃ othdiscr_RETEMPN -0.000008\n", - "┃ othdiscr_TOTHH 0.000000\n", - "┃ othmaint_HEREMPN -14.917882\n", - "┃ othmaint_RETEMPN 0.000013\n", - "┃ othmaint_TOTHH 0.000000\n", - "┃ shopping_RETEMPN -6.303186\n", - "┃ shopping_TOTHH 0.000000\n", - "┃ social_HEREMPN -2.298135\n", - "┃ social_RETEMPN -0.000206\n", - "┃ social_TOTHH 0.000000\n", - "┃ univ_COLLFTE -12.165359\n", - "┃ univ_COLLPTE -12.781555\n", - "┃ univ_TOTHH 0.000000\n", - "┃ work_AGREMPN 0.000453\n", - "┃ work_FPSEMPN -0.905637\n", - "┃ work_HEREMPN 0.000222\n", - "┃ work_MWTEMPN -0.021745\n", - "┃ work_OTHEMPN -0.000419\n", - "┃ work_RETEMPN 0.000000\n", + "┣ logloss: 2.543504818049292\n", + "┣ d_logloss: coef_UNAVAILABLE 0.000000\n", + "┃ coef_distance_joint 0.000054\n", + "┃ coef_mode_choice_logsum 0.000028\n", + "┃ coef_one 0.000000\n", + "┃ coef_prox_dest_outbound_work -0.000016\n", + "┃ coef_prox_home_inbound_work 0.000044\n", + "┃ coef_prox_home_outbound_work -0.000010\n", + "┃ coef_util_distance_atwork 0.000000\n", + "┃ coef_util_distance_eatout 0.000017\n", + "┃ coef_util_distance_escort 0.000004\n", + "┃ coef_util_distance_othdiscr -0.000030\n", + "┃ coef_util_distance_othmaint -0.000009\n", + "┃ coef_util_distance_school 0.000000\n", + "┃ coef_util_distance_shopping 0.000006\n", + "┃ coef_util_distance_social -0.000076\n", + "┃ coef_util_distance_univ 0.000026\n", + "┃ coef_util_distance_work_inbound -0.000026\n", + "┃ coef_util_distance_work_outbound 0.000069\n", + "┃ eatout_HEREMPN -0.000049\n", + "┃ eatout_RETEMPN 0.000000\n", + "┃ escort_AGE0519 -0.000144\n", + "┃ escort_HEREMPN 0.000048\n", + "┃ escort_HSENROLL 0.000044\n", + "┃ escort_RETEMPN 0.000042\n", + "┃ escort_TOTHH 0.000000\n", + "┃ othdiscr_HEREMPN 0.000056\n", + "┃ othdiscr_HSENROLL -0.000088\n", + "┃ othdiscr_OTHEMPN 0.000216\n", + "┃ othdiscr_RETEMPN -0.000059\n", + "┃ othdiscr_TOTHH 0.000000\n", + "┃ othmaint_HEREMPN -0.000220\n", + "┃ othmaint_RETEMPN -0.000006\n", + "┃ othmaint_TOTHH 0.000000\n", + "┃ shopping_RETEMPN -0.005801\n", + "┃ shopping_TOTHH 0.000000\n", + "┃ social_HEREMPN 0.000007\n", + "┃ social_RETEMPN -0.000072\n", + "┃ social_TOTHH 0.000000\n", + "┃ univ_COLLFTE -0.003131\n", + "┃ univ_COLLPTE -0.002441\n", + "┃ univ_TOTHH 0.000000\n", + "┃ work_AGREMPN -0.000051\n", + "┃ work_FPSEMPN -0.000190\n", + "┃ work_HEREMPN 0.000081\n", + "┃ work_MWTEMPN -0.000196\n", + "┃ work_OTHEMPN -0.000045\n", + "┃ work_RETEMPN 0.000000\n", "┃ dtype: float64\n", "┣ nit: 87\n", - "┣ nfev: 147\n", + "┣ nfev: 92\n", "┣ njev: 87\n", "┣ status: 0\n", "┣ message: 'Optimization terminated successfully'\n", "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=21, microseconds=469689)\n", + "┣ elapsed_time: datetime.timedelta(seconds=19, microseconds=360953)\n", "┣ method: 'SLSQP'\n", - "┣ n_cases: 2490\n", + "┣ n_cases: 31028\n", "┣ iteration_number: 87\n", - "┣ logloss: 5.04798638553042" + "┣ loglike: -78919.86749443343" ] }, "execution_count": 11, @@ -3345,490 +3357,469 @@ { "data": { "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Std Err t Stat Signif Like Ratio Null Value Constrained
coef_UNAVAILABLE-999. NA NA NA 0.00fixed value
coef_distance_joint-0.376 0.0762-4.94*** NA 0.00
coef_mode_choice_logsum 0.163 0.00797 20.46*** NA 0.00
coef_one 1.00 NA NA NA 0.00fixed value
coef_prox_dest_outbound_work-0.360 441.-0.00 NA 0.00
coef_prox_home_inbound_work-0.174 0.0368-4.73*** NA 0.00
coef_prox_home_outbound_work-0.523 441.-0.00 NA 0.00
coef_util_distance_atwork-0.122 2.43e-06-BIG*** NA 0.00
coef_util_distance_eatout-0.366 0.0630-5.81*** NA 0.00
coef_util_distance_escort-0.338 0.0329-10.28*** NA 0.00
coef_util_distance_othdiscr-0.409 0.0322-12.71*** NA 0.00
coef_util_distance_othmaint-0.258 0.0368-7.02*** NA 0.00
coef_util_distance_school-0.106 4.08e-06-BIG*** NA 0.00
coef_util_distance_shopping-0.390 0.0251-15.56*** NA 0.00
coef_util_distance_social-0.339 0.0631-5.36*** NA 0.00
coef_util_distance_univ-0.186 0.0428-4.35*** NA 0.00
coef_util_distance_work_inbound-0.0948 441.-0.00 NA 0.00
coef_util_distance_work_outbound-0.301 0.0272-11.05*** NA 0.00
eatout_HEREMPN-4.27 1.02-4.19*** NA 0.00
eatout_RETEMPN-0.298 NA NA NA 0.00fixed value
escort_AGE0519-1.51 2.88-0.53 NA 0.00
escort_HEREMPN-6.00 NA NA[***] 93.05 0.00escort_HEREMPN ≥ -6.0
escort_HSENROLL-3.17 2.87-1.10 NA 0.00
escort_RETEMPN-2.10 3.12-0.67 NA 0.00
escort_TOTHH-6.91 NA NA NA 0.00fixed value
othdiscr_HEREMPN-6.00 NA NA[***] 63.28 0.00othdiscr_HEREMPN ≥ -6.0
othdiscr_HSENROLL-6.00 NA NA[***] 23.13 0.00othdiscr_HSENROLL ≥ -6.0
othdiscr_OTHEMPN-4.74 2.07-2.29* NA 0.00
othdiscr_RETEMPN-0.421 0.383-1.10 NA 0.00
othdiscr_TOTHH-1.38 NA NA NA 0.00fixed value
othmaint_HEREMPN-6.00 NA NA[***] 93.87 0.00othmaint_HEREMPN ≥ -6.0
othmaint_RETEMPN-4.47 0.487-9.18*** NA 0.00
othmaint_TOTHH-6.91 NA NA NA 0.00fixed value
shopping_RETEMPN-6.00 NA NA[***] 107.89 0.00shopping_RETEMPN ≥ -6.0
shopping_TOTHH-6.91 NA NA NA 0.00fixed value
social_HEREMPN-6.00 NA NA[***] 33.82 0.00social_HEREMPN ≥ -6.0
social_RETEMPN-3.46 0.666-5.20*** NA 0.00
social_TOTHH-6.91 NA NA NA 0.00fixed value
univ_COLLFTE-6.00 NA NA[***] 379.06 0.00univ_COLLFTE ≥ -6.0
univ_COLLPTE-6.00 NA NA[***] 390.32 0.00univ_COLLPTE ≥ -6.0
univ_TOTHH-6.91 NA NA NA 0.00fixed value
work_AGREMPN 1.15 0.433 2.65** NA 0.00
work_FPSEMPN-6.00 NA NA[***] 647.25 0.00work_FPSEMPN ≥ -6.0
work_HEREMPN-4.55 0.535-8.51*** NA 0.00
work_MWTEMPN-6.00 NA NA[***] 106.49 0.00work_MWTEMPN ≥ -6.0
work_OTHEMPN-5.21 1.18-4.42*** NA 0.00
work_RETEMPN 0.00 NA NA NA 0.00fixed value
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 ValueStd Errt StatSignifNull ValueConstrained
Parameter      
coef_UNAVAILABLE-999. 0.00 NA 0.00fixed value
coef_distance_joint-0.223 0.0134-16.56*** 0.00
coef_mode_choice_logsum 0.908 0.0111 82.17*** 0.00
coef_one 1.00 0.00 NA 0.00fixed value
coef_prox_dest_outbound_work-0.279 158.-0.00 0.00
coef_prox_home_inbound_work-0.122 0.00393-31.03*** 0.00
coef_prox_home_outbound_work-0.419 158.-0.00 0.00
coef_util_distance_atwork-0.122 NA NA 0.00
coef_util_distance_eatout-0.220 0.0130-16.94*** 0.00
coef_util_distance_escort-0.236 0.00671-35.15*** 0.00
coef_util_distance_othdiscr-0.242 0.00636-37.96*** 0.00
coef_util_distance_othmaint-0.178 0.00584-30.41*** 0.00
coef_util_distance_school-0.106 NA NA 0.00
coef_util_distance_shopping-0.227 0.00490-46.30*** 0.00
coef_util_distance_social-0.228 0.0116-19.56*** 0.00
coef_util_distance_univ-0.139 0.00887-15.71*** 0.00
coef_util_distance_work_inbound 0.0898 158. 0.00 0.00
coef_util_distance_work_outbound-0.138 0.00378-36.55*** 0.00
eatout_HEREMPN-2.55 0.279-9.16*** 0.00
eatout_RETEMPN-0.298 0.00 NA 0.00fixed value
escort_AGE0519-0.0396 NA NA 0.00
escort_HEREMPN-2.85 NA NA 0.00
escort_HSENROLL-2.26 NA NA 0.00
escort_RETEMPN-0.886 NA NA 0.00
escort_TOTHH-6.91 0.00 NA 0.00fixed value
othdiscr_HEREMPN-4.39 0.449-9.78*** 0.00
othdiscr_HSENROLL-3.31 0.341-9.70*** 0.00
othdiscr_OTHEMPN-2.83 0.181-15.63*** 0.00
othdiscr_RETEMPN-2.88 0.379-7.60*** 0.00
othdiscr_TOTHH-1.38 0.00 NA 0.00fixed value
othmaint_HEREMPN-1.69 NA NA 0.00
othmaint_RETEMPN-0.351 NA NA 0.00
othmaint_TOTHH-6.91 0.00 NA 0.00fixed value
shopping_RETEMPN-6.00 0.00 NA 0.00shopping_RETEMPN ≥ -6.0
shopping_TOTHH-6.91 0.00 NA 0.00fixed value
social_HEREMPN-1.52 NA NA 0.00
social_RETEMPN-0.0988 NA NA 0.00
social_TOTHH-6.91 0.00 NA 0.00fixed value
univ_COLLFTE-6.00 0.00 NA 0.00univ_COLLFTE ≥ -6.0
univ_COLLPTE-6.00 0.00 NA 0.00univ_COLLPTE ≥ -6.0
univ_TOTHH-6.91 0.00 NA 0.00fixed value
work_AGREMPN 0.122 0.169 0.73 0.00
work_FPSEMPN-6.00 5.27e-09-BIG*** 0.00work_FPSEMPN ≥ -6.0
work_HEREMPN-1.96 0.0705-27.78*** 0.00
work_MWTEMPN-5.32 0.384-13.86*** 0.00
work_OTHEMPN-2.51 0.0972-25.86*** 0.00
work_RETEMPN 0.00 0.00 NA 0.00fixed value
\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 12, @@ -4157,12 +4148,12 @@ " work\n", " trip\n", " 0.000000\n", - " 0.240157\n", - " 0.000595\n", - " 0.002534\n", - " 0.001318\n", - " 0.754800\n", - " 0.000595\n", + " 0.423805\n", + " 0.001051\n", + " 0.059726\n", + " 0.034350\n", + " 0.479002\n", + " 0.002067\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4172,15 +4163,15 @@ " 15\n", " escort\n", " trip\n", - " 0.002577\n", - " 0.315809\n", + " 0.000651\n", + " 0.268207\n", " 0.000000\n", - " 0.006387\n", + " 0.037695\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", - " 0.567232\n", - " 0.107996\n", + " 0.625554\n", + " 0.067893\n", " 0.000000\n", " 0.000000\n", " \n", @@ -4205,9 +4196,9 @@ " eatout\n", " trip\n", " 0.000000\n", - " 0.981581\n", + " 0.904850\n", " 0.000000\n", - " 0.018419\n", + " 0.095150\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4220,10 +4211,10 @@ " 18\n", " othmaint\n", " trip\n", - " 0.066899\n", - " 0.767274\n", + " 0.001125\n", + " 0.791941\n", " 0.000000\n", - " 0.165826\n", + " 0.206934\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4236,10 +4227,10 @@ " 19\n", " social\n", " trip\n", - " 0.028736\n", - " 0.900036\n", + " 0.000888\n", + " 0.804213\n", " 0.000000\n", - " 0.071228\n", + " 0.194899\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4252,15 +4243,15 @@ " 20\n", " othdiscr\n", " trip\n", - " 0.273261\n", - " 0.711905\n", + " 0.605815\n", + " 0.134341\n", " 0.000000\n", - " 0.002688\n", - " 0.009458\n", + " 0.029688\n", + " 0.142442\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", - " 0.002688\n", + " 0.087714\n", " 0.000000\n", " 0.000000\n", " \n", @@ -4300,13 +4291,13 @@ "11 social non_mandatory 0.000000 0.522000 0.000000 0.478000 \n", "12 othdiscr non_mandatory 0.252252 0.212212 0.000000 0.272272 \n", "13 atwork atwork 0.000000 0.742000 0.000000 0.258000 \n", - "14 work trip 0.000000 0.240157 0.000595 0.002534 \n", - "15 escort trip 0.002577 0.315809 0.000000 0.006387 \n", + "14 work trip 0.000000 0.423805 0.001051 0.059726 \n", + "15 escort trip 0.000651 0.268207 0.000000 0.037695 \n", "16 shopping trip 0.287459 0.712541 0.000000 0.000000 \n", - "17 eatout trip 0.000000 0.981581 0.000000 0.018419 \n", - "18 othmaint trip 0.066899 0.767274 0.000000 0.165826 \n", - "19 social trip 0.028736 0.900036 0.000000 0.071228 \n", - "20 othdiscr trip 0.273261 0.711905 0.000000 0.002688 \n", + "17 eatout trip 0.000000 0.904850 0.000000 0.095150 \n", + "18 othmaint trip 0.001125 0.791941 0.000000 0.206934 \n", + "19 social trip 0.000888 0.804213 0.000000 0.194899 \n", + "20 othdiscr trip 0.605815 0.134341 0.000000 0.029688 \n", "21 univ trip 0.167856 0.000000 0.000000 0.000000 \n", "\n", " OTHEMPN AGREMPN MWTEMPN AGE0519 HSENROLL COLLFTE COLLPTE \n", @@ -4324,13 +4315,13 @@ "11 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "12 0.165165 0.000000 0.000000 0.000000 0.098098 0.000000 0.000000 \n", "13 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "14 0.001318 0.754800 0.000595 0.000000 0.000000 0.000000 0.000000 \n", - "15 0.000000 0.000000 0.000000 0.567232 0.107996 0.000000 0.000000 \n", + "14 0.034350 0.479002 0.002067 0.000000 0.000000 0.000000 0.000000 \n", + "15 0.000000 0.000000 0.000000 0.625554 0.067893 0.000000 0.000000 \n", "16 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "17 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "18 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "19 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "20 0.009458 0.000000 0.000000 0.000000 0.002688 0.000000 0.000000 \n", + "20 0.142442 0.000000 0.000000 0.000000 0.087714 0.000000 0.000000 \n", "21 0.000000 0.000000 0.000000 0.000000 0.000000 0.416072 0.416072 " ] }, @@ -4424,31 +4415,31 @@ " \n", " 2\n", " coef_mode_choice_logsum\n", - " 0.163028\n", + " 0.908189\n", " F\n", " \n", " \n", " 3\n", " coef_distance_joint\n", - " -0.376392\n", + " -0.222590\n", " F\n", " \n", " \n", " 4\n", " coef_util_distance_work_outbound\n", - " -0.300511\n", + " -0.138174\n", " F\n", " \n", " \n", " 5\n", " coef_util_distance_work_inbound\n", - " -0.094761\n", + " 0.089849\n", " F\n", " \n", " \n", " 6\n", " coef_util_distance_univ\n", - " -0.186380\n", + " -0.139388\n", " F\n", " \n", " \n", @@ -4460,37 +4451,37 @@ " \n", " 8\n", " coef_util_distance_escort\n", - " -0.337785\n", + " -0.235858\n", " F\n", " \n", " \n", " 9\n", " coef_util_distance_shopping\n", - " -0.390483\n", + " -0.227090\n", " F\n", " \n", " \n", " 10\n", " coef_util_distance_eatout\n", - " -0.366193\n", + " -0.219723\n", " F\n", " \n", " \n", " 11\n", " coef_util_distance_othmaint\n", - " -0.257971\n", + " -0.177610\n", " F\n", " \n", " \n", " 12\n", " coef_util_distance_social\n", - " -0.338764\n", + " -0.227558\n", " F\n", " \n", " \n", " 13\n", " coef_util_distance_othdiscr\n", - " -0.408787\n", + " -0.241573\n", " F\n", " \n", " \n", @@ -4502,19 +4493,19 @@ " \n", " 15\n", " coef_prox_home_outbound_work\n", - " -0.522711\n", + " -0.419012\n", " F\n", " \n", " \n", " 16\n", " coef_prox_home_inbound_work\n", - " -0.174104\n", + " -0.121975\n", " F\n", " \n", " \n", " 17\n", " coef_prox_dest_outbound_work\n", - " -0.359504\n", + " -0.278949\n", " F\n", " \n", " \n", @@ -4525,22 +4516,22 @@ " coefficient_name value constrain\n", "0 coef_UNAVAILABLE -999.000000 T\n", "1 coef_one 1.000000 T\n", - "2 coef_mode_choice_logsum 0.163028 F\n", - "3 coef_distance_joint -0.376392 F\n", - "4 coef_util_distance_work_outbound -0.300511 F\n", - "5 coef_util_distance_work_inbound -0.094761 F\n", - "6 coef_util_distance_univ -0.186380 F\n", + "2 coef_mode_choice_logsum 0.908189 F\n", + "3 coef_distance_joint -0.222590 F\n", + "4 coef_util_distance_work_outbound -0.138174 F\n", + "5 coef_util_distance_work_inbound 0.089849 F\n", + "6 coef_util_distance_univ -0.139388 F\n", "7 coef_util_distance_school -0.105600 F\n", - "8 coef_util_distance_escort -0.337785 F\n", - "9 coef_util_distance_shopping -0.390483 F\n", - "10 coef_util_distance_eatout -0.366193 F\n", - "11 coef_util_distance_othmaint -0.257971 F\n", - "12 coef_util_distance_social -0.338764 F\n", - "13 coef_util_distance_othdiscr -0.408787 F\n", + "8 coef_util_distance_escort -0.235858 F\n", + "9 coef_util_distance_shopping -0.227090 F\n", + "10 coef_util_distance_eatout -0.219723 F\n", + "11 coef_util_distance_othmaint -0.177610 F\n", + "12 coef_util_distance_social -0.227558 F\n", + "13 coef_util_distance_othdiscr -0.241573 F\n", "14 coef_util_distance_atwork -0.122335 F\n", - "15 coef_prox_home_outbound_work -0.522711 F\n", - "16 coef_prox_home_inbound_work -0.174104 F\n", - "17 coef_prox_dest_outbound_work -0.359504 F" + "15 coef_prox_home_outbound_work -0.419012 F\n", + "16 coef_prox_home_inbound_work -0.121975 F\n", + "17 coef_prox_dest_outbound_work -0.278949 F" ] }, "execution_count": 17, @@ -4839,12 +4830,12 @@ " work\n", " trip\n", " 0.000000\n", - " 0.240157\n", - " 0.000595\n", - " 0.002534\n", - " 0.001318\n", - " 0.754800\n", - " 0.000595\n", + " 0.423805\n", + " 0.001051\n", + " 0.059726\n", + " 0.034350\n", + " 0.479002\n", + " 0.002067\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4855,15 +4846,15 @@ " 15\n", " escort\n", " trip\n", - " 0.002577\n", - " 0.315809\n", + " 0.000651\n", + " 0.268207\n", " 0.000000\n", - " 0.006387\n", + " 0.037695\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", - " 0.567232\n", - " 0.107996\n", + " 0.625554\n", + " 0.067893\n", " 0.000000\n", " 0.000000\n", " \n", @@ -4890,9 +4881,9 @@ " eatout\n", " trip\n", " 0.000000\n", - " 0.981581\n", + " 0.904850\n", " 0.000000\n", - " 0.018419\n", + " 0.095150\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4906,10 +4897,10 @@ " 18\n", " othmaint\n", " trip\n", - " 0.066899\n", - " 0.767274\n", + " 0.001125\n", + " 0.791941\n", " 0.000000\n", - " 0.165826\n", + " 0.206934\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4923,10 +4914,10 @@ " 19\n", " social\n", " trip\n", - " 0.028736\n", - " 0.900036\n", + " 0.000888\n", + " 0.804213\n", " 0.000000\n", - " 0.071228\n", + " 0.194899\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -4940,15 +4931,15 @@ " 20\n", " othdiscr\n", " trip\n", - " 0.273261\n", - " 0.711905\n", + " 0.605815\n", + " 0.134341\n", " 0.000000\n", - " 0.002688\n", - " 0.009458\n", + " 0.029688\n", + " 0.142442\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", - " 0.002688\n", + " 0.087714\n", " 0.000000\n", " 0.000000\n", " \n", @@ -4989,13 +4980,13 @@ "11 11 social non_mandatory 0.000000 0.522000 0.000000 \n", "12 12 othdiscr non_mandatory 0.252252 0.212212 0.000000 \n", "13 13 atwork atwork 0.000000 0.742000 0.000000 \n", - "14 14 work trip 0.000000 0.240157 0.000595 \n", - "15 15 escort trip 0.002577 0.315809 0.000000 \n", + "14 14 work trip 0.000000 0.423805 0.001051 \n", + "15 15 escort trip 0.000651 0.268207 0.000000 \n", "16 16 shopping trip 0.287459 0.712541 0.000000 \n", - "17 17 eatout trip 0.000000 0.981581 0.000000 \n", - "18 18 othmaint trip 0.066899 0.767274 0.000000 \n", - "19 19 social trip 0.028736 0.900036 0.000000 \n", - "20 20 othdiscr trip 0.273261 0.711905 0.000000 \n", + "17 17 eatout trip 0.000000 0.904850 0.000000 \n", + "18 18 othmaint trip 0.001125 0.791941 0.000000 \n", + "19 19 social trip 0.000888 0.804213 0.000000 \n", + "20 20 othdiscr trip 0.605815 0.134341 0.000000 \n", "21 21 univ trip 0.167856 0.000000 0.000000 \n", "\n", " HEREMPN OTHEMPN AGREMPN MWTEMPN AGE0519 HSENROLL COLLFTE \\\n", @@ -5013,13 +5004,13 @@ "11 0.478000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "12 0.272272 0.165165 0.000000 0.000000 0.000000 0.098098 0.000000 \n", "13 0.258000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "14 0.002534 0.001318 0.754800 0.000595 0.000000 0.000000 0.000000 \n", - "15 0.006387 0.000000 0.000000 0.000000 0.567232 0.107996 0.000000 \n", + "14 0.059726 0.034350 0.479002 0.002067 0.000000 0.000000 0.000000 \n", + "15 0.037695 0.000000 0.000000 0.000000 0.625554 0.067893 0.000000 \n", "16 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "17 0.018419 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "18 0.165826 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "19 0.071228 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "20 0.002688 0.009458 0.000000 0.000000 0.000000 0.002688 0.000000 \n", + "17 0.095150 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "18 0.206934 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "19 0.194899 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "20 0.029688 0.142442 0.000000 0.000000 0.000000 0.087714 0.000000 \n", "21 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.416072 \n", "\n", " COLLPTE \n", @@ -5064,7 +5055,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -5078,7 +5069,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/23_trip_mode_choice.ipynb b/activitysim/examples/example_estimation/notebooks/23_trip_mode_choice.ipynb index acf84e2740..a38eb92392 100644 --- a/activitysim/examples/example_estimation/notebooks/23_trip_mode_choice.ipynb +++ b/activitysim/examples/example_estimation/notebooks/23_trip_mode_choice.ipynb @@ -34,27 +34,74 @@ "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "JAX not found. Some functionality will be unavailable.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'larch': '6.0.32',\n", + " 'sharrow': '2.13.0',\n", + " 'numpy': '1.26.4',\n", + " 'pandas': '1.5.3',\n", + " 'xarray': '2024.3.0',\n", + " 'numba': '0.60.0'}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "import os\n", - "import larch # !conda install larch -c conda-forge # for estimation\n", - "import pandas as pd" + "import larch as lx\n", + "import pandas as pd\n", + "\n", + "lx.versions()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We'll work in our `test` directory, where ActivitySim has saved the estimation data bundles." + "For this demo, we will assume that you have already run ActivitySim in estimation\n", + "mode, and saved the required estimation data bundles (EDB's) to disk. See\n", + "the [first notebook](./01_estimation_mode.ipynb) for details. The following module\n", + "will run a script to set everything up if the example data is not already available." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EDB directory already populated.\n" + ] + }, + { + "data": { + "text/plain": [ + "PosixPath('test-estimation-data/activitysim-prototype-mtc-extended')" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "os.chdir('test')" + "from est_mode_setup import prepare\n", + "\n", + "prepare()" ] }, { @@ -70,11 +117,13 @@ "metadata": {}, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "/Users/jeffnewman/OneDrive - Cambridge Systematics/Git/activitysim/activitysim/estimation/larch/mode_choice.py:126: DtypeWarning: Columns (411) have mixed types.Specify dtype option on import or set low_memory=False.\n", - " return mode_choice_model(\n" + "loading from output-est-mode/estimation_data_bundle/trip_mode_choice/trip_mode_choice_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/trip_mode_choice/trip_mode_choice_coefficients_template.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/trip_mode_choice/trip_mode_choice_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/trip_mode_choice/trip_mode_choice_values_combined.parquet\n" ] } ], @@ -82,7 +131,11 @@ "modelname = \"trip_mode_choice\"\n", "\n", "from activitysim.estimation.larch import component_model\n", - "model, data = component_model(modelname, return_data=True)" + "model, data = component_model(\n", + " modelname,\n", + " edb_directory=f\"output-est-mode/estimation_data_bundle/{modelname}/\",\n", + " return_data=True,\n", + ")" ] }, { @@ -685,15 +738,15 @@ " util_DRIVEALONEFREE_In_vehicle_time\n", " util_DRIVEALONEFREE_Terminal_time\n", " ...\n", - " drive_lrf_available_inbound\n", - " drive_express_available_outbound\n", - " drive_express_available_inbound\n", " drive_heavyrail_available_outbound\n", " drive_heavyrail_available_inbound\n", " drive_commuter_available_outbound\n", " drive_commuter_available_inbound\n", " walk_ferry_available\n", " drive_ferry_available\n", + " distance\n", + " distance_walk_od\n", + " distance_bike_od\n", " override_choice_code\n", " \n", " \n", @@ -723,17 +776,17 @@ " \n", " \n", " \n", - " 6812\n", - " 54497\n", + " 1870\n", + " 14961\n", " WALK\n", " WALK\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 2.72\n", - " 7.72508\n", + " 0.0\n", + " 10.52\n", + " 10.63286\n", " ...\n", " False\n", " False\n", @@ -741,23 +794,23 @@ " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", + " 3.78\n", + " 3.78\n", + " 3.78\n", " 7\n", " \n", " \n", - " 6812\n", - " 54501\n", + " 1870\n", + " 14965\n", " WALK\n", " WALK\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 2.76\n", - " 7.72508\n", + " 0.0\n", + " 10.31\n", + " 10.63286\n", " ...\n", " False\n", " False\n", @@ -765,71 +818,71 @@ " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", + " 3.79\n", + " 3.79\n", + " 3.79\n", " 7\n", " \n", " \n", - " 8110\n", - " 64881\n", - " WALK\n", - " WALK\n", + " 20468\n", + " 163745\n", + " WALK_LOC\n", + " WALK_LOC\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 4.43\n", - " 17.09892\n", + " 0.0\n", + " 4.72\n", + " 6.62312\n", " ...\n", + " True\n", " False\n", + " True\n", " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " 7\n", + " 2.07\n", + " 2.07\n", + " 2.07\n", + " 9\n", " \n", " \n", - " 8110\n", - " 64885\n", - " WALK\n", - " WALK\n", + " 20468\n", + " 163749\n", + " WALK_LOC\n", + " TNC_SINGLE\n", " 0.0\n", - " 1.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 4.43\n", - " 17.09892\n", + " 0.0\n", + " 4.72\n", + " 6.62312\n", " ...\n", " False\n", + " True\n", " False\n", + " True\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " False\n", - " 7\n", + " 2.07\n", + " 2.07\n", + " 2.07\n", + " 20\n", " \n", " \n", - " 11013\n", - " 88105\n", - " DRIVEALONEFREE\n", + " 27055\n", + " 216441\n", + " SHARED3FREE\n", " DRIVEALONEFREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 10.53\n", - " 9.08660\n", + " 6.77\n", + " 4.26534\n", " ...\n", " False\n", " False\n", @@ -837,9 +890,9 @@ " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", + " 2.49\n", + " 2.49\n", + " 2.49\n", " 1\n", " \n", " \n", @@ -867,17 +920,17 @@ " ...\n", " \n", " \n", - " 309796968\n", - " 2478375745\n", - " SHARED3FREE\n", - " SHARED3FREE\n", + " 310202384\n", + " 2481619077\n", + " DRIVEALONEFREE\n", + " DRIVEALONEFREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 8.84\n", - " 6.83436\n", + " 2.74\n", + " 1.91196\n", " ...\n", " False\n", " False\n", @@ -885,23 +938,23 @@ " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", - " 5\n", + " 1.66\n", + " 2.55\n", + " 2.55\n", + " 1\n", " \n", " \n", - " 309796968\n", - " 2478375749\n", - " SHARED3FREE\n", - " SHARED3FREE\n", + " 310212634\n", + " 2481701073\n", + " DRIVEALONEFREE\n", + " DRIVEALONEFREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 8.50\n", - " 6.83436\n", + " 6.42\n", + " 2.66128\n", " ...\n", " False\n", " False\n", @@ -909,14 +962,14 @@ " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", - " 5\n", + " 2.57\n", + " 2.57\n", + " 2.57\n", + " 1\n", " \n", " \n", - " 309796969\n", - " 2478375753\n", + " 310212634\n", + " 2481701077\n", " DRIVEALONEFREE\n", " DRIVEALONEFREE\n", " 0.0\n", @@ -924,8 +977,8 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 4.00\n", - " 5.00346\n", + " 6.42\n", + " 2.66128\n", " ...\n", " False\n", " False\n", @@ -933,23 +986,23 @@ " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", + " 2.57\n", + " 2.57\n", + " 2.57\n", " 1\n", " \n", " \n", - " 309796969\n", - " 2478375757\n", - " TNC_SHARED\n", - " TNC_SHARED\n", + " 310220296\n", + " 2481762369\n", + " DRIVEALONEFREE\n", + " DRIVEALONEFREE\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 1.89\n", - " 9.29502\n", + " 6.72\n", + " 4.02884\n", " ...\n", " False\n", " False\n", @@ -957,14 +1010,14 @@ " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", - " 21\n", + " 2.90\n", + " 2.90\n", + " 2.90\n", + " 1\n", " \n", " \n", - " 309796969\n", - " 2478375758\n", + " 310220296\n", + " 2481762373\n", " DRIVEALONEFREE\n", " DRIVEALONEFREE\n", " 0.0\n", @@ -972,8 +1025,8 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 3.73\n", - " 4.29156\n", + " 6.87\n", + " 4.02884\n", " ...\n", " False\n", " False\n", @@ -981,228 +1034,214 @@ " False\n", " False\n", " False\n", - " False\n", - " False\n", - " False\n", + " 2.90\n", + " 2.90\n", + " 2.90\n", " 1\n", " \n", " \n", "\n", - "

14352 rows × 475 columns

\n", + "

176389 rows × 480 columns

\n", "" ], "text/plain": [ " trip_id model_choice override_choice \\\n", "tour_id \n", - "6812 54497 WALK WALK \n", - "6812 54501 WALK WALK \n", - "8110 64881 WALK WALK \n", - "8110 64885 WALK WALK \n", - "11013 88105 DRIVEALONEFREE DRIVEALONEFREE \n", + "1870 14961 WALK WALK \n", + "1870 14965 WALK WALK \n", + "20468 163745 WALK_LOC WALK_LOC \n", + "20468 163749 WALK_LOC TNC_SINGLE \n", + "27055 216441 SHARED3FREE DRIVEALONEFREE \n", "... ... ... ... \n", - "309796968 2478375745 SHARED3FREE SHARED3FREE \n", - "309796968 2478375749 SHARED3FREE SHARED3FREE \n", - "309796969 2478375753 DRIVEALONEFREE DRIVEALONEFREE \n", - "309796969 2478375757 TNC_SHARED TNC_SHARED \n", - "309796969 2478375758 DRIVEALONEFREE DRIVEALONEFREE \n", + "310202384 2481619077 DRIVEALONEFREE DRIVEALONEFREE \n", + "310212634 2481701073 DRIVEALONEFREE DRIVEALONEFREE \n", + "310212634 2481701077 DRIVEALONEFREE DRIVEALONEFREE \n", + "310220296 2481762369 DRIVEALONEFREE DRIVEALONEFREE \n", + "310220296 2481762373 DRIVEALONEFREE DRIVEALONEFREE \n", "\n", " util_DRIVEALONEFREE_Unavailable \\\n", "tour_id \n", - "6812 0.0 \n", - "6812 0.0 \n", - "8110 0.0 \n", - "8110 0.0 \n", - "11013 0.0 \n", + "1870 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", "... ... \n", - "309796968 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_Unavailable_for_zero_auto_households \\\n", "tour_id \n", - "6812 1.0 \n", - "6812 1.0 \n", - "8110 1.0 \n", - "8110 1.0 \n", - "11013 0.0 \n", + "1870 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", "... ... \n", - "309796968 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_Unavailable_for_persons_less_than_16 \\\n", "tour_id \n", - "6812 0.0 \n", - "6812 0.0 \n", - "8110 0.0 \n", - "8110 0.0 \n", - "11013 0.0 \n", + "1870 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", "... ... \n", - "309796968 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_Unavailable_for_joint_tours \\\n", "tour_id \n", - "6812 0.0 \n", - "6812 0.0 \n", - "8110 0.0 \n", - "8110 0.0 \n", - "11013 0.0 \n", + "1870 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", "... ... \n", - "309796968 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_Unavailable_if_didnt_drive_to_work \\\n", "tour_id \n", - "6812 0.0 \n", - "6812 0.0 \n", - "8110 0.0 \n", - "8110 0.0 \n", - "11013 0.0 \n", + "1870 0.0 \n", + "1870 0.0 \n", + "20468 0.0 \n", + "20468 0.0 \n", + "27055 0.0 \n", "... ... \n", - "309796968 0.0 \n", - "309796968 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", - "309796969 0.0 \n", + "310202384 0.0 \n", + "310212634 0.0 \n", + "310212634 0.0 \n", + "310220296 0.0 \n", + "310220296 0.0 \n", "\n", " util_DRIVEALONEFREE_In_vehicle_time \\\n", "tour_id \n", - "6812 2.72 \n", - "6812 2.76 \n", - "8110 4.43 \n", - "8110 4.43 \n", - "11013 10.53 \n", + "1870 10.52 \n", + "1870 10.31 \n", + "20468 4.72 \n", + "20468 4.72 \n", + "27055 6.77 \n", "... ... \n", - "309796968 8.84 \n", - "309796968 8.50 \n", - "309796969 4.00 \n", - "309796969 1.89 \n", - "309796969 3.73 \n", + "310202384 2.74 \n", + "310212634 6.42 \n", + "310212634 6.42 \n", + "310220296 6.72 \n", + "310220296 6.87 \n", "\n", " util_DRIVEALONEFREE_Terminal_time ... \\\n", "tour_id ... \n", - "6812 7.72508 ... \n", - "6812 7.72508 ... \n", - "8110 17.09892 ... \n", - "8110 17.09892 ... \n", - "11013 9.08660 ... \n", + "1870 10.63286 ... \n", + "1870 10.63286 ... \n", + "20468 6.62312 ... \n", + "20468 6.62312 ... \n", + "27055 4.26534 ... \n", "... ... ... \n", - "309796968 6.83436 ... \n", - "309796968 6.83436 ... \n", - "309796969 5.00346 ... \n", - "309796969 9.29502 ... \n", - "309796969 4.29156 ... \n", - "\n", - " drive_lrf_available_inbound drive_express_available_outbound \\\n", - "tour_id \n", - "6812 False False \n", - "6812 False False \n", - "8110 False False \n", - "8110 False False \n", - "11013 False False \n", - "... ... ... \n", - "309796968 False False \n", - "309796968 False False \n", - "309796969 False False \n", - "309796969 False False \n", - "309796969 False False \n", - "\n", - " drive_express_available_inbound \\\n", - "tour_id \n", - "6812 False \n", - "6812 False \n", - "8110 False \n", - "8110 False \n", - "11013 False \n", - "... ... \n", - "309796968 False \n", - "309796968 False \n", - "309796969 False \n", - "309796969 False \n", - "309796969 False \n", + "310202384 1.91196 ... \n", + "310212634 2.66128 ... \n", + "310212634 2.66128 ... \n", + "310220296 4.02884 ... \n", + "310220296 4.02884 ... \n", "\n", " drive_heavyrail_available_outbound \\\n", "tour_id \n", - "6812 False \n", - "6812 False \n", - "8110 False \n", - "8110 False \n", - "11013 False \n", + "1870 False \n", + "1870 False \n", + "20468 True \n", + "20468 False \n", + "27055 False \n", "... ... \n", - "309796968 False \n", - "309796968 False \n", - "309796969 False \n", - "309796969 False \n", - "309796969 False \n", + "310202384 False \n", + "310212634 False \n", + "310212634 False \n", + "310220296 False \n", + "310220296 False \n", "\n", " drive_heavyrail_available_inbound \\\n", "tour_id \n", - "6812 False \n", - "6812 False \n", - "8110 False \n", - "8110 False \n", - "11013 False \n", + "1870 False \n", + "1870 False \n", + "20468 False \n", + "20468 True \n", + "27055 False \n", "... ... \n", - "309796968 False \n", - "309796968 False \n", - "309796969 False \n", - "309796969 False \n", - "309796969 False \n", + "310202384 False \n", + "310212634 False \n", + "310212634 False \n", + "310220296 False \n", + "310220296 False \n", "\n", " drive_commuter_available_outbound \\\n", "tour_id \n", - "6812 False \n", - "6812 False \n", - "8110 False \n", - "8110 False \n", - "11013 False \n", + "1870 False \n", + "1870 False \n", + "20468 True \n", + "20468 False \n", + "27055 False \n", "... ... \n", - "309796968 False \n", - "309796968 False \n", - "309796969 False \n", - "309796969 False \n", - "309796969 False \n", + "310202384 False \n", + "310212634 False \n", + "310212634 False \n", + "310220296 False \n", + "310220296 False \n", "\n", " drive_commuter_available_inbound walk_ferry_available \\\n", "tour_id \n", - "6812 False False \n", - "6812 False False \n", - "8110 False False \n", - "8110 False False \n", - "11013 False False \n", + "1870 False False \n", + "1870 False False \n", + "20468 False False \n", + "20468 True False \n", + "27055 False False \n", "... ... ... \n", - "309796968 False False \n", - "309796968 False False \n", - "309796969 False False \n", - "309796969 False False \n", - "309796969 False False \n", + "310202384 False False \n", + "310212634 False False \n", + "310212634 False False \n", + "310220296 False False \n", + "310220296 False False \n", "\n", - " drive_ferry_available override_choice_code \n", - "tour_id \n", - "6812 False 7 \n", - "6812 False 7 \n", - "8110 False 7 \n", - "8110 False 7 \n", - "11013 False 1 \n", - "... ... ... \n", - "309796968 False 5 \n", - "309796968 False 5 \n", - "309796969 False 1 \n", - "309796969 False 21 \n", - "309796969 False 1 \n", + " drive_ferry_available distance distance_walk_od \\\n", + "tour_id \n", + "1870 False 3.78 3.78 \n", + "1870 False 3.79 3.79 \n", + "20468 False 2.07 2.07 \n", + "20468 False 2.07 2.07 \n", + "27055 False 2.49 2.49 \n", + "... ... ... ... \n", + "310202384 False 1.66 2.55 \n", + "310212634 False 2.57 2.57 \n", + "310212634 False 2.57 2.57 \n", + "310220296 False 2.90 2.90 \n", + "310220296 False 2.90 2.90 \n", + "\n", + " distance_bike_od override_choice_code \n", + "tour_id \n", + "1870 3.78 7 \n", + "1870 3.79 7 \n", + "20468 2.07 9 \n", + "20468 2.07 20 \n", + "27055 2.49 1 \n", + "... ... ... \n", + "310202384 2.55 1 \n", + "310212634 2.57 1 \n", + "310212634 2.57 1 \n", + "310220296 2.90 1 \n", + "310220296 2.90 1 \n", "\n", - "[14352 rows x 475 columns]" + "[176389 rows x 480 columns]" ] }, "execution_count": 6, @@ -1228,41 +1267,10 @@ "execution_count": 7, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "req_data does not request avail_ca or avail_co but it is set and being provided\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (1 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (1 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (1 issues)\n", - "problem: low-variance-data-co (1 issues)\n", - "problem: chosen-but-not-available (2 issues)\n", - "problem: low-variance-data-co (1 issues)\n" - ] - }, { "data": { "text/plain": [ - "-10094.898223413013" + "-94787.94601063678" ] }, "execution_count": 7, @@ -1271,7 +1279,6 @@ } ], "source": [ - "model.load_data()\n", "model.doctor(repair_ch_av='-')\n", "model.loglike()" ] @@ -1284,7 +1291,7 @@ { "data": { "text/html": [ - "

Iteration 110 [Optimization terminated successfully]

" + "

Iteration 304 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1296,7 +1303,7 @@ { "data": { "text/html": [ - "

Best LL = -7541.342641931288

" + "

Best LL = -83882.48668326798

" ], "text/plain": [ "" @@ -1327,70 +1334,74 @@ " \n", " \n", " value\n", + " best\n", " initvalue\n", - " nullvalue\n", " minimum\n", " maximum\n", + " nullvalue\n", " holdfast\n", - " note\n", - " best\n", + " \n", + " \n", + " param_name\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " -999\n", " -999.000000\n", + " -999.000000\n", " -999.0000\n", " -999.0\n", " -999.0\n", - " -999.0\n", + " 0.0\n", " 1\n", - " \n", - " -999.000000\n", " \n", " \n", " 1\n", " 1.000000\n", + " 1.000000\n", " 1.0000\n", " 1.0\n", " 1.0\n", - " 1.0\n", + " 0.0\n", " 1\n", - " \n", - " 1.000000\n", " \n", " \n", " coef_age010_trn\n", - " 0.360551\n", + " 0.131028\n", + " 0.131028\n", " 0.0000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.360551\n", " \n", " \n", " coef_age1619_da\n", - " 0.344530\n", + " 0.432972\n", + " 0.432972\n", " 0.0000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.344530\n", " \n", " \n", " coef_age16p_sr\n", - " -0.151886\n", + " -0.403317\n", + " -0.403317\n", " 0.0000\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.151886\n", " \n", " \n", " ...\n", @@ -1401,114 +1412,106 @@ " ...\n", " ...\n", " ...\n", - " ...\n", " \n", " \n", - " coef_sr3p_ASC_sr3p_othdiscr\n", - " 0.844944\n", - " 0.7398\n", + " coef_walk_transit_ASC_walk_school\n", + " -1.566510\n", + " -1.566510\n", + " -1.1828\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " 0.844944\n", " \n", " \n", - " coef_sr3p_ASC_walk_othdiscr\n", - " -5.841028\n", - " -0.5272\n", + " coef_walk_transit_ASC_walk_shopping\n", + " -1.250219\n", + " -1.250219\n", + " -0.1943\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -5.841028\n", " \n", " \n", - " coef_walk_transit_ASC_sr2_othdiscr\n", - " -1.232224\n", - " -2.7590\n", + " coef_walk_transit_ASC_walk_social\n", + " -0.846190\n", + " -0.846190\n", + " -0.7651\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.232224\n", " \n", " \n", - " coef_walk_transit_ASC_sr3p_othdiscr\n", - " -1.199264\n", - " -2.5126\n", + " coef_walk_transit_ASC_walk_univ\n", + " -1.031100\n", + " -1.031100\n", + " -1.0311\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -1.199264\n", " \n", " \n", - " coef_walk_transit_ASC_walk_othdiscr\n", - " -0.980497\n", - " -0.4997\n", + " coef_walk_transit_ASC_walk_work\n", + " 0.296352\n", + " 0.296352\n", + " 0.4432\n", + " -inf\n", + " inf\n", " 0.0\n", - " NaN\n", - " NaN\n", " 0\n", - " \n", - " -0.980497\n", " \n", " \n", "\n", - "

272 rows × 8 columns

\n", + "

272 rows × 7 columns

\n", "" ], "text/plain": [ - " value initvalue nullvalue \\\n", - "-999 -999.000000 -999.0000 -999.0 \n", - "1 1.000000 1.0000 1.0 \n", - "coef_age010_trn 0.360551 0.0000 0.0 \n", - "coef_age1619_da 0.344530 0.0000 0.0 \n", - "coef_age16p_sr -0.151886 0.0000 0.0 \n", - "... ... ... ... \n", - "coef_sr3p_ASC_sr3p_othdiscr 0.844944 0.7398 0.0 \n", - "coef_sr3p_ASC_walk_othdiscr -5.841028 -0.5272 0.0 \n", - "coef_walk_transit_ASC_sr2_othdiscr -1.232224 -2.7590 0.0 \n", - "coef_walk_transit_ASC_sr3p_othdiscr -1.199264 -2.5126 0.0 \n", - "coef_walk_transit_ASC_walk_othdiscr -0.980497 -0.4997 0.0 \n", + " value best initvalue \\\n", + "param_name \n", + "-999 -999.000000 -999.000000 -999.0000 \n", + "1 1.000000 1.000000 1.0000 \n", + "coef_age010_trn 0.131028 0.131028 0.0000 \n", + "coef_age1619_da 0.432972 0.432972 0.0000 \n", + "coef_age16p_sr -0.403317 -0.403317 0.0000 \n", + "... ... ... ... \n", + "coef_walk_transit_ASC_walk_school -1.566510 -1.566510 -1.1828 \n", + "coef_walk_transit_ASC_walk_shopping -1.250219 -1.250219 -0.1943 \n", + "coef_walk_transit_ASC_walk_social -0.846190 -0.846190 -0.7651 \n", + "coef_walk_transit_ASC_walk_univ -1.031100 -1.031100 -1.0311 \n", + "coef_walk_transit_ASC_walk_work 0.296352 0.296352 0.4432 \n", "\n", - " minimum maximum holdfast note \\\n", - "-999 -999.0 -999.0 1 \n", - "1 1.0 1.0 1 \n", - "coef_age010_trn NaN NaN 0 \n", - "coef_age1619_da NaN NaN 0 \n", - "coef_age16p_sr NaN NaN 0 \n", - "... ... ... ... ... \n", - "coef_sr3p_ASC_sr3p_othdiscr NaN NaN 0 \n", - "coef_sr3p_ASC_walk_othdiscr NaN NaN 0 \n", - "coef_walk_transit_ASC_sr2_othdiscr NaN NaN 0 \n", - "coef_walk_transit_ASC_sr3p_othdiscr NaN NaN 0 \n", - "coef_walk_transit_ASC_walk_othdiscr NaN NaN 0 \n", + " minimum maximum nullvalue holdfast \n", + "param_name \n", + "-999 -999.0 -999.0 0.0 1 \n", + "1 1.0 1.0 0.0 1 \n", + "coef_age010_trn -inf inf 0.0 0 \n", + "coef_age1619_da -inf inf 0.0 0 \n", + "coef_age16p_sr -inf inf 0.0 0 \n", + "... ... ... ... ... \n", + "coef_walk_transit_ASC_walk_school -inf inf 0.0 0 \n", + "coef_walk_transit_ASC_walk_shopping -inf inf 0.0 0 \n", + "coef_walk_transit_ASC_walk_social -inf inf 0.0 0 \n", + "coef_walk_transit_ASC_walk_univ -inf inf 0.0 0 \n", + "coef_walk_transit_ASC_walk_work -inf inf 0.0 0 \n", "\n", - " best \n", - "-999 -999.000000 \n", - "1 1.000000 \n", - "coef_age010_trn 0.360551 \n", - "coef_age1619_da 0.344530 \n", - "coef_age16p_sr -0.151886 \n", - "... ... \n", - "coef_sr3p_ASC_sr3p_othdiscr 0.844944 \n", - "coef_sr3p_ASC_walk_othdiscr -5.841028 \n", - "coef_walk_transit_ASC_sr2_othdiscr -1.232224 \n", - "coef_walk_transit_ASC_sr3p_othdiscr -1.199264 \n", - "coef_walk_transit_ASC_walk_othdiscr -0.980497 \n", - "\n", - "[272 rows x 8 columns]" + "[272 rows x 7 columns]" ] }, "metadata": {}, "output_type": "display_data" }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/jpn/Git/est-mode/larch/src/larch/model/optimization.py:338: UserWarning: SLSQP may not play nicely with unbounded parameters\n", + "if you get poor results, consider setting global bounds with model.set_cap()\n", + " warnings.warn( # infinite bounds # )\n" + ] + }, { "data": { "text/html": [ @@ -1530,173 +1533,461 @@ " \n", " \n", " coef_age010_trn\n", - " 0.360551\n", + " 0.131028\n", " \n", " \n", " coef_age1619_da\n", - " 0.344530\n", + " 0.432972\n", " \n", " \n", " coef_age16p_sr\n", - " -0.151886\n", + " -0.403317\n", " \n", " \n", " coef_bike_ASC_rh\n", " -7.000000\n", " \n", " \n", - " coef_bike_ASC_walk_work\n", - " -2.659172\n", + " coef_bike_ASC_walk_eatout\n", + " -1.688820\n", " \n", " \n", - " coef_drive_transit_ASC_commuter_work\n", - " 0.426505\n", + " coef_bike_ASC_walk_escort\n", + " -13.520300\n", " \n", " \n", - " coef_drive_transit_ASC_express_work\n", - " -0.355400\n", + " coef_bike_ASC_walk_othdiscr\n", + " -1.324400\n", " \n", " \n", - " coef_drive_transit_ASC_ferry_work\n", - " 0.527700\n", + " coef_bike_ASC_walk_othmaint\n", + " -0.712317\n", " \n", " \n", - " coef_drive_transit_ASC_heavyrail_work\n", - " -11.994128\n", + " coef_bike_ASC_walk_school\n", + " -2.411542\n", " \n", " \n", - " coef_drive_transit_ASC_lightrail_work\n", - " -10.300241\n", + " coef_bike_ASC_walk_shopping\n", + " -1.577746\n", " \n", " \n", - " coef_drive_transit_ASC_rh\n", - " -162.171583\n", + " coef_bike_ASC_walk_social\n", + " -13.238401\n", " \n", " \n", - " coef_hhsize1_sr\n", - " -0.890929\n", + " coef_bike_ASC_walk_univ\n", + " -0.339900\n", " \n", " \n", - " coef_hhsize2_sr\n", - " 0.039653\n", + " coef_bike_ASC_walk_work\n", + " -2.059726\n", " \n", " \n", - " coef_ivt_work\n", - " -0.010155\n", + " coef_drive_transit_ASC_commuter_escort\n", + " 0.544200\n", " \n", " \n", - " coef_joint_auto_ASC_rh_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork\n", + " 6.898234\n", " \n", " \n", - " coef_joint_auto_ASC_sr2_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_commuter_univ_school\n", + " 3.472482\n", " \n", " \n", - " coef_joint_auto_ASC_sr3p_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_commuter_work\n", + " 0.928536\n", " \n", " \n", - " coef_joint_auto_ASC_walk_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_express_escort\n", + " 0.754700\n", " \n", " \n", - " coef_joint_bike_ASC_rh_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork\n", + " 0.673466\n", " \n", " \n", - " coef_joint_bike_ASC_walk_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_express_univ_school\n", + " -0.091011\n", " \n", " \n", - " coef_joint_drive_transit_ASC_commuter_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_express_work\n", + " 0.063342\n", " \n", " \n", - " coef_joint_drive_transit_ASC_express_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_ferry_escort\n", + " 0.600500\n", " \n", " \n", - " coef_joint_drive_transit_ASC_ferry_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork\n", + " -1.435555\n", " \n", " \n", - " coef_joint_drive_transit_ASC_heavyrail_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_ferry_univ_school\n", + " 0.935424\n", " \n", " \n", - " coef_joint_drive_transit_ASC_lightrail_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_ferry_work\n", + " 0.556372\n", " \n", " \n", - " coef_joint_drive_transit_ASC_rh_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_heavyrail_escort\n", + " -3.973160\n", " \n", " \n", - " coef_joint_ride_hail_ASC_sr2_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork\n", + " 0.985065\n", " \n", " \n", - " coef_joint_ride_hail_ASC_sr3p_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_heavyrail_univ_school\n", + " 0.729763\n", " \n", " \n", - " coef_joint_ride_hail_ASC_taxi_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_heavyrail_work\n", + " 0.821984\n", " \n", " \n", - " coef_joint_ride_hail_ASC_tnc_shared\n", - " 0.000000\n", + " coef_drive_transit_ASC_lightrail_escort\n", + " 2.308376\n", " \n", " \n", - " coef_joint_ride_hail_ASC_tnc_single_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork\n", + " 0.501609\n", " \n", " \n", - " coef_joint_ride_hail_ASC_walk_transit\n", - " 0.000000\n", + " coef_drive_transit_ASC_lightrail_univ_school\n", + " 3.943847\n", " \n", " \n", - " coef_joint_ride_hail_ASC_walk_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_lightrail_work\n", + " 0.635303\n", " \n", " \n", - " coef_joint_walk_ASC_rh_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_drive_transit_ASC_rh\n", + " -3.908149\n", " \n", " \n", - " coef_joint_walk_transit_ASC_commuter_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_hhsize1_sr\n", + " -0.789606\n", " \n", " \n", - " coef_joint_walk_transit_ASC_express_work_univ_school_escort_atwork\n", - " 0.000000\n", + " coef_hhsize2_sr\n", + " -0.058339\n", + " \n", + " \n", + " coef_ivt_escort_shopping_eatout_othdiscr_atwork\n", + " -0.011979\n", + " \n", + " \n", + " coef_ivt_othmaint_social\n", + " -0.008160\n", + " \n", + " \n", + " coef_ivt_univ_school\n", + " -0.016233\n", + " \n", + " \n", + " coef_ivt_work\n", + " -0.014958\n", + " \n", + " \n", + " coef_joint_auto_ASC_rh_shopping_eatout_othmaint_social_othdiscr\n", + " -7.345956\n", + " \n", + " \n", + " coef_joint_auto_ASC_rh_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_auto_ASC_sr2_eatout_othmaint_social_othdiscr\n", + " 1.280849\n", + " \n", + " \n", + " coef_joint_auto_ASC_sr2_shopping\n", + " 2.351884\n", + " \n", + " \n", + " coef_joint_auto_ASC_sr2_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_auto_ASC_sr3p_eatout_othmaint_social_othdiscr\n", + " 1.246167\n", + " \n", + " \n", + " coef_joint_auto_ASC_sr3p_shopping\n", + " -19.045412\n", + " \n", + " \n", + " coef_joint_auto_ASC_sr3p_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_auto_ASC_walk_eatout_othmaint_social_othdiscr\n", + " -0.098984\n", + " \n", + " \n", + " coef_joint_auto_ASC_walk_shopping\n", + " -23.468800\n", + " \n", + " \n", + " coef_joint_auto_ASC_walk_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_bike_ASC_rh_shopping_eatout_othmaint_social_othdiscr\n", + " -12.305749\n", + " \n", + " \n", + " coef_joint_bike_ASC_rh_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_bike_ASC_walk_eatout\n", + " -15.558800\n", + " \n", + " \n", + " coef_joint_bike_ASC_walk_othdiscr\n", + " -14.444000\n", + " \n", + " \n", + " coef_joint_bike_ASC_walk_othmaint\n", + " -13.519200\n", + " \n", + " \n", + " coef_joint_bike_ASC_walk_shopping\n", + " -7.047600\n", + " \n", + " \n", + " coef_joint_bike_ASC_walk_social\n", + " -26.171400\n", + " \n", + " \n", + " coef_joint_bike_ASC_walk_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr\n", + " 0.512900\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_commuter_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr\n", + " -0.805943\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_express_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr\n", + " 2.029768\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_ferry_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr\n", + " 3.190747\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_heavyrail_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr\n", + " 0.539200\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_lightrail_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr\n", + " 2.050928\n", + " \n", + " \n", + " coef_joint_drive_transit_ASC_rh_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_sr2_shopping_eatout_othmaint_social_othdiscr\n", + " -6.819150\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_sr2_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_sr3p_shopping_eatout_othmaint_social_othdiscr\n", + " -6.822328\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_sr3p_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_taxi_shopping_eatout_othmaint_social_othdiscr\n", + " -7.000000\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_taxi_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_tnc_shared\n", + " -0.345956\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_tnc_single_shopping_eatout_othmaint_social_othdiscr\n", + " -4.733900\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_tnc_single_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_walk_shopping_eatout_othmaint_social_othdiscr\n", + " -7.012565\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_walk_transit\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_ride_hail_ASC_walk_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_walk_ASC_rh_shopping_eatout_othmaint_social_othdiscr\n", + " -3.048765\n", + " \n", + " \n", + " coef_joint_walk_ASC_rh_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr\n", + " 0.512900\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_commuter_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr\n", + " 0.664800\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_express_work_univ_school_escort_atwork\n", + " 0.000000\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr\n", + " 0.646600\n", " \n", " \n", " coef_joint_walk_transit_ASC_ferry_work_univ_school_escort_atwork\n", " 0.000000\n", " \n", " \n", + " coef_joint_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr\n", + " 2.769790\n", + " \n", + " \n", " coef_joint_walk_transit_ASC_heavyrail_work_univ_school_escort_atwork\n", " 0.000000\n", " \n", " \n", + " coef_joint_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr\n", + " 0.727835\n", + " \n", + " \n", " coef_joint_walk_transit_ASC_lightrail_work_univ_school_escort_atwork\n", " 0.000000\n", " \n", " \n", + " coef_joint_walk_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr\n", + " 0.073906\n", + " \n", + " \n", " coef_joint_walk_transit_ASC_rh_work_univ_school_escort_atwork\n", " 0.000000\n", " \n", " \n", + " coef_joint_walk_transit_ASC_sr2_eatout\n", + " -14.913400\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_sr2_othdiscr\n", + " -14.980100\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_sr2_othmaint\n", + " -5.324150\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_sr2_shopping\n", + " -21.576800\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_sr2_social\n", + " -20.502200\n", + " \n", + " \n", " coef_joint_walk_transit_ASC_sr2_work_univ_school_escort_atwork\n", " 0.000000\n", " \n", " \n", + " coef_joint_walk_transit_ASC_sr3p_eatout\n", + " -16.758700\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_sr3p_othdiscr\n", + " -16.735400\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_sr3p_othmaint\n", + " -3.973990\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_sr3p_shopping\n", + " -25.595300\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_sr3p_social\n", + " -34.737800\n", + " \n", + " \n", " coef_joint_walk_transit_ASC_sr3p_work_univ_school_escort_atwork\n", " 0.000000\n", " \n", " \n", + " coef_joint_walk_transit_ASC_walk_eatout\n", + " 3.421757\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_walk_othdiscr\n", + " -1.023876\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_walk_othmaint\n", + " 0.282606\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_walk_shopping\n", + " 0.717138\n", + " \n", + " \n", + " coef_joint_walk_transit_ASC_walk_social\n", + " -2.272422\n", + " \n", + " \n", " coef_joint_walk_transit_ASC_walk_work_univ_school_escort_atwork\n", " 0.000000\n", " \n", @@ -1737,3414 +2028,3144 @@ " 0.500000\n", " \n", " \n", - " coef_ride_hail_ASC_sr2_work\n", - " -24.964153\n", + " coef_ride_hail_ASC_sr2_eatout_social_othdiscr\n", + " -6.474676\n", + " \n", + " \n", + " coef_ride_hail_ASC_sr2_escort_shopping_othmaint\n", + " -3.837659\n", + " \n", + " \n", + " coef_ride_hail_ASC_sr2_school\n", + " -1.923960\n", + " \n", + " \n", + " coef_ride_hail_ASC_sr2_univ\n", + " -4.337200\n", + " \n", + " \n", + " coef_ride_hail_ASC_sr2_work\n", + " -12.531625\n", + " \n", + " \n", + " coef_ride_hail_ASC_sr3p_eatout_social_othdiscr\n", + " -6.907989\n", + " \n", + " \n", + " coef_ride_hail_ASC_sr3p_school\n", + " -8.857391\n", + " \n", + " \n", + " coef_ride_hail_ASC_sr3p_univ\n", + " -4.922000\n", " \n", " \n", " coef_ride_hail_ASC_sr3p_work_escort_shopping_othmaint_atwork\n", - " -29.661854\n", + " -10.063483\n", + " \n", + " \n", + " coef_ride_hail_ASC_taxi_eatout_social_othdiscr\n", + " -2.560139\n", + " \n", + " \n", + " coef_ride_hail_ASC_taxi_escort_shopping_othmaint\n", + " -3.667690\n", + " \n", + " \n", + " coef_ride_hail_ASC_taxi_school\n", + " 0.194629\n", + " \n", + " \n", + " coef_ride_hail_ASC_taxi_univ\n", + " -1.599400\n", " \n", " \n", " coef_ride_hail_ASC_taxi_work\n", - " -2.519566\n", + " -2.416191\n", " \n", " \n", " coef_ride_hail_ASC_tnc_shared\n", - " 23.268241\n", + " 0.940193\n", + " \n", + " \n", + " coef_ride_hail_ASC_tnc_single_eatout_social_othdiscr\n", + " 3.020074\n", + " \n", + " \n", + " coef_ride_hail_ASC_tnc_single_escort_shopping_othmaint\n", + " 2.436588\n", + " \n", + " \n", + " coef_ride_hail_ASC_tnc_single_school\n", + " 2.043069\n", + " \n", + " \n", + " coef_ride_hail_ASC_tnc_single_univ\n", + " 0.108100\n", " \n", " \n", " coef_ride_hail_ASC_tnc_single_work\n", - " 23.984210\n", + " 2.658594\n", + " \n", + " \n", + " coef_ride_hail_ASC_walk_eatout_social_othdiscr\n", + " -1.924015\n", + " \n", + " \n", + " coef_ride_hail_ASC_walk_school\n", + " -0.961041\n", " \n", " \n", " coef_ride_hail_ASC_walk_transit\n", - " 22.114587\n", + " 1.263022\n", + " \n", + " \n", + " coef_ride_hail_ASC_walk_univ_escort_shopping_othmaint\n", + " -3.676198\n", " \n", " \n", " coef_ride_hail_ASC_walk_work\n", - " 21.771188\n", + " 1.329192\n", + " \n", + " \n", + " coef_sov_ASC_rh_escort_shopping_eatout_othmaint_social_othdiscr\n", + " 0.000000\n", + " \n", + " \n", + " coef_sov_ASC_rh_school\n", + " -9.212494\n", + " \n", + " \n", + " coef_sov_ASC_rh_univ\n", + " -6.649000\n", " 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coef_sr2_ASC_sr2_social0.768269coef_walk_transit_ASC_sr2_shopping-9.388409e-06
coef_sr2_ASC_walk_social-2.850657coef_walk_transit_ASC_sr2_social9.230328e-07
coef_sr3p_ASC_sr2_social-0.122347coef_walk_transit_ASC_sr2_univ0.000000e+00
coef_sr3p_ASC_sr3p_social1.210687coef_walk_transit_ASC_sr2_work-1.261236e-04
coef_sr3p_ASC_walk_social-3.080113coef_walk_transit_ASC_sr3p_eatout6.744761e-06
coef_walk_transit_ASC_sr2_social-2.064534coef_walk_transit_ASC_sr3p_escort-2.229624e-07
coef_walk_transit_ASC_sr3p_social-21.630900coef_walk_transit_ASC_sr3p_othdiscr-1.310142e-05
coef_walk_transit_ASC_walk_social-2.314604coef_walk_transit_ASC_sr3p_othmaint-1.028683e-16
coef_bike_ASC_walk_othdiscr-1.397187coef_walk_transit_ASC_sr3p_school1.154167e-04
coef_joint_bike_ASC_walk_othdiscr-14.444000coef_walk_transit_ASC_sr3p_shopping-5.588721e-05
coef_joint_walk_transit_ASC_sr2_othdiscr-14.980100coef_walk_transit_ASC_sr3p_social-1.622526e-16
coef_joint_walk_transit_ASC_sr3p_othdiscr-16.735568coef_walk_transit_ASC_sr3p_univ0.000000e+00
coef_joint_walk_transit_ASC_walk_othdiscr-25.948045coef_walk_transit_ASC_sr3p_work-1.697982e-05
coef_sov_ASC_walk_othdiscr-4.939783coef_walk_transit_ASC_walk_eatout-1.290994e-04
coef_sr2_ASC_sr2_othdiscr0.855704coef_walk_transit_ASC_walk_escort1.459589e-06
coef_sr2_ASC_walk_othdiscr-2.470470coef_walk_transit_ASC_walk_othdiscr-6.642421e-05
coef_sr3p_ASC_sr2_othdiscr-0.417630coef_walk_transit_ASC_walk_othmaint-5.294680e-05
coef_sr3p_ASC_sr3p_othdiscr0.844944coef_walk_transit_ASC_walk_school9.694344e-05
coef_sr3p_ASC_walk_othdiscr-5.841028coef_walk_transit_ASC_walk_shopping4.504021e-05
coef_walk_transit_ASC_sr2_othdiscr-1.232224coef_walk_transit_ASC_walk_social-7.533156e-05
coef_walk_transit_ASC_sr3p_othdiscr-1.199264coef_walk_transit_ASC_walk_univ0.000000e+00
coef_walk_transit_ASC_walk_othdiscr-0.980497coef_walk_transit_ASC_walk_work-1.629846e-04
loglike-7541.342641931288d_loglike\n", + "
nit304nfev317njev304status0message'Optimization terminated successfully'successTrueelapsed_time0:03:32.168906method'SLSQP'n_cases162587iteration_number304loglike-83882.486683268" + ], + "text/plain": [ + "┣ x: -999 -999.000000\n", + "┃ 1 1.000000\n", + "┃ coef_age010_trn 0.131028\n", + "┃ coef_age1619_da 0.432972\n", + "┃ coef_age16p_sr -0.403317\n", + "┃ ... \n", + "┃ coef_walk_transit_ASC_walk_school -1.566510\n", + "┃ coef_walk_transit_ASC_walk_shopping -1.250219\n", + "┃ coef_walk_transit_ASC_walk_social -0.846190\n", + "┃ coef_walk_transit_ASC_walk_univ -1.031100\n", + "┃ coef_walk_transit_ASC_walk_work 0.296352\n", + "┃ Length: 272, dtype: float64\n", + "┣ logloss: 0.5159237004389526\n", + "┣ d_logloss: -999 0.000000\n", + "┃ 1 0.000000\n", + "┃ coef_age010_trn -0.000081\n", + "┃ coef_age1619_da -0.000052\n", + "┃ coef_age16p_sr -0.000041\n", + "┃ ... \n", + "┃ coef_walk_transit_ASC_walk_school 0.000097\n", + "┃ coef_walk_transit_ASC_walk_shopping 0.000045\n", + "┃ coef_walk_transit_ASC_walk_social -0.000075\n", + "┃ coef_walk_transit_ASC_walk_univ 0.000000\n", + "┃ coef_walk_transit_ASC_walk_work -0.000163\n", + "┃ Length: 272, dtype: float64\n", + "┣ nit: 304\n", + "┣ nfev: 317\n", + "┣ njev: 304\n", + "┣ status: 0\n", + "┣ message: 'Optimization terminated successfully'\n", + "┣ success: True\n", + "┣ elapsed_time: datetime.timedelta(seconds=212, microseconds=168906)\n", + "┣ method: 'SLSQP'\n", + "┣ n_cases: 162587\n", + "┣ iteration_number: 304\n", + "┣ loglike: -83882.486683268" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.maximize_loglike(method='SLSQP', options={\"maxiter\": 1000})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Estimated coefficients" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", " \n", - 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0
 ValueNull Value
Parameter  
-9990.000000e+00-999-999. 0.00
10.000000e+001 1.00 0.00
coef_age010_trn6.536294e-06coef_age010_trn 0.131 0.00
coef_age1619_da-2.022165e-05coef_age1619_da 0.433 0.00
coef_age16p_sr-1.531626e-03coef_age16p_sr-0.403 0.00
coef_bike_ASC_rh0.000000e+00coef_bike_ASC_rh-7.00 0.00
coef_bike_ASC_walk_work4.331337e-05coef_bike_ASC_walk_eatout-1.69 0.00
coef_drive_transit_ASC_commuter_work-4.495517e-05coef_bike_ASC_walk_escort-13.5 0.00
coef_drive_transit_ASC_express_work0.000000e+00coef_bike_ASC_walk_othdiscr-1.32 0.00
coef_drive_transit_ASC_ferry_work0.000000e+00coef_bike_ASC_walk_othmaint-0.712 0.00
coef_drive_transit_ASC_heavyrail_work-4.473961e-10coef_bike_ASC_walk_school-2.41 0.00
coef_drive_transit_ASC_lightrail_work-2.507220e-09coef_bike_ASC_walk_shopping-1.58 0.00
coef_drive_transit_ASC_rh-1.718236e-62coef_bike_ASC_walk_social-13.2 0.00
coef_hhsize1_sr4.378810e-05coef_bike_ASC_walk_univ-0.340 0.00
coef_hhsize2_sr-9.408883e-04coef_bike_ASC_walk_work-2.06 0.00
coef_ivt_work5.462510e-02coef_drive_transit_ASC_commuter_escort 0.544 0.00
coef_joint_auto_ASC_rh_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork 6.90 0.00
coef_joint_auto_ASC_sr2_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_commuter_univ_school 3.47 0.00
coef_joint_auto_ASC_sr3p_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_commuter_work 0.929 0.00
coef_joint_auto_ASC_walk_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_express_escort 0.755 0.00
coef_joint_bike_ASC_rh_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork 0.673 0.00
coef_joint_bike_ASC_walk_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_express_univ_school-0.0910 0.00
coef_joint_drive_transit_ASC_commuter_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_express_work 0.0633 0.00
coef_joint_drive_transit_ASC_express_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_ferry_escort 0.601 0.00
coef_joint_drive_transit_ASC_ferry_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork-1.44 0.00
coef_joint_drive_transit_ASC_heavyrail_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_ferry_univ_school 0.935 0.00
coef_joint_drive_transit_ASC_lightrail_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_ferry_work 0.556 0.00
coef_joint_drive_transit_ASC_rh_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_heavyrail_escort-3.97 0.00
coef_joint_ride_hail_ASC_sr2_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork 0.985 0.00
coef_joint_ride_hail_ASC_sr3p_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_heavyrail_univ_school 0.730 0.00
coef_joint_ride_hail_ASC_taxi_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_heavyrail_work 0.822 0.00
coef_joint_ride_hail_ASC_tnc_shared0.000000e+00coef_drive_transit_ASC_lightrail_escort 2.31 0.00
coef_joint_ride_hail_ASC_tnc_single_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork 0.502 0.00
coef_joint_ride_hail_ASC_walk_transit0.000000e+00coef_drive_transit_ASC_lightrail_univ_school 3.94 0.00
coef_joint_ride_hail_ASC_walk_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_lightrail_work 0.635 0.00
coef_joint_walk_ASC_rh_work_univ_school_escort_atwork0.000000e+00coef_drive_transit_ASC_rh-3.91 0.00
coef_joint_walk_transit_ASC_commuter_work_univ_school_escort_atwork0.000000e+00coef_hhsize1_sr-0.790 0.00
coef_joint_walk_transit_ASC_express_work_univ_school_escort_atwork0.000000e+00coef_hhsize2_sr-0.0583 0.00
coef_joint_walk_transit_ASC_ferry_work_univ_school_escort_atwork0.000000e+00coef_ivt_escort_shopping_eatout_othdiscr_atwork-0.0120 0.00
coef_joint_walk_transit_ASC_heavyrail_work_univ_school_escort_atwork0.000000e+00coef_ivt_othmaint_social-0.00816 0.00
coef_joint_walk_transit_ASC_lightrail_work_univ_school_escort_atwork0.000000e+00coef_ivt_univ_school-0.0162 0.00
coef_joint_walk_transit_ASC_rh_work_univ_school_escort_atwork0.000000e+00coef_ivt_work-0.0150 0.00
coef_joint_walk_transit_ASC_sr2_work_univ_school_escort_atwork0.000000e+00coef_joint_auto_ASC_rh_shopping_eatout_othmaint_social_othdiscr-7.35 0.00
coef_joint_walk_transit_ASC_sr3p_work_univ_school_escort_atwork0.000000e+00coef_joint_auto_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_walk_work_univ_school_escort_atwork0.000000e+00coef_joint_auto_ASC_sr2_eatout_othmaint_social_othdiscr 1.28 0.00
coef_nest_AUTO0.000000e+00coef_joint_auto_ASC_sr2_shopping 2.35 0.00
coef_nest_AUTO_DRIVEALONE0.000000e+00coef_joint_auto_ASC_sr2_work_univ_school_escort_atwork 0.00 0.00
coef_nest_AUTO_SHAREDRIDE20.000000e+00coef_joint_auto_ASC_sr3p_eatout_othmaint_social_othdiscr 1.25 0.00
coef_nest_AUTO_SHAREDRIDE30.000000e+00coef_joint_auto_ASC_sr3p_shopping-19.0 0.00
coef_nest_NONMOTORIZED0.000000e+00coef_joint_auto_ASC_sr3p_work_univ_school_escort_atwork 0.00 0.00
coef_nest_RIDEHAIL0.000000e+00coef_joint_auto_ASC_walk_eatout_othmaint_social_othdiscr-0.0990 0.00
coef_nest_TRANSIT0.000000e+00coef_joint_auto_ASC_walk_shopping-23.5 0.00
coef_nest_TRANSIT_DRIVEACCESS0.000000e+00coef_joint_auto_ASC_walk_work_univ_school_escort_atwork 0.00 0.00
coef_nest_TRANSIT_WALKACCESS0.000000e+00coef_joint_bike_ASC_rh_shopping_eatout_othmaint_social_othdiscr-12.3 0.00
coef_ride_hail_ASC_sr2_work-1.076131e-17coef_joint_bike_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_ride_hail_ASC_sr3p_work_escort_shopping_othmaint_atwork-4.912817e-20coef_joint_bike_ASC_walk_eatout-15.6 0.00
coef_ride_hail_ASC_taxi_work-2.445223e-27coef_joint_bike_ASC_walk_othdiscr-14.4 0.00
coef_ride_hail_ASC_tnc_shared9.512800e-04coef_joint_bike_ASC_walk_othmaint-13.5 0.00
coef_ride_hail_ASC_tnc_single_work-5.210129e-04coef_joint_bike_ASC_walk_shopping-7.05 0.00
coef_ride_hail_ASC_walk_transit-1.264748e-04coef_joint_bike_ASC_walk_social-26.2 0.00
coef_ride_hail_ASC_walk_work-1.549984e-05coef_joint_bike_ASC_walk_work_univ_school_escort_atwork 0.00 0.00
coef_sov_ASC_rh_work_atwork0.000000e+00coef_joint_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr 0.513 0.00
coef_sov_ASC_sr2_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_joint_drive_transit_ASC_commuter_work_univ_school_escort_atwork 0.00 0.00
coef_sov_ASC_sr3p_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_joint_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr-0.806 0.00
coef_sov_ASC_walk_work-1.293137e-04coef_joint_drive_transit_ASC_express_work_univ_school_escort_atwork 0.00 0.00
coef_sr2_ASC_rh_work_school_escort_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_joint_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr 2.03 0.00
coef_sr2_ASC_sr2_work-4.657072e-04coef_joint_drive_transit_ASC_ferry_work_univ_school_escort_atwork 0.00 0.00
coef_sr2_ASC_sr3p0.000000e+00coef_joint_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr 3.19 0.00
coef_sr2_ASC_walk_work-5.813633e-05coef_joint_drive_transit_ASC_heavyrail_work_univ_school_escort_atwork 0.00 0.00
coef_sr3p_ASC_rh_work-8.206902e-30coef_joint_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr 0.539 0.00
coef_sr3p_ASC_sr2_work2.351910e-04coef_joint_drive_transit_ASC_lightrail_work_univ_school_escort_atwork 0.00 0.00
coef_sr3p_ASC_sr3p_work-5.735054e-04coef_joint_drive_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr 2.05 0.00
coef_sr3p_ASC_walk_work3.486286e-05coef_joint_drive_transit_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_walk_ASC_rh0.000000e+00coef_joint_ride_hail_ASC_sr2_shopping_eatout_othmaint_social_othdiscr-6.82 0.00
coef_walk_transit_ASC_commuter_work0.000000e+00coef_joint_ride_hail_ASC_sr2_work_univ_school_escort_atwork 0.00 0.00
coef_walk_transit_ASC_express_work0.000000e+00coef_joint_ride_hail_ASC_sr3p_shopping_eatout_othmaint_social_othdiscr-6.82 0.00
coef_walk_transit_ASC_ferry_work0.000000e+00coef_joint_ride_hail_ASC_sr3p_work_univ_school_escort_atwork 0.00 0.00
coef_walk_transit_ASC_heavyrail_work3.025768e-04coef_joint_ride_hail_ASC_taxi_shopping_eatout_othmaint_social_othdiscr-7.00 0.00
coef_walk_transit_ASC_lightrail_work-1.644943e-03coef_joint_ride_hail_ASC_taxi_work_univ_school_escort_atwork 0.00 0.00
coef_walk_transit_ASC_rh_work-2.191119e-05coef_joint_ride_hail_ASC_tnc_shared-0.346 0.00
coef_walk_transit_ASC_sr2_work5.241777e-05coef_joint_ride_hail_ASC_tnc_single_shopping_eatout_othmaint_social_othdiscr-4.73 0.00
coef_walk_transit_ASC_sr3p_work-2.945579e-05coef_joint_ride_hail_ASC_tnc_single_work_univ_school_escort_atwork 0.00 0.00
coef_walk_transit_ASC_walk_work6.752091e-04coef_joint_ride_hail_ASC_walk_shopping_eatout_othmaint_social_othdiscr-7.01 0.00
coef_bike_ASC_walk_univ0.000000e+00coef_joint_ride_hail_ASC_walk_transit 0.00 0.00
coef_drive_transit_ASC_commuter_univ_school0.000000e+00coef_joint_ride_hail_ASC_walk_work_univ_school_escort_atwork 0.00 0.00
coef_drive_transit_ASC_express_univ_school0.000000e+00coef_joint_walk_ASC_rh_shopping_eatout_othmaint_social_othdiscr-3.05 0.00
coef_drive_transit_ASC_ferry_univ_school0.000000e+00coef_joint_walk_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_drive_transit_ASC_heavyrail_univ_school0.000000e+00coef_joint_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr 0.513 0.00
coef_drive_transit_ASC_lightrail_univ_school0.000000e+00coef_joint_walk_transit_ASC_commuter_work_univ_school_escort_atwork 0.00 0.00
coef_ivt_univ_school-1.050483e-02coef_joint_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr 0.665 0.00
coef_ride_hail_ASC_sr2_univ0.000000e+00coef_joint_walk_transit_ASC_express_work_univ_school_escort_atwork 0.00 0.00
coef_ride_hail_ASC_sr3p_univ0.000000e+00coef_joint_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr 0.647 0.00
coef_ride_hail_ASC_taxi_univ0.000000e+00coef_joint_walk_transit_ASC_ferry_work_univ_school_escort_atwork 0.00 0.00
coef_ride_hail_ASC_tnc_single_univ0.000000e+00coef_joint_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr 2.77 0.00
coef_ride_hail_ASC_walk_univ_escort_shopping_othmaint-2.749099e-18coef_joint_walk_transit_ASC_heavyrail_work_univ_school_escort_atwork 0.00 0.00
coef_sov_ASC_rh_univ0.000000e+00coef_joint_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr 0.728 0.00
coef_sov_ASC_walk_univ0.000000e+00coef_joint_walk_transit_ASC_lightrail_work_univ_school_escort_atwork 0.00 0.00
coef_sr2_ASC_rh_univ0.000000e+00coef_joint_walk_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr 0.0739 0.00
coef_sr2_ASC_sr2_univ0.000000e+00coef_joint_walk_transit_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_sr2_ASC_walk_univ0.000000e+00coef_joint_walk_transit_ASC_sr2_eatout-14.9 0.00
coef_sr3p_ASC_rh_univ_escort_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_joint_walk_transit_ASC_sr2_othdiscr-15.0 0.00
coef_sr3p_ASC_sr2_univ0.000000e+00coef_joint_walk_transit_ASC_sr2_othmaint-5.32 0.00
coef_sr3p_ASC_sr3p_univ0.000000e+00coef_joint_walk_transit_ASC_sr2_shopping-21.6 0.00
coef_sr3p_ASC_walk_univ0.000000e+00coef_joint_walk_transit_ASC_sr2_social-20.5 0.00
coef_walk_transit_ASC_commuter_univ_school0.000000e+00
coef_joint_walk_transit_ASC_sr2_work_univ_school_escort_atwork 0.00 0.00
coef_walk_transit_ASC_express_univ_school0.000000e+00coef_joint_walk_transit_ASC_sr3p_eatout-16.8 0.00
coef_walk_transit_ASC_ferry_univ_school0.000000e+00coef_joint_walk_transit_ASC_sr3p_othdiscr-16.7 0.00
coef_walk_transit_ASC_heavyrail_univ_school-5.322431e-05coef_joint_walk_transit_ASC_sr3p_othmaint-3.97 0.00
coef_walk_transit_ASC_lightrail_univ_school1.268521e-04coef_joint_walk_transit_ASC_sr3p_shopping-25.6 0.00
coef_walk_transit_ASC_rh_univ0.000000e+00coef_joint_walk_transit_ASC_sr3p_social-34.7 0.00
coef_walk_transit_ASC_sr2_univ0.000000e+00coef_joint_walk_transit_ASC_sr3p_work_univ_school_escort_atwork 0.00 0.00
coef_walk_transit_ASC_sr3p_univ0.000000e+00coef_joint_walk_transit_ASC_walk_eatout 3.42 0.00
coef_walk_transit_ASC_walk_univ0.000000e+00coef_joint_walk_transit_ASC_walk_othdiscr-1.02 0.00
coef_bike_ASC_walk_school-2.045778e-57coef_joint_walk_transit_ASC_walk_othmaint 0.283 0.00
coef_ride_hail_ASC_sr2_school-7.168630e-16coef_joint_walk_transit_ASC_walk_shopping 0.717 0.00
coef_ride_hail_ASC_sr3p_school-4.930109e-16coef_joint_walk_transit_ASC_walk_social-2.27 0.00
coef_ride_hail_ASC_taxi_school-4.621869e-27coef_joint_walk_transit_ASC_walk_work_univ_school_escort_atwork 0.00 0.00
coef_ride_hail_ASC_tnc_single_school-1.784036e-04coef_nest_AUTO 0.720 1.00
coef_ride_hail_ASC_walk_school-4.237276e-16coef_nest_AUTO_DRIVEALONE 0.350 1.00
coef_sov_ASC_rh_school-4.635032e-48coef_nest_AUTO_SHAREDRIDE2 0.350 1.00
coef_sov_ASC_walk_school-2.359157e-05coef_nest_AUTO_SHAREDRIDE3 0.350 1.00
coef_sr2_ASC_sr2_school5.082394e-05coef_nest_NONMOTORIZED 0.720 1.00
coef_sr2_ASC_walk_school-3.377311e-05coef_nest_RIDEHAIL 0.360 1.00
coef_sr3p_ASC_rh_school-8.786869e-64coef_nest_TRANSIT 0.720 1.00
coef_sr3p_ASC_sr2_school-1.979710e-04coef_nest_TRANSIT_DRIVEACCESS 0.500 1.00
coef_sr3p_ASC_sr3p_school2.444092e-04coef_nest_TRANSIT_WALKACCESS 0.500 1.00
coef_sr3p_ASC_walk_school-1.610767e-04coef_ride_hail_ASC_sr2_eatout_social_othdiscr-6.47 0.00
coef_walk_transit_ASC_rh_school1.961319e-05coef_ride_hail_ASC_sr2_escort_shopping_othmaint-3.84 0.00
coef_walk_transit_ASC_sr2_school2.811230e-05coef_ride_hail_ASC_sr2_school-1.92 0.00
coef_walk_transit_ASC_sr3p_school-4.190001e-05coef_ride_hail_ASC_sr2_univ-4.34 0.00
coef_walk_transit_ASC_walk_school-1.524977e-05coef_ride_hail_ASC_sr2_work-12.5 0.00
coef_bike_ASC_walk_escort-8.352243e-10coef_ride_hail_ASC_sr3p_eatout_social_othdiscr-6.91 0.00
coef_drive_transit_ASC_commuter_escort0.000000e+00coef_ride_hail_ASC_sr3p_school-8.86 0.00
coef_drive_transit_ASC_express_escort0.000000e+00coef_ride_hail_ASC_sr3p_univ-4.92 0.00
coef_drive_transit_ASC_ferry_escort0.000000e+00coef_ride_hail_ASC_sr3p_work_escort_shopping_othmaint_atwork-10.1 0.00
coef_drive_transit_ASC_heavyrail_escort-1.175371e-11coef_ride_hail_ASC_taxi_eatout_social_othdiscr-2.56 0.00
coef_drive_transit_ASC_lightrail_escort0.000000e+00coef_ride_hail_ASC_taxi_escort_shopping_othmaint-3.67 0.00
coef_ivt_escort_shopping_eatout_othdiscr_atwork-7.640350e-02coef_ride_hail_ASC_taxi_school 0.195 0.00
coef_ride_hail_ASC_sr2_escort_shopping_othmaint-2.138916e-17coef_ride_hail_ASC_taxi_univ-1.60 0.00
coef_ride_hail_ASC_taxi_escort_shopping_othmaint-2.798746e-29coef_ride_hail_ASC_taxi_work-2.42 0.00
coef_ride_hail_ASC_tnc_single_escort_shopping_othmaint9.394624e-05coef_ride_hail_ASC_tnc_shared 0.940 0.00
coef_sov_ASC_rh_escort_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_ride_hail_ASC_tnc_single_eatout_social_othdiscr 3.02 0.00
coef_sov_ASC_sr2_escort0.000000e+00coef_ride_hail_ASC_tnc_single_escort_shopping_othmaint 2.44 0.00
coef_sov_ASC_sr3p_escort0.000000e+00coef_ride_hail_ASC_tnc_single_school 2.04 0.00
coef_sov_ASC_walk_escort0.000000e+00coef_ride_hail_ASC_tnc_single_univ 0.108 0.00
coef_sr2_ASC_sr2_escort-6.160566e-04coef_ride_hail_ASC_tnc_single_work 2.66 0.00
coef_sr2_ASC_walk_escort-1.374539e-08coef_ride_hail_ASC_walk_eatout_social_othdiscr-1.92 0.00
coef_sr3p_ASC_sr2_escort4.939249e-05coef_ride_hail_ASC_walk_school-0.961 0.00
coef_sr3p_ASC_sr3p_escort-5.312809e-05coef_ride_hail_ASC_walk_transit 1.26 0.00
coef_sr3p_ASC_walk_escort7.813745e-07coef_ride_hail_ASC_walk_univ_escort_shopping_othmaint-3.68 0.00
coef_walk_transit_ASC_commuter_escort0.000000e+00coef_ride_hail_ASC_walk_work 1.33 0.00
coef_walk_transit_ASC_express_escort0.000000e+00coef_sov_ASC_rh_escort_shopping_eatout_othmaint_social_othdiscr 0.00 0.00
coef_walk_transit_ASC_ferry_escort0.000000e+00coef_sov_ASC_rh_school-9.21 0.00
coef_walk_transit_ASC_heavyrail_escort1.847275e-05coef_sov_ASC_rh_univ-6.65 0.00
coef_walk_transit_ASC_lightrail_escort-6.175222e-05coef_sov_ASC_rh_work_atwork-7.00 0.00
coef_walk_transit_ASC_rh_escort_shopping_othmaint-3.544690e-05coef_sov_ASC_sr2_escort 0.00 0.00
coef_walk_transit_ASC_sr2_escort-4.425501e-05coef_sov_ASC_sr2_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork-999. 0.00
coef_walk_transit_ASC_sr3p_escort-4.715077e-99coef_sov_ASC_sr3p_escort 0.00 0.00
coef_walk_transit_ASC_walk_escort-5.506864e-35coef_sov_ASC_sr3p_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork-999. 0.00
coef_bike_ASC_walk_shopping-1.404547e-12coef_sov_ASC_walk_eatout-1.88 0.00
coef_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_sov_ASC_walk_escort 0.00 0.00
coef_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_sov_ASC_walk_othdiscr-1.66 0.00
coef_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_sov_ASC_walk_othmaint-1.38 0.00
coef_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_sov_ASC_walk_school-2.30 0.00
coef_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_sov_ASC_walk_shopping-1.59 0.00
coef_joint_auto_ASC_rh_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sov_ASC_walk_social-1.87 0.00
coef_joint_auto_ASC_sr2_shopping1.199811e-05coef_sov_ASC_walk_univ-1.06 0.00
coef_joint_auto_ASC_sr3p_shopping-5.796288e-07coef_sov_ASC_walk_work-1.17 0.00
coef_joint_auto_ASC_walk_shopping-1.431461e-09coef_sr2_ASC_rh_univ-6.69 0.00
coef_joint_bike_ASC_rh_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_rh_work_school_escort_shopping_eatout_othmaint_social_othdiscr_atwork-7.00 0.00
coef_joint_bike_ASC_walk_shopping0.000000e+00coef_sr2_ASC_sr2_eatout 1.54 0.00
coef_joint_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr2_escort 0.829 0.00
coef_joint_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr2_othdiscr 1.16 0.00
coef_joint_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr2_othmaint 1.50 0.00
coef_joint_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr2_school-0.206 0.00
coef_joint_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr2_shopping 1.78 0.00
coef_joint_drive_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr2_social 0.975 0.00
coef_joint_ride_hail_ASC_sr2_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr2_univ 0.430 0.00
coef_joint_ride_hail_ASC_sr3p_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr2_work 0.470 0.00
coef_joint_ride_hail_ASC_taxi_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_sr3p-999. 0.00
coef_joint_ride_hail_ASC_tnc_single_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_walk_eatout-0.189 0.00
coef_joint_ride_hail_ASC_walk_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_walk_escort-2.21 0.00
coef_joint_walk_ASC_rh_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_walk_othdiscr-0.449 0.00
coef_joint_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_walk_othmaint-0.603 0.00
coef_joint_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_walk_school-0.134 0.00
coef_joint_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr0.000000e+00coef_sr2_ASC_walk_shopping-0.528 0.00
coef_joint_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr3.150898e-09coef_sr2_ASC_walk_social-0.791 0.00
coef_joint_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr-1.676959e-05coef_sr2_ASC_walk_univ 1.30 0.00
coef_joint_walk_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr-4.853053e-05coef_sr2_ASC_walk_work-0.125 0.00
coef_joint_walk_transit_ASC_sr2_shopping-6.388223e-11coef_sr3p_ASC_rh_school-6.90 0.00
coef_joint_walk_transit_ASC_sr3p_shopping-3.009123e-13coef_sr3p_ASC_rh_univ_escort_shopping_eatout_othmaint_social_othdiscr-7.00 0.00
coef_joint_walk_transit_ASC_walk_shopping-1.854492e-40coef_sr3p_ASC_rh_work-71.9 0.00
coef_sov_ASC_walk_shopping1.979504e-05coef_sr3p_ASC_sr2_eatout 0.0170 0.00
coef_sr2_ASC_sr2_shopping-1.633169e-04coef_sr3p_ASC_sr2_escort 0.132 0.00
coef_sr2_ASC_walk_shopping-2.087183e-05coef_sr3p_ASC_sr2_othdiscr-0.193 0.00
coef_sr3p_ASC_sr2_shopping-2.114611e-05coef_sr3p_ASC_sr2_othmaint 0.0597 0.00
coef_sr3p_ASC_sr3p_shopping-7.777893e-06coef_sr3p_ASC_sr2_school-1.38 0.00
coef_sr3p_ASC_walk_shopping-5.499761e-05coef_sr3p_ASC_sr2_shopping 0.409 0.00
coef_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_sr3p_ASC_sr2_social 0.441 0.00
coef_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_sr3p_ASC_sr2_univ-0.312 0.00
coef_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork0.000000e+00coef_sr3p_ASC_sr2_work-0.769 0.00
coef_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork-9.355912e-05coef_sr3p_ASC_sr3p_eatout 1.75 0.00
coef_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork1.458827e-04coef_sr3p_ASC_sr3p_escort 1.12 0.00
coef_walk_transit_ASC_sr2_shopping-4.838269e-05coef_sr3p_ASC_sr3p_othdiscr 1.21 0.00
coef_walk_transit_ASC_sr3p_shopping-7.841219e-48coef_sr3p_ASC_sr3p_othmaint 1.48 0.00
coef_walk_transit_ASC_walk_shopping-5.761910e-05coef_sr3p_ASC_sr3p_school-0.385 0.00
coef_bike_ASC_walk_eatout-5.163611e-94coef_sr3p_ASC_sr3p_shopping 1.86 0.00
coef_joint_auto_ASC_sr2_eatout_othmaint_social_othdiscr1.042498e-05coef_sr3p_ASC_sr3p_social 1.38 0.00
coef_joint_auto_ASC_sr3p_eatout_othmaint_social_othdiscr6.920224e-06coef_sr3p_ASC_sr3p_univ 0.629 0.00
coef_joint_auto_ASC_walk_eatout_othmaint_social_othdiscr-5.600401e-05coef_sr3p_ASC_sr3p_work 0.255 0.00
coef_joint_bike_ASC_walk_eatout0.000000e+00coef_sr3p_ASC_walk_eatout-0.240 0.00
coef_joint_walk_transit_ASC_sr2_eatout-2.828607e-08coef_sr3p_ASC_walk_escort-1.30 0.00
coef_joint_walk_transit_ASC_sr3p_eatout-2.226057e-09coef_sr3p_ASC_walk_othdiscr-0.712 0.00
coef_joint_walk_transit_ASC_walk_eatout-1.504477e-05coef_sr3p_ASC_walk_othmaint-0.347 0.00
coef_ride_hail_ASC_sr2_eatout_social_othdiscr-3.869795e-16coef_sr3p_ASC_walk_school-0.603 0.00
coef_ride_hail_ASC_sr3p_eatout_social_othdiscr-1.643875e-13coef_sr3p_ASC_walk_shopping-0.431 0.00
coef_ride_hail_ASC_taxi_eatout_social_othdiscr-2.363466e-28coef_sr3p_ASC_walk_social-0.451 0.00
coef_ride_hail_ASC_tnc_single_eatout_social_othdiscr-2.038351e-04coef_sr3p_ASC_walk_univ 1.68 0.00
coef_ride_hail_ASC_walk_eatout_social_othdiscr-1.208287e-15coef_sr3p_ASC_walk_work-0.120 0.00
coef_sov_ASC_walk_eatout1.478005e-05coef_walk_ASC_rh-7.00 0.00
coef_sr2_ASC_sr2_eatout1.134955e-05coef_walk_transit_ASC_commuter_escort 0.544 0.00
coef_sr2_ASC_walk_eatout-5.387236e-05coef_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork 0.183 0.00
coef_sr3p_ASC_sr2_eatout-4.592690e-05coef_walk_transit_ASC_commuter_univ_school 2.15 0.00
coef_sr3p_ASC_sr3p_eatout8.013239e-05coef_walk_transit_ASC_commuter_work 0.646 0.00
coef_sr3p_ASC_walk_eatout-2.559943e-05coef_walk_transit_ASC_express_escort 0.755 0.00
coef_walk_transit_ASC_rh_eatout_social_othdiscr2.475426e-05coef_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork 1.09 0.00
coef_walk_transit_ASC_sr2_eatout-8.378197e-06coef_walk_transit_ASC_express_univ_school 0.736 0.00
coef_walk_transit_ASC_sr3p_eatout5.928461e-05coef_walk_transit_ASC_express_work-0.116 0.00
coef_walk_transit_ASC_walk_eatout3.351367e-05coef_walk_transit_ASC_ferry_escort 0.601 0.00
coef_bike_ASC_walk_othmaint-1.105637e-05coef_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork-5.31 0.00
coef_ivt_othmaint_social5.370351e-02coef_walk_transit_ASC_ferry_univ_school 0.102 0.00
coef_joint_bike_ASC_walk_othmaint0.000000e+00coef_walk_transit_ASC_ferry_work-0.283 0.00
coef_joint_walk_transit_ASC_sr2_othmaint-1.624906e-06coef_walk_transit_ASC_heavyrail_escort 1.73 0.00
coef_joint_walk_transit_ASC_sr3p_othmaint-7.397451e-24coef_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork 1.19 0.00
coef_joint_walk_transit_ASC_walk_othmaint-3.953263e-30coef_walk_transit_ASC_heavyrail_univ_school 1.50 0.00
coef_sov_ASC_walk_othmaint5.401771e-05coef_walk_transit_ASC_heavyrail_work 0.661 0.00
coef_sr2_ASC_sr2_othmaint-4.666221e-05coef_walk_transit_ASC_lightrail_escort 2.37 0.00
coef_sr2_ASC_walk_othmaint4.186596e-05coef_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork 0.939 0.00
coef_sr3p_ASC_sr2_othmaint7.950676e-05coef_walk_transit_ASC_lightrail_univ_school 1.96 0.00
coef_sr3p_ASC_sr3p_othmaint-8.383183e-05coef_walk_transit_ASC_lightrail_work 0.724 0.00
coef_sr3p_ASC_walk_othmaint1.080875e-04coef_walk_transit_ASC_rh_eatout_social_othdiscr-4.96 0.00
coef_walk_transit_ASC_sr2_othmaint-4.017102e-15coef_walk_transit_ASC_rh_escort_shopping_othmaint-5.01 0.00
coef_walk_transit_ASC_sr3p_othmaint-6.376816e-12coef_walk_transit_ASC_rh_school-7.20 0.00
coef_walk_transit_ASC_walk_othmaint1.941271e-05coef_walk_transit_ASC_rh_univ-4.27 0.00
coef_bike_ASC_walk_social-7.802548e-08coef_walk_transit_ASC_rh_work-4.01 0.00
coef_joint_bike_ASC_walk_social0.000000e+00coef_walk_transit_ASC_sr2_eatout-2.12 0.00
coef_joint_walk_transit_ASC_sr2_social0.000000e+00coef_walk_transit_ASC_sr2_escort-0.579 0.00
coef_joint_walk_transit_ASC_sr3p_social-2.473076e-24coef_walk_transit_ASC_sr2_othdiscr-1.93 0.00
coef_joint_walk_transit_ASC_walk_social-4.316912e-11coef_walk_transit_ASC_sr2_othmaint-34.7 0.00
coef_sov_ASC_walk_social-5.943503e-10coef_walk_transit_ASC_sr2_school-3.46 0.00
coef_sr2_ASC_sr2_social-2.952234e-05coef_walk_transit_ASC_sr2_shopping-2.57 0.00
coef_sr2_ASC_walk_social2.268310e-05coef_walk_transit_ASC_sr2_social-2.27 0.00
coef_sr3p_ASC_sr2_social1.341521e-05coef_walk_transit_ASC_sr2_univ-4.00 0.00
coef_sr3p_ASC_sr3p_social3.699722e-05coef_walk_transit_ASC_sr2_work-2.58 0.00
coef_sr3p_ASC_walk_social1.658572e-05coef_walk_transit_ASC_sr3p_eatout-4.64 0.00
coef_walk_transit_ASC_sr2_social2.083999e-04coef_walk_transit_ASC_sr3p_escort-4.04 0.00
coef_walk_transit_ASC_sr3p_social-4.566934e-12coef_walk_transit_ASC_sr3p_othdiscr-1.89 0.00
coef_walk_transit_ASC_walk_social-1.676922e-04coef_walk_transit_ASC_sr3p_othmaint-29.4 0.00
coef_bike_ASC_walk_othdiscr5.983509e-05coef_walk_transit_ASC_sr3p_school-3.51 0.00
coef_joint_bike_ASC_walk_othdiscr0.000000e+00coef_walk_transit_ASC_sr3p_shopping-2.48 0.00
coef_joint_walk_transit_ASC_sr2_othdiscr0.000000e+00coef_walk_transit_ASC_sr3p_social-21.6 0.00
coef_joint_walk_transit_ASC_sr3p_othdiscr-5.170098e-09coef_walk_transit_ASC_sr3p_univ-28.7 0.00
coef_joint_walk_transit_ASC_walk_othdiscr-8.676475e-14coef_walk_transit_ASC_sr3p_work-3.23 0.00
coef_sov_ASC_walk_othdiscr4.282980e-06coef_walk_transit_ASC_walk_eatout 1.42 0.00
coef_sr2_ASC_sr2_othdiscr-6.122804e-05coef_walk_transit_ASC_walk_escort-1.54 0.00
coef_sr2_ASC_walk_othdiscr-2.831322e-05coef_walk_transit_ASC_walk_othdiscr-0.863 0.00
coef_sr3p_ASC_sr2_othdiscr-4.358718e-05coef_walk_transit_ASC_walk_othmaint 0.213 0.00
coef_sr3p_ASC_sr3p_othdiscr-8.122719e-06coef_walk_transit_ASC_walk_school-1.57 0.00
coef_sr3p_ASC_walk_othdiscr4.957928e-05coef_walk_transit_ASC_walk_shopping-1.25 0.00
coef_walk_transit_ASC_sr2_othdiscr8.887145e-06coef_walk_transit_ASC_walk_social-0.846 0.00
coef_walk_transit_ASC_sr3p_othdiscr2.325113e-05coef_walk_transit_ASC_walk_univ-1.03 0.00
coef_walk_transit_ASC_walk_othdiscr-4.684099e-05coef_walk_transit_ASC_walk_work 0.296 0.00
nit110nfev255njev110status0message'Optimization terminated successfully'successTrueelapsed_time0:02:12.823819method'SLSQP'n_cases13279iteration_number110logloss0.5679149515725046" - ], - "text/plain": [ - "┣ x: -999 -999.000000\n", - "┃ 1 1.000000\n", - "┃ coef_age010_trn 0.360551\n", - "┃ coef_age1619_da 0.344530\n", - "┃ coef_age16p_sr -0.151886\n", - "┃ ... \n", - "┃ coef_sr3p_ASC_sr3p_othdiscr 0.844944\n", - "┃ coef_sr3p_ASC_walk_othdiscr -5.841028\n", - "┃ coef_walk_transit_ASC_sr2_othdiscr -1.232224\n", - "┃ coef_walk_transit_ASC_sr3p_othdiscr -1.199264\n", - "┃ coef_walk_transit_ASC_walk_othdiscr -0.980497\n", - "┃ Length: 272, dtype: float64\n", - "┣ loglike: -7541.342641931288\n", - "┣ d_loglike: -999 0.000000\n", - "┃ 1 0.000000\n", - "┃ coef_age010_trn 0.000007\n", - "┃ coef_age1619_da -0.000020\n", - "┃ coef_age16p_sr -0.001532\n", - "┃ ... \n", - "┃ coef_sr3p_ASC_sr3p_othdiscr -0.000008\n", - "┃ coef_sr3p_ASC_walk_othdiscr 0.000050\n", - "┃ coef_walk_transit_ASC_sr2_othdiscr 0.000009\n", - "┃ coef_walk_transit_ASC_sr3p_othdiscr 0.000023\n", - "┃ coef_walk_transit_ASC_walk_othdiscr -0.000047\n", - "┃ Length: 272, dtype: float64\n", - "┣ nit: 110\n", - "┣ nfev: 255\n", - "┣ njev: 110\n", - "┣ status: 0\n", - "┣ message: 'Optimization terminated successfully'\n", - "┣ success: True\n", - "┣ elapsed_time: datetime.timedelta(seconds=132, microseconds=823819)\n", - "┣ method: 'SLSQP'\n", - "┣ n_cases: 13279\n", - "┣ iteration_number: 110\n", - "┣ logloss: 0.5679149515725046" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.maximize_loglike(method='SLSQP', options={\"maxiter\": 1000})" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Estimated coefficients" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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Value Null Value
-999-999.-999.00
1 1.00 1.00
coef_age010_trn 0.361 0.00
coef_age1619_da 0.345 0.00
coef_age16p_sr-0.152 0.00
coef_bike_ASC_rh-7.00 0.00
coef_bike_ASC_walk_work-2.66 0.00
coef_drive_transit_ASC_commuter_work 0.427 0.00
coef_drive_transit_ASC_express_work-0.355 0.00
coef_drive_transit_ASC_ferry_work 0.528 0.00
coef_drive_transit_ASC_heavyrail_work-12.0 0.00
coef_drive_transit_ASC_lightrail_work-10.3 0.00
coef_drive_transit_ASC_rh-162. 0.00
coef_hhsize1_sr-0.891 0.00
coef_hhsize2_sr 0.0397 0.00
coef_ivt_work-0.0102 0.00
coef_joint_auto_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_joint_auto_ASC_sr2_work_univ_school_escort_atwork 0.00 0.00
coef_joint_auto_ASC_sr3p_work_univ_school_escort_atwork 0.00 0.00
coef_joint_auto_ASC_walk_work_univ_school_escort_atwork 0.00 0.00
coef_joint_bike_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_joint_bike_ASC_walk_work_univ_school_escort_atwork 0.00 0.00
coef_joint_drive_transit_ASC_commuter_work_univ_school_escort_atwork 0.00 0.00
coef_joint_drive_transit_ASC_express_work_univ_school_escort_atwork 0.00 0.00
coef_joint_drive_transit_ASC_ferry_work_univ_school_escort_atwork 0.00 0.00
coef_joint_drive_transit_ASC_heavyrail_work_univ_school_escort_atwork 0.00 0.00
coef_joint_drive_transit_ASC_lightrail_work_univ_school_escort_atwork 0.00 0.00
coef_joint_drive_transit_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_joint_ride_hail_ASC_sr2_work_univ_school_escort_atwork 0.00 0.00
coef_joint_ride_hail_ASC_sr3p_work_univ_school_escort_atwork 0.00 0.00
coef_joint_ride_hail_ASC_taxi_work_univ_school_escort_atwork 0.00 0.00
coef_joint_ride_hail_ASC_tnc_shared 0.00 0.00
coef_joint_ride_hail_ASC_tnc_single_work_univ_school_escort_atwork 0.00 0.00
coef_joint_ride_hail_ASC_walk_transit 0.00 0.00
coef_joint_ride_hail_ASC_walk_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_commuter_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_express_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_ferry_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_heavyrail_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_lightrail_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_rh_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_sr2_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_sr3p_work_univ_school_escort_atwork 0.00 0.00
coef_joint_walk_transit_ASC_walk_work_univ_school_escort_atwork 0.00 0.00
coef_nest_AUTO 0.720 1.00
coef_nest_AUTO_DRIVEALONE 0.350 1.00
coef_nest_AUTO_SHAREDRIDE2 0.350 1.00
coef_nest_AUTO_SHAREDRIDE3 0.350 1.00
coef_nest_NONMOTORIZED 0.720 1.00
coef_nest_RIDEHAIL 0.360 1.00
coef_nest_TRANSIT 0.720 1.00
coef_nest_TRANSIT_DRIVEACCESS 0.500 1.00
coef_nest_TRANSIT_WALKACCESS 0.500 1.00
coef_ride_hail_ASC_sr2_work-25.0 0.00
coef_ride_hail_ASC_sr3p_work_escort_shopping_othmaint_atwork-29.7 0.00
coef_ride_hail_ASC_taxi_work-2.52 0.00
coef_ride_hail_ASC_tnc_shared 23.3 0.00
coef_ride_hail_ASC_tnc_single_work 24.0 0.00
coef_ride_hail_ASC_walk_transit 22.1 0.00
coef_ride_hail_ASC_walk_work 21.8 0.00
coef_sov_ASC_rh_work_atwork-7.00 0.00
coef_sov_ASC_sr2_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork-999. 0.00
coef_sov_ASC_sr3p_work_univ_school_shopping_eatout_othmaint_social_othdiscr_atwork-999. 0.00
coef_sov_ASC_walk_work-3.01 0.00
coef_sr2_ASC_rh_work_school_escort_shopping_eatout_othmaint_social_othdiscr_atwork-7.00 0.00
coef_sr2_ASC_sr2_work 0.197 0.00
coef_sr2_ASC_sr3p-999. 0.00
coef_sr2_ASC_walk_work-2.22 0.00
coef_sr3p_ASC_rh_work-71.9 0.00
coef_sr3p_ASC_sr2_work-0.954 0.00
coef_sr3p_ASC_sr3p_work 0.00228 0.00
coef_sr3p_ASC_walk_work-2.36 0.00
coef_walk_ASC_rh-7.00 0.00
coef_walk_transit_ASC_commuter_work 0.401 0.00
coef_walk_transit_ASC_express_work-0.355 0.00
coef_walk_transit_ASC_ferry_work 0.528 0.00
coef_walk_transit_ASC_heavyrail_work 0.503 0.00
coef_walk_transit_ASC_lightrail_work 0.633 0.00
coef_walk_transit_ASC_rh_work-2.87 0.00
coef_walk_transit_ASC_sr2_work-2.26 0.00
coef_walk_transit_ASC_sr3p_work-2.65 0.00
coef_walk_transit_ASC_walk_work-0.391 0.00
coef_bike_ASC_walk_univ-0.340 0.00
coef_drive_transit_ASC_commuter_univ_school 0.908 0.00
coef_drive_transit_ASC_express_univ_school 0.322 0.00
coef_drive_transit_ASC_ferry_univ_school 1.72 0.00
coef_drive_transit_ASC_heavyrail_univ_school 0.849 0.00
coef_drive_transit_ASC_lightrail_univ_school 1.44 0.00
coef_ivt_univ_school-0.00827 0.00
coef_ride_hail_ASC_sr2_univ-4.34 0.00
coef_ride_hail_ASC_sr3p_univ-4.92 0.00
coef_ride_hail_ASC_taxi_univ-1.60 0.00
coef_ride_hail_ASC_tnc_single_univ 0.108 0.00
coef_ride_hail_ASC_walk_univ_escort_shopping_othmaint-26.3 0.00
coef_sov_ASC_rh_univ-6.65 0.00
coef_sov_ASC_walk_univ-1.06 0.00
coef_sr2_ASC_rh_univ-6.69 0.00
coef_sr2_ASC_sr2_univ 0.430 0.00
coef_sr2_ASC_walk_univ 1.30 0.00
coef_sr3p_ASC_rh_univ_escort_shopping_eatout_othmaint_social_othdiscr-7.00 0.00
coef_sr3p_ASC_sr2_univ-0.312 0.00
coef_sr3p_ASC_sr3p_univ 0.629 0.00
coef_sr3p_ASC_walk_univ 1.68 0.00
coef_walk_transit_ASC_commuter_univ_school 0.908 0.00
coef_walk_transit_ASC_express_univ_school 0.322 0.00
coef_walk_transit_ASC_ferry_univ_school 1.72 0.00
coef_walk_transit_ASC_heavyrail_univ_school 0.867 0.00
coef_walk_transit_ASC_lightrail_univ_school 1.57 0.00
coef_walk_transit_ASC_rh_univ-4.27 0.00
coef_walk_transit_ASC_sr2_univ-4.00 0.00
coef_walk_transit_ASC_sr3p_univ-28.7 0.00
coef_walk_transit_ASC_walk_univ-1.03 0.00
coef_bike_ASC_walk_school-106. 0.00
coef_ride_hail_ASC_sr2_school-17.6 0.00
coef_ride_hail_ASC_sr3p_school-17.9 0.00
coef_ride_hail_ASC_taxi_school-1.64 0.00
coef_ride_hail_ASC_tnc_single_school 23.7 0.00
coef_ride_hail_ASC_walk_school-17.9 0.00
coef_sov_ASC_rh_school-126. 0.00
coef_sov_ASC_walk_school-3.12 0.00
coef_sr2_ASC_sr2_school-0.541 0.00
coef_sr2_ASC_walk_school-2.04 0.00
coef_sr3p_ASC_rh_school-168. 0.00
coef_sr3p_ASC_sr2_school-1.02 0.00
coef_sr3p_ASC_sr3p_school 0.193 0.00
coef_sr3p_ASC_walk_school-2.44 0.00
coef_walk_transit_ASC_rh_school-4.36 0.00
coef_walk_transit_ASC_sr2_school-2.27 0.00
coef_walk_transit_ASC_sr3p_school-2.41 0.00
coef_walk_transit_ASC_walk_school-1.50 0.00
coef_bike_ASC_walk_escort-13.5 0.00
coef_drive_transit_ASC_commuter_escort 0.544 0.00
coef_drive_transit_ASC_express_escort 0.755 0.00
coef_drive_transit_ASC_ferry_escort 0.601 0.00
coef_drive_transit_ASC_heavyrail_escort-14.2 0.00
coef_drive_transit_ASC_lightrail_escort 0.525 0.00
coef_ivt_escort_shopping_eatout_othdiscr_atwork-0.0119 0.00
coef_ride_hail_ASC_sr2_escort_shopping_othmaint-23.9 0.00
coef_ride_hail_ASC_taxi_escort_shopping_othmaint-3.66 0.00
coef_ride_hail_ASC_tnc_single_escort_shopping_othmaint 24.2 0.00
coef_sov_ASC_rh_escort_shopping_eatout_othmaint_social_othdiscr 0.00 0.00
coef_sov_ASC_sr2_escort 0.00 0.00
coef_sov_ASC_sr3p_escort 0.00 0.00
coef_sov_ASC_walk_escort 0.00 0.00
coef_sr2_ASC_sr2_escort 0.488 0.00
coef_sr2_ASC_walk_escort-25.5 0.00
coef_sr3p_ASC_sr2_escort-0.207 0.00
coef_sr3p_ASC_sr3p_escort 0.896 0.00
coef_sr3p_ASC_walk_escort-3.42 0.00
coef_walk_transit_ASC_commuter_escort 0.544 0.00
coef_walk_transit_ASC_express_escort 0.755 0.00
coef_walk_transit_ASC_ferry_escort 0.601 0.00
coef_walk_transit_ASC_heavyrail_escort 0.850 0.00
coef_walk_transit_ASC_lightrail_escort 1.13 0.00
coef_walk_transit_ASC_rh_escort_shopping_othmaint-2.36 0.00
coef_walk_transit_ASC_sr2_escort-1.02 0.00
coef_walk_transit_ASC_sr3p_escort-185. 0.00
coef_walk_transit_ASC_walk_escort-88.1 0.00
coef_bike_ASC_walk_shopping-23.2 0.00
coef_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork 0.513 0.00
coef_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork 0.665 0.00
coef_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork 0.647 0.00
coef_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork 0.540 0.00
coef_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork 0.539 0.00
coef_joint_auto_ASC_rh_shopping_eatout_othmaint_social_othdiscr-7.00 0.00
coef_joint_auto_ASC_sr2_shopping 2.78 0.00
coef_joint_auto_ASC_sr3p_shopping-19.1 0.00
coef_joint_auto_ASC_walk_shopping-23.5 0.00
coef_joint_bike_ASC_rh_shopping_eatout_othmaint_social_othdiscr-12.3 0.00
coef_joint_bike_ASC_walk_shopping-7.05 0.00
coef_joint_drive_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr 0.513 0.00
coef_joint_drive_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr 0.665 0.00
coef_joint_drive_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr 0.647 0.00
coef_joint_drive_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr 0.540 0.00
coef_joint_drive_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr 0.539 0.00
coef_joint_drive_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr 4.61 0.00
coef_joint_ride_hail_ASC_sr2_shopping_eatout_othmaint_social_othdiscr-7.00 0.00
coef_joint_ride_hail_ASC_sr3p_shopping_eatout_othmaint_social_othdiscr-7.00 0.00
coef_joint_ride_hail_ASC_taxi_shopping_eatout_othmaint_social_othdiscr-7.00 0.00
coef_joint_ride_hail_ASC_tnc_single_shopping_eatout_othmaint_social_othdiscr-4.73 0.00
coef_joint_ride_hail_ASC_walk_shopping_eatout_othmaint_social_othdiscr-7.00 0.00
coef_joint_walk_ASC_rh_shopping_eatout_othmaint_social_othdiscr-3.04 0.00
coef_joint_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr 0.513 0.00
coef_joint_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr 0.665 0.00
coef_joint_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr 0.647 0.00
coef_joint_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr 21.6 0.00
coef_joint_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr 0.924 0.00
coef_joint_walk_transit_ASC_rh_shopping_eatout_othmaint_social_othdiscr 3.13 0.00
coef_joint_walk_transit_ASC_sr2_shopping-21.6 0.00
coef_joint_walk_transit_ASC_sr3p_shopping-25.6 0.00
coef_joint_walk_transit_ASC_walk_shopping-102. 0.00
coef_sov_ASC_walk_shopping-3.79 0.00
coef_sr2_ASC_sr2_shopping 1.75 0.00
coef_sr2_ASC_walk_shopping-3.65 0.00
coef_sr3p_ASC_sr2_shopping 0.336 0.00
coef_sr3p_ASC_sr3p_shopping 1.64 0.00
coef_sr3p_ASC_walk_shopping-3.92 0.00
coef_walk_transit_ASC_commuter_shopping_eatout_othmaint_social_othdiscr_atwork 0.513 0.00
coef_walk_transit_ASC_express_shopping_eatout_othmaint_social_othdiscr_atwork 0.665 0.00
coef_walk_transit_ASC_ferry_shopping_eatout_othmaint_social_othdiscr_atwork 0.647 0.00
coef_walk_transit_ASC_heavyrail_shopping_eatout_othmaint_social_othdiscr_atwork 0.926 0.00
coef_walk_transit_ASC_lightrail_shopping_eatout_othmaint_social_othdiscr_atwork 0.831 0.00
coef_walk_transit_ASC_sr2_shopping-2.12 0.00
coef_walk_transit_ASC_sr3p_shopping-91.1 0.00
coef_walk_transit_ASC_walk_shopping-0.814 0.00
coef_bike_ASC_walk_eatout-175. 0.00
coef_joint_auto_ASC_sr2_eatout_othmaint_social_othdiscr 0.381 0.00
coef_joint_auto_ASC_sr3p_eatout_othmaint_social_othdiscr 0.389 0.00
coef_joint_auto_ASC_walk_eatout_othmaint_social_othdiscr-4.38 0.00
coef_joint_bike_ASC_walk_eatout-15.6 0.00
coef_joint_walk_transit_ASC_sr2_eatout-14.9 0.00
coef_joint_walk_transit_ASC_sr3p_eatout-16.8 0.00
coef_joint_walk_transit_ASC_walk_eatout 1.10 0.00
coef_ride_hail_ASC_sr2_eatout_social_othdiscr-16.9 0.00
coef_ride_hail_ASC_sr3p_eatout_social_othdiscr-11.9 0.00
coef_ride_hail_ASC_taxi_eatout_social_othdiscr-2.56 0.00
coef_ride_hail_ASC_tnc_single_eatout_social_othdiscr 24.0 0.00
coef_ride_hail_ASC_walk_eatout_social_othdiscr-17.7 0.00
coef_sov_ASC_walk_eatout-2.63 0.00
coef_sr2_ASC_sr2_eatout 1.10 0.00
coef_sr2_ASC_walk_eatout-4.55 0.00
coef_sr3p_ASC_sr2_eatout-0.213 0.00
coef_sr3p_ASC_sr3p_eatout 1.47 0.00
coef_sr3p_ASC_walk_eatout-2.51 0.00
coef_walk_transit_ASC_rh_eatout_social_othdiscr-2.66 0.00
coef_walk_transit_ASC_sr2_eatout-2.01 0.00
coef_walk_transit_ASC_sr3p_eatout-2.52 0.00
coef_walk_transit_ASC_walk_eatout 0.166 0.00
coef_bike_ASC_walk_othmaint-0.784 0.00
coef_ivt_othmaint_social-0.0121 0.00
coef_joint_bike_ASC_walk_othmaint-13.5 0.00
coef_joint_walk_transit_ASC_sr2_othmaint-11.3 0.00
coef_joint_walk_transit_ASC_sr3p_othmaint-44.0 0.00
coef_joint_walk_transit_ASC_walk_othmaint-73.6 0.00
coef_sov_ASC_walk_othmaint-4.43 0.00
coef_sr2_ASC_sr2_othmaint 0.935 0.00
coef_sr2_ASC_walk_othmaint-3.14 0.00
coef_sr3p_ASC_sr2_othmaint 0.0421 0.00
coef_sr3p_ASC_sr3p_othmaint 1.13 0.00
coef_sr3p_ASC_walk_othmaint-5.07 0.00
coef_walk_transit_ASC_sr2_othmaint-34.7 0.00
coef_walk_transit_ASC_sr3p_othmaint-29.4 0.00
coef_walk_transit_ASC_walk_othmaint-0.288 0.00
coef_bike_ASC_walk_social-13.2 0.00
coef_joint_bike_ASC_walk_social-26.2 0.00
coef_joint_walk_transit_ASC_sr2_social-20.5 0.00
coef_joint_walk_transit_ASC_sr3p_social-34.7 0.00
coef_joint_walk_transit_ASC_walk_social-2.39 0.00
coef_sov_ASC_walk_social-25.3 0.00
coef_sr2_ASC_sr2_social 0.768 0.00
coef_sr2_ASC_walk_social-2.85 0.00
coef_sr3p_ASC_sr2_social-0.122 0.00
coef_sr3p_ASC_sr3p_social 1.21 0.00
coef_sr3p_ASC_walk_social-3.08 0.00
coef_walk_transit_ASC_sr2_social-2.06 0.00
coef_walk_transit_ASC_sr3p_social-21.6 0.00
coef_walk_transit_ASC_walk_social-2.31 0.00
coef_bike_ASC_walk_othdiscr-1.40 0.00
coef_joint_bike_ASC_walk_othdiscr-14.4 0.00
coef_joint_walk_transit_ASC_sr2_othdiscr-15.0 0.00
coef_joint_walk_transit_ASC_sr3p_othdiscr-16.7 0.00
coef_joint_walk_transit_ASC_walk_othdiscr-25.9 0.00
coef_sov_ASC_walk_othdiscr-4.94 0.00
coef_sr2_ASC_sr2_othdiscr 0.856 0.00
coef_sr2_ASC_walk_othdiscr-2.47 0.00
coef_sr3p_ASC_sr2_othdiscr-0.418 0.00
coef_sr3p_ASC_sr3p_othdiscr 0.845 0.00
coef_sr3p_ASC_walk_othdiscr-5.84 0.00
coef_walk_transit_ASC_sr2_othdiscr-1.23 0.00
coef_walk_transit_ASC_sr3p_othdiscr-1.20 0.00
coef_walk_transit_ASC_walk_othdiscr-0.980 0.00
" + "\n" ], "text/plain": [ - "" + "" ] }, "execution_count": 9, @@ -5168,7 +5189,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -5189,7 +5210,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -5211,7 +5232,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -5280,7 +5301,7 @@ " \n", " 309\n", " coef_walk_transit_ASC_walk_eatout\n", - " 0.166429\n", + " 1.418767\n", " F\n", " \n", " \n", @@ -5320,7 +5341,7 @@ "3 coef_nest_AUTO_DRIVEALONE 0.350000 T\n", "4 coef_nest_AUTO_SHAREDRIDE2 0.350000 T\n", ".. ... ... ...\n", - "309 coef_walk_transit_ASC_walk_eatout 0.166429 F\n", + "309 coef_walk_transit_ASC_walk_eatout 1.418767 F\n", "310 walk_express_penalty 10.000000 T\n", "311 adjust_tnc_shared 30.000000 T\n", "312 coef_origin_density_applied_work_univ_school 0.000000 T\n", @@ -5329,7 +5350,7 @@ "[314 rows x 3 columns]" ] }, - "execution_count": 19, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -5346,7 +5367,7 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Python 3", + "display_name": "ESTER", "language": "python", "name": "python3" }, @@ -5360,7 +5381,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.10.15" }, "toc": { "base_numbering": 1, diff --git a/activitysim/examples/example_estimation/notebooks/est_mode_setup.py b/activitysim/examples/example_estimation/notebooks/est_mode_setup.py new file mode 100644 index 0000000000..af0546cbe2 --- /dev/null +++ b/activitysim/examples/example_estimation/notebooks/est_mode_setup.py @@ -0,0 +1,83 @@ +from __future__ import annotations + +import argparse +import os +import shutil +import sys +import warnings +from pathlib import Path + +# suppress RuntimeWarning from xarray +warnings.filterwarnings( + "ignore", + category=RuntimeWarning, + module="xarray", +) + + +def prepare( + household_sample_size: int = 20_000, subdir: str = "test-estimation-data" +) -> Path: + """Prepare the example for estimation. + + This function prepares the example for estimation by downloading the example data and + setting up the working directory. The current working directory is then set to the + created example directory. + + Parameters + ---------- + household_sample_size : int, optional + The number of households to sample from the synthetic population. The default is 20_000. + subdir : str, optional + The subdirectory to store the example data. The default is "test-estimation-data". + + Returns + ------- + Path + The path to the created example directory. + """ + root_dir = Path(__file__).parent.parent.resolve() + sys.path.insert(0, str(root_dir)) + + try: + from build_full_mtc_example import as_needed + except ImportError: + print( + "Please run this script from the " + "activitysim/examples/example_estimation/notebooks directory." + ) + raise + + as_needed(root_dir / "notebooks" / subdir, household_sample_size) + relative_path = os.path.relpath( + root_dir / "notebooks" / subdir / "activitysim-prototype-mtc-extended" + ) + os.chdir(relative_path) + return Path(relative_path) + + +def backup(filename: str | os.PathLike): + """Create or restore from a backup copy of a file.""" + backup_filename = f"{filename}.bak" + if Path(backup_filename).exists(): + shutil.copy(backup_filename, filename) + else: + shutil.copy(filename, backup_filename) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Prepare the example for estimation.") + parser.add_argument( + "--household_sample_size", + type=int, + default=20_000, + help="The number of households to sample from the synthetic population.", + ) + parser.add_argument( + "--subdir", + type=str, + default="test-estimation-data", + help="The subdirectory to store the example data.", + ) + args = parser.parse_args() + prepare(args.household_sample_size, args.subdir) diff --git a/activitysim/examples/example_estimation/scripts/infer.py b/activitysim/examples/example_estimation/scripts/infer.py index 02fbd97d8f..94869cffb2 100644 --- a/activitysim/examples/example_estimation/scripts/infer.py +++ b/activitysim/examples/example_estimation/scripts/infer.py @@ -1,6 +1,8 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import logging import os import sys @@ -165,7 +167,8 @@ def read_alts(): alts = read_alts() tour_types = list(alts.columns.values) - tour_types.remove("tot_tours") + if "tot_tours" in tour_types: + tour_types.remove("tot_tours") # tour_frequency is index in alts table alts["alt_id"] = alts.index diff --git a/activitysim/examples/placeholder_psrc/configs/tour_scheduling_school.csv b/activitysim/examples/placeholder_psrc/configs/tour_scheduling_school.csv index 8cc5fb59e8..039fa9e66d 100755 --- a/activitysim/examples/placeholder_psrc/configs/tour_scheduling_school.csv +++ b/activitysim/examples/placeholder_psrc/configs/tour_scheduling_school.csv @@ -33,7 +33,7 @@ util_adjacent_window_exists_before_this_departure_hour_second_plus_tour_interact util_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction,Adjacent window exists after this arrival hour - second+ tour interaction,"@(df.tour_num > 1) * _adjacent_window_after",coef_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction util_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours,Remaining work/school tours to be scheduled / number of unscheduled hours,"@((df.tour_count>1) & (df.tour_num == 1)) * 1.0 / tt.remaining_periods_available(df.person_id, df.start, df.end)",coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours util_departure_constants_early_up_to_5,Departure Constants -- Early (up to 5),start < 6,coef_departure_constants_early -util_departure_constants_am_peak_1 _6,Departure Constants -- AM peak 1 (6),start == 6,coef_departure_constants_am_peak_1 +util_departure_constants_am_peak_1_6,Departure Constants -- AM peak 1 (6),start == 6,coef_departure_constants_am_peak_1 util_departure_constants_am_peak_2_7,Departure Constants -- AM peak 2 (7),start == 7,coef_departure_constants_am_peak_2 util_departure_constants_am_peak_3_8,Departure Constants -- AM peak 3 (8),start == 8,coef_departure_constants_am_peak_3 util_departure_constants_am_peak_4_9,Departure Constants -- AM peak 4 (9),start == 9,coef_departure_constants_am_peak_4 diff --git a/activitysim/examples/prototype_mtc/configs/tour_scheduling_school.csv b/activitysim/examples/prototype_mtc/configs/tour_scheduling_school.csv index 6c735c4237..779109503a 100644 --- a/activitysim/examples/prototype_mtc/configs/tour_scheduling_school.csv +++ b/activitysim/examples/prototype_mtc/configs/tour_scheduling_school.csv @@ -32,7 +32,7 @@ util_adjacent_window_exists_after_this_arrival_hour_second_plus_tour_interaction util_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours,Remaining work/school tours to be scheduled / number of unscheduled hours,"@((df.tour_count>1) & (df.tour_num == 1)) * 1.0 / tt.remaining_periods_available(df.person_id, df.start, df.end)",coef_remaining_work_school_tours_to_be_scheduled_div_number_of_unscheduled_hours #,,, util_departure_constants_early_up_to_5,Departure Constants -- Early (up to 5),start < 6,coef_departure_constants_early -util_departure_constants_am_peak_1 _6,Departure Constants -- AM peak 1 (6),start == 6,coef_departure_constants_am_peak_1 +util_departure_constants_am_peak_1_6,Departure Constants -- AM peak 1 (6),start == 6,coef_departure_constants_am_peak_1 util_departure_constants_am_peak_2_7,Departure Constants -- AM peak 2 (7),start == 7,coef_departure_constants_am_peak_2 util_departure_constants_am_peak_3_8,Departure Constants -- AM peak 3 (8),start == 8,coef_departure_constants_am_peak_3 util_departure_constants_am_peak_4_9,Departure Constants -- AM peak 4 (9),start == 9,coef_departure_constants_am_peak_4 diff --git a/activitysim/examples/prototype_sandag_xborder/configs/estimation.yaml b/activitysim/examples/prototype_sandag_xborder/configs/estimation.yaml index bbe11f7fc8..d3844fc4fc 100644 --- a/activitysim/examples/prototype_sandag_xborder/configs/estimation.yaml +++ b/activitysim/examples/prototype_sandag_xborder/configs/estimation.yaml @@ -40,7 +40,7 @@ estimation_table_recipes: alternatives_combined: - interaction_sample_alternatives - interaction_expression_values - omnibus_tables_append_columns: [choosers_combined] + omnibus_tables_append_columns: [choosers_combined, alternatives_combined] interaction_simulate: omnibus_tables: @@ -77,7 +77,7 @@ estimation_table_recipes: omnibus_tables_append_columns: [values_combined] -model_estimation_table_types: +estimation_table_types: tour_scheduling_probabilistic: simple_probabilistic tour_od_choice: interaction_sample_simulate school_location: interaction_sample_simulate diff --git a/conda-environments/activitysim-dev-base.yml b/conda-environments/activitysim-dev-base.yml index f7aa5c735b..18c02afaaa 100644 --- a/conda-environments/activitysim-dev-base.yml +++ b/conda-environments/activitysim-dev-base.yml @@ -31,7 +31,7 @@ dependencies: - ipykernel # so this env will appear in jupyter as a selection - isort - jupyterlab -- larch = 5.7.* +- larch6 >= 6.0.34 - matplotlib - myst-parser # allows markdown in sphinx - nbconvert diff --git a/conda-environments/activitysim-dev.yml b/conda-environments/activitysim-dev.yml index 107b4b355e..35cda2bce6 100644 --- a/conda-environments/activitysim-dev.yml +++ b/conda-environments/activitysim-dev.yml @@ -27,7 +27,6 @@ dependencies: - ipykernel # so this env will appear in jupyter as a selection - isort - jupyterlab -- larch = 5.7.* - matplotlib - myst-parser # allows markdown in sphinx - nbconvert @@ -75,4 +74,5 @@ dependencies: - pip: - autodoc_pydantic + - larch6 >= 6.0.34 - -e .. diff --git a/conda-environments/docbuild.yml b/conda-environments/docbuild.yml index 2553fbb17f..30385c9718 100644 --- a/conda-environments/docbuild.yml +++ b/conda-environments/docbuild.yml @@ -23,7 +23,6 @@ dependencies: - git - jupyter-book - jupyterlab -- larch >=5.5.3 - matplotlib - myst-nb - myst-parser @@ -59,4 +58,5 @@ dependencies: - pip: - autodoc_pydantic + - larch6 >= 6.0.34 - -e .. diff --git a/conda-environments/github-actions-tests.yml b/conda-environments/github-actions-tests.yml index 692ee11928..d38d75650d 100644 --- a/conda-environments/github-actions-tests.yml +++ b/conda-environments/github-actions-tests.yml @@ -12,6 +12,7 @@ dependencies: - cytoolz = 0.12.2 - dask = 2023.3.2 - isort = 5.12.0 +- matplotlib = 3.9.* - nbmake = 1.4.6 - numba = 0.57.* - numpy = 1.23.5 @@ -36,5 +37,6 @@ dependencies: - simwrapper > 1.7 - sparse - xarray = 2023.2.* +- xlsxwriter = 3.2.* - zarr = 2.14.* - zstandard diff --git a/pyproject.toml b/pyproject.toml index b92b00856c..1cb6915f10 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -75,7 +75,6 @@ log_cli = true tb = "native" [tool.ruff] -select = ["E", "F", "B", "UP", "TID"] line-length = 140 exclude = [ ".git", @@ -87,12 +86,15 @@ exclude = [ "sandbox/" ] -[tool.ruff.isort] +[tool.ruff.lint] +select = ["E", "F", "B", "UP", "TID"] + +[tool.ruff.lint.isort] known-first-party = ["activitysim"] required-imports = ["from __future__ import annotations"] -[tool.ruff.pydocstyle] +[tool.ruff.lint.pydocstyle] convention = "numpy" -[tool.ruff.per-file-ignores] +[tool.ruff.lint.per-file-ignores] "__init__.py" = ["E402", "F401"] # Ignore import violations in all `__init__.py` files From aa874f69a5f3aa7caae6eab0a44b63289f4528b7 Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Fri, 13 Dec 2024 16:22:17 -0800 Subject: [PATCH 28/56] Removing estimation.yaml settings that are no longer needed --- activitysim/core/estimation.py | 172 +++++++----------- .../estimation_template.yaml | 51 ------ .../configs_estimation/estimation.yaml | 49 ----- 3 files changed, 63 insertions(+), 209 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 98bbb73f7c..4c10492c9b 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -21,6 +21,49 @@ ESTIMATION_SETTINGS_FILE_NAME = "estimation.yaml" +ESTIMATION_TABLE_RECIPES = { + "interaction_sample_simulate": { + "omnibus_tables": { + "choosers_combined": ["choices", "override_choices", "choosers"], + "alternatives_combined": [ + "interaction_sample_alternatives", + "interaction_expression_values", + ], + }, + "omnibus_tables_append_columns": ["choosers_combined", "alternatives_combined"], + }, + "interaction_simulate": { + "omnibus_tables": { + "choosers_combined": ["choices", "override_choices", "choosers"], + "alternatives_combined": ["interaction_expression_values"], + }, + "omnibus_tables_append_columns": ["choosers_combined", "alternatives_combined"], + }, + "simple_simulate": { + "omnibus_tables": { + "values_combined": [ + "choices", + "override_choices", + "expression_values", + "choosers", + ] + }, + "omnibus_tables_append_columns": ["values_combined"], + }, + "cdap_simulate": { + "omnibus_tables": { + "values_combined": ["choices", "override_choices", "choosers"] + }, + "omnibus_tables_append_columns": ["values_combined"], + }, + "simple_probabilistic": { + "omnibus_tables": { + "values_combined": ["choices", "override_choices", "choosers", "probs"] + }, + "omnibus_tables_append_columns": ["values_combined"], + }, +} + def unlink_files(directory_path, file_types=("csv", "yaml", "parquet", "pkl")): """ @@ -76,12 +119,7 @@ class EstimationConfig(PydanticReadable): if you do not care about the estimation output for all models. """ EDB_FILETYPE: Literal["csv", "parquet", "pkl"] = "csv" - EDB_ALTS_FILE_FORMAT: Literal["verbose", "compact"] = "compact" - """Format of the alternatives table in the estimation data bundle. - verbose: every possible alternative is listed in the table - compact: alternatives are renumbered from 1 to sample_size - """ DELETE_MP_SUBDIRS: bool = True """Flag to delete the multiprocessing subdirectories after coalescing the results. @@ -104,8 +142,10 @@ class EstimationConfig(PydanticReadable): 'interaction_sample_simulate', etc. """ - estimation_table_recipes: dict[str, EstimationTableRecipeConfig] = {} - """Mapping of estimation table recipe names to their configurations. + estimation_table_recipes: dict[str, EstimationTableRecipeConfig] = None + """This option has been removed from the user-facing configuration file. + + Mapping of estimation table recipe names to their configurations. The keys of this mapping are the names of the estimation table recipes. The recipes are generally related to the generic model types, such as @@ -113,6 +153,17 @@ class EstimationConfig(PydanticReadable): etc. The values are the configurations for the estimation table recipes. """ + @model_validator(mode="before") + def check_estimation_table_recipes(cls, values): + if ( + "estimation_table_recipes" in values + and values["estimation_table_recipes"] is not None + ): + raise ValueError( + "estimation_table_recipes is no longer an accepted input. Please delete it from your estimation.yaml file." + ) + return values + survey_tables: dict[str, SurveyTableConfig] = {} # pydantic class validator to ensure that the estimation_table_types @@ -121,7 +172,7 @@ class EstimationConfig(PydanticReadable): @model_validator(mode="after") def validate_estimation_table_types(self): for key, value in self.estimation_table_types.items(): - if value not in self.estimation_table_recipes: + if value not in ESTIMATION_TABLE_RECIPES: raise ValueError( f"estimation_table_types value '{value}' not in estimation_table_recipes" ) @@ -639,100 +690,7 @@ def write_model_settings( model_settings, "inherited_model_settings", bundle_directory ) - def melt_alternatives(self, df): - alt_id_name = self.alt_id_column_name - - assert alt_id_name is not None, ( - "alt_id not set. Did you forget to call set_alt_id()? (%s)" - % self.model_name - ) - assert ( - alt_id_name in df - ), "alt_id_column_name '%s' not in alternatives table (%s)" % ( - alt_id_name, - self.model_name, - ) - - variable_column = "variable" - - # alt_dest util_dist_0_1 util_dist_1_2 ... - # person_id ... - # 31153 1 1.0 0.75 ... - # 31153 2 1.0 0.46 ... - # 31153 3 1.0 0.28 ... - - if df.index.name is not None: - chooser_name = df.index.name - assert self.chooser_id_column_name in (chooser_name, None) - df = df.reset_index() - else: - assert self.chooser_id_column_name is not None - chooser_name = self.chooser_id_column_name - assert chooser_name in df - - # mergesort is the only stable sort, and we want the expressions to appear in original df column order - melt_df = ( - pd.melt(df, id_vars=[chooser_name, alt_id_name]) - .sort_values(by=[chooser_name, alt_id_name, "variable"], kind="mergesort") - .rename(columns={"variable": variable_column}) - ) - - # person_id,alt_dest,expression,value - # 31153,1,util_dist_0_1,1.0 - # 31153,2,util_dist_0_1,1.0 - # 31153,3,util_dist_0_1,1.0 - - output_format = self.settings.EDB_ALTS_FILE_FORMAT - assert output_format in ["verbose", "compact"] - - # original_alt_ids = None - # if output_format == "compact": - # # preserve the original alt_ids in the EDB output - # original_alt_ids = melt_df[[chooser_name, alt_id_name]].drop_duplicates( - # ignore_index=True - # ) - # original_alt_ids = original_alt_ids.set_index( - # [chooser_name, alt_id_name], drop=False - # )[alt_id_name] - # original_alt_ids.index = pd.MultiIndex.from_arrays( - # [ - # original_alt_ids.index.get_level_values(0), - # original_alt_ids.groupby(level=0).cumcount(), - # ], - # names=[chooser_name, alt_id_name], - # ) - # original_alt_ids = original_alt_ids.unstack(1, fill_value=-1) - # - # # renumber the alt_id column to just count from 1 to n - # # this loses the alt_id information, but drops all of the empty columns - # # (can still get empty columns if not every chooser has same number of alts) - # # (this can happen if the pick count > 1 and/or sampled alts are not included) - # melt_df[alt_id_name] = melt_df.groupby([chooser_name, variable_column])[ - # alt_id_name - # ].cumcount() - - melt_df = melt_df.set_index( - [chooser_name, variable_column, alt_id_name] - ).unstack(2) - melt_df.columns = melt_df.columns.droplevel(0) - # if original_alt_ids is not None: - # original_alt_ids.index = pd.MultiIndex.from_arrays( - # [original_alt_ids.index, pd.Index(["alt_id"] * len(original_alt_ids))], - # names=melt_df.index.names, - # ) - # melt_df = pd.concat([melt_df, original_alt_ids], axis=0) - melt_df = melt_df.sort_index().reset_index(1) - - # person_id,expression,1,2,3,4,5,... - # 31153,util_dist_0_1,0.75,0.46,0.27,0.63,0.48,... - # 31153,util_dist_1_2,0.0,0.0,0.0,0.0,0.0,... - # 31153,util_dist_2_3,0.0,0.0,0.0,0.0,0.0,... - - return melt_df - def write_interaction_expression_values(self, df): - if self.settings.EDB_ALTS_FILE_FORMAT == "verbose": - df = self.melt_alternatives(df) self.write_table( df, "interaction_expression_values", @@ -757,8 +715,6 @@ def write_alternatives(self, alternatives_df, bundle_directory=False): ) def write_interaction_sample_alternatives(self, alternatives_df): - if self.settings.EDB_ALTS_FILE_FORMAT == "verbose": - alternatives_df = self.melt_alternatives(alternatives_df) self.write_table( alternatives_df, "interaction_sample_alternatives", @@ -767,8 +723,6 @@ def write_interaction_sample_alternatives(self, alternatives_df): ) def write_interaction_simulate_alternatives(self, interaction_df): - if self.settings.EDB_ALTS_FILE_FORMAT == "verbose": - interaction_df = self.melt_alternatives(interaction_df) self.write_table( interaction_df, "interaction_simulate_alternatives", @@ -828,7 +782,7 @@ def initialize_settings(self, state): self.bundles = self.settings.bundles self.estimation_table_types = self.settings.estimation_table_types - self.estimation_table_recipes = self.settings.estimation_table_recipes + self.estimation_table_recipes = ESTIMATION_TABLE_RECIPES if self.enabled: self.survey_tables = self.settings.survey_tables @@ -925,9 +879,9 @@ def begin_estimation( state, bundle_name, model_name, - estimation_table_recipe=self.estimation_table_recipes[ - model_estimation_table_type - ], + estimation_table_recipe=EstimationTableRecipeConfig( + **self.estimation_table_recipes[model_estimation_table_type] + ), settings=self.settings, ) diff --git a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml index ff50c99ab5..6cab9136ad 100644 --- a/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml +++ b/activitysim/estimation/test/test_edb_creation/configs_estimation/estimation_template.yaml @@ -1,6 +1,4 @@ -EDB_ALTS_FILE_FORMAT: compact # options: compact, verbose EDB_FILETYPE: csv # options: csv, parquet, pkl -DELETE_MP_SUBDIRS: True enable: True @@ -52,55 +50,6 @@ survey_tables: file_name: override_trips.csv index_col: trip_id -estimation_table_recipes: - - interaction_sample_simulate: - omnibus_tables: - choosers_combined: - - choices - - override_choices - - choosers - alternatives_combined: - - interaction_sample_alternatives - - interaction_expression_values - omnibus_tables_append_columns: [choosers_combined, alternatives_combined] - - interaction_simulate: - omnibus_tables: - choosers_combined: - - choices - - override_choices - - choosers - alternatives_combined: - - interaction_expression_values - omnibus_tables_append_columns: [choosers_combined, alternatives_combined] - - simple_simulate: - omnibus_tables: - values_combined: - - choices - - override_choices - - expression_values - - choosers - omnibus_tables_append_columns: [values_combined] - - cdap_simulate: - omnibus_tables: - values_combined: - - choices - - override_choices - - choosers - omnibus_tables_append_columns: [values_combined] - - simple_probabilistic: - omnibus_tables: - values_combined: - - choices - - override_choices - - choosers - - probs - omnibus_tables_append_columns: [values_combined] - estimation_table_types: school_location: interaction_sample_simulate diff --git a/activitysim/examples/example_estimation/configs_estimation/estimation.yaml b/activitysim/examples/example_estimation/configs_estimation/estimation.yaml index 1f7bdfa6cd..dd9cd0c24c 100644 --- a/activitysim/examples/example_estimation/configs_estimation/estimation.yaml +++ b/activitysim/examples/example_estimation/configs_estimation/estimation.yaml @@ -1,4 +1,3 @@ -EDB_ALTS_FILE_FORMAT: compact # options: compact, verbose EDB_FILETYPE: parquet # options: csv, parquet, pkl enable: True @@ -51,54 +50,6 @@ survey_tables: file_name: override_trips.csv index_col: trip_id -estimation_table_recipes: - - interaction_sample_simulate: - omnibus_tables: - choosers_combined: - - choices - - override_choices - - choosers - alternatives_combined: - - interaction_sample_alternatives - - interaction_expression_values - omnibus_tables_append_columns: [choosers_combined, alternatives_combined] - - interaction_simulate: - omnibus_tables: - choosers_combined: - - choices - - override_choices - - choosers - omnibus_tables_append_columns: [choosers_combined] - - simple_simulate: - omnibus_tables: - values_combined: - - choices - - override_choices - - expression_values - - choosers - omnibus_tables_append_columns: [values_combined] - - cdap_simulate: - omnibus_tables: - values_combined: - - choices - - override_choices - - choosers - omnibus_tables_append_columns: [values_combined] - - simple_probabilistic: - omnibus_tables: - values_combined: - - choices - - override_choices - - choosers - - probs - omnibus_tables_append_columns: [values_combined] - - estimation_table_types: school_location: interaction_sample_simulate workplace_location: interaction_sample_simulate From af7e67ea6659b1ae05b6b4dc17f1af4597f1ea6a Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Fri, 13 Dec 2024 16:42:04 -0800 Subject: [PATCH 29/56] fixing unit tests, setting parquet edb default --- activitysim/core/estimation.py | 2 +- .../configs/estimation.yaml | 48 ------------------- 2 files changed, 1 insertion(+), 49 deletions(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 4c10492c9b..d320cc9315 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -118,7 +118,7 @@ class EstimationConfig(PydanticReadable): This is useful for saving disk space and decreasing runtime if you do not care about the estimation output for all models. """ - EDB_FILETYPE: Literal["csv", "parquet", "pkl"] = "csv" + EDB_FILETYPE: Literal["csv", "parquet", "pkl"] = "parquet" DELETE_MP_SUBDIRS: bool = True """Flag to delete the multiprocessing subdirectories after coalescing the results. diff --git a/activitysim/examples/example_estimation/configs/estimation.yaml b/activitysim/examples/example_estimation/configs/estimation.yaml index b6bb5831ab..0c86d786d3 100644 --- a/activitysim/examples/example_estimation/configs/estimation.yaml +++ b/activitysim/examples/example_estimation/configs/estimation.yaml @@ -49,54 +49,6 @@ survey_tables: file_name: survey_data/override_trips.csv index_col: trip_id -estimation_table_recipes: - - interaction_sample_simulate: - omnibus_tables: - choosers_combined: - - choices - - override_choices - - choosers - alternatives_combined: - - interaction_sample_alternatives - - interaction_expression_values - omnibus_tables_append_columns: [choosers_combined, alternatives_combined] - - interaction_simulate: - omnibus_tables: - choosers_combined: - - choices - - override_choices - - choosers - omnibus_tables_append_columns: [choosers_combined] - - simple_simulate: - omnibus_tables: - values_combined: - - choices - - override_choices - - expression_values - - choosers - omnibus_tables_append_columns: [values_combined] - - cdap_simulate: - omnibus_tables: - values_combined: - - choices - - override_choices - - choosers - omnibus_tables_append_columns: [values_combined] - - simple_probabilistic: - omnibus_tables: - values_combined: - - choices - - override_choices - - choosers - - probs - omnibus_tables_append_columns: [values_combined] - - estimation_table_types: school_location: interaction_sample_simulate workplace_location: interaction_sample_simulate From 99822ca154df836cfa63009ceec0a5a067ab1b0b Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Fri, 13 Dec 2024 16:46:09 -0800 Subject: [PATCH 30/56] one more missed estimation.yaml --- .../configs/estimation.yaml | 48 ------------------- 1 file changed, 48 deletions(-) diff --git a/activitysim/examples/prototype_sandag_xborder/configs/estimation.yaml b/activitysim/examples/prototype_sandag_xborder/configs/estimation.yaml index d3844fc4fc..fc857fbb98 100644 --- a/activitysim/examples/prototype_sandag_xborder/configs/estimation.yaml +++ b/activitysim/examples/prototype_sandag_xborder/configs/estimation.yaml @@ -29,54 +29,6 @@ survey_tables: file_name: trips_survey.csv index_col: trip_id -estimation_table_recipes: - - interaction_sample_simulate: - omnibus_tables: - choosers_combined: - - choices - - override_choices - - choosers - alternatives_combined: - - interaction_sample_alternatives - - interaction_expression_values - omnibus_tables_append_columns: [choosers_combined, alternatives_combined] - - interaction_simulate: - omnibus_tables: - choosers_combined: - - choices - - override_choices - - choosers - omnibus_tables_append_columns: [choosers_combined] - - simple_simulate: - omnibus_tables: - values_combined: - - choices - - override_choices - - expression_values - - choosers - omnibus_tables_append_columns: [values_combined] - - cdap_simulate: - omnibus_tables: - values_combined: - - choices - - override_choices - - choosers - omnibus_tables_append_columns: [values_combined] - - simple_probabilistic: - omnibus_tables: - values_combined: - - choices - - override_choices - - choosers - - probs - omnibus_tables_append_columns: [values_combined] - - estimation_table_types: tour_scheduling_probabilistic: simple_probabilistic tour_od_choice: interaction_sample_simulate From 17776375489dca01f9b2bb3b02ea739fbd8b0f95 Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Fri, 13 Dec 2024 17:20:16 -0800 Subject: [PATCH 31/56] using df.items for pandas 2 compatibility --- activitysim/core/estimation.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index d320cc9315..4d4836708e 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -328,7 +328,7 @@ def write_parquet(self, df, file_path, index, append=False): ), f"file already exists: {file_path}" # Explicitly set the data types of the columns - for col_name, col_data in df.iteritems(): + for col_name, col_data in df.items(): if "int" in str(col_data.dtype): pass elif ( From 420ed8e8c19d0b9ea1299e9bcd602ce2e70464f6 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Tue, 17 Dec 2024 15:06:06 -0600 Subject: [PATCH 32/56] tidy doc --- docs/users-guide/model_dev.rst | 56 ++++++++++++++++++++++++---------- 1 file changed, 40 insertions(+), 16 deletions(-) diff --git a/docs/users-guide/model_dev.rst b/docs/users-guide/model_dev.rst index b9fbc8572f..dda8c2f0e9 100644 --- a/docs/users-guide/model_dev.rst +++ b/docs/users-guide/model_dev.rst @@ -11,30 +11,54 @@ Input Data Preparation Estimation ---------- -ActivitySim includes the ability to re-estimate submodels using choice model estimation tools -such as `larch `__. To do so, ActivitySim adopts the concept of an estimation -data bundle (EDB), which is a collection of the necessary data to re-estimate a submodel. For example, for the auto ownership submodel, +ActivitySim includes the ability to re-estimate submodels using choice model estimation +tools such as `larch `__. To do so, ActivitySim adopts +the concept of an estimation data bundle (EDB), which is a collection of the necessary +data to re-estimate a submodel. For example, for the auto ownership submodel, the EDB consists of the following files: -* model settings - the auto_ownership_model_settings.yaml file -* coefficients - the auto_ownership_coefficients.csv file with each coefficient name, value, and constrain set to True or False if the coefficient is estimatable -* utilities specification - the auto_ownership_SPEC.csv utility expressions file -* chooser and alternatives data - the auto_ownership_values_combined.csv file with all chooser and alternatives data such as household information, land use information, and the utility data components for each alternative +* model settings - the auto_ownership_model_settings.yaml file -ActivitySim also includes Jupyter :ref:`estimation_example_notebooks` for estimating submodels with larch, as well as an ``activitysim.estimation.larch`` submodule that transforms EDBs into larch models. Additional estimation software translators can be added later if desired. +* coefficients - the auto_ownership_coefficients.csv file with each coefficient + name, value, and constrain set to True or False if the coefficient is estimatable -The combination of writing an EDB for a submodel + a larch estimation notebook means users can easily re-estimate submodels. This -combination of functionality means: +* utilities specification - the auto_ownership_SPEC.csv utility expressions file -* There is no duplication of model specifications. ActivitySim owns the specification and larch pivots off of it. Users code model specifications and utility expressions in ActivitySim so as to facilitate ease of use and eliminate inconsistencies and errors between the code used to estimate the models and the code used to apply the models. -* The EDB includes all the data and model structure information and the ``activitysim.estimation.larch`` submodule used by the example notebooks transforms the EDB to larch's data model for estimation. -* Users are able to add zones, alternatives, new chooser data, new taz data, new modes, new coefficients, revise utilities, and revise nesting structures in ActivitySim and larch responds accordingly. -* Eventually it may be desirable for ActivitySim to automatically write larch estimators (or other types of estimators), but for now the integration is loosely coupled rather than tightly coupled in order to provide flexibility. +* chooser and alternatives data - the auto_ownership_values_combined.csv file with + all chooser and alternatives data such as household information, land use + information, and the utility data components for each alternative + +ActivitySim also includes Jupyter :ref:`estimation_example_notebooks` for estimating +submodels with larch, as well as an ``activitysim.estimation.larch`` submodule that +transforms EDBs into larch models. Additional estimation software translators can +be added later if desired. + +The combination of writing an EDB for a submodel + a larch estimation notebook +means users can easily re-estimate submodels. This combination of functionality means: + +* There is no duplication of model specifications. ActivitySim owns the specification + and larch pivots off of it. Users code model specifications and utility expressions + in ActivitySim so as to facilitate ease of use and eliminate inconsistencies and + errors between the code used to estimate the models and the code used to apply the + models. + +* The EDB includes all the data and model structure information and the + ``activitysim.estimation.larch`` submodule used by the example notebooks transforms + the EDB to larch's data model for estimation. + +* Users are able to add zones, alternatives, new chooser data, new taz data, new + modes, new coefficients, revise utilities, and revise nesting structures in + ActivitySim and larch responds accordingly. + +* In the future ActivitySim may be more tightly coupled to Larch, but for now the + integration is loosely coupled to provide flexibility. Users preferring a different + estimation tool can write their own translator. Workflow ~~~~~~~~ -The general workflow for estimating models is shown in the following figures and explained in more detail below. +The general workflow for estimating models is shown in the following figures and +explained in more detail below. .. image:: ../images/estimation_tools.jpg @@ -193,4 +217,4 @@ Models API Calibration ----------- - \ No newline at end of file + From 44bf0374553a9f9d28b90c3055da891db7731f54 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 20 Dec 2024 16:48:34 -0800 Subject: [PATCH 33/56] updating edb file name for NMTF --- activitysim/estimation/larch/nonmand_tour_freq.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/activitysim/estimation/larch/nonmand_tour_freq.py b/activitysim/estimation/larch/nonmand_tour_freq.py index ff6835c410..0986e63838 100644 --- a/activitysim/estimation/larch/nonmand_tour_freq.py +++ b/activitysim/estimation/larch/nonmand_tour_freq.py @@ -30,7 +30,7 @@ def interaction_simulate_data( alt_def_file="{name}_alternatives.csv", coefficients_files="{segment_name}/{name}_coefficients_{segment_name}.csv", chooser_data_files="{segment_name}/{name}_choosers_combined.csv", - alt_values_files="{segment_name}/{name}_interaction_expression_values.csv", + alt_values_files="{segment_name}/{name}_alternatives_combined.csv", segment_subset=(), ): edb_directory = edb_directory.format(name=name) From 8bccf2f1bfdbb8bc555a246e43f3889352a019b9 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Thu, 26 Dec 2024 11:06:22 -0800 Subject: [PATCH 34/56] updating numba and pandas in the conda env files --- conda-environments/activitysim-dev-base.yml | 4 ++-- conda-environments/activitysim-dev.yml | 4 ++-- conda-environments/github-actions-tests.yml | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/conda-environments/activitysim-dev-base.yml b/conda-environments/activitysim-dev-base.yml index 18c02afaaa..03e2f7da03 100644 --- a/conda-environments/activitysim-dev-base.yml +++ b/conda-environments/activitysim-dev-base.yml @@ -37,13 +37,13 @@ dependencies: - nbconvert - nbformat - nbmake -- numba = 0.57.* +- numba = 0.60.* - numexpr - numpy = 1.23.* - numpydoc - openmatrix = 0.3.* - orca = 1.8 -- pandas = 1.4.* +- pandas = 1.5.* - pandera >= 0.15, <0.18.1 - platformdirs = 3.2.* - pre-commit diff --git a/conda-environments/activitysim-dev.yml b/conda-environments/activitysim-dev.yml index 35cda2bce6..5bdd04cb26 100644 --- a/conda-environments/activitysim-dev.yml +++ b/conda-environments/activitysim-dev.yml @@ -32,13 +32,13 @@ dependencies: - nbconvert - nbformat - nbmake -- numba = 0.57.* +- numba = 0.60.* - numexpr - numpy = 1.23.* - numpydoc - openmatrix = 0.3.* - orca = 1.8 -- pandas = 1.4.* +- pandas = 1.5.* - pandera >= 0.15, <0.18.1 - platformdirs = 3.2.* - pre-commit diff --git a/conda-environments/github-actions-tests.yml b/conda-environments/github-actions-tests.yml index d38d75650d..334628790e 100644 --- a/conda-environments/github-actions-tests.yml +++ b/conda-environments/github-actions-tests.yml @@ -14,12 +14,12 @@ dependencies: - isort = 5.12.0 - matplotlib = 3.9.* - nbmake = 1.4.6 -- numba = 0.57.* +- numba = 0.60.* - numpy = 1.23.5 - openmatrix = 0.3.5.0 - orca = 1.8 - pandera >= 0.15, <0.18.1 -- pandas = 1.4.* +- pandas = 1.5.* - platformdirs = 3.2.* - psutil = 5.9.* - pyarrow = 11.* From 7e59bd3a53d660fb95b7a12c4dd10d9981cda8b0 Mon Sep 17 00:00:00 2001 From: Jeffrey Newman Date: Wed, 14 May 2025 20:29:13 -0400 Subject: [PATCH 35/56] Improve test stability (#4) * handle dev versions of Larch * test stability * pin multimethod < 2.0 * add availability_expression * starting est docs * Resolve package version conflicts (#923) * limit multimethod version to 2.0 and earlier * add multimethod version to other settings * [makedocs] update installer download link * [makedocs] update branch docs * GitHub Actions updates (#926) * use libmamba solver * add permissions [makedocs] * add write permission for dev docs [makedocs] * conda-solver: classic * trace proto tables if available, otherwise synthetic population (#901) Co-authored-by: Jeffrey Newman * release instructions (#927) * use libmamba solver * add permissions [makedocs] * add write permission for dev docs [makedocs] * conda-solver: classic * include workflow dispatch option for tests * update release instructions * add installer build to instructions * Pin mamba for now, per https://github.com/conda-incubator/setup-miniconda/issues/392 * conda-remove-defaults * when no unavailability parameters are included * some general estimation docs * Use pandas 2 for docbuild environment (#928) * fix link * allow failure to import larch * workflow * blacken * try some pins * speed up docbuild * use pandas 2 for docs * oops wrong file * restore foundation * Update HOW_TO_RELEASE.md * refactor(shadow_pricing.py): remove a duplicated `default_segment_to_name_dict` (#930) * fix typo * fixing disaggregate accessibility bug in zone sampler * Revert "fixing disaggregate accessibility bug in zone sampler" This reverts commit be5d093a972905d2fb4694fed6fa143cda58f581. * notes on size terms * clean up docbuild * fix version check * add some doc * tidy * estimation docs * more on alternative avail * model evaluation * add doc on component_model * documentation enhancements * larch6 is now larch>6 * branch docs on workflow_dispatch * missing doc section on model respec --------- Co-authored-by: Yue Shuai <48269801+yueshuaing@users.noreply.github.com> Co-authored-by: David Hensle <51132108+dhensle@users.noreply.github.com> Co-authored-by: amarin <17020181+asiripanich@users.noreply.github.com> Co-authored-by: Ali Etezady <58451076+aletzdy@users.noreply.github.com> Co-authored-by: Sijia Wang --- .github/workflows/branch-docs.yml | 12 +- .github/workflows/core_tests.yml | 52 ++- HOW_TO_RELEASE.md | 110 +++---- activitysim/abm/misc.py | 3 - activitysim/abm/models/auto_ownership.py | 1 - .../abm/models/disaggregate_accessibility.py | 8 +- activitysim/abm/models/initialize.py | 1 - activitysim/abm/models/input_checker.py | 1 - .../models/non_mandatory_tour_frequency.py | 1 - .../models/trip_purpose_and_destination.py | 1 - .../abm/models/trip_scheduling_choice.py | 2 - activitysim/abm/models/util/cdap.py | 4 - activitysim/abm/models/util/overlap.py | 4 - .../models/util/probabilistic_scheduling.py | 5 - .../models/util/test/test_input_checker.py | 8 +- activitysim/abm/models/util/trip.py | 1 - activitysim/abm/tables/households.py | 1 - activitysim/abm/tables/shadow_pricing.py | 6 - activitysim/abm/tables/table_dict.py | 2 - activitysim/abm/test/run_multi_zone_mp.py | 4 +- activitysim/abm/test/test_misc/setup_utils.py | 2 - .../abm/test/test_pipeline/test_pipeline.py | 18 -- activitysim/benchmarking/latest.py | 10 +- activitysim/benchmarking/profile_inspector.py | 3 +- activitysim/cli/main.py | 2 - activitysim/cli/test/test_cli.py | 8 +- activitysim/core/assign.py | 1 - activitysim/core/estimation.py | 18 +- activitysim/core/flow.py | 5 +- activitysim/core/interaction_sample.py | 1 - .../core/interaction_sample_simulate.py | 4 +- activitysim/core/interaction_simulate.py | 1 - activitysim/core/logit.py | 3 - activitysim/core/mem.py | 5 - activitysim/core/memory_sidecar.py | 1 - activitysim/core/pathbuilder_cache.py | 5 - activitysim/core/skim_dict_factory.py | 7 - activitysim/core/skim_dictionary.py | 6 +- activitysim/core/test/extensions/steps.py | 6 - activitysim/core/test/test_assign.py | 1 - activitysim/core/test/test_inject_defaults.py | 1 - activitysim/core/test/test_input.py | 7 - activitysim/core/test/test_logging.py | 1 - activitysim/core/test/test_los.py | 9 - activitysim/core/test/test_pipeline.py | 4 - activitysim/core/test/test_random.py | 2 - activitysim/core/test/test_simulate.py | 4 - activitysim/core/test/test_skim.py | 2 - activitysim/core/test/test_timetable.py | 3 - activitysim/core/test/test_tracing.py | 9 - activitysim/core/test/test_util.py | 5 +- activitysim/core/timetable.py | 7 - activitysim/core/workflow/logging.py | 1 - activitysim/core/workflow/tracing.py | 21 +- activitysim/estimation/larch/__init__.py | 51 ++- activitysim/estimation/larch/cdap.py | 52 +-- activitysim/estimation/larch/general.py | 15 +- .../estimation/larch/location_choice.py | 87 ++++- activitysim/estimation/larch/mode_choice.py | 21 +- .../estimation/larch/nonmand_tour_freq.py | 21 +- activitysim/estimation/larch/scheduling.py | 18 +- .../estimation/larch/simple_simulate.py | 18 +- .../estimation/larch/stop_frequency.py | 16 +- .../estimation/test/test_larch_estimation.py | 9 +- ...test_loc_trip_destination_BHHH_loglike.csv | 2 +- ...est_loc_trip_destination_SLSQP_loglike.csv | 2 + ...t_loc_trip_destination_SLSQP_size_spec.csv | 23 ++ ...tion_model_trip_destination_BHHH_None_.csv | 74 ++--- ...ion_model_trip_destination_SLSQP_None_.csv | 48 +++ .../build_example_data/build_stop_coeffs.py | 3 +- activitysim/examples/optimize_example_data.py | 3 +- .../scripts/three_zone_example_data.py | 5 +- .../scripts/two_zone_example_data.py | 5 +- .../placeholder_multiple_zone/simulation.py | 3 +- .../test/simulation.py | 3 +- .../test/test_multiple_zone.py | 3 - .../three_zone_example_data.py | 5 +- .../two_zone_example_data.py | 5 +- .../placeholder_psrc/scripts/integrity.py | 3 +- .../placeholder_psrc/scripts/psrc_crop.py | 4 +- .../placeholder_psrc/test/simulation.py | 3 +- .../scripts/sandag_crop_1_zone.py | 4 +- .../scripts/sandag_crop_2_zone.py | 4 +- .../scripts/sandag_crop_3_zone.py | 4 +- .../placeholder_sandag/test/simulation.py | 3 +- .../placeholder_sandag/test/test_sandag.py | 2 - .../production_semcog/scripts/semcog_crop.py | 4 +- .../examples/production_semcog/simulation.py | 7 +- .../prototype_arc/scripts/arc_crop.py | 4 +- .../examples/prototype_arc/simulation.py | 3 +- .../examples/prototype_arc/test/simulation.py | 3 +- .../examples/prototype_arc/test/test_arc.py | 1 - .../prototype_marin/scripts/marin_crop.py | 3 +- .../prototype_marin/test/simulation.py | 3 +- .../examples/prototype_mtc/simulation.py | 3 +- .../examples/prototype_mtc/test/simulation.py | 3 +- .../sampling_scenarios.py | 1 - .../prototype_mtc_extended/test/simulation.py | 3 +- .../prototype_mwcog/scripts/mwcog_crop.py | 10 +- .../examples/prototype_mwcog/simulation.py | 3 +- .../prototype_mwcog/test/test_mwcog.py | 1 - .../extensions/reassign_tour_purpose.py | 1 - .../scripts/sandag_crop_3_zone.py | 3 +- .../prototype_sandag_xborder/simulation.py | 3 +- activitysim/workflows/steps/chunk_sizing.py | 1 - .../workflows/steps/contrast/composite_log.py | 3 +- .../workflows/steps/contrast/runtime.py | 4 +- .../steps/contrast/transform_data.py | 3 +- activitysim/workflows/steps/main.py | 2 - .../workflows/steps/memory_stress_test.py | 1 - activitysim/workflows/steps/progression.py | 4 +- .../workflows/steps/reporting/save_report.py | 3 +- conda-environments/activitysim-dev-base.yml | 3 +- conda-environments/activitysim-dev.yml | 3 +- conda-environments/docbuild.yml | 8 +- conda-environments/github-actions-tests.yml | 1 + docs/conf.py | 2 +- docs/dev-guide/changes.md | 15 + docs/gettingstarted.rst | 2 +- docs/users-guide/estimation-mode/asim-est.md | 34 ++ docs/users-guide/estimation-mode/index.md | 58 ++++ .../users-guide/estimation-mode/larch-api.rst | 50 +++ docs/users-guide/estimation-mode/larch.md | 303 ++++++++++++++++++ docs/users-guide/index.rst | 1 + docs/users-guide/modelsetup.rst | 2 +- other_resources/scripts/build_omx.py | 8 +- other_resources/scripts/create_sf_example.py | 3 +- .../scripts/make_pipeline_output.py | 3 +- other_resources/scripts/omx32.py | 3 +- other_resources/scripts/simulation.py | 6 +- other_resources/scripts/verify_results.py | 3 +- pyproject.toml | 1 + test/cdap/test_cdap.py | 1 + test/joint_tours/test_joint_tours.py | 3 +- .../test_non_mandatory_tour_frequency.py | 1 + .../parking_location/test_parking_location.py | 1 + test/random_seed/simulation.py | 3 +- test/random_seed/test_random_seed.py | 2 - 138 files changed, 1034 insertions(+), 495 deletions(-) create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_SLSQP_loglike.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_SLSQP_size_spec.csv create mode 100644 activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_SLSQP_None_.csv create mode 100644 docs/users-guide/estimation-mode/asim-est.md create mode 100644 docs/users-guide/estimation-mode/index.md create mode 100644 docs/users-guide/estimation-mode/larch-api.rst create mode 100644 docs/users-guide/estimation-mode/larch.md diff --git a/.github/workflows/branch-docs.yml b/.github/workflows/branch-docs.yml index 6447d047d1..3f2b8d549d 100644 --- a/.github/workflows/branch-docs.yml +++ b/.github/workflows/branch-docs.yml @@ -7,10 +7,12 @@ on: jobs: docbuild: - if: "contains(github.event.head_commit.message, '[makedocs]') && (github.repository_owner != 'ActivitySim') && (github.ref_name != 'develop')" + if: "github.event_name == 'workflow_dispatch' || (contains(github.event.head_commit.message, '[makedocs]') && (github.repository_owner != 'ActivitySim') && (github.ref_name != 'develop'))" # develop branch docs are built at the end of the core test workflow, regardless of repository owner or commit message flags name: ubuntu-latest py3.10 runs-on: ubuntu-latest + permissions: + contents: write defaults: run: shell: bash -l {0} @@ -19,12 +21,10 @@ jobs: with: fetch-depth: 0 # get all tags, lets setuptools_scm do its thing - - name: Setup Mambaforge + - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v2 with: - miniforge-variant: Mambaforge miniforge-version: latest - use-mamba: true python-version: "3.10" activate-environment: docbuild auto-activate-base: false @@ -40,7 +40,7 @@ jobs: id: cache - name: Update environment - run: mamba env update --verbose -n docbuild -f conda-environments/docbuild.yml + run: conda env update --verbose -n docbuild -f conda-environments/docbuild.yml if: steps.cache.outputs.cache-hit != 'true' - name: Install activitysim @@ -62,7 +62,7 @@ jobs: make html - name: Push to GitHub Pages - uses: peaceiris/actions-gh-pages@v3.8.0 + uses: peaceiris/actions-gh-pages@v4 with: github_token: ${{ secrets.GITHUB_TOKEN }} # Token is created automatically by Github Actions, no other config needed diff --git a/.github/workflows/core_tests.yml b/.github/workflows/core_tests.yml index 3b1a03b9ed..12f3da09bb 100644 --- a/.github/workflows/core_tests.yml +++ b/.github/workflows/core_tests.yml @@ -9,8 +9,10 @@ on: branches: - '*' + workflow_dispatch: + env: - CACHE_NUMBER: 2 # increase to reset cache manually + CACHE_NUMBER: 0 # increase to reset cache manually jobs: foundation: @@ -29,9 +31,13 @@ jobs: - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-version: latest - activate-environment: asim-test - python-version: ${{ matrix.python-version }} + auto-update-conda: true + miniforge-version: latest + mamba-version: "2.0.5" + conda-solver: classic + conda-remove-defaults: true + activate-environment: asim-test + python-version: ${{ matrix.python-version }} - name: Set cache date for year and month run: echo "DATE=$(date +'%Y%m')" >> $GITHUB_ENV @@ -112,9 +118,13 @@ jobs: - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: - miniforge-version: latest - activate-environment: asim-test - python-version: ${{ matrix.python-version }} + auto-update-conda: true + miniforge-version: latest + mamba-version: "2.0.5" + conda-solver: classic + conda-remove-defaults: true + activate-environment: asim-test + python-version: ${{ matrix.python-version }} - name: Set cache date for year and month run: echo "DATE=$(date +'%Y%m')" >> $GITHUB_ENV @@ -193,7 +203,11 @@ jobs: - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: + auto-update-conda: true miniforge-version: latest + mamba-version: "2.0.5" + conda-solver: classic + conda-remove-defaults: true activate-environment: asim-test python-version: ${{ env.python-version }} @@ -279,7 +293,11 @@ jobs: - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: + auto-update-conda: true miniforge-version: latest + mamba-version: "2.0.5" + conda-solver: classic + conda-remove-defaults: true activate-environment: asim-test python-version: ${{ env.python-version }} @@ -340,7 +358,11 @@ jobs: - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: + auto-update-conda: true miniforge-version: latest + mamba-version: "2.0.5" + conda-solver: classic + conda-remove-defaults: true activate-environment: asim-test python-version: ${{ env.python-version }} @@ -390,7 +412,11 @@ jobs: - name: Setup Miniforge uses: conda-incubator/setup-miniconda@v3 with: + auto-update-conda: true miniforge-version: latest + mamba-version: "2.0.5" + conda-solver: classic + conda-remove-defaults: true activate-environment: asim-test python-version: ${{ env.python-version }} @@ -409,7 +435,7 @@ jobs: if: steps.cache.outputs.cache-hit != 'true' - name: Install Larch v6 - run: python -m pip install larch6 + run: python -m pip install "larch>=6" - name: Install activitysim # installing without dependencies is faster, we trust that all needed dependencies @@ -465,7 +491,7 @@ jobs: uses: ts-graphviz/setup-graphviz@v2 - name: Install Larch v6 - run: python -m pip install larch6 "pandas<2" pydot + run: python -m pip install "larch>=6" "pandas<2" pydot - name: Install activitysim # installing without dependencies is faster, we trust that all needed dependencies @@ -541,9 +567,11 @@ jobs: develop-docbuild: needs: foundation - if: github.ref_name == 'main' + if: github.ref_name == 'main' || github.ref_name == 'docs-fix' name: develop-docbuild runs-on: ubuntu-latest + permissions: + contents: write defaults: run: shell: bash -l {0} @@ -559,6 +587,8 @@ jobs: uses: conda-incubator/setup-miniconda@v3 with: miniforge-version: latest + mamba-version: "2.0.5" + conda-remove-defaults: true environment-file: conda-environments/docbuild.yml python-version: "3.10" activate-environment: docbuild @@ -584,7 +614,7 @@ jobs: make clean make html - name: Push to GitHub Pages - uses: peaceiris/actions-gh-pages@v3.8.0 + uses: peaceiris/actions-gh-pages@v4 with: github_token: ${{ secrets.GITHUB_TOKEN }} # Token is created automatically by Github Actions, no other config needed diff --git a/HOW_TO_RELEASE.md b/HOW_TO_RELEASE.md index 89558a46c5..786a71d131 100644 --- a/HOW_TO_RELEASE.md +++ b/HOW_TO_RELEASE.md @@ -1,35 +1,28 @@ # How to issue an ActivitySim release -> **WARNING: These instructions are incomplete.** - -01. Check that the branch you intend to release is passing tests on Travis. - If it's not passing there you should not release it. +00. Check that the main branch is passing tests, especially the "core tests" on + [GitHub Actions](https://github.com/ActivitySim/activitysim/actions/workflows/core_tests.yml). + It is generally the policy that the main branch should always be passing tests, + becuase PRs must pass tests before they can be merged. However, it is + possible that tests may fail after a PR is merged, so it is important to + double-check that the main branch is passing tests before issuing a release. 00. Start from a completely clean conda environment and git repository. Assuming you have `conda` installed, you can do so by starting where ActivitySim is not yet cloned (e.g. in an empty directory) and running: ```sh - conda create -n TEMP-ASIM-DEV python=3.10 git gh -c conda-forge --override-channels - conda activate TEMP-ASIM-DEV + conda create -p ./TEMP-ASIM-DEV python=3.10 git gh -c conda-forge --override-channels + conda activate ./TEMP-ASIM-DEV gh auth login # <--- (only needed if gh is not logged in) gh repo clone ActivitySim/activitysim cd activitysim ``` -00. Per project policy, code on the main branch should have been released, - but if you are *preparing* a release then the code should be on the `develop` - branch. Switch to that branch now, and make sure it is synced to the - version on GitHub: - ```sh - git switch develop - git pull - ``` - 00. Update your Conda environment for testing. We do not want to use an - existing environment on your machine, as it may be out-of-date + existing environment on your machine, as it may be out-of-sync and we want to make sure everything passes muster using the - most up-to-date dependencies available. The following command + dependencies as they are available today. The following command will update the active environment (we made this to be `TEMP-ASIM-DEV` if you followed the directions above). ```sh @@ -48,7 +41,7 @@ black --check --diff . ``` -00. Run the regular test suite on Windows. Most GitHub Actions tests are done on Linux, +00. Run the regular test suite on Windows. Most GitHub Actions tests are done on Linux (it's faster to start up and run a new clean VM for testing) but most users are on Windows, and the test suite should also be run on Windows to ensure that it works on that platform as well. If you @@ -67,7 +60,7 @@ ``` 00. Test the full-scale regional examples. These examples are big, too - large to run on Travis, and will take a lot of time (many hours) to + large to run on GitHub Actions, and will take a lot of time (many hours) to download and run. ```sh mkdir tmp-asim @@ -88,30 +81,13 @@ There are also demo notebooks for estimation, but their functionality is completely tested in the unit tests run previously. -00. Use bump2version to tag the release commit and update the - version number. The following code will generate a "patch" release, - incrementing the third value in the version number (i.e. "1.2.3" - becomes "1.2.4"). Alternatively, make a "minor" or "major" release. - The `--list` command will generate output to your console to confirm - that the old and new version numbers are what you expect, before you - push the commit (with the changed version in the code) and tags to - GitHub. - ```sh - bump2version patch --list - ``` - - It is also possible to make a development pre-release. To do so, - explicitly set the version number to the next patch plus a ".devN" - suffix: - +00. Tag the release commit with the new version number. ActivitySim uses + dynamic versioning, so the version number is not stored in a file but + is instead read from the most recent git tag, so it is important to tag + the repository with the correct version. The following command will + generate a new tag with the version number "1.2.3" (for example): ```sh - bump2version patch --new-version 1.2.3.dev0 --list - ``` - - Then, when ready to make a "final" release, set the version by - explicitly removing the suffix: - ```sh - bump2version patch --new-version 1.2.3 --list + git -a v1.2.3 -m "Release v1.2.3" ``` 00. Push the tagged commit to GitHub. @@ -119,44 +95,40 @@ git push --tags ``` -00. For non-development releases, open a pull request to merge the proposed - release into main. The following command will open a web browser for - you to create the pull request. - ```sh - gh pr create --web - ``` - After creating the PR, confirm with the ActivitySim PMC that the release - is ready before actually merging it. - - Once final approval is granted, merge the PR into main. The presence - of the git tags added earlier will trigger automated build steps to - prepare and deploy the release to pypi and conda-forge. - -00. Create a "release" on GitHub. +00. Create a "release" on GitHub. You can do this from the command line using + the `gh` command line tool: ```sh gh release create v1.2.3 ``` + But it may be easier to do this through the + [GitHub web interface](https://github.com/ActivitySim/activitysim/releases/new), + where you can select the tag you just created and add a title and description. + Both the interactive command line tool shown above and the web interface include + the ability to create release notes automatically from the commit messages of + all accepted PRs since the last release, but you may want to add additional + notes to the release to highlight important changes or new features. + The process of creating and tagging a release will automatically trigger various GitHub Actions scripts to build, test, and publish the new release to PyPI and conda forge, assuming there are no errors. - For a development pre-release, include the `--prerelease` argument. - As the project's policy is that only formally released code is merged - to the main branch, any pre-release should also be built against a - non-default branch. For example, to pre-release from the `develop` - branch: - ```sh - gh release create v1.2.3.dev0 \ - --prerelease \ - --target develop \ - --notes "this pre-release is for a cool new feature" \ - --title "Development Pre-Release" - ``` +00. If the dependencies of ActivitySim have changed, also be sure to update the + dependencies of the conda-forge [recipe](https://github.com/conda-forge/activitysim-feedstock/tree/main/recipe). + If the dependencies of ActivitySim have not changed, the conda-forge version + of ActivitySim should auto-update within a few hours of making the release on + Github. + +00. Build the ActivitySim Standalone Windows Installer. This is done using + GitHub Actions, but it is not done automatically when a release is created, + instead it requires a manual workflow dispatch trigger. You can do this by + going to the [build_installer workflow page](https://github.com/ActivitySim/activitysim/actions/workflows/build_installer.yml) + and clicking on the "Run workflow" button. You will need to provide the + version number and choose to add the built installer to the release. 00. Clean up your workspace, including removing the Conda environment used for testing (which will prevent you from accidentally using an old environment when you should have a fresh up-to-date one next time). ```sh conda deactivate - conda env remove -n TEMP-ASIM-DEV + conda env remove -p ./TEMP-ASIM-DEV ``` diff --git a/activitysim/abm/misc.py b/activitysim/abm/misc.py index 2dd0afdf5f..ddf87af0da 100644 --- a/activitysim/abm/misc.py +++ b/activitysim/abm/misc.py @@ -18,7 +18,6 @@ @workflow.cached_object def households_sample_size(state: workflow.State, override_hh_ids) -> int: - if override_hh_ids is None: return state.settings.households_sample_size else: @@ -27,7 +26,6 @@ def households_sample_size(state: workflow.State, override_hh_ids) -> int: @workflow.cached_object def override_hh_ids(state: workflow.State) -> np.ndarray | None: - hh_ids_filename = state.settings.hh_ids if hh_ids_filename is None: return None @@ -65,7 +63,6 @@ def override_hh_ids(state: workflow.State) -> np.ndarray | None: @workflow.cached_object def trace_od(state: workflow.State) -> tuple[int, int] | None: - od = state.settings.trace_od if od and not ( diff --git a/activitysim/abm/models/auto_ownership.py b/activitysim/abm/models/auto_ownership.py index 1f6f84648b..a66ce763a7 100644 --- a/activitysim/abm/models/auto_ownership.py +++ b/activitysim/abm/models/auto_ownership.py @@ -72,7 +72,6 @@ def auto_ownership_simulate( # - preprocessor preprocessor_settings = model_settings.preprocessor if preprocessor_settings: - locals_d = {} if constants is not None: locals_d.update(constants) diff --git a/activitysim/abm/models/disaggregate_accessibility.py b/activitysim/abm/models/disaggregate_accessibility.py index c5c723f920..de878cfa07 100644 --- a/activitysim/abm/models/disaggregate_accessibility.py +++ b/activitysim/abm/models/disaggregate_accessibility.py @@ -923,10 +923,6 @@ def compute_disaggregate_accessibility( for ch in list(state.get_rn_generator().channels.keys()): state.get_rn_generator().drop_channel(ch) - # Drop any prematurely added traceables - for trace in [x for x in state.tracing.traceable_tables if "proto_" not in x]: - state.tracing.deregister_traceable_table(trace) - # # need to clear any premature tables that were added during the previous run for name in list(state.existing_table_status): if name not in tables_prior: @@ -955,4 +951,8 @@ def compute_disaggregate_accessibility( ) state.add_table(tablename, df) + # drop all proto-related tables and make way for synthetic population + for trace in state.tracing.traceable_tables: + state.tracing.deregister_traceable_table(trace) + return diff --git a/activitysim/abm/models/initialize.py b/activitysim/abm/models/initialize.py index af1ba079bb..84fe001e90 100644 --- a/activitysim/abm/models/initialize.py +++ b/activitysim/abm/models/initialize.py @@ -148,7 +148,6 @@ def initialize_households( model_settings_file_name: str = "initialize_households.yaml", trace_label: str = "initialize_households", ) -> None: - with chunk.chunk_log(state, trace_label, base=True) as chunk_sizer: chunk_sizer.log_rss(f"{trace_label}.inside-yield") diff --git a/activitysim/abm/models/input_checker.py b/activitysim/abm/models/input_checker.py index 3a24056cea..d1c8284f88 100644 --- a/activitysim/abm/models/input_checker.py +++ b/activitysim/abm/models/input_checker.py @@ -209,7 +209,6 @@ class HouseholdValidator(pydantic.BaseModel) list_of_households... def report_errors(state, input_checker_settings, v_warnings, v_errors): - # logging overall statistics first before printing details for table_settings in input_checker_settings["table_list"]: table_name = table_settings["name"] diff --git a/activitysim/abm/models/non_mandatory_tour_frequency.py b/activitysim/abm/models/non_mandatory_tour_frequency.py index f656840e11..532d3386cb 100644 --- a/activitysim/abm/models/non_mandatory_tour_frequency.py +++ b/activitysim/abm/models/non_mandatory_tour_frequency.py @@ -236,7 +236,6 @@ def non_mandatory_tour_frequency( # - preprocessor preprocessor_settings = model_settings.preprocessor if preprocessor_settings: - locals_dict = { "person_max_window": lambda x: person_max_window(state, x), "person_available_periods": lambda persons, start_bin, end_bin, continuous: person_available_periods( diff --git a/activitysim/abm/models/trip_purpose_and_destination.py b/activitysim/abm/models/trip_purpose_and_destination.py index 1c91f19bff..66443e0892 100644 --- a/activitysim/abm/models/trip_purpose_and_destination.py +++ b/activitysim/abm/models/trip_purpose_and_destination.py @@ -69,7 +69,6 @@ def trip_purpose_and_destination( model_settings_file_name: str = "trip_purpose_and_destination.yaml", trace_label: str = "trip_purpose_and_destination", ) -> None: - if model_settings is None: model_settings = TripPurposeAndDestinationSettings.read_settings_file( state.filesystem, diff --git a/activitysim/abm/models/trip_scheduling_choice.py b/activitysim/abm/models/trip_scheduling_choice.py index a8ac461680..5f58e68ee4 100644 --- a/activitysim/abm/models/trip_scheduling_choice.py +++ b/activitysim/abm/models/trip_scheduling_choice.py @@ -358,7 +358,6 @@ def trip_scheduling_choice( model_settings_file_name: str = "trip_scheduling_choice.yaml", trace_label: str = "trip_scheduling_choice", ) -> None: - if model_settings is None: model_settings = TripSchedulingChoiceSettings.read_settings_file( state.filesystem, @@ -416,7 +415,6 @@ def trip_scheduling_choice( } if preprocessor_settings: - simulate.set_skim_wrapper_targets(tours_df, skims) expressions.assign_columns( diff --git a/activitysim/abm/models/util/cdap.py b/activitysim/abm/models/util/cdap.py index f7d1d8c062..3b4c41466e 100644 --- a/activitysim/abm/models/util/cdap.py +++ b/activitysim/abm/models/util/cdap.py @@ -297,7 +297,6 @@ def cached_joint_spec_name(hhsize): def get_cached_spec(state: workflow.State, hhsize): - spec_name = cached_spec_name(hhsize) spec = state.get_injectable(spec_name, None) @@ -319,7 +318,6 @@ def get_cached_spec(state: workflow.State, hhsize): def get_cached_joint_spec(state: workflow.State, hhsize): - spec_name = cached_joint_spec_name(hhsize) spec = state.get_injectable(spec_name, None) @@ -625,7 +623,6 @@ def build_cdap_joint_spec( # N_p1 0.0 0.0 0.0 1.0 1.0 1.0 0.0 0.0 0.0 for pnum in range(1, hhsize + 1): for activity in ["M", "N", "H"]: - new_row_index = len(spec) spec.loc[new_row_index, expression_name] = add_pn(activity, pnum) @@ -638,7 +635,6 @@ def build_cdap_joint_spec( # for each row in the joint util table for row in joint_tour_coefficients.itertuples(): - # if there is no dependencies if row.dependency is np.nan: expression = row.Expression diff --git a/activitysim/abm/models/util/overlap.py b/activitysim/abm/models/util/overlap.py index 514d3d9b3d..2e3b24887f 100644 --- a/activitysim/abm/models/util/overlap.py +++ b/activitysim/abm/models/util/overlap.py @@ -138,7 +138,6 @@ def p2p_time_window_overlap(state: workflow.State, p1_ids, p2_ids): def person_pairs(persons): - p = persons[["household_id", "adult"]].reset_index() p2p = pd.merge(p, p, left_on="household_id", right_on="household_id", how="outer") @@ -166,7 +165,6 @@ def person_pairs(persons): def hh_time_window_overlap(state: workflow.State, households, persons): - p2p = person_pairs(persons) p2p["max_overlap"] = p2p_time_window_overlap(state, p2p.person1, p2p.person2) @@ -189,7 +187,6 @@ def hh_time_window_overlap(state: workflow.State, households, persons): def person_time_window_overlap(state: workflow.State, persons): - p2p = person_pairs(persons) p2p["max_overlap"] = p2p_time_window_overlap(state, p2p.person1, p2p.person2) @@ -224,7 +221,6 @@ def person_time_window_overlap(state: workflow.State, persons): def person_max_window(state: workflow.State, persons): - timetable = state.get_injectable("timetable") # ndarray with one row per person and one column per time period diff --git a/activitysim/abm/models/util/probabilistic_scheduling.py b/activitysim/abm/models/util/probabilistic_scheduling.py index 1b6b063baf..cdaf64da5a 100644 --- a/activitysim/abm/models/util/probabilistic_scheduling.py +++ b/activitysim/abm/models/util/probabilistic_scheduling.py @@ -93,7 +93,6 @@ def _report_bad_choices( # log the indexes of the first MAX_PRINT offending rows MAX_PRINT = 0 for idx in df.index[:MAX_PRINT].values: - row_msg = "%s : failed %s = %s (hh_id = %s)" % ( trace_label, df.index.name, @@ -113,7 +112,6 @@ def _preprocess_departure_probs( depart_alt_base, first_trip_in_leg, ): - # zero out probs outside earliest-latest window if one exists probs_cols = [c for c in probs_spec.columns if c not in probs_join_cols] if clip_earliest_latest: @@ -129,7 +127,6 @@ def _preprocess_departure_probs( def _preprocess_stop_duration_probs(choosers): - # convert wide to long. duration probs are stored in long format so that # inbound/outbound duration probs, which both have a 0 alternative, can be # stored in a single config file. open to better suggestions here. @@ -203,7 +200,6 @@ def _preprocess_scheduling_probs( def _postprocess_scheduling_choices( scheduling_mode, depart_alt_base, choices, choice_cols, choosers ): - """ This method just converts the choice column indexes returned by the logit.make_choices() method into actual departure time values that are @@ -222,7 +218,6 @@ def _postprocess_scheduling_choices( # get applied to trip-specific departure and arrival times, so depart_alt_base # is a column/series rather than a scalar. if scheduling_mode == "stop_duration": - # for outbound trips, offsets get added to the departure time constraint if choosers.outbound.all(): depart_alt_base = choosers["earliest"] diff --git a/activitysim/abm/models/util/test/test_input_checker.py b/activitysim/abm/models/util/test/test_input_checker.py index cdd9f41394..daecc47bf3 100644 --- a/activitysim/abm/models/util/test/test_input_checker.py +++ b/activitysim/abm/models/util/test/test_input_checker.py @@ -7,11 +7,11 @@ import pandas as pd import pandas.testing as pdt +import pandera as pa import pytest import yaml -import pandera as pa -from activitysim.abm.models.input_checker import validate_with_pandera, TABLE_STORE +from activitysim.abm.models.input_checker import TABLE_STORE, validate_with_pandera @pytest.fixture(scope="class") @@ -56,7 +56,6 @@ def households(): def test_passing_dataframe(households, v_errors, v_warnings, validation_settings): - TABLE_STORE["households"] = households class input_checker: @@ -83,7 +82,6 @@ def dummy_example(cls, households: pd.DataFrame): def test_error_dataframe(households, v_errors, v_warnings, validation_settings): - TABLE_STORE["households"] = households class input_checker: @@ -107,7 +105,6 @@ class Household(pa.DataFrameModel): def test_warning_dataframe(households, v_errors, v_warnings, validation_settings): - TABLE_STORE["households"] = households class input_checker: @@ -132,7 +129,6 @@ class Household(pa.DataFrameModel): def test_custom_check_failure_dataframe( households, v_errors, v_warnings, validation_settings ): - TABLE_STORE["households"] = households class input_checker: diff --git a/activitysim/abm/models/util/trip.py b/activitysim/abm/models/util/trip.py index f427fb8430..e62456f6fa 100644 --- a/activitysim/abm/models/util/trip.py +++ b/activitysim/abm/models/util/trip.py @@ -15,7 +15,6 @@ def failed_trip_cohorts(trips, failed): - # outbound trips in a tour with a failed outbound trip bad_outbound_trips = trips.outbound & ( trips.tour_id.isin(trips.tour_id[failed & trips.outbound]) diff --git a/activitysim/abm/tables/households.py b/activitysim/abm/tables/households.py index 142da7a015..9f121e7082 100644 --- a/activitysim/abm/tables/households.py +++ b/activitysim/abm/tables/households.py @@ -127,7 +127,6 @@ def households_merged( land_use: pd.DataFrame, accessibility: pd.DataFrame, ) -> pd.DataFrame: - households = simple_table_join( households, land_use, diff --git a/activitysim/abm/tables/shadow_pricing.py b/activitysim/abm/tables/shadow_pricing.py index 1b28883df9..586924efc9 100644 --- a/activitysim/abm/tables/shadow_pricing.py +++ b/activitysim/abm/tables/shadow_pricing.py @@ -67,12 +67,6 @@ "workplace": "income_segment", } -default_segment_to_name_dict = { - # model_selector : persons_segment_name - "school": "school_segment", - "workplace": "income_segment", -} - def size_table_name(model_selector): """ diff --git a/activitysim/abm/tables/table_dict.py b/activitysim/abm/tables/table_dict.py index 12894516cb..1c7536d665 100644 --- a/activitysim/abm/tables/table_dict.py +++ b/activitysim/abm/tables/table_dict.py @@ -18,13 +18,11 @@ @workflow.cached_object def rng_channels(state: workflow.State): - return cid.RANDOM_CHANNELS @workflow.cached_object def traceable_tables(state: workflow.State): - # names of all traceable tables ordered by dependency on household_id # e.g. 'persons' has to be registered AFTER 'households' diff --git a/activitysim/abm/test/run_multi_zone_mp.py b/activitysim/abm/test/run_multi_zone_mp.py index f4751864ba..f5d3df7ad2 100644 --- a/activitysim/abm/test/run_multi_zone_mp.py +++ b/activitysim/abm/test/run_multi_zone_mp.py @@ -1,3 +1,5 @@ +from __future__ import annotations + # ActivitySim # See full license in LICENSE.txt. import os @@ -13,7 +15,6 @@ def test_mp_run(): - configs_dir = [example_path("configs_3_zone"), example_path("configs")] data_dir = example_path("data_3") @@ -34,5 +35,4 @@ def test_mp_run(): if __name__ == "__main__": - test_mp_run() diff --git a/activitysim/abm/test/test_misc/setup_utils.py b/activitysim/abm/test/test_misc/setup_utils.py index 65deed2129..a4fe7e9c06 100644 --- a/activitysim/abm/test/test_misc/setup_utils.py +++ b/activitysim/abm/test/test_misc/setup_utils.py @@ -36,7 +36,6 @@ def example_path(dirname): def setup_dirs(ancillary_configs_dir=None, data_dir=None): - # ancillary_configs_dir is used by run_mp to test multiprocess # test_pipeline_configs_dir = os.path.join(os.path.dirname(__file__), "configs") @@ -69,7 +68,6 @@ def setup_dirs(ancillary_configs_dir=None, data_dir=None): def close_handlers(): - loggers = logging.Logger.manager.loggerDict for name in loggers: logger = logging.getLogger(name) diff --git a/activitysim/abm/test/test_pipeline/test_pipeline.py b/activitysim/abm/test/test_pipeline/test_pipeline.py index d5b4253b64..70bc26f4b1 100644 --- a/activitysim/abm/test/test_pipeline/test_pipeline.py +++ b/activitysim/abm/test/test_pipeline/test_pipeline.py @@ -34,7 +34,6 @@ def example_path(dirname): def setup_dirs(ancillary_configs_dir=None, data_dir=None): - # ancillary_configs_dir is used by run_mp to test multiprocess test_pipeline_configs_dir = os.path.join(os.path.dirname(__file__), "configs") @@ -66,7 +65,6 @@ def setup_dirs(ancillary_configs_dir=None, data_dir=None): def close_handlers(): - loggers = logging.Logger.manager.loggerDict for name in loggers: logger = logging.getLogger(name) @@ -76,7 +74,6 @@ def close_handlers(): def test_rng_access(): - state = setup_dirs() state.settings.rng_base_seed = 0 @@ -90,7 +87,6 @@ def test_rng_access(): def regress_mini_auto(state: workflow.State): - # regression test: these are among the middle households in households table # should be the same results as in run_mp (multiprocessing) test case hh_ids = [1099626, 1173905, 1196298, 1286259] @@ -123,7 +119,6 @@ def regress_mini_auto(state: workflow.State): def regress_mini_mtf(state: workflow.State): - mtf_choice = ( state.checkpoint.load_dataframe("persons").sort_index().mandatory_tour_frequency ) @@ -156,7 +151,6 @@ def regress_mini_mtf(state: workflow.State): def regress_mini_location_choice_logsums(state: workflow.State): - persons = state.checkpoint.load_dataframe("persons") # DEST_CHOICE_LOGSUM_COLUMN_NAME is specified in school_location.yaml and should be assigned @@ -168,7 +162,6 @@ def regress_mini_location_choice_logsums(state: workflow.State): def test_mini_pipeline_run(): - from activitysim.abm.tables.skims import network_los_preload state = setup_dirs() @@ -217,7 +210,6 @@ def test_mini_pipeline_run(): def test_mini_pipeline_run2(): - # the important thing here is that we should get # exactly the same results as for test_mini_pipeline_run # when we restart pipeline @@ -270,7 +262,6 @@ def test_mini_pipeline_run2(): def test_mini_pipeline_run3(): - # test that hh_ids setting overrides household sampling state = setup_dirs() @@ -300,7 +291,6 @@ def full_run( trace_od=None, check_for_variability=False, ): - state = setup_dirs() state.settings.households_sample_size = households_sample_size @@ -328,7 +318,6 @@ def full_run( def regress_tour_modes(tours_df): - mode_cols = ["tour_mode", "person_id", "tour_type", "tour_num", "tour_category"] tours_df = tours_df[tours_df.household_id == HH_ID] @@ -376,7 +365,6 @@ def regress_tour_modes(tours_df): def regress(state: workflow.State): - persons_df = state.checkpoint.load_dataframe("persons") persons_df = persons_df[persons_df.household_id == HH_ID] print("persons_df\n%s" % persons_df[["value_of_time", "distance_to_work"]]) @@ -443,7 +431,6 @@ def regress(state: workflow.State): def test_full_run1(): - if SKIP_FULL_RUN: return @@ -465,7 +452,6 @@ def test_full_run1(): def test_full_run2(): - # resume_after should successfully load tours table and replicate results if SKIP_FULL_RUN: @@ -485,7 +471,6 @@ def test_full_run2(): def test_full_run3_with_chunks(): - # should get the same result with different chunk size if SKIP_FULL_RUN: @@ -507,7 +492,6 @@ def test_full_run3_with_chunks(): def test_full_run4_stability(): - # hh should get the same result with different sample size if SKIP_FULL_RUN: @@ -523,7 +507,6 @@ def test_full_run4_stability(): def test_full_run5_singleton(): - # should work with only one hh # run with minimum chunk size to drive potential chunking errors in models # where choosers has multiple rows that all have to be included in the same chunk @@ -541,7 +524,6 @@ def test_full_run5_singleton(): if __name__ == "__main__": - print("running test_full_run1") test_full_run1() # teardown_function(None) diff --git a/activitysim/benchmarking/latest.py b/activitysim/benchmarking/latest.py index 8a6579513d..418b7f012c 100644 --- a/activitysim/benchmarking/latest.py +++ b/activitysim/benchmarking/latest.py @@ -1,6 +1,12 @@ # -*- coding: utf-8 -*- -from __future__ import absolute_import, division, print_function, unicode_literals +from __future__ import ( + absolute_import, + annotations, + division, + print_function, + unicode_literals, +) import logging import shlex @@ -149,7 +155,7 @@ def run_from_conf_args(cls, conf, args, **kwargs): pull=not args.no_pull, interleave_processes=args.interleave_processes, launch_method=args.launch_method, - **kwargs + **kwargs, ) diff --git a/activitysim/benchmarking/profile_inspector.py b/activitysim/benchmarking/profile_inspector.py index 1c8ab9e57a..42524f637a 100644 --- a/activitysim/benchmarking/profile_inspector.py +++ b/activitysim/benchmarking/profile_inspector.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import base64 import contextlib import io @@ -51,7 +53,6 @@ def benchmark_snakeviz(json_record, benchmark=None): except KeyboardInterrupt: pass except Exception: - traceback.print_exc() input(input("Press Enter to continue...")) finally: diff --git a/activitysim/cli/main.py b/activitysim/cli/main.py index 2a68910ca3..8ac2666b20 100644 --- a/activitysim/cli/main.py +++ b/activitysim/cli/main.py @@ -6,7 +6,6 @@ def prog(): - from activitysim import __doc__, __version__, workflows from activitysim.cli import CLI, benchmark, create, exercise, run @@ -45,7 +44,6 @@ def prog(): def main(): - # set all these before we import numpy or any other math library if len(sys.argv) > 1 and sys.argv[1] == "benchmark": os.environ["MKL_NUM_THREADS"] = "1" diff --git a/activitysim/cli/test/test_cli.py b/activitysim/cli/test/test_cli.py index 9358fb7405..0a02133529 100644 --- a/activitysim/cli/test/test_cli.py +++ b/activitysim/cli/test/test_cli.py @@ -1,3 +1,5 @@ +from __future__ import annotations + # ActivitySim # See full license in LICENSE.txt. import os @@ -12,7 +14,6 @@ def test_help(): - # cp = completed process cp = subprocess.run(["activitysim", "-h"], capture_output=True) @@ -20,14 +21,12 @@ def test_help(): def test_create_help(): - cp = subprocess.run(["activitysim", "create", "-h"], capture_output=True) assert "usage: activitysim create [-h] (-l | -e PATH) [-d PATH]" in str(cp.stdout) def test_create_list(): - cp = subprocess.run(["activitysim", "create", "--list"], capture_output=True) assert "Available examples" in str(cp.stdout) @@ -35,7 +34,6 @@ def test_create_list(): def test_create_copy(): - target = os.path.join(os.path.dirname(__file__), "test_example") cp = subprocess.run( [ @@ -67,7 +65,6 @@ def test_create_copy(): def test_run(): - cp = subprocess.run(["activitysim", "run"], capture_output=True) # expect error @@ -75,7 +72,6 @@ def test_run(): if __name__ == "__main__": - test_help() test_create_help() test_create_list() diff --git a/activitysim/core/assign.py b/activitysim/core/assign.py index 19693f2ab7..4054b2aec9 100644 --- a/activitysim/core/assign.py +++ b/activitysim/core/assign.py @@ -282,7 +282,6 @@ def to_series(x): n_randoms += 1 assignment_expressions.loc[expression_idx, "expression"] = expression if n_randoms: - try: random_draws = state.get_rn_generator().normal_for_df( df, broadcast=True, size=n_randoms diff --git a/activitysim/core/estimation.py b/activitysim/core/estimation.py index 4d4836708e..5b29de6960 100644 --- a/activitysim/core/estimation.py +++ b/activitysim/core/estimation.py @@ -118,7 +118,19 @@ class EstimationConfig(PydanticReadable): This is useful for saving disk space and decreasing runtime if you do not care about the estimation output for all models. """ + EDB_FILETYPE: Literal["csv", "parquet", "pkl"] = "parquet" + """File type for dataframes written to the estimation data bundles. + + Options are 'csv', 'parquet', or 'pkl'. When set to 'parquet', if file + writing fails for any reason, it will fall back to 'pkl'. This typically + will happen when the data types in the dataframe are not compatible with + parquet (e.g. Python 'object' dtype with mixed format content). + + Legacy ActivitySim used 'csv' to maximize compatibility with other software. + As of version 1.4, the default changed to 'parquet', which is more efficient + and better preserves data types. + """ DELETE_MP_SUBDIRS: bool = True """Flag to delete the multiprocessing subdirectories after coalescing the results. @@ -144,7 +156,7 @@ class EstimationConfig(PydanticReadable): estimation_table_recipes: dict[str, EstimationTableRecipeConfig] = None """This option has been removed from the user-facing configuration file. - + Mapping of estimation table recipe names to their configurations. The keys of this mapping are the names of the estimation table recipes. @@ -165,6 +177,10 @@ def check_estimation_table_recipes(cls, values): return values survey_tables: dict[str, SurveyTableConfig] = {} + """Mapping of survey table names to their configurations. + + Each survey table should have a file name and an index column. These files + are where the survey data is read from while running in estimation mode.""" # pydantic class validator to ensure that the estimation_table_types # dictionary is a valid dictionary with string keys and string values, and diff --git a/activitysim/core/flow.py b/activitysim/core/flow.py index 0b1e9fce18..d3e83e72bc 100644 --- a/activitysim/core/flow.py +++ b/activitysim/core/flow.py @@ -63,7 +63,6 @@ def logtime(tag, tag2=""): class TimeLogger: - aggregate_timing = {} def __init__(self, tag1): @@ -662,7 +661,7 @@ def _apply_filter(_dataset, renames: list): defs = {} # duplicate labels cause problems for sharrow, so we need to dedupe existing_labels = set() - for (expr, label) in zip(exprs, labels): + for expr, label in zip(exprs, labels): while label in existing_labels: label = label + "_" existing_labels.add(label) @@ -691,7 +690,7 @@ def _apply_filter(_dataset, renames: list): orig_col_name: {orig_col_name} dest_col_name: {dest_col_name} expressions:""" - for (expr, label) in zip(exprs, labels): + for expr, label in zip(exprs, labels): readme += f"\n - {label}: {expr}" if extra_vars: readme += "\n extra_vars:" diff --git a/activitysim/core/interaction_sample.py b/activitysim/core/interaction_sample.py index a43f414106..8db19a416d 100644 --- a/activitysim/core/interaction_sample.py +++ b/activitysim/core/interaction_sample.py @@ -251,7 +251,6 @@ def _interaction_sample( # check if tracing is enabled and if we have trace targets # if not estimation mode, drop unused columns if (not have_trace_targets) and (compute_settings.drop_unused_columns): - choosers = util.drop_unused_columns( choosers, spec, diff --git a/activitysim/core/interaction_sample_simulate.py b/activitysim/core/interaction_sample_simulate.py index 2df1fe4ced..9cdea3292d 100644 --- a/activitysim/core/interaction_sample_simulate.py +++ b/activitysim/core/interaction_sample_simulate.py @@ -7,8 +7,7 @@ import numpy as np import pandas as pd - -from activitysim.core import chunk, interaction_simulate, logit, tracing, workflow, util +from activitysim.core import chunk, interaction_simulate, logit, tracing, util, workflow from activitysim.core.configuration.base import ComputeSettings from activitysim.core.simulate import set_skim_wrapper_targets @@ -151,7 +150,6 @@ def _interaction_sample_simulate( and (estimator is None) and (compute_settings.drop_unused_columns) ): - choosers = util.drop_unused_columns( choosers, spec, diff --git a/activitysim/core/interaction_simulate.py b/activitysim/core/interaction_simulate.py index 38a90655e0..1089de3edc 100644 --- a/activitysim/core/interaction_simulate.py +++ b/activitysim/core/interaction_simulate.py @@ -743,7 +743,6 @@ def _interaction_simulate( and (estimator is None) and (compute_settings.drop_unused_columns) ): - choosers = util.drop_unused_columns( choosers, spec, diff --git a/activitysim/core/logit.py b/activitysim/core/logit.py index 9d282dddaf..034d970ca6 100644 --- a/activitysim/core/logit.py +++ b/activitysim/core/logit.py @@ -72,7 +72,6 @@ def report_bad_choices( # log the indexes of the first MAX_DUMP offending rows for idx in df.index[:MAX_PRINT].values: - row_msg = "%s : %s in: %s = %s (hh_id = %s)" % ( trace_label, msg, @@ -313,7 +312,6 @@ def make_choices( ).abs() > BAD_PROB_THRESHOLD * np.ones(len(probs.index)) if bad_probs.any() and not allow_bad_probs: - report_bad_choices( state, bad_probs, @@ -458,7 +456,6 @@ def nest_types(cls): def validate_nest_spec(nest_spec: dict | LogitNestSpec, trace_label: str): - keys = [] duplicates = [] for nest in each_nest(nest_spec): diff --git a/activitysim/core/mem.py b/activitysim/core/mem.py index d17b84adc8..fbfa11fbe5 100644 --- a/activitysim/core/mem.py +++ b/activitysim/core/mem.py @@ -147,7 +147,6 @@ def consolidate_logs(state: workflow.State): def check_global_hwm(tag, value, label): - assert value is not None hwm = GLOBAL_HWM.setdefault(tag, {}) @@ -164,7 +163,6 @@ def check_global_hwm(tag, value, label): def log_global_hwm(): - process_name = multiprocessing.current_process().name for tag in GLOBAL_HWM: @@ -177,7 +175,6 @@ def log_global_hwm(): def trace_memory_info(event, trace_ticks=0, force_garbage_collect=False, *, state): - global MEM_TICK if state is None: @@ -232,7 +229,6 @@ def trace_memory_info(event, trace_ticks=0, force_garbage_collect=False, *, stat noteworthy = check_global_hwm("uss", uss, event) or noteworthy if noteworthy: - # logger.debug(f"trace_memory_info {event} " # f"rss: {GB(full_rss) if num_children else GB(rss)} " # f"uss: {GB(rss)} ") @@ -266,7 +262,6 @@ def trace_memory_info(event, trace_ticks=0, force_garbage_collect=False, *, stat def get_rss(force_garbage_collect=False, uss=False): - if force_garbage_collect: was_disabled = not gc.isenabled() if was_disabled: diff --git a/activitysim/core/memory_sidecar.py b/activitysim/core/memory_sidecar.py index 7ad8d35ffd..301dbaad2a 100644 --- a/activitysim/core/memory_sidecar.py +++ b/activitysim/core/memory_sidecar.py @@ -11,7 +11,6 @@ def record_memory_usage( logstream, event="", event_idx=-1, measure_uss=False, measure_cpu=False, pid=None ): - if pid is None: pid = os.getpid() current_process = psutil.Process(pid) diff --git a/activitysim/core/pathbuilder_cache.py b/activitysim/core/pathbuilder_cache.py index 02f8db8dd0..a59ca17ec4 100644 --- a/activitysim/core/pathbuilder_cache.py +++ b/activitysim/core/pathbuilder_cache.py @@ -70,7 +70,6 @@ class TVPBCache(object): """ def __init__(self, network_los: "los.Network_LOS", uid_calculator, cache_tag): - # lightweight until opened self.cache_tag = cache_tag @@ -121,7 +120,6 @@ def cleanup(self): break def write_static_cache(self, data): - assert not self.is_open assert self._data is None assert not self.is_changed @@ -336,7 +334,6 @@ class TapTapUidCalculator: """ def __init__(self, network_los): - self.network_los = network_los # ensure that tap_df has been loaded @@ -420,7 +417,6 @@ def get_unique_ids(self, df, scalar_attributes): # need to know cardinality and integer representation of each tap/attribute for name, ordinalizer in self.ordinalizers.items(): - cardinality = ordinalizer.max() + 1 if name in df: @@ -484,7 +480,6 @@ def each_scalar_attribute_combination(self): # attribute names as list of strings attribute_names = list(self.segmentation.keys()) for attribute_value_tuple in self.attribute_combination_tuples: - # attribute_value_tuple is an tuple of attribute values - e.g. (0, 'AM', 'walk') # build dict of attribute name:value pairs - e.g. {'demographic_segment': 0, 'tod': 'AM', }) scalar_attributes = { diff --git a/activitysim/core/skim_dict_factory.py b/activitysim/core/skim_dict_factory.py index eb0195749f..78c7053583 100644 --- a/activitysim/core/skim_dict_factory.py +++ b/activitysim/core/skim_dict_factory.py @@ -114,11 +114,9 @@ def load_skim_info(self, state, skim_tag): self.omx_manifest = {} # dict mapping { omx_key: skim_name } for omx_file_path in self.omx_file_paths: - logger.debug(f"load_skim_info {skim_tag} reading {omx_file_path}") with omx.open_file(omx_file_path, mode="r") as omx_file: - # fixme call to omx_file.shape() failing in windows p3.5 if self.omx_shape is None: self.omx_shape = tuple( @@ -190,7 +188,6 @@ def load_skim_info(self, state, skim_tag): # ('DRV_COM_WLK_BOARDS', 'MD') 4, ... self.block_offsets = dict() for skim_key in self.omx_keys: - if isinstance(skim_key, tuple): key1, key2 = skim_key else: @@ -281,7 +278,6 @@ def _read_skims_from_omx(self, skim_info, skim_data): omx_manifest = skim_info.omx_manifest # dict mapping { omx_key: skim_name } for omx_file_path in skim_info.omx_file_paths: - num_skims_loaded = 0 logger.info(f"_read_skims_from_omx {omx_file_path}") @@ -289,9 +285,7 @@ def _read_skims_from_omx(self, skim_info, skim_data): # read skims into skim_data with omx.open_file(omx_file_path, mode="r") as omx_file: for skim_key, omx_key in omx_keys.items(): - if omx_manifest[omx_key] == omx_file_path: - offset = skim_info.block_offsets[skim_key] logger.debug( f"_read_skims_from_omx file {omx_file_path} omx_key {omx_key} " @@ -366,7 +360,6 @@ def _create_empty_writable_memmap_skim_cache(self, skim_info): return data def copy_omx_to_mmap_file(self, skim_info): - skim_data = self._create_empty_writable_memmap_skim_cache(skim_info) self._read_skims_from_omx(skim_info, skim_data) skim_data._mmap.close() diff --git a/activitysim/core/skim_dictionary.py b/activitysim/core/skim_dictionary.py index caafd08e64..020002e252 100644 --- a/activitysim/core/skim_dictionary.py +++ b/activitysim/core/skim_dictionary.py @@ -1,10 +1,10 @@ # ActivitySim # See full license in LICENSE.txt. from __future__ import annotations -from collections import OrderedDict import logging from builtins import object, range +from collections import OrderedDict import numpy as np import pandas as pd @@ -38,7 +38,6 @@ class OffsetMapper(object): """ def __init__(self, offset_int=None, offset_list=None, offset_series=None): - self.offset_int = self.offset_series = None assert (offset_int is not None) + (offset_list is not None) + ( @@ -160,7 +159,6 @@ class SkimDict: """ def __init__(self, state, skim_tag, skim_info, skim_data): - logger.info(f"SkimDict init {skim_tag}") self.skim_tag = skim_tag @@ -772,7 +770,6 @@ def sparse_lookup(self, orig, dest, key): is_nan = np.isnan(values) if max_blend_distance > 0: - # print(f"{is_nan.sum()} nans out of {len(is_nan)} for key '{self.key}") # print(f"blend_distance_skim_name {self.blend_distance_skim_name}") @@ -802,7 +799,6 @@ def sparse_lookup(self, orig, dest, key): # print(f"{is_nan.sum()} nans out of {len(is_nan)} for key '{self.key}") if key in self.base_keys: - # replace nan values using simple backstop without blending backstop_values = super().lookup(orig, dest, key) values = np.where(is_nan, backstop_values, values) diff --git a/activitysim/core/test/extensions/steps.py b/activitysim/core/test/extensions/steps.py index 6772853168..0ac63f0952 100644 --- a/activitysim/core/test/extensions/steps.py +++ b/activitysim/core/test/extensions/steps.py @@ -7,28 +7,24 @@ @workflow.step def step1(state: workflow.State) -> None: - table1 = pd.DataFrame({"c": [1, 2, 3]}) state.add_table("table1", table1) @workflow.step def step2(state: workflow.State) -> None: - table1 = pd.DataFrame({"c": [2, 4, 6]}) state.add_table("table2", table1) @workflow.step def step3(state: workflow.State) -> None: - table1 = pd.DataFrame({"c": [3, 6, 9]}) state.add_table("table3", table1) @workflow.step def step_add_col(state: workflow.State) -> None: - table_name = state.get_step_arg("table_name") assert table_name is not None @@ -46,7 +42,6 @@ def step_add_col(state: workflow.State) -> None: @workflow.step def step_forget_tab(state: workflow.State) -> None: - table_name = state.get_step_arg("table_name") assert table_name is not None @@ -57,7 +52,6 @@ def step_forget_tab(state: workflow.State) -> None: @workflow.step def create_households(state: workflow.State) -> None: - df = pd.DataFrame({"household_id": [1, 2, 3], "home_zone_id": {100, 100, 101}}) state.add_table("households", df) diff --git a/activitysim/core/test/test_assign.py b/activitysim/core/test/test_assign.py index e018ec1d50..192b3b0c8c 100644 --- a/activitysim/core/test/test_assign.py +++ b/activitysim/core/test/test_assign.py @@ -14,7 +14,6 @@ def close_handlers(): - loggers = logging.Logger.manager.loggerDict for name in loggers: logger = logging.getLogger(name) diff --git a/activitysim/core/test/test_inject_defaults.py b/activitysim/core/test/test_inject_defaults.py index 399756ae00..da77f4ccd6 100644 --- a/activitysim/core/test/test_inject_defaults.py +++ b/activitysim/core/test/test_inject_defaults.py @@ -15,7 +15,6 @@ def test_defaults(): - state = workflow.State() with pytest.raises(ValidationError): state.initialize_filesystem(working_dir=Path(__file__).parents[1]) diff --git a/activitysim/core/test/test_input.py b/activitysim/core/test/test_input.py index bedf100d75..0db2c43891 100644 --- a/activitysim/core/test/test_input.py +++ b/activitysim/core/test/test_input.py @@ -48,7 +48,6 @@ def state(): def test_missing_table_list(state): - state.load_settings() assert isinstance(state.settings, configuration.Settings) @@ -58,7 +57,6 @@ def test_missing_table_list(state): def test_csv_reader(seed_households, state): - settings_yaml = """ input_table_list: - tablename: households @@ -83,7 +81,6 @@ def test_csv_reader(seed_households, state): def test_hdf_reader1(seed_households, state): - settings_yaml = """ input_table_list: - tablename: households @@ -108,7 +105,6 @@ def test_hdf_reader1(seed_households, state): def test_hdf_reader2(seed_households, state): - settings_yaml = """ input_table_list: - tablename: households @@ -134,7 +130,6 @@ def test_hdf_reader2(seed_households, state): def test_hdf_reader3(seed_households, state): - settings_yaml = """ input_store: input_data.h5 input_table_list: @@ -159,7 +154,6 @@ def test_hdf_reader3(seed_households, state): def test_missing_filename(seed_households, state): - settings_yaml = """ input_table_list: - tablename: households @@ -178,7 +172,6 @@ def test_missing_filename(seed_households, state): def test_create_input_store(seed_households, state): - settings_yaml = """ create_input_store: True input_table_list: diff --git a/activitysim/core/test/test_logging.py b/activitysim/core/test/test_logging.py index b99e808963..5d9b9c8991 100644 --- a/activitysim/core/test/test_logging.py +++ b/activitysim/core/test/test_logging.py @@ -114,7 +114,6 @@ def close_handlers(): @pytest.mark.parametrize("logging_yaml", logging_config_content.keys()) def test_config_logger(capsys, logging_yaml): - print(logging_config_content[logging_yaml]) state = workflow.State.make_temp() diff --git a/activitysim/core/test/test_los.py b/activitysim/core/test/test_los.py index 00372a53ef..fdb241ba6c 100644 --- a/activitysim/core/test/test_los.py +++ b/activitysim/core/test/test_los.py @@ -15,7 +15,6 @@ def add_canonical_dirs(configs_dir_name): - state = workflow.State() configs_dir = os.path.join(os.path.dirname(__file__), f"los/{configs_dir_name}") data_dir = os.path.join(os.path.dirname(__file__), f"los/data") @@ -30,7 +29,6 @@ def add_canonical_dirs(configs_dir_name): def test_legacy_configs(): - state = add_canonical_dirs("configs_legacy_settings").load_settings() with pytest.raises(exceptions.SettingsFileNotFoundError): @@ -42,7 +40,6 @@ def test_legacy_configs(): def test_one_zone(): - state = add_canonical_dirs("configs_1z").load_settings() network_los = los.Network_LOS(state) @@ -88,7 +85,6 @@ def test_one_zone(): def test_two_zone(): - state = add_canonical_dirs("configs_2z").load_settings() network_los = los.Network_LOS(state) @@ -138,7 +134,6 @@ def test_two_zone(): def test_three_zone(): - state = add_canonical_dirs("configs_3z").load_settings() network_los = los.Network_LOS(state) @@ -163,7 +158,6 @@ def test_three_zone(): def test_30_minute_windows(): - state = add_canonical_dirs("configs_test_misc").default_settings() network_los = los.Network_LOS(state, los_settings_file_name="settings_30_min.yaml") @@ -180,7 +174,6 @@ def test_30_minute_windows(): def test_60_minute_windows(): - state = add_canonical_dirs("configs_test_misc").default_settings() network_los = los.Network_LOS(state, los_settings_file_name="settings_60_min.yaml") @@ -197,7 +190,6 @@ def test_60_minute_windows(): def test_1_week_time_window(): - state = add_canonical_dirs("configs_test_misc").default_settings() network_los = los.Network_LOS(state, los_settings_file_name="settings_1_week.yaml") @@ -228,7 +220,6 @@ def test_1_week_time_window(): def test_skim_time_periods_future_warning(): - state = add_canonical_dirs("configs_test_misc").default_settings() with pytest.warns(FutureWarning) as warning_test: diff --git a/activitysim/core/test/test_pipeline.py b/activitysim/core/test/test_pipeline.py index e061fdbb92..dfa6d770a8 100644 --- a/activitysim/core/test/test_pipeline.py +++ b/activitysim/core/test/test_pipeline.py @@ -18,7 +18,6 @@ @pytest.fixture def state(): - configs_dir = os.path.join(os.path.dirname(__file__), "configs") output_dir = os.path.join(os.path.dirname(__file__), "output") data_dir = os.path.join(os.path.dirname(__file__), "data") @@ -38,7 +37,6 @@ def state(): def close_handlers(): - loggers = logging.Logger.manager.loggerDict for name in loggers: logger = logging.getLogger(name) @@ -49,7 +47,6 @@ def close_handlers(): # @pytest.mark.filterwarnings('ignore::tables.NaturalNameWarning') def test_pipeline_run(state): - # workflow.step(steps.step1, step_name="step1") # workflow.step(steps.step2, step_name="step2") # workflow.step(steps.step3, step_name="step3") @@ -93,7 +90,6 @@ def test_pipeline_run(state): def test_pipeline_checkpoint_drop(state): - # workflow.step(steps.step1, step_name="step1") # workflow.step(steps.step2, step_name="step2") # workflow.step(steps.step3, step_name="step3") diff --git a/activitysim/core/test/test_random.py b/activitysim/core/test/test_random.py index 4a461811fa..63809278c1 100644 --- a/activitysim/core/test/test_random.py +++ b/activitysim/core/test/test_random.py @@ -11,7 +11,6 @@ def test_basic(): - rng = random.Random() rng.set_base_seed(0) @@ -34,7 +33,6 @@ def test_basic(): def test_channel(): - channels = { "households": "household_id", "persons": "person_id", diff --git a/activitysim/core/test/test_simulate.py b/activitysim/core/test/test_simulate.py index 9647b49454..17d4ba2cd6 100644 --- a/activitysim/core/test/test_simulate.py +++ b/activitysim/core/test/test_simulate.py @@ -43,7 +43,6 @@ def data(data_dir): def test_read_model_spec(state, spec_name): - spec = state.filesystem.read_model_spec(file_name=spec_name) assert len(spec) == 4 @@ -53,7 +52,6 @@ def test_read_model_spec(state, spec_name): def test_eval_variables(state, spec, data): - result = simulate.eval_variables(state, spec.index, data) expected = pd.DataFrame( @@ -72,7 +70,6 @@ def test_eval_variables(state, spec, data): def test_simple_simulate(state, data, spec): - state.settings.check_for_variability = False choices = simulate.simple_simulate(state, choosers=data, spec=spec, nest_spec=None) @@ -81,7 +78,6 @@ def test_simple_simulate(state, data, spec): def test_simple_simulate_chunked(state, data, spec): - state.settings.check_for_variability = False state.settings.chunk_size = 2 choices = simulate.simple_simulate( diff --git a/activitysim/core/test/test_skim.py b/activitysim/core/test/test_skim.py index ff6d0a9d19..d497a8656f 100644 --- a/activitysim/core/test/test_skim.py +++ b/activitysim/core/test/test_skim.py @@ -22,7 +22,6 @@ def __init__(self): def test_skims(data): - # ROW_MAJOR_LAYOUT omx_shape = (10, 10) num_skims = 2 @@ -61,7 +60,6 @@ def test_skims(data): def test_3dskims(data): - # ROW_MAJOR_LAYOUT omx_shape = (10, 10) num_skims = 2 diff --git a/activitysim/core/test/test_timetable.py b/activitysim/core/test/test_timetable.py index 576217ced7..a7295458f5 100644 --- a/activitysim/core/test/test_timetable.py +++ b/activitysim/core/test/test_timetable.py @@ -15,7 +15,6 @@ @pytest.fixture def persons(): - df = pd.DataFrame(index=list(range(6))) return df @@ -55,11 +54,9 @@ def tdd_alts(): def test_basic(persons, tdd_alts): - state = workflow.State().default_settings() with chunk.chunk_log(state, "test_basic", base=True): - person_windows = tt.create_timetable_windows(persons, tdd_alts) timetable = tt.TimeTable(person_windows, tdd_alts, "person_windows") diff --git a/activitysim/core/test/test_tracing.py b/activitysim/core/test/test_tracing.py index 8ae27add1c..ab97fcfa4c 100644 --- a/activitysim/core/test/test_tracing.py +++ b/activitysim/core/test/test_tracing.py @@ -13,7 +13,6 @@ def close_handlers(): - loggers = logging.Logger.manager.loggerDict for name in loggers: logger = logging.getLogger(name) @@ -23,7 +22,6 @@ def close_handlers(): def add_canonical_dirs(): - state = workflow.State() configs_dir = os.path.join(os.path.dirname(__file__), "configs") @@ -42,7 +40,6 @@ def add_canonical_dirs(): def test_config_logger(capsys): - state = add_canonical_dirs() state.logging.config_logger() @@ -81,7 +78,6 @@ def test_config_logger(capsys): def test_print_summary(capsys): - state = add_canonical_dirs() state.logging.config_logger() @@ -101,7 +97,6 @@ def test_print_summary(capsys): def test_register_households(capsys): - state = add_canonical_dirs() state.load_settings() @@ -130,7 +125,6 @@ def test_register_households(capsys): def test_register_tours(capsys): - state = add_canonical_dirs().load_settings() state.logging.config_logger() @@ -178,7 +172,6 @@ def test_register_tours(capsys): def test_write_csv(capsys): - state = add_canonical_dirs() state.logging.config_logger() @@ -196,7 +189,6 @@ def test_write_csv(capsys): def test_slice_ids(): - df = pd.DataFrame({"household_id": [1, 2, 3]}, index=[11, 12, 13]) # slice by named column @@ -214,7 +206,6 @@ def test_slice_ids(): def test_basic(capsys): - close_handlers() state = add_canonical_dirs() diff --git a/activitysim/core/test/test_util.py b/activitysim/core/test/test_util.py index 415ec1f9ee..940c9a081d 100644 --- a/activitysim/core/test/test_util.py +++ b/activitysim/core/test/test_util.py @@ -7,7 +7,7 @@ import pandas.testing as pdt import pytest -from ..util import other_than, quick_loc_df, quick_loc_series, reindex, df_from_dict +from ..util import df_from_dict, other_than, quick_loc_df, quick_loc_series, reindex @pytest.fixture(scope="module") @@ -41,7 +41,6 @@ def test_reindex(): def test_quick_loc_df(): - df = pd.DataFrame({"attrib": ["1", "2", "3", "4", "5"]}, index=[1, 2, 3, 4, 5]) loc_list = np.asanyarray([2, 1, 3, 4, 4, 5, 1]) @@ -54,7 +53,6 @@ def test_quick_loc_df(): def test_quick_loc_series(): - series = pd.Series(["1", "2", "3", "4", "5"], index=[1, 2, 3, 4, 5]) loc_list = np.asanyarray([2, 1, 3, 4, 4, 5, 1]) @@ -65,7 +63,6 @@ def test_quick_loc_series(): def test_df_from_dict(): - index = [1, 2, 3, 4, 5] df = pd.DataFrame({"attrib": [1, 2, 2, 3, 1]}, index=index) diff --git a/activitysim/core/timetable.py b/activitysim/core/timetable.py index 85ecc69544..5743aeef0a 100644 --- a/activitysim/core/timetable.py +++ b/activitysim/core/timetable.py @@ -176,7 +176,6 @@ def _available_run_length_2( available[0] = 0 available[-1] = 0 for row in range(num_rows): - row_ix = window_row_mapper[window_row_id_values[row]] window_row = windows[row_ix] for j in range(1, num_cols - 1): @@ -205,7 +204,6 @@ def _available_run_length_2( def tour_map(persons, tours, tdd_alts, persons_id_col="person_id"): - sigil = { "empty": " ", "overlap": "+++", @@ -251,7 +249,6 @@ def tour_map(persons, tours, tdd_alts, persons_id_col="person_id"): window_periods_df = pd.DataFrame(data=window_periods, index=tdd_alts.index) for keys, nth_tours in tours.groupby(["tour_type", "tour_type_num"], sort=True): - tour_type = keys[0] tour_sigil = sigil[tour_type] @@ -430,7 +427,6 @@ def slice_windows_by_row_id(self, window_row_ids): return windows def slice_windows_by_row_id_and_period(self, window_row_ids, periods): - # row ixs of tour_df group rows in windows row_ixs = self.window_row_ix.apply_to(window_row_ids) @@ -442,7 +438,6 @@ def slice_windows_by_row_id_and_period(self, window_row_ids, periods): return windows def get_windows_df(self): - # It appears that assignments into windows write through to underlying pandas table. # because we set windows = windows_df.values, and since all the columns are the same type # so no need to refresh pandas dataframe, but if we had to it would go here @@ -611,14 +606,12 @@ def assign_footprints(self, window_row_ids, footprints): self.windows[row_ixs] = np.bitwise_or(self.windows[row_ixs], footprints) def pairwise_available(self, window1_row_ids, window2_row_ids): - available1 = (self.slice_windows_by_row_id(window1_row_ids) != I_MIDDLE) * 1 available2 = (self.slice_windows_by_row_id(window2_row_ids) != I_MIDDLE) * 1 return available1 * available2 def individually_available(self, window_row_ids): - return (self.slice_windows_by_row_id(window_row_ids) != I_MIDDLE) * 1 def adjacent_window_run_length(self, window_row_ids, periods, before): diff --git a/activitysim/core/workflow/logging.py b/activitysim/core/workflow/logging.py index 5f0ddd6fb3..c800ca294a 100644 --- a/activitysim/core/workflow/logging.py +++ b/activitysim/core/workflow/logging.py @@ -128,7 +128,6 @@ def config_logger(self, basic=False): logger.log(basic, "Configured logging using basicConfig") def rotate_log_directory(self): - output_dir = self._obj.filesystem.get_output_dir() log_dir = output_dir.joinpath("log") if not log_dir.exists(): diff --git a/activitysim/core/workflow/tracing.py b/activitysim/core/workflow/tracing.py index 384e10f59b..580c6fad9b 100644 --- a/activitysim/core/workflow/tracing.py +++ b/activitysim/core/workflow/tracing.py @@ -506,18 +506,19 @@ def interaction_trace_rows(self, interaction_df, choosers, sample_size=None): traceable_table_ids = self.traceable_table_ids - # Determine whether actual tables or proto_ tables for disaggregate accessibilities - persons_table_name = set(traceable_table_ids).intersection( - ["persons", "proto_persons"] - ) - households_table_name = set(traceable_table_ids).intersection( - ["households", "proto_households"] + # trace proto tables if they exist, otherwise trace actual tables + # proto tables are used for disaggregate accessibilities and + # are removed from the traceable_table_ids after the accessibilities are created + households_table_name = ( + "proto_households" + if "proto_households" in traceable_table_ids.keys() + else "households" ) - assert len(persons_table_name) == 1 and len(persons_table_name) == 1 - persons_table_name, households_table_name = ( - persons_table_name.pop(), - households_table_name.pop(), + persons_table_name = ( + "proto_persons" + if "proto_persons" in traceable_table_ids.keys() + else "persons" ) if ( diff --git a/activitysim/estimation/larch/__init__.py b/activitysim/estimation/larch/__init__.py index 76d1cb8e9c..f1baa2404e 100644 --- a/activitysim/estimation/larch/__init__.py +++ b/activitysim/estimation/larch/__init__.py @@ -1,6 +1,7 @@ from __future__ import annotations -import larch as lx +from typing import Iterable + from packaging.version import Version from .cdap import * @@ -13,14 +14,50 @@ from .simple_simulate import * from .stop_frequency import * -# require larch version 6.0.0 or later -if Version(larch.__version__) < Version("6.0.0"): - raise ImportError( - f"activitysim estimation mode requires larch version 6.0.0 or later. Found {larch.__version__}" - ) +try: + import larch as lx +except ImportError: + lx = None +else: + # if larch is installed, require larch version 6.0.0 or later + if Version(lx.__version__) < Version("6.0.0"): + # when installed from source without a full git history including version + # tags, sometimes development versions of larch default to version 0.1.devX + if not lx.__version__.startswith("0.1.dev"): + raise ImportError( + f"activitysim estimation mode requires larch version 6.0.0 or later. Found {lx.__version__}" + ) + + +def component_model(name: str | Iterable[str], *args, **kwargs): + """ + Load a component model from the estimation data bundle (EDB). + Parameters + ---------- + name : str or iterable of str + The name of the model to load. If an iterable is provided, a ModelGroup + will be returned, which will be the collection of models named. + *args, **kwargs + Additional arguments and keyword arguments to pass to the model constructor. + Usually these will include `edb_directory` (a path to the EDB directory), + and `return_data` (a boolean indicating whether to return the data objects. -def component_model(name, *args, **kwargs): + Returns + ------- + Model or ModelGroup + The loaded model or ModelGroup. + Dict or list[Dict], optional + The data objects associated with the model. If `return_data` is True, this may + include the coefficients, chooser data, and alternative values, and possibly + other data objects depending on the model. If `name` is a single string, a + single data object will be returned. If `name` is an iterable, a list of data + objects will be returned, one for each model in the ModelGroup. Note these + data objects are primarily for the user to review, and are not the same + objects used by the Model or ModelGroup for estimation. If some data transformation + or manipulation is needed, it should be done on the data embedded in the + Model(s). + """ if isinstance(name, str): m = globals().get(f"{name}_model") if m: diff --git a/activitysim/estimation/larch/cdap.py b/activitysim/estimation/larch/cdap.py index 018c6976da..8944c5c8b5 100644 --- a/activitysim/estimation/larch/cdap.py +++ b/activitysim/estimation/larch/cdap.py @@ -7,18 +7,24 @@ import re from pathlib import Path -import larch import numpy as np import pandas as pd import xarray as xr import yaml -from larch import Dataset, Model, P, X -from larch.model.model_group import ModelGroup -from larch.util import Dict from ...abm.models.util import cdap from .general import apply_coefficients, explicit_value_parameters +try: + import larch as lx +except ImportError: + lx = None + logger_name = "larch" +else: + from larch import P, X + from larch.util import Dict + + _logger = logging.getLogger("larch") MAX_HHSIZE = 5 @@ -151,7 +157,6 @@ def interact_pattern(n_persons, select_persons, tag): def cdap_interaction_utility(model, n_persons, alts, interaction_coef, coefficients): - person_numbers = list(range(1, n_persons + 1)) matcher = re.compile("coef_[HMN]_.*") @@ -329,12 +334,12 @@ def cdap_split_data(households, values, add_joint): return cdap_data -def cdap_dataframes(households, values, add_joint) -> dict[int, Dataset]: +def cdap_dataframes(households, values, add_joint) -> dict[int, lx.Dataset]: data = cdap_split_data(households, values, add_joint) dfs = {} for hhsize in data.keys(): alts = generate_alternatives(hhsize, add_joint) - dfs[hhsize] = Dataset.construct.from_idco( + dfs[hhsize] = lx.Dataset.construct.from_idco( data[hhsize], alts=dict(zip(alts.values(), alts.keys())), ) @@ -355,33 +360,6 @@ def cdap_dataframes(households, values, add_joint) -> dict[int, Dataset]: return dfs -# def _cdap_model(households, values, spec1, interaction_coef, coefficients): -# cdap_data = cdap_dataframes(households, values) -# m = {} -# _logger.info(f"building for model 1") -# m[1] = Model(dataservice=cdap_data[1]) -# cdap_base_utility_by_person(m[1], n_persons=1, spec=spec1) -# m[1].choice_any = True -# m[1].availability_any = True -# -# # Add cardinality into interaction_coef if not present -# if 'cardinality' not in interaction_coef: -# interaction_coef['cardinality'] = interaction_coef['interaction_ptypes'].str.len() -# for s in [2, 3, 4, 5]: -# _logger.info(f"building for model {s}") -# m[s] = Model(dataservice=cdap_data[s]) -# alts = generate_alternatives(s) -# cdap_base_utility_by_person(m[s], s, spec1, alts, values.columns) -# cdap_interaction_utility(m[s], s, alts, interaction_coef, coefficients) -# m[s].choice_any = True -# m[s].availability_any = True -# -# result = ModelGroup(m.values()) -# explicit_value_parameters(result) -# apply_coefficients(coefficients, result) -# return result - - def cdap_data( name="cdap", edb_directory="output/estimation_data_bundle/{name}/", @@ -515,7 +493,7 @@ def cdap_model( cdap_dfs = cdap_dataframes(households, values, add_joint) m = {} _logger.info(f"building for model 1") - m[1] = Model(datatree=cdap_dfs[1], compute_engine="numba") + m[1] = lx.Model(datatree=cdap_dfs[1], compute_engine="numba") cdap_base_utility_by_person(m[1], n_persons=1, spec=spec1) m[1].choice_co_code = "override_choice" m[1].availability_any = True @@ -528,7 +506,7 @@ def cdap_model( for s in range(2, MAX_HHSIZE + 1): # for s in [2, 3, 4, 5]: _logger.info(f"building for model {s}") - m[s] = Model(datatree=cdap_dfs[s]) + m[s] = lx.Model(datatree=cdap_dfs[s]) alts = generate_alternatives(s, add_joint) cdap_base_utility_by_person(m[s], s, spec1, alts, values.columns) cdap_interaction_utility(m[s], s, alts, interaction_coef, coefficients) @@ -537,7 +515,7 @@ def cdap_model( m[s].choice_co_code = "override_choice" m[s].availability_any = True - model = ModelGroup(m.values()) + model = lx.ModelGroup(m.values()) explicit_value_parameters(model) apply_coefficients(coefficients, model) if return_data: diff --git a/activitysim/estimation/larch/general.py b/activitysim/estimation/larch/general.py index 19fb76e18a..cfb81c756b 100644 --- a/activitysim/estimation/larch/general.py +++ b/activitysim/estimation/larch/general.py @@ -7,12 +7,17 @@ import numpy as np import pandas as pd -from larch import Model, P, X # noqa: F401 -# from larch.log import logger_name -# from larch.model.abstract_model import AbstractChoiceModel -from larch.model.tree import NestingTree -from larch.util import Dict # noqa: F401 +try: + # Larch is an optional dependency, and we don't want to fail when importing + # this module simply because larch is not installed. + import larch as lx +except ImportError: + lx = None +else: + from larch import Model, P, X # noqa: F401 + from larch.model.tree import NestingTree + from larch.util import Dict # noqa: F401 _logger = logging.getLogger("larch") diff --git a/activitysim/estimation/larch/location_choice.py b/activitysim/estimation/larch/location_choice.py index 7d797a754e..784ce4f124 100644 --- a/activitysim/estimation/larch/location_choice.py +++ b/activitysim/estimation/larch/location_choice.py @@ -11,8 +11,6 @@ import numpy as np import pandas as pd import yaml -from larch import Dataset, Model, P, X -from larch.util import Dict from .general import ( apply_coefficients, @@ -24,6 +22,15 @@ str_repr, ) +try: + # Larch is an optional dependency, and we don't want to fail when importing + # this module simply because larch is not installed. + import larch as lx +except ImportError: + lx = None +else: + from larch.util import Dict + def size_coefficients_from_spec(size_spec): size_coef = size_spec.stack().reset_index() @@ -71,7 +78,58 @@ def location_choice_model( chunking_size=None, *, alts_in_cv_format=False, -) -> Model | tuple[Model, LocationChoiceData]: + availability_expression=None, +) -> lx.Model | tuple[lx.Model, LocationChoiceData]: + """ + Construct a location choice model from the estimation data bundle. + + Parameters + ---------- + name : str, optional + The name of the location choice model. The default is "workplace_location". + edb_directory : str, optional + The directory containing the estimation data bundle. The default is + "output/estimation_data_bundle/{name}/", where "{name}" is the name of + the model (see above). + coefficients_file : str, optional + The name of the coefficients file. The default is "{name}_coefficients.csv", + where "{name}" is the name of the model (see above). + spec_file : str, optional + The name of the spec file. The default is "{name}_SPEC.csv", where "{name}" + is the name of the model (see above). + size_spec_file : str, optional + The name of the size spec file. The default is "{name}_size_terms.csv", where + "{name}" is the name of the model (see above). + alt_values_file : str, optional + The name of the alternative values file. The default is + "{name}_alternatives_combined.csv", where "{name}" is the name of the model + (see above). + chooser_file : str, optional + The name of the chooser file. The default is "{name}_choosers_combined.csv", + where "{name}" is the name of the model (see above). + settings_file : str, optional + The name of the settings file. The default is "{name}_model_settings.yaml", + where "{name}" is the name of the model (see above). + landuse_file : str, optional + The name of the land use file. The default is "{name}_landuse.csv", where + "{name}" is the name of the model (see above). + return_data : bool, optional + If True, return a tuple containing the model and the location choice data. + The default is False, which returns only the model. + alt_values_to_feather : bool, default False + If True, convert the alternative values to a feather file. + chunking_size : int, optional + The number of rows per chunk for processing the alternative values. The default + is None, which processes all rows at once. + alts_in_cv_format : bool, default False + If True, the alternatives are in CV format. The default is False. + availability_expression : str, optional + The name of the availability expression. This is the "Label" from the + spec file that identifies an expression that evaluates truthy (non-zero) + if the alternative is available, and falsey otherwise. If not provided, + the code will attempt to infer the availability expression from the + expressions, but this is not reliable. The default is None. + """ model_selector = name.replace("_location", "") model_selector = model_selector.replace("_destination", "") model_selector = model_selector.replace("_subtour", "") @@ -340,7 +398,14 @@ def split(a, n): choice_def = {"choice_ca_var": "override_choice == _original_zone_id"} # Availability of choice zones - if "util_no_attractions" in x_ca_1: + if availability_expression is not None and availability_expression in x_ca_1: + av = ( + x_ca_1[availability_expression] + .apply(lambda x: False if x == 1 else True) + .astype(np.int8) + .to_xarray() + ) + elif "util_no_attractions" in x_ca_1: av = ( x_ca_1["util_no_attractions"] .apply(lambda x: False if x == 1 else True) @@ -367,13 +432,13 @@ def split(a, n): assert len(x_co) > 0, "Empty chooser dataframe" assert len(x_ca_1) > 0, "Empty alternatives dataframe" - d_ca = Dataset.construct.from_idca(x_ca_1) - d_co = Dataset.construct.from_idco(x_co) + d_ca = lx.Dataset.construct.from_idca(x_ca_1) + d_co = lx.Dataset.construct.from_idco(x_co) d = d_ca.merge(d_co) if av is not None: d["_avail_"] = av - m = Model(datatree=d, compute_engine="numba") + m = lx.Model(datatree=d, compute_engine="numba") # One of the alternatives might be coded as 0, so # we need to explicitly initialize the MNL nesting graph @@ -422,16 +487,16 @@ def split(a, n): if CHOOSER_SEGMENT_COLUMN_NAME is None: assert len(size_spec) == 1 m.quantity_ca = sum( - P(f"{i}_{q}") * X(q) + lx.P(f"{i}_{q}") * lx.X(q) for i in size_spec.index for q in size_spec.columns if size_spec.loc[i, q] != 0 ) else: m.quantity_ca = sum( - P(f"{i}_{q}") - * X(q) - * X(f"{CHOOSER_SEGMENT_COLUMN_NAME}=={str_repr(SEGMENT_IDS[i])}") + lx.P(f"{i}_{q}") + * lx.X(q) + * lx.X(f"{CHOOSER_SEGMENT_COLUMN_NAME}=={str_repr(SEGMENT_IDS[i])}") for i in size_spec.index for q in size_spec.columns if size_spec.loc[i, q] != 0 diff --git a/activitysim/estimation/larch/mode_choice.py b/activitysim/estimation/larch/mode_choice.py index 5e15fd0e0a..4f9e17b7ca 100644 --- a/activitysim/estimation/larch/mode_choice.py +++ b/activitysim/estimation/larch/mode_choice.py @@ -8,8 +8,6 @@ import pandas as pd import xarray as xr import yaml -from larch import Dataset, Model, P, X -from larch.util import Dict from .general import ( apply_coefficients, @@ -21,6 +19,15 @@ ) from .simple_simulate import construct_availability, simple_simulate_data +try: + # Larch is an optional dependency, and we don't want to fail when importing + # this module simply because larch is not installed. + import larch as lx +except ImportError: + lx = None +else: + from larch.util import Dict + def mode_choice_model( name, @@ -58,7 +65,7 @@ def mode_choice_model( # Setup purpose specific models m = { - purpose: Model(graph=tree, title=purpose, compute_engine="numba") + purpose: lx.Model(graph=tree, title=purpose, compute_engine="numba") for purpose in purposes } for alt_code, alt_name in tree.elemental_names().items(): @@ -72,7 +79,7 @@ def mode_choice_model( for purpose in purposes: # Modify utility function based on template for purpose u_purp = sum( - (P(coef_template[purpose].get(i.param, i.param)) * i.data * i.scale) + (lx.P(coef_template[purpose].get(i.param, i.param)) * i.data * i.scale) for i in u ) m[purpose].utility_co[alt_code] = u_purp @@ -86,7 +93,7 @@ def mode_choice_model( m[purposes[0]], chooser_data, data.alt_codes_to_names ) - d = Dataset.construct.from_idco( + d = lx.Dataset.construct.from_idco( chooser_data, alts=dict(zip(data.alt_codes, data.alt_names)) ) d["_avail_"] = xr.DataArray(avail, dims=(d.dc.CASEID, d.dc.ALTID)) @@ -100,9 +107,7 @@ def mode_choice_model( model.datatree = d model.choice_co_code = "override_choice_code" - from larch.model.model_group import ModelGroup - - mg = ModelGroup(m.values()) + mg = lx.ModelGroup(m.values()) explicit_value_parameters(mg) apply_coefficients(coefficients, mg) diff --git a/activitysim/estimation/larch/nonmand_tour_freq.py b/activitysim/estimation/larch/nonmand_tour_freq.py index 0986e63838..90c56ecedb 100644 --- a/activitysim/estimation/larch/nonmand_tour_freq.py +++ b/activitysim/estimation/larch/nonmand_tour_freq.py @@ -9,8 +9,6 @@ import pandas as pd import yaml -from larch import Dataset, Model -from larch.util import Dict from .general import ( apply_coefficients, @@ -19,6 +17,16 @@ remove_apostrophes, ) +try: + # Larch is an optional dependency, and we don't want to fail when importing + # this module simply because larch is not installed. + import larch as lx +except ImportError: + lx = None +else: + from larch.util import Dict + + _logger = logging.getLogger("larch") @@ -160,6 +168,9 @@ def unavail(model, x_ca): unav = x_ca[lock_data[0]] > 0 for j in lock_data[1:]: unav |= x_ca[j] > 0 + else: + # no unavailability parameters are included + return pd.DataFrame(0, index=x_ca.index, columns=["_avail_"]) return unav @@ -284,7 +295,7 @@ def nonmand_tour_freq_model( m = {} for segment_name in segment_names: print(f"Creating larch model for {segment_name}") - segment_model = m[segment_name] = Model(compute_engine="numba") + segment_model = m[segment_name] = lx.Model(compute_engine="numba") # One of the alternatives is coded as 0, so # we need to explicitly initialize the MNL nesting graph # and set to root_id to a value other than zero. @@ -318,13 +329,13 @@ def nonmand_tour_freq_model( else: x_ca = alt_values[segment_name].set_index(["person_id", "alt_id"]) - d_co = Dataset.construct.from_idco( + d_co = lx.Dataset.construct.from_idco( x_co, alts=alt_def.index.rename("alt_id"), ) x_ca["_avail_"] = ~unavail(segment_model, x_ca) # we set crack to False here so that we do not dissolve zero variance IDCAs - d_ca = Dataset.construct.from_idca(x_ca, crack=False) + d_ca = lx.Dataset.construct.from_idca(x_ca, crack=False) d = d_ca.merge(d_co) m[segment_name].datatree = d m[segment_name].availability_ca_var = "_avail_" diff --git a/activitysim/estimation/larch/scheduling.py b/activitysim/estimation/larch/scheduling.py index 74d87e8af5..5ef4a72a98 100644 --- a/activitysim/estimation/larch/scheduling.py +++ b/activitysim/estimation/larch/scheduling.py @@ -7,8 +7,6 @@ import numpy as np import pandas as pd import yaml -from larch import Dataset, Model, P, X -from larch.util import Dict from .general import ( apply_coefficients, @@ -20,6 +18,16 @@ str_repr, ) +try: + # Larch is an optional dependency, and we don't want to fail when importing + # this module simply because larch is not installed. + import larch as lx +except ImportError: + lx = None +else: + from larch import P, X + from larch.util import Dict + def schedule_choice_model( name, @@ -102,7 +110,7 @@ def _read_csv(filename, optional=False, **kwargs): else: raise ValueError("cannot find Label or Expression in spec file") - m = Model(compute_engine="numba") + m = lx.Model(compute_engine="numba") if len(spec.columns) == 4 and ( [c.lower() for c in spec.columns] == ["label", "description", "expression", "coefficient"] @@ -174,12 +182,12 @@ def _read_csv(filename, optional=False, **kwargs): joint_avail = None # d = DataFrames(co=x_co, ca=x_ca, av=joint_avail) # larch 5.7 - d_ca = Dataset.construct.from_idca(x_ca) + d_ca = lx.Dataset.construct.from_idca(x_ca) if joint_avail == "~(mode_choice_logsum_missing)": tmp = np.isnan(d_ca["mode_choice_logsum"]) tmp = tmp.drop_vars(tmp.coords) d_ca = d_ca.assign(mode_choice_logsum_missing=tmp) - d_co = Dataset.construct.from_idco(x_co) + d_co = lx.Dataset.construct.from_idco(x_co) d = d_ca.merge(d_co) # if joint_avail is not None: # d["_avail_"] = joint_avail diff --git a/activitysim/estimation/larch/simple_simulate.py b/activitysim/estimation/larch/simple_simulate.py index f75d9642cb..30a9defffb 100644 --- a/activitysim/estimation/larch/simple_simulate.py +++ b/activitysim/estimation/larch/simple_simulate.py @@ -4,12 +4,9 @@ import os from pathlib import Path -import larch import numpy as np import pandas as pd import yaml -from larch import Model -from larch.util import Dict from .general import ( apply_coefficients, @@ -18,6 +15,15 @@ remove_apostrophes, ) +try: + # Larch is an optional dependency, and we don't want to fail when importing + # this module simply because larch is not installed. + import larch as lx +except ImportError: + lx = None +else: + from larch.util import Dict + def construct_availability(model, chooser_data, alt_codes_to_names): """ @@ -193,7 +199,7 @@ def simple_simulate_model( else: tree = construct_nesting_tree(data.alt_names_to_codes, {}) - m = Model(compute_engine="numba") + m = lx.Model(compute_engine="numba") m.utility_co = dict_of_linear_utility_from_spec( spec, "Label", @@ -206,13 +212,13 @@ def simple_simulate_model( if construct_avail: avail = construct_availability(m, chooser_data, data.alt_codes_to_names) - d = larch.Dataset.construct.from_idco( + d = lx.Dataset.construct.from_idco( pd.concat([chooser_data, avail], axis=1), alts=dict(zip(alt_codes, alt_names, strict=False)), ) else: avail = True - d = larch.Dataset.construct.from_idco( + d = lx.Dataset.construct.from_idco( chooser_data, alts=dict(zip(alt_codes, alt_names, strict=False)) ) diff --git a/activitysim/estimation/larch/stop_frequency.py b/activitysim/estimation/larch/stop_frequency.py index 17c8bd5050..dea82de5a9 100644 --- a/activitysim/estimation/larch/stop_frequency.py +++ b/activitysim/estimation/larch/stop_frequency.py @@ -16,6 +16,15 @@ remove_apostrophes, ) +try: + # Larch is an optional dependency, and we don't want to fail when importing + # this module simply because larch is not installed. + import larch as lx +except ImportError: + lx = None +else: + from larch.util import Dict + def stop_frequency_data( edb_directory="output/estimation_data_bundle/{name}/", @@ -183,7 +192,6 @@ def stop_frequency_model( models = [] for n in range(len(data.spec)): - coefficients = data.coefficients # coef_template = data.coef_template # not used spec = data.spec[n] @@ -220,12 +228,6 @@ def stop_frequency_model( d = Dataset.construct.from_idco( chooser_data, alts=dict(zip(alt_codes, alt_names)) ) - # d = DataFrames( - # co=chooser_data, - # av=avail, - # alt_codes=alt_codes, - # alt_names=alt_names, - # ) m.datatree = d m.choice_co_code = "override_choice_code" diff --git a/activitysim/estimation/test/test_larch_estimation.py b/activitysim/estimation/test/test_larch_estimation.py index c0ed4a44d3..2d2427c41b 100644 --- a/activitysim/estimation/test/test_larch_estimation.py +++ b/activitysim/estimation/test/test_larch_estimation.py @@ -91,7 +91,7 @@ def test_simple_simulate(est_data, num_regression, dataframe_regression, name, m ("non_mandatory_tour_destination", "SLSQP", None), ("atwork_subtour_destination", "BHHH", None), ("trip_destination", "BHHH", None), - # ("trip_destination", "SLSQP", 0.12), + ("trip_destination", "SLSQP", None), # trip_destination model has unusual parameter variance on a couple # parameters when switching platforms, possibly related to default data # types and high standard errors. Most parameters and the overall @@ -105,6 +105,13 @@ def test_location_model( from activitysim.estimation.larch import component_model, update_size_spec m, data = component_model(name, return_data=True) + + if name == "trip_destination": + # this model is overspecified in the example, so we need to lock a + # parameter to make it identifiable. + m.lock_value("coef_prox_dest_outbound_work", 0.0) + m.set_cap(25.0) + m.doctor(repair_av_zq="-", repair_nan_utility=True) loglike_prior = m.loglike() r = m.maximize_loglike(method=method, options={"maxiter": 1000, "ftol": 1.0e-8}) diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_loglike.csv index b6a4640e0d..83144fe122 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_loglike.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_BHHH_loglike.csv @@ -1,2 +1,2 @@ ,loglike_prior,loglike_converge -0,-21837.014551855944,-8695.4742987000536 +0,-21855.73573427651,-8695.4742752868151 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_SLSQP_loglike.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_SLSQP_loglike.csv new file mode 100644 index 0000000000..a2e43ac4ff --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_SLSQP_loglike.csv @@ -0,0 +1,2 @@ +,loglike_prior,loglike_converge +0,-21855.73573427651,-8952.9587499637983 diff --git a/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_SLSQP_size_spec.csv b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_SLSQP_size_spec.csv new file mode 100644 index 0000000000..e3f4e0538d --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_loc_trip_destination_SLSQP_size_spec.csv @@ -0,0 +1,23 @@ +,segment,model_selector,TOTHH,RETEMPN,FPSEMPN,HEREMPN,OTHEMPN,AGREMPN,MWTEMPN,AGE0519,HSENROLL,COLLFTE,COLLPTE +0,work_low,workplace,0,0.12912912912912911,0.19319319319319317,0.38338338338338335,0.12012012012012011,0.01001001001001001,0.16416416416416416,0,0,0,0 +1,work_med,workplace,0,0.12012012012012012,0.19719719719719719,0.32532532532532532,0.13913913913913914,0.0080080080080080079,0.21021021021021019,0,0,0,0 +2,work_high,workplace,0,0.11,0.20699999999999999,0.28399999999999997,0.154,0.0060000000000000001,0.23899999999999999,0,0,0,0 +3,work_veryhigh,workplace,0,0.092999999999999999,0.27000000000000002,0.24099999999999999,0.14599999999999999,0.0040000000000000001,0.246,0,0,0,0 +4,university,school,0,0,0,0,0,0,0,0,0,0.59199999999999997,0.40799999999999997 +5,gradeschool,school,0,0,0,0,0,0,0,1,0,0,0 +6,highschool,school,0,0,0,0,0,0,0,0,1,0,0 +7,escort,non_mandatory,0,0.22500000000000001,0,0.14399999999999999,0,0,0,0.46500000000000002,0.16600000000000001,0,0 +8,shopping,non_mandatory,0,1,0,0,0,0,0,0,0,0,0 +9,eatout,non_mandatory,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 +10,othmaint,non_mandatory,0,0.48199999999999998,0,0.51800000000000002,0,0,0,0,0,0,0 +11,social,non_mandatory,0,0.52200000000000002,0,0.47799999999999998,0,0,0,0,0,0,0 +12,othdiscr,non_mandatory,0.25225225225225223,0.2122122122122122,0,0.2722722722722723,0.16516516516516516,0,0,0,0.098098098098098108,0,0 +13,atwork,atwork,0,0.74199999999999999,0,0.25800000000000001,0,0,0,0,0,0,0 +14,work,trip,0,0.74787786056587513,0.0018538038747582422,0.001853803876100025,0.0018538038747592663,0.24470692393187074,0.0018538038766366914,0,0,0,0 +15,escort,trip,4.4398622176416287e-05,0.0018145828132440462,0,0.00025862750482263144,0,0,0,0.97914326797093931,0.018739123088817596,0,0 +16,shopping,trip,0.28745937648450037,0.71254062351549963,0,0,0,0,0,0,0,0,0 +17,eatout,trip,0,0.99667048634136579,0,0.0033295136586341872,0,0,0,0,0,0,0 +18,othmaint,trip,0.16785550808846833,0.41607224595773862,0,0.41607224595379305,0,0,0,0,0,0,0 +19,social,trip,0.00044482261527767418,0.98033336959213913,0,0.019221807792583361,0,0,0,0,0,0,0 +20,othdiscr,trip,0.9406951398181691,0.022347626204726488,0,0.0092529765597407446,0.009252976559785164,0,0,0,0.018451280857578346,0,0 +21,univ,trip,0.16785550808973149,0,0,0,0,0,0,0,0,0.41607224595513576,0.41607224595513281 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_BHHH_None_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_BHHH_None_.csv index 23e3026cfb..6c9c6beb27 100644 --- a/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_BHHH_None_.csv +++ b/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_BHHH_None_.csv @@ -1,48 +1,48 @@ param_name,value,best,initvalue,nullvalue coef_UNAVAILABLE,-999,-999,-999,0 -coef_distance_joint,-0.30113542396064802,-0.30113542396064802,-0.12380000203847885,0 -coef_mode_choice_logsum,0.082682967088151746,0.082682967088151746,1.8209999799728394,0 +coef_distance_joint,-0.30113542071627925,-0.30113542071627925,-0.12380000203847885,0 +coef_mode_choice_logsum,0.082682969035499751,0.082682969035499751,1.8209999799728394,0 coef_one,1,1,1,0 -coef_prox_dest_outbound_work,6.4877761350612664,6.4877761350612664,-0.25999999046325684,0 -coef_prox_home_inbound_work,-0.42511543980575345,-0.42511543980575345,-0.15000000596046448,0 -coef_prox_home_outbound_work,6.4721898798728912,6.4721898798728912,-0.37999999523162842,0 -coef_util_distance_atwork,-0.12262386654203787,-0.12262386654203787,-0.12233459949493408,0 -coef_util_distance_eatout,-0.31527866138216842,-0.31527866138216842,-0.10289999842643738,0 -coef_util_distance_escort,-0.20896432406414306,-0.20896432406414306,-0.14910000562667847,0 -coef_util_distance_othdiscr,-0.32948687106831859,-0.32948687106831859,-0.12617222964763641,0 -coef_util_distance_othmaint,-0.18983651887636419,-0.18983651887636419,-0.096199996769428253,0 -coef_util_distance_school,-0.10589786663451535,-0.10589786663451535,-0.10559999942779541,0 -coef_util_distance_shopping,-0.31439120424553951,-0.31439120424553951,-0.11919999867677689,0 -coef_util_distance_social,-0.21252031645681738,-0.21252031645681738,-0.13289999961853027,0 -coef_util_distance_univ,-0.16366566512380015,-0.16366566512380015,-0.061299998313188553,0 -coef_util_distance_work_inbound,-6.9206223055934686,-6.9206223055934686,0.14781327545642853,0 -coef_util_distance_work_outbound,-0.15694164906466096,-0.15694164906466096,-0.049725916236639023,0 -eatout_HEREMPN,-819.1055252552693,-819.1055252552693,-1.3547956943511963,0 +coef_prox_dest_outbound_work,0,0,0,0 +coef_prox_home_inbound_work,-0.42511545535361761,-0.42511545535361761,-0.15000000596046448,0 +coef_prox_home_outbound_work,-0.015586316153796702,-0.015586316153796702,-0.37999999523162842,0 +coef_util_distance_atwork,-0.12233412535963523,-0.12233412535963523,-0.12233459949493408,0 +coef_util_distance_eatout,-0.31527860777732059,-0.31527860777732059,-0.10289999842643738,0 +coef_util_distance_escort,-0.20896432333181236,-0.20896432333181236,-0.14910000562667847,0 +coef_util_distance_othdiscr,-0.32948686834710317,-0.32948686834710317,-0.12617222964763641,0 +coef_util_distance_othmaint,-0.189836518023934,-0.189836518023934,-0.096199996769428253,0 +coef_util_distance_school,-0.10560055139570937,-0.10560055139570937,-0.10559999942779541,0 +coef_util_distance_shopping,-0.31439120387739444,-0.31439120387739444,-0.11919999867677689,0 +coef_util_distance_social,-0.21252031607377456,-0.21252031607377456,-0.13289999961853027,0 +coef_util_distance_univ,-0.16366566463671706,-0.16366566463671706,-0.061299998313188553,0 +coef_util_distance_work_inbound,-0.43284610617518143,-0.43284610617518143,0.14781327545642853,0 +coef_util_distance_work_outbound,-0.15694162700147077,-0.15694162700147077,-0.049725916236639023,0 +eatout_HEREMPN,-735.35391763180496,-735.35391763180496,-1.3547956943511963,0 eatout_RETEMPN,-0.29840603470802307,-0.29840603470802307,-0.29840603470802307,0 -escort_AGE0519,-34.168581928799881,-34.168581928799881,-0.76787072420120239,0 -escort_HEREMPN,-36.209681359186099,-36.209681359186099,-1.9379420280456543,0 -escort_HSENROLL,-35.504680589841293,-35.504680589841293,-1.7957675457000732,0 -escort_RETEMPN,-35.308657067519476,-35.308657067519476,-1.4916548728942871,0 +escort_AGE0519,-34.146330319047635,-34.146330319047635,-0.76787072420120239,0 +escort_HEREMPN,-36.185934740550735,-36.185934740550735,-1.9379420280456543,0 +escort_HSENROLL,-35.482441440764148,-35.482441440764148,-1.7957675457000732,0 +escort_RETEMPN,-35.28779133946658,-35.28779133946658,-1.4916548728942871,0 escort_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 -othdiscr_HEREMPN,-1590.2443769893835,-1590.2443769893835,-1.3019531965255737,0 -othdiscr_HSENROLL,-17.480780456151027,-17.480780456151027,-2.3227877616882324,0 -othdiscr_OTHEMPN,-4066.3792692241386,-4066.3792692241386,-1.8018097877502441,0 -othdiscr_RETEMPN,-4.8145886079817819,-4.8145886079817819,-1.5511690378189087,0 +othdiscr_HEREMPN,-1407.1767066933987,-1407.1767066933987,-1.3019531965255737,0 +othdiscr_HSENROLL,-16.410343601026089,-16.410343601026089,-2.3227877616882324,0 +othdiscr_OTHEMPN,-18880.507669912509,-18880.507669912509,-1.8018097877502441,0 +othdiscr_RETEMPN,-4.8145914198400339,-4.8145914198400339,-1.5511690378189087,0 othdiscr_TOTHH,-1.3783261775970459,-1.3783261775970459,-1.3783261775970459,0 -othmaint_HEREMPN,-33.040600275142353,-33.040600275142353,-0.65778005123138428,0 -othmaint_RETEMPN,-32.334391297442174,-32.334391297442174,-0.73188799619674683,0 +othmaint_HEREMPN,-33.024962428999153,-33.024962428999153,-0.65778005123138428,0 +othmaint_RETEMPN,-32.319889481391705,-32.319889481391705,-0.73188799619674683,0 othmaint_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 -shopping_RETEMPN,-27.336163711692908,-27.336163711692908,-0.0010005002841353416,0 +shopping_RETEMPN,-23.892728970934463,-23.892728970934463,-0.0010005002841353416,0 shopping_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 -social_HEREMPN,-40.099928545719862,-40.099928545719862,-0.73814451694488525,0 -social_RETEMPN,-38.683289277404818,-38.683289277404818,-0.65200525522232056,0 +social_HEREMPN,-40.084022821895907,-40.084022821895907,-0.73814451694488525,0 +social_RETEMPN,-38.668703835173424,-38.668703835173424,-0.65200525522232056,0 social_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 -univ_COLLFTE,-53.686637539870517,-53.686637539870517,-0.52424865961074829,0 -univ_COLLPTE,-18324.145024591242,-18324.145024591242,-0.89648813009262085,0 +univ_COLLFTE,-52.916360377104091,-52.916360377104091,-0.52424865961074829,0 +univ_COLLPTE,-19661.749288729949,-19661.749288729949,-0.89648813009262085,0 univ_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 -work_AGREMPN,-0.045746743293575393,-0.045746743293575393,0,0 -work_FPSEMPN,-334.44500929829275,-334.44500929829275,0,0 -work_HEREMPN,-11947.426957365406,-11947.426957365406,0,0 -work_MWTEMPN,-5.1249753110793721,-5.1249753110793721,0,0 -work_OTHEMPN,-26.746358353776838,-26.746358353776838,0,0 +work_AGREMPN,-0.045747060225834933,-0.045747060225834933,0,0 +work_FPSEMPN,-485.71888319359556,-485.71888319359556,0,0 +work_HEREMPN,-138.10600027993303,-138.10600027993303,0,0 +work_MWTEMPN,-5.1249743665982441,-5.1249743665982441,0,0 +work_OTHEMPN,-24.742530479368806,-24.742530479368806,0,0 work_RETEMPN,0,0,0,0 diff --git a/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_SLSQP_None_.csv b/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_SLSQP_None_.csv new file mode 100644 index 0000000000..00234b5079 --- /dev/null +++ b/activitysim/estimation/test/test_larch_estimation/test_location_model_trip_destination_SLSQP_None_.csv @@ -0,0 +1,48 @@ +param_name,value,best,initvalue,nullvalue +coef_UNAVAILABLE,-999,-999,-999,0 +coef_distance_joint,-0.33134844410661268,-0.33135365019482871,-0.12380000203847885,0 +coef_mode_choice_logsum,0.10404782558776673,0.10404902119734737,1.8209999799728394,0 +coef_one,1,1,1,0 +coef_prox_dest_outbound_work,0,0,0,0 +coef_prox_home_inbound_work,-0.43355983407617132,-0.43356515858610667,-0.15000000596046448,0 +coef_prox_home_outbound_work,-0.013630490468606973,-0.013630962107906125,-0.37999999523162842,0 +coef_util_distance_atwork,-0.12233459949493408,-0.12233459949493408,-0.12233459949493408,0 +coef_util_distance_eatout,-0.30369611711207345,-0.30370280168537217,-0.10289999842643738,0 +coef_util_distance_escort,-0.20130525011921385,-0.20130417694904884,-0.14910000562667847,0 +coef_util_distance_othdiscr,-0.31715754635603827,-0.31715481907154325,-0.12617222964763641,0 +coef_util_distance_othmaint,-0.1812975225573846,-0.18128613104067043,-0.096199996769428253,0 +coef_util_distance_school,-0.10559999942779541,-0.10559999942779541,-0.10559999942779541,0 +coef_util_distance_shopping,-0.3307589512022982,-0.33076061020463604,-0.11919999867677689,0 +coef_util_distance_social,-0.2659252249486278,-0.265920931953054,-0.13289999961853027,0 +coef_util_distance_univ,-0.14321261083041822,-0.14321492496348073,-0.061299998313188553,0 +coef_util_distance_work_inbound,-0.42854398962663698,-0.42853407623707079,0.14781327545642853,0 +coef_util_distance_work_outbound,-0.14563469653404526,-0.14563242024181883,-0.049725916236639023,0 +eatout_HEREMPN,-5.9999999999987965,-5.9999999998720117,-1.3547956943511963,0 +eatout_RETEMPN,-0.29840603470802307,-0.29840603470802307,-0.29840603470802307,0 +escort_AGE0519,3.0934694401381719,3.0934669149506493,-0.76787072420120239,0 +escort_HEREMPN,-5.1455749906308634,-5.1455755332943429,-1.9379420280456543,0 +escort_HSENROLL,-0.86259505065782127,-0.86258990666041102,-1.7957675457000732,0 +escort_RETEMPN,-3.197352946486133,-3.1973553524377385,-1.4916548728942871,0 +escort_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +othdiscr_HEREMPN,-5.9999999999996385,-5.9999999999615348,-1.3019531965255737,0 +othdiscr_HSENROLL,-5.3098114987510021,-5.3098141692353842,-2.3227877616882324,0 +othdiscr_OTHEMPN,-5.9999999999948379,-5.9999999994512185,-1.8018097877502441,0 +othdiscr_RETEMPN,-5.1182251846633031,-5.1182380614929812,-1.5511690378189087,0 +othdiscr_TOTHH,-1.3783261775970459,-1.3783261775970459,-1.3783261775970459,0 +othmaint_HEREMPN,-5.999999999995695,-5.9999999995423137,-0.65778005123138428,0 +othmaint_RETEMPN,-5.9999999999862119,-5.9999999985341876,-0.73188799619674683,0 +othmaint_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +shopping_RETEMPN,-5.9999999999999991,-5.9999999999999076,-0.0010005002841353416,0 +shopping_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +social_HEREMPN,-3.1416302242642606,-3.1416126892727569,-0.73814451694488525,0 +social_RETEMPN,0.79021700560209307,0.79019473285367858,-0.65200525522232056,0 +social_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +univ_COLLFTE,-5.9999999999999929,-5.9999999999999938,-0.52424865961074829,0 +univ_COLLPTE,-6,-5.9999999999999902,-0.89648813009262085,0 +univ_TOTHH,-6.9077553749084473,-6.9077553749084473,-6.9077553749084473,0 +work_AGREMPN,-1.1171784109856115,-1.1171768623786988,0,0 +work_FPSEMPN,-6,-5.9999999999999938,0,0 +work_HEREMPN,-5.9999999992762003,-5.9999999993504787,0,0 +work_MWTEMPN,-5.9999999989867057,-5.9999999990906927,0,0 +work_OTHEMPN,-5.9999999999994476,-5.999999999941287,0,0 +work_RETEMPN,0,0,0,0 diff --git a/activitysim/examples/example_estimation/build_example_data/build_stop_coeffs.py b/activitysim/examples/example_estimation/build_example_data/build_stop_coeffs.py index 69a3f38fbc..4eb08207f5 100644 --- a/activitysim/examples/example_estimation/build_example_data/build_stop_coeffs.py +++ b/activitysim/examples/example_estimation/build_example_data/build_stop_coeffs.py @@ -1,5 +1,7 @@ # python ~/work/activitysim/activitysim/examples/example_estimation/build_example_data/build_stop_coeffs.py +from __future__ import annotations + import numpy as np import pandas as pd @@ -18,7 +20,6 @@ "othmaint", "othdiscr", ]: - if FIRST_RUN: df = pd.read_csv(f"stop_frequency_{what}.csv", comment="#") df.to_csv(f"stop_frequency_backup_{what}.csv", index=False) diff --git a/activitysim/examples/optimize_example_data.py b/activitysim/examples/optimize_example_data.py index 490bea110c..d80da032f7 100644 --- a/activitysim/examples/optimize_example_data.py +++ b/activitysim/examples/optimize_example_data.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import os import openmatrix @@ -5,7 +7,6 @@ def patch_example_sandag_1_zone(example_dir): - cwd = os.getcwd() try: os.chdir(example_dir) diff --git a/activitysim/examples/placeholder_multiple_zone/scripts/three_zone_example_data.py b/activitysim/examples/placeholder_multiple_zone/scripts/three_zone_example_data.py index 248f9e2f45..7291c65337 100644 --- a/activitysim/examples/placeholder_multiple_zone/scripts/three_zone_example_data.py +++ b/activitysim/examples/placeholder_multiple_zone/scripts/three_zone_example_data.py @@ -9,6 +9,8 @@ # # This script should work for the full TM1 example as well. +from __future__ import annotations + import os import sys @@ -111,7 +113,6 @@ with omx.open_file(os.path.join(input_data, "skims.omx")) as ur_skims: - # create df with DIST column maz_to_maz = pd.DataFrame(ur_skims["DIST"]).unstack().reset_index() maz_to_maz.columns = ["OMAZ", "DMAZ", "DIST"] @@ -155,9 +156,7 @@ ) as output_taz_skims_file, omx.open_file( os.path.join(output_data, "tap_skims.omx"), "w" ) as output_tap_skims_file: - for skim_name in ur_skims.list_matrices(): - ur_skim = ur_skims[skim_name][:] new_skim = ur_skim[taz_zone_indexes, :][:, taz_zone_indexes] # print("skim:", skim_name, ": shape", str(new_skim.shape)) diff --git a/activitysim/examples/placeholder_multiple_zone/scripts/two_zone_example_data.py b/activitysim/examples/placeholder_multiple_zone/scripts/two_zone_example_data.py index 0b247905f5..a4c6c46fcb 100644 --- a/activitysim/examples/placeholder_multiple_zone/scripts/two_zone_example_data.py +++ b/activitysim/examples/placeholder_multiple_zone/scripts/two_zone_example_data.py @@ -9,6 +9,8 @@ # # This script should work for the full TM1 example as well. +from __future__ import annotations + import os import sys @@ -107,7 +109,6 @@ ) as skims_file, omx.open_file( os.path.join(output_data, "taz_skims.omx"), "w" ) as output_skims_file: - skims = skims_file.list_matrices() num_zones = skims_file.shape()[0] @@ -116,7 +117,6 @@ assert num_zones == len(land_use) for skim_name in skims_file.list_matrices(): - old_skim = skims_file[skim_name][:] new_skim = old_skim[new_zone_indexes, :][:, new_zone_indexes] output_skims_file[skim_name] = new_skim @@ -133,7 +133,6 @@ with omx.open_file(os.path.join(input_data, "skims.omx")) as skims_file: - # create df with DIST column maz_to_maz = pd.DataFrame(np.transpose(skims_file["DIST"])).unstack().reset_index() maz_to_maz.columns = ["OMAZ", "DMAZ", "DIST"] diff --git a/activitysim/examples/placeholder_multiple_zone/simulation.py b/activitysim/examples/placeholder_multiple_zone/simulation.py index 8313dd45e7..70cf3457fd 100644 --- a/activitysim/examples/placeholder_multiple_zone/simulation.py +++ b/activitysim/examples/placeholder_multiple_zone/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/placeholder_multiple_zone/test/simulation.py b/activitysim/examples/placeholder_multiple_zone/test/simulation.py index 8313dd45e7..70cf3457fd 100755 --- a/activitysim/examples/placeholder_multiple_zone/test/simulation.py +++ b/activitysim/examples/placeholder_multiple_zone/test/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/placeholder_multiple_zone/test/test_multiple_zone.py b/activitysim/examples/placeholder_multiple_zone/test/test_multiple_zone.py index f0c9e1587f..46aa8bf466 100644 --- a/activitysim/examples/placeholder_multiple_zone/test/test_multiple_zone.py +++ b/activitysim/examples/placeholder_multiple_zone/test/test_multiple_zone.py @@ -44,7 +44,6 @@ def test_path(dirname): return os.path.join(os.path.dirname(__file__), dirname) def regress(zone): - # regress tours regress_tours_df = pd.read_csv( test_path(f"regress/final_tours_{zone}_zone.csv") @@ -157,7 +156,6 @@ def test_3_zone_mp(data): @test.run_if_exists("reference_pipeline_2_zone.zip") def test_multizone_progressive(zone="2"): - zone = str(zone) import activitysim.abm # register components @@ -205,7 +203,6 @@ def test_path(dirname): if __name__ == "__main__": - build_data() run_test(zone="2", multiprocess=False) run_test(zone="2", multiprocess=True) diff --git a/activitysim/examples/placeholder_multiple_zone/three_zone_example_data.py b/activitysim/examples/placeholder_multiple_zone/three_zone_example_data.py index 9f0dae1ad7..0a43cce220 100644 --- a/activitysim/examples/placeholder_multiple_zone/three_zone_example_data.py +++ b/activitysim/examples/placeholder_multiple_zone/three_zone_example_data.py @@ -9,6 +9,8 @@ # # This script should work for the full TM1 example as well. +from __future__ import annotations + import os import shutil @@ -108,7 +110,6 @@ with omx.open_file(os.path.join(input_data, "skims.omx")) as ur_skims: - # create df with DIST column maz_to_maz = pd.DataFrame(ur_skims["DIST"]).unstack().reset_index() maz_to_maz.columns = ["OMAZ", "DMAZ", "DIST"] @@ -149,9 +150,7 @@ ) as output_taz_skims_file, omx.open_file( os.path.join(output_data, "tap_skims.omx"), "w" ) as output_tap_skims_file: - for skim_name in ur_skims.list_matrices(): - ur_skim = ur_skims[skim_name][:] new_skim = ur_skim[taz_zone_indexes, :][:, taz_zone_indexes] # print("skim:", skim_name, ": shape", str(new_skim.shape)) diff --git a/activitysim/examples/placeholder_multiple_zone/two_zone_example_data.py b/activitysim/examples/placeholder_multiple_zone/two_zone_example_data.py index 90ab0ca1a7..fbb26e2aaa 100644 --- a/activitysim/examples/placeholder_multiple_zone/two_zone_example_data.py +++ b/activitysim/examples/placeholder_multiple_zone/two_zone_example_data.py @@ -9,6 +9,8 @@ # # This script should work for the full TM1 example as well. +from __future__ import annotations + import os import shutil @@ -104,7 +106,6 @@ ) as skims_file, omx.open_file( os.path.join(output_data, "taz_skims.omx"), "w" ) as output_skims_file: - skims = skims_file.list_matrices() num_zones = skims_file.shape()[0] @@ -113,7 +114,6 @@ assert num_zones == len(land_use) for skim_name in skims_file.list_matrices(): - old_skim = skims_file[skim_name][:] new_skim = old_skim[new_zone_indexes, :][:, new_zone_indexes] output_skims_file[skim_name] = new_skim @@ -129,7 +129,6 @@ with omx.open_file(os.path.join(input_data, "skims.omx")) as skims_file: - # create df with DIST column maz_to_maz = pd.DataFrame(np.transpose(skims_file["DIST"])).unstack().reset_index() maz_to_maz.columns = ["OMAZ", "DMAZ", "DIST"] diff --git a/activitysim/examples/placeholder_psrc/scripts/integrity.py b/activitysim/examples/placeholder_psrc/scripts/integrity.py index b2e81656d8..ea02423b85 100644 --- a/activitysim/examples/placeholder_psrc/scripts/integrity.py +++ b/activitysim/examples/placeholder_psrc/scripts/integrity.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import argparse import os @@ -60,7 +62,6 @@ def to_csv(df, file_name): def report_baddies(df, tag, fatal=False): - if len(df) > 0: print(f"\n### OOPS ### {len(df)} {tag}\n") diff --git a/activitysim/examples/placeholder_psrc/scripts/psrc_crop.py b/activitysim/examples/placeholder_psrc/scripts/psrc_crop.py index 304963b580..b91e0d70b6 100644 --- a/activitysim/examples/placeholder_psrc/scripts/psrc_crop.py +++ b/activitysim/examples/placeholder_psrc/scripts/psrc_crop.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import argparse import os @@ -99,7 +101,6 @@ def to_csv(df, file_name): if check_geography: - # ######## check for orphan_households not in any maz in land_use land_use = read_csv("land_use.csv") land_use = land_use[["MAZ", "TAZ"]] # King County @@ -264,7 +265,6 @@ def to_csv(df, file_name): iskim = 0 for mat_name in omx_in.list_matrices(): - # make sure we have a vanilla numpy array, not a CArray m = np.asanyarray(omx_in[mat_name]).astype(skim_data_type) m = m[tazs_indexes, :][:, tazs_indexes] diff --git a/activitysim/examples/placeholder_psrc/test/simulation.py b/activitysim/examples/placeholder_psrc/test/simulation.py index 8313dd45e7..70cf3457fd 100755 --- a/activitysim/examples/placeholder_psrc/test/simulation.py +++ b/activitysim/examples/placeholder_psrc/test/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/placeholder_sandag/scripts/sandag_crop_1_zone.py b/activitysim/examples/placeholder_sandag/scripts/sandag_crop_1_zone.py index 0c84e53794..7fe9b6b0ca 100644 --- a/activitysim/examples/placeholder_sandag/scripts/sandag_crop_1_zone.py +++ b/activitysim/examples/placeholder_sandag/scripts/sandag_crop_1_zone.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import argparse import os @@ -84,7 +86,6 @@ def to_csv(df, file_name): if check_geography: - # ######## check for orphan_households not in any taz in land_use land_use = read_csv("land_use.csv") @@ -159,7 +160,6 @@ def to_csv(df, file_name): iskim = 0 for mat_name in omx_in.list_matrices(): - # make sure we have a vanilla numpy array, not a CArray m = np.asanyarray(omx_in[mat_name]).astype(skim_data_type) m = m[zone_indexes, :][:, zone_indexes] diff --git a/activitysim/examples/placeholder_sandag/scripts/sandag_crop_2_zone.py b/activitysim/examples/placeholder_sandag/scripts/sandag_crop_2_zone.py index bfcf9c84d6..77325c3053 100644 --- a/activitysim/examples/placeholder_sandag/scripts/sandag_crop_2_zone.py +++ b/activitysim/examples/placeholder_sandag/scripts/sandag_crop_2_zone.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import argparse import os @@ -91,7 +93,6 @@ def to_csv(df, file_name): if check_geography: - # ######## check for orphan_households not in any maz in land_use land_use = read_csv("land_use.csv") land_use = land_use[["MAZ", "TAZ"]] # King County @@ -255,7 +256,6 @@ def to_csv(df, file_name): iskim = 0 for mat_name in omx_in.list_matrices(): - # make sure we have a vanilla numpy array, not a CArray m = np.asanyarray(omx_in[mat_name]).astype(skim_data_type) m = m[tazs_indexes, :][:, tazs_indexes] diff --git a/activitysim/examples/placeholder_sandag/scripts/sandag_crop_3_zone.py b/activitysim/examples/placeholder_sandag/scripts/sandag_crop_3_zone.py index 908692d3d4..e19ac4939b 100644 --- a/activitysim/examples/placeholder_sandag/scripts/sandag_crop_3_zone.py +++ b/activitysim/examples/placeholder_sandag/scripts/sandag_crop_3_zone.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import argparse import os @@ -83,7 +85,6 @@ def to_csv(df, file_name): def crop_omx(omx_file_name, zones, num_outfiles=1): - skim_data_type = np.float32 omx_in = omx.open_file(input_path(f"{omx_file_name}.omx")) @@ -139,7 +140,6 @@ def crop_omx(omx_file_name, zones, num_outfiles=1): if check_geography: - # ######## check for orphan_households not in any maz in land_use land_use = read_csv(LAND_USE) land_use = land_use[["MAZ", "TAZ"]] diff --git a/activitysim/examples/placeholder_sandag/test/simulation.py b/activitysim/examples/placeholder_sandag/test/simulation.py index 8313dd45e7..70cf3457fd 100755 --- a/activitysim/examples/placeholder_sandag/test/simulation.py +++ b/activitysim/examples/placeholder_sandag/test/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/placeholder_sandag/test/test_sandag.py b/activitysim/examples/placeholder_sandag/test/test_sandag.py index 32e18ff1c9..a907333ee0 100644 --- a/activitysim/examples/placeholder_sandag/test/test_sandag.py +++ b/activitysim/examples/placeholder_sandag/test/test_sandag.py @@ -47,7 +47,6 @@ def test_path(dirname): return os.path.join(os.path.dirname(__file__), dirname) def regress(zone): - # ## regress tours if sharrow and os.path.isfile( test_path(f"regress/final_{zone}_zone_tours_sh.csv") @@ -315,7 +314,6 @@ def test_3_zone_progressive(): if __name__ == "__main__": - # call each test explicitly so we get a pass/fail for each build_data() run_test(zone="1", multiprocess=False) diff --git a/activitysim/examples/production_semcog/scripts/semcog_crop.py b/activitysim/examples/production_semcog/scripts/semcog_crop.py index f20ed4e7ea..289a75142b 100644 --- a/activitysim/examples/production_semcog/scripts/semcog_crop.py +++ b/activitysim/examples/production_semcog/scripts/semcog_crop.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import argparse import os @@ -94,7 +96,6 @@ def to_csv(df, file_name): if check_geography: - # ######## check for orphan_households not in any maz in land_use land_use = read_csv("land_use.csv") @@ -199,7 +200,6 @@ def to_csv(df, file_name): iskim = 0 for mat_name in omx_in.list_matrices(): - # make sure we have a vanilla numpy array, not a CArray m = np.asanyarray(omx_in[mat_name]).astype(skim_data_type) m = m[zone_indexes, :][:, zone_indexes] diff --git a/activitysim/examples/production_semcog/simulation.py b/activitysim/examples/production_semcog/simulation.py index cba7add1b9..15040c3769 100644 --- a/activitysim/examples/production_semcog/simulation.py +++ b/activitysim/examples/production_semcog/simulation.py @@ -1,15 +1,16 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys -from activitysim.cli.run import add_run_args, run - import extensions -if __name__ == "__main__": +from activitysim.cli.run import add_run_args, run +if __name__ == "__main__": parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/prototype_arc/scripts/arc_crop.py b/activitysim/examples/prototype_arc/scripts/arc_crop.py index 32cfc092da..93d878b843 100644 --- a/activitysim/examples/prototype_arc/scripts/arc_crop.py +++ b/activitysim/examples/prototype_arc/scripts/arc_crop.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import argparse import os @@ -92,7 +94,6 @@ def to_csv(df, file_name): if check_geography: - # ######## check for orphan_households not in any maz in land_use land_use = read_csv("land_use.csv") @@ -170,7 +171,6 @@ def to_csv(df, file_name): iskim = 0 for mat_name in omx_in.list_matrices(): - # make sure we have a vanilla numpy array, not a CArray m = np.asanyarray(omx_in[mat_name]).astype(skim_data_type) m = m[zone_indexes, :][:, zone_indexes] diff --git a/activitysim/examples/prototype_arc/simulation.py b/activitysim/examples/prototype_arc/simulation.py index e328406328..f24e2a0bc0 100644 --- a/activitysim/examples/prototype_arc/simulation.py +++ b/activitysim/examples/prototype_arc/simulation.py @@ -4,13 +4,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/prototype_arc/test/simulation.py b/activitysim/examples/prototype_arc/test/simulation.py index 8313dd45e7..70cf3457fd 100755 --- a/activitysim/examples/prototype_arc/test/simulation.py +++ b/activitysim/examples/prototype_arc/test/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/prototype_arc/test/test_arc.py b/activitysim/examples/prototype_arc/test/test_arc.py index aeb6a56155..54462ec958 100644 --- a/activitysim/examples/prototype_arc/test/test_arc.py +++ b/activitysim/examples/prototype_arc/test/test_arc.py @@ -91,7 +91,6 @@ def test_arc_sharrow(): if __name__ == "__main__": - _test_arc() _test_arc(recode=True) _test_arc(sharrow=True) diff --git a/activitysim/examples/prototype_marin/scripts/marin_crop.py b/activitysim/examples/prototype_marin/scripts/marin_crop.py index b82f596c08..c3f75ffc85 100644 --- a/activitysim/examples/prototype_marin/scripts/marin_crop.py +++ b/activitysim/examples/prototype_marin/scripts/marin_crop.py @@ -1,6 +1,8 @@ # crop marin tvpb example data processing to one county # Ben Stabler, ben.stabler@rsginc.com, 09/17/20 +from __future__ import annotations + import argparse import os @@ -95,7 +97,6 @@ def to_csv(df, file_name): WORK_TOURS = "work_tours.csv" if check_geography: - # ######## check for orphan_households not in any maz in land_use land_use = read_csv(LAND_USE) land_use = land_use[["MAZ", "TAZ"]] diff --git a/activitysim/examples/prototype_marin/test/simulation.py b/activitysim/examples/prototype_marin/test/simulation.py index 8313dd45e7..70cf3457fd 100755 --- a/activitysim/examples/prototype_marin/test/simulation.py +++ b/activitysim/examples/prototype_marin/test/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/prototype_mtc/simulation.py b/activitysim/examples/prototype_mtc/simulation.py index e89ab18e33..27ca7ac3c8 100644 --- a/activitysim/examples/prototype_mtc/simulation.py +++ b/activitysim/examples/prototype_mtc/simulation.py @@ -1,6 +1,8 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys @@ -8,7 +10,6 @@ from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/prototype_mtc/test/simulation.py b/activitysim/examples/prototype_mtc/test/simulation.py index 8313dd45e7..70cf3457fd 100755 --- a/activitysim/examples/prototype_mtc/test/simulation.py +++ b/activitysim/examples/prototype_mtc/test/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/prototype_mtc_extended/sampling_scenarios.py b/activitysim/examples/prototype_mtc_extended/sampling_scenarios.py index 03f480fb97..f718f4745d 100644 --- a/activitysim/examples/prototype_mtc_extended/sampling_scenarios.py +++ b/activitysim/examples/prototype_mtc_extended/sampling_scenarios.py @@ -95,7 +95,6 @@ def make_scene_name(it, params): def copy_output(scene_name, model_settings): - scene_dir_name = os.path.join("scenarios_output", scene_name) if os.path.exists(extended_path(scene_dir_name)): diff --git a/activitysim/examples/prototype_mtc_extended/test/simulation.py b/activitysim/examples/prototype_mtc_extended/test/simulation.py index 8313dd45e7..70cf3457fd 100644 --- a/activitysim/examples/prototype_mtc_extended/test/simulation.py +++ b/activitysim/examples/prototype_mtc_extended/test/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/prototype_mwcog/scripts/mwcog_crop.py b/activitysim/examples/prototype_mwcog/scripts/mwcog_crop.py index 3ba678f225..d4094c40b3 100644 --- a/activitysim/examples/prototype_mwcog/scripts/mwcog_crop.py +++ b/activitysim/examples/prototype_mwcog/scripts/mwcog_crop.py @@ -1,11 +1,14 @@ # crop marin tvpb example data processing to one county # Ben Stabler, ben.stabler@rsginc.com, 09/17/20 -import os -import pandas as pd -import openmatrix as omx +from __future__ import annotations + import argparse +import os + import numpy as np +import openmatrix as omx +import pandas as pd MAZ_OFFSET = 0 @@ -259,7 +262,6 @@ def crop_omx(omx_file_name, zones, num_outfiles=1): if check_geography: - # ######## check for orphan_households not in any maz in land_use land_use = read_csv(LAND_USE) land_use = land_use[["maz", "taz"]] diff --git a/activitysim/examples/prototype_mwcog/simulation.py b/activitysim/examples/prototype_mwcog/simulation.py index 8313dd45e7..70cf3457fd 100644 --- a/activitysim/examples/prototype_mwcog/simulation.py +++ b/activitysim/examples/prototype_mwcog/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/examples/prototype_mwcog/test/test_mwcog.py b/activitysim/examples/prototype_mwcog/test/test_mwcog.py index 27d56a2a2b..8978d269d0 100644 --- a/activitysim/examples/prototype_mwcog/test/test_mwcog.py +++ b/activitysim/examples/prototype_mwcog/test/test_mwcog.py @@ -73,5 +73,4 @@ def test_mwcog_sharrow(): if __name__ == "__main__": - test_mwcog() diff --git a/activitysim/examples/prototype_sandag_xborder/extensions/reassign_tour_purpose.py b/activitysim/examples/prototype_sandag_xborder/extensions/reassign_tour_purpose.py index cc52818324..be1a05bf48 100644 --- a/activitysim/examples/prototype_sandag_xborder/extensions/reassign_tour_purpose.py +++ b/activitysim/examples/prototype_sandag_xborder/extensions/reassign_tour_purpose.py @@ -14,7 +14,6 @@ @workflow.step def reassign_tour_purpose_by_poe(state: workflow.State, tours: pd.DataFrame) -> None: - """ Simulates tour purpose choices after tour origin has been assigned. This is useful when the original tour purposes are assigned randomly diff --git a/activitysim/examples/prototype_sandag_xborder/scripts/sandag_crop_3_zone.py b/activitysim/examples/prototype_sandag_xborder/scripts/sandag_crop_3_zone.py index f0968d6400..0af73513ae 100644 --- a/activitysim/examples/prototype_sandag_xborder/scripts/sandag_crop_3_zone.py +++ b/activitysim/examples/prototype_sandag_xborder/scripts/sandag_crop_3_zone.py @@ -2,6 +2,8 @@ # crop marin tvpb example data processing to one county # Ben Stabler, ben.stabler@rsginc.com, 09/17/20 +from __future__ import annotations + import argparse import glob import os @@ -83,7 +85,6 @@ def to_csv(df, file_name): def crop_omx(omx_file_name, zones, num_outfiles=1): - skim_data_type = np.float32 omx_in = omx.open_file(input_path(f"{omx_file_name}.omx")) diff --git a/activitysim/examples/prototype_sandag_xborder/simulation.py b/activitysim/examples/prototype_sandag_xborder/simulation.py index 9e10fd4c9a..122d47017e 100644 --- a/activitysim/examples/prototype_sandag_xborder/simulation.py +++ b/activitysim/examples/prototype_sandag_xborder/simulation.py @@ -1,6 +1,8 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import os import sys @@ -10,7 +12,6 @@ from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/activitysim/workflows/steps/chunk_sizing.py b/activitysim/workflows/steps/chunk_sizing.py index f19c19ab39..e267835ba9 100644 --- a/activitysim/workflows/steps/chunk_sizing.py +++ b/activitysim/workflows/steps/chunk_sizing.py @@ -28,7 +28,6 @@ def chunk_sizing( # if chunk size is set explicitly, use it without regard to other settings if chunk_size is None: - if chunk_size_pct_of_available is not None: if chunk_size_pct_of_available > 1: chunk_size_pct_of_available /= 100 diff --git a/activitysim/workflows/steps/contrast/composite_log.py b/activitysim/workflows/steps/contrast/composite_log.py index 81c90c599a..0ea23c9e4b 100644 --- a/activitysim/workflows/steps/contrast/composite_log.py +++ b/activitysim/workflows/steps/contrast/composite_log.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import os import pandas as pd @@ -26,7 +28,6 @@ def composite_log( archive_dir, compares=("compile", "sharrow", "legacy", "reference"), ) -> dict: - reset_progress_step(description="composite timing and memory logs") timings = {} diff --git a/activitysim/workflows/steps/contrast/runtime.py b/activitysim/workflows/steps/contrast/runtime.py index 7437f331bc..8c37163305 100644 --- a/activitysim/workflows/steps/contrast/runtime.py +++ b/activitysim/workflows/steps/contrast/runtime.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import logging import altair as alt @@ -65,7 +67,6 @@ def relabel_source(x): ) if len(include_runs) == 1: - result = c.mark_bar(size=6,).encode( x=alt.X("seconds:Q", stack=None), y=alt.Y("model_name", type="nominal", sort=None), @@ -79,7 +80,6 @@ def relabel_source(x): ) elif len(include_runs) == 2: - result = c.mark_bar(yOffset=-3, size=6,).transform_filter( (alt.datum.source == relabel_source(include_runs[0])) ).encode( diff --git a/activitysim/workflows/steps/contrast/transform_data.py b/activitysim/workflows/steps/contrast/transform_data.py index 1b621631ec..05b777ea21 100644 --- a/activitysim/workflows/steps/contrast/transform_data.py +++ b/activitysim/workflows/steps/contrast/transform_data.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import logging import numpy as np @@ -22,7 +24,6 @@ def transform_data( censor=None, eval=None, ) -> dict: - if qcut is None and cut is None and clip is None and censor is None: raise ValueError("must give at least one of {cut, qcut, clip, censor}") diff --git a/activitysim/workflows/steps/main.py b/activitysim/workflows/steps/main.py index aa4e0d5281..ccefaa825b 100644 --- a/activitysim/workflows/steps/main.py +++ b/activitysim/workflows/steps/main.py @@ -21,7 +21,6 @@ def get_pipeline_definition(pipeline_name, parent): with open(workflow_file) as yaml_file: return pypyr.yaml.get_pipeline_yaml(yaml_file) else: - return get_pipeline_definition(pipeline_name, parent) @@ -53,7 +52,6 @@ def main(args): os.environ["NO_RICH"] = "1" with get_progress(): - try: import pypyr.log.logger import pypyr.pipelinerunner diff --git a/activitysim/workflows/steps/memory_stress_test.py b/activitysim/workflows/steps/memory_stress_test.py index 371d5104c3..57f1d8a769 100644 --- a/activitysim/workflows/steps/memory_stress_test.py +++ b/activitysim/workflows/steps/memory_stress_test.py @@ -25,7 +25,6 @@ def ping_mem(pid=None): @workstep(updates_context=True) def memory_stress_test(n=37): - logging.critical(f"ping_mem = {ping_mem()}") big = np.arange(int(2 ** float(n) / 8), dtype=np.float64) big *= 2.0 diff --git a/activitysim/workflows/steps/progression.py b/activitysim/workflows/steps/progression.py index 50c128ac26..c0832dc46c 100644 --- a/activitysim/workflows/steps/progression.py +++ b/activitysim/workflows/steps/progression.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import os import time from datetime import timedelta @@ -26,12 +28,10 @@ def update(self, *args, **kwargs): dummy_progress = DummyProgress() try: - from rich.panel import Panel from rich.progress import Progress, ProgressColumn, Text except ImportError: - # allow printing in color on windows terminal if os.name == "nt": import ctypes diff --git a/activitysim/workflows/steps/reporting/save_report.py b/activitysim/workflows/steps/reporting/save_report.py index 1722084571..d4d0a17389 100644 --- a/activitysim/workflows/steps/reporting/save_report.py +++ b/activitysim/workflows/steps/reporting/save_report.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import logging import os import shutil @@ -22,7 +24,6 @@ def save_report( toc_color="forest", copy_filename=None, ): - bootstrap_font_family = ( 'font-family: -apple-system, "system-ui", "Segoe UI",' ' "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji",' diff --git a/conda-environments/activitysim-dev-base.yml b/conda-environments/activitysim-dev-base.yml index 03e2f7da03..9a5f6d9cfc 100644 --- a/conda-environments/activitysim-dev-base.yml +++ b/conda-environments/activitysim-dev-base.yml @@ -31,8 +31,9 @@ dependencies: - ipykernel # so this env will appear in jupyter as a selection - isort - jupyterlab -- larch6 >= 6.0.34 +- larch >= 6.0.34 - matplotlib +- multimethod <2.0 - myst-parser # allows markdown in sphinx - nbconvert - nbformat diff --git a/conda-environments/activitysim-dev.yml b/conda-environments/activitysim-dev.yml index 5bdd04cb26..5f0edf02e5 100644 --- a/conda-environments/activitysim-dev.yml +++ b/conda-environments/activitysim-dev.yml @@ -28,6 +28,7 @@ dependencies: - isort - jupyterlab - matplotlib +- multimethod <2.0 - myst-parser # allows markdown in sphinx - nbconvert - nbformat @@ -74,5 +75,5 @@ dependencies: - pip: - autodoc_pydantic - - larch6 >= 6.0.34 + - larch >= 6.0.34 - -e .. diff --git a/conda-environments/docbuild.yml b/conda-environments/docbuild.yml index 30385c9718..302ab9379c 100644 --- a/conda-environments/docbuild.yml +++ b/conda-environments/docbuild.yml @@ -24,18 +24,18 @@ dependencies: - jupyter-book - jupyterlab - matplotlib +- multimethod <2.0 - myst-nb - myst-parser - numba >= 0.57 - numpy >= 1.16.1, <2 - numpydoc - openmatrix >= 0.3.4.1 -- orca >= 1.6 -- pandas >= 1.1.0,<2 +- pandas = 2.2.* - pandera >= 0.15, <0.18.1 - platformdirs - psutil >= 4.1 -- pyarrow >= 2.0 +- pyarrow >= 2.0,<19 - pydantic = 2.6.* - pypyr >= 5.3 - pytables >=3.7 @@ -58,5 +58,5 @@ dependencies: - pip: - autodoc_pydantic - - larch6 >= 6.0.34 + - larch >= 6.0.34 - -e .. diff --git a/conda-environments/github-actions-tests.yml b/conda-environments/github-actions-tests.yml index 334628790e..dec794ddc3 100644 --- a/conda-environments/github-actions-tests.yml +++ b/conda-environments/github-actions-tests.yml @@ -13,6 +13,7 @@ dependencies: - dask = 2023.3.2 - isort = 5.12.0 - matplotlib = 3.9.* +- multimethod < 2.0 - nbmake = 1.4.6 - numba = 0.60.* - numpy = 1.23.5 diff --git a/docs/conf.py b/docs/conf.py index ef358b4cfd..c148e6b6bd 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -236,7 +236,7 @@ "pandas": ("http://pandas.pydata.org/pandas-docs/stable", None), "xarray": ("https://docs.xarray.dev/en/stable", None), "pyarrow": ("https://arrow.apache.org/docs", None), - "numba": ("https://numba.pydata.org/numba-doc/latest", None), + "numba": ("https://numba.readthedocs.io/en/latest/", None), "psutil": ("https://psutil.readthedocs.io/en/latest", None), } diff --git a/docs/dev-guide/changes.md b/docs/dev-guide/changes.md index e8a94effd4..360ab1026e 100644 --- a/docs/dev-guide/changes.md +++ b/docs/dev-guide/changes.md @@ -5,6 +5,21 @@ major new features that may require modifications to existing model configuratio or code to utilize, as well as breaking changes that may cause existing model configurations or code to fail to run correctly. +## v1.4 + +### Improved Estimation Mode + +Version 1.4 includes several improvements to the estimation mode, including: + +- The ability to run estimation mode in parallel, which can significantly + speed up the estimation process for large models. +- The ability to modify the model specification and coefficients file(s) for + the estimated submodels without re-running ActivitySim, which allows for more + flexibility in the estimation process. +- Other improvements to the estimation mode workflow, including better error + handling, logging, and model evaluation tools. + + ## v1.3 ### New Canonical Examples diff --git a/docs/gettingstarted.rst b/docs/gettingstarted.rst index 3dcb27bada..e318cdba58 100644 --- a/docs/gettingstarted.rst +++ b/docs/gettingstarted.rst @@ -24,7 +24,7 @@ installs a variety of things on your system, and it is quite likely to be flagge Windows, anti-virus, or institutional IT policies as "unusual" software, which may require special treatment to actually install and use. -Download the installer from GitHub `here `_. +Download the installer from GitHub `here `_. It is strongly recommended to choose the option to install "for me only", as this should not require administrator privileges on your machine. Pay attention to the *complete path* of the installation location. You will need to know diff --git a/docs/users-guide/estimation-mode/asim-est.md b/docs/users-guide/estimation-mode/asim-est.md new file mode 100644 index 0000000000..77ef1e65aa --- /dev/null +++ b/docs/users-guide/estimation-mode/asim-est.md @@ -0,0 +1,34 @@ +# Running ActivitySim in Estimation Mode + +ActivitySim is run in estimation mode to read ActivitySim-format travel survey +files, and apply the ActivitySim submodels to write estimation data bundles (EDBs) +that contains the model utility specifications, coefficients, chooser data, and +alternatives data for each submodel. These EDBs are then used with Larch to +re-estimate the model parameters. + +ActivitySim can be run in estimation mode by including a few extra settings in +the `estimation.yaml` config file. The key setting in this file is the `enabled` +setting, which must be set to `True` in order to run in estimation mode. The +default value for this setting is `False`, so if it is not explicitly set to +`True`, ActivitySim will run in normal simulation mode, and everything else +in the `estimation.yaml` config file will be ignored. These settings are +documented below. After running ActivitySim in estimation mode, the EDBs will be +written to disk, and can be used with Larch to re-estimate the model parameters. + +```{eval-rst} +.. currentmodule:: activitysim.core.estimation +``` + +## Configuration Settings + +```{eval-rst} +.. autopydantic_model:: EstimationConfig + :inherited-members: PydanticReadable + :show-inheritance: +``` + +## Survey Table Settings + +```{eval-rst} +.. autopydantic_model:: SurveyTableConfig +``` diff --git a/docs/users-guide/estimation-mode/index.md b/docs/users-guide/estimation-mode/index.md new file mode 100644 index 0000000000..4593a5a42c --- /dev/null +++ b/docs/users-guide/estimation-mode/index.md @@ -0,0 +1,58 @@ + +# Estimation Mode + +ActivitySim includes the ability to re-estimate submodels using choice model estimation +tools. It is possible to output the data needed for estimation and then use more or less +any parameter estimation tool to find the best-fitting parameters for each model, but +ActivitySim has a built-in integration with the [`larch`](https://larch.driftless.xyz) +package, which is an open source Python package for estimating discrete choice models. + +## Estimation Workflow, Summarized + +The general workflow for estimating models is shown in the following figures and +explained in more detail below. + +![estimation workflow](https://activitysim.github.io/activitysim/develop/_images/estimation_tools.jpg) + +First, the user converts their household travel survey into ActivitySim-format +households, persons, tours, joint tour participants, and trip tables. The +households and persons tables must have the same fields as the synthetic population +input tables since the surveyed households and persons will be run through the same +set of submodels as the simulated households and persons. + +The ActivitySim estimation example [``scripts\infer.py``](https://github.com/ActivitySim/activitysim/blob/main/activitysim/examples/example_estimation/scripts/infer.py) +module reads the ActivitySim-format household travel survey files and checks for +inconsistencies in the input tables versus the model design, and calculates +additional fields such as the household joint tour frequency based on the trips +and joint tour participants table. Survey households and persons observed choices +much match the model design (i.e. a person cannot have more work tours than the model +allows). + +ActivitySim is then run in estimation mode to read the ActivitySim-format +travel survey files, and apply the ActivitySim submodels to write estimation data bundles +(EDBs) that contains the model utility specifications, coefficients, chooser data, +and alternatives data for each submodel. + +The relevant EDBs are read and transformed into the format required by the model +estimation tool (i.e. larch) and then the coefficients are re-estimated. The +``activitysim.estimation.larch`` library is included for integration with larch +and there is a Jupyter Notebook estimation example for most core submodels. +Certain kinds of changes to the model specification are allowed during the estimation +process, as long as the required data fields are present in the EDB. For example, +the user can add new expressions that transform existing data, such as converting +a continuous variable into a categorical variable, a polynomial transform, or a +piecewise linear form. More intensive changes to the model specification, such as +adding data that is not in the EDB, or adding new alternatives, are generally not +possible without re-running the estimation mode to write a new EDB. + +Based on the results of the estimation, the user can then update the model +specification and coefficients file(s) for the estimated submodel. + +```{eval-rst} +.. toctree:: + :maxdepth: 2 + + Running ActivitySim in Estimation Mode + Using Larch to Re-estimate Models + ActivitySim Larch Tool API +``` diff --git a/docs/users-guide/estimation-mode/larch-api.rst b/docs/users-guide/estimation-mode/larch-api.rst new file mode 100644 index 0000000000..94805cda03 --- /dev/null +++ b/docs/users-guide/estimation-mode/larch-api.rst @@ -0,0 +1,50 @@ +============== +Larch Tool API +============== + +.. currentmodule:: activitysim.estimation.larch + + +activitysim.estimation.larch.general +------------------------------------ + +.. automodule:: activitysim.estimation.larch.general + :members: + + +activitysim.estimation.larch.data_maker +--------------------------------------- + +.. automodule:: activitysim.estimation.larch.data_maker + :members: + +activitysim.estimation.larch.simple_simulate +-------------------------------------------- + +.. automodule:: activitysim.estimation.larch.simple_simulate + :members: + +activitysim.estimation.larch.cdap +--------------------------------- + +.. automodule:: activitysim.estimation.larch.cdap + :members: + +activitysim.estimation.larch.location_choice +-------------------------------------------- + +.. automodule:: activitysim.estimation.larch.location_choice + :members: + +.. automodule:: activitysim.estimation.larch.mode_choice + :members: + +.. automodule:: activitysim.estimation.larch.nonmand_tour_freq + :members: + +.. automodule:: activitysim.estimation.larch.scheduling + :members: + +.. automodule:: activitysim.estimation.larch.stop_frequency + :members: +``` diff --git a/docs/users-guide/estimation-mode/larch.md b/docs/users-guide/estimation-mode/larch.md new file mode 100644 index 0000000000..370c2ac400 --- /dev/null +++ b/docs/users-guide/estimation-mode/larch.md @@ -0,0 +1,303 @@ +# Using Larch + +ActivitySim component models are mostly built as discrete choice models. The +parameters for these models typically need to be estimated based on observed +survey data. The estimation process is facilitated by the Larch package, which +is a Python package for estimating discrete choice models. Larch is a +general-purpose package that can be used to estimate a wide variety of discrete +choice models, including the multinomial logit and nested logit models that +are commonly used in ActivitySim. This section highlights some of the features +of Larch, particularly as they relate to ActivitySim, as there are a few subtle +differences between the two packages that users should be aware of when +estimating models. + +## Setting up Larch Models + +ActivitySim includes a number of scripts and tools to set up Larch models +for estimation. The `activitysim.estimation.larch` library includes +functions to read the EDBs written by ActivitySim and convert them into +Larch models, including a generic [`component_model`](activitysim.estimation.larch.component_model) +function that can be used to load the data and set up Larch for any standard ActivitySim component. +This function is demonstrated in the [example notebooks](#example-notebooks). + +When given a truthy `return_data` argument, the `component_model` function +will return a 2-tuple of the Larch model and the data used to create it. The +data as the second element of this tuple should be treated as a *copy* of the +data used to create the model, and is provided primarily for the user to review +and use in debugging if needed. If it is necessary to modify the data (e.g. to +recreate temporary variables), the user should modify the `data` attribute of +the model itself (i.e. `model.data` if `model` is the first element of the +returned tuple), not the data returned in the second element of the tuple. + +## Model Specification + +By default, the process of estimating parameters for ActivitySim model components +with Larch is based on the existing model specification files. These are the +CSV files that are used to define the utility function for each logit component. +When running ActivitySim, these files are typically found in the configs directory, +but when running in estimation mode, they are written out to the EDB as well, which +is where the `activitysim.estimation.larch` library functions look for these +input files. + +Users are not limited to using the existing model specification files, however. The +Larch tools for model estimation now allow users to modify the model specification +files, and then re-estimate the model, including existing and new parameters. +The revised model specification files must rely on the same data that has already +been written out to the EDB, but the user can add new expressions to the specification +to transform the data, or to create new variables. This is particularly useful +for creating new piecewise linear transformations, or for creating new categorical +variables from continuous variables. The user can also add new variables to the +specification that are not in the EDB, but this will require re-running ActivitySim +in estimation mode to write a new EDB. Examples for how to re-specify the model +specification files are included in +[selected example notebooks](#examples-that-include-re-specification). + +## Maximum Likelihood Estimation + +The approach used to estimate the parameters of a discrete choice model is +maximum likelihood estimation (MLE). The goal of MLE is to find the set of +parameters that maximize the likelihood of observing the choice data that we +have collected. + +Finding the maximum likelihood estimates of the parameters is a non-linear +optimization problem. To solve this problem, Larch primarily relies on the +widely-used `scipy.optimize` package, which provides a number of +[optimization algorithms](https://docs.scipy.org/doc/scipy/reference/optimize.html#local-multivariate-optimization) +that can be used to find the maximum likelihood estimates. Different algorithms +have different strengths and weaknesses, and the choice of algorithm can have a +significant impact on the speed and accuracy of the estimation process. By default, +when no constraints or bounds are present, Larch uses an implementation of the +[BHHH algorithm](https://en.wikipedia.org/wiki/Berndt–Hall–Hall–Hausman_algorithm), +which is not included in scipy but is usually efficient for simple, well specified +choice models without any constraints. When constraints or bounds are present, by default Larch uses the +Larch uses the `scipy.optimize.minimize` function with the `SLSQP` algorithm. +The `larch.Model.estimate` method allows the +user to specify the optimization algorithm to use via the `method` argument, which +can be set to 'BHHH', 'SLSQP', or any other algorithm supported by `scipy.optimize.minimize`. +If you are estimating a model and find the optimization is not converging as +fast as expected (or at all), you may want to try a different optimization algorithm. + +## Model Evaluation + +The `larch.Model` class includes a number of methods for evaluating the +quality of each estimated model. These tools are explained in +[detail](https://larch.driftless.xyz/v6.0/user-guide/analysis.html) in the +Larch documentation. + +A [simple aggregate analysis](https://larch.driftless.xyz/v6.0/user-guide/analysis.html#choice-and-availability-summary) +of a Larch model data’s choice and availability statistics is available. + +Larch also includes methods to +[analyze model predictions](https://larch.driftless.xyz/v6.0/user-guide/analysis.html#analyze-predictions) +across various dimensions. The `analyze_predictions_co` method can be used to +examine how well the model predicts choices against any available (or computable) +attribute of the chooser. In addition, there are tools to evaluate +[demand elasticity](https://larch.driftless.xyz/v6.0/user-guide/analysis.html#elasticity) +with respect to changes in underlying data. + +## Model Overspecification + +When using ActivitySim for simulation, there are generally few limitations or +requirements on the uniqueness of data elements. For example, it may end up being +confusing for a user, but there is nothing +fundamentally wrong with having two different variables in the model specification +that both represent "income" but have different scales, or with having +alternative-specific constants for all the alternatives. +In model estimation, however, this can lead to problems. Having two data elements +that are perfectly correlated (e.g. two different variables that both represent "income") +or having a full set of alternative-specific values for all the alternatives can lead to +numerical problems in the estimation process, as the log likelihood function will +have flat areas and will not have a unique maximum. This is called "model overspecification". +In Larch, the user is warned if an estimated model appears to be overspecified, +see the Larch documentation [for details](https://larch.driftless.xyz/v6.0/user-guide/choice-models.html#overspecification). + +## Recreating Temporary Variables + +When writing out estimation data bundles, ActivitySim may omit certain +temporary variables included in a model spec. For example, in the example +workplace location choice model, the spec creates a temporary variable +["_DIST"](https://github.com/ActivitySim/activitysim-prototype-mtc/blob/7da9d6d6deca670cc4701fea749a270ab6fe77aa/configs/workplace_location.csv#L2) +which is then reused in several subsequent expressions. When the model's +estimation data bundle is written out, the "_DIST" variable may not be +included[^1]. This is not a problem when simply re-estimating the parameters +of the current model specification, as all of the piecewise linear transformations +that use "_DIST" are included. However, if the user wanted to change those +piecewise linear transformations (e.g. by moving the breakpoints), the +absence of the "_DIST" value will be relevant. + +[^1]: Future versions of ActivitySim may include these values in the EDB output. + +If the missing temporary value can be reconstructed from the data that *is* +included in the EDB, it can be added back into the model's data. For example, +here we reconstitute the total distance by summing up over the piecewise +component parts: + +```{python} +model.data["_DIST"] = ( + model.data.util_dist_0_1 + + model.data.util_dist_1_2 + + model.data.util_dist_2_5 + + model.data.util_dist_5_15 + + model.data.util_dist_15_up +) +``` + +Note in this expression, we are modifying `model.data`, i.e. the data attached +to the model. If have other raw data available in our estimation notebook, +e.g. from running `model, data = component_model(..., return_data=True)`, it +is not sufficient to manipulate `data` itself, we must manipulate `model.data` +or otherwise re-attach any data changes to the model, or else the changes will +not show up in estimation. + +## Expressing Alternative Availability + +In ActivitySim, the unavailability of alternatives is typically expressed in the +utility function given in the model specification, by including a indicator variable +for unavailable alternatives, which is then attached to a large negative coefficient. +This creates a large negative utility for the unavailable alternative, which will +render it effectively unavailable in the choice model. If *all* the alternatives +are made unavailable in this manner, this can result in a condition where no +alternative can be chosen, and ActivitySim will raise an error. + +When estimating models in Larch for use with ActivitySim, it is totally acceptable and +appropriate to use this approach to express alternative availability, +by embedding it in the utility function. This will greatly simplify the process +of subsequently transferring the resulting model specification and parameters +back to the ActivitySim model. However, it is important to note that this +approach is not the only way to express alternative availability in Larch. + +Larch includes a system to define the availability of alternatives explicitly as a +[separate array of values](https://larch.driftless.xyz/dev/user-guide/choice-models.html#availability), +which is not included in the utility function. This is +more robust in estimation, as the Larch computational engine can (and will) +automatically shift the utility values to avoid numerical underflow or overflow +issues that can arise when some choices are very unlikely but not strictly unavailable. +When using the ActivitySim style of expressing alternative availability, the onus +is entirely on the user to ensure that the utility values are not so large or small +that they cause numerical problems. If this is not checked, it is possible that +the model will appear to be estimating correctly in Larch, but the resulting model +will underflow in ActivitySim, resulting in an error when the model is run. + +The scripts that build Larch models from estimation data bundles +(`activitysim.estimation.larch`) will attempt to identify unavailability flags +in the utility specifications, and when such flags are found it will automatically +convert them to the Larch availability array format. However, since specification +files can be complex, and the unavailability flags can be expressed in many different +ways, it is possible that the automatic detection will not always work as expected. +It is a good idea to check the +[choice and availability summary](https://larch.driftless.xyz/dev/user-guide/analysis.html#choice-and-availability-summary) +on the Larch model to confirm that the availability of alternatives is being +processes as expected. + +## Components that have Related Models + +Within ActivitySim, it is possible for multiple parts of model components +to share a common set of coefficients. It is even possible for completely +separate components to do so. For example, in the MTC example model, +the joint tour destination choice model and the non-mandatory tour destination +choice model share a common set of coefficients written in a single file. +To re-estimate these coefficients, the user must simultaneously work with all +the estimation survey data from both models. + +In Larch, the case of two models sharing coefficients is handled by creating two separate +`Model` objects, one for each model, and then using the `ModelGroup` object to link them +together. The `ModelGroup` object allows the user to specify a set of common parameters +for two or more models, and then estimate them together. In the case of re-estimating +the joint tour destination choice model and the non-mandatory tour destination +choice model, it may be that both models have a similar (or even identical) +utility structure. In other cases, the linked models may have different utility +structures, which share a subset of parameters, but also may have other parameters +that are unique to each model. In either case, when using the `ModelGroup` object, +parameters are identified as being linked across models by having a common name. + +There are also components in ActivitySim where a single component can embed multiple +discrete choice models which share details, but each sub-model can have a different +utility structure or different sets of parameters. For example, the `tour_mode_choice` +component has a coefficient template file, which allows the model developer to +specify a different set of coefficients for each tour purpose, which are otherwise +processed using a common utility function. This is implemented in Larch with the +`ModelGroup` object, where each purpose is represented as a separate `Model` object, +and the `ModelGroup` object is used to link them together. This logic is further +extended by including the at-work subtour mode choice component, which allows for +the joint estimation of the tour mode choice model and the at-work subtour mode +choice model, which very reasonably share numerous parameters, but also have a few +differences. Similarly, the stop frequency and CDAP models are implemented for +Larch estimation as `ModelGroup` objects, segmented on tour purpose and household +size, respectively. + +When estimating a `ModelGroup` object, process for estimating the likelihood +maximizing parameters is the same as for a single model: the log likelihood is computed +for each observation (i.e. chooser) in the data set according to the parameters, model, +and data for that chooser, and the overall log likelihood is the sum of all the +chooser log likelihoods. By using this approach, the rest of the estimation process is +the same as for a single model, including finding parameter estimates, the standard +error of those estimates, and any statistical tests or interpretations that are +desired. + +## Components with Size Terms + +Location choice models in ActivitySim (and in discrete choice modeling +in general) usually include a "size" term. The size term is a measure +of the quantity of the alternative, which in location choice models is +typically a geographic area that contains multiple distinct alternatives. +For example, in a workplace location choice model, the size term might +be the number of jobs in the zone. In practice, the size term is a statistical +approximation of the number of opportunities available in the zone, and +can be composed of multiple components, such as the number of employers, the +number of households, and/or the number of retail establishments. + +The size term is included in the utility function of the model, but it is +expressed differently from other qualitative measures. The typical model +specification for a location choice model will include a utility function +given in a spec file, which will represent the quality of the alternative(s) +that are being considered. Put another way, the "regular" utility function +is a measure of the quality of the alternative, while the size term is a +measure of the quantity of the alternative. + +In ActivitySim, size terms appear not in the utility spec files, but instead +are expressed in a separate "size term" spec file, typically named +"destination_choice_size_terms.csv". This one file contains all of the size +terms for all of the location choice models. + +When using Larch for model estimation, size terms can be estimated alongside the +other parameters. The `update_size_spec` function in the `activitysim.estimation.larch` library +allows the user to update the size term specification for a model. This function +takes the existing size term specification and updates the appropriate rows +that correspond to the model being re-estimated. The resulting updated size +term output file will also include the (unmodified) size term specification +for all other size-based models. When copying the revised size term specification +to the model configuration, the user should be careful that re-estimation updates +from multiple models are not inadvertently overwriting each other. + +## Example Notebooks + +ActivitySim includes a collection of Jupyter notebooks with +interactive re-estimation examples for many core submodels, which can be found in the +GitHub repository under the [`activitysim/examples/example_estimation/notebooks`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks) +directory. Most of these notebooks demonstrate the process of re-estimating model +parameters, without changing the model specification, i.e. finding updated values +for coefficients without changing the mathematical form of a model's utility +function. + +### Examples that include Re-Specification + +A selection of these notebooks have also been updated to demonstrate +the process of estimating model parameters and also *changing the model specification*. +These notebooks generally include instrucations and a demonstration of how to +modify the model specification, and then re-estimate the model parameters, as +well as how to compare the results of the original and modified models side-by-side, +which can be useful for understanding the impact of the changes made, and conducting +statistical tests to determine if the changes made are statistically significant. + +The following notebooks include examples of modifying the model specification: + +- `03_work_location.ipynb`: This notebook includes a demonstration of + modification to the SPEC file for a destination choice model, using the + "interact-sample-simulate" type model. +- `04_auto_ownership.ipynb`: This notebook includes a demonstration of + modification to the SPEC file for the + auto ownership model. It shows an example of an edit in the utility function + for a "simple simulate" type model. +- `06_cdap.ipynb`: This notebook includes a demonstration of modification to + the SPEC file for the CDAP model. This model has a complex structure that is + unique among the ActivitySim component models. diff --git a/docs/users-guide/index.rst b/docs/users-guide/index.rst index 35f60622fb..d464a6cd0d 100644 --- a/docs/users-guide/index.rst +++ b/docs/users-guide/index.rst @@ -44,6 +44,7 @@ Contents visualization example_models example_performance + estimation-mode/index .. toctree:: :maxdepth: 1 other_examples diff --git a/docs/users-guide/modelsetup.rst b/docs/users-guide/modelsetup.rst index 3ba8c650a2..2a64830625 100644 --- a/docs/users-guide/modelsetup.rst +++ b/docs/users-guide/modelsetup.rst @@ -134,7 +134,7 @@ installs a variety of things on your system, and it is quite likely to be flagge Windows, anti-virus, or institutional IT policies as "unusual" software, which may require special treatment to actually install and use. -Download the installer from GitHub `here `_. +Download the installer from GitHub `here `_. It is strongly recommended to choose the option to install "for me only", as this should not require administrator privileges on your machine. Pay attention to the *complete path* of the installation location. You will need to know diff --git a/other_resources/scripts/build_omx.py b/other_resources/scripts/build_omx.py index 4f70265915..f298e34a2e 100644 --- a/other_resources/scripts/build_omx.py +++ b/other_resources/scripts/build_omx.py @@ -3,6 +3,8 @@ # See full license in LICENSE.txt. # run from the mtc tm1 skims folder +from __future__ import annotations + import os import openmatrix as omx @@ -10,7 +12,6 @@ def read_manifest(manifest_file_name): - column_map = { "Token": "skim_key1", "TimePeriod": "skim_key2", @@ -29,9 +30,7 @@ def read_manifest(manifest_file_name): def omx_getMatrix(omx_file_name, omx_key): - with omx.open_file(omx_file_name, "r") as omx_file: - if omx_key not in omx_file.list_matrices(): print( "Source matrix with key '%s' not found in file '%s" @@ -62,11 +61,9 @@ def omx_getMatrix(omx_file_name, omx_key): dest_file_name = os.path.join(dest_data_dir, "skims.omx") with omx.open_file(dest_file_name, "a") as dest_omx: - manifest = read_manifest(manifest_file_name) for row in manifest.itertuples(index=True): - source_file_name = os.path.join(source_data_dir, row.source_file_name) if row.skim_key2: @@ -83,7 +80,6 @@ def omx_getMatrix(omx_file_name, omx_key): ) ) with omx.open_file(source_file_name, "r") as source_omx: - if row.source_key not in source_omx.list_matrices(): print( "Source matrix with key '%s' not found in file '%s" diff --git a/other_resources/scripts/create_sf_example.py b/other_resources/scripts/create_sf_example.py index de6c7758d1..fb6f077124 100644 --- a/other_resources/scripts/create_sf_example.py +++ b/other_resources/scripts/create_sf_example.py @@ -1,6 +1,8 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import os import sys @@ -23,7 +25,6 @@ def create_subset(dest_store, dest_skims, maxZone, households_sample_size=0): - dest_store_path = os.path.join(dest_data_dir, dest_store) dest_skims_path = os.path.join(dest_data_dir, dest_skims) diff --git a/other_resources/scripts/make_pipeline_output.py b/other_resources/scripts/make_pipeline_output.py index 4dd69d4a8b..deb8965a2d 100644 --- a/other_resources/scripts/make_pipeline_output.py +++ b/other_resources/scripts/make_pipeline_output.py @@ -2,6 +2,8 @@ # Ben Stabler, ben.stabler@rsginc.com, 06/06/18 # C:\projects\development\activitysim\example>python ../scripts/make_pipeline_output.py +from __future__ import annotations + import pandas as pd pipeline_filename = "output\\pipeline.h5" @@ -26,7 +28,6 @@ # TABLE, FIELD, DTYPE, CREATOR, NCOL, NROW tables_fields = dict() for i in range(len(p_tables)): - cur_table = p_tables["table"].iloc[i] cur_cp = p_tables["cp"].iloc[i] diff --git a/other_resources/scripts/omx32.py b/other_resources/scripts/omx32.py index 53be977ec5..d471383e1e 100644 --- a/other_resources/scripts/omx32.py +++ b/other_resources/scripts/omx32.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import argparse import os @@ -37,7 +39,6 @@ for mat_name in omx_in.list_matrices(): - # make sure we have a vanilla numpy array, not a CArray m = np.asanyarray(omx_in[mat_name]) print(f"{mat_name} {m.shape} {type(m[0,0])}") diff --git a/other_resources/scripts/simulation.py b/other_resources/scripts/simulation.py index 0f0d0d5f09..9ad24395aa 100644 --- a/other_resources/scripts/simulation.py +++ b/other_resources/scripts/simulation.py @@ -1,6 +1,8 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import logging import sys @@ -13,7 +15,6 @@ def cleanup_output_files(state: workflow.State): - active_log_files = [ h.baseFilename for h in logger.root.handlers @@ -30,7 +31,6 @@ def cleanup_output_files(state: workflow.State): def run(run_list, injectables=None): - if run_list["multiprocess"]: logger.info("run multiprocess simulation") mp_tasks.run_multiprocess(run_list, injectables) @@ -42,7 +42,6 @@ def run(run_list, injectables=None): def log_settings(injectables): - settings = [ "households_sample_size", "chunk_size", @@ -59,7 +58,6 @@ def log_settings(injectables): if __name__ == "__main__": - state.add_injectable("data_dir", "data") state.add_injectable("configs_dir", "configs") diff --git a/other_resources/scripts/verify_results.py b/other_resources/scripts/verify_results.py index d5868ae165..efe93d1c3b 100644 --- a/other_resources/scripts/verify_results.py +++ b/other_resources/scripts/verify_results.py @@ -4,6 +4,8 @@ # C:\projects\activitysim\verification>python compare_results.py ############################################################# +from __future__ import annotations + import openmatrix as omx import pandas as pd @@ -138,7 +140,6 @@ # work and school location if process_sp: - if process_tm1: tm1_markets = [ "work_low", diff --git a/pyproject.toml b/pyproject.toml index 1cb6915f10..f8990da5ed 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,6 +11,7 @@ name = "activitysim" dynamic = ["version"] dependencies = [ "cytoolz >= 0.8.1", + "multimethod < 2.0", "numba >= 0.57", "numpy >= 1.16.1, <2", "openmatrix >= 0.3.4.1", diff --git a/test/cdap/test_cdap.py b/test/cdap/test_cdap.py index c48a4f1ac2..38e2657769 100644 --- a/test/cdap/test_cdap.py +++ b/test/cdap/test_cdap.py @@ -18,6 +18,7 @@ logger = logging.getLogger(__name__) + # Used by conftest.py initialize_pipeline method @pytest.fixture(scope="module") def module() -> str: diff --git a/test/joint_tours/test_joint_tours.py b/test/joint_tours/test_joint_tours.py index 40c022240e..3f68acb48a 100644 --- a/test/joint_tours/test_joint_tours.py +++ b/test/joint_tours/test_joint_tours.py @@ -16,6 +16,7 @@ logger = logging.getLogger(__name__) + # Used by conftest.py initialize_pipeline method @pytest.fixture(scope="module") def module() -> str: @@ -81,7 +82,6 @@ def test_prepare_input_pipeline(initialize_pipeline: workflow.State, caplog): def test_joint_tours_frequency_composition(reconnect_pipeline: workflow.State, caplog): - caplog.set_level(logging.INFO) state = reconnect_pipeline @@ -96,7 +96,6 @@ def test_joint_tours_frequency_composition(reconnect_pipeline: workflow.State, c def test_joint_tours_participation(reconnect_pipeline: workflow.State, caplog): - caplog.set_level(logging.INFO) state = reconnect_pipeline diff --git a/test/non_mandatory_tour_frequency/test_non_mandatory_tour_frequency.py b/test/non_mandatory_tour_frequency/test_non_mandatory_tour_frequency.py index 135ea34542..c11e2f67b8 100644 --- a/test/non_mandatory_tour_frequency/test_non_mandatory_tour_frequency.py +++ b/test/non_mandatory_tour_frequency/test_non_mandatory_tour_frequency.py @@ -18,6 +18,7 @@ logger = logging.getLogger(__name__) + # Used by conftest.py initialize_pipeline method @pytest.fixture(scope="module") def module() -> str: diff --git a/test/parking_location/test_parking_location.py b/test/parking_location/test_parking_location.py index 3062c3a9d6..53d228ca6e 100644 --- a/test/parking_location/test_parking_location.py +++ b/test/parking_location/test_parking_location.py @@ -19,6 +19,7 @@ logger = logging.getLogger(__name__) + # Used by conftest.py initialize_pipeline method @pytest.fixture(scope="module") def module() -> str: diff --git a/test/random_seed/simulation.py b/test/random_seed/simulation.py index 8313dd45e7..70cf3457fd 100644 --- a/test/random_seed/simulation.py +++ b/test/random_seed/simulation.py @@ -1,13 +1,14 @@ # ActivitySim # See full license in LICENSE.txt. +from __future__ import annotations + import argparse import sys from activitysim.cli.run import add_run_args, run if __name__ == "__main__": - parser = argparse.ArgumentParser() add_run_args(parser) args = parser.parse_args() diff --git a/test/random_seed/test_random_seed.py b/test/random_seed/test_random_seed.py index e3cae43f1a..6f4997f62d 100644 --- a/test/random_seed/test_random_seed.py +++ b/test/random_seed/test_random_seed.py @@ -25,7 +25,6 @@ def update_settings(settings_file, key, value): def run_test_random_seed(): - steps_to_run = [ "initialize_landuse", "initialize_households", @@ -86,7 +85,6 @@ def check_outputs(df1, df2, should_be_equal=True): # running prototype mtc model through workplace_location with 3 random seed settings, 0, 1, None, and undefined. # final_persons.csv is compared to ensure the same setting returns the same variables and a different setting returns something different. for name, seed in runs: - run_args = [ "-c", test_path("configs_random_seed__{}".format(seed)), From ed3ee7f4c5a7ad982533a66e6fd441b4e45370c9 Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Thu, 15 May 2025 16:24:45 -0700 Subject: [PATCH 36/56] handling missing data or availability conditions --- activitysim/estimation/larch/location_choice.py | 4 ++++ activitysim/estimation/larch/nonmand_tour_freq.py | 2 ++ 2 files changed, 6 insertions(+) diff --git a/activitysim/estimation/larch/location_choice.py b/activitysim/estimation/larch/location_choice.py index 784ce4f124..5c50f6b736 100644 --- a/activitysim/estimation/larch/location_choice.py +++ b/activitysim/estimation/larch/location_choice.py @@ -350,6 +350,10 @@ def split(a, n): total_size_segment += ( landuse[land_use_field] * size_spec.loc[segment, land_use_field] ) + if -1 in x_co["override_choice"].values: + print("Warning: override_choice contains -1, adding 0 to total_size") + print("You should probably remove data containing -1 from your data") + total_size_segment.loc[-1] = 0 x_co["total_size_" + segment] = total_size_segment.loc[ x_co["override_choice"] ].to_numpy() diff --git a/activitysim/estimation/larch/nonmand_tour_freq.py b/activitysim/estimation/larch/nonmand_tour_freq.py index 90c56ecedb..5db873b68f 100644 --- a/activitysim/estimation/larch/nonmand_tour_freq.py +++ b/activitysim/estimation/larch/nonmand_tour_freq.py @@ -164,6 +164,8 @@ def unavail_data_cols(model): def unavail(model, x_ca): lock_data = unavail_data_cols(model) + # intialize unavail to False array of same length as x_ca + unav = pd.Series(False, index=x_ca.index) if len(lock_data): unav = x_ca[lock_data[0]] > 0 for j in lock_data[1:]: From 4ed400e815fde2bcd96f279f85d481d65d559f18 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Mon, 19 May 2025 21:36:47 -0500 Subject: [PATCH 37/56] add docs on locking size terms --- docs/users-guide/estimation-mode/larch.md | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/docs/users-guide/estimation-mode/larch.md b/docs/users-guide/estimation-mode/larch.md index 370c2ac400..c120111876 100644 --- a/docs/users-guide/estimation-mode/larch.md +++ b/docs/users-guide/estimation-mode/larch.md @@ -269,6 +269,16 @@ for all other size-based models. When copying the revised size term specificati to the model configuration, the user should be careful that re-estimation updates from multiple models are not inadvertently overwriting each other. +As an alternative, users can choose to *not* re-estimate the size terms, by +providing exogenous size terms in the model specification, and instructing Larch +not to re-estimate these parameters. This is done via the `Model.lock_value` +command, which will fix any given named parameter to a specific value. This command +takes two arguments: the name of the parameter to be fixed, and the value to +fix it to. The `lock_value` command can be used to fix the size term parameters +to the values in the size term specification file, and then the model will be +estimated without re-estimating the size terms. If no re-estimation is desired, +users can also safely ignore the `update_size_spec` function. + ## Example Notebooks ActivitySim includes a collection of Jupyter notebooks with From 8f3439c0defc520dc1bb880ce31ab98b2d38ef8b Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Tue, 27 May 2025 13:58:05 -0500 Subject: [PATCH 38/56] include constants in CDAP --- activitysim/estimation/larch/cdap.py | 31 ++++++++++++++++------------ 1 file changed, 18 insertions(+), 13 deletions(-) diff --git a/activitysim/estimation/larch/cdap.py b/activitysim/estimation/larch/cdap.py index 8944c5c8b5..401cb1ae4b 100644 --- a/activitysim/estimation/larch/cdap.py +++ b/activitysim/estimation/larch/cdap.py @@ -111,11 +111,17 @@ def cdap_base_utility_by_person( if n_persons == 1: for i in spec.index: if not pd.isna(spec.loc[i, "M"]): - model.utility_co[1] += X(spec.Expression[i]) * P(spec.loc[i, "M"]) + model.utility_co[1] += X(spec.Expression[i].lstrip("@")) * P( + spec.loc[i, "M"] + ) if not pd.isna(spec.loc[i, "N"]): - model.utility_co[2] += X(spec.Expression[i]) * P(spec.loc[i, "N"]) + model.utility_co[2] += X(spec.Expression[i].lstrip("@")) * P( + spec.loc[i, "N"] + ) if not pd.isna(spec.loc[i, "H"]): - model.utility_co[3] += X(spec.Expression[i]) * P(spec.loc[i, "H"]) + model.utility_co[3] += X(spec.Expression[i].lstrip("@")) * P( + spec.loc[i, "H"] + ) else: if alts is None: alts = generate_alternatives(n_persons, add_joint) @@ -128,7 +134,9 @@ def cdap_base_utility_by_person( x = apply_replacements( spec.Expression[i], f"p{pnum}", value_tokens ) - model.utility_co[anum] += X(x) * P(spec.loc[i, aname[z]]) + model.utility_co[anum] += X(x.lstrip("@")) * P( + spec.loc[i, aname[z]] + ) def interact_pattern(n_persons, select_persons, tag): @@ -350,13 +358,6 @@ def cdap_dataframes(households, values, add_joint) -> dict[int, lx.Dataset]: dims=dfs[hhsize].override_choice.dims, name="override_choice", ) - # dfs[hhsize] = DataFrames( - # co=data[hhsize], - # alt_names=alts.keys(), - # alt_codes=alts.values(), - # av=1, - # ch=data[hhsize].override_choice.map(alts), - # ) return dfs @@ -489,11 +490,15 @@ def cdap_model( interaction_coef = d.interaction_coef coefficients = d.coefficients add_joint = d.add_joint + extra_vars = d.settings.get("CONSTANTS", {}) cdap_dfs = cdap_dataframes(households, values, add_joint) m = {} _logger.info(f"building for model 1") - m[1] = lx.Model(datatree=cdap_dfs[1], compute_engine="numba") + m[1] = lx.Model( + datatree=cdap_dfs[1].dc.as_tree("df", extra_vars=extra_vars), + compute_engine="numba", + ) cdap_base_utility_by_person(m[1], n_persons=1, spec=spec1) m[1].choice_co_code = "override_choice" m[1].availability_any = True @@ -506,7 +511,7 @@ def cdap_model( for s in range(2, MAX_HHSIZE + 1): # for s in [2, 3, 4, 5]: _logger.info(f"building for model {s}") - m[s] = lx.Model(datatree=cdap_dfs[s]) + m[s] = lx.Model(datatree=cdap_dfs[s].dc.as_tree("df", extra_vars=extra_vars)) alts = generate_alternatives(s, add_joint) cdap_base_utility_by_person(m[s], s, spec1, alts, values.columns) cdap_interaction_utility(m[s], s, alts, interaction_coef, coefficients) From c2f8570fbae30dd86080795bf85e4894fc625d58 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Wed, 28 May 2025 12:14:39 -0500 Subject: [PATCH 39/56] bump larch requirement --- conda-environments/activitysim-dev-base.yml | 2 +- conda-environments/activitysim-dev.yml | 2 +- conda-environments/docbuild.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/conda-environments/activitysim-dev-base.yml b/conda-environments/activitysim-dev-base.yml index 2fd28c5f3e..6b3a2d7911 100644 --- a/conda-environments/activitysim-dev-base.yml +++ b/conda-environments/activitysim-dev-base.yml @@ -31,7 +31,7 @@ dependencies: - ipykernel # so this env will appear in jupyter as a selection - isort - jupyterlab -- larch >= 6.0.34 +- larch >= 6.0.39 - matplotlib - multimethod <2.0 - myst-parser # allows markdown in sphinx diff --git a/conda-environments/activitysim-dev.yml b/conda-environments/activitysim-dev.yml index 90faa881b4..bb1549ef8d 100644 --- a/conda-environments/activitysim-dev.yml +++ b/conda-environments/activitysim-dev.yml @@ -75,5 +75,5 @@ dependencies: - pip: - autodoc_pydantic - - larch >= 6.0.34 + - larch >= 6.0.39 - -e .. diff --git a/conda-environments/docbuild.yml b/conda-environments/docbuild.yml index 69b8a047f2..de471874b2 100644 --- a/conda-environments/docbuild.yml +++ b/conda-environments/docbuild.yml @@ -58,5 +58,5 @@ dependencies: - pip: - autodoc_pydantic - - larch >= 6.0.34 + - larch >= 6.0.39 - -e .. From cdc97526f03d665096dc8fb25e680ed5c3312146 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Thu, 29 May 2025 09:25:56 -0500 Subject: [PATCH 40/56] require larch 6.0.40 --- conda-environments/activitysim-dev-base.yml | 2 +- conda-environments/activitysim-dev.yml | 2 +- conda-environments/docbuild.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/conda-environments/activitysim-dev-base.yml b/conda-environments/activitysim-dev-base.yml index 6b3a2d7911..a83aa5d8df 100644 --- a/conda-environments/activitysim-dev-base.yml +++ b/conda-environments/activitysim-dev-base.yml @@ -31,7 +31,7 @@ dependencies: - ipykernel # so this env will appear in jupyter as a selection - isort - jupyterlab -- larch >= 6.0.39 +- larch >= 6.0.40 - matplotlib - multimethod <2.0 - myst-parser # allows markdown in sphinx diff --git a/conda-environments/activitysim-dev.yml b/conda-environments/activitysim-dev.yml index bb1549ef8d..b5f7b68adb 100644 --- a/conda-environments/activitysim-dev.yml +++ b/conda-environments/activitysim-dev.yml @@ -75,5 +75,5 @@ dependencies: - pip: - autodoc_pydantic - - larch >= 6.0.39 + - larch >= 6.0.40 - -e .. diff --git a/conda-environments/docbuild.yml b/conda-environments/docbuild.yml index de471874b2..c91b734f03 100644 --- a/conda-environments/docbuild.yml +++ b/conda-environments/docbuild.yml @@ -58,5 +58,5 @@ dependencies: - pip: - autodoc_pydantic - - larch >= 6.0.39 + - larch >= 6.0.40 - -e .. From 6f1b66a7784b9d5973d853281cd45ff07d42991a Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Thu, 29 May 2025 10:20:47 -0500 Subject: [PATCH 41/56] add xlsxwriter to envs --- conda-environments/activitysim-dev-base.yml | 1 + conda-environments/activitysim-dev.yml | 1 + conda-environments/docbuild.yml | 1 + 3 files changed, 3 insertions(+) diff --git a/conda-environments/activitysim-dev-base.yml b/conda-environments/activitysim-dev-base.yml index a83aa5d8df..456405ebed 100644 --- a/conda-environments/activitysim-dev-base.yml +++ b/conda-environments/activitysim-dev-base.yml @@ -73,6 +73,7 @@ dependencies: - sphinx_rtd_theme = 1.2.* - sphinx-argparse = 0.4.* - xarray = 2025.01.* +- xlsxwriter - xmle - zarr>=2,<3 - zstandard diff --git a/conda-environments/activitysim-dev.yml b/conda-environments/activitysim-dev.yml index b5f7b68adb..0cf2805340 100644 --- a/conda-environments/activitysim-dev.yml +++ b/conda-environments/activitysim-dev.yml @@ -69,6 +69,7 @@ dependencies: - sphinx_rtd_theme = 1.2.* - sphinx-argparse = 0.4.* - xarray = 2025.01.* +- xlsxwriter - xmle - zarr>=2,<3 - zstandard diff --git a/conda-environments/docbuild.yml b/conda-environments/docbuild.yml index c91b734f03..99738e8221 100644 --- a/conda-environments/docbuild.yml +++ b/conda-environments/docbuild.yml @@ -54,6 +54,7 @@ dependencies: - sphinx-remove-toctrees - sphinx_rtd_theme - xarray = 2025.01.* +- xlsxwriter - zarr>=2,<3 - pip: From f08dc51038b98364b152c168cfec8608db9425c3 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Fri, 30 May 2025 20:17:27 -0500 Subject: [PATCH 42/56] require larch 6.0.41 --- conda-environments/activitysim-dev-base.yml | 2 +- conda-environments/activitysim-dev.yml | 2 +- conda-environments/docbuild.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/conda-environments/activitysim-dev-base.yml b/conda-environments/activitysim-dev-base.yml index 456405ebed..64bbbf1309 100644 --- a/conda-environments/activitysim-dev-base.yml +++ b/conda-environments/activitysim-dev-base.yml @@ -31,7 +31,7 @@ dependencies: - ipykernel # so this env will appear in jupyter as a selection - isort - jupyterlab -- larch >= 6.0.40 +- larch >= 6.0.41 - matplotlib - multimethod <2.0 - myst-parser # allows markdown in sphinx diff --git a/conda-environments/activitysim-dev.yml b/conda-environments/activitysim-dev.yml index 0cf2805340..f37d6c0d48 100644 --- a/conda-environments/activitysim-dev.yml +++ b/conda-environments/activitysim-dev.yml @@ -76,5 +76,5 @@ dependencies: - pip: - autodoc_pydantic - - larch >= 6.0.40 + - larch >= 6.0.41 - -e .. diff --git a/conda-environments/docbuild.yml b/conda-environments/docbuild.yml index 99738e8221..4515cb883a 100644 --- a/conda-environments/docbuild.yml +++ b/conda-environments/docbuild.yml @@ -59,5 +59,5 @@ dependencies: - pip: - autodoc_pydantic - - larch >= 6.0.40 + - larch >= 6.0.41 - -e .. From aa8091af133f30118416da4c09c0172391ad3982 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Thu, 5 Jun 2025 09:19:53 -0500 Subject: [PATCH 43/56] add links --- docs/users-guide/estimation-mode/larch.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/docs/users-guide/estimation-mode/larch.md b/docs/users-guide/estimation-mode/larch.md index c120111876..e9497657b5 100644 --- a/docs/users-guide/estimation-mode/larch.md +++ b/docs/users-guide/estimation-mode/larch.md @@ -301,13 +301,15 @@ statistical tests to determine if the changes made are statistically significant The following notebooks include examples of modifying the model specification: -- `03_work_location.ipynb`: This notebook includes a demonstration of +- [`03_work_location.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/03_work_location.ipynb): + This notebook includes a demonstration of modification to the SPEC file for a destination choice model, using the "interact-sample-simulate" type model. -- `04_auto_ownership.ipynb`: This notebook includes a demonstration of - modification to the SPEC file for the +- [`04_auto_ownership.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/04_auto_ownership.ipynb): + This notebook includes a demonstration of modification to the SPEC file for the auto ownership model. It shows an example of an edit in the utility function for a "simple simulate" type model. -- `06_cdap.ipynb`: This notebook includes a demonstration of modification to +- [`06_cdap.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/06_cdap.ipynb): + This notebook includes a demonstration of modification to the SPEC file for the CDAP model. This model has a complex structure that is unique among the ActivitySim component models. From c08236192c5f00d4ec4ebb005576addc9ad37761 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Thu, 5 Jun 2025 09:34:12 -0500 Subject: [PATCH 44/56] fix typos and formatting --- docs/users-guide/estimation-mode/larch.md | 269 +++++++++++----------- 1 file changed, 136 insertions(+), 133 deletions(-) diff --git a/docs/users-guide/estimation-mode/larch.md b/docs/users-guide/estimation-mode/larch.md index e9497657b5..a1c7ee3ef6 100644 --- a/docs/users-guide/estimation-mode/larch.md +++ b/docs/users-guide/estimation-mode/larch.md @@ -1,81 +1,83 @@ # Using Larch -ActivitySim component models are mostly built as discrete choice models. The +ActivitySim component models are mostly built as discrete choice models. The parameters for these models typically need to be estimated based on observed -survey data. The estimation process is facilitated by the Larch package, which -is a Python package for estimating discrete choice models. Larch is a +survey data. The estimation process is facilitated by the Larch package, which +is a Python package for estimating discrete choice models. Larch is a general-purpose package that can be used to estimate a wide variety of discrete -choice models, including the multinomial logit and nested logit models that -are commonly used in ActivitySim. This section highlights some of the features -of Larch, particularly as they relate to ActivitySim, as there are a few subtle +choice models, including the multinomial logit and nested logit models that are +commonly used in ActivitySim. This section highlights some of the features of +Larch, particularly as they relate to ActivitySim, as there are a few subtle differences between the two packages that users should be aware of when estimating models. ## Setting up Larch Models -ActivitySim includes a number of scripts and tools to set up Larch models -for estimation. The `activitysim.estimation.larch` library includes -functions to read the EDBs written by ActivitySim and convert them into -Larch models, including a generic [`component_model`](activitysim.estimation.larch.component_model) -function that can be used to load the data and set up Larch for any standard ActivitySim component. -This function is demonstrated in the [example notebooks](#example-notebooks). - -When given a truthy `return_data` argument, the `component_model` function -will return a 2-tuple of the Larch model and the data used to create it. The -data as the second element of this tuple should be treated as a *copy* of the -data used to create the model, and is provided primarily for the user to review -and use in debugging if needed. If it is necessary to modify the data (e.g. to -recreate temporary variables), the user should modify the `data` attribute of -the model itself (i.e. `model.data` if `model` is the first element of the -returned tuple), not the data returned in the second element of the tuple. +ActivitySim includes a number of scripts and tools to set up Larch models for +estimation. The `activitysim.estimation.larch` library includes functions to +read the EDBs written by ActivitySim and convert them into Larch models, +including a generic [`component_model`](activitysim.estimation.larch.component_model) +function that can be used to load the data and set up Larch for any standard +ActivitySim component. This function is demonstrated in the [example notebooks] +(#example-notebooks). + +When given a truthy `return_data` argument, the `component_model` function will +return a 2-tuple of the Larch model and the data used to create it. The data as +the second element of this tuple should be treated as a *copy* of the data used +to create the model, and is provided primarily for the user to review and use in +debugging if needed. If it is necessary to modify the data (e.g. to recreate +temporary variables), the user should modify the `data` attribute of the model +itself (i.e. `model.data` if `model` is the first element of the returned +tuple), not the data returned in the second element of the tuple. ## Model Specification -By default, the process of estimating parameters for ActivitySim model components -with Larch is based on the existing model specification files. These are the -CSV files that are used to define the utility function for each logit component. -When running ActivitySim, these files are typically found in the configs directory, -but when running in estimation mode, they are written out to the EDB as well, which -is where the `activitysim.estimation.larch` library functions look for these -input files. - -Users are not limited to using the existing model specification files, however. The -Larch tools for model estimation now allow users to modify the model specification -files, and then re-estimate the model, including existing and new parameters. -The revised model specification files must rely on the same data that has already -been written out to the EDB, but the user can add new expressions to the specification -to transform the data, or to create new variables. This is particularly useful -for creating new piecewise linear transformations, or for creating new categorical -variables from continuous variables. The user can also add new variables to the -specification that are not in the EDB, but this will require re-running ActivitySim -in estimation mode to write a new EDB. Examples for how to re-specify the model -specification files are included in -[selected example notebooks](#examples-that-include-re-specification). +By default, the process of estimating parameters for ActivitySim model +components with Larch is based on the existing model specification files. These +are the CSV files that are used to define the utility function for each logit +component. When running ActivitySim, these files are typically found in the +configs directory, but when running in estimation mode, they are written out to +the EDB as well, which is where the `activitysim.estimation.larch` library +functions look for these input files. + +Users are not limited to using the existing model specification files, however. +The Larch tools for model estimation now allow users to modify the model +specification files, and then re-estimate the model, including existing and new +parameters. The revised model specification files must rely on the same data +that has already been written out to the EDB, but the user can add new +expressions to the specification to transform the data, or to create new +variables. This is particularly useful for creating new piecewise linear +transformations, or for creating new categorical variables from continuous +variables. The user can also add new variables to the specification that are not +in the EDB, but this will require re-running ActivitySim in estimation mode to +write a new EDB. Examples for how to re-specify the model specification files +are included in [selected example notebooks](#examples-that-include-re-specification). ## Maximum Likelihood Estimation The approach used to estimate the parameters of a discrete choice model is -maximum likelihood estimation (MLE). The goal of MLE is to find the set of +maximum likelihood estimation (MLE). The goal of MLE is to find the set of parameters that maximize the likelihood of observing the choice data that we have collected. Finding the maximum likelihood estimates of the parameters is a non-linear -optimization problem. To solve this problem, Larch primarily relies on the +optimization problem. To solve this problem, Larch primarily relies on the widely-used `scipy.optimize` package, which provides a number of [optimization algorithms](https://docs.scipy.org/doc/scipy/reference/optimize.html#local-multivariate-optimization) that can be used to find the maximum likelihood estimates. Different algorithms have different strengths and weaknesses, and the choice of algorithm can have a -significant impact on the speed and accuracy of the estimation process. By default, -when no constraints or bounds are present, Larch uses an implementation of the -[BHHH algorithm](https://en.wikipedia.org/wiki/Berndt–Hall–Hall–Hausman_algorithm), -which is not included in scipy but is usually efficient for simple, well specified -choice models without any constraints. When constraints or bounds are present, by default Larch uses the -Larch uses the `scipy.optimize.minimize` function with the `SLSQP` algorithm. -The `larch.Model.estimate` method allows the -user to specify the optimization algorithm to use via the `method` argument, which -can be set to 'BHHH', 'SLSQP', or any other algorithm supported by `scipy.optimize.minimize`. +significant impact on the speed and accuracy of the estimation process. By +default, when no constraints or bounds are present, Larch uses an +implementation of the [BHHH algorithm](https://en.wikipedia.org/wiki/Berndt–Hall–Hall–Hausman_algorithm), +which is not included in scipy but is usually efficient for simple, well +specified choice models without any constraints. When constraints or bounds are +present, by default Larch uses the `scipy.optimize.minimize` function with the +`SLSQP` algorithm. The `larch.Model.estimate` method allows the user to specify +the optimization algorithm to use via the `method` argument, which can be set to +'BHHH', 'SLSQP', or any other algorithm supported by `scipy.optimize.minimize`. If you are estimating a model and find the optimization is not converging as -fast as expected (or at all), you may want to try a different optimization algorithm. +fast as expected (or at all), you may want to try a different optimization +algorithm. ## Model Evaluation @@ -90,45 +92,46 @@ of a Larch model data’s choice and availability statistics is available. Larch also includes methods to [analyze model predictions](https://larch.driftless.xyz/v6.0/user-guide/analysis.html#analyze-predictions) across various dimensions. The `analyze_predictions_co` method can be used to -examine how well the model predicts choices against any available (or computable) -attribute of the chooser. In addition, there are tools to evaluate -[demand elasticity](https://larch.driftless.xyz/v6.0/user-guide/analysis.html#elasticity) -with respect to changes in underlying data. +examine how well the model predicts choices against any available (or +computable) attribute of the chooser. In addition, there are tools to evaluate +[demand elasticity](https://larch.driftless.xyz/v6.0/user-guide/analysis.html#elasticity) with +respect to changes in underlying data. ## Model Overspecification When using ActivitySim for simulation, there are generally few limitations or -requirements on the uniqueness of data elements. For example, it may end up being -confusing for a user, but there is nothing -fundamentally wrong with having two different variables in the model specification -that both represent "income" but have different scales, or with having -alternative-specific constants for all the alternatives. -In model estimation, however, this can lead to problems. Having two data elements -that are perfectly correlated (e.g. two different variables that both represent "income") -or having a full set of alternative-specific values for all the alternatives can lead to -numerical problems in the estimation process, as the log likelihood function will -have flat areas and will not have a unique maximum. This is called "model overspecification". -In Larch, the user is warned if an estimated model appears to be overspecified, -see the Larch documentation [for details](https://larch.driftless.xyz/v6.0/user-guide/choice-models.html#overspecification). +requirements on the uniqueness of data elements. For example, it may end up +being confusing for a user, but there is nothing fundamentally wrong with having +two different variables in the model specification that both represent "income" +but have different scales, or with having alternative-specific constants for all +the alternatives. In model estimation, however, this can lead to problems. +Having two data elements that are perfectly correlated (e.g. two different +variables that both represent "income") or having a full set of +alternative-specific values for all the alternatives can lead to numerical +problems in the estimation process, as the log likelihood function will have +flat areas and will not have a unique maximum. This is called "model +overspecification". In Larch, the user is warned if an estimated model appears +to be overspecified, see the Larch documentation +[for details](https://larch.driftless.xyz/v6.0/user-guide/choice-models.html#overspecification). ## Recreating Temporary Variables -When writing out estimation data bundles, ActivitySim may omit certain -temporary variables included in a model spec. For example, in the example -workplace location choice model, the spec creates a temporary variable +When writing out estimation data bundles, ActivitySim may omit certain temporary +variables included in a model spec. For example, in the example workplace +location choice model, the spec creates a temporary variable ["_DIST"](https://github.com/ActivitySim/activitysim-prototype-mtc/blob/7da9d6d6deca670cc4701fea749a270ab6fe77aa/configs/workplace_location.csv#L2) -which is then reused in several subsequent expressions. When the model's +which is then reused in several subsequent expressions. When the model's estimation data bundle is written out, the "_DIST" variable may not be -included[^1]. This is not a problem when simply re-estimating the parameters -of the current model specification, as all of the piecewise linear transformations -that use "_DIST" are included. However, if the user wanted to change those -piecewise linear transformations (e.g. by moving the breakpoints), the -absence of the "_DIST" value will be relevant. +included[^1]. This is not a problem when simply re-estimating the parameters of +the current model specification, as all the piecewise linear transformations +that use "_DIST" are included. However, if the user wanted to change those +piecewise linear transformations (e.g. by moving the breakpoints), the absence +of the "_DIST" value will be relevant. [^1]: Future versions of ActivitySim may include these values in the EDB output. If the missing temporary value can be reconstructed from the data that *is* -included in the EDB, it can be added back into the model's data. For example, +included in the EDB, it can be added back into the model's data. For example, here we reconstitute the total distance by summing up over the piecewise component parts: @@ -143,19 +146,19 @@ model.data["_DIST"] = ( ``` Note in this expression, we are modifying `model.data`, i.e. the data attached -to the model. If have other raw data available in our estimation notebook, -e.g. from running `model, data = component_model(..., return_data=True)`, it -is not sufficient to manipulate `data` itself, we must manipulate `model.data` -or otherwise re-attach any data changes to the model, or else the changes will -not show up in estimation. +to the model. If you have other raw data available in your estimation notebook, +e.g., from running `model, data = component_model(..., return_data=True)`, it is +not sufficient to manipulate `data` itself; you must manipulate `model.data` or +otherwise re-attach any data changes to the model, or else the changes will not +show up in estimation. ## Expressing Alternative Availability In ActivitySim, the unavailability of alternatives is typically expressed in the -utility function given in the model specification, by including a indicator variable +utility function given in the model specification, by including an indicator variable for unavailable alternatives, which is then attached to a large negative coefficient. This creates a large negative utility for the unavailable alternative, which will -render it effectively unavailable in the choice model. If *all* the alternatives +render it effectively unavailable in the choice model. If *all* the alternatives are made unavailable in this manner, this can result in a condition where no alternative can be chosen, and ActivitySim will raise an error. @@ -163,12 +166,12 @@ When estimating models in Larch for use with ActivitySim, it is totally acceptab appropriate to use this approach to express alternative availability, by embedding it in the utility function. This will greatly simplify the process of subsequently transferring the resulting model specification and parameters -back to the ActivitySim model. However, it is important to note that this +back to the ActivitySim model. However, it is important to note that this approach is not the only way to express alternative availability in Larch. Larch includes a system to define the availability of alternatives explicitly as a [separate array of values](https://larch.driftless.xyz/dev/user-guide/choice-models.html#availability), -which is not included in the utility function. This is +which is not included in the utility function. This is more robust in estimation, as the Larch computational engine can (and will) automatically shift the utility values to avoid numerical underflow or overflow issues that can arise when some choices are very unlikely but not strictly unavailable. @@ -192,8 +195,8 @@ processes as expected. ## Components that have Related Models Within ActivitySim, it is possible for multiple parts of model components -to share a common set of coefficients. It is even possible for completely -separate components to do so. For example, in the MTC example model, +to share a common set of coefficients. It is even possible for completely +separate components to do so. For example, in the MTC example model, the joint tour destination choice model and the non-mandatory tour destination choice model share a common set of coefficients written in a single file. To re-estimate these coefficients, the user must simultaneously work with all @@ -201,27 +204,27 @@ the estimation survey data from both models. In Larch, the case of two models sharing coefficients is handled by creating two separate `Model` objects, one for each model, and then using the `ModelGroup` object to link them -together. The `ModelGroup` object allows the user to specify a set of common parameters +together. The `ModelGroup` object allows the user to specify a set of common parameters for two or more models, and then estimate them together. In the case of re-estimating the joint tour destination choice model and the non-mandatory tour destination choice model, it may be that both models have a similar (or even identical) utility structure. In other cases, the linked models may have different utility structures, which share a subset of parameters, but also may have other parameters -that are unique to each model. In either case, when using the `ModelGroup` object, +that are unique to each model. In either case, when using the `ModelGroup` object, parameters are identified as being linked across models by having a common name. There are also components in ActivitySim where a single component can embed multiple discrete choice models which share details, but each sub-model can have a different -utility structure or different sets of parameters. For example, the `tour_mode_choice` +utility structure or different sets of parameters. For example, the `tour_mode_choice` component has a coefficient template file, which allows the model developer to specify a different set of coefficients for each tour purpose, which are otherwise -processed using a common utility function. This is implemented in Larch with the +processed using a common utility function. This is implemented in Larch with the `ModelGroup` object, where each purpose is represented as a separate `Model` object, -and the `ModelGroup` object is used to link them together. This logic is further +and the `ModelGroup` object is used to link them together. This logic is further extended by including the at-work subtour mode choice component, which allows for the joint estimation of the tour mode choice model and the at-work subtour mode choice model, which very reasonably share numerous parameters, but also have a few -differences. Similarly, the stop frequency and CDAP models are implemented for +differences. Similarly, the stop frequency and CDAP models are implemented for Larch estimation as `ModelGroup` objects, segmented on tour purpose and household size, respectively. @@ -229,7 +232,7 @@ When estimating a `ModelGroup` object, process for estimating the likelihood maximizing parameters is the same as for a single model: the log likelihood is computed for each observation (i.e. chooser) in the data set according to the parameters, model, and data for that chooser, and the overall log likelihood is the sum of all the -chooser log likelihoods. By using this approach, the rest of the estimation process is +chooser log likelihoods. By using this approach, the rest of the estimation process is the same as for a single model, including finding parameter estimates, the standard error of those estimates, and any statistical tests or interpretations that are desired. @@ -237,7 +240,7 @@ desired. ## Components with Size Terms Location choice models in ActivitySim (and in discrete choice modeling -in general) usually include a "size" term. The size term is a measure +in general) usually include a "size" term. The size term is a measure of the quantity of the alternative, which in location choice models is typically a geographic area that contains multiple distinct alternatives. For example, in a workplace location choice model, the size term might @@ -247,69 +250,69 @@ can be composed of multiple components, such as the number of employers, the number of households, and/or the number of retail establishments. The size term is included in the utility function of the model, but it is -expressed differently from other qualitative measures. The typical model +expressed differently from other qualitative measures. The typical model specification for a location choice model will include a utility function given in a spec file, which will represent the quality of the alternative(s) -that are being considered. Put another way, the "regular" utility function +that are being considered. Put another way, the "regular" utility function is a measure of the quality of the alternative, while the size term is a measure of the quantity of the alternative. In ActivitySim, size terms appear not in the utility spec files, but instead are expressed in a separate "size term" spec file, typically named -"destination_choice_size_terms.csv". This one file contains all of the size -terms for all of the location choice models. +"destination_choice_size_terms.csv". This one file contains all the size +terms for all the location choice models. When using Larch for model estimation, size terms can be estimated alongside the other parameters. The `update_size_spec` function in the `activitysim.estimation.larch` library -allows the user to update the size term specification for a model. This function +allows the user to update the size term specification for a model. This function takes the existing size term specification and updates the appropriate rows -that correspond to the model being re-estimated. The resulting updated size +that correspond to the model being re-estimated. The resulting updated size term output file will also include the (unmodified) size term specification -for all other size-based models. When copying the revised size term specification +for all other size-based models. When copying the revised size term specification to the model configuration, the user should be careful that re-estimation updates from multiple models are not inadvertently overwriting each other. As an alternative, users can choose to *not* re-estimate the size terms, by providing exogenous size terms in the model specification, and instructing Larch -not to re-estimate these parameters. This is done via the `Model.lock_value` -command, which will fix any given named parameter to a specific value. This command +not to re-estimate these parameters. This is done via the `Model.lock_value` +command, which will fix any given named parameter to a specific value. This command takes two arguments: the name of the parameter to be fixed, and the value to -fix it to. The `lock_value` command can be used to fix the size term parameters +fix it to. The `lock_value` command can be used to fix the size term parameters to the values in the size term specification file, and then the model will be estimated without re-estimating the size terms. If no re-estimation is desired, users can also safely ignore the `update_size_spec` function. ## Example Notebooks -ActivitySim includes a collection of Jupyter notebooks with -interactive re-estimation examples for many core submodels, which can be found in the -GitHub repository under the [`activitysim/examples/example_estimation/notebooks`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks) -directory. Most of these notebooks demonstrate the process of re-estimating model -parameters, without changing the model specification, i.e. finding updated values -for coefficients without changing the mathematical form of a model's utility -function. +ActivitySim includes a collection of Jupyter notebooks with interactive +re-estimation examples for many core submodels, which can be found in the GitHub +repository under the [`activitysim/examples/example_estimation/notebooks`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks) +directory. Most of these notebooks demonstrate the process of re-estimating +model parameters, without changing the model specification, i.e. finding updated +values for coefficients without changing the mathematical form of a model's +utility function. ### Examples that include Re-Specification -A selection of these notebooks have also been updated to demonstrate -the process of estimating model parameters and also *changing the model specification*. -These notebooks generally include instrucations and a demonstration of how to +A selection of these notebooks have also been updated to demonstrate the process +of estimating model parameters and also *changing the model specification*. +These notebooks generally include instructions and a demonstration of how to modify the model specification, and then re-estimate the model parameters, as -well as how to compare the results of the original and modified models side-by-side, -which can be useful for understanding the impact of the changes made, and conducting -statistical tests to determine if the changes made are statistically significant. +well as how to compare the results of the original and modified models +side-by-side, which can be useful for understanding the impact of the changes +made, and conducting statistical tests to determine if the changes made are +statistically significant. The following notebooks include examples of modifying the model specification: -- [`03_work_location.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/03_work_location.ipynb): - This notebook includes a demonstration of - modification to the SPEC file for a destination choice model, using the - "interact-sample-simulate" type model. -- [`04_auto_ownership.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/04_auto_ownership.ipynb): - This notebook includes a demonstration of modification to the SPEC file for the - auto ownership model. It shows an example of an edit in the utility function - for a "simple simulate" type model. -- [`06_cdap.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/06_cdap.ipynb): - This notebook includes a demonstration of modification to - the SPEC file for the CDAP model. This model has a complex structure that is - unique among the ActivitySim component models. +- [`03_work_location.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/03_work_location.ipynb): + This notebook includes a demonstration of modification to the SPEC file for a + destination choice model, using the "interact-sample-simulate" type model. +- [`04_auto_ownership.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/04_auto_ownership.ipynb): + This notebook includes a demonstration of modification to the SPEC file for the + auto ownership model. It shows an example of an edit in the utility function + for a "simple simulate" type model. +- [`06_cdap.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/06_cdap.ipynb): + This notebook includes a demonstration of modification to the SPEC file for the + CDAP model. This model has a complex structure that is unique among the + ActivitySim component models. From c1fed6719a7bdf26d14478913bad70fde55850e6 Mon Sep 17 00:00:00 2001 From: David Hensle <51132108+dhensle@users.noreply.github.com> Date: Wed, 11 Jun 2025 15:38:07 -0700 Subject: [PATCH 45/56] cdap hh and per parquet read match csv --- activitysim/estimation/larch/cdap.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/activitysim/estimation/larch/cdap.py b/activitysim/estimation/larch/cdap.py index 401cb1ae4b..ba63ec3c3c 100644 --- a/activitysim/estimation/larch/cdap.py +++ b/activitysim/estimation/larch/cdap.py @@ -383,7 +383,11 @@ def read_csv(filename, **kwargs): if "comment" in kwargs: del kwargs["comment"] print(f"Reading {filename.with_suffix('.parquet')}") - return pd.read_parquet(filename.with_suffix(".parquet"), **kwargs) + df = pd.read_parquet(filename.with_suffix(".parquet"), **kwargs) + if df.index.name is not None: + # want the data to be read in the same as csv format -- without the index + df = df.reset_index(drop=False) + return df print(f"Reading {filename}") return pd.read_csv(filename, **kwargs) From 689e3f641e578f0e6c0b3a4c1c6e9398d5eb0a40 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Wed, 25 Jun 2025 20:54:26 -0500 Subject: [PATCH 46/56] add missing x_validator for mode choice and nonmand tour freq --- activitysim/estimation/larch/mode_choice.py | 2 ++ activitysim/estimation/larch/nonmand_tour_freq.py | 3 +++ 2 files changed, 5 insertions(+) diff --git a/activitysim/estimation/larch/mode_choice.py b/activitysim/estimation/larch/mode_choice.py index 4f9e17b7ca..f3d933d3f1 100644 --- a/activitysim/estimation/larch/mode_choice.py +++ b/activitysim/estimation/larch/mode_choice.py @@ -75,6 +75,8 @@ def mode_choice_model( x_col="Label", p_col=alt_name, ignore_x=("#",), + x_validator=chooser_data.columns, + expr_col="Expression", ) for purpose in purposes: # Modify utility function based on template for purpose diff --git a/activitysim/estimation/larch/nonmand_tour_freq.py b/activitysim/estimation/larch/nonmand_tour_freq.py index 5db873b68f..7fab946375 100644 --- a/activitysim/estimation/larch/nonmand_tour_freq.py +++ b/activitysim/estimation/larch/nonmand_tour_freq.py @@ -308,6 +308,9 @@ def nonmand_tour_freq_model( spec, x_col="Label", p_col=segment_name, + x_validator=set(chooser_data[segment_name].columns) + + set(alt_values[segment_name].columns), + expr_col="Expression", ) apply_coefficients(coefficients[segment_name], segment_model) segment_model.choice_co_code = "override_choice" From cf7f7ee26fe0460e1094f85b51602bb26b8383c4 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Wed, 25 Jun 2025 21:29:09 -0500 Subject: [PATCH 47/56] add tour mode choice edit example --- .../notebooks/17_tour_mode_choice.ipynb | 12784 +++++++++++++--- 1 file changed, 10718 insertions(+), 2066 deletions(-) diff --git a/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb b/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb index 766538fa48..58246f47ad 100644 --- a/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb +++ b/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb @@ -31,6 +31,13 @@ "height": 34 }, "colab_type": "code", + "execution": { + "iopub.execute_input": "2025-06-26T02:18:53.757761Z", + "iopub.status.busy": "2025-06-26T02:18:53.757352Z", + "iopub.status.idle": "2025-06-26T02:18:55.343119Z", + "shell.execute_reply": "2025-06-26T02:18:55.342813Z", + "shell.execute_reply.started": "2025-06-26T02:18:53.757721Z" + }, "id": "s53VwlPwtNnr", "outputId": "d1208b7a-c1f2-4b0b-c439-bf312fe12be0" }, @@ -42,15 +49,23 @@ "JAX not found. Some functionality will be unavailable.\n" ] }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n" + ] + }, { "data": { "text/plain": [ - "{'larch': '6.0.32',\n", - " 'sharrow': '2.13.0',\n", - " 'numpy': '1.26.4',\n", - " 'pandas': '1.5.3',\n", - " 'xarray': '2024.3.0',\n", - " 'numba': '0.60.0'}" + "{'larch': '6.0.41',\n", + " 'sharrow': '2.13.1.dev2+g065e1fe',\n", + " 'numpy': '1.24.4',\n", + " 'pandas': '2.3.0',\n", + " 'xarray': '2025.4.0',\n", + " 'numba': '0.60.0',\n", + " 'jax': 'not installed'}" ] }, "execution_count": 1, @@ -78,7 +93,15 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:18:55.343775Z", + "iopub.status.busy": "2025-06-26T02:18:55.343576Z", + "iopub.status.idle": "2025-06-26T02:18:55.594289Z", + "shell.execute_reply": "2025-06-26T02:18:55.593986Z", + "shell.execute_reply.started": "2025-06-26T02:18:55.343766Z" + } + }, "outputs": [ { "name": "stdout", @@ -99,7 +122,7 @@ } ], "source": [ - "from est_mode_setup import prepare\n", + "from est_mode_setup import prepare, backup\n", "\n", "prepare()" ] @@ -108,13 +131,49 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Load data and prep model for estimation" + "In this demo notebook, we will (later) edit some model files. But for demo purposes, we want to\n", + "make sure we are starting from the \"original\" files, so we'll check that now. For actual \n", + "applications, this step would not be necessary." ] }, { "cell_type": "code", "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:18:55.594903Z", + "iopub.status.busy": "2025-06-26T02:18:55.594763Z", + "iopub.status.idle": "2025-06-26T02:18:55.597557Z", + "shell.execute_reply": "2025-06-26T02:18:55.597315Z", + "shell.execute_reply.started": "2025-06-26T02:18:55.594892Z" + } + }, + "outputs": [], + "source": [ + "backup(\"output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_coefficients.csv\")\n", + "backup(\"output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_coefficients_template.csv\")\n", + "backup(\"output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_SPEC.csv\")" + ] + }, + { + "cell_type": "markdown", "metadata": {}, + "source": [ + "# Load data and prep model for estimation" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:18:55.599005Z", + "iopub.status.busy": "2025-06-26T02:18:55.598789Z", + "iopub.status.idle": "2025-06-26T02:19:10.986768Z", + "shell.execute_reply": "2025-06-26T02:19:10.986372Z", + "shell.execute_reply.started": "2025-06-26T02:18:55.598996Z" + } + }, "outputs": [ { "name": "stdout", @@ -149,8 +208,16 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": {}, + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:19:10.987338Z", + "iopub.status.busy": "2025-06-26T02:19:10.987239Z", + "iopub.status.idle": "2025-06-26T02:19:12.247678Z", + "shell.execute_reply": "2025-06-26T02:19:12.247318Z", + "shell.execute_reply.started": "2025-06-26T02:19:10.987328Z" + } + }, "outputs": [ { "name": "stdout", @@ -173,8 +240,16 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, + "execution_count": 6, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:19:12.248184Z", + "iopub.status.busy": "2025-06-26T02:19:12.248080Z", + "iopub.status.idle": "2025-06-26T02:19:14.272297Z", + "shell.execute_reply": "2025-06-26T02:19:14.271908Z", + "shell.execute_reply.started": "2025-06-26T02:19:12.248174Z" + } + }, "outputs": [], "source": [ "model.extend(model2)" @@ -198,8 +273,16 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": {}, + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:19:14.272784Z", + "iopub.status.busy": "2025-06-26T02:19:14.272698Z", + "iopub.status.idle": "2025-06-26T02:19:14.277447Z", + "shell.execute_reply": "2025-06-26T02:19:14.277183Z", + "shell.execute_reply.started": "2025-06-26T02:19:14.272775Z" + } + }, "outputs": [ { "data": { @@ -263,16 +346,6 @@ " ...\n", " \n", " \n", - " walk_transit_CBD_ASC_atwork\n", - " 0.564\n", - " F\n", - " \n", - " \n", - " drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social\n", - " 0.525\n", - " F\n", - " \n", - " \n", " drive_transit_CBD_ASC_school_univ\n", " 0.672\n", " F\n", @@ -287,9 +360,19 @@ " 0.564\n", " F\n", " \n", + " \n", + " coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork\n", + " 0.000\n", + " F\n", + " \n", + " \n", + " coef_test_school_univ\n", + " 0.000\n", + " F\n", + " \n", " \n", "\n", - "

307 rows × 2 columns

\n", + "

309 rows × 2 columns

\n", "" ], "text/plain": [ @@ -301,16 +384,16 @@ "coef_nest_AUTO_DRIVEALONE 0.350 T\n", "coef_nest_AUTO_SHAREDRIDE2 0.350 T\n", "... ... ...\n", - "walk_transit_CBD_ASC_atwork 0.564 F\n", - "drive_transit_CBD_ASC_eatout_escort_othdiscr_ot... 0.525 F\n", "drive_transit_CBD_ASC_school_univ 0.672 F\n", "drive_transit_CBD_ASC_work 1.100 F\n", "drive_transit_CBD_ASC_atwork 0.564 F\n", + "coef_test_eatout_escort_othdiscr_othmaint_shopp... 0.000 F\n", + "coef_test_school_univ 0.000 F\n", "\n", - "[307 rows x 2 columns]" + "[309 rows x 2 columns]" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -328,8 +411,16 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": {}, + "execution_count": 8, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:19:14.277824Z", + "iopub.status.busy": "2025-06-26T02:19:14.277744Z", + "iopub.status.idle": "2025-06-26T02:19:14.284481Z", + "shell.execute_reply": "2025-06-26T02:19:14.284213Z", + "shell.execute_reply.started": "2025-06-26T02:19:14.277816Z" + } + }, "outputs": [ { "data": { @@ -521,30 +612,6 @@ " ...\n", " \n", " \n", - " 310\n", - " util_Drive_to_Transit_dest_CBD\n", - " Drive to Transit dest CBD\n", - " @df.destination_in_cbd\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " ...\n", - " NaN\n", - " NaN\n", - " drive_transit_CBD_ASC\n", - " drive_transit_CBD_ASC\n", - " drive_transit_CBD_ASC\n", - " drive_transit_CBD_ASC\n", - " drive_transit_CBD_ASC\n", - " NaN\n", - " NaN\n", - " NaN\n", - " \n", - " \n", " 311\n", " util_Drive_to_Transit_distance_penalty\n", " Drive to Transit - distance penalty\n", @@ -640,9 +707,33 @@ " NaN\n", " NaN\n", " \n", + " \n", + " 315\n", + " util_test\n", + " Drive alone not available for escort tours\n", + " @1\n", + " coef_test\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " ...\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", " \n", "\n", - "

315 rows × 24 columns

\n", + "

316 rows × 24 columns

\n", "" ], "text/plain": [ @@ -653,11 +744,11 @@ "3 util_DRIVEALONEFREE_Unavailable_for_joint_tours \n", "4 util_DRIVEALONEFREE_Unavailable_if_didnt_drive... \n", ".. ... \n", - "310 util_Drive_to_Transit_dest_CBD \n", "311 util_Drive_to_Transit_distance_penalty \n", "312 util_Walk_not_available_for_long_distances \n", "313 util_Bike_not_available_for_long_distances \n", "314 util_Drive_alone_not_available_for_escort_tours \n", + "315 util_test \n", "\n", " Description \\\n", "0 DRIVEALONEFREE - Unavailable \n", @@ -666,11 +757,11 @@ "3 DRIVEALONEFREE - Unavailable for joint tours \n", "4 DRIVEALONEFREE - Unavailable if didn't drive t... \n", ".. ... \n", - "310 Drive to Transit dest CBD \n", "311 Drive to Transit - distance penalty \n", "312 Walk not available for long distances \n", "313 Bike not available for long distances \n", "314 Drive alone not available for escort tours \n", + "315 Drive alone not available for escort tours \n", "\n", " Expression DRIVEALONEFREE \\\n", "0 sov_available == False -999 \n", @@ -679,11 +770,11 @@ "3 is_joint == True -999 \n", "4 is_atwork_subtour & ~work_tour_is_SOV -999 \n", ".. ... ... \n", - "310 @df.destination_in_cbd NaN \n", "311 @drvtrn_distpen_0_multiplier * (1-od_skims['DI... NaN \n", "312 @od_skims.max('DISTWALK') > 3 NaN \n", "313 @od_skims.max('DISTBIKE') > 8 NaN \n", "314 is_escort -999 \n", + "315 @1 coef_test \n", "\n", " DRIVEALONEPAY SHARED2FREE SHARED2PAY SHARED3FREE SHARED3PAY WALK ... \\\n", "0 NaN NaN NaN NaN NaN NaN ... \n", @@ -692,37 +783,24 @@ "3 NaN NaN NaN NaN NaN NaN ... \n", "4 NaN NaN NaN NaN NaN NaN ... \n", ".. ... ... ... ... ... ... ... \n", - "310 NaN NaN NaN NaN NaN NaN ... \n", "311 NaN NaN NaN NaN NaN NaN ... \n", "312 NaN NaN NaN NaN NaN -999 ... \n", "313 NaN NaN NaN NaN NaN NaN ... \n", "314 -999 NaN NaN NaN NaN NaN ... \n", + "315 NaN NaN NaN NaN NaN NaN ... \n", "\n", - " WALK_HVY WALK_COM DRIVE_LOC DRIVE_LRF \\\n", - "0 NaN NaN NaN NaN \n", - "1 NaN NaN NaN NaN \n", - "2 NaN NaN NaN NaN \n", - "3 NaN NaN NaN NaN \n", - "4 NaN NaN NaN NaN \n", - ".. ... ... ... ... \n", - "310 NaN NaN drive_transit_CBD_ASC drive_transit_CBD_ASC \n", - "311 NaN NaN coef_ivt coef_ivt \n", - "312 NaN NaN NaN NaN \n", - "313 NaN NaN NaN NaN \n", - "314 NaN NaN NaN NaN \n", - "\n", - " DRIVE_EXP DRIVE_HVY DRIVE_COM TAXI \\\n", - "0 NaN NaN NaN NaN \n", - "1 NaN NaN NaN NaN \n", - "2 NaN NaN NaN NaN \n", - "3 NaN NaN NaN NaN \n", - "4 NaN NaN NaN NaN \n", - ".. ... ... ... ... \n", - "310 drive_transit_CBD_ASC drive_transit_CBD_ASC drive_transit_CBD_ASC NaN \n", - "311 coef_ivt coef_ivt coef_ivt NaN \n", - "312 NaN NaN NaN NaN \n", - "313 NaN NaN NaN NaN \n", - "314 NaN NaN NaN NaN \n", + " WALK_HVY WALK_COM DRIVE_LOC DRIVE_LRF DRIVE_EXP DRIVE_HVY DRIVE_COM TAXI \\\n", + "0 NaN NaN NaN NaN NaN NaN NaN NaN \n", + "1 NaN NaN NaN NaN NaN NaN NaN NaN \n", + "2 NaN NaN NaN NaN NaN NaN NaN NaN \n", + "3 NaN NaN NaN NaN NaN NaN NaN NaN \n", + "4 NaN NaN NaN NaN NaN NaN NaN NaN \n", + ".. ... ... ... ... ... ... ... ... \n", + "311 NaN NaN coef_ivt coef_ivt coef_ivt coef_ivt coef_ivt NaN \n", + "312 NaN NaN NaN NaN NaN NaN NaN NaN \n", + "313 NaN NaN NaN NaN NaN NaN NaN NaN \n", + "314 NaN NaN NaN NaN NaN NaN NaN NaN \n", + "315 NaN NaN NaN NaN NaN NaN NaN NaN \n", "\n", " TNC_SINGLE TNC_SHARED \n", "0 NaN NaN \n", @@ -731,16 +809,16 @@ "3 NaN NaN \n", "4 NaN NaN \n", ".. ... ... \n", - "310 NaN NaN \n", "311 NaN NaN \n", "312 NaN NaN \n", "313 NaN NaN \n", "314 NaN NaN \n", + "315 NaN NaN \n", "\n", - "[315 rows x 24 columns]" + "[316 rows x 24 columns]" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -758,8 +836,16 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": {}, + "execution_count": 9, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:19:14.284943Z", + "iopub.status.busy": "2025-06-26T02:19:14.284856Z", + "iopub.status.idle": "2025-06-26T02:19:14.298921Z", + "shell.execute_reply": "2025-06-26T02:19:14.298594Z", + "shell.execute_reply.started": "2025-06-26T02:19:14.284935Z" + } + }, "outputs": [ { "data": { @@ -1271,7 +1357,7 @@ "[63935 rows x 536 columns]" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -1291,13 +1377,21 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": {}, + "execution_count": 10, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:19:14.299439Z", + "iopub.status.busy": "2025-06-26T02:19:14.299343Z", + "iopub.status.idle": "2025-06-26T02:19:14.389799Z", + "shell.execute_reply": "2025-06-26T02:19:14.389326Z", + "shell.execute_reply.started": "2025-06-26T02:19:14.299429Z" + } + }, "outputs": [ { "data": { "text/plain": [ - "(,\n", + "(,\n", " [(, dictx()),\n", " (, dictx()),\n", " (, dictx()),\n", @@ -1310,7 +1404,7 @@ " (, dictx())])" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -1321,13 +1415,21 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": {}, + "execution_count": 11, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:19:14.390341Z", + "iopub.status.busy": "2025-06-26T02:19:14.390244Z", + "iopub.status.idle": "2025-06-26T02:20:19.068878Z", + "shell.execute_reply": "2025-06-26T02:20:19.068547Z", + "shell.execute_reply.started": "2025-06-26T02:19:14.390332Z" + } + }, "outputs": [ { "data": { "text/html": [ - "

Iteration 186 [Optimization terminated successfully]

" + "

Iteration 189 [Optimization terminated successfully]

" ], "text/plain": [ "" @@ -1339,7 +1441,7 @@ { "data": { "text/html": [ - "

Best LL = -76504.13129817661

" + "

Best LL = -76508.28923895479

" ], "text/plain": [ "" @@ -1411,8 +1513,8 @@ " \n", " \n", " bike_ASC_auto_deficient_atwork\n", - " -0.997746\n", - " -0.997746\n", + " -1.054274\n", + " -1.054274\n", " -0.807408\n", " -inf\n", " inf\n", @@ -1421,8 +1523,8 @@ " \n", " \n", " bike_ASC_auto_deficient_eatout\n", - " -1.673695\n", - " -1.673695\n", + " -1.458927\n", + " -1.458927\n", " -1.569111\n", " -inf\n", " inf\n", @@ -1431,8 +1533,8 @@ " \n", " \n", " bike_ASC_auto_deficient_escort\n", - " -4.147119\n", - " -4.147119\n", + " -3.980018\n", + " -3.980018\n", " -4.527928\n", " -inf\n", " inf\n", @@ -1451,8 +1553,8 @@ " \n", " \n", " walk_transit_ASC_no_auto_work\n", - " 4.665799\n", - " 4.665799\n", + " 4.604150\n", + " 4.604150\n", " 5.035417\n", " -inf\n", " inf\n", @@ -1461,8 +1563,8 @@ " \n", " \n", " walk_transit_CBD_ASC_atwork\n", - " 1.146544\n", - " 1.146544\n", + " 1.296785\n", + " 1.296785\n", " 0.564000\n", " -inf\n", " inf\n", @@ -1471,8 +1573,8 @@ " \n", " \n", " walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social\n", - " 1.074027\n", - " 1.074027\n", + " 1.078110\n", + " 1.078110\n", " 0.525000\n", " -inf\n", " inf\n", @@ -1481,8 +1583,8 @@ " \n", " \n", " walk_transit_CBD_ASC_school_univ\n", - " 0.818861\n", - " 0.818861\n", + " 0.834010\n", + " 0.834010\n", " 0.672000\n", " -inf\n", " inf\n", @@ -1491,8 +1593,8 @@ " \n", " \n", " walk_transit_CBD_ASC_work\n", - " 1.158108\n", - " 1.158108\n", + " 1.157993\n", + " 1.157993\n", " 0.804000\n", " -inf\n", " inf\n", @@ -1501,7 +1603,7 @@ " \n", " \n", "\n", - "

301 rows × 7 columns

\n", + "

303 rows × 7 columns

\n", "" ], "text/plain": [ @@ -1509,15 +1611,15 @@ "param_name \n", "-999 -999.000000 -999.000000 \n", "1 1.000000 1.000000 \n", - "bike_ASC_auto_deficient_atwork -0.997746 -0.997746 \n", - "bike_ASC_auto_deficient_eatout -1.673695 -1.673695 \n", - "bike_ASC_auto_deficient_escort -4.147119 -4.147119 \n", + "bike_ASC_auto_deficient_atwork -1.054274 -1.054274 \n", + "bike_ASC_auto_deficient_eatout -1.458927 -1.458927 \n", + "bike_ASC_auto_deficient_escort -3.980018 -3.980018 \n", "... ... ... \n", - "walk_transit_ASC_no_auto_work 4.665799 4.665799 \n", - "walk_transit_CBD_ASC_atwork 1.146544 1.146544 \n", - "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth... 1.074027 1.074027 \n", - "walk_transit_CBD_ASC_school_univ 0.818861 0.818861 \n", - "walk_transit_CBD_ASC_work 1.158108 1.158108 \n", + "walk_transit_ASC_no_auto_work 4.604150 4.604150 \n", + "walk_transit_CBD_ASC_atwork 1.296785 1.296785 \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth... 1.078110 1.078110 \n", + "walk_transit_CBD_ASC_school_univ 0.834010 0.834010 \n", + "walk_transit_CBD_ASC_work 1.157993 1.157993 \n", "\n", " initvalue minimum \\\n", "param_name \n", @@ -1561,7 +1663,7 @@ "walk_transit_CBD_ASC_school_univ 0 \n", "walk_transit_CBD_ASC_work 0 \n", "\n", - "[301 rows x 7 columns]" + "[303 rows x 7 columns]" ] }, "metadata": {}, @@ -1571,7 +1673,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jpn/Git/est-mode/larch/src/larch/model/optimization.py:338: UserWarning: SLSQP may not play nicely with unbounded parameters\n", + "/Users/jpn/Git/aestival/repos/larch/src/larch/model/optimization.py:338: UserWarning: SLSQP may not play nicely with unbounded parameters\n", "if you get poor results, consider setting global bounds with model.set_cap()\n", " warnings.warn( # infinite bounds # )\n" ] @@ -1583,125 +1685,133 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, + "execution_count": 12, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:20:19.069508Z", + "iopub.status.busy": "2025-06-26T02:20:19.069365Z", + "iopub.status.idle": "2025-06-26T02:22:22.469509Z", + "shell.execute_reply": "2025-06-26T02:22:22.469199Z", + "shell.execute_reply.started": "2025-06-26T02:20:19.069498Z" + } + }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - 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 ValueStd Errt StatSignifNull ValueValueStd Errt StatSignifNull Value
Parameter
-999-999. 0.00 NA 0.00-999-999. 0.00 NA 0.00
1 1.00 0.00 NA 0.001 1.00 0.00 NA 0.00
bike_ASC_auto_deficient_atwork-0.998 0.336-2.97** 0.00bike_ASC_auto_deficient_atwork-1.05 0.344-3.07** 0.00
bike_ASC_auto_deficient_eatout-1.67 0.404-4.14*** 0.00bike_ASC_auto_deficient_eatout-1.46 0.396-3.69*** 0.00
bike_ASC_auto_deficient_escort-4.15 0.398-10.41*** 0.00bike_ASC_auto_deficient_escort-3.98 0.406-9.79*** 0.00
bike_ASC_auto_deficient_othdiscr-1.11 0.204-5.42*** 0.00bike_ASC_auto_deficient_othdiscr-0.910 0.203-4.47*** 0.00
bike_ASC_auto_deficient_othmaint-2.34 0.344-6.81*** 0.00bike_ASC_auto_deficient_othmaint-2.06 0.323-6.37*** 0.00
bike_ASC_auto_deficient_school-1.44 0.305-4.71*** 0.00bike_ASC_auto_deficient_school-1.20 0.964-1.24 0.00
bike_ASC_auto_deficient_shopping-1.92 0.220-8.74*** 0.00bike_ASC_auto_deficient_shopping-1.74 0.218-7.99*** 0.00
bike_ASC_auto_deficient_social 0.185 0.319 0.58 0.00bike_ASC_auto_deficient_social 0.361 0.325 1.11 0.00
bike_ASC_auto_deficient_univ-0.669 0.0356-18.78*** 0.00bike_ASC_auto_deficient_univ-0.669 NA NA 0.00
bike_ASC_auto_deficient_work-0.335 0.0775-4.33*** 0.00bike_ASC_auto_deficient_work-0.279 0.0926-3.01** 0.00
bike_ASC_auto_sufficient_atwork 15.7 437. 0.04 0.00bike_ASC_auto_sufficient_atwork 15.7 470. 0.03 0.00
bike_ASC_auto_sufficient_eatout-1.88 0.147-12.80*** 0.00bike_ASC_auto_sufficient_eatout-1.85 0.159-11.60*** 0.00
bike_ASC_auto_sufficient_escort-6.00 0.388-15.46*** 0.00bike_ASC_auto_sufficient_escort-5.65 0.337-16.76*** 0.00
bike_ASC_auto_sufficient_othdiscr-1.97 0.0937-21.00*** 0.00bike_ASC_auto_sufficient_othdiscr-1.86 0.105-17.64*** 0.00
bike_ASC_auto_sufficient_othmaint-3.17 0.179-17.71*** 0.00bike_ASC_auto_sufficient_othmaint-3.17 0.193-16.40*** 0.00
bike_ASC_auto_sufficient_school-2.70 0.104-25.91*** 0.00bike_ASC_auto_sufficient_school-2.21 0.919-2.40* 0.00
bike_ASC_auto_sufficient_shopping-3.22 0.129-24.92*** 0.00bike_ASC_auto_sufficient_shopping-3.14 0.138-22.70*** 0.00
bike_ASC_auto_sufficient_social-2.25 0.201-11.15*** 0.00bike_ASC_auto_sufficient_social-2.14 0.207-10.36*** 0.00
bike_ASC_auto_sufficient_univ-1.94 0.0158-122.87*** 0.00bike_ASC_auto_sufficient_univ-1.94 0.00657-295.46*** 0.00
bike_ASC_auto_sufficient_work-2.04 0.0656-31.15*** 0.00bike_ASC_auto_sufficient_work-1.93 0.0814-23.72*** 0.00
bike_ASC_no_auto_atwork-0.909 78.2-0.01 0.00bike_ASC_no_auto_atwork-0.910 76.5-0.01 0.00
bike_ASC_no_auto_eatout 0.420 77.7 0.01 0.00bike_ASC_no_auto_eatout 0.428 75.9 0.01 0.00
bike_ASC_no_auto_escort-0.754 77.7-0.01 0.00bike_ASC_no_auto_escort-0.745 75.9-0.01 0.00
bike_ASC_no_auto_othdiscr-0.514 77.7-0.01 0.00bike_ASC_no_auto_othdiscr-0.501 75.9-0.01 0.00
bike_ASC_no_auto_othmaint 1.48 77.7 0.02 0.00bike_ASC_no_auto_othmaint 1.53 75.9 0.02 0.00
bike_ASC_no_auto_school 13.3 106. 0.13 0.00bike_ASC_no_auto_school 13.5 109. 0.12 0.00
bike_ASC_no_auto_shopping 0.955 77.7 0.01 0.00bike_ASC_no_auto_shopping 0.951 75.9 0.01 0.00
bike_ASC_no_auto_social 0.352 77.7 0.00 0.00bike_ASC_no_auto_social 0.374 75.9 0.00 0.00
bike_ASC_no_auto_univ 4.29 0.0225 190.79*** 0.00bike_ASC_no_auto_univ 4.29 0.00148 BIG*** 0.00
bike_ASC_no_auto_work 3.46 77.7 0.04 0.00bike_ASC_no_auto_work 3.43 75.9 0.05 0.00
coef_age010_trn_multiplier_atwork 0.000722 NA NA 0.00coef_age010_trn_multiplier_atwork 0.000722 0.00785 0.09 0.00
coef_age010_trn_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work 0.277 0.177 1.56 0.00coef_age010_trn_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work 0.490 0.176 2.79** 0.00
coef_age010_trn_multiplier_school_univ-0.884 0.0900-9.82*** 0.00coef_age010_trn_multiplier_school_univ-0.851 0.0900-9.46*** 0.00
coef_age1619_da_multiplier_atwork-0.184 0.205-0.90 0.00coef_age1619_da_multiplier_atwork-0.175 0.205-0.85 0.00
coef_age1619_da_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work 0.0300 0.0425 0.71 0.00coef_age1619_da_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work 0.0357 0.0425 0.84 0.00
coef_age1619_da_multiplier_school_univ-1.63 0.0746-21.80*** 0.00coef_age1619_da_multiplier_school_univ-1.67 0.0748-22.31*** 0.00
coef_age16p_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social-1.42 0.0807-17.61*** 0.00coef_age16p_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social-1.58 0.0842-18.71*** 0.00
coef_age16p_sr_multiplier_school_univ_work_atwork-0.663 0.0682-9.72*** 0.00coef_age16p_sr_multiplier_school_univ_work_atwork-0.688 0.0682-10.08*** 0.00
coef_hhsize1_sr_multiplier_eatout_escort_othdiscr_othmaint_school_shopping_social_univ_atwork-0.0800 0.0313-2.56* 0.00coef_hhsize1_sr_multiplier_eatout_escort_othdiscr_othmaint_school_shopping_social_univ_atwork-0.0721 0.0312-2.31* 0.00
coef_hhsize1_sr_multiplier_work-0.839 0.0576-14.56*** 0.00coef_hhsize1_sr_multiplier_work-0.822 0.0571-14.39*** 0.00
coef_hhsize2_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork-0.00550 0.0178-0.31 0.00coef_hhsize2_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork-0.00404 0.0178-0.23 0.00
coef_hhsize2_sr_multiplier_school_univ-0.733 0.0909-8.06*** 0.00coef_hhsize2_sr_multiplier_school_univ-0.743 0.0912-8.15*** 0.00
coef_ivt_atwork-0.0112 0.000480-23.42*** 0.00coef_ivt_atwork-0.0112 0.000479-23.41*** 0.00
coef_ivt_eatout_escort_othdiscr_othmaint_shopping_social-0.00688 0.000144-47.63*** 0.00coef_ivt_eatout_escort_othdiscr_othmaint_shopping_social-0.00691 0.000145-47.76*** 0.00
coef_ivt_school_univ-0.0106 0.000322-33.03*** 0.00coef_ivt_school_univ-0.0103 0.000316-32.62*** 0.00
coef_ivt_work-0.00787 0.000147-53.42*** 0.00coef_ivt_work-0.00791 0.000147-53.62*** 0.00
coef_nest_AUTO 0.720 0.00 NA 1.00coef_nest_AUTO 0.720 0.00 NA 1.00
coef_nest_AUTO_DRIVEALONE 0.350 0.00 NA 1.00coef_nest_AUTO_DRIVEALONE 0.350 0.00 NA 1.00
coef_nest_AUTO_SHAREDRIDE2 0.350 0.00 NA 1.00coef_nest_AUTO_SHAREDRIDE2 0.350 0.00 NA 1.00
coef_nest_AUTO_SHAREDRIDE3 0.350 0.00 NA 1.00coef_nest_AUTO_SHAREDRIDE3 0.350 0.00 NA 1.00
coef_nest_NONMOTORIZED 0.720 0.00 NA 1.00coef_nest_NONMOTORIZED 0.720 0.00 NA 1.00
coef_nest_RIDEHAIL 0.360 0.00 NA 1.00coef_nest_RIDEHAIL 0.360 0.00 NA 1.00
coef_nest_TRANSIT 0.720 0.00 NA 1.00coef_nest_TRANSIT 0.720 0.00 NA 1.00
coef_nest_TRANSIT_DRIVEACCESS 0.500 0.00 NA 1.00coef_nest_TRANSIT_DRIVEACCESS 0.500 0.00 NA 1.00
coef_nest_TRANSIT_WALKACCESS 0.500 0.00 NA 1.00coef_nest_TRANSIT_WALKACCESS 0.500 0.00 NA 1.00
commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-1.08 266.-0.00 0.00coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork 0.0770 0.0494 1.56 0.00
commuter_rail_ASC_school_univ-0.338 527.-0.00 0.00coef_test_school_univ 0.518 0.913 0.57 0.00
commuter_rail_ASC_work 0.168 NA NA 0.00commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.958 16.4-0.06 0.00
drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.764 266.-0.00 0.00commuter_rail_ASC_school_univ-0.258 NA NA 0.00
drive_ferry_ASC_school_univ 1.41 527. 0.00 0.00commuter_rail_ASC_work 0.196 278. 0.00 0.00
drive_ferry_ASC_work 0.187 NA NA 0.00drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.628 16.4-0.04 0.00
drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.402 266.-0.00 0.00drive_ferry_ASC_school_univ 1.43 NA NA 0.00
drive_light_rail_ASC_school_univ 0.615 527. 0.00 0.00drive_ferry_ASC_work 0.232 278. 0.00 0.00
drive_light_rail_ASC_work 0.520 NA NA 0.00drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.325 16.4-0.02 0.00
drive_transit_ASC_auto_deficient_atwork-999. NA NA 0.00drive_light_rail_ASC_school_univ 0.691 NA NA 0.00
drive_transit_ASC_auto_deficient_eatout-0.277 266.-0.00 0.00drive_light_rail_ASC_work 0.530 278. 0.00 0.00
drive_transit_ASC_auto_deficient_escort-2.24 266.-0.01 0.00drive_transit_ASC_auto_deficient_atwork-999. 0.000360-BIG*** 0.00
drive_transit_ASC_auto_deficient_othdiscr-0.968 266.-0.00 0.00drive_transit_ASC_auto_deficient_eatout-0.173 16.4-0.01 0.00
drive_transit_ASC_auto_deficient_othmaint-1.43 266.-0.01 0.00drive_transit_ASC_auto_deficient_escort-2.19 16.4-0.13 0.00
drive_transit_ASC_auto_deficient_school 1.63 527. 0.00 0.00drive_transit_ASC_auto_deficient_othdiscr-0.852 16.4-0.05 0.00
drive_transit_ASC_auto_deficient_shopping-1.68 266.-0.01 0.00drive_transit_ASC_auto_deficient_othmaint-1.36 16.4-0.08 0.00
drive_transit_ASC_auto_deficient_social 0.629 266. 0.00 0.00drive_transit_ASC_auto_deficient_school 1.59 NA NA 0.00
drive_transit_ASC_auto_deficient_univ 1.85 0.00197 939.88*** 0.00drive_transit_ASC_auto_deficient_shopping-1.58 16.4-0.10 0.00
drive_transit_ASC_auto_deficient_work-0.896 NA NA 0.00drive_transit_ASC_auto_deficient_social 0.610 16.4 0.04 0.00
drive_transit_ASC_auto_sufficient_atwork-999. NA NA 0.00drive_transit_ASC_auto_deficient_univ 1.85 NA NA 0.00
drive_transit_ASC_auto_sufficient_eatout-1.75 266.-0.01 0.00drive_transit_ASC_auto_deficient_work-0.824 278.-0.00 0.00
drive_transit_ASC_auto_sufficient_escort-5.32 266.-0.02 0.00drive_transit_ASC_auto_sufficient_atwork-999. 0.000176-BIG*** 0.00
drive_transit_ASC_auto_sufficient_othdiscr-1.27 266.-0.00 0.00drive_transit_ASC_auto_sufficient_eatout-1.65 16.4-0.10 0.00
drive_transit_ASC_auto_sufficient_othmaint-2.85 266.-0.01 0.00drive_transit_ASC_auto_sufficient_escort-5.31 16.4-0.32 0.00
drive_transit_ASC_auto_sufficient_school-0.182 527.-0.00 0.00drive_transit_ASC_auto_sufficient_othdiscr-1.24 16.4-0.08 0.00
drive_transit_ASC_auto_sufficient_shopping-4.23 266.-0.02 0.00drive_transit_ASC_auto_sufficient_othmaint-2.80 16.4-0.17 0.00
drive_transit_ASC_auto_sufficient_social-1.47 266.-0.01 0.00drive_transit_ASC_auto_sufficient_school 0.105 NA NA 0.00
drive_transit_ASC_auto_sufficient_univ 1.36 0.000573 BIG*** 0.00drive_transit_ASC_auto_sufficient_shopping-4.16 16.4-0.25 0.00
drive_transit_ASC_auto_sufficient_work-1.81 NA NA 0.00drive_transit_ASC_auto_sufficient_social-1.37 16.4-0.08 0.00
drive_transit_ASC_no_auto_all 0.00 0.000507 0.00 0.00drive_transit_ASC_auto_sufficient_univ 1.36 NA NA 0.00
drive_transit_CBD_ASC_atwork 0.564 0.000881 639.86*** 0.00drive_transit_ASC_auto_sufficient_work-1.73 278.-0.01 0.00
drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social 1.41 0.142 9.88*** 0.00drive_transit_ASC_no_auto_all 0.00 NA NA 0.00
drive_transit_CBD_ASC_school_univ 1.18 0.250 4.72*** 0.00drive_transit_CBD_ASC_atwork 0.564 NA NA 0.00
drive_transit_CBD_ASC_work 1.65 0.0699 23.57*** 0.00drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social 1.37 0.142 9.63*** 0.00
express_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.396 266.-0.00 0.00drive_transit_CBD_ASC_school_univ 1.23 0.251 4.89*** 0.00
express_bus_ASC_school_univ-0.568 527.-0.00 0.00drive_transit_CBD_ASC_work 1.64 0.0698 23.45*** 0.00
express_bus_ASC_work-0.917 NA NA 0.00express_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.342 16.4-0.02 0.00
heavy_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.251 266.-0.00 0.00express_bus_ASC_school_univ-0.451 NA NA 0.00
heavy_rail_ASC_school_univ-0.00300 527.-0.00 0.00express_bus_ASC_work-0.881 278.-0.00 0.00
heavy_rail_ASC_work 0.495 NA NA 0.00heavy_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.207 16.4-0.01 0.00
joint_bike_ASC_auto_deficient_all-6.18 1.39-4.45*** 0.00heavy_rail_ASC_school_univ 0.110 NA NA 0.00
joint_bike_ASC_auto_sufficient_all-7.13 0.506-14.09*** 0.00heavy_rail_ASC_work 0.513 278. 0.00 0.00
joint_bike_ASC_no_auto_all-2.70 1.11-2.43* 0.00joint_bike_ASC_auto_deficient_all-6.18 1.34-4.62*** 0.00
joint_drive_transit_ASC_auto_deficient_all-6.03 266.-0.02 0.00joint_bike_ASC_auto_sufficient_all-7.10 0.465-15.28*** 0.00
joint_drive_transit_ASC_auto_sufficient_all-7.80 266.-0.03 0.00joint_bike_ASC_no_auto_all-2.67 1.08-2.48* 0.00
joint_drive_transit_ASC_no_auto_all 0.00 0.00 NA 0.00joint_drive_transit_ASC_auto_deficient_all-6.04 16.4-0.37 0.00
joint_sr2_ASC_auto_deficient_all 0.00 0.00 NA 0.00joint_drive_transit_ASC_auto_sufficient_all-7.79 16.4-0.48 0.00
joint_sr2_ASC_auto_sufficient_all 0.00 0.00 NA 0.00joint_drive_transit_ASC_no_auto_all 0.00 0.00 NA 0.00
joint_sr2_ASC_no_auto_all 0.00 0.00 NA 0.00joint_sr2_ASC_auto_deficient_all 0.00 0.00 NA 0.00
joint_sr3p_ASC_auto_deficient_all-1.55 0.265-5.85*** 0.00joint_sr2_ASC_auto_sufficient_all 0.00 0.00 NA 0.00
joint_sr3p_ASC_auto_sufficient_all-2.28 0.133-17.16*** 0.00joint_sr2_ASC_no_auto_all 0.00 0.00 NA 0.00
joint_sr3p_ASC_no_auto_all 0.656 0.458 1.43 0.00joint_sr3p_ASC_auto_deficient_all-1.49 0.258-5.77*** 0.00
joint_taxi_ASC_auto_deficient_all-9.82 8.47-1.16 0.00joint_sr3p_ASC_auto_sufficient_all-2.29 0.133-17.17*** 0.00
joint_taxi_ASC_auto_sufficient_all-11.7 0.00 NA 0.00joint_sr3p_ASC_no_auto_all 0.699 0.470 1.49 0.00
joint_taxi_ASC_no_auto_all-4.58 4.30-1.07 0.00joint_taxi_ASC_auto_deficient_all-9.82 8.15-1.21 0.00
joint_tnc_shared_ASC_auto_deficient_all-11.2 17.8-0.63 0.00joint_taxi_ASC_auto_sufficient_all-11.7 0.00 NA 0.00
joint_tnc_shared_ASC_auto_sufficient_all-13.2 0.00 NA 0.00joint_taxi_ASC_no_auto_all-4.58 4.29-1.07 0.00
joint_tnc_shared_ASC_no_auto_all-4.69 2.26-2.07* 0.00joint_tnc_shared_ASC_auto_deficient_all-11.2 17.0-0.66 0.00
joint_tnc_single_ASC_auto_deficient_all-9.90 7.49-1.32 0.00joint_tnc_shared_ASC_auto_sufficient_all-13.2 0.00 NA 0.00
joint_tnc_single_ASC_auto_sufficient_all-14.0 0.00 NA 0.00joint_tnc_shared_ASC_no_auto_all-4.72 2.18-2.17* 0.00
joint_tnc_single_ASC_no_auto_all-3.91 2.15-1.82 0.00joint_tnc_single_ASC_auto_deficient_all-9.90 7.20-1.38 0.00
joint_walk_ASC_auto_deficient_all-2.24 0.387-5.78*** 0.00joint_tnc_single_ASC_auto_sufficient_all-14.0 0.00 NA 0.00
joint_walk_ASC_auto_sufficient_all-4.23 0.246-17.23*** 0.00joint_tnc_single_ASC_no_auto_all-3.86 2.05-1.88 0.00
joint_walk_ASC_no_auto_all-0.402 0.729-0.55 0.00joint_walk_ASC_auto_deficient_all-2.22 0.376-5.89*** 0.00
joint_walk_transit_ASC_auto_deficient_all-5.28 266.-0.02 0.00joint_walk_ASC_auto_sufficient_all-4.34 0.245-17.76*** 0.00
joint_walk_transit_ASC_auto_sufficient_all-18.3 777.-0.02 0.00joint_walk_ASC_no_auto_all-0.367 0.727-0.51 0.00
joint_walk_transit_ASC_no_auto_all 0.489 266. 0.00 0.00joint_walk_transit_ASC_auto_deficient_all-5.30 16.4-0.32 0.00
local_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-1.24 266.-0.00 0.00joint_walk_transit_ASC_auto_sufficient_all-18.3 655.-0.03 0.00
local_bus_ASC_school_univ-0.934 527.-0.00 0.00joint_walk_transit_ASC_no_auto_all 0.386 16.4 0.02 0.00
local_bus_ASC_work-0.196 NA NA 0.00local_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-1.18 16.4-0.07 0.00
sr2_ASC_auto_deficient_atwork-1.58 0.134-11.80*** 0.00local_bus_ASC_school_univ-0.819 NA NA 0.00
sr2_ASC_auto_deficient_eatout 0.592 0.145 4.07*** 0.00local_bus_ASC_work-0.179 278.-0.00 0.00
sr2_ASC_auto_deficient_escort-0.0768 0.151-0.51 0.00sr2_ASC_auto_deficient_atwork-1.49 0.132-11.34*** 0.00
sr2_ASC_auto_deficient_othdiscr 0.821 0.119 6.92*** 0.00sr2_ASC_auto_deficient_eatout 0.874 0.155 5.64*** 0.00
sr2_ASC_auto_deficient_othmaint 0.318 0.135 2.35* 0.00sr2_ASC_auto_deficient_escort 0.254 0.160 1.58 0.00
sr2_ASC_auto_deficient_school 0.162 0.175 0.93 0.00sr2_ASC_auto_deficient_othdiscr 1.06 0.131 8.13*** 0.00
sr2_ASC_auto_deficient_shopping 0.283 0.115 2.46* 0.00sr2_ASC_auto_deficient_othmaint 0.584 0.145 4.02*** 0.00
sr2_ASC_auto_deficient_social 1.99 0.203 9.83*** 0.00sr2_ASC_auto_deficient_school 0.518 0.928 0.56 0.00
sr2_ASC_auto_deficient_univ-1.69 NA NA 0.00sr2_ASC_auto_deficient_shopping 0.522 0.127 4.09*** 0.00
sr2_ASC_auto_deficient_work 0.325 0.0744 4.36*** 0.00sr2_ASC_auto_deficient_social 2.30 0.215 10.70*** 0.00
sr2_ASC_auto_sufficient_atwork-0.800 0.0784-10.21*** 0.00sr2_ASC_auto_deficient_univ-1.69 NA NA 0.00
sr2_ASC_auto_sufficient_eatout 0.925 0.0894 10.35*** 0.00sr2_ASC_auto_deficient_work 0.424 0.0892 4.76*** 0.00
sr2_ASC_auto_sufficient_escort 0.188 0.117 1.61 0.00sr2_ASC_auto_sufficient_atwork-0.772 0.0784-9.85*** 0.00
sr2_ASC_auto_sufficient_othdiscr 0.596 0.0846 7.05*** 0.00sr2_ASC_auto_sufficient_eatout 1.17 0.105 11.19*** 0.00
sr2_ASC_auto_sufficient_othmaint 0.416 0.0870 4.79*** 0.00sr2_ASC_auto_sufficient_escort 0.427 0.129 3.31*** 0.00
sr2_ASC_auto_sufficient_school-1.23 0.0803-15.34*** 0.00sr2_ASC_auto_sufficient_othdiscr 0.830 0.101 8.23*** 0.00
sr2_ASC_auto_sufficient_shopping 0.292 0.0841 3.48*** 0.00sr2_ASC_auto_sufficient_othmaint 0.642 0.103 6.24*** 0.00
sr2_ASC_auto_sufficient_social 0.641 0.0953 6.72*** 0.00sr2_ASC_auto_sufficient_school-0.720 0.916-0.79 0.00
sr2_ASC_auto_sufficient_univ-1.86 NA NA 0.00sr2_ASC_auto_sufficient_shopping 0.518 0.100 5.16*** 0.00
sr2_ASC_auto_sufficient_work-0.396 0.0705-5.62*** 0.00sr2_ASC_auto_sufficient_social 0.867 0.110 7.88*** 0.00
sr2_ASC_no_auto_all 1.10 77.7 0.01 0.00sr2_ASC_auto_sufficient_univ-1.86 NA NA 0.00
sr3p_ASC_auto_deficient_atwork-1.90 0.138-13.76*** 0.00sr2_ASC_auto_sufficient_work-0.295 0.0860-3.43*** 0.00
sr3p_ASC_auto_deficient_eatout-0.120 0.182-0.66 0.00sr2_ASC_no_auto_all 1.22 75.9 0.02 0.00
sr3p_ASC_auto_deficient_escort-0.301 0.154-1.96 0.00sr3p_ASC_auto_deficient_atwork-1.81 0.136-13.30*** 0.00
sr3p_ASC_auto_deficient_othdiscr 1.18 0.112 10.56*** 0.00sr3p_ASC_auto_deficient_eatout 0.184 0.187 0.98 0.00
sr3p_ASC_auto_deficient_othmaint-0.936 0.225-4.16*** 0.00sr3p_ASC_auto_deficient_escort 0.0300 0.163 0.18 0.00
sr3p_ASC_auto_deficient_school 0.708 0.170 4.16*** 0.00sr3p_ASC_auto_deficient_othdiscr 1.42 0.124 11.40*** 0.00
sr3p_ASC_auto_deficient_shopping-0.0640 0.126-0.51 0.00sr3p_ASC_auto_deficient_othmaint-0.607 0.223-2.71** 0.00
sr3p_ASC_auto_deficient_social 1.72 0.212 8.14*** 0.00sr3p_ASC_auto_deficient_school 1.10 0.927 1.18 0.00
sr3p_ASC_auto_deficient_univ-1.73 0.000100-BIG*** 0.00sr3p_ASC_auto_deficient_shopping 0.180 0.138 1.31 0.00
sr3p_ASC_auto_deficient_work-0.219 0.0779-2.81** 0.00sr3p_ASC_auto_deficient_social 2.04 0.223 9.16*** 0.00
sr3p_ASC_auto_sufficient_atwork-0.984 0.0796-12.35*** 0.00sr3p_ASC_auto_deficient_univ-1.73 1.83e-05-BIG*** 0.00
sr3p_ASC_auto_sufficient_eatout 0.898 0.0894 10.04*** 0.00sr3p_ASC_auto_deficient_work-0.127 0.0922-1.38 0.00
sr3p_ASC_auto_sufficient_escort 0.162 0.117 1.38 0.00sr3p_ASC_auto_sufficient_atwork-0.954 0.0797-11.97*** 0.00
sr3p_ASC_auto_sufficient_othdiscr 0.697 0.0841 8.29*** 0.00sr3p_ASC_auto_sufficient_eatout 1.13 0.105 10.73*** 0.00
sr3p_ASC_auto_sufficient_othmaint 0.0330 0.0899 0.37 0.00sr3p_ASC_auto_sufficient_escort 0.400 0.129 3.10** 0.00
sr3p_ASC_auto_sufficient_school-0.663 0.0792-8.37*** 0.00sr3p_ASC_auto_sufficient_othdiscr 0.929 0.101 9.25*** 0.00
sr3p_ASC_auto_sufficient_shopping 0.0515 0.0851 0.61 0.00sr3p_ASC_auto_sufficient_othmaint 0.257 0.105 2.44* 0.00
sr3p_ASC_auto_sufficient_social 0.642 0.0951 6.75*** 0.00sr3p_ASC_auto_sufficient_school-0.151 0.916-0.16 0.00
sr3p_ASC_auto_sufficient_univ-1.90 NA NA 0.00sr3p_ASC_auto_sufficient_shopping 0.275 0.101 2.72** 0.00
sr3p_ASC_auto_sufficient_work-0.763 0.0714-10.68*** 0.00sr3p_ASC_auto_sufficient_social 0.870 0.110 7.91*** 0.00
sr3p_ASC_no_auto_atwork 1.45 77.7 0.02 0.00sr3p_ASC_auto_sufficient_univ-1.90 2.57e-05-BIG*** 0.00
sr3p_ASC_no_auto_eatout 1.56 77.7 0.02 0.00sr3p_ASC_auto_sufficient_work-0.662 0.0868-7.63*** 0.00
sr3p_ASC_no_auto_escort-1.86 77.7-0.02 0.00sr3p_ASC_no_auto_atwork 1.49 75.9 0.02 0.00
sr3p_ASC_no_auto_othdiscr 1.27 77.7 0.02 0.00sr3p_ASC_no_auto_eatout 1.62 75.9 0.02 0.00
sr3p_ASC_no_auto_othmaint 0.243 77.7 0.00 0.00sr3p_ASC_no_auto_escort-1.87 75.9-0.02 0.00
sr3p_ASC_no_auto_school-6.02 102.-0.06 0.00sr3p_ASC_no_auto_othdiscr 1.43 75.9 0.02 0.00
sr3p_ASC_no_auto_shopping 0.711 77.7 0.01 0.00sr3p_ASC_no_auto_othmaint 0.296 75.9 0.00 0.00
sr3p_ASC_no_auto_social-1.16 77.7-0.01 0.00sr3p_ASC_no_auto_school-6.02 105.-0.06 0.00
sr3p_ASC_no_auto_univ-6.06 NA NA 0.00sr3p_ASC_no_auto_shopping 0.881 75.9 0.01 0.00
sr3p_ASC_no_auto_work 0.560 77.7 0.01 0.00sr3p_ASC_no_auto_social-1.17 75.9-0.02 0.00
taxi_ASC_auto_deficient_atwork-4.54 0.419-10.84*** 0.00sr3p_ASC_no_auto_univ-6.06 1.79e-05-BIG*** 0.00
taxi_ASC_auto_deficient_eatout_othdiscr_social-3.37 0.476-7.09*** 0.00sr3p_ASC_no_auto_work 0.614 75.9 0.01 0.00
taxi_ASC_auto_deficient_escort_othmaint_shopping-1.10 0.109-10.15*** 0.00taxi_ASC_auto_deficient_atwork-4.59 0.435-10.57*** 0.00
taxi_ASC_auto_deficient_school 0.626 0.205 3.05** 0.00taxi_ASC_auto_deficient_eatout_othdiscr_social-3.26 0.483-6.76*** 0.00
taxi_ASC_auto_deficient_univ 4.25 NA NA 0.00taxi_ASC_auto_deficient_escort_othmaint_shopping-0.930 0.118-7.89*** 0.00
taxi_ASC_auto_deficient_work-2.11 0.191-11.04*** 0.00taxi_ASC_auto_deficient_school 0.840 0.935 0.90 0.00
taxi_ASC_auto_sufficient_atwork-3.35 0.151-22.19*** 0.00taxi_ASC_auto_deficient_univ 4.25 1.62e-05 BIG*** 0.00
taxi_ASC_auto_sufficient_eatout_othdiscr_social-4.24 0.278-15.26*** 0.00taxi_ASC_auto_deficient_work-2.04 0.205-9.95*** 0.00
taxi_ASC_auto_sufficient_escort_othmaint_shopping-2.90 0.0839-34.57*** 0.00taxi_ASC_auto_sufficient_atwork-3.34 0.150-22.22*** 0.00
taxi_ASC_auto_sufficient_school-2.68 0.128-20.89*** 0.00taxi_ASC_auto_sufficient_eatout_othdiscr_social-3.93 0.246-15.96*** 0.00
taxi_ASC_auto_sufficient_univ-0.313 2.26e-05-BIG*** 0.00taxi_ASC_auto_sufficient_escort_othmaint_shopping-2.78 0.0965-28.85*** 0.00
taxi_ASC_auto_sufficient_work-5.12 0.363-14.09*** 0.00taxi_ASC_auto_sufficient_school-2.26 0.922-2.45* 0.00
taxi_ASC_no_auto_atwork 3.64 77.7 0.05 0.00taxi_ASC_auto_sufficient_univ-0.313 NA NA 0.00
taxi_ASC_no_auto_eatout_othdiscr_social-0.558 77.7-0.01 0.00taxi_ASC_auto_sufficient_work-4.85 0.303-16.01*** 0.00
taxi_ASC_no_auto_escort_othmaint_shopping 1.46 77.7 0.02 0.00taxi_ASC_no_auto_atwork 3.65 75.9 0.05 0.00
taxi_ASC_no_auto_school_univ-7.00 0.00 NA 0.00taxi_ASC_no_auto_eatout_othdiscr_social-0.571 75.9-0.01 0.00
taxi_ASC_no_auto_work 3.94 77.7 0.05 0.00taxi_ASC_no_auto_escort_othmaint_shopping 1.45 75.9 0.02 0.00
tnc_shared_ASC_auto_deficient_atwork-5.10 0.397-12.85*** 0.00taxi_ASC_no_auto_school_univ-7.00 0.00 NA 0.00
tnc_shared_ASC_auto_deficient_eatout_othdiscr_social-4.48 0.814-5.51*** 0.00taxi_ASC_no_auto_work 3.94 75.9 0.05 0.00
tnc_shared_ASC_auto_deficient_escort_othmaint_shopping-1.38 0.0981-14.08*** 0.00tnc_shared_ASC_auto_deficient_atwork-5.17 0.414-12.49*** 0.00
tnc_shared_ASC_auto_deficient_school 0.0328 0.199 0.17 0.00tnc_shared_ASC_auto_deficient_eatout_othdiscr_social-4.46 0.900-4.95*** 0.00
tnc_shared_ASC_auto_deficient_univ 3.25 1.81e-05 BIG*** 0.00tnc_shared_ASC_auto_deficient_escort_othmaint_shopping-1.24 0.109-11.36*** 0.00
tnc_shared_ASC_auto_deficient_work-3.60 0.218-16.52*** 0.00tnc_shared_ASC_auto_deficient_school 0.283 0.933 0.30 0.00
tnc_shared_ASC_auto_sufficient_atwork-4.09 0.166-24.61*** 0.00tnc_shared_ASC_auto_deficient_univ 3.25 1.25e-05 BIG*** 0.00
tnc_shared_ASC_auto_sufficient_eatout_othdiscr_social-4.53 0.201-22.49*** 0.00tnc_shared_ASC_auto_deficient_work-3.40 0.214-15.89*** 0.00
tnc_shared_ASC_auto_sufficient_escort_othmaint_shopping-3.38 0.0779-43.43*** 0.00tnc_shared_ASC_auto_sufficient_atwork-4.08 0.166-24.64*** 0.00
tnc_shared_ASC_auto_sufficient_school-4.04 0.158-25.50*** 0.00tnc_shared_ASC_auto_sufficient_eatout_othdiscr_social-4.32 0.199-21.67*** 0.00
tnc_shared_ASC_auto_sufficient_univ-0.907 NA NA 0.00tnc_shared_ASC_auto_sufficient_escort_othmaint_shopping-3.29 0.0920-35.76*** 0.00
tnc_shared_ASC_auto_sufficient_work-6.73 0.417-16.13*** 0.00tnc_shared_ASC_auto_sufficient_school-3.62 0.927-3.91*** 0.00
tnc_shared_ASC_no_auto_atwork 3.04 77.7 0.04 0.00tnc_shared_ASC_auto_sufficient_univ-0.907 NA NA 0.00
tnc_shared_ASC_no_auto_eatout_othdiscr_social-0.0561 77.7-0.00 0.00tnc_shared_ASC_auto_sufficient_work-6.48 0.411-15.77*** 0.00
tnc_shared_ASC_no_auto_escort_othmaint_shopping 0.675 77.7 0.01 0.00tnc_shared_ASC_no_auto_atwork 3.06 75.9 0.04 0.00
tnc_shared_ASC_no_auto_school-7.00 0.00 NA 0.00tnc_shared_ASC_no_auto_eatout_othdiscr_social-0.0803 75.9-0.00 0.00
tnc_shared_ASC_no_auto_univ-5.81 NA NA 0.00tnc_shared_ASC_no_auto_escort_othmaint_shopping 0.685 75.9 0.01 0.00
tnc_shared_ASC_no_auto_work 2.26 77.7 0.03 0.00tnc_shared_ASC_no_auto_school-7.00 0.00 NA 0.00
tnc_single_ASC_auto_deficient_atwork-4.20 0.308-13.65*** 0.00tnc_shared_ASC_no_auto_univ-5.81 NA NA 0.00
tnc_single_ASC_auto_deficient_eatout_othdiscr_social-3.40 0.433-7.84*** 0.00tnc_shared_ASC_no_auto_work 2.23 75.9 0.03 0.00
tnc_single_ASC_auto_deficient_escort_othmaint_shopping-0.493 0.0900-5.48*** 0.00tnc_single_ASC_auto_deficient_atwork-4.24 0.319-13.29*** 0.00
tnc_single_ASC_auto_deficient_school-0.235 0.239-0.98 0.00tnc_single_ASC_auto_deficient_eatout_othdiscr_social-3.27 0.436-7.50*** 0.00
tnc_single_ASC_auto_deficient_univ 1.02 NA NA 0.00tnc_single_ASC_auto_deficient_escort_othmaint_shopping-0.340 0.102-3.34*** 0.00
tnc_single_ASC_auto_deficient_work-1.42 0.106-13.40*** 0.00tnc_single_ASC_auto_deficient_school-0.0137 0.943-0.01 0.00
tnc_single_ASC_auto_sufficient_atwork-3.14 0.126-25.00*** 0.00tnc_single_ASC_auto_deficient_univ 1.02 NA NA 0.00
tnc_single_ASC_auto_sufficient_eatout_othdiscr_social-3.44 0.147-23.37*** 0.00tnc_single_ASC_auto_deficient_work-1.30 0.115-11.28*** 0.00
tnc_single_ASC_auto_sufficient_escort_othmaint_shopping-2.31 0.0677-34.09*** 0.00tnc_single_ASC_auto_sufficient_atwork-3.14 0.126-25.00*** 0.00
tnc_single_ASC_auto_sufficient_school-2.47 0.110-22.48*** 0.00tnc_single_ASC_auto_sufficient_eatout_othdiscr_social-3.26 0.149-21.84*** 0.00
tnc_single_ASC_auto_sufficient_univ 0.209 1.24e-05 BIG*** 0.00tnc_single_ASC_auto_sufficient_escort_othmaint_shopping-2.20 0.0833-26.43*** 0.00
tnc_single_ASC_auto_sufficient_work-4.30 0.174-24.71*** 0.00tnc_single_ASC_auto_sufficient_school-2.07 0.920-2.25* 0.00
tnc_single_ASC_no_auto_atwork 4.25 77.7 0.05 0.00tnc_single_ASC_auto_sufficient_univ 0.209 5.09e-06 BIG*** 0.00
tnc_single_ASC_no_auto_eatout_othdiscr_social 0.988 77.7 0.01 0.00tnc_single_ASC_auto_sufficient_work-4.24 0.182-23.29*** 0.00
tnc_single_ASC_no_auto_escort_othmaint_shopping 1.61 77.7 0.02 0.00tnc_single_ASC_no_auto_atwork 4.26 75.9 0.06 0.00
tnc_single_ASC_no_auto_school-7.00 0.00 NA 0.00tnc_single_ASC_no_auto_eatout_othdiscr_social 0.982 75.9 0.01 0.00
tnc_single_ASC_no_auto_univ-2.52 1.04e-05-BIG*** 0.00tnc_single_ASC_no_auto_escort_othmaint_shopping 1.60 75.9 0.02 0.00
tnc_single_ASC_no_auto_work 5.36 77.7 0.07 0.00tnc_single_ASC_no_auto_school-7.00 0.00 NA 0.00
walk_ASC_auto_deficient_atwork 0.179 0.125 1.44 0.00tnc_single_ASC_no_auto_univ-2.52 NA NA 0.00
walk_ASC_auto_deficient_eatout 1.97 0.189 10.38*** 0.00tnc_single_ASC_no_auto_work 5.31 75.9 0.07 0.00
walk_ASC_auto_deficient_escort-2.25 0.269-8.35*** 0.00walk_ASC_auto_deficient_atwork 0.227 0.123 1.84 0.00
walk_ASC_auto_deficient_othdiscr 1.07 0.146 7.33*** 0.00walk_ASC_auto_deficient_eatout 2.17 0.198 10.96*** 0.00
walk_ASC_auto_deficient_othmaint-0.0496 0.206-0.24 0.00walk_ASC_auto_deficient_escort-1.98 0.265-7.46*** 0.00
walk_ASC_auto_deficient_school 2.31 0.190 12.13*** 0.00walk_ASC_auto_deficient_othdiscr 1.21 0.154 7.86*** 0.00
walk_ASC_auto_deficient_shopping 0.790 0.128 6.18*** 0.00walk_ASC_auto_deficient_othmaint 0.145 0.208 0.70 0.00
walk_ASC_auto_deficient_social 2.06 0.291 7.09*** 0.00walk_ASC_auto_deficient_school 2.61 0.931 2.81** 0.00
walk_ASC_auto_deficient_univ 4.51 9.40e-06 BIG*** 0.00walk_ASC_auto_deficient_shopping 0.909 0.137 6.63*** 0.00
walk_ASC_auto_deficient_work 1.60 0.0818 19.57*** 0.00walk_ASC_auto_deficient_social 2.26 0.299 7.56*** 0.00
walk_ASC_auto_sufficient_atwork 0.0778 0.0580 1.34 0.00walk_ASC_auto_deficient_univ 4.51 1.92e-06 BIG*** 0.00
walk_ASC_auto_sufficient_eatout 0.530 0.0933 5.68*** 0.00walk_ASC_auto_deficient_work 1.70 0.0955 17.84*** 0.00
walk_ASC_auto_sufficient_escort-1.81 0.106-17.07*** 0.00walk_ASC_auto_sufficient_atwork 0.0776 0.0580 1.34 0.00
walk_ASC_auto_sufficient_othdiscr 0.218 0.0663 3.28** 0.00walk_ASC_auto_sufficient_eatout 0.613 0.106 5.78*** 0.00
walk_ASC_auto_sufficient_othmaint-0.244 0.0814-2.99** 0.00walk_ASC_auto_sufficient_escort-1.74 0.117-14.88*** 0.00
walk_ASC_auto_sufficient_school-0.101 0.0864-1.17 0.00walk_ASC_auto_sufficient_othdiscr 0.305 0.0829 3.68*** 0.00
walk_ASC_auto_sufficient_shopping-0.368 0.0638-5.76*** 0.00walk_ASC_auto_sufficient_othmaint-0.168 0.0955-1.76 0.00
walk_ASC_auto_sufficient_social 0.469 0.107 4.39*** 0.00walk_ASC_auto_sufficient_school 0.374 0.917 0.41 0.00
walk_ASC_auto_sufficient_univ 1.06 3.73e-07 BIG*** 0.00walk_ASC_auto_sufficient_shopping-0.304 0.0811-3.75*** 0.00
walk_ASC_auto_sufficient_work-0.393 0.0617-6.37*** 0.00walk_ASC_auto_sufficient_social 0.592 0.117 5.04*** 0.00
walk_ASC_no_auto_atwork 6.64 77.7 0.09 0.00walk_ASC_auto_sufficient_univ 1.06 NA NA 0.00
walk_ASC_no_auto_eatout 4.42 77.7 0.06 0.00walk_ASC_auto_sufficient_work-0.291 0.0787-3.70*** 0.00
walk_ASC_no_auto_escort 2.50 77.7 0.03 0.00walk_ASC_no_auto_atwork 6.63 75.9 0.09 0.00
walk_ASC_no_auto_othdiscr 2.90 77.7 0.04 0.00walk_ASC_no_auto_eatout 4.41 75.9 0.06 0.00
walk_ASC_no_auto_othmaint 0.919 77.7 0.01 0.00walk_ASC_no_auto_escort 2.51 75.9 0.03 0.00
walk_ASC_no_auto_school 17.8 106. 0.17 0.00walk_ASC_no_auto_othdiscr 2.89 75.9 0.04 0.00
walk_ASC_no_auto_shopping 2.17 77.7 0.03 0.00walk_ASC_no_auto_othmaint 0.930 75.9 0.01 0.00
walk_ASC_no_auto_social 1.71 77.7 0.02 0.00walk_ASC_no_auto_school 17.8 109. 0.16 0.00
walk_ASC_no_auto_univ 6.41 1.10e-07 BIG*** 0.00walk_ASC_no_auto_shopping 2.17 75.9 0.03 0.00
walk_ASC_no_auto_work 5.32 77.7 0.07 0.00walk_ASC_no_auto_social 1.74 75.9 0.02 0.00
walk_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.371 266.-0.00 0.00walk_ASC_no_auto_univ 6.41 NA NA 0.00
walk_ferry_ASC_school_univ 0.875 527. 0.00 0.00walk_ASC_no_auto_work 5.28 75.9 0.07 0.00
walk_ferry_ASC_work 0.153 NA NA 0.00walk_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.239 16.4-0.01 0.00
walk_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.197 266.-0.00 0.00walk_ferry_ASC_school_univ 0.858 NA NA 0.00
walk_light_rail_ASC_school_univ 0.611 527. 0.00 0.00walk_ferry_ASC_work 0.189 278. 0.00 0.00
walk_light_rail_ASC_work 0.753 NA NA 0.00walk_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.136 16.4-0.01 0.00
walk_transit_ASC_auto_deficient_atwork-2.55 266.-0.01 0.00walk_light_rail_ASC_school_univ 0.724 NA NA 0.00
walk_transit_ASC_auto_deficient_eatout-0.608 266.-0.00 0.00walk_light_rail_ASC_work 0.786 278. 0.00 0.00
walk_transit_ASC_auto_deficient_escort-4.51 266.-0.02 0.00walk_transit_ASC_auto_deficient_atwork-2.63 16.4-0.16 0.00
walk_transit_ASC_auto_deficient_othdiscr 0.823 266. 0.00 0.00walk_transit_ASC_auto_deficient_eatout-0.489 16.4-0.03 0.00
walk_transit_ASC_auto_deficient_othmaint-3.04 266.-0.01 0.00walk_transit_ASC_auto_deficient_escort-4.45 16.4-0.27 0.00
walk_transit_ASC_auto_deficient_school 2.82 527. 0.01 0.00walk_transit_ASC_auto_deficient_othdiscr 0.873 16.4 0.05 0.00
walk_transit_ASC_auto_deficient_shopping-1.17 266.-0.00 0.00walk_transit_ASC_auto_deficient_othmaint-2.97 16.4-0.18 0.00
walk_transit_ASC_auto_deficient_social 1.30 266. 0.00 0.00walk_transit_ASC_auto_deficient_school 2.97 NA NA 0.00
walk_transit_ASC_auto_deficient_univ 3.14 0.00 NA 0.00walk_transit_ASC_auto_deficient_shopping-1.07 16.4-0.07 0.00
walk_transit_ASC_auto_deficient_work 0.0872 NA NA 0.00walk_transit_ASC_auto_deficient_social 1.32 16.4 0.08 0.00
walk_transit_ASC_auto_sufficient_atwork-3.57 266.-0.01 0.00walk_transit_ASC_auto_deficient_univ 3.14 0.00 NA 0.00
walk_transit_ASC_auto_sufficient_eatout-1.34 266.-0.01 0.00walk_transit_ASC_auto_deficient_work 0.159 278. 0.00 0.00
walk_transit_ASC_auto_sufficient_escort-4.99 266.-0.02 0.00walk_transit_ASC_auto_sufficient_atwork-3.66 16.4-0.22 0.00
walk_transit_ASC_auto_sufficient_othdiscr-0.924 266.-0.00 0.00walk_transit_ASC_auto_sufficient_eatout-1.32 16.4-0.08 0.00
walk_transit_ASC_auto_sufficient_othmaint-1.71 266.-0.01 0.00walk_transit_ASC_auto_sufficient_escort-4.82 16.4-0.29 0.00
walk_transit_ASC_auto_sufficient_school 0.156 527. 0.00 0.00walk_transit_ASC_auto_sufficient_othdiscr-0.914 16.4-0.06 0.00
walk_transit_ASC_auto_sufficient_shopping-2.38 266.-0.01 0.00walk_transit_ASC_auto_sufficient_othmaint-1.68 16.4-0.10 0.00
walk_transit_ASC_auto_sufficient_social-0.668 266.-0.00 0.00walk_transit_ASC_auto_sufficient_school 0.487 NA NA 0.00
walk_transit_ASC_auto_sufficient_univ 0.473 0.00 NA 0.00walk_transit_ASC_auto_sufficient_shopping-2.35 16.4-0.14 0.00
walk_transit_ASC_auto_sufficient_work-1.43 NA NA 0.00walk_transit_ASC_auto_sufficient_social-0.647 16.4-0.04 0.00
walk_transit_ASC_no_auto_atwork 3.19 280. 0.01 0.00walk_transit_ASC_auto_sufficient_univ 0.473 0.00 NA 0.00
walk_transit_ASC_no_auto_eatout 3.02 280. 0.01 0.00walk_transit_ASC_auto_sufficient_work-1.37 278.-0.00 0.00
walk_transit_ASC_no_auto_escort-2.25 280.-0.01 0.00walk_transit_ASC_no_auto_atwork 3.13 66.9 0.05 0.00
walk_transit_ASC_no_auto_othdiscr 2.90 280. 0.01 0.00walk_transit_ASC_no_auto_eatout 2.92 66.9 0.04 0.00
walk_transit_ASC_no_auto_othmaint 2.65 280. 0.01 0.00walk_transit_ASC_no_auto_escort-2.26 67.0-0.03 0.00
walk_transit_ASC_no_auto_school 20.6 524. 0.04 0.00walk_transit_ASC_no_auto_othdiscr 2.80 66.9 0.04 0.00
walk_transit_ASC_no_auto_shopping 2.45 280. 0.01 0.00walk_transit_ASC_no_auto_othmaint 2.59 66.9 0.04 0.00
walk_transit_ASC_no_auto_social 2.11 280. 0.01 0.00walk_transit_ASC_no_auto_school 20.4 NA NA 0.00
walk_transit_ASC_no_auto_univ 8.79 0.00 NA 0.00walk_transit_ASC_no_auto_shopping 2.33 66.9 0.03 0.00
walk_transit_ASC_no_auto_work 4.67 NA NA 0.00walk_transit_ASC_no_auto_social 2.06 66.9 0.03 0.00
walk_transit_CBD_ASC_atwork 1.15 0.283 4.05*** 0.00walk_transit_ASC_no_auto_univ 8.79 0.00 NA 0.00
walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social 1.07 0.0756 14.20*** 0.00walk_transit_ASC_no_auto_work 4.60 285. 0.02 0.00
walk_transit_CBD_ASC_school_univ 0.819 0.114 7.16*** 0.00walk_transit_CBD_ASC_atwork 1.30 0.284 4.57*** 0.00
walk_transit_CBD_ASC_work 1.16 0.0539 21.50*** 0.00walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social 1.08 0.0757 14.25*** 0.00
walk_transit_CBD_ASC_school_univ 0.834 0.114 7.30*** 0.00
walk_transit_CBD_ASC_work 1.16 0.0539 21.50*** 0.00
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -4194,8 +4328,16 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": {}, + "execution_count": 14, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:22:22.519480Z", + "iopub.status.busy": "2025-06-26T02:22:22.519378Z", + "iopub.status.idle": "2025-06-26T02:22:22.604985Z", + "shell.execute_reply": "2025-06-26T02:22:22.604582Z", + "shell.execute_reply.started": "2025-06-26T02:22:22.519470Z" + } + }, "outputs": [], "source": [ "from activitysim.estimation.larch import update_coefficients\n", @@ -4215,8 +4357,16 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": {}, + "execution_count": 15, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:22:22.605439Z", + "iopub.status.busy": "2025-06-26T02:22:22.605332Z", + "iopub.status.idle": "2025-06-26T02:22:33.125948Z", + "shell.execute_reply": "2025-06-26T02:22:33.125494Z", + "shell.execute_reply.started": "2025-06-26T02:22:22.605418Z" + } + }, "outputs": [], "source": [ "model.to_xlsx(\n", @@ -4236,8 +4386,16 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": {}, + "execution_count": 16, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:22:33.126652Z", + "iopub.status.busy": "2025-06-26T02:22:33.126545Z", + "iopub.status.idle": "2025-06-26T02:22:33.132608Z", + "shell.execute_reply": "2025-06-26T02:22:33.132330Z", + "shell.execute_reply.started": "2025-06-26T02:22:33.126642Z" + } + }, "outputs": [ { "data": { @@ -4303,27 +4461,15 @@ " ...\n", " \n", " \n", - " 302\n", - " walk_transit_CBD_ASC_atwork\n", - " 1.146544\n", - " F\n", - " \n", - " \n", - " 303\n", - " drive_transit_CBD_ASC_eatout_escort_othdiscr_o...\n", - " 1.407306\n", - " F\n", - " \n", - " \n", " 304\n", " drive_transit_CBD_ASC_school_univ\n", - " 1.179871\n", + " 1.227148\n", " F\n", " \n", " \n", " 305\n", " drive_transit_CBD_ASC_work\n", - " 1.648397\n", + " 1.636347\n", " F\n", " \n", " \n", @@ -4332,9 +4478,21 @@ " 0.564000\n", " F\n", " \n", + " \n", + " 307\n", + " coef_test_eatout_escort_othdiscr_othmaint_shop...\n", + " 0.076990\n", + " F\n", + " \n", + " \n", + " 308\n", + " coef_test_school_univ\n", + " 0.518279\n", + " F\n", + " \n", " \n", "\n", - "

307 rows × 3 columns

\n", + "

309 rows × 3 columns

\n", "" ], "text/plain": [ @@ -4345,16 +4503,16 @@ "3 coef_nest_AUTO_DRIVEALONE 0.350000 T\n", "4 coef_nest_AUTO_SHAREDRIDE2 0.350000 T\n", ".. ... ... ...\n", - "302 walk_transit_CBD_ASC_atwork 1.146544 F\n", - "303 drive_transit_CBD_ASC_eatout_escort_othdiscr_o... 1.407306 F\n", - "304 drive_transit_CBD_ASC_school_univ 1.179871 F\n", - "305 drive_transit_CBD_ASC_work 1.648397 F\n", + "304 drive_transit_CBD_ASC_school_univ 1.227148 F\n", + "305 drive_transit_CBD_ASC_work 1.636347 F\n", "306 drive_transit_CBD_ASC_atwork 0.564000 F\n", + "307 coef_test_eatout_escort_othdiscr_othmaint_shop... 0.076990 F\n", + "308 coef_test_school_univ 0.518279 F\n", "\n", - "[307 rows x 3 columns]" + "[309 rows x 3 columns]" ] }, - "execution_count": 15, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -4362,6 +4520,8500 @@ "source": [ "pd.read_csv(result_dir/f\"{modelname}_coefficients_revised.csv\")" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Modify Spec\n", + "\n", + "Here, we will demonstrate the process of re-estimating the model with a modified\n", + "SPEC file. This does *not* require re-running ActivitySim, it just requires\n", + "changing the SPEC file, and possibly the coefficients and/or coefficients template files, and re-running the Larch estimation only.\n", + "\n", + "The `backup` command we ran earlier made a backup copy of the\n", + "original spec file in the EDB directory.\n", + "This was not strictly necessary, but since we're about to modify it and\n", + "we may want undo our changes, it can be handy to keep a copy of the\n", + "original spec file around. Since we already have a backup copy, we'll make some \n", + "changes directly in the SPEC file. As an example here, we're going\n", + "to add a constant term to the model, with a coefficient that is shared in common across \n", + "several (but not all) purposes.\n", + "\n", + "For this demo we are editing \n", + "the model files using Python code to make the changes, but a user does not need\n", + "to change the file using Python; any CSV editor (e.g. Excel) can be used. We will\n", + "edit three files: the spec, the coefficients, and the coefficients template.\n", + "We're not going to edit any of the existing content in any of these files, instead \n", + "we will simply add a few lines to each to add an extra expression to the spec, and\n", + "the coefficients for that expression." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:22:33.133126Z", + "iopub.status.busy": "2025-06-26T02:22:33.133030Z", + "iopub.status.idle": "2025-06-26T02:22:33.135058Z", + "shell.execute_reply": "2025-06-26T02:22:33.134812Z", + "shell.execute_reply.started": "2025-06-26T02:22:33.133117Z" + } + }, + "outputs": [], + "source": [ + "with open(data.edb_directory / \"tour_mode_choice_SPEC.csv\", mode=\"a\") as f:\n", + " f.write(\"util_test,Additional DA constant,1,coef_test,,,,,,,,,,,,,,,,,,,,\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:22:33.135393Z", + "iopub.status.busy": "2025-06-26T02:22:33.135303Z", + "iopub.status.idle": "2025-06-26T02:22:33.137578Z", + "shell.execute_reply": "2025-06-26T02:22:33.137342Z", + "shell.execute_reply.started": "2025-06-26T02:22:33.135372Z" + } + }, + "outputs": [], + "source": [ + "with open(data.edb_directory / \"tour_mode_choice_coefficients_template.csv\", mode=\"a\") as f:\n", + " f.write(\"coef_test,\"\n", + " \"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,\"\n", + " \"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,\"\n", + " \"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,\"\n", + " \"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,\"\n", + " \"coef_test_school_univ,\"\n", + " \"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,\"\n", + " \"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,\"\n", + " \"coef_test_school_univ,\"\n", + " \"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,\"\n", + " \"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:22:33.138092Z", + "iopub.status.busy": "2025-06-26T02:22:33.137967Z", + "iopub.status.idle": "2025-06-26T02:22:33.139786Z", + "shell.execute_reply": "2025-06-26T02:22:33.139542Z", + "shell.execute_reply.started": "2025-06-26T02:22:33.138083Z" + } + }, + "outputs": [], + "source": [ + "with open(data.edb_directory / \"tour_mode_choice_coefficients.csv\", mode=\"a\") as f:\n", + " f.write(\"coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork,0,F\\n\"\n", + " \"coef_test_school_univ,0,F\\n\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now to re-estimate the model, we just re-run the same steps as the original estimation above." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:23:19.234087Z", + "iopub.status.busy": "2025-06-26T02:23:19.233080Z", + "iopub.status.idle": "2025-06-26T02:23:34.736566Z", + "shell.execute_reply": "2025-06-26T02:23:34.736111Z", + "shell.execute_reply.started": "2025-06-26T02:23:19.234014Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading from output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_coefficients.csv\n", + "loading from output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_coefficients_template.csv\n", + "loading spec from output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_SPEC.csv\n", + "loading from output-est-mode/estimation_data_bundle/tour_mode_choice/tour_mode_choice_values_combined.parquet\n" + ] + } + ], + "source": [ + "remodel, redata = component_model(modelname, edb_directory=str(data.edb_directory), return_data=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:23:37.086759Z", + "iopub.status.busy": "2025-06-26T02:23:37.086146Z", + "iopub.status.idle": "2025-06-26T02:23:39.392179Z", + "shell.execute_reply": "2025-06-26T02:23:39.391840Z", + "shell.execute_reply.started": "2025-06-26T02:23:37.086721Z" + } + }, + "outputs": [], + "source": [ + "remodel.extend(model2)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:23:40.195214Z", + "iopub.status.busy": "2025-06-26T02:23:40.194549Z", + "iopub.status.idle": "2025-06-26T02:27:37.904716Z", + "shell.execute_reply": "2025-06-26T02:27:37.904362Z", + "shell.execute_reply.started": "2025-06-26T02:23:40.195175Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "

Iteration 200 [Iteration limit reached]

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Best LL = -76502.09343717809

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bike_ASC_auto_deficient_atwork-1.059385
bike_ASC_auto_deficient_eatout-1.201250
bike_ASC_auto_deficient_escort-3.880330
bike_ASC_auto_deficient_othdiscr-0.528102
bike_ASC_auto_deficient_othmaint-1.629975
bike_ASC_auto_deficient_school-1.182724
bike_ASC_auto_deficient_shopping-1.304686
bike_ASC_auto_deficient_social0.592094
bike_ASC_auto_deficient_univ-0.669235
bike_ASC_auto_deficient_work-0.360143
bike_ASC_auto_sufficient_atwork15.720172
bike_ASC_auto_sufficient_eatout-1.297285
bike_ASC_auto_sufficient_escort-5.264113
bike_ASC_auto_sufficient_othdiscr-1.491319
bike_ASC_auto_sufficient_othmaint-2.511651
bike_ASC_auto_sufficient_school-2.201436
bike_ASC_auto_sufficient_shopping-2.777945
bike_ASC_auto_sufficient_social-1.828315
bike_ASC_auto_sufficient_univ-1.939783
bike_ASC_auto_sufficient_work-2.058472
bike_ASC_no_auto_atwork-0.911319
bike_ASC_no_auto_eatout0.509502
bike_ASC_no_auto_escort-0.730310
bike_ASC_no_auto_othdiscr-0.404361
bike_ASC_no_auto_othmaint1.614051
bike_ASC_no_auto_school13.403780
bike_ASC_no_auto_shopping1.048175
bike_ASC_no_auto_social0.485746
bike_ASC_no_auto_univ4.294516
bike_ASC_no_auto_work3.427768
coef_age010_trn_multiplier_atwork0.000722
coef_age010_trn_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work0.363546
coef_age010_trn_multiplier_school_univ-0.874785
coef_age1619_da_multiplier_atwork-0.192883
coef_age1619_da_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work0.000513
coef_age1619_da_multiplier_school_univ-1.677960
coef_age16p_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social-1.451060
coef_age16p_sr_multiplier_school_univ_work_atwork-0.648072
coef_hhsize1_sr_multiplier_eatout_escort_othdiscr_othmaint_school_shopping_social_univ_atwork-0.071030
coef_hhsize1_sr_multiplier_work-0.836007
coef_hhsize2_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork0.002091
coef_hhsize2_sr_multiplier_school_univ-0.747693
coef_ivt_atwork-0.011188
coef_ivt_eatout_escort_othdiscr_othmaint_shopping_social-0.006884
coef_ivt_school_univ-0.010386
coef_ivt_work-0.007950
coef_nest_AUTO0.720000
coef_nest_AUTO_DRIVEALONE0.350000
coef_nest_AUTO_SHAREDRIDE20.350000
coef_nest_AUTO_SHAREDRIDE30.350000
coef_nest_NONMOTORIZED0.720000
coef_nest_RIDEHAIL0.360000
coef_nest_TRANSIT0.720000
coef_nest_TRANSIT_DRIVEACCESS0.500000
coef_nest_TRANSIT_WALKACCESS0.500000
coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork0.076990
coef_test_school_univ0.518279
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: eatout, dtype: object0.339513
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: escort, dtype: object0.000000
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: othdiscr, dtype: object0.230600
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: othmaint, dtype: object0.332934
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: shopping, dtype: object0.244712
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: social, dtype: object0.196574
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: work, dtype: object-0.030571
coefficient_name\\ncoef_test coef_test_school_univ\\ncoef_test coef_test_school_univ\\nName: school, dtype: object0.278054
coefficient_name\\ncoef_test coef_test_school_univ\\ncoef_test coef_test_school_univ\\nName: univ, dtype: object0.000000
commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.744041
commuter_rail_ASC_school_univ-0.247252
commuter_rail_ASC_work0.157688
drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.393253
drive_ferry_ASC_school_univ1.448664
drive_ferry_ASC_work0.193999
drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.091901
drive_light_rail_ASC_school_univ0.706784
drive_light_rail_ASC_work0.506525
drive_transit_ASC_auto_deficient_atwork-998.819580
drive_transit_ASC_auto_deficient_eatout0.104696
drive_transit_ASC_auto_deficient_escort-2.135178
drive_transit_ASC_auto_deficient_othdiscr-0.725510
drive_transit_ASC_auto_deficient_othmaint-1.174854
drive_transit_ASC_auto_deficient_school1.572565
drive_transit_ASC_auto_deficient_shopping-1.430278
drive_transit_ASC_auto_deficient_social0.594346
drive_transit_ASC_auto_deficient_univ1.850118
drive_transit_ASC_auto_deficient_work-0.911001
drive_transit_ASC_auto_sufficient_atwork-999.214661
drive_transit_ASC_auto_sufficient_eatout-1.297555
drive_transit_ASC_auto_sufficient_escort-5.253544
drive_transit_ASC_auto_sufficient_othdiscr-1.114939
drive_transit_ASC_auto_sufficient_othmaint-2.442900
drive_transit_ASC_auto_sufficient_school0.154528
drive_transit_ASC_auto_sufficient_shopping-3.967262
drive_transit_ASC_auto_sufficient_social-1.343284
drive_transit_ASC_auto_sufficient_univ1.358775
drive_transit_ASC_auto_sufficient_work-1.831235
drive_transit_ASC_no_auto_all0.000000
drive_transit_CBD_ASC_atwork0.564000
drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social1.413499
drive_transit_CBD_ASC_school_univ1.203794
drive_transit_CBD_ASC_work1.616319
express_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.088784
express_bus_ASC_school_univ-0.449853
express_bus_ASC_work-0.920137
heavy_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork0.040071
heavy_rail_ASC_school_univ0.126501
heavy_rail_ASC_work0.496146
joint_bike_ASC_auto_deficient_all-6.159645
joint_bike_ASC_auto_sufficient_all-6.948677
joint_bike_ASC_no_auto_all-2.667145
joint_drive_transit_ASC_auto_deficient_all-6.040459
joint_drive_transit_ASC_auto_sufficient_all-7.802616
joint_drive_transit_ASC_no_auto_all0.000000
joint_sr2_ASC_auto_deficient_all0.000000
joint_sr2_ASC_auto_sufficient_all0.000000
joint_sr2_ASC_no_auto_all0.000000
joint_sr3p_ASC_auto_deficient_all-1.508271
joint_sr3p_ASC_auto_sufficient_all-2.268077
joint_sr3p_ASC_no_auto_all0.680128
joint_taxi_ASC_auto_deficient_all-9.817099
joint_taxi_ASC_auto_sufficient_all-11.709900
joint_taxi_ASC_no_auto_all-4.583211
joint_tnc_shared_ASC_auto_deficient_all-11.157463
joint_tnc_shared_ASC_auto_sufficient_all-13.205000
joint_tnc_shared_ASC_no_auto_all-4.699899
joint_tnc_single_ASC_auto_deficient_all-9.898289
joint_tnc_single_ASC_auto_sufficient_all-14.015900
joint_tnc_single_ASC_no_auto_all-3.890298
joint_walk_ASC_auto_deficient_all-2.049580
joint_walk_ASC_auto_sufficient_all-4.151795
joint_walk_ASC_no_auto_all-0.294038
joint_walk_transit_ASC_auto_deficient_all-5.295731
joint_walk_transit_ASC_auto_sufficient_all-18.264534
joint_walk_transit_ASC_no_auto_all0.350958
local_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.943275
local_bus_ASC_school_univ-0.811253
local_bus_ASC_work-0.210576
sr2_ASC_auto_deficient_atwork-1.571425
sr2_ASC_auto_deficient_eatout1.323994
sr2_ASC_auto_deficient_escort0.560298
sr2_ASC_auto_deficient_othdiscr1.316437
sr2_ASC_auto_deficient_othmaint1.027389
sr2_ASC_auto_deficient_school0.521971
sr2_ASC_auto_deficient_shopping0.800981
sr2_ASC_auto_deficient_social2.418469
sr2_ASC_auto_deficient_univ-1.692235
sr2_ASC_auto_deficient_work0.248251
sr2_ASC_auto_sufficient_atwork-0.810446
sr2_ASC_auto_sufficient_eatout1.632701
sr2_ASC_auto_sufficient_escort0.754348
sr2_ASC_auto_sufficient_othdiscr1.091357
sr2_ASC_auto_sufficient_othmaint1.094521
sr2_ASC_auto_sufficient_school-0.720077
sr2_ASC_auto_sufficient_shopping0.805726
sr2_ASC_auto_sufficient_social1.065900
sr2_ASC_auto_sufficient_univ-1.859427
sr2_ASC_auto_sufficient_work-0.477609
sr2_ASC_no_auto_all1.173523
sr3p_ASC_auto_deficient_atwork-1.881594
sr3p_ASC_auto_deficient_eatout0.638190
sr3p_ASC_auto_deficient_escort0.335767
sr3p_ASC_auto_deficient_othdiscr1.672007
sr3p_ASC_auto_deficient_othmaint-0.202298
sr3p_ASC_auto_deficient_school1.094613
sr3p_ASC_auto_deficient_shopping0.457352
sr3p_ASC_auto_deficient_social2.155012
sr3p_ASC_auto_deficient_univ-1.727742
sr3p_ASC_auto_deficient_work-0.289309
sr3p_ASC_auto_sufficient_atwork-1.003854
sr3p_ASC_auto_sufficient_eatout1.576426
sr3p_ASC_auto_sufficient_escort0.729492
sr3p_ASC_auto_sufficient_othdiscr1.182849
sr3p_ASC_auto_sufficient_othmaint0.726042
sr3p_ASC_auto_sufficient_school-0.151086
sr3p_ASC_auto_sufficient_shopping0.560767
sr3p_ASC_auto_sufficient_social1.073137
sr3p_ASC_auto_sufficient_univ-1.904710
sr3p_ASC_auto_sufficient_work-0.848535
sr3p_ASC_no_auto_atwork1.665939
sr3p_ASC_no_auto_eatout1.528129
sr3p_ASC_no_auto_escort-1.866823
sr3p_ASC_no_auto_othdiscr1.403607
sr3p_ASC_no_auto_othmaint0.194971
sr3p_ASC_no_auto_school-6.024155
sr3p_ASC_no_auto_shopping0.846912
sr3p_ASC_no_auto_social-1.209366
sr3p_ASC_no_auto_univ-6.056001
sr3p_ASC_no_auto_work0.522935
taxi_ASC_auto_deficient_atwork-4.750529
taxi_ASC_auto_deficient_eatout_othdiscr_social-3.164652
taxi_ASC_auto_deficient_escort_othmaint_shopping-0.502553
taxi_ASC_auto_deficient_school0.899118
taxi_ASC_auto_deficient_univ4.249200
taxi_ASC_auto_deficient_work-2.299959
taxi_ASC_auto_sufficient_atwork-3.311568
taxi_ASC_auto_sufficient_eatout_othdiscr_social-3.474973
taxi_ASC_auto_sufficient_escort_othmaint_shopping-2.325136
taxi_ASC_auto_sufficient_school-2.230947
taxi_ASC_auto_sufficient_univ-0.313100
taxi_ASC_auto_sufficient_work-5.138446
taxi_ASC_no_auto_atwork3.627714
taxi_ASC_no_auto_eatout_othdiscr_social-0.460021
taxi_ASC_no_auto_escort_othmaint_shopping1.536364
taxi_ASC_no_auto_school_univ-7.000000
taxi_ASC_no_auto_work3.889335
tnc_shared_ASC_auto_deficient_atwork-5.208859
tnc_shared_ASC_auto_deficient_eatout_othdiscr_social-4.431790
tnc_shared_ASC_auto_deficient_escort_othmaint_shopping-0.796074
tnc_shared_ASC_auto_deficient_school0.312003
tnc_shared_ASC_auto_deficient_univ3.250000
tnc_shared_ASC_auto_deficient_work-3.733595
tnc_shared_ASC_auto_sufficient_atwork-4.094668
tnc_shared_ASC_auto_sufficient_eatout_othdiscr_social-3.879623
tnc_shared_ASC_auto_sufficient_escort_othmaint_shopping-2.832616
tnc_shared_ASC_auto_sufficient_school-3.620468
tnc_shared_ASC_auto_sufficient_univ-0.906800
tnc_shared_ASC_auto_sufficient_work-6.741197
tnc_shared_ASC_no_auto_atwork3.035906
tnc_shared_ASC_no_auto_eatout_othdiscr_social-0.000529
tnc_shared_ASC_no_auto_escort_othmaint_shopping0.776143
tnc_shared_ASC_no_auto_school-7.000000
tnc_shared_ASC_no_auto_univ-5.811600
tnc_shared_ASC_no_auto_work2.211617
tnc_single_ASC_auto_deficient_atwork-4.359982
tnc_single_ASC_auto_deficient_eatout_othdiscr_social-3.121747
tnc_single_ASC_auto_deficient_escort_othmaint_shopping0.092823
tnc_single_ASC_auto_deficient_school0.059727
tnc_single_ASC_auto_deficient_univ1.022100
tnc_single_ASC_auto_deficient_work-1.472138
tnc_single_ASC_auto_sufficient_atwork-3.135939
tnc_single_ASC_auto_sufficient_eatout_othdiscr_social-2.826943
tnc_single_ASC_auto_sufficient_escort_othmaint_shopping-1.756842
tnc_single_ASC_auto_sufficient_school-2.018347
tnc_single_ASC_auto_sufficient_univ0.208800
tnc_single_ASC_auto_sufficient_work-4.328498
tnc_single_ASC_no_auto_atwork4.240527
tnc_single_ASC_no_auto_eatout_othdiscr_social1.063350
tnc_single_ASC_no_auto_escort_othmaint_shopping1.698535
tnc_single_ASC_no_auto_school-7.000000
tnc_single_ASC_no_auto_univ-2.519000
tnc_single_ASC_no_auto_work5.312088
walk_ASC_auto_deficient_atwork0.174536
walk_ASC_auto_deficient_eatout2.703990
walk_ASC_auto_deficient_escort-1.602460
walk_ASC_auto_deficient_othdiscr1.568287
walk_ASC_auto_deficient_othmaint0.642511
walk_ASC_auto_deficient_school2.647520
walk_ASC_auto_deficient_shopping1.312088
walk_ASC_auto_deficient_social2.482888
walk_ASC_auto_deficient_univ4.505910
walk_ASC_auto_deficient_work1.589921
walk_ASC_auto_sufficient_atwork0.078581
walk_ASC_auto_sufficient_eatout1.185624
walk_ASC_auto_sufficient_escort-1.315039
walk_ASC_auto_sufficient_othdiscr0.660807
walk_ASC_auto_sufficient_othmaint0.439213
walk_ASC_auto_sufficient_school0.382641
walk_ASC_auto_sufficient_shopping0.081775
walk_ASC_auto_sufficient_social0.911126
walk_ASC_auto_sufficient_univ1.060766
walk_ASC_auto_sufficient_work-0.417450
walk_ASC_no_auto_atwork6.611279
walk_ASC_no_auto_eatout4.520665
walk_ASC_no_auto_escort2.558862
walk_ASC_no_auto_othdiscr2.961389
walk_ASC_no_auto_othmaint1.056949
walk_ASC_no_auto_school17.800582
walk_ASC_no_auto_shopping2.263652
walk_ASC_no_auto_social1.844138
walk_ASC_no_auto_univ6.408967
walk_ASC_no_auto_work5.277625
walk_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.034691
walk_ferry_ASC_school_univ0.903288
walk_ferry_ASC_work0.075113
walk_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork0.115212
walk_light_rail_ASC_school_univ0.720550
walk_light_rail_ASC_work0.730077
walk_transit_ASC_auto_deficient_atwork-2.844239
walk_transit_ASC_auto_deficient_eatout-0.205432
walk_transit_ASC_auto_deficient_escort-4.464762
walk_transit_ASC_auto_deficient_othdiscr0.997111
walk_transit_ASC_auto_deficient_othmaint-2.906453
walk_transit_ASC_auto_deficient_school3.003413
walk_transit_ASC_auto_deficient_shopping-0.898698
walk_transit_ASC_auto_deficient_social1.324930
walk_transit_ASC_auto_deficient_univ3.136256
walk_transit_ASC_auto_deficient_work0.066276
walk_transit_ASC_auto_sufficient_atwork-3.764087
walk_transit_ASC_auto_sufficient_eatout-0.985317
walk_transit_ASC_auto_sufficient_escort-4.683494
walk_transit_ASC_auto_sufficient_othdiscr-0.771461
walk_transit_ASC_auto_sufficient_othmaint-1.309230
walk_transit_ASC_auto_sufficient_school0.522457
walk_transit_ASC_auto_sufficient_shopping-2.202302
walk_transit_ASC_auto_sufficient_social-0.595214
walk_transit_ASC_auto_sufficient_univ0.473116
walk_transit_ASC_auto_sufficient_work-1.474310
walk_transit_ASC_no_auto_atwork2.978048
walk_transit_ASC_no_auto_eatout2.764558
walk_transit_ASC_no_auto_escort-2.263431
walk_transit_ASC_no_auto_othdiscr2.638916
walk_transit_ASC_no_auto_othmaint2.431884
walk_transit_ASC_no_auto_school20.462674
walk_transit_ASC_no_auto_shopping2.182496
walk_transit_ASC_no_auto_social1.900415
walk_transit_ASC_no_auto_univ8.786037
walk_transit_ASC_no_auto_work4.631023
walk_transit_CBD_ASC_atwork1.184225
walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social1.088968
walk_transit_CBD_ASC_school_univ0.826484
walk_transit_CBD_ASC_work1.146513
logloss1.0933400042471608
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0
-9990.000000e+00
10.000000e+00
bike_ASC_auto_deficient_atwork1.774086e-05
bike_ASC_auto_deficient_eatout5.086225e-06
bike_ASC_auto_deficient_escort1.041342e-05
bike_ASC_auto_deficient_othdiscr-5.778635e-07
bike_ASC_auto_deficient_othmaint-6.765009e-06
bike_ASC_auto_deficient_school2.953352e-05
bike_ASC_auto_deficient_shopping-9.789016e-07
bike_ASC_auto_deficient_social-1.500595e-05
bike_ASC_auto_deficient_univ0.000000e+00
bike_ASC_auto_deficient_work-2.177390e-05
bike_ASC_auto_sufficient_atwork7.360022e-11
bike_ASC_auto_sufficient_eatout5.699513e-06
bike_ASC_auto_sufficient_escort-1.189039e-05
bike_ASC_auto_sufficient_othdiscr-3.053639e-06
bike_ASC_auto_sufficient_othmaint6.207501e-06
bike_ASC_auto_sufficient_school-3.955640e-05
bike_ASC_auto_sufficient_shopping2.371630e-06
bike_ASC_auto_sufficient_social8.079152e-06
bike_ASC_auto_sufficient_univ0.000000e+00
bike_ASC_auto_sufficient_work-7.377310e-05
bike_ASC_no_auto_atwork-1.079009e-07
bike_ASC_no_auto_eatout-1.351470e-05
bike_ASC_no_auto_escort-6.632985e-07
bike_ASC_no_auto_othdiscr-7.848992e-06
bike_ASC_no_auto_othmaint-1.700614e-05
bike_ASC_no_auto_school5.416195e-05
bike_ASC_no_auto_shopping-1.106327e-05
bike_ASC_no_auto_social-1.724981e-05
bike_ASC_no_auto_univ0.000000e+00
bike_ASC_no_auto_work-4.669114e-05
coef_age010_trn_multiplier_atwork0.000000e+00
coef_age010_trn_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work-4.351067e-05
coef_age010_trn_multiplier_school_univ-6.148052e-06
coef_age1619_da_multiplier_atwork2.370563e-06
coef_age1619_da_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work7.865522e-05
coef_age1619_da_multiplier_school_univ5.794259e-05
coef_age16p_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social6.559047e-06
coef_age16p_sr_multiplier_school_univ_work_atwork2.000044e-04
coef_hhsize1_sr_multiplier_eatout_escort_othdiscr_othmaint_school_shopping_social_univ_atwork7.346641e-05
coef_hhsize1_sr_multiplier_work-3.556634e-05
coef_hhsize2_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork-1.320963e-04
coef_hhsize2_sr_multiplier_school_univ-2.237656e-06
coef_ivt_atwork5.354940e-05
coef_ivt_eatout_escort_othdiscr_othmaint_shopping_social1.361858e-03
coef_ivt_school_univ5.392887e-04
coef_ivt_work1.007546e-03
coef_nest_AUTO1.718013e-03
coef_nest_AUTO_DRIVEALONE3.960085e-04
coef_nest_AUTO_SHAREDRIDE2-4.321150e-05
coef_nest_AUTO_SHAREDRIDE3-4.203121e-17
coef_nest_NONMOTORIZED2.445183e-04
coef_nest_RIDEHAIL3.970494e-02
coef_nest_TRANSIT-6.735168e-03
coef_nest_TRANSIT_DRIVEACCESS-5.412309e-03
coef_nest_TRANSIT_WALKACCESS-4.990662e-03
coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork0.000000e+00
coef_test_school_univ0.000000e+00
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: eatout, dtype: object2.972870e-05
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: escort, dtype: object0.000000e+00
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: othdiscr, dtype: object-3.077223e-05
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: othmaint, dtype: object2.351673e-05
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: shopping, dtype: object-9.832621e-06
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: social, dtype: object-2.774498e-05
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: work, dtype: object5.099878e-05
coefficient_name\\ncoef_test coef_test_school_univ\\ncoef_test coef_test_school_univ\\nName: school, dtype: object2.043797e-04
coefficient_name\\ncoef_test coef_test_school_univ\\ncoef_test coef_test_school_univ\\nName: univ, dtype: object0.000000e+00
commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-1.076357e-05
commuter_rail_ASC_school_univ4.538199e-05
commuter_rail_ASC_work2.680006e-05
drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-1.539882e-05
drive_ferry_ASC_school_univ-1.492963e-05
drive_ferry_ASC_work5.248967e-05
drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-3.564786e-05
drive_light_rail_ASC_school_univ-5.604245e-06
drive_light_rail_ASC_work3.779577e-05
drive_transit_ASC_auto_deficient_atwork0.000000e+00
drive_transit_ASC_auto_deficient_eatout4.925097e-06
drive_transit_ASC_auto_deficient_escort-1.075357e-05
drive_transit_ASC_auto_deficient_othdiscr-9.490300e-06
drive_transit_ASC_auto_deficient_othmaint1.225259e-06
drive_transit_ASC_auto_deficient_school6.513910e-05
drive_transit_ASC_auto_deficient_shopping-1.342895e-05
drive_transit_ASC_auto_deficient_social-7.970583e-07
drive_transit_ASC_auto_deficient_univ0.000000e+00
drive_transit_ASC_auto_deficient_work-2.589444e-05
drive_transit_ASC_auto_sufficient_atwork0.000000e+00
drive_transit_ASC_auto_sufficient_eatout-1.080784e-05
drive_transit_ASC_auto_sufficient_escort-2.626942e-05
drive_transit_ASC_auto_sufficient_othdiscr-7.774693e-06
drive_transit_ASC_auto_sufficient_othmaint-1.165773e-05
drive_transit_ASC_auto_sufficient_school2.119160e-05
drive_transit_ASC_auto_sufficient_shopping-1.340120e-07
drive_transit_ASC_auto_sufficient_social-8.214597e-06
drive_transit_ASC_auto_sufficient_univ0.000000e+00
drive_transit_ASC_auto_sufficient_work-4.622149e-05
drive_transit_ASC_no_auto_all0.000000e+00
drive_transit_CBD_ASC_atwork0.000000e+00
drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social-4.684988e-06
drive_transit_CBD_ASC_school_univ-3.805396e-05
drive_transit_CBD_ASC_work-6.488983e-05
express_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-1.885124e-05
express_bus_ASC_school_univ5.641507e-06
express_bus_ASC_work-9.987402e-07
heavy_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-1.544009e-05
heavy_rail_ASC_school_univ-4.234502e-05
heavy_rail_ASC_work-2.393953e-04
joint_bike_ASC_auto_deficient_all-6.478420e-06
joint_bike_ASC_auto_sufficient_all-4.580153e-05
joint_bike_ASC_no_auto_all7.966080e-06
joint_drive_transit_ASC_auto_deficient_all-6.199588e-06
joint_drive_transit_ASC_auto_sufficient_all4.372034e-06
joint_drive_transit_ASC_no_auto_all0.000000e+00
joint_sr2_ASC_auto_deficient_all0.000000e+00
joint_sr2_ASC_auto_sufficient_all0.000000e+00
joint_sr2_ASC_no_auto_all0.000000e+00
joint_sr3p_ASC_auto_deficient_all-1.008236e-05
joint_sr3p_ASC_auto_sufficient_all2.534002e-05
joint_sr3p_ASC_no_auto_all5.235127e-06
joint_taxi_ASC_auto_deficient_all-1.164850e-07
joint_taxi_ASC_auto_sufficient_all0.000000e+00
joint_taxi_ASC_no_auto_all-3.151328e-07
joint_tnc_shared_ASC_auto_deficient_all-2.107226e-08
joint_tnc_shared_ASC_auto_sufficient_all0.000000e+00
joint_tnc_shared_ASC_no_auto_all-1.881990e-05
joint_tnc_single_ASC_auto_deficient_all-1.783185e-07
joint_tnc_single_ASC_auto_sufficient_all0.000000e+00
joint_tnc_single_ASC_no_auto_all3.023204e-05
joint_walk_ASC_auto_deficient_all-3.050589e-05
joint_walk_ASC_auto_sufficient_all-1.286366e-05
joint_walk_ASC_no_auto_all-1.617279e-05
joint_walk_transit_ASC_auto_deficient_all-6.415354e-06
joint_walk_transit_ASC_auto_sufficient_all-2.728968e-11
joint_walk_transit_ASC_no_auto_all-5.541879e-06
local_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork1.259957e-04
local_bus_ASC_school_univ-5.596945e-05
local_bus_ASC_work1.016212e-04
sr2_ASC_auto_deficient_atwork2.242653e-05
sr2_ASC_auto_deficient_eatout9.816584e-07
sr2_ASC_auto_deficient_escort5.813310e-06
sr2_ASC_auto_deficient_othdiscr-1.246664e-05
sr2_ASC_auto_deficient_othmaint-1.373838e-05
sr2_ASC_auto_deficient_school2.466906e-05
sr2_ASC_auto_deficient_shopping1.962366e-05
sr2_ASC_auto_deficient_social-1.133811e-05
sr2_ASC_auto_deficient_univ0.000000e+00
sr2_ASC_auto_deficient_work3.366868e-05
sr2_ASC_auto_sufficient_atwork-3.856744e-05
sr2_ASC_auto_sufficient_eatout-6.401070e-06
sr2_ASC_auto_sufficient_escort3.483448e-05
sr2_ASC_auto_sufficient_othdiscr-1.727323e-04
sr2_ASC_auto_sufficient_othmaint8.908591e-05
sr2_ASC_auto_sufficient_school-7.725139e-05
sr2_ASC_auto_sufficient_shopping-5.510640e-05
sr2_ASC_auto_sufficient_social3.858880e-05
sr2_ASC_auto_sufficient_univ0.000000e+00
sr2_ASC_auto_sufficient_work1.019533e-04
sr2_ASC_no_auto_all1.418570e-05
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nit200
nfev211
njev200
status9
message'Iteration limit reached'
successFalse
elapsed_time0:01:46.414845
method'slsqp'
n_cases69971
iteration_number200
loglike-76502.09343717809
" + ], + "text/plain": [ + "┣ x: -999 -999.000000\n", + "┃ 1 1.000000\n", + "┃ bike_ASC_auto_deficient_atwork -1.059385\n", + "┃ bike_ASC_auto_deficient_eatout -1.201250\n", + "┃ bike_ASC_auto_deficient_escort -3.880330\n", + "┃ ... \n", + "┃ walk_transit_ASC_no_auto_work 4.631023\n", + "┃ walk_transit_CBD_ASC_atwork 1.184225\n", + "┃ walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social 1.088968\n", + "┃ walk_transit_CBD_ASC_school_univ 0.826484\n", + "┃ walk_transit_CBD_ASC_work 1.146513\n", + "┃ Length: 312, dtype: float64\n", + "┣ logloss: 1.0933400042471608\n", + "┣ d_logloss: -999 0.000000\n", + "┃ 1 0.000000\n", + "┃ bike_ASC_auto_deficient_atwork 0.000018\n", + "┃ bike_ASC_auto_deficient_eatout 0.000005\n", + "┃ bike_ASC_auto_deficient_escort 0.000010\n", + "┃ ... \n", + "┃ walk_transit_ASC_no_auto_work 0.000049\n", + "┃ walk_transit_CBD_ASC_atwork -0.000097\n", + "┃ walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social 0.000019\n", + "┃ walk_transit_CBD_ASC_school_univ 0.000020\n", + "┃ walk_transit_CBD_ASC_work 0.000038\n", + "┃ Length: 312, dtype: float64\n", + "┣ nit: 200\n", + "┣ nfev: 211\n", + "┣ njev: 200\n", + "┣ status: 9\n", + "┣ message: 'Iteration limit reached'\n", + "┣ success: False\n", + "┣ elapsed_time: datetime.timedelta(seconds=106, microseconds=414845)\n", + "┣ method: 'slsqp'\n", + "┣ n_cases: 69971\n", + "┣ iteration_number: 200\n", + "┣ loglike: -76502.09343717809" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "remodel.estimate(maxiter=200)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can easily review the parameter estimates from the original and\n", + "revised models side by side to see what changed." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:27:37.905478Z", + "iopub.status.busy": "2025-06-26T02:27:37.905380Z", + "iopub.status.idle": "2025-06-26T02:27:37.943038Z", + "shell.execute_reply": "2025-06-26T02:27:37.942668Z", + "shell.execute_reply.started": "2025-06-26T02:27:37.905469Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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modelremodel
ValueStd Errt StatSignifNull ValueValueStd Errt StatSignifNull Value
Parameter
-999-999.0.00NA0.0-999.0.00NA0.0
11.000.00NA0.01.000.00NA0.0
bike_ASC_auto_deficient_atwork-1.050.344-3.07**0.0-1.060.340-3.11**0.0
bike_ASC_auto_deficient_eatout-1.460.396-3.69***0.0-1.200.594-2.02*0.0
bike_ASC_auto_deficient_escort-3.980.406-9.79***0.0-3.880.559-6.94***0.0
bike_ASC_auto_deficient_othdiscr-0.9100.203-4.47***0.0-0.5280.418-1.260.0
bike_ASC_auto_deficient_othmaint-2.060.323-6.37***0.0-1.630.448-3.64***0.0
bike_ASC_auto_deficient_school-1.200.964-1.240.0-1.180.997-1.190.0
bike_ASC_auto_deficient_shopping-1.740.218-7.99***0.0-1.300.363-3.59***0.0
bike_ASC_auto_deficient_social0.3610.3251.110.00.5920.5321.110.0
bike_ASC_auto_deficient_univ-0.669NANA0.0-0.6690.00146-458.48***0.0
bike_ASC_auto_deficient_work-0.2790.0926-3.01**0.0-0.3600.0922-3.90***0.0
bike_ASC_auto_sufficient_atwork15.7470.0.030.015.7463.0.030.0
bike_ASC_auto_sufficient_eatout-1.850.159-11.60***0.0-1.300.409-3.17**0.0
bike_ASC_auto_sufficient_escort-5.650.337-16.76***0.0-5.260.453-11.62***0.0
bike_ASC_auto_sufficient_othdiscr-1.860.105-17.64***0.0-1.490.382-3.91***0.0
bike_ASC_auto_sufficient_othmaint-3.170.193-16.40***0.0-2.510.349-7.20***0.0
bike_ASC_auto_sufficient_school-2.210.919-2.40*0.0-2.200.953-2.31*0.0
bike_ASC_auto_sufficient_shopping-3.140.138-22.70***0.0-2.780.326-8.52***0.0
bike_ASC_auto_sufficient_social-2.140.207-10.36***0.0-1.830.471-3.88***0.0
bike_ASC_auto_sufficient_univ-1.940.00657-295.46***0.0-1.940.00650-298.24***0.0
bike_ASC_auto_sufficient_work-1.930.0814-23.72***0.0-2.060.0822-25.06***0.0
bike_ASC_no_auto_atwork-0.91076.5-0.010.0-0.91187.8-0.010.0
bike_ASC_no_auto_eatout0.42875.90.010.00.51087.20.010.0
bike_ASC_no_auto_escort-0.74575.9-0.010.0-0.73087.2-0.010.0
bike_ASC_no_auto_othdiscr-0.50175.9-0.010.0-0.40487.2-0.000.0
bike_ASC_no_auto_othmaint1.5375.90.020.01.6187.20.020.0
bike_ASC_no_auto_school13.5109.0.120.013.4116.0.120.0
bike_ASC_no_auto_shopping0.95175.90.010.01.0587.20.010.0
bike_ASC_no_auto_social0.37475.90.000.00.48687.20.010.0
bike_ASC_no_auto_univ4.290.00148BIG***0.04.290.00688624.05***0.0
bike_ASC_no_auto_work3.4375.90.050.03.4387.20.040.0
coef_age010_trn_multiplier_atwork0.0007220.007850.090.00.000722NANA0.0
coef_age010_trn_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work0.4900.1762.79**0.00.3640.1752.08*0.0
coef_age010_trn_multiplier_school_univ-0.8510.0900-9.46***0.0-0.8750.0898-9.74***0.0
coef_age1619_da_multiplier_atwork-0.1750.205-0.850.0-0.1930.205-0.940.0
coef_age1619_da_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work0.03570.04250.840.00.0005130.04240.010.0
coef_age1619_da_multiplier_school_univ-1.670.0748-22.31***0.0-1.680.0748-22.42***0.0
coef_age16p_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social-1.580.0842-18.71***0.0-1.450.0814-17.82***0.0
coef_age16p_sr_multiplier_school_univ_work_atwork-0.6880.0682-10.08***0.0-0.6480.0683-9.49***0.0
coef_hhsize1_sr_multiplier_eatout_escort_othdiscr_othmaint_school_shopping_social_univ_atwork-0.07210.0312-2.31*0.0-0.07100.0312-2.27*0.0
coef_hhsize1_sr_multiplier_work-0.8220.0571-14.39***0.0-0.8360.0577-14.48***0.0
coef_hhsize2_sr_multiplier_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork-0.004040.0178-0.230.00.002090.01780.120.0
coef_hhsize2_sr_multiplier_school_univ-0.7430.0912-8.15***0.0-0.7480.0912-8.20***0.0
coef_ivt_atwork-0.01120.000479-23.41***0.0-0.01120.000478-23.41***0.0
coef_ivt_eatout_escort_othdiscr_othmaint_shopping_social-0.006910.000145-47.76***0.0-0.006880.000144-47.65***0.0
coef_ivt_school_univ-0.01030.000316-32.62***0.0-0.01040.000318-32.71***0.0
coef_ivt_work-0.007910.000147-53.62***0.0-0.007950.000148-53.70***0.0
coef_nest_AUTO0.7200.00NA1.00.7200.00NA1.0
coef_nest_AUTO_DRIVEALONE0.3500.00NA1.00.3500.00NA1.0
coef_nest_AUTO_SHAREDRIDE20.3500.00NA1.00.3500.00NA1.0
coef_nest_AUTO_SHAREDRIDE30.3500.00NA1.00.3500.00NA1.0
coef_nest_NONMOTORIZED0.7200.00NA1.00.7200.00NA1.0
coef_nest_RIDEHAIL0.3600.00NA1.00.3600.00NA1.0
coef_nest_TRANSIT0.7200.00NA1.00.7200.00NA1.0
coef_nest_TRANSIT_DRIVEACCESS0.5000.00NA1.00.5000.00NA1.0
coef_nest_TRANSIT_WALKACCESS0.5000.00NA1.00.5000.00NA1.0
coef_test_eatout_escort_othdiscr_othmaint_shopping_social_work_atwork0.07700.04941.560.00.0770NANA0.0
coef_test_school_univ0.5180.9130.570.00.518NANA0.0
commuter_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.95816.4-0.060.0-0.74420.6-0.040.0
commuter_rail_ASC_school_univ-0.258NANA0.0-0.247NANA0.0
commuter_rail_ASC_work0.196278.0.000.00.158NANA0.0
drive_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.62816.4-0.040.0-0.39320.6-0.020.0
drive_ferry_ASC_school_univ1.43NANA0.01.45NANA0.0
drive_ferry_ASC_work0.232278.0.000.00.194NANA0.0
drive_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.32516.4-0.020.0-0.091920.6-0.000.0
drive_light_rail_ASC_school_univ0.691NANA0.00.707NANA0.0
drive_light_rail_ASC_work0.530278.0.000.00.507NANA0.0
drive_transit_ASC_auto_deficient_atwork-999.0.000360-BIG***0.0-999.0.000231-BIG***0.0
drive_transit_ASC_auto_deficient_eatout-0.17316.4-0.010.00.10520.60.010.0
drive_transit_ASC_auto_deficient_escort-2.1916.4-0.130.0-2.1420.6-0.100.0
drive_transit_ASC_auto_deficient_othdiscr-0.85216.4-0.050.0-0.72620.6-0.040.0
drive_transit_ASC_auto_deficient_othmaint-1.3616.4-0.080.0-1.1720.6-0.060.0
drive_transit_ASC_auto_deficient_school1.59NANA0.01.57NANA0.0
drive_transit_ASC_auto_deficient_shopping-1.5816.4-0.100.0-1.4320.6-0.070.0
drive_transit_ASC_auto_deficient_social0.61016.40.040.00.59420.60.030.0
drive_transit_ASC_auto_deficient_univ1.85NANA0.01.85NANA0.0
drive_transit_ASC_auto_deficient_work-0.824278.-0.000.0-0.911NANA0.0
drive_transit_ASC_auto_sufficient_atwork-999.0.000176-BIG***0.0-999.NANA0.0
drive_transit_ASC_auto_sufficient_eatout-1.6516.4-0.100.0-1.3020.6-0.060.0
drive_transit_ASC_auto_sufficient_escort-5.3116.4-0.320.0-5.2520.6-0.260.0
drive_transit_ASC_auto_sufficient_othdiscr-1.2416.4-0.080.0-1.1120.6-0.050.0
drive_transit_ASC_auto_sufficient_othmaint-2.8016.4-0.170.0-2.4420.6-0.120.0
drive_transit_ASC_auto_sufficient_school0.105NANA0.00.155NANA0.0
drive_transit_ASC_auto_sufficient_shopping-4.1616.4-0.250.0-3.9720.6-0.190.0
drive_transit_ASC_auto_sufficient_social-1.3716.4-0.080.0-1.3420.6-0.070.0
drive_transit_ASC_auto_sufficient_univ1.36NANA0.01.360.000291BIG***0.0
drive_transit_ASC_auto_sufficient_work-1.73278.-0.010.0-1.83NANA0.0
drive_transit_ASC_no_auto_all0.00NANA0.00.000.0002930.000.0
drive_transit_CBD_ASC_atwork0.564NANA0.00.564NANA0.0
drive_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social1.370.1429.63***0.01.410.1429.95***0.0
drive_transit_CBD_ASC_school_univ1.230.2514.89***0.01.200.2534.76***0.0
drive_transit_CBD_ASC_work1.640.069823.45***0.01.620.069723.19***0.0
express_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.34216.4-0.020.0-0.088820.6-0.000.0
express_bus_ASC_school_univ-0.451NANA0.0-0.450NANA0.0
express_bus_ASC_work-0.881278.-0.000.0-0.920NANA0.0
heavy_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.20716.4-0.010.00.040120.60.000.0
heavy_rail_ASC_school_univ0.110NANA0.00.127NANA0.0
heavy_rail_ASC_work0.513278.0.000.00.496NANA0.0
joint_bike_ASC_auto_deficient_all-6.181.34-4.62***0.0-6.161.42-4.35***0.0
joint_bike_ASC_auto_sufficient_all-7.100.465-15.28***0.0-6.950.465-14.96***0.0
joint_bike_ASC_no_auto_all-2.671.08-2.48*0.0-2.671.14-2.35*0.0
joint_drive_transit_ASC_auto_deficient_all-6.0416.4-0.370.0-6.0420.6-0.290.0
joint_drive_transit_ASC_auto_sufficient_all-7.7916.4-0.480.0-7.8020.6-0.380.0
joint_drive_transit_ASC_no_auto_all0.000.00NA0.00.000.00NA0.0
joint_sr2_ASC_auto_deficient_all0.000.00NA0.00.000.00NA0.0
joint_sr2_ASC_auto_sufficient_all0.000.00NA0.00.000.00NA0.0
joint_sr2_ASC_no_auto_all0.000.00NA0.00.000.00NA0.0
joint_sr3p_ASC_auto_deficient_all-1.490.258-5.77***0.0-1.510.260-5.80***0.0
joint_sr3p_ASC_auto_sufficient_all-2.290.133-17.17***0.0-2.270.131-17.25***0.0
joint_sr3p_ASC_no_auto_all0.6990.4701.490.00.6800.4711.440.0
joint_taxi_ASC_auto_deficient_all-9.828.15-1.210.0-9.828.64-1.140.0
joint_taxi_ASC_auto_sufficient_all-11.70.00NA0.0-11.70.00NA0.0
joint_taxi_ASC_no_auto_all-4.584.29-1.070.0-4.584.45-1.030.0
joint_tnc_shared_ASC_auto_deficient_all-11.217.0-0.660.0-11.218.0-0.620.0
joint_tnc_shared_ASC_auto_sufficient_all-13.20.00NA0.0-13.20.00NA0.0
joint_tnc_shared_ASC_no_auto_all-4.722.18-2.17*0.0-4.702.31-2.03*0.0
joint_tnc_single_ASC_auto_deficient_all-9.907.20-1.380.0-9.907.63-1.300.0
joint_tnc_single_ASC_auto_sufficient_all-14.00.00NA0.0-14.00.00NA0.0
joint_tnc_single_ASC_no_auto_all-3.862.05-1.880.0-3.892.20-1.770.0
joint_walk_ASC_auto_deficient_all-2.220.376-5.89***0.0-2.050.372-5.51***0.0
joint_walk_ASC_auto_sufficient_all-4.340.245-17.76***0.0-4.150.240-17.32***0.0
joint_walk_ASC_no_auto_all-0.3670.727-0.510.0-0.2940.735-0.400.0
joint_walk_transit_ASC_auto_deficient_all-5.3016.4-0.320.0-5.3020.6-0.260.0
joint_walk_transit_ASC_auto_sufficient_all-18.3655.-0.030.0-18.3620.-0.030.0
joint_walk_transit_ASC_no_auto_all0.38616.40.020.00.35120.60.020.0
local_bus_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-1.1816.4-0.070.0-0.94320.6-0.050.0
local_bus_ASC_school_univ-0.819NANA0.0-0.811NANA0.0
local_bus_ASC_work-0.179278.-0.000.0-0.211NANA0.0
sr2_ASC_auto_deficient_atwork-1.490.132-11.34***0.0-1.570.133-11.82***0.0
sr2_ASC_auto_deficient_eatout0.8740.1555.64***0.01.320.4073.25**0.0
sr2_ASC_auto_deficient_escort0.2540.1601.580.00.5600.3311.690.0
sr2_ASC_auto_deficient_othdiscr1.060.1318.13***0.01.320.3893.39***0.0
sr2_ASC_auto_deficient_othmaint0.5840.1454.02***0.01.030.3273.14**0.0
sr2_ASC_auto_deficient_school0.5180.9280.560.00.5220.9610.540.0
sr2_ASC_auto_deficient_shopping0.5220.1274.09***0.00.8010.3192.51*0.0
sr2_ASC_auto_deficient_social2.300.21510.70***0.02.420.4735.12***0.0
sr2_ASC_auto_deficient_univ-1.69NANA0.0-1.690.000112-BIG***0.0
sr2_ASC_auto_deficient_work0.4240.08924.76***0.00.2480.09002.76**0.0
sr2_ASC_auto_sufficient_atwork-0.7720.0784-9.85***0.0-0.8100.0784-10.34***0.0
sr2_ASC_auto_sufficient_eatout1.170.10511.19***0.01.630.3904.18***0.0
sr2_ASC_auto_sufficient_escort0.4270.1293.31***0.00.7540.3172.38*0.0
sr2_ASC_auto_sufficient_othdiscr0.8300.1018.23***0.01.090.3802.87**0.0
sr2_ASC_auto_sufficient_othmaint0.6420.1036.24***0.01.090.3123.51***0.0
sr2_ASC_auto_sufficient_school-0.7200.916-0.790.0-0.7200.950-0.760.0
sr2_ASC_auto_sufficient_shopping0.5180.1005.16***0.00.8060.3102.60**0.0
sr2_ASC_auto_sufficient_social0.8670.1107.88***0.01.070.4382.43*0.0
sr2_ASC_auto_sufficient_univ-1.86NANA0.0-1.866.12e-05-BIG***0.0
sr2_ASC_auto_sufficient_work-0.2950.0860-3.43***0.0-0.4780.0868-5.50***0.0
sr2_ASC_no_auto_all1.2275.90.020.01.1787.20.010.0
sr3p_ASC_auto_deficient_atwork-1.810.136-13.30***0.0-1.880.137-13.71***0.0
sr3p_ASC_auto_deficient_eatout0.1840.1870.980.00.6380.4201.520.0
sr3p_ASC_auto_deficient_escort0.03000.1630.180.00.3360.3321.010.0
sr3p_ASC_auto_deficient_othdiscr1.420.12411.40***0.01.670.3874.32***0.0
sr3p_ASC_auto_deficient_othmaint-0.6070.223-2.71**0.0-0.2020.371-0.550.0
sr3p_ASC_auto_deficient_school1.100.9271.180.01.090.9611.140.0
sr3p_ASC_auto_deficient_shopping0.1800.1381.310.00.4570.3241.410.0
sr3p_ASC_auto_deficient_social2.040.2239.16***0.02.160.4764.52***0.0
sr3p_ASC_auto_deficient_univ-1.731.83e-05-BIG***0.0-1.73NANA0.0
sr3p_ASC_auto_deficient_work-0.1270.0922-1.380.0-0.2890.0929-3.11**0.0
sr3p_ASC_auto_sufficient_atwork-0.9540.0797-11.97***0.0-1.000.0798-12.59***0.0
sr3p_ASC_auto_sufficient_eatout1.130.10510.73***0.01.580.3904.04***0.0
sr3p_ASC_auto_sufficient_escort0.4000.1293.10**0.00.7290.3172.30*0.0
sr3p_ASC_auto_sufficient_othdiscr0.9290.1019.25***0.01.180.3803.12**0.0
sr3p_ASC_auto_sufficient_othmaint0.2570.1052.44*0.00.7260.3132.32*0.0
sr3p_ASC_auto_sufficient_school-0.1510.916-0.160.0-0.1510.950-0.160.0
sr3p_ASC_auto_sufficient_shopping0.2750.1012.72**0.00.5610.3101.810.0
sr3p_ASC_auto_sufficient_social0.8700.1107.91***0.01.070.4382.45*0.0
sr3p_ASC_auto_sufficient_univ-1.902.57e-05-BIG***0.0-1.901.95e-05-BIG***0.0
sr3p_ASC_auto_sufficient_work-0.6620.0868-7.63***0.0-0.8490.0876-9.68***0.0
sr3p_ASC_no_auto_atwork1.4975.90.020.01.6787.20.020.0
sr3p_ASC_no_auto_eatout1.6275.90.020.01.5387.20.020.0
sr3p_ASC_no_auto_escort-1.8775.9-0.020.0-1.8787.3-0.020.0
sr3p_ASC_no_auto_othdiscr1.4375.90.020.01.4087.20.020.0
sr3p_ASC_no_auto_othmaint0.29675.90.000.00.19587.20.000.0
sr3p_ASC_no_auto_school-6.02105.-0.060.0-6.02112.-0.050.0
sr3p_ASC_no_auto_shopping0.88175.90.010.00.84787.20.010.0
sr3p_ASC_no_auto_social-1.1775.9-0.020.0-1.2187.2-0.010.0
sr3p_ASC_no_auto_univ-6.061.79e-05-BIG***0.0-6.065.30e-05-BIG***0.0
sr3p_ASC_no_auto_work0.61475.90.010.00.52387.20.010.0
taxi_ASC_auto_deficient_atwork-4.590.435-10.57***0.0-4.750.459-10.34***0.0
taxi_ASC_auto_deficient_eatout_othdiscr_social-3.260.483-6.76***0.0-3.160.647-4.89***0.0
taxi_ASC_auto_deficient_escort_othmaint_shopping-0.9300.118-7.89***0.0-0.5030.313-1.600.0
taxi_ASC_auto_deficient_school0.8400.9350.900.00.8990.9680.930.0
taxi_ASC_auto_deficient_univ4.251.62e-05BIG***0.04.254.12e-06BIG***0.0
taxi_ASC_auto_deficient_work-2.040.205-9.95***0.0-2.300.226-10.19***0.0
taxi_ASC_auto_sufficient_atwork-3.340.150-22.22***0.0-3.310.148-22.34***0.0
taxi_ASC_auto_sufficient_eatout_othdiscr_social-3.930.246-15.96***0.0-3.470.416-8.35***0.0
taxi_ASC_auto_sufficient_escort_othmaint_shopping-2.780.0965-28.85***0.0-2.330.306-7.60***0.0
taxi_ASC_auto_sufficient_school-2.260.922-2.45*0.0-2.230.956-2.33*0.0
taxi_ASC_auto_sufficient_univ-0.313NANA0.0-0.313NANA0.0
taxi_ASC_auto_sufficient_work-4.850.303-16.01***0.0-5.140.361-14.22***0.0
taxi_ASC_no_auto_atwork3.6575.90.050.03.6387.20.040.0
taxi_ASC_no_auto_eatout_othdiscr_social-0.57175.9-0.010.0-0.46087.2-0.010.0
taxi_ASC_no_auto_escort_othmaint_shopping1.4575.90.020.01.5487.20.020.0
taxi_ASC_no_auto_school_univ-7.000.00NA0.0-7.000.00NA0.0
taxi_ASC_no_auto_work3.9475.90.050.03.8987.20.040.0
tnc_shared_ASC_auto_deficient_atwork-5.170.414-12.49***0.0-5.210.410-12.71***0.0
tnc_shared_ASC_auto_deficient_eatout_othdiscr_social-4.460.900-4.95***0.0-4.431.17-3.78***0.0
tnc_shared_ASC_auto_deficient_escort_othmaint_shopping-1.240.109-11.36***0.0-0.7960.310-2.57*0.0
tnc_shared_ASC_auto_deficient_school0.2830.9330.300.00.3120.9660.320.0
tnc_shared_ASC_auto_deficient_univ3.251.25e-05BIG***0.03.25NANA0.0
tnc_shared_ASC_auto_deficient_work-3.400.214-15.89***0.0-3.730.231-16.16***0.0
tnc_shared_ASC_auto_sufficient_atwork-4.080.166-24.64***0.0-4.090.167-24.51***0.0
tnc_shared_ASC_auto_sufficient_eatout_othdiscr_social-4.320.199-21.67***0.0-3.880.393-9.86***0.0
tnc_shared_ASC_auto_sufficient_escort_othmaint_shopping-3.290.0920-35.76***0.0-2.830.305-9.30***0.0
tnc_shared_ASC_auto_sufficient_school-3.620.927-3.91***0.0-3.620.961-3.77***0.0
tnc_shared_ASC_auto_sufficient_univ-0.907NANA0.0-0.907NANA0.0
tnc_shared_ASC_auto_sufficient_work-6.480.411-15.77***0.0-6.740.419-16.11***0.0
tnc_shared_ASC_no_auto_atwork3.0675.90.040.03.0487.20.030.0
tnc_shared_ASC_no_auto_eatout_othdiscr_social-0.080375.9-0.000.0-0.00052987.2-0.000.0
tnc_shared_ASC_no_auto_escort_othmaint_shopping0.68575.90.010.00.77687.20.010.0
tnc_shared_ASC_no_auto_school-7.000.00NA0.0-7.000.00NA0.0
tnc_shared_ASC_no_auto_univ-5.81NANA0.0-5.81NANA0.0
tnc_shared_ASC_no_auto_work2.2375.90.030.02.2187.20.030.0
tnc_single_ASC_auto_deficient_atwork-4.240.319-13.29***0.0-4.360.331-13.19***0.0
tnc_single_ASC_auto_deficient_eatout_othdiscr_social-3.270.436-7.50***0.0-3.120.599-5.21***0.0
tnc_single_ASC_auto_deficient_escort_othmaint_shopping-0.3400.102-3.34***0.00.09280.3080.300.0
tnc_single_ASC_auto_deficient_school-0.01370.943-0.010.00.05970.9750.060.0
tnc_single_ASC_auto_deficient_univ1.02NANA0.01.022.45e-06BIG***0.0
tnc_single_ASC_auto_deficient_work-1.300.115-11.28***0.0-1.470.118-12.49***0.0
tnc_single_ASC_auto_sufficient_atwork-3.140.126-25.00***0.0-3.140.125-25.04***0.0
tnc_single_ASC_auto_sufficient_eatout_othdiscr_social-3.260.149-21.84***0.0-2.830.371-7.62***0.0
tnc_single_ASC_auto_sufficient_escort_othmaint_shopping-2.200.0833-26.43***0.0-1.760.302-5.81***0.0
tnc_single_ASC_auto_sufficient_school-2.070.920-2.25*0.0-2.020.953-2.12*0.0
tnc_single_ASC_auto_sufficient_univ0.2095.09e-06BIG***0.00.2092.79e-06BIG***0.0
tnc_single_ASC_auto_sufficient_work-4.240.182-23.29***0.0-4.330.179-24.13***0.0
tnc_single_ASC_no_auto_atwork4.2675.90.060.04.2487.20.050.0
tnc_single_ASC_no_auto_eatout_othdiscr_social0.98275.90.010.01.0687.20.010.0
tnc_single_ASC_no_auto_escort_othmaint_shopping1.6075.90.020.01.7087.20.020.0
tnc_single_ASC_no_auto_school-7.000.00NA0.0-7.000.00NA0.0
tnc_single_ASC_no_auto_univ-2.52NANA0.0-2.525.36e-06-BIG***0.0
tnc_single_ASC_no_auto_work5.3175.90.070.05.3187.20.060.0
walk_ASC_auto_deficient_atwork0.2270.1231.840.00.1750.1241.410.0
walk_ASC_auto_deficient_eatout2.170.19810.96***0.02.700.4256.37***0.0
walk_ASC_auto_deficient_escort-1.980.265-7.46***0.0-1.600.396-4.04***0.0
walk_ASC_auto_deficient_othdiscr1.210.1547.86***0.01.570.3983.94***0.0
walk_ASC_auto_deficient_othmaint0.1450.2080.700.00.6430.3601.790.0
walk_ASC_auto_deficient_school2.610.9312.81**0.02.650.9642.75**0.0
walk_ASC_auto_deficient_shopping0.9090.1376.63***0.01.310.3234.06***0.0
walk_ASC_auto_deficient_social2.260.2997.56***0.02.480.5164.82***0.0
walk_ASC_auto_deficient_univ4.511.92e-06BIG***0.04.51NANA0.0
walk_ASC_auto_deficient_work1.700.095517.84***0.01.590.096216.52***0.0
walk_ASC_auto_sufficient_atwork0.07760.05801.340.00.07860.05791.360.0
walk_ASC_auto_sufficient_eatout0.6130.1065.78***0.01.190.3913.04**0.0
walk_ASC_auto_sufficient_escort-1.740.117-14.88***0.0-1.320.313-4.20***0.0
walk_ASC_auto_sufficient_othdiscr0.3050.08293.68***0.00.6610.3761.760.0
walk_ASC_auto_sufficient_othmaint-0.1680.0955-1.760.00.4390.3101.420.0
walk_ASC_auto_sufficient_school0.3740.9170.410.00.3830.9510.400.0
walk_ASC_auto_sufficient_shopping-0.3040.0811-3.75***0.00.08180.3050.270.0
walk_ASC_auto_sufficient_social0.5920.1175.04***0.00.9110.4392.08*0.0
walk_ASC_auto_sufficient_univ1.06NANA0.01.061.94e-07BIG***0.0
walk_ASC_auto_sufficient_work-0.2910.0787-3.70***0.0-0.4170.0795-5.25***0.0
walk_ASC_no_auto_atwork6.6375.90.090.06.6187.20.080.0
walk_ASC_no_auto_eatout4.4175.90.060.04.5287.20.050.0
walk_ASC_no_auto_escort2.5175.90.030.02.5687.20.030.0
walk_ASC_no_auto_othdiscr2.8975.90.040.02.9687.20.030.0
walk_ASC_no_auto_othmaint0.93075.90.010.01.0687.20.010.0
walk_ASC_no_auto_school17.8109.0.160.017.8116.0.150.0
walk_ASC_no_auto_shopping2.1775.90.030.02.2687.20.030.0
walk_ASC_no_auto_social1.7475.90.020.01.8487.20.020.0
walk_ASC_no_auto_univ6.41NANA0.06.413.50e-09BIG***0.0
walk_ASC_no_auto_work5.2875.90.070.05.2887.20.060.0
walk_ferry_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.23916.4-0.010.0-0.034720.6-0.000.0
walk_ferry_ASC_school_univ0.858NANA0.00.903NANA0.0
walk_ferry_ASC_work0.189278.0.000.00.0751NANA0.0
walk_light_rail_ASC_eatout_escort_othdiscr_othmaint_shopping_social_atwork-0.13616.4-0.010.00.11520.60.010.0
walk_light_rail_ASC_school_univ0.724NANA0.00.721NANA0.0
walk_light_rail_ASC_work0.786278.0.000.00.730NANA0.0
walk_transit_ASC_auto_deficient_atwork-2.6316.4-0.160.0-2.8420.6-0.140.0
walk_transit_ASC_auto_deficient_eatout-0.48916.4-0.030.0-0.20520.6-0.010.0
walk_transit_ASC_auto_deficient_escort-4.4516.4-0.270.0-4.4620.6-0.220.0
walk_transit_ASC_auto_deficient_othdiscr0.87316.40.050.00.99720.60.050.0
walk_transit_ASC_auto_deficient_othmaint-2.9716.4-0.180.0-2.9120.6-0.140.0
walk_transit_ASC_auto_deficient_school2.97NANA0.03.00NANA0.0
walk_transit_ASC_auto_deficient_shopping-1.0716.4-0.070.0-0.89920.6-0.040.0
walk_transit_ASC_auto_deficient_social1.3216.40.080.01.3220.60.060.0
walk_transit_ASC_auto_deficient_univ3.140.00NA0.03.140.00NA0.0
walk_transit_ASC_auto_deficient_work0.159278.0.000.00.0663NANA0.0
walk_transit_ASC_auto_sufficient_atwork-3.6616.4-0.220.0-3.7620.6-0.180.0
walk_transit_ASC_auto_sufficient_eatout-1.3216.4-0.080.0-0.98520.6-0.050.0
walk_transit_ASC_auto_sufficient_escort-4.8216.4-0.290.0-4.6820.6-0.230.0
walk_transit_ASC_auto_sufficient_othdiscr-0.91416.4-0.060.0-0.77120.6-0.040.0
walk_transit_ASC_auto_sufficient_othmaint-1.6816.4-0.100.0-1.3120.6-0.060.0
walk_transit_ASC_auto_sufficient_school0.487NANA0.00.522NANA0.0
walk_transit_ASC_auto_sufficient_shopping-2.3516.4-0.140.0-2.2020.6-0.110.0
walk_transit_ASC_auto_sufficient_social-0.64716.4-0.040.0-0.59520.6-0.030.0
walk_transit_ASC_auto_sufficient_univ0.4730.00NA0.00.4730.00NA0.0
walk_transit_ASC_auto_sufficient_work-1.37278.-0.000.0-1.47NANA0.0
walk_transit_ASC_no_auto_atwork3.1366.90.050.02.9873.60.040.0
walk_transit_ASC_no_auto_eatout2.9266.90.040.02.7673.60.040.0
walk_transit_ASC_no_auto_escort-2.2667.0-0.030.0-2.2673.7-0.030.0
walk_transit_ASC_no_auto_othdiscr2.8066.90.040.02.6473.60.040.0
walk_transit_ASC_no_auto_othmaint2.5966.90.040.02.4373.60.030.0
walk_transit_ASC_no_auto_school20.4NANA0.020.5NANA0.0
walk_transit_ASC_no_auto_shopping2.3366.90.030.02.1873.60.030.0
walk_transit_ASC_no_auto_social2.0666.90.030.01.9073.60.030.0
walk_transit_ASC_no_auto_univ8.790.00NA0.08.790.00NA0.0
walk_transit_ASC_no_auto_work4.60285.0.020.04.63NANA0.0
walk_transit_CBD_ASC_atwork1.300.2844.57***0.01.180.2774.28***0.0
walk_transit_CBD_ASC_eatout_escort_othdiscr_othmaint_shopping_social1.080.075714.25***0.01.090.075614.41***0.0
walk_transit_CBD_ASC_school_univ0.8340.1147.30***0.00.8260.1147.24***0.0
walk_transit_CBD_ASC_work1.160.053921.50***0.01.150.053921.27***0.0
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: eatout, dtype: object0.3400.1901.780.0
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: escort, dtype: object0.00NANA0.0
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: othdiscr, dtype: object0.2310.1851.240.0
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: othmaint, dtype: object0.3330.1502.22*0.0
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: shopping, dtype: object0.2450.1491.640.0
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: social, dtype: object0.1970.2140.920.0
coefficient_name\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\ncoef_test coef_test_eatout_escort_othdiscr_othmaint_shop...\\nName: work, dtype: object-0.03060.0255-1.200.0
coefficient_name\\ncoef_test coef_test_school_univ\\ncoef_test coef_test_school_univ\\nName: school, dtype: object0.2780.4740.590.0
coefficient_name\\ncoef_test coef_test_school_univ\\ncoef_test coef_test_school_univ\\nName: univ, dtype: object0.00NANA0.0
\n", + "
" + ], + "text/plain": [ + " model \\\n", + " Value Std Err \n", + "Parameter \n", + "-999 -999.  0.00 \n", + "1  1.00  0.00 \n", + "bike_ASC_auto_deficient_atwork -1.05  0.344 \n", + "bike_ASC_auto_deficient_eatout -1.46  0.396 \n", + "bike_ASC_auto_deficient_escort -3.98  0.406 \n", + "bike_ASC_auto_deficient_othdiscr -0.910  0.203 \n", + "bike_ASC_auto_deficient_othmaint -2.06  0.323 \n", + "bike_ASC_auto_deficient_school -1.20  0.964 \n", + "bike_ASC_auto_deficient_shopping -1.74  0.218 \n", + "bike_ASC_auto_deficient_social  0.361  0.325 \n", + "bike_ASC_auto_deficient_univ -0.669  NA \n", + "bike_ASC_auto_deficient_work -0.279  0.0926 \n", + "bike_ASC_auto_sufficient_atwork  15.7  470. \n", + "bike_ASC_auto_sufficient_eatout -1.85  0.159 \n", + "bike_ASC_auto_sufficient_escort -5.65  0.337 \n", + "bike_ASC_auto_sufficient_othdiscr -1.86  0.105 \n", + "bike_ASC_auto_sufficient_othmaint -3.17  0.193 \n", + "bike_ASC_auto_sufficient_school -2.21  0.919 \n", + "bike_ASC_auto_sufficient_shopping -3.14  0.138 \n", + "bike_ASC_auto_sufficient_social -2.14  0.207 \n", + "bike_ASC_auto_sufficient_univ -1.94  0.00657 \n", + "bike_ASC_auto_sufficient_work -1.93  0.0814 \n", + "bike_ASC_no_auto_atwork -0.910  76.5 \n", + "bike_ASC_no_auto_eatout  0.428  75.9 \n", + "bike_ASC_no_auto_escort -0.745  75.9 \n", + "bike_ASC_no_auto_othdiscr -0.501  75.9 \n", + "bike_ASC_no_auto_othmaint  1.53  75.9 \n", + "bike_ASC_no_auto_school  13.5  109. \n", + "bike_ASC_no_auto_shopping  0.951  75.9 \n", + "bike_ASC_no_auto_social  0.374  75.9 \n", + "bike_ASC_no_auto_univ  4.29  0.00148 \n", + "bike_ASC_no_auto_work  3.43  75.9 \n", + "coef_age010_trn_multiplier_atwork  0.000722  0.00785 \n", + "coef_age010_trn_multiplier_eatout_escort_othdis...  0.490  0.176 \n", + "coef_age010_trn_multiplier_school_univ -0.851  0.0900 \n", + "coef_age1619_da_multiplier_atwork -0.175  0.205 \n", + "coef_age1619_da_multiplier_eatout_escort_othdis...  0.0357  0.0425 \n", + "coef_age1619_da_multiplier_school_univ -1.67  0.0748 \n", + "coef_age16p_sr_multiplier_eatout_escort_othdisc... -1.58  0.0842 \n", + "coef_age16p_sr_multiplier_school_univ_work_atwork -0.688  0.0682 \n", + "coef_hhsize1_sr_multiplier_eatout_escort_othdis... -0.0721  0.0312 \n", + "coef_hhsize1_sr_multiplier_work -0.822  0.0571 \n", + "coef_hhsize2_sr_multiplier_eatout_escort_othdis... -0.00404  0.0178 \n", + "coef_hhsize2_sr_multiplier_school_univ -0.743  0.0912 \n", + "coef_ivt_atwork -0.0112  0.000479 \n", + "coef_ivt_eatout_escort_othdiscr_othmaint_shoppi... -0.00691  0.000145 \n", + "coef_ivt_school_univ -0.0103  0.000316 \n", + "coef_ivt_work -0.00791  0.000147 \n", + "coef_nest_AUTO  0.720  0.00 \n", + "coef_nest_AUTO_DRIVEALONE  0.350  0.00 \n", + "coef_nest_AUTO_SHAREDRIDE2  0.350  0.00 \n", + "coef_nest_AUTO_SHAREDRIDE3  0.350  0.00 \n", + "coef_nest_NONMOTORIZED  0.720  0.00 \n", + "coef_nest_RIDEHAIL  0.360  0.00 \n", + "coef_nest_TRANSIT  0.720  0.00 \n", + "coef_nest_TRANSIT_DRIVEACCESS  0.500  0.00 \n", + "coef_nest_TRANSIT_WALKACCESS  0.500  0.00 \n", + "coef_test_eatout_escort_othdiscr_othmaint_shopp...  0.0770  0.0494 \n", + "coef_test_school_univ  0.518  0.913 \n", + "commuter_rail_ASC_eatout_escort_othdiscr_othmai... -0.958  16.4 \n", + "commuter_rail_ASC_school_univ -0.258  NA \n", + "commuter_rail_ASC_work  0.196  278. \n", + "drive_ferry_ASC_eatout_escort_othdiscr_othmaint... -0.628  16.4 \n", + "drive_ferry_ASC_school_univ  1.43  NA \n", + "drive_ferry_ASC_work  0.232  278. \n", + "drive_light_rail_ASC_eatout_escort_othdiscr_oth... -0.325  16.4 \n", + "drive_light_rail_ASC_school_univ  0.691  NA \n", + "drive_light_rail_ASC_work  0.530  278. \n", + "drive_transit_ASC_auto_deficient_atwork -999.  0.000360 \n", + "drive_transit_ASC_auto_deficient_eatout -0.173  16.4 \n", + "drive_transit_ASC_auto_deficient_escort -2.19  16.4 \n", + "drive_transit_ASC_auto_deficient_othdiscr -0.852  16.4 \n", + "drive_transit_ASC_auto_deficient_othmaint -1.36  16.4 \n", + "drive_transit_ASC_auto_deficient_school  1.59  NA \n", + "drive_transit_ASC_auto_deficient_shopping -1.58  16.4 \n", + "drive_transit_ASC_auto_deficient_social  0.610  16.4 \n", + "drive_transit_ASC_auto_deficient_univ  1.85  NA \n", + "drive_transit_ASC_auto_deficient_work -0.824  278. \n", + "drive_transit_ASC_auto_sufficient_atwork -999.  0.000176 \n", + "drive_transit_ASC_auto_sufficient_eatout -1.65  16.4 \n", + "drive_transit_ASC_auto_sufficient_escort -5.31  16.4 \n", + "drive_transit_ASC_auto_sufficient_othdiscr -1.24  16.4 \n", + "drive_transit_ASC_auto_sufficient_othmaint -2.80  16.4 \n", + "drive_transit_ASC_auto_sufficient_school  0.105  NA \n", + "drive_transit_ASC_auto_sufficient_shopping -4.16  16.4 \n", + "drive_transit_ASC_auto_sufficient_social -1.37  16.4 \n", + "drive_transit_ASC_auto_sufficient_univ  1.36  NA \n", + "drive_transit_ASC_auto_sufficient_work -1.73  278. \n", + "drive_transit_ASC_no_auto_all  0.00  NA \n", + "drive_transit_CBD_ASC_atwork  0.564  NA \n", + "drive_transit_CBD_ASC_eatout_escort_othdiscr_ot...  1.37  0.142 \n", + "drive_transit_CBD_ASC_school_univ  1.23  0.251 \n", + "drive_transit_CBD_ASC_work  1.64  0.0698 \n", + "express_bus_ASC_eatout_escort_othdiscr_othmaint... -0.342  16.4 \n", + "express_bus_ASC_school_univ -0.451  NA \n", + "express_bus_ASC_work -0.881  278. \n", + "heavy_rail_ASC_eatout_escort_othdiscr_othmaint_... -0.207  16.4 \n", + "heavy_rail_ASC_school_univ  0.110  NA \n", + "heavy_rail_ASC_work  0.513  278. \n", + "joint_bike_ASC_auto_deficient_all -6.18  1.34 \n", + "joint_bike_ASC_auto_sufficient_all -7.10  0.465 \n", + "joint_bike_ASC_no_auto_all -2.67  1.08 \n", + "joint_drive_transit_ASC_auto_deficient_all -6.04  16.4 \n", + "joint_drive_transit_ASC_auto_sufficient_all -7.79  16.4 \n", + "joint_drive_transit_ASC_no_auto_all  0.00  0.00 \n", + "joint_sr2_ASC_auto_deficient_all  0.00  0.00 \n", + "joint_sr2_ASC_auto_sufficient_all  0.00  0.00 \n", + "joint_sr2_ASC_no_auto_all  0.00  0.00 \n", + "joint_sr3p_ASC_auto_deficient_all -1.49  0.258 \n", + "joint_sr3p_ASC_auto_sufficient_all -2.29  0.133 \n", + "joint_sr3p_ASC_no_auto_all  0.699  0.470 \n", + "joint_taxi_ASC_auto_deficient_all -9.82  8.15 \n", + "joint_taxi_ASC_auto_sufficient_all -11.7  0.00 \n", + "joint_taxi_ASC_no_auto_all -4.58  4.29 \n", + "joint_tnc_shared_ASC_auto_deficient_all -11.2  17.0 \n", + "joint_tnc_shared_ASC_auto_sufficient_all -13.2  0.00 \n", + "joint_tnc_shared_ASC_no_auto_all -4.72  2.18 \n", + "joint_tnc_single_ASC_auto_deficient_all -9.90  7.20 \n", + "joint_tnc_single_ASC_auto_sufficient_all -14.0  0.00 \n", + "joint_tnc_single_ASC_no_auto_all -3.86  2.05 \n", + "joint_walk_ASC_auto_deficient_all -2.22  0.376 \n", + "joint_walk_ASC_auto_sufficient_all -4.34  0.245 \n", + "joint_walk_ASC_no_auto_all -0.367  0.727 \n", + "joint_walk_transit_ASC_auto_deficient_all -5.30  16.4 \n", + "joint_walk_transit_ASC_auto_sufficient_all -18.3  655. \n", + "joint_walk_transit_ASC_no_auto_all  0.386  16.4 \n", + "local_bus_ASC_eatout_escort_othdiscr_othmaint_s... -1.18  16.4 \n", + "local_bus_ASC_school_univ -0.819  NA \n", + "local_bus_ASC_work -0.179  278. \n", + "sr2_ASC_auto_deficient_atwork -1.49  0.132 \n", + "sr2_ASC_auto_deficient_eatout  0.874  0.155 \n", + "sr2_ASC_auto_deficient_escort  0.254  0.160 \n", + "sr2_ASC_auto_deficient_othdiscr  1.06  0.131 \n", + "sr2_ASC_auto_deficient_othmaint  0.584  0.145 \n", + "sr2_ASC_auto_deficient_school  0.518  0.928 \n", + "sr2_ASC_auto_deficient_shopping  0.522  0.127 \n", + "sr2_ASC_auto_deficient_social  2.30  0.215 \n", + "sr2_ASC_auto_deficient_univ -1.69  NA \n", + "sr2_ASC_auto_deficient_work  0.424  0.0892 \n", + "sr2_ASC_auto_sufficient_atwork -0.772  0.0784 \n", + "sr2_ASC_auto_sufficient_eatout  1.17  0.105 \n", + "sr2_ASC_auto_sufficient_escort  0.427  0.129 \n", + "sr2_ASC_auto_sufficient_othdiscr  0.830  0.101 \n", + "sr2_ASC_auto_sufficient_othmaint  0.642  0.103 \n", + "sr2_ASC_auto_sufficient_school -0.720  0.916 \n", + "sr2_ASC_auto_sufficient_shopping  0.518  0.100 \n", + "sr2_ASC_auto_sufficient_social  0.867  0.110 \n", + "sr2_ASC_auto_sufficient_univ -1.86  NA \n", + "sr2_ASC_auto_sufficient_work -0.295  0.0860 \n", + "sr2_ASC_no_auto_all  1.22  75.9 \n", + "sr3p_ASC_auto_deficient_atwork -1.81  0.136 \n", + "sr3p_ASC_auto_deficient_eatout  0.184  0.187 \n", + "sr3p_ASC_auto_deficient_escort  0.0300  0.163 \n", + "sr3p_ASC_auto_deficient_othdiscr  1.42  0.124 \n", + "sr3p_ASC_auto_deficient_othmaint -0.607  0.223 \n", + "sr3p_ASC_auto_deficient_school  1.10  0.927 \n", + "sr3p_ASC_auto_deficient_shopping  0.180  0.138 \n", + "sr3p_ASC_auto_deficient_social  2.04  0.223 \n", + "sr3p_ASC_auto_deficient_univ -1.73  1.83e-05 \n", + "sr3p_ASC_auto_deficient_work -0.127  0.0922 \n", + "sr3p_ASC_auto_sufficient_atwork -0.954  0.0797 \n", + "sr3p_ASC_auto_sufficient_eatout  1.13  0.105 \n", + "sr3p_ASC_auto_sufficient_escort  0.400  0.129 \n", + "sr3p_ASC_auto_sufficient_othdiscr  0.929  0.101 \n", + "sr3p_ASC_auto_sufficient_othmaint  0.257  0.105 \n", + "sr3p_ASC_auto_sufficient_school -0.151  0.916 \n", + "sr3p_ASC_auto_sufficient_shopping  0.275  0.101 \n", + "sr3p_ASC_auto_sufficient_social  0.870  0.110 \n", + "sr3p_ASC_auto_sufficient_univ -1.90  2.57e-05 \n", + "sr3p_ASC_auto_sufficient_work -0.662  0.0868 \n", + "sr3p_ASC_no_auto_atwork  1.49  75.9 \n", + "sr3p_ASC_no_auto_eatout  1.62  75.9 \n", + "sr3p_ASC_no_auto_escort -1.87  75.9 \n", + "sr3p_ASC_no_auto_othdiscr  1.43  75.9 \n", + "sr3p_ASC_no_auto_othmaint  0.296  75.9 \n", + "sr3p_ASC_no_auto_school -6.02  105. \n", + "sr3p_ASC_no_auto_shopping  0.881  75.9 \n", + "sr3p_ASC_no_auto_social -1.17  75.9 \n", + "sr3p_ASC_no_auto_univ -6.06  1.79e-05 \n", + "sr3p_ASC_no_auto_work  0.614  75.9 \n", + "taxi_ASC_auto_deficient_atwork -4.59  0.435 \n", + "taxi_ASC_auto_deficient_eatout_othdiscr_social -3.26  0.483 \n", + "taxi_ASC_auto_deficient_escort_othmaint_shopping -0.930  0.118 \n", + "taxi_ASC_auto_deficient_school  0.840  0.935 \n", + "taxi_ASC_auto_deficient_univ  4.25  1.62e-05 \n", + "taxi_ASC_auto_deficient_work -2.04  0.205 \n", + "taxi_ASC_auto_sufficient_atwork -3.34  0.150 \n", + "taxi_ASC_auto_sufficient_eatout_othdiscr_social -3.93  0.246 \n", + "taxi_ASC_auto_sufficient_escort_othmaint_shopping -2.78  0.0965 \n", + "taxi_ASC_auto_sufficient_school -2.26  0.922 \n", + "taxi_ASC_auto_sufficient_univ -0.313  NA \n", + "taxi_ASC_auto_sufficient_work -4.85  0.303 \n", + "taxi_ASC_no_auto_atwork  3.65  75.9 \n", + "taxi_ASC_no_auto_eatout_othdiscr_social -0.571  75.9 \n", + "taxi_ASC_no_auto_escort_othmaint_shopping  1.45  75.9 \n", + "taxi_ASC_no_auto_school_univ -7.00  0.00 \n", + "taxi_ASC_no_auto_work  3.94  75.9 \n", + "tnc_shared_ASC_auto_deficient_atwork -5.17  0.414 \n", + "tnc_shared_ASC_auto_deficient_eatout_othdiscr_s... -4.46  0.900 \n", + "tnc_shared_ASC_auto_deficient_escort_othmaint_s... -1.24  0.109 \n", + "tnc_shared_ASC_auto_deficient_school  0.283  0.933 \n", + "tnc_shared_ASC_auto_deficient_univ  3.25  1.25e-05 \n", + "tnc_shared_ASC_auto_deficient_work -3.40  0.214 \n", + "tnc_shared_ASC_auto_sufficient_atwork -4.08  0.166 \n", + "tnc_shared_ASC_auto_sufficient_eatout_othdiscr_... -4.32  0.199 \n", + "tnc_shared_ASC_auto_sufficient_escort_othmaint_... -3.29  0.0920 \n", + "tnc_shared_ASC_auto_sufficient_school -3.62  0.927 \n", + "tnc_shared_ASC_auto_sufficient_univ -0.907  NA \n", + "tnc_shared_ASC_auto_sufficient_work -6.48  0.411 \n", + "tnc_shared_ASC_no_auto_atwork  3.06  75.9 \n", + "tnc_shared_ASC_no_auto_eatout_othdiscr_social -0.0803  75.9 \n", + "tnc_shared_ASC_no_auto_escort_othmaint_shopping  0.685  75.9 \n", + "tnc_shared_ASC_no_auto_school -7.00  0.00 \n", + "tnc_shared_ASC_no_auto_univ -5.81  NA \n", + "tnc_shared_ASC_no_auto_work  2.23  75.9 \n", + "tnc_single_ASC_auto_deficient_atwork -4.24  0.319 \n", + "tnc_single_ASC_auto_deficient_eatout_othdiscr_s... -3.27  0.436 \n", + "tnc_single_ASC_auto_deficient_escort_othmaint_s... -0.340  0.102 \n", + "tnc_single_ASC_auto_deficient_school -0.0137  0.943 \n", + "tnc_single_ASC_auto_deficient_univ  1.02  NA \n", + "tnc_single_ASC_auto_deficient_work -1.30  0.115 \n", + "tnc_single_ASC_auto_sufficient_atwork -3.14  0.126 \n", + "tnc_single_ASC_auto_sufficient_eatout_othdiscr_... -3.26  0.149 \n", + "tnc_single_ASC_auto_sufficient_escort_othmaint_... -2.20  0.0833 \n", + "tnc_single_ASC_auto_sufficient_school -2.07  0.920 \n", + "tnc_single_ASC_auto_sufficient_univ  0.209  5.09e-06 \n", + "tnc_single_ASC_auto_sufficient_work -4.24  0.182 \n", + "tnc_single_ASC_no_auto_atwork  4.26  75.9 \n", + "tnc_single_ASC_no_auto_eatout_othdiscr_social  0.982  75.9 \n", + "tnc_single_ASC_no_auto_escort_othmaint_shopping  1.60  75.9 \n", + "tnc_single_ASC_no_auto_school -7.00  0.00 \n", + "tnc_single_ASC_no_auto_univ -2.52  NA \n", + "tnc_single_ASC_no_auto_work  5.31  75.9 \n", + "walk_ASC_auto_deficient_atwork  0.227  0.123 \n", + "walk_ASC_auto_deficient_eatout  2.17  0.198 \n", + "walk_ASC_auto_deficient_escort -1.98  0.265 \n", + "walk_ASC_auto_deficient_othdiscr  1.21  0.154 \n", + "walk_ASC_auto_deficient_othmaint  0.145  0.208 \n", + "walk_ASC_auto_deficient_school  2.61  0.931 \n", + "walk_ASC_auto_deficient_shopping  0.909  0.137 \n", + "walk_ASC_auto_deficient_social  2.26  0.299 \n", + "walk_ASC_auto_deficient_univ  4.51  1.92e-06 \n", + "walk_ASC_auto_deficient_work  1.70  0.0955 \n", + "walk_ASC_auto_sufficient_atwork  0.0776  0.0580 \n", + "walk_ASC_auto_sufficient_eatout  0.613  0.106 \n", + "walk_ASC_auto_sufficient_escort -1.74  0.117 \n", + "walk_ASC_auto_sufficient_othdiscr  0.305  0.0829 \n", + "walk_ASC_auto_sufficient_othmaint -0.168  0.0955 \n", + "walk_ASC_auto_sufficient_school  0.374  0.917 \n", + "walk_ASC_auto_sufficient_shopping -0.304  0.0811 \n", + "walk_ASC_auto_sufficient_social  0.592  0.117 \n", + "walk_ASC_auto_sufficient_univ  1.06  NA \n", + "walk_ASC_auto_sufficient_work -0.291  0.0787 \n", + "walk_ASC_no_auto_atwork  6.63  75.9 \n", + "walk_ASC_no_auto_eatout  4.41  75.9 \n", + "walk_ASC_no_auto_escort  2.51  75.9 \n", + "walk_ASC_no_auto_othdiscr  2.89  75.9 \n", + "walk_ASC_no_auto_othmaint  0.930  75.9 \n", + "walk_ASC_no_auto_school  17.8  109. \n", + "walk_ASC_no_auto_shopping  2.17  75.9 \n", + "walk_ASC_no_auto_social  1.74  75.9 \n", + "walk_ASC_no_auto_univ  6.41  NA \n", + "walk_ASC_no_auto_work  5.28  75.9 \n", + "walk_ferry_ASC_eatout_escort_othdiscr_othmaint_... -0.239  16.4 \n", + "walk_ferry_ASC_school_univ  0.858  NA \n", + "walk_ferry_ASC_work  0.189  278. \n", + "walk_light_rail_ASC_eatout_escort_othdiscr_othm... -0.136  16.4 \n", + "walk_light_rail_ASC_school_univ  0.724  NA \n", + "walk_light_rail_ASC_work  0.786  278. \n", + "walk_transit_ASC_auto_deficient_atwork -2.63  16.4 \n", + "walk_transit_ASC_auto_deficient_eatout -0.489  16.4 \n", + "walk_transit_ASC_auto_deficient_escort -4.45  16.4 \n", + "walk_transit_ASC_auto_deficient_othdiscr  0.873  16.4 \n", + "walk_transit_ASC_auto_deficient_othmaint -2.97  16.4 \n", + "walk_transit_ASC_auto_deficient_school  2.97  NA \n", + "walk_transit_ASC_auto_deficient_shopping -1.07  16.4 \n", + "walk_transit_ASC_auto_deficient_social  1.32  16.4 \n", + "walk_transit_ASC_auto_deficient_univ  3.14  0.00 \n", + "walk_transit_ASC_auto_deficient_work  0.159  278. \n", + "walk_transit_ASC_auto_sufficient_atwork -3.66  16.4 \n", + "walk_transit_ASC_auto_sufficient_eatout -1.32  16.4 \n", + "walk_transit_ASC_auto_sufficient_escort -4.82  16.4 \n", + "walk_transit_ASC_auto_sufficient_othdiscr -0.914  16.4 \n", + "walk_transit_ASC_auto_sufficient_othmaint -1.68  16.4 \n", + "walk_transit_ASC_auto_sufficient_school  0.487  NA \n", + "walk_transit_ASC_auto_sufficient_shopping -2.35  16.4 \n", + "walk_transit_ASC_auto_sufficient_social -0.647  16.4 \n", + "walk_transit_ASC_auto_sufficient_univ  0.473  0.00 \n", + "walk_transit_ASC_auto_sufficient_work -1.37  278. \n", + "walk_transit_ASC_no_auto_atwork  3.13  66.9 \n", + "walk_transit_ASC_no_auto_eatout  2.92  66.9 \n", + "walk_transit_ASC_no_auto_escort -2.26  67.0 \n", + "walk_transit_ASC_no_auto_othdiscr  2.80  66.9 \n", + "walk_transit_ASC_no_auto_othmaint  2.59  66.9 \n", + "walk_transit_ASC_no_auto_school  20.4  NA \n", + "walk_transit_ASC_no_auto_shopping  2.33  66.9 \n", + "walk_transit_ASC_no_auto_social  2.06  66.9 \n", + "walk_transit_ASC_no_auto_univ  8.79  0.00 \n", + "walk_transit_ASC_no_auto_work  4.60  285. \n", + "walk_transit_CBD_ASC_atwork  1.30  0.284 \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth...  1.08  0.0757 \n", + "walk_transit_CBD_ASC_school_univ  0.834  0.114 \n", + "walk_transit_CBD_ASC_work  1.16  0.0539 \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_school... \n", + "coefficient_name\\ncoef_test coef_test_school... \n", + "\n", + " \\\n", + " t Stat Signif Null Value \n", + "Parameter \n", + "-999  NA 0.0 \n", + "1  NA 0.0 \n", + "bike_ASC_auto_deficient_atwork -3.07 ** 0.0 \n", + "bike_ASC_auto_deficient_eatout -3.69 *** 0.0 \n", + "bike_ASC_auto_deficient_escort -9.79 *** 0.0 \n", + "bike_ASC_auto_deficient_othdiscr -4.47 *** 0.0 \n", + "bike_ASC_auto_deficient_othmaint -6.37 *** 0.0 \n", + "bike_ASC_auto_deficient_school -1.24 0.0 \n", + "bike_ASC_auto_deficient_shopping -7.99 *** 0.0 \n", + "bike_ASC_auto_deficient_social  1.11 0.0 \n", + "bike_ASC_auto_deficient_univ  NA 0.0 \n", + "bike_ASC_auto_deficient_work -3.01 ** 0.0 \n", + "bike_ASC_auto_sufficient_atwork  0.03 0.0 \n", + "bike_ASC_auto_sufficient_eatout -11.60 *** 0.0 \n", + "bike_ASC_auto_sufficient_escort -16.76 *** 0.0 \n", + "bike_ASC_auto_sufficient_othdiscr -17.64 *** 0.0 \n", + "bike_ASC_auto_sufficient_othmaint -16.40 *** 0.0 \n", + "bike_ASC_auto_sufficient_school -2.40 * 0.0 \n", + "bike_ASC_auto_sufficient_shopping -22.70 *** 0.0 \n", + "bike_ASC_auto_sufficient_social -10.36 *** 0.0 \n", + "bike_ASC_auto_sufficient_univ -295.46 *** 0.0 \n", + "bike_ASC_auto_sufficient_work -23.72 *** 0.0 \n", + "bike_ASC_no_auto_atwork -0.01 0.0 \n", + "bike_ASC_no_auto_eatout  0.01 0.0 \n", + "bike_ASC_no_auto_escort -0.01 0.0 \n", + "bike_ASC_no_auto_othdiscr -0.01 0.0 \n", + "bike_ASC_no_auto_othmaint  0.02 0.0 \n", + "bike_ASC_no_auto_school  0.12 0.0 \n", + "bike_ASC_no_auto_shopping  0.01 0.0 \n", + "bike_ASC_no_auto_social  0.00 0.0 \n", + "bike_ASC_no_auto_univ  BIG *** 0.0 \n", + "bike_ASC_no_auto_work  0.05 0.0 \n", + "coef_age010_trn_multiplier_atwork  0.09 0.0 \n", + "coef_age010_trn_multiplier_eatout_escort_othdis...  2.79 ** 0.0 \n", + "coef_age010_trn_multiplier_school_univ -9.46 *** 0.0 \n", + "coef_age1619_da_multiplier_atwork -0.85 0.0 \n", + "coef_age1619_da_multiplier_eatout_escort_othdis...  0.84 0.0 \n", + "coef_age1619_da_multiplier_school_univ -22.31 *** 0.0 \n", + "coef_age16p_sr_multiplier_eatout_escort_othdisc... -18.71 *** 0.0 \n", + "coef_age16p_sr_multiplier_school_univ_work_atwork -10.08 *** 0.0 \n", + "coef_hhsize1_sr_multiplier_eatout_escort_othdis... -2.31 * 0.0 \n", + "coef_hhsize1_sr_multiplier_work -14.39 *** 0.0 \n", + "coef_hhsize2_sr_multiplier_eatout_escort_othdis... -0.23 0.0 \n", + "coef_hhsize2_sr_multiplier_school_univ -8.15 *** 0.0 \n", + "coef_ivt_atwork -23.41 *** 0.0 \n", + "coef_ivt_eatout_escort_othdiscr_othmaint_shoppi... -47.76 *** 0.0 \n", + "coef_ivt_school_univ -32.62 *** 0.0 \n", + "coef_ivt_work -53.62 *** 0.0 \n", + "coef_nest_AUTO  NA 1.0 \n", + "coef_nest_AUTO_DRIVEALONE  NA 1.0 \n", + "coef_nest_AUTO_SHAREDRIDE2  NA 1.0 \n", + "coef_nest_AUTO_SHAREDRIDE3  NA 1.0 \n", + "coef_nest_NONMOTORIZED  NA 1.0 \n", + "coef_nest_RIDEHAIL  NA 1.0 \n", + "coef_nest_TRANSIT  NA 1.0 \n", + "coef_nest_TRANSIT_DRIVEACCESS  NA 1.0 \n", + "coef_nest_TRANSIT_WALKACCESS  NA 1.0 \n", + "coef_test_eatout_escort_othdiscr_othmaint_shopp...  1.56 0.0 \n", + "coef_test_school_univ  0.57 0.0 \n", + "commuter_rail_ASC_eatout_escort_othdiscr_othmai... -0.06 0.0 \n", + "commuter_rail_ASC_school_univ  NA 0.0 \n", + "commuter_rail_ASC_work  0.00 0.0 \n", + "drive_ferry_ASC_eatout_escort_othdiscr_othmaint... -0.04 0.0 \n", + "drive_ferry_ASC_school_univ  NA 0.0 \n", + "drive_ferry_ASC_work  0.00 0.0 \n", + "drive_light_rail_ASC_eatout_escort_othdiscr_oth... -0.02 0.0 \n", + "drive_light_rail_ASC_school_univ  NA 0.0 \n", + "drive_light_rail_ASC_work  0.00 0.0 \n", + "drive_transit_ASC_auto_deficient_atwork -BIG *** 0.0 \n", + "drive_transit_ASC_auto_deficient_eatout -0.01 0.0 \n", + "drive_transit_ASC_auto_deficient_escort -0.13 0.0 \n", + "drive_transit_ASC_auto_deficient_othdiscr -0.05 0.0 \n", + "drive_transit_ASC_auto_deficient_othmaint -0.08 0.0 \n", + "drive_transit_ASC_auto_deficient_school  NA 0.0 \n", + "drive_transit_ASC_auto_deficient_shopping -0.10 0.0 \n", + "drive_transit_ASC_auto_deficient_social  0.04 0.0 \n", + "drive_transit_ASC_auto_deficient_univ  NA 0.0 \n", + "drive_transit_ASC_auto_deficient_work -0.00 0.0 \n", + "drive_transit_ASC_auto_sufficient_atwork -BIG *** 0.0 \n", + "drive_transit_ASC_auto_sufficient_eatout -0.10 0.0 \n", + "drive_transit_ASC_auto_sufficient_escort -0.32 0.0 \n", + "drive_transit_ASC_auto_sufficient_othdiscr -0.08 0.0 \n", + "drive_transit_ASC_auto_sufficient_othmaint -0.17 0.0 \n", + "drive_transit_ASC_auto_sufficient_school  NA 0.0 \n", + "drive_transit_ASC_auto_sufficient_shopping -0.25 0.0 \n", + "drive_transit_ASC_auto_sufficient_social -0.08 0.0 \n", + "drive_transit_ASC_auto_sufficient_univ  NA 0.0 \n", + "drive_transit_ASC_auto_sufficient_work -0.01 0.0 \n", + "drive_transit_ASC_no_auto_all  NA 0.0 \n", + "drive_transit_CBD_ASC_atwork  NA 0.0 \n", + "drive_transit_CBD_ASC_eatout_escort_othdiscr_ot...  9.63 *** 0.0 \n", + "drive_transit_CBD_ASC_school_univ  4.89 *** 0.0 \n", + "drive_transit_CBD_ASC_work  23.45 *** 0.0 \n", + "express_bus_ASC_eatout_escort_othdiscr_othmaint... -0.02 0.0 \n", + "express_bus_ASC_school_univ  NA 0.0 \n", + "express_bus_ASC_work -0.00 0.0 \n", + "heavy_rail_ASC_eatout_escort_othdiscr_othmaint_... -0.01 0.0 \n", + "heavy_rail_ASC_school_univ  NA 0.0 \n", + "heavy_rail_ASC_work  0.00 0.0 \n", + "joint_bike_ASC_auto_deficient_all -4.62 *** 0.0 \n", + "joint_bike_ASC_auto_sufficient_all -15.28 *** 0.0 \n", + "joint_bike_ASC_no_auto_all -2.48 * 0.0 \n", + "joint_drive_transit_ASC_auto_deficient_all -0.37 0.0 \n", + "joint_drive_transit_ASC_auto_sufficient_all -0.48 0.0 \n", + "joint_drive_transit_ASC_no_auto_all  NA 0.0 \n", + "joint_sr2_ASC_auto_deficient_all  NA 0.0 \n", + "joint_sr2_ASC_auto_sufficient_all  NA 0.0 \n", + "joint_sr2_ASC_no_auto_all  NA 0.0 \n", + "joint_sr3p_ASC_auto_deficient_all -5.77 *** 0.0 \n", + "joint_sr3p_ASC_auto_sufficient_all -17.17 *** 0.0 \n", + "joint_sr3p_ASC_no_auto_all  1.49 0.0 \n", + "joint_taxi_ASC_auto_deficient_all -1.21 0.0 \n", + "joint_taxi_ASC_auto_sufficient_all  NA 0.0 \n", + "joint_taxi_ASC_no_auto_all -1.07 0.0 \n", + "joint_tnc_shared_ASC_auto_deficient_all -0.66 0.0 \n", + "joint_tnc_shared_ASC_auto_sufficient_all  NA 0.0 \n", + "joint_tnc_shared_ASC_no_auto_all -2.17 * 0.0 \n", + "joint_tnc_single_ASC_auto_deficient_all -1.38 0.0 \n", + "joint_tnc_single_ASC_auto_sufficient_all  NA 0.0 \n", + "joint_tnc_single_ASC_no_auto_all -1.88 0.0 \n", + "joint_walk_ASC_auto_deficient_all -5.89 *** 0.0 \n", + "joint_walk_ASC_auto_sufficient_all -17.76 *** 0.0 \n", + "joint_walk_ASC_no_auto_all -0.51 0.0 \n", + "joint_walk_transit_ASC_auto_deficient_all -0.32 0.0 \n", + "joint_walk_transit_ASC_auto_sufficient_all -0.03 0.0 \n", + "joint_walk_transit_ASC_no_auto_all  0.02 0.0 \n", + "local_bus_ASC_eatout_escort_othdiscr_othmaint_s... -0.07 0.0 \n", + "local_bus_ASC_school_univ  NA 0.0 \n", + "local_bus_ASC_work -0.00 0.0 \n", + "sr2_ASC_auto_deficient_atwork -11.34 *** 0.0 \n", + "sr2_ASC_auto_deficient_eatout  5.64 *** 0.0 \n", + "sr2_ASC_auto_deficient_escort  1.58 0.0 \n", + "sr2_ASC_auto_deficient_othdiscr  8.13 *** 0.0 \n", + "sr2_ASC_auto_deficient_othmaint  4.02 *** 0.0 \n", + "sr2_ASC_auto_deficient_school  0.56 0.0 \n", + "sr2_ASC_auto_deficient_shopping  4.09 *** 0.0 \n", + "sr2_ASC_auto_deficient_social  10.70 *** 0.0 \n", + "sr2_ASC_auto_deficient_univ  NA 0.0 \n", + "sr2_ASC_auto_deficient_work  4.76 *** 0.0 \n", + "sr2_ASC_auto_sufficient_atwork -9.85 *** 0.0 \n", + "sr2_ASC_auto_sufficient_eatout  11.19 *** 0.0 \n", + "sr2_ASC_auto_sufficient_escort  3.31 *** 0.0 \n", + "sr2_ASC_auto_sufficient_othdiscr  8.23 *** 0.0 \n", + "sr2_ASC_auto_sufficient_othmaint  6.24 *** 0.0 \n", + "sr2_ASC_auto_sufficient_school -0.79 0.0 \n", + "sr2_ASC_auto_sufficient_shopping  5.16 *** 0.0 \n", + "sr2_ASC_auto_sufficient_social  7.88 *** 0.0 \n", + "sr2_ASC_auto_sufficient_univ  NA 0.0 \n", + "sr2_ASC_auto_sufficient_work -3.43 *** 0.0 \n", + "sr2_ASC_no_auto_all  0.02 0.0 \n", + "sr3p_ASC_auto_deficient_atwork -13.30 *** 0.0 \n", + "sr3p_ASC_auto_deficient_eatout  0.98 0.0 \n", + "sr3p_ASC_auto_deficient_escort  0.18 0.0 \n", + "sr3p_ASC_auto_deficient_othdiscr  11.40 *** 0.0 \n", + "sr3p_ASC_auto_deficient_othmaint -2.71 ** 0.0 \n", + "sr3p_ASC_auto_deficient_school  1.18 0.0 \n", + "sr3p_ASC_auto_deficient_shopping  1.31 0.0 \n", + "sr3p_ASC_auto_deficient_social  9.16 *** 0.0 \n", + "sr3p_ASC_auto_deficient_univ -BIG *** 0.0 \n", + "sr3p_ASC_auto_deficient_work -1.38 0.0 \n", + "sr3p_ASC_auto_sufficient_atwork -11.97 *** 0.0 \n", + "sr3p_ASC_auto_sufficient_eatout  10.73 *** 0.0 \n", + "sr3p_ASC_auto_sufficient_escort  3.10 ** 0.0 \n", + "sr3p_ASC_auto_sufficient_othdiscr  9.25 *** 0.0 \n", + "sr3p_ASC_auto_sufficient_othmaint  2.44 * 0.0 \n", + "sr3p_ASC_auto_sufficient_school -0.16 0.0 \n", + "sr3p_ASC_auto_sufficient_shopping  2.72 ** 0.0 \n", + "sr3p_ASC_auto_sufficient_social  7.91 *** 0.0 \n", + "sr3p_ASC_auto_sufficient_univ -BIG *** 0.0 \n", + "sr3p_ASC_auto_sufficient_work -7.63 *** 0.0 \n", + "sr3p_ASC_no_auto_atwork  0.02 0.0 \n", + "sr3p_ASC_no_auto_eatout  0.02 0.0 \n", + "sr3p_ASC_no_auto_escort -0.02 0.0 \n", + "sr3p_ASC_no_auto_othdiscr  0.02 0.0 \n", + "sr3p_ASC_no_auto_othmaint  0.00 0.0 \n", + "sr3p_ASC_no_auto_school -0.06 0.0 \n", + "sr3p_ASC_no_auto_shopping  0.01 0.0 \n", + "sr3p_ASC_no_auto_social -0.02 0.0 \n", + "sr3p_ASC_no_auto_univ -BIG *** 0.0 \n", + "sr3p_ASC_no_auto_work  0.01 0.0 \n", + "taxi_ASC_auto_deficient_atwork -10.57 *** 0.0 \n", + "taxi_ASC_auto_deficient_eatout_othdiscr_social -6.76 *** 0.0 \n", + "taxi_ASC_auto_deficient_escort_othmaint_shopping -7.89 *** 0.0 \n", + "taxi_ASC_auto_deficient_school  0.90 0.0 \n", + "taxi_ASC_auto_deficient_univ  BIG *** 0.0 \n", + "taxi_ASC_auto_deficient_work -9.95 *** 0.0 \n", + "taxi_ASC_auto_sufficient_atwork -22.22 *** 0.0 \n", + "taxi_ASC_auto_sufficient_eatout_othdiscr_social -15.96 *** 0.0 \n", + "taxi_ASC_auto_sufficient_escort_othmaint_shopping -28.85 *** 0.0 \n", + "taxi_ASC_auto_sufficient_school -2.45 * 0.0 \n", + "taxi_ASC_auto_sufficient_univ  NA 0.0 \n", + "taxi_ASC_auto_sufficient_work -16.01 *** 0.0 \n", + "taxi_ASC_no_auto_atwork  0.05 0.0 \n", + "taxi_ASC_no_auto_eatout_othdiscr_social -0.01 0.0 \n", + "taxi_ASC_no_auto_escort_othmaint_shopping  0.02 0.0 \n", + "taxi_ASC_no_auto_school_univ  NA 0.0 \n", + "taxi_ASC_no_auto_work  0.05 0.0 \n", + "tnc_shared_ASC_auto_deficient_atwork -12.49 *** 0.0 \n", + "tnc_shared_ASC_auto_deficient_eatout_othdiscr_s... -4.95 *** 0.0 \n", + "tnc_shared_ASC_auto_deficient_escort_othmaint_s... -11.36 *** 0.0 \n", + "tnc_shared_ASC_auto_deficient_school  0.30 0.0 \n", + "tnc_shared_ASC_auto_deficient_univ  BIG *** 0.0 \n", + "tnc_shared_ASC_auto_deficient_work -15.89 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_atwork -24.64 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_eatout_othdiscr_... -21.67 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_escort_othmaint_... -35.76 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_school -3.91 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_univ  NA 0.0 \n", + "tnc_shared_ASC_auto_sufficient_work -15.77 *** 0.0 \n", + "tnc_shared_ASC_no_auto_atwork  0.04 0.0 \n", + "tnc_shared_ASC_no_auto_eatout_othdiscr_social -0.00 0.0 \n", + "tnc_shared_ASC_no_auto_escort_othmaint_shopping  0.01 0.0 \n", + "tnc_shared_ASC_no_auto_school  NA 0.0 \n", + "tnc_shared_ASC_no_auto_univ  NA 0.0 \n", + "tnc_shared_ASC_no_auto_work  0.03 0.0 \n", + "tnc_single_ASC_auto_deficient_atwork -13.29 *** 0.0 \n", + "tnc_single_ASC_auto_deficient_eatout_othdiscr_s... -7.50 *** 0.0 \n", + "tnc_single_ASC_auto_deficient_escort_othmaint_s... -3.34 *** 0.0 \n", + "tnc_single_ASC_auto_deficient_school -0.01 0.0 \n", + "tnc_single_ASC_auto_deficient_univ  NA 0.0 \n", + "tnc_single_ASC_auto_deficient_work -11.28 *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_atwork -25.00 *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_eatout_othdiscr_... -21.84 *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_escort_othmaint_... -26.43 *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_school -2.25 * 0.0 \n", + "tnc_single_ASC_auto_sufficient_univ  BIG *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_work -23.29 *** 0.0 \n", + "tnc_single_ASC_no_auto_atwork  0.06 0.0 \n", + "tnc_single_ASC_no_auto_eatout_othdiscr_social  0.01 0.0 \n", + "tnc_single_ASC_no_auto_escort_othmaint_shopping  0.02 0.0 \n", + "tnc_single_ASC_no_auto_school  NA 0.0 \n", + "tnc_single_ASC_no_auto_univ  NA 0.0 \n", + "tnc_single_ASC_no_auto_work  0.07 0.0 \n", + "walk_ASC_auto_deficient_atwork  1.84 0.0 \n", + "walk_ASC_auto_deficient_eatout  10.96 *** 0.0 \n", + "walk_ASC_auto_deficient_escort -7.46 *** 0.0 \n", + "walk_ASC_auto_deficient_othdiscr  7.86 *** 0.0 \n", + "walk_ASC_auto_deficient_othmaint  0.70 0.0 \n", + "walk_ASC_auto_deficient_school  2.81 ** 0.0 \n", + "walk_ASC_auto_deficient_shopping  6.63 *** 0.0 \n", + "walk_ASC_auto_deficient_social  7.56 *** 0.0 \n", + "walk_ASC_auto_deficient_univ  BIG *** 0.0 \n", + "walk_ASC_auto_deficient_work  17.84 *** 0.0 \n", + "walk_ASC_auto_sufficient_atwork  1.34 0.0 \n", + "walk_ASC_auto_sufficient_eatout  5.78 *** 0.0 \n", + "walk_ASC_auto_sufficient_escort -14.88 *** 0.0 \n", + "walk_ASC_auto_sufficient_othdiscr  3.68 *** 0.0 \n", + "walk_ASC_auto_sufficient_othmaint -1.76 0.0 \n", + "walk_ASC_auto_sufficient_school  0.41 0.0 \n", + "walk_ASC_auto_sufficient_shopping -3.75 *** 0.0 \n", + "walk_ASC_auto_sufficient_social  5.04 *** 0.0 \n", + "walk_ASC_auto_sufficient_univ  NA 0.0 \n", + "walk_ASC_auto_sufficient_work -3.70 *** 0.0 \n", + "walk_ASC_no_auto_atwork  0.09 0.0 \n", + "walk_ASC_no_auto_eatout  0.06 0.0 \n", + "walk_ASC_no_auto_escort  0.03 0.0 \n", + "walk_ASC_no_auto_othdiscr  0.04 0.0 \n", + "walk_ASC_no_auto_othmaint  0.01 0.0 \n", + "walk_ASC_no_auto_school  0.16 0.0 \n", + "walk_ASC_no_auto_shopping  0.03 0.0 \n", + "walk_ASC_no_auto_social  0.02 0.0 \n", + "walk_ASC_no_auto_univ  NA 0.0 \n", + "walk_ASC_no_auto_work  0.07 0.0 \n", + "walk_ferry_ASC_eatout_escort_othdiscr_othmaint_... -0.01 0.0 \n", + "walk_ferry_ASC_school_univ  NA 0.0 \n", + "walk_ferry_ASC_work  0.00 0.0 \n", + "walk_light_rail_ASC_eatout_escort_othdiscr_othm... -0.01 0.0 \n", + "walk_light_rail_ASC_school_univ  NA 0.0 \n", + "walk_light_rail_ASC_work  0.00 0.0 \n", + "walk_transit_ASC_auto_deficient_atwork -0.16 0.0 \n", + "walk_transit_ASC_auto_deficient_eatout -0.03 0.0 \n", + "walk_transit_ASC_auto_deficient_escort -0.27 0.0 \n", + "walk_transit_ASC_auto_deficient_othdiscr  0.05 0.0 \n", + "walk_transit_ASC_auto_deficient_othmaint -0.18 0.0 \n", + "walk_transit_ASC_auto_deficient_school  NA 0.0 \n", + "walk_transit_ASC_auto_deficient_shopping -0.07 0.0 \n", + "walk_transit_ASC_auto_deficient_social  0.08 0.0 \n", + "walk_transit_ASC_auto_deficient_univ  NA 0.0 \n", + "walk_transit_ASC_auto_deficient_work  0.00 0.0 \n", + "walk_transit_ASC_auto_sufficient_atwork -0.22 0.0 \n", + "walk_transit_ASC_auto_sufficient_eatout -0.08 0.0 \n", + "walk_transit_ASC_auto_sufficient_escort -0.29 0.0 \n", + "walk_transit_ASC_auto_sufficient_othdiscr -0.06 0.0 \n", + "walk_transit_ASC_auto_sufficient_othmaint -0.10 0.0 \n", + "walk_transit_ASC_auto_sufficient_school  NA 0.0 \n", + "walk_transit_ASC_auto_sufficient_shopping -0.14 0.0 \n", + "walk_transit_ASC_auto_sufficient_social -0.04 0.0 \n", + "walk_transit_ASC_auto_sufficient_univ  NA 0.0 \n", + "walk_transit_ASC_auto_sufficient_work -0.00 0.0 \n", + "walk_transit_ASC_no_auto_atwork  0.05 0.0 \n", + "walk_transit_ASC_no_auto_eatout  0.04 0.0 \n", + "walk_transit_ASC_no_auto_escort -0.03 0.0 \n", + "walk_transit_ASC_no_auto_othdiscr  0.04 0.0 \n", + "walk_transit_ASC_no_auto_othmaint  0.04 0.0 \n", + "walk_transit_ASC_no_auto_school  NA 0.0 \n", + "walk_transit_ASC_no_auto_shopping  0.03 0.0 \n", + "walk_transit_ASC_no_auto_social  0.03 0.0 \n", + "walk_transit_ASC_no_auto_univ  NA 0.0 \n", + "walk_transit_ASC_no_auto_work  0.02 0.0 \n", + "walk_transit_CBD_ASC_atwork  4.57 *** 0.0 \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth...  14.25 *** 0.0 \n", + "walk_transit_CBD_ASC_school_univ  7.30 *** 0.0 \n", + "walk_transit_CBD_ASC_work  21.50 *** 0.0 \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_eatout... \n", + "coefficient_name\\ncoef_test coef_test_school... \n", + "coefficient_name\\ncoef_test coef_test_school... \n", + "\n", + " remodel \\\n", + " Value Std Err \n", + "Parameter \n", + "-999 -999.  0.00 \n", + "1  1.00  0.00 \n", + "bike_ASC_auto_deficient_atwork -1.06  0.340 \n", + "bike_ASC_auto_deficient_eatout -1.20  0.594 \n", + "bike_ASC_auto_deficient_escort -3.88  0.559 \n", + "bike_ASC_auto_deficient_othdiscr -0.528  0.418 \n", + "bike_ASC_auto_deficient_othmaint -1.63  0.448 \n", + "bike_ASC_auto_deficient_school -1.18  0.997 \n", + "bike_ASC_auto_deficient_shopping -1.30  0.363 \n", + "bike_ASC_auto_deficient_social  0.592  0.532 \n", + "bike_ASC_auto_deficient_univ -0.669  0.00146 \n", + "bike_ASC_auto_deficient_work -0.360  0.0922 \n", + "bike_ASC_auto_sufficient_atwork  15.7  463. \n", + "bike_ASC_auto_sufficient_eatout -1.30  0.409 \n", + "bike_ASC_auto_sufficient_escort -5.26  0.453 \n", + "bike_ASC_auto_sufficient_othdiscr -1.49  0.382 \n", + "bike_ASC_auto_sufficient_othmaint -2.51  0.349 \n", + "bike_ASC_auto_sufficient_school -2.20  0.953 \n", + "bike_ASC_auto_sufficient_shopping -2.78  0.326 \n", + "bike_ASC_auto_sufficient_social -1.83  0.471 \n", + "bike_ASC_auto_sufficient_univ -1.94  0.00650 \n", + "bike_ASC_auto_sufficient_work -2.06  0.0822 \n", + "bike_ASC_no_auto_atwork -0.911  87.8 \n", + "bike_ASC_no_auto_eatout  0.510  87.2 \n", + "bike_ASC_no_auto_escort -0.730  87.2 \n", + "bike_ASC_no_auto_othdiscr -0.404  87.2 \n", + "bike_ASC_no_auto_othmaint  1.61  87.2 \n", + "bike_ASC_no_auto_school  13.4  116. \n", + "bike_ASC_no_auto_shopping  1.05  87.2 \n", + "bike_ASC_no_auto_social  0.486  87.2 \n", + "bike_ASC_no_auto_univ  4.29  0.00688 \n", + "bike_ASC_no_auto_work  3.43  87.2 \n", + "coef_age010_trn_multiplier_atwork  0.000722  NA \n", + "coef_age010_trn_multiplier_eatout_escort_othdis...  0.364  0.175 \n", + "coef_age010_trn_multiplier_school_univ -0.875  0.0898 \n", + "coef_age1619_da_multiplier_atwork -0.193  0.205 \n", + "coef_age1619_da_multiplier_eatout_escort_othdis...  0.000513  0.0424 \n", + "coef_age1619_da_multiplier_school_univ -1.68  0.0748 \n", + "coef_age16p_sr_multiplier_eatout_escort_othdisc... -1.45  0.0814 \n", + "coef_age16p_sr_multiplier_school_univ_work_atwork -0.648  0.0683 \n", + "coef_hhsize1_sr_multiplier_eatout_escort_othdis... -0.0710  0.0312 \n", + "coef_hhsize1_sr_multiplier_work -0.836  0.0577 \n", + "coef_hhsize2_sr_multiplier_eatout_escort_othdis...  0.00209  0.0178 \n", + "coef_hhsize2_sr_multiplier_school_univ -0.748  0.0912 \n", + "coef_ivt_atwork -0.0112  0.000478 \n", + "coef_ivt_eatout_escort_othdiscr_othmaint_shoppi... -0.00688  0.000144 \n", + "coef_ivt_school_univ -0.0104  0.000318 \n", + "coef_ivt_work -0.00795  0.000148 \n", + "coef_nest_AUTO  0.720  0.00 \n", + "coef_nest_AUTO_DRIVEALONE  0.350  0.00 \n", + "coef_nest_AUTO_SHAREDRIDE2  0.350  0.00 \n", + "coef_nest_AUTO_SHAREDRIDE3  0.350  0.00 \n", + "coef_nest_NONMOTORIZED  0.720  0.00 \n", + "coef_nest_RIDEHAIL  0.360  0.00 \n", + "coef_nest_TRANSIT  0.720  0.00 \n", + "coef_nest_TRANSIT_DRIVEACCESS  0.500  0.00 \n", + "coef_nest_TRANSIT_WALKACCESS  0.500  0.00 \n", + "coef_test_eatout_escort_othdiscr_othmaint_shopp...  0.0770  NA \n", + "coef_test_school_univ  0.518  NA \n", + "commuter_rail_ASC_eatout_escort_othdiscr_othmai... -0.744  20.6 \n", + "commuter_rail_ASC_school_univ -0.247  NA \n", + "commuter_rail_ASC_work  0.158  NA \n", + "drive_ferry_ASC_eatout_escort_othdiscr_othmaint... -0.393  20.6 \n", + "drive_ferry_ASC_school_univ  1.45  NA \n", + "drive_ferry_ASC_work  0.194  NA \n", + "drive_light_rail_ASC_eatout_escort_othdiscr_oth... -0.0919  20.6 \n", + "drive_light_rail_ASC_school_univ  0.707  NA \n", + "drive_light_rail_ASC_work  0.507  NA \n", + "drive_transit_ASC_auto_deficient_atwork -999.  0.000231 \n", + "drive_transit_ASC_auto_deficient_eatout  0.105  20.6 \n", + "drive_transit_ASC_auto_deficient_escort -2.14  20.6 \n", + "drive_transit_ASC_auto_deficient_othdiscr -0.726  20.6 \n", + "drive_transit_ASC_auto_deficient_othmaint -1.17  20.6 \n", + "drive_transit_ASC_auto_deficient_school  1.57  NA \n", + "drive_transit_ASC_auto_deficient_shopping -1.43  20.6 \n", + "drive_transit_ASC_auto_deficient_social  0.594  20.6 \n", + "drive_transit_ASC_auto_deficient_univ  1.85  NA \n", + "drive_transit_ASC_auto_deficient_work -0.911  NA \n", + "drive_transit_ASC_auto_sufficient_atwork -999.  NA \n", + "drive_transit_ASC_auto_sufficient_eatout -1.30  20.6 \n", + "drive_transit_ASC_auto_sufficient_escort -5.25  20.6 \n", + "drive_transit_ASC_auto_sufficient_othdiscr -1.11  20.6 \n", + "drive_transit_ASC_auto_sufficient_othmaint -2.44  20.6 \n", + "drive_transit_ASC_auto_sufficient_school  0.155  NA \n", + "drive_transit_ASC_auto_sufficient_shopping -3.97  20.6 \n", + "drive_transit_ASC_auto_sufficient_social -1.34  20.6 \n", + "drive_transit_ASC_auto_sufficient_univ  1.36  0.000291 \n", + "drive_transit_ASC_auto_sufficient_work -1.83  NA \n", + "drive_transit_ASC_no_auto_all  0.00  0.000293 \n", + "drive_transit_CBD_ASC_atwork  0.564  NA \n", + "drive_transit_CBD_ASC_eatout_escort_othdiscr_ot...  1.41  0.142 \n", + "drive_transit_CBD_ASC_school_univ  1.20  0.253 \n", + "drive_transit_CBD_ASC_work  1.62  0.0697 \n", + "express_bus_ASC_eatout_escort_othdiscr_othmaint... -0.0888  20.6 \n", + "express_bus_ASC_school_univ -0.450  NA \n", + "express_bus_ASC_work -0.920  NA \n", + "heavy_rail_ASC_eatout_escort_othdiscr_othmaint_...  0.0401  20.6 \n", + "heavy_rail_ASC_school_univ  0.127  NA \n", + "heavy_rail_ASC_work  0.496  NA \n", + "joint_bike_ASC_auto_deficient_all -6.16  1.42 \n", + "joint_bike_ASC_auto_sufficient_all -6.95  0.465 \n", + "joint_bike_ASC_no_auto_all -2.67  1.14 \n", + "joint_drive_transit_ASC_auto_deficient_all -6.04  20.6 \n", + "joint_drive_transit_ASC_auto_sufficient_all -7.80  20.6 \n", + "joint_drive_transit_ASC_no_auto_all  0.00  0.00 \n", + "joint_sr2_ASC_auto_deficient_all  0.00  0.00 \n", + "joint_sr2_ASC_auto_sufficient_all  0.00  0.00 \n", + "joint_sr2_ASC_no_auto_all  0.00  0.00 \n", + "joint_sr3p_ASC_auto_deficient_all -1.51  0.260 \n", + "joint_sr3p_ASC_auto_sufficient_all -2.27  0.131 \n", + "joint_sr3p_ASC_no_auto_all  0.680  0.471 \n", + "joint_taxi_ASC_auto_deficient_all -9.82  8.64 \n", + "joint_taxi_ASC_auto_sufficient_all -11.7  0.00 \n", + "joint_taxi_ASC_no_auto_all -4.58  4.45 \n", + "joint_tnc_shared_ASC_auto_deficient_all -11.2  18.0 \n", + "joint_tnc_shared_ASC_auto_sufficient_all -13.2  0.00 \n", + "joint_tnc_shared_ASC_no_auto_all -4.70  2.31 \n", + "joint_tnc_single_ASC_auto_deficient_all -9.90  7.63 \n", + "joint_tnc_single_ASC_auto_sufficient_all -14.0  0.00 \n", + "joint_tnc_single_ASC_no_auto_all -3.89  2.20 \n", + "joint_walk_ASC_auto_deficient_all -2.05  0.372 \n", + "joint_walk_ASC_auto_sufficient_all -4.15  0.240 \n", + "joint_walk_ASC_no_auto_all -0.294  0.735 \n", + "joint_walk_transit_ASC_auto_deficient_all -5.30  20.6 \n", + "joint_walk_transit_ASC_auto_sufficient_all -18.3  620. \n", + "joint_walk_transit_ASC_no_auto_all  0.351  20.6 \n", + "local_bus_ASC_eatout_escort_othdiscr_othmaint_s... -0.943  20.6 \n", + "local_bus_ASC_school_univ -0.811  NA \n", + "local_bus_ASC_work -0.211  NA \n", + "sr2_ASC_auto_deficient_atwork -1.57  0.133 \n", + "sr2_ASC_auto_deficient_eatout  1.32  0.407 \n", + "sr2_ASC_auto_deficient_escort  0.560  0.331 \n", + "sr2_ASC_auto_deficient_othdiscr  1.32  0.389 \n", + "sr2_ASC_auto_deficient_othmaint  1.03  0.327 \n", + "sr2_ASC_auto_deficient_school  0.522  0.961 \n", + "sr2_ASC_auto_deficient_shopping  0.801  0.319 \n", + "sr2_ASC_auto_deficient_social  2.42  0.473 \n", + "sr2_ASC_auto_deficient_univ -1.69  0.000112 \n", + "sr2_ASC_auto_deficient_work  0.248  0.0900 \n", + "sr2_ASC_auto_sufficient_atwork -0.810  0.0784 \n", + "sr2_ASC_auto_sufficient_eatout  1.63  0.390 \n", + "sr2_ASC_auto_sufficient_escort  0.754  0.317 \n", + "sr2_ASC_auto_sufficient_othdiscr  1.09  0.380 \n", + "sr2_ASC_auto_sufficient_othmaint  1.09  0.312 \n", + "sr2_ASC_auto_sufficient_school -0.720  0.950 \n", + "sr2_ASC_auto_sufficient_shopping  0.806  0.310 \n", + "sr2_ASC_auto_sufficient_social  1.07  0.438 \n", + "sr2_ASC_auto_sufficient_univ -1.86  6.12e-05 \n", + "sr2_ASC_auto_sufficient_work -0.478  0.0868 \n", + "sr2_ASC_no_auto_all  1.17  87.2 \n", + "sr3p_ASC_auto_deficient_atwork -1.88  0.137 \n", + "sr3p_ASC_auto_deficient_eatout  0.638  0.420 \n", + "sr3p_ASC_auto_deficient_escort  0.336  0.332 \n", + "sr3p_ASC_auto_deficient_othdiscr  1.67  0.387 \n", + "sr3p_ASC_auto_deficient_othmaint -0.202  0.371 \n", + "sr3p_ASC_auto_deficient_school  1.09  0.961 \n", + "sr3p_ASC_auto_deficient_shopping  0.457  0.324 \n", + "sr3p_ASC_auto_deficient_social  2.16  0.476 \n", + "sr3p_ASC_auto_deficient_univ -1.73  NA \n", + "sr3p_ASC_auto_deficient_work -0.289  0.0929 \n", + "sr3p_ASC_auto_sufficient_atwork -1.00  0.0798 \n", + "sr3p_ASC_auto_sufficient_eatout  1.58  0.390 \n", + "sr3p_ASC_auto_sufficient_escort  0.729  0.317 \n", + "sr3p_ASC_auto_sufficient_othdiscr  1.18  0.380 \n", + "sr3p_ASC_auto_sufficient_othmaint  0.726  0.313 \n", + "sr3p_ASC_auto_sufficient_school -0.151  0.950 \n", + "sr3p_ASC_auto_sufficient_shopping  0.561  0.310 \n", + "sr3p_ASC_auto_sufficient_social  1.07  0.438 \n", + "sr3p_ASC_auto_sufficient_univ -1.90  1.95e-05 \n", + "sr3p_ASC_auto_sufficient_work -0.849  0.0876 \n", + "sr3p_ASC_no_auto_atwork  1.67  87.2 \n", + "sr3p_ASC_no_auto_eatout  1.53  87.2 \n", + "sr3p_ASC_no_auto_escort -1.87  87.3 \n", + "sr3p_ASC_no_auto_othdiscr  1.40  87.2 \n", + "sr3p_ASC_no_auto_othmaint  0.195  87.2 \n", + "sr3p_ASC_no_auto_school -6.02  112. \n", + "sr3p_ASC_no_auto_shopping  0.847  87.2 \n", + "sr3p_ASC_no_auto_social -1.21  87.2 \n", + "sr3p_ASC_no_auto_univ -6.06  5.30e-05 \n", + "sr3p_ASC_no_auto_work  0.523  87.2 \n", + "taxi_ASC_auto_deficient_atwork -4.75  0.459 \n", + "taxi_ASC_auto_deficient_eatout_othdiscr_social -3.16  0.647 \n", + "taxi_ASC_auto_deficient_escort_othmaint_shopping -0.503  0.313 \n", + "taxi_ASC_auto_deficient_school  0.899  0.968 \n", + "taxi_ASC_auto_deficient_univ  4.25  4.12e-06 \n", + "taxi_ASC_auto_deficient_work -2.30  0.226 \n", + "taxi_ASC_auto_sufficient_atwork -3.31  0.148 \n", + "taxi_ASC_auto_sufficient_eatout_othdiscr_social -3.47  0.416 \n", + "taxi_ASC_auto_sufficient_escort_othmaint_shopping -2.33  0.306 \n", + "taxi_ASC_auto_sufficient_school -2.23  0.956 \n", + "taxi_ASC_auto_sufficient_univ -0.313  NA \n", + "taxi_ASC_auto_sufficient_work -5.14  0.361 \n", + "taxi_ASC_no_auto_atwork  3.63  87.2 \n", + "taxi_ASC_no_auto_eatout_othdiscr_social -0.460  87.2 \n", + "taxi_ASC_no_auto_escort_othmaint_shopping  1.54  87.2 \n", + "taxi_ASC_no_auto_school_univ -7.00  0.00 \n", + "taxi_ASC_no_auto_work  3.89  87.2 \n", + "tnc_shared_ASC_auto_deficient_atwork -5.21  0.410 \n", + "tnc_shared_ASC_auto_deficient_eatout_othdiscr_s... -4.43  1.17 \n", + "tnc_shared_ASC_auto_deficient_escort_othmaint_s... -0.796  0.310 \n", + "tnc_shared_ASC_auto_deficient_school  0.312  0.966 \n", + "tnc_shared_ASC_auto_deficient_univ  3.25  NA \n", + "tnc_shared_ASC_auto_deficient_work -3.73  0.231 \n", + "tnc_shared_ASC_auto_sufficient_atwork -4.09  0.167 \n", + "tnc_shared_ASC_auto_sufficient_eatout_othdiscr_... -3.88  0.393 \n", + "tnc_shared_ASC_auto_sufficient_escort_othmaint_... -2.83  0.305 \n", + "tnc_shared_ASC_auto_sufficient_school -3.62  0.961 \n", + "tnc_shared_ASC_auto_sufficient_univ -0.907  NA \n", + "tnc_shared_ASC_auto_sufficient_work -6.74  0.419 \n", + "tnc_shared_ASC_no_auto_atwork  3.04  87.2 \n", + "tnc_shared_ASC_no_auto_eatout_othdiscr_social -0.000529  87.2 \n", + "tnc_shared_ASC_no_auto_escort_othmaint_shopping  0.776  87.2 \n", + "tnc_shared_ASC_no_auto_school -7.00  0.00 \n", + "tnc_shared_ASC_no_auto_univ -5.81  NA \n", + "tnc_shared_ASC_no_auto_work  2.21  87.2 \n", + "tnc_single_ASC_auto_deficient_atwork -4.36  0.331 \n", + "tnc_single_ASC_auto_deficient_eatout_othdiscr_s... -3.12  0.599 \n", + "tnc_single_ASC_auto_deficient_escort_othmaint_s...  0.0928  0.308 \n", + "tnc_single_ASC_auto_deficient_school  0.0597  0.975 \n", + "tnc_single_ASC_auto_deficient_univ  1.02  2.45e-06 \n", + "tnc_single_ASC_auto_deficient_work -1.47  0.118 \n", + "tnc_single_ASC_auto_sufficient_atwork -3.14  0.125 \n", + "tnc_single_ASC_auto_sufficient_eatout_othdiscr_... -2.83  0.371 \n", + "tnc_single_ASC_auto_sufficient_escort_othmaint_... -1.76  0.302 \n", + "tnc_single_ASC_auto_sufficient_school -2.02  0.953 \n", + "tnc_single_ASC_auto_sufficient_univ  0.209  2.79e-06 \n", + "tnc_single_ASC_auto_sufficient_work -4.33  0.179 \n", + "tnc_single_ASC_no_auto_atwork  4.24  87.2 \n", + "tnc_single_ASC_no_auto_eatout_othdiscr_social  1.06  87.2 \n", + "tnc_single_ASC_no_auto_escort_othmaint_shopping  1.70  87.2 \n", + "tnc_single_ASC_no_auto_school -7.00  0.00 \n", + "tnc_single_ASC_no_auto_univ -2.52  5.36e-06 \n", + "tnc_single_ASC_no_auto_work  5.31  87.2 \n", + "walk_ASC_auto_deficient_atwork  0.175  0.124 \n", + "walk_ASC_auto_deficient_eatout  2.70  0.425 \n", + "walk_ASC_auto_deficient_escort -1.60  0.396 \n", + "walk_ASC_auto_deficient_othdiscr  1.57  0.398 \n", + "walk_ASC_auto_deficient_othmaint  0.643  0.360 \n", + "walk_ASC_auto_deficient_school  2.65  0.964 \n", + "walk_ASC_auto_deficient_shopping  1.31  0.323 \n", + "walk_ASC_auto_deficient_social  2.48  0.516 \n", + "walk_ASC_auto_deficient_univ  4.51  NA \n", + "walk_ASC_auto_deficient_work  1.59  0.0962 \n", + "walk_ASC_auto_sufficient_atwork  0.0786  0.0579 \n", + "walk_ASC_auto_sufficient_eatout  1.19  0.391 \n", + "walk_ASC_auto_sufficient_escort -1.32  0.313 \n", + "walk_ASC_auto_sufficient_othdiscr  0.661  0.376 \n", + "walk_ASC_auto_sufficient_othmaint  0.439  0.310 \n", + "walk_ASC_auto_sufficient_school  0.383  0.951 \n", + "walk_ASC_auto_sufficient_shopping  0.0818  0.305 \n", + "walk_ASC_auto_sufficient_social  0.911  0.439 \n", + "walk_ASC_auto_sufficient_univ  1.06  1.94e-07 \n", + "walk_ASC_auto_sufficient_work -0.417  0.0795 \n", + "walk_ASC_no_auto_atwork  6.61  87.2 \n", + "walk_ASC_no_auto_eatout  4.52  87.2 \n", + "walk_ASC_no_auto_escort  2.56  87.2 \n", + "walk_ASC_no_auto_othdiscr  2.96  87.2 \n", + "walk_ASC_no_auto_othmaint  1.06  87.2 \n", + "walk_ASC_no_auto_school  17.8  116. \n", + "walk_ASC_no_auto_shopping  2.26  87.2 \n", + "walk_ASC_no_auto_social  1.84  87.2 \n", + "walk_ASC_no_auto_univ  6.41  3.50e-09 \n", + "walk_ASC_no_auto_work  5.28  87.2 \n", + "walk_ferry_ASC_eatout_escort_othdiscr_othmaint_... -0.0347  20.6 \n", + "walk_ferry_ASC_school_univ  0.903  NA \n", + "walk_ferry_ASC_work  0.0751  NA \n", + "walk_light_rail_ASC_eatout_escort_othdiscr_othm...  0.115  20.6 \n", + "walk_light_rail_ASC_school_univ  0.721  NA \n", + "walk_light_rail_ASC_work  0.730  NA \n", + "walk_transit_ASC_auto_deficient_atwork -2.84  20.6 \n", + "walk_transit_ASC_auto_deficient_eatout -0.205  20.6 \n", + "walk_transit_ASC_auto_deficient_escort -4.46  20.6 \n", + "walk_transit_ASC_auto_deficient_othdiscr  0.997  20.6 \n", + "walk_transit_ASC_auto_deficient_othmaint -2.91  20.6 \n", + "walk_transit_ASC_auto_deficient_school  3.00  NA \n", + "walk_transit_ASC_auto_deficient_shopping -0.899  20.6 \n", + "walk_transit_ASC_auto_deficient_social  1.32  20.6 \n", + "walk_transit_ASC_auto_deficient_univ  3.14  0.00 \n", + "walk_transit_ASC_auto_deficient_work  0.0663  NA \n", + "walk_transit_ASC_auto_sufficient_atwork -3.76  20.6 \n", + "walk_transit_ASC_auto_sufficient_eatout -0.985  20.6 \n", + "walk_transit_ASC_auto_sufficient_escort -4.68  20.6 \n", + "walk_transit_ASC_auto_sufficient_othdiscr -0.771  20.6 \n", + "walk_transit_ASC_auto_sufficient_othmaint -1.31  20.6 \n", + "walk_transit_ASC_auto_sufficient_school  0.522  NA \n", + "walk_transit_ASC_auto_sufficient_shopping -2.20  20.6 \n", + "walk_transit_ASC_auto_sufficient_social -0.595  20.6 \n", + "walk_transit_ASC_auto_sufficient_univ  0.473  0.00 \n", + "walk_transit_ASC_auto_sufficient_work -1.47  NA \n", + "walk_transit_ASC_no_auto_atwork  2.98  73.6 \n", + "walk_transit_ASC_no_auto_eatout  2.76  73.6 \n", + "walk_transit_ASC_no_auto_escort -2.26  73.7 \n", + "walk_transit_ASC_no_auto_othdiscr  2.64  73.6 \n", + "walk_transit_ASC_no_auto_othmaint  2.43  73.6 \n", + "walk_transit_ASC_no_auto_school  20.5  NA \n", + "walk_transit_ASC_no_auto_shopping  2.18  73.6 \n", + "walk_transit_ASC_no_auto_social  1.90  73.6 \n", + "walk_transit_ASC_no_auto_univ  8.79  0.00 \n", + "walk_transit_ASC_no_auto_work  4.63  NA \n", + "walk_transit_CBD_ASC_atwork  1.18  0.277 \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth...  1.09  0.0756 \n", + "walk_transit_CBD_ASC_school_univ  0.826  0.114 \n", + "walk_transit_CBD_ASC_work  1.15  0.0539 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  0.340  0.190 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  0.00  NA \n", + "coefficient_name\\ncoef_test coef_test_eatout...  0.231  0.185 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  0.333  0.150 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  0.245  0.149 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  0.197  0.214 \n", + "coefficient_name\\ncoef_test coef_test_eatout... -0.0306  0.0255 \n", + "coefficient_name\\ncoef_test coef_test_school...  0.278  0.474 \n", + "coefficient_name\\ncoef_test coef_test_school...  0.00  NA \n", + "\n", + " \n", + " t Stat Signif Null Value \n", + "Parameter \n", + "-999  NA 0.0 \n", + "1  NA 0.0 \n", + "bike_ASC_auto_deficient_atwork -3.11 ** 0.0 \n", + "bike_ASC_auto_deficient_eatout -2.02 * 0.0 \n", + "bike_ASC_auto_deficient_escort -6.94 *** 0.0 \n", + "bike_ASC_auto_deficient_othdiscr -1.26 0.0 \n", + "bike_ASC_auto_deficient_othmaint -3.64 *** 0.0 \n", + "bike_ASC_auto_deficient_school -1.19 0.0 \n", + "bike_ASC_auto_deficient_shopping -3.59 *** 0.0 \n", + "bike_ASC_auto_deficient_social  1.11 0.0 \n", + "bike_ASC_auto_deficient_univ -458.48 *** 0.0 \n", + "bike_ASC_auto_deficient_work -3.90 *** 0.0 \n", + "bike_ASC_auto_sufficient_atwork  0.03 0.0 \n", + "bike_ASC_auto_sufficient_eatout -3.17 ** 0.0 \n", + "bike_ASC_auto_sufficient_escort -11.62 *** 0.0 \n", + "bike_ASC_auto_sufficient_othdiscr -3.91 *** 0.0 \n", + "bike_ASC_auto_sufficient_othmaint -7.20 *** 0.0 \n", + "bike_ASC_auto_sufficient_school -2.31 * 0.0 \n", + "bike_ASC_auto_sufficient_shopping -8.52 *** 0.0 \n", + "bike_ASC_auto_sufficient_social -3.88 *** 0.0 \n", + "bike_ASC_auto_sufficient_univ -298.24 *** 0.0 \n", + "bike_ASC_auto_sufficient_work -25.06 *** 0.0 \n", + "bike_ASC_no_auto_atwork -0.01 0.0 \n", + "bike_ASC_no_auto_eatout  0.01 0.0 \n", + "bike_ASC_no_auto_escort -0.01 0.0 \n", + "bike_ASC_no_auto_othdiscr -0.00 0.0 \n", + "bike_ASC_no_auto_othmaint  0.02 0.0 \n", + "bike_ASC_no_auto_school  0.12 0.0 \n", + "bike_ASC_no_auto_shopping  0.01 0.0 \n", + "bike_ASC_no_auto_social  0.01 0.0 \n", + "bike_ASC_no_auto_univ  624.05 *** 0.0 \n", + "bike_ASC_no_auto_work  0.04 0.0 \n", + "coef_age010_trn_multiplier_atwork  NA 0.0 \n", + "coef_age010_trn_multiplier_eatout_escort_othdis...  2.08 * 0.0 \n", + "coef_age010_trn_multiplier_school_univ -9.74 *** 0.0 \n", + "coef_age1619_da_multiplier_atwork -0.94 0.0 \n", + "coef_age1619_da_multiplier_eatout_escort_othdis...  0.01 0.0 \n", + "coef_age1619_da_multiplier_school_univ -22.42 *** 0.0 \n", + "coef_age16p_sr_multiplier_eatout_escort_othdisc... -17.82 *** 0.0 \n", + "coef_age16p_sr_multiplier_school_univ_work_atwork -9.49 *** 0.0 \n", + "coef_hhsize1_sr_multiplier_eatout_escort_othdis... -2.27 * 0.0 \n", + "coef_hhsize1_sr_multiplier_work -14.48 *** 0.0 \n", + "coef_hhsize2_sr_multiplier_eatout_escort_othdis...  0.12 0.0 \n", + "coef_hhsize2_sr_multiplier_school_univ -8.20 *** 0.0 \n", + "coef_ivt_atwork -23.41 *** 0.0 \n", + "coef_ivt_eatout_escort_othdiscr_othmaint_shoppi... -47.65 *** 0.0 \n", + "coef_ivt_school_univ -32.71 *** 0.0 \n", + "coef_ivt_work -53.70 *** 0.0 \n", + "coef_nest_AUTO  NA 1.0 \n", + "coef_nest_AUTO_DRIVEALONE  NA 1.0 \n", + "coef_nest_AUTO_SHAREDRIDE2  NA 1.0 \n", + "coef_nest_AUTO_SHAREDRIDE3  NA 1.0 \n", + "coef_nest_NONMOTORIZED  NA 1.0 \n", + "coef_nest_RIDEHAIL  NA 1.0 \n", + "coef_nest_TRANSIT  NA 1.0 \n", + "coef_nest_TRANSIT_DRIVEACCESS  NA 1.0 \n", + "coef_nest_TRANSIT_WALKACCESS  NA 1.0 \n", + "coef_test_eatout_escort_othdiscr_othmaint_shopp...  NA 0.0 \n", + "coef_test_school_univ  NA 0.0 \n", + "commuter_rail_ASC_eatout_escort_othdiscr_othmai... -0.04 0.0 \n", + "commuter_rail_ASC_school_univ  NA 0.0 \n", + "commuter_rail_ASC_work  NA 0.0 \n", + "drive_ferry_ASC_eatout_escort_othdiscr_othmaint... -0.02 0.0 \n", + "drive_ferry_ASC_school_univ  NA 0.0 \n", + "drive_ferry_ASC_work  NA 0.0 \n", + "drive_light_rail_ASC_eatout_escort_othdiscr_oth... -0.00 0.0 \n", + "drive_light_rail_ASC_school_univ  NA 0.0 \n", + "drive_light_rail_ASC_work  NA 0.0 \n", + "drive_transit_ASC_auto_deficient_atwork -BIG *** 0.0 \n", + "drive_transit_ASC_auto_deficient_eatout  0.01 0.0 \n", + "drive_transit_ASC_auto_deficient_escort -0.10 0.0 \n", + "drive_transit_ASC_auto_deficient_othdiscr -0.04 0.0 \n", + "drive_transit_ASC_auto_deficient_othmaint -0.06 0.0 \n", + "drive_transit_ASC_auto_deficient_school  NA 0.0 \n", + "drive_transit_ASC_auto_deficient_shopping -0.07 0.0 \n", + "drive_transit_ASC_auto_deficient_social  0.03 0.0 \n", + "drive_transit_ASC_auto_deficient_univ  NA 0.0 \n", + "drive_transit_ASC_auto_deficient_work  NA 0.0 \n", + "drive_transit_ASC_auto_sufficient_atwork  NA 0.0 \n", + "drive_transit_ASC_auto_sufficient_eatout -0.06 0.0 \n", + "drive_transit_ASC_auto_sufficient_escort -0.26 0.0 \n", + "drive_transit_ASC_auto_sufficient_othdiscr -0.05 0.0 \n", + "drive_transit_ASC_auto_sufficient_othmaint -0.12 0.0 \n", + "drive_transit_ASC_auto_sufficient_school  NA 0.0 \n", + "drive_transit_ASC_auto_sufficient_shopping -0.19 0.0 \n", + "drive_transit_ASC_auto_sufficient_social -0.07 0.0 \n", + "drive_transit_ASC_auto_sufficient_univ  BIG *** 0.0 \n", + "drive_transit_ASC_auto_sufficient_work  NA 0.0 \n", + "drive_transit_ASC_no_auto_all  0.00 0.0 \n", + "drive_transit_CBD_ASC_atwork  NA 0.0 \n", + "drive_transit_CBD_ASC_eatout_escort_othdiscr_ot...  9.95 *** 0.0 \n", + "drive_transit_CBD_ASC_school_univ  4.76 *** 0.0 \n", + "drive_transit_CBD_ASC_work  23.19 *** 0.0 \n", + "express_bus_ASC_eatout_escort_othdiscr_othmaint... -0.00 0.0 \n", + "express_bus_ASC_school_univ  NA 0.0 \n", + "express_bus_ASC_work  NA 0.0 \n", + "heavy_rail_ASC_eatout_escort_othdiscr_othmaint_...  0.00 0.0 \n", + "heavy_rail_ASC_school_univ  NA 0.0 \n", + "heavy_rail_ASC_work  NA 0.0 \n", + "joint_bike_ASC_auto_deficient_all -4.35 *** 0.0 \n", + "joint_bike_ASC_auto_sufficient_all -14.96 *** 0.0 \n", + "joint_bike_ASC_no_auto_all -2.35 * 0.0 \n", + "joint_drive_transit_ASC_auto_deficient_all -0.29 0.0 \n", + "joint_drive_transit_ASC_auto_sufficient_all -0.38 0.0 \n", + "joint_drive_transit_ASC_no_auto_all  NA 0.0 \n", + "joint_sr2_ASC_auto_deficient_all  NA 0.0 \n", + "joint_sr2_ASC_auto_sufficient_all  NA 0.0 \n", + "joint_sr2_ASC_no_auto_all  NA 0.0 \n", + "joint_sr3p_ASC_auto_deficient_all -5.80 *** 0.0 \n", + "joint_sr3p_ASC_auto_sufficient_all -17.25 *** 0.0 \n", + "joint_sr3p_ASC_no_auto_all  1.44 0.0 \n", + "joint_taxi_ASC_auto_deficient_all -1.14 0.0 \n", + "joint_taxi_ASC_auto_sufficient_all  NA 0.0 \n", + "joint_taxi_ASC_no_auto_all -1.03 0.0 \n", + "joint_tnc_shared_ASC_auto_deficient_all -0.62 0.0 \n", + "joint_tnc_shared_ASC_auto_sufficient_all  NA 0.0 \n", + "joint_tnc_shared_ASC_no_auto_all -2.03 * 0.0 \n", + "joint_tnc_single_ASC_auto_deficient_all -1.30 0.0 \n", + "joint_tnc_single_ASC_auto_sufficient_all  NA 0.0 \n", + "joint_tnc_single_ASC_no_auto_all -1.77 0.0 \n", + "joint_walk_ASC_auto_deficient_all -5.51 *** 0.0 \n", + "joint_walk_ASC_auto_sufficient_all -17.32 *** 0.0 \n", + "joint_walk_ASC_no_auto_all -0.40 0.0 \n", + "joint_walk_transit_ASC_auto_deficient_all -0.26 0.0 \n", + "joint_walk_transit_ASC_auto_sufficient_all -0.03 0.0 \n", + "joint_walk_transit_ASC_no_auto_all  0.02 0.0 \n", + "local_bus_ASC_eatout_escort_othdiscr_othmaint_s... -0.05 0.0 \n", + "local_bus_ASC_school_univ  NA 0.0 \n", + "local_bus_ASC_work  NA 0.0 \n", + "sr2_ASC_auto_deficient_atwork -11.82 *** 0.0 \n", + "sr2_ASC_auto_deficient_eatout  3.25 ** 0.0 \n", + "sr2_ASC_auto_deficient_escort  1.69 0.0 \n", + "sr2_ASC_auto_deficient_othdiscr  3.39 *** 0.0 \n", + "sr2_ASC_auto_deficient_othmaint  3.14 ** 0.0 \n", + "sr2_ASC_auto_deficient_school  0.54 0.0 \n", + "sr2_ASC_auto_deficient_shopping  2.51 * 0.0 \n", + "sr2_ASC_auto_deficient_social  5.12 *** 0.0 \n", + "sr2_ASC_auto_deficient_univ -BIG *** 0.0 \n", + "sr2_ASC_auto_deficient_work  2.76 ** 0.0 \n", + "sr2_ASC_auto_sufficient_atwork -10.34 *** 0.0 \n", + "sr2_ASC_auto_sufficient_eatout  4.18 *** 0.0 \n", + "sr2_ASC_auto_sufficient_escort  2.38 * 0.0 \n", + "sr2_ASC_auto_sufficient_othdiscr  2.87 ** 0.0 \n", + "sr2_ASC_auto_sufficient_othmaint  3.51 *** 0.0 \n", + "sr2_ASC_auto_sufficient_school -0.76 0.0 \n", + "sr2_ASC_auto_sufficient_shopping  2.60 ** 0.0 \n", + "sr2_ASC_auto_sufficient_social  2.43 * 0.0 \n", + "sr2_ASC_auto_sufficient_univ -BIG *** 0.0 \n", + "sr2_ASC_auto_sufficient_work -5.50 *** 0.0 \n", + "sr2_ASC_no_auto_all  0.01 0.0 \n", + "sr3p_ASC_auto_deficient_atwork -13.71 *** 0.0 \n", + "sr3p_ASC_auto_deficient_eatout  1.52 0.0 \n", + "sr3p_ASC_auto_deficient_escort  1.01 0.0 \n", + "sr3p_ASC_auto_deficient_othdiscr  4.32 *** 0.0 \n", + "sr3p_ASC_auto_deficient_othmaint -0.55 0.0 \n", + "sr3p_ASC_auto_deficient_school  1.14 0.0 \n", + "sr3p_ASC_auto_deficient_shopping  1.41 0.0 \n", + "sr3p_ASC_auto_deficient_social  4.52 *** 0.0 \n", + "sr3p_ASC_auto_deficient_univ  NA 0.0 \n", + "sr3p_ASC_auto_deficient_work -3.11 ** 0.0 \n", + "sr3p_ASC_auto_sufficient_atwork -12.59 *** 0.0 \n", + "sr3p_ASC_auto_sufficient_eatout  4.04 *** 0.0 \n", + "sr3p_ASC_auto_sufficient_escort  2.30 * 0.0 \n", + "sr3p_ASC_auto_sufficient_othdiscr  3.12 ** 0.0 \n", + "sr3p_ASC_auto_sufficient_othmaint  2.32 * 0.0 \n", + "sr3p_ASC_auto_sufficient_school -0.16 0.0 \n", + "sr3p_ASC_auto_sufficient_shopping  1.81 0.0 \n", + "sr3p_ASC_auto_sufficient_social  2.45 * 0.0 \n", + "sr3p_ASC_auto_sufficient_univ -BIG *** 0.0 \n", + "sr3p_ASC_auto_sufficient_work -9.68 *** 0.0 \n", + "sr3p_ASC_no_auto_atwork  0.02 0.0 \n", + "sr3p_ASC_no_auto_eatout  0.02 0.0 \n", + "sr3p_ASC_no_auto_escort -0.02 0.0 \n", + "sr3p_ASC_no_auto_othdiscr  0.02 0.0 \n", + "sr3p_ASC_no_auto_othmaint  0.00 0.0 \n", + "sr3p_ASC_no_auto_school -0.05 0.0 \n", + "sr3p_ASC_no_auto_shopping  0.01 0.0 \n", + "sr3p_ASC_no_auto_social -0.01 0.0 \n", + "sr3p_ASC_no_auto_univ -BIG *** 0.0 \n", + "sr3p_ASC_no_auto_work  0.01 0.0 \n", + "taxi_ASC_auto_deficient_atwork -10.34 *** 0.0 \n", + "taxi_ASC_auto_deficient_eatout_othdiscr_social -4.89 *** 0.0 \n", + "taxi_ASC_auto_deficient_escort_othmaint_shopping -1.60 0.0 \n", + "taxi_ASC_auto_deficient_school  0.93 0.0 \n", + "taxi_ASC_auto_deficient_univ  BIG *** 0.0 \n", + "taxi_ASC_auto_deficient_work -10.19 *** 0.0 \n", + "taxi_ASC_auto_sufficient_atwork -22.34 *** 0.0 \n", + "taxi_ASC_auto_sufficient_eatout_othdiscr_social -8.35 *** 0.0 \n", + "taxi_ASC_auto_sufficient_escort_othmaint_shopping -7.60 *** 0.0 \n", + "taxi_ASC_auto_sufficient_school -2.33 * 0.0 \n", + "taxi_ASC_auto_sufficient_univ  NA 0.0 \n", + "taxi_ASC_auto_sufficient_work -14.22 *** 0.0 \n", + "taxi_ASC_no_auto_atwork  0.04 0.0 \n", + "taxi_ASC_no_auto_eatout_othdiscr_social -0.01 0.0 \n", + "taxi_ASC_no_auto_escort_othmaint_shopping  0.02 0.0 \n", + "taxi_ASC_no_auto_school_univ  NA 0.0 \n", + "taxi_ASC_no_auto_work  0.04 0.0 \n", + "tnc_shared_ASC_auto_deficient_atwork -12.71 *** 0.0 \n", + "tnc_shared_ASC_auto_deficient_eatout_othdiscr_s... -3.78 *** 0.0 \n", + "tnc_shared_ASC_auto_deficient_escort_othmaint_s... -2.57 * 0.0 \n", + "tnc_shared_ASC_auto_deficient_school  0.32 0.0 \n", + "tnc_shared_ASC_auto_deficient_univ  NA 0.0 \n", + "tnc_shared_ASC_auto_deficient_work -16.16 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_atwork -24.51 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_eatout_othdiscr_... -9.86 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_escort_othmaint_... -9.30 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_school -3.77 *** 0.0 \n", + "tnc_shared_ASC_auto_sufficient_univ  NA 0.0 \n", + "tnc_shared_ASC_auto_sufficient_work -16.11 *** 0.0 \n", + "tnc_shared_ASC_no_auto_atwork  0.03 0.0 \n", + "tnc_shared_ASC_no_auto_eatout_othdiscr_social -0.00 0.0 \n", + "tnc_shared_ASC_no_auto_escort_othmaint_shopping  0.01 0.0 \n", + "tnc_shared_ASC_no_auto_school  NA 0.0 \n", + "tnc_shared_ASC_no_auto_univ  NA 0.0 \n", + "tnc_shared_ASC_no_auto_work  0.03 0.0 \n", + "tnc_single_ASC_auto_deficient_atwork -13.19 *** 0.0 \n", + "tnc_single_ASC_auto_deficient_eatout_othdiscr_s... -5.21 *** 0.0 \n", + "tnc_single_ASC_auto_deficient_escort_othmaint_s...  0.30 0.0 \n", + "tnc_single_ASC_auto_deficient_school  0.06 0.0 \n", + "tnc_single_ASC_auto_deficient_univ  BIG *** 0.0 \n", + "tnc_single_ASC_auto_deficient_work -12.49 *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_atwork -25.04 *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_eatout_othdiscr_... -7.62 *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_escort_othmaint_... -5.81 *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_school -2.12 * 0.0 \n", + "tnc_single_ASC_auto_sufficient_univ  BIG *** 0.0 \n", + "tnc_single_ASC_auto_sufficient_work -24.13 *** 0.0 \n", + "tnc_single_ASC_no_auto_atwork  0.05 0.0 \n", + "tnc_single_ASC_no_auto_eatout_othdiscr_social  0.01 0.0 \n", + "tnc_single_ASC_no_auto_escort_othmaint_shopping  0.02 0.0 \n", + "tnc_single_ASC_no_auto_school  NA 0.0 \n", + "tnc_single_ASC_no_auto_univ -BIG *** 0.0 \n", + "tnc_single_ASC_no_auto_work  0.06 0.0 \n", + "walk_ASC_auto_deficient_atwork  1.41 0.0 \n", + "walk_ASC_auto_deficient_eatout  6.37 *** 0.0 \n", + "walk_ASC_auto_deficient_escort -4.04 *** 0.0 \n", + "walk_ASC_auto_deficient_othdiscr  3.94 *** 0.0 \n", + "walk_ASC_auto_deficient_othmaint  1.79 0.0 \n", + "walk_ASC_auto_deficient_school  2.75 ** 0.0 \n", + "walk_ASC_auto_deficient_shopping  4.06 *** 0.0 \n", + "walk_ASC_auto_deficient_social  4.82 *** 0.0 \n", + "walk_ASC_auto_deficient_univ  NA 0.0 \n", + "walk_ASC_auto_deficient_work  16.52 *** 0.0 \n", + "walk_ASC_auto_sufficient_atwork  1.36 0.0 \n", + "walk_ASC_auto_sufficient_eatout  3.04 ** 0.0 \n", + "walk_ASC_auto_sufficient_escort -4.20 *** 0.0 \n", + "walk_ASC_auto_sufficient_othdiscr  1.76 0.0 \n", + "walk_ASC_auto_sufficient_othmaint  1.42 0.0 \n", + "walk_ASC_auto_sufficient_school  0.40 0.0 \n", + "walk_ASC_auto_sufficient_shopping  0.27 0.0 \n", + "walk_ASC_auto_sufficient_social  2.08 * 0.0 \n", + "walk_ASC_auto_sufficient_univ  BIG *** 0.0 \n", + "walk_ASC_auto_sufficient_work -5.25 *** 0.0 \n", + "walk_ASC_no_auto_atwork  0.08 0.0 \n", + "walk_ASC_no_auto_eatout  0.05 0.0 \n", + "walk_ASC_no_auto_escort  0.03 0.0 \n", + "walk_ASC_no_auto_othdiscr  0.03 0.0 \n", + "walk_ASC_no_auto_othmaint  0.01 0.0 \n", + "walk_ASC_no_auto_school  0.15 0.0 \n", + "walk_ASC_no_auto_shopping  0.03 0.0 \n", + "walk_ASC_no_auto_social  0.02 0.0 \n", + "walk_ASC_no_auto_univ  BIG *** 0.0 \n", + "walk_ASC_no_auto_work  0.06 0.0 \n", + "walk_ferry_ASC_eatout_escort_othdiscr_othmaint_... -0.00 0.0 \n", + "walk_ferry_ASC_school_univ  NA 0.0 \n", + "walk_ferry_ASC_work  NA 0.0 \n", + "walk_light_rail_ASC_eatout_escort_othdiscr_othm...  0.01 0.0 \n", + "walk_light_rail_ASC_school_univ  NA 0.0 \n", + "walk_light_rail_ASC_work  NA 0.0 \n", + "walk_transit_ASC_auto_deficient_atwork -0.14 0.0 \n", + "walk_transit_ASC_auto_deficient_eatout -0.01 0.0 \n", + "walk_transit_ASC_auto_deficient_escort -0.22 0.0 \n", + "walk_transit_ASC_auto_deficient_othdiscr  0.05 0.0 \n", + "walk_transit_ASC_auto_deficient_othmaint -0.14 0.0 \n", + "walk_transit_ASC_auto_deficient_school  NA 0.0 \n", + "walk_transit_ASC_auto_deficient_shopping -0.04 0.0 \n", + "walk_transit_ASC_auto_deficient_social  0.06 0.0 \n", + "walk_transit_ASC_auto_deficient_univ  NA 0.0 \n", + "walk_transit_ASC_auto_deficient_work  NA 0.0 \n", + "walk_transit_ASC_auto_sufficient_atwork -0.18 0.0 \n", + "walk_transit_ASC_auto_sufficient_eatout -0.05 0.0 \n", + "walk_transit_ASC_auto_sufficient_escort -0.23 0.0 \n", + "walk_transit_ASC_auto_sufficient_othdiscr -0.04 0.0 \n", + "walk_transit_ASC_auto_sufficient_othmaint -0.06 0.0 \n", + "walk_transit_ASC_auto_sufficient_school  NA 0.0 \n", + "walk_transit_ASC_auto_sufficient_shopping -0.11 0.0 \n", + "walk_transit_ASC_auto_sufficient_social -0.03 0.0 \n", + "walk_transit_ASC_auto_sufficient_univ  NA 0.0 \n", + "walk_transit_ASC_auto_sufficient_work  NA 0.0 \n", + "walk_transit_ASC_no_auto_atwork  0.04 0.0 \n", + "walk_transit_ASC_no_auto_eatout  0.04 0.0 \n", + "walk_transit_ASC_no_auto_escort -0.03 0.0 \n", + "walk_transit_ASC_no_auto_othdiscr  0.04 0.0 \n", + "walk_transit_ASC_no_auto_othmaint  0.03 0.0 \n", + "walk_transit_ASC_no_auto_school  NA 0.0 \n", + "walk_transit_ASC_no_auto_shopping  0.03 0.0 \n", + "walk_transit_ASC_no_auto_social  0.03 0.0 \n", + "walk_transit_ASC_no_auto_univ  NA 0.0 \n", + "walk_transit_ASC_no_auto_work  NA 0.0 \n", + "walk_transit_CBD_ASC_atwork  4.28 *** 0.0 \n", + "walk_transit_CBD_ASC_eatout_escort_othdiscr_oth...  14.41 *** 0.0 \n", + "walk_transit_CBD_ASC_school_univ  7.24 *** 0.0 \n", + "walk_transit_CBD_ASC_work  21.27 *** 0.0 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  1.78 0.0 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  NA 0.0 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  1.24 0.0 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  2.22 * 0.0 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  1.64 0.0 \n", + "coefficient_name\\ncoef_test coef_test_eatout...  0.92 0.0 \n", + "coefficient_name\\ncoef_test coef_test_eatout... -1.20 0.0 \n", + "coefficient_name\\ncoef_test coef_test_school...  0.59 0.0 \n", + "coefficient_name\\ncoef_test coef_test_school...  NA 0.0 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with pd.option_context('display.max_rows', 999):\n", + " display(pd.concat({\n", + " \"model\": model.parameter_summary().data,\n", + " \"remodel\": remodel.parameter_summary().data,\n", + " }, axis=1).fillna(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "execution": { + "iopub.execute_input": "2025-06-26T02:27:37.943631Z", + "iopub.status.busy": "2025-06-26T02:27:37.943503Z", + "iopub.status.idle": "2025-06-26T02:27:38.022217Z", + "shell.execute_reply": "2025-06-26T02:27:38.021934Z", + "shell.execute_reply.started": "2025-06-26T02:27:37.943621Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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modelremodel
Number of CasesAggregate69971.00000069971.000000
Log Likelihood at ConvergenceAggregate-76508.289239-76502.093437
Per Case-1.093429-1.093340
Log Likelihood at Null ParametersAggregate-142469.530288-142469.530288
Per Case-2.036123-2.036123
Rho Squared w.r.t. Null ParametersAggregate0.4629850.463028
\n", + "
" + ], + "text/plain": [ + " model remodel\n", + "Number of Cases Aggregate 69971.000000 69971.000000\n", + "Log Likelihood at Convergence Aggregate -76508.289239 -76502.093437\n", + " Per Case -1.093429 -1.093340\n", + "Log Likelihood at Null Parameters Aggregate -142469.530288 -142469.530288\n", + " Per Case -2.036123 -2.036123\n", + "Rho Squared w.r.t. Null Parameters Aggregate 0.462985 0.463028" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "with pd.option_context('display.max_rows', 999):\n", + " display(pd.concat({\n", + " \"model\": model.estimation_statistics_raw(),\n", + " \"remodel\": remodel.estimation_statistics_raw(),\n", + " }, axis=1).fillna(\"\"))" + ] } ], "metadata": { @@ -4371,9 +13023,9 @@ "toc_visible": true }, "kernelspec": { - "display_name": "ESTER", + "display_name": "Aestival", "language": "python", - "name": "python3" + "name": "aestival" }, "language_info": { "codemirror_mode": { @@ -4385,7 +13037,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.15" + "version": "3.10.0" }, "toc": { "base_numbering": 1, From 5d19936aa90d13ae32e19f803179f05d79964200 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Wed, 25 Jun 2025 22:14:37 -0500 Subject: [PATCH 48/56] add to docs --- docs/users-guide/estimation-mode/larch.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/users-guide/estimation-mode/larch.md b/docs/users-guide/estimation-mode/larch.md index a1c7ee3ef6..da029b6365 100644 --- a/docs/users-guide/estimation-mode/larch.md +++ b/docs/users-guide/estimation-mode/larch.md @@ -316,3 +316,6 @@ The following notebooks include examples of modifying the model specification: This notebook includes a demonstration of modification to the SPEC file for the CDAP model. This model has a complex structure that is unique among the ActivitySim component models. +- [`17_tour_mode_choice.ipynb`](https://github.com/ActivitySim/activitysim/tree/main/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb): + This notebook includes a demonstration of modification to the spec, coefficients, + and coefficients template file for the tour mode choice model. From 42c007e73891789c477506402f2bc552cf1834ff Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Thu, 26 Jun 2025 10:46:54 -0500 Subject: [PATCH 49/56] union not addition on sets --- activitysim/estimation/larch/nonmand_tour_freq.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/activitysim/estimation/larch/nonmand_tour_freq.py b/activitysim/estimation/larch/nonmand_tour_freq.py index 7fab946375..c35d44453a 100644 --- a/activitysim/estimation/larch/nonmand_tour_freq.py +++ b/activitysim/estimation/larch/nonmand_tour_freq.py @@ -309,7 +309,7 @@ def nonmand_tour_freq_model( x_col="Label", p_col=segment_name, x_validator=set(chooser_data[segment_name].columns) - + set(alt_values[segment_name].columns), + | set(alt_values[segment_name].columns), expr_col="Expression", ) apply_coefficients(coefficients[segment_name], segment_model) From c2742a409a41d4a1bcbce66b57593e4bde783a68 Mon Sep 17 00:00:00 2001 From: Jeff Newman Date: Thu, 26 Jun 2025 10:47:05 -0500 Subject: [PATCH 50/56] restore nb kernel --- .../example_estimation/notebooks/17_tour_mode_choice.ipynb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb b/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb index 58246f47ad..535c1bedb7 100644 --- a/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb +++ b/activitysim/examples/example_estimation/notebooks/17_tour_mode_choice.ipynb @@ -13023,9 +13023,9 @@ "toc_visible": true }, "kernelspec": { - "display_name": "Aestival", + "display_name": "ESTER", "language": "python", - "name": "aestival" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -13037,7 +13037,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.0" + "version": "3.10.15" }, "toc": { "base_numbering": 1, From 9433a50d36106c69edf6b7c186d133cfdb8bf714 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Tue, 22 Jul 2025 09:34:06 -0700 Subject: [PATCH 51/56] blacken --- activitysim/abm/models/util/tour_destination.py | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/activitysim/abm/models/util/tour_destination.py b/activitysim/abm/models/util/tour_destination.py index b5eaeadd78..e98cac5875 100644 --- a/activitysim/abm/models/util/tour_destination.py +++ b/activitysim/abm/models/util/tour_destination.py @@ -9,7 +9,15 @@ from activitysim.abm.models.util import logsums as logsum from activitysim.abm.tables.size_terms import tour_destination_size_terms -from activitysim.core import config, estimation, los, simulate, tracing, workflow, expressions +from activitysim.core import ( + config, + estimation, + los, + simulate, + tracing, + workflow, + expressions, +) from activitysim.core.configuration.logit import TourLocationComponentSettings from activitysim.core.interaction_sample import interaction_sample from activitysim.core.interaction_sample_simulate import interaction_sample_simulate From d279c83d1fa923d2948a38abd637be2755630ad0 Mon Sep 17 00:00:00 2001 From: David Hensle Date: Thu, 24 Jul 2025 14:24:50 -0700 Subject: [PATCH 52/56] replacing conda with uv in estimation tests --- .github/workflows/core_tests.yml | 97 +++++++++----------------------- 1 file changed, 27 insertions(+), 70 deletions(-) diff --git a/.github/workflows/core_tests.yml b/.github/workflows/core_tests.yml index 1de3c5fcc0..e6aa672c28 100644 --- a/.github/workflows/core_tests.yml +++ b/.github/workflows/core_tests.yml @@ -323,64 +323,38 @@ jobs: needs: foundation env: python-version: "3.10" - label: linux-64 + label: win-64 defaults: run: - shell: bash -l {0} + shell: pwsh name: Estimation Notebooks Test - runs-on: ubuntu-latest + runs-on: windows-latest steps: - uses: actions/checkout@v4 - - name: Setup Miniforge - uses: conda-incubator/setup-miniconda@v3 + - name: Install uv + uses: astral-sh/setup-uv@v5 with: - miniforge-version: latest - mamba-version: "2.0.5" - conda-solver: classic - conda-remove-defaults: true - activate-environment: asim-test - python-version: ${{ env.python-version }} - - - name: Set cache date for year and month - run: echo "DATE=$(date +'%Y%m')" >> $GITHUB_ENV + version: "0.7.12" + enable-cache: true + cache-dependency-glob: "uv.lock" - - uses: actions/cache@v4 + - name: "Set up Python" + uses: actions/setup-python@v5 with: - path: ${{ env.CONDA }}/envs - key: ${{ env.label }}-conda-${{ hashFiles('conda-environments/github-actions-tests.yml') }}-${{ env.DATE }}-${{ env.CACHE_NUMBER }} - id: cache - - - name: Update environment - run: | - conda env update -n asim-test -f conda-environments/github-actions-tests.yml - if: steps.cache.outputs.cache-hit != 'true' - - - name: Install Graphviz - uses: ts-graphviz/setup-graphviz@v2 - - - name: Install Larch v6 - run: python -m pip install "larch>=6" "pandas<2" pydot + python-version-file: ".python-version" - name: Install activitysim - # installing without dependencies is faster, we trust that all needed dependencies - # are in the conda environment defined above. Also, this avoids pip getting - # confused and reinstalling tables (pytables). - run: | - python -m pip install -e . --no-deps - - - name: Conda checkup run: | - conda info -a - conda list + uv sync --locked --only-group github-action - name: Create Estimation Data run: | - python activitysim/examples/example_estimation/notebooks/est_mode_setup.py --household_sample_size 5000 + uv run python activitysim/examples/example_estimation/notebooks/est_mode_setup.py --household_sample_size 5000 - name: Test Estimation Notebooks run: | - python -m pytest activitysim/examples/example_estimation/notebooks/*.ipynb \ + uv run pytest activitysim/examples/example_estimation/notebooks/*.ipynb \ --nbmake-timeout=3000 \ --ignore=activitysim/examples/example_estimation/notebooks/01_estimation_mode.ipynb @@ -388,51 +362,34 @@ jobs: needs: foundation env: python-version: "3.10" - label: linux-64 + label: win-64 defaults: run: - shell: bash -l {0} + shell: pwsh name: estimation_edb_creation_test - runs-on: ubuntu-latest + runs-on: windows-latest steps: - uses: actions/checkout@v4 - - name: Setup Miniforge - uses: conda-incubator/setup-miniconda@v3 + - name: Install uv + uses: astral-sh/setup-uv@v5 with: - miniforge-version: latest - activate-environment: asim-test - python-version: ${{ env.python-version }} - - - name: Set cache date for year and month - run: echo "DATE=$(date +'%Y%m')" >> $GITHUB_ENV + version: "0.7.12" + enable-cache: true + cache-dependency-glob: "uv.lock" - - uses: actions/cache@v4 + - name: "Set up Python" + uses: actions/setup-python@v5 with: - path: ${{ env.CONDA }}/envs - key: ${{ env.label }}-conda-${{ hashFiles('conda-environments/github-actions-tests.yml') }}-${{ env.DATE }}-${{ env.CACHE_NUMBER }} - id: cache - - - name: Update environment - run: | - conda env update -n asim-test -f conda-environments/github-actions-tests.yml - if: steps.cache.outputs.cache-hit != 'true' + python-version-file: ".python-version" - name: Install activitysim - # installing without dependencies is faster, we trust that all needed dependencies - # are in the conda environment defined above. Also, this avoids pip getting - # confused and reinstalling tables (pytables). run: | - python -m pip install -e . --no-deps - - - name: Conda checkup - run: | - conda info -a - conda list + uv sync --locked --only-group github-action - name: Test Estimation EDB Creation run: | - python -m pytest activitysim/estimation/test/test_edb_creation/test_edb_formation.py --durations=0 + uv run pytest activitysim/estimation/test/test_edb_creation/test_edb_formation.py --durations=0 develop-docbuild: needs: foundation From 19d2bb10992799e6009a462f59c4afa8071d376c Mon Sep 17 00:00:00 2001 From: David Hensle Date: Thu, 24 Jul 2025 16:35:03 -0700 Subject: [PATCH 53/56] add requests to github-action dependencies --- pyproject.toml | 3 ++- uv.lock | 2 ++ 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 7ac5c25153..1b7ce99ca1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -160,9 +160,10 @@ github-action = [ "pytest==7.2", "pytest-cov", "pytest-regressions", + "requests>=2.32.3", "ruff", "zarr>=2,<3", - "zstandard" + "zstandard", ] [tool.uv] diff --git a/uv.lock b/uv.lock index 527124b1c7..b91cb048ec 100644 --- a/uv.lock +++ b/uv.lock @@ -107,6 +107,7 @@ github-action = [ { name = "pytest" }, { name = "pytest-cov" }, { name = "pytest-regressions" }, + { name = "requests" }, { name = "ruff" }, { name = "zarr", version = "2.18.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, { name = "zarr", version = "2.18.7", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" }, @@ -197,6 +198,7 @@ github-action = [ { name = "pytest", specifier = "==7.2" }, { name = "pytest-cov" }, { name = "pytest-regressions" }, + { name = "requests", specifier = ">=2.32.3" }, { name = "ruff" }, { name = "zarr", specifier = ">=2,<3" }, { name = "zstandard" }, From f50122acba2b882d379bf5e937434c81cbe5466d Mon Sep 17 00:00:00 2001 From: David Hensle Date: Fri, 25 Jul 2025 09:57:45 -0700 Subject: [PATCH 54/56] running with created virtual env instead --- .github/workflows/core_tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/core_tests.yml b/.github/workflows/core_tests.yml index e6aa672c28..6c95dadccf 100644 --- a/.github/workflows/core_tests.yml +++ b/.github/workflows/core_tests.yml @@ -350,7 +350,7 @@ jobs: - name: Create Estimation Data run: | - uv run python activitysim/examples/example_estimation/notebooks/est_mode_setup.py --household_sample_size 5000 + .venv\Scripts\python activitysim/examples/example_estimation/notebooks/est_mode_setup.py --household_sample_size 5000 - name: Test Estimation Notebooks run: | From aa5f20074ca284b3857e8476e6d22d8a277b90e0 Mon Sep 17 00:00:00 2001 From: Jeffrey Newman Date: Tue, 12 Aug 2025 10:42:21 -0500 Subject: [PATCH 55/56] Fix estimation notebook tests (#8) --- .github/workflows/core_tests.yml | 29 +++++++++++-------- .../build_full_mtc_example.py | 7 +++-- pyproject.toml | 2 ++ uv.lock | 27 ++++++++++++++++- 4 files changed, 49 insertions(+), 16 deletions(-) diff --git a/.github/workflows/core_tests.yml b/.github/workflows/core_tests.yml index 6c95dadccf..a0c225923f 100644 --- a/.github/workflows/core_tests.yml +++ b/.github/workflows/core_tests.yml @@ -332,6 +332,11 @@ jobs: steps: - uses: actions/checkout@v4 + - name: "Set up Python" + uses: actions/setup-python@v5 + with: + python-version-file: ".python-version" + - name: Install uv uses: astral-sh/setup-uv@v5 with: @@ -339,24 +344,24 @@ jobs: enable-cache: true cache-dependency-glob: "uv.lock" - - name: "Set up Python" - uses: actions/setup-python@v5 - with: - python-version-file: ".python-version" + - name: setup graphviz + uses: ts-graphviz/setup-graphviz@v2 - name: Install activitysim run: | - uv sync --locked --only-group github-action + uv sync --locked --group github-action - name: Create Estimation Data - run: | - .venv\Scripts\python activitysim/examples/example_estimation/notebooks/est_mode_setup.py --household_sample_size 5000 + run: > + uv run --group github-action python activitysim/examples/example_estimation/notebooks/est_mode_setup.py + --household_sample_size 5000 - name: Test Estimation Notebooks - run: | - uv run pytest activitysim/examples/example_estimation/notebooks/*.ipynb \ - --nbmake-timeout=3000 \ - --ignore=activitysim/examples/example_estimation/notebooks/01_estimation_mode.ipynb + run: > + uv run --group github-action pytest activitysim/examples/example_estimation/notebooks + --nbmake-timeout=3000 + --ignore=activitysim/examples/example_estimation/notebooks/01_estimation_mode.ipynb + --ignore-glob=activitysim/examples/example_estimation/notebooks/test-estimation-data/** estimation_edb_creation: needs: foundation @@ -434,4 +439,4 @@ jobs: github_token: ${{ secrets.GITHUB_TOKEN }} # Token is created automatically by Github Actions, no other config needed publish_dir: ./docs/_build/html - destination_dir: develop + destination_dir: develop \ No newline at end of file diff --git a/activitysim/examples/example_estimation/build_full_mtc_example.py b/activitysim/examples/example_estimation/build_full_mtc_example.py index 1d92a35acd..63878a7156 100644 --- a/activitysim/examples/example_estimation/build_full_mtc_example.py +++ b/activitysim/examples/example_estimation/build_full_mtc_example.py @@ -30,6 +30,7 @@ import os import shutil import subprocess +import sys import time from pathlib import Path @@ -74,7 +75,7 @@ def main(working_dir: Path, household_sample_size: int, skip_to_edb: bool = Fals subprocess.run( [ - "python", + sys.executable, "-m", "activitysim", "run", @@ -115,7 +116,7 @@ def main(working_dir: Path, household_sample_size: int, skip_to_edb: bool = Fals subprocess.run( [ - "python", + sys.executable, str(infer_py), str(pseudosurvey_dir), str(configs_dir), @@ -132,7 +133,7 @@ def main(working_dir: Path, household_sample_size: int, skip_to_edb: bool = Fals subprocess.run( [ - "python", + sys.executable, "-m", "activitysim", "run", diff --git a/pyproject.toml b/pyproject.toml index 1b7ce99ca1..c7814e601d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -157,11 +157,13 @@ github-action = [ "dask==2023.11", "isort==5.12.0", "nbmake==1.4.6", + "pydot>=4.0.1", "pytest==7.2", "pytest-cov", "pytest-regressions", "requests>=2.32.3", "ruff", + "xlsxwriter==3.2.5", "zarr>=2,<3", "zstandard", ] diff --git a/uv.lock b/uv.lock index b91cb048ec..b5cf49c6c9 100644 --- a/uv.lock +++ b/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.10" resolution-markers = [ "python_full_version >= '3.12'", @@ -104,11 +104,13 @@ github-action = [ { name = "dask" }, { name = "isort" }, { name = "nbmake" }, + { name = "pydot" }, { name = "pytest" }, { name = "pytest-cov" }, { name = "pytest-regressions" }, { name = "requests" }, { name = "ruff" }, + { name = "xlsxwriter" }, { name = "zarr", version = "2.18.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, { name = "zarr", version = "2.18.7", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" }, { name = "zstandard" }, @@ -195,11 +197,13 @@ github-action = [ { name = "dask", specifier = "==2023.11" }, { name = "isort", specifier = "==5.12.0" }, { name = "nbmake", specifier = "==1.4.6" }, + { name = "pydot", specifier = ">=4.0.1" }, { name = "pytest", specifier = "==7.2" }, { name = "pytest-cov" }, { name = "pytest-regressions" }, { name = "requests", specifier = ">=2.32.3" }, { name = "ruff" }, + { name = "xlsxwriter", specifier = "==3.2.5" }, { name = "zarr", specifier = ">=2,<3" }, { name = "zstandard" }, ] @@ -3143,6 +3147,18 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/e2/0d/8ba33fa83a7dcde13eb3c1c2a0c1cc29950a048bfed6d9b0d8b6bd710b4c/pydata_sphinx_theme-0.16.1-py3-none-any.whl", hash = "sha256:225331e8ac4b32682c18fcac5a57a6f717c4e632cea5dd0e247b55155faeccde", size = 6723264, upload-time = "2024-12-17T10:53:35.645Z" }, ] +[[package]] +name = "pydot" +version = "4.0.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pyparsing" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/50/35/b17cb89ff865484c6a20ef46bf9d95a5f07328292578de0b295f4a6beec2/pydot-4.0.1.tar.gz", hash = "sha256:c2148f681c4a33e08bf0e26a9e5f8e4099a82e0e2a068098f32ce86577364ad5", size = 162594, upload-time = "2025-06-17T20:09:56.454Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7e/32/a7125fb28c4261a627f999d5fb4afff25b523800faed2c30979949d6facd/pydot-4.0.1-py3-none-any.whl", hash = "sha256:869c0efadd2708c0be1f916eb669f3d664ca684bc57ffb7ecc08e70d5e93fee6", size = 37087, upload-time = "2025-06-17T20:09:55.25Z" }, +] + [[package]] name = "pygments" version = "2.19.1" @@ -4905,6 +4921,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/a4/1e/96fd96419fec1a37da998a1ca3d558f2cae2f6f3cd5015170371b05a2b6b/xarray-2025.4.0-py3-none-any.whl", hash = "sha256:b27defd082c5cb85d32c695708de6bb05c2838fb7caaf3f952982e602a35b9b8", size = 1290171, upload-time = "2025-04-29T23:27:57.059Z" }, ] +[[package]] +name = "xlsxwriter" +version = "3.2.5" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/a7/47/7704bac42ac6fe1710ae099b70e6a1e68ed173ef14792b647808c357da43/xlsxwriter-3.2.5.tar.gz", hash = "sha256:7e88469d607cdc920151c0ab3ce9cf1a83992d4b7bc730c5ffdd1a12115a7dbe", size = 213306, upload-time = "2025-06-17T08:59:14.619Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/fa/34/a22e6664211f0c8879521328000bdcae9bf6dbafa94a923e531f6d5b3f73/xlsxwriter-3.2.5-py3-none-any.whl", hash = "sha256:4f4824234e1eaf9d95df9a8fe974585ff91d0f5e3d3f12ace5b71e443c1c6abd", size = 172347, upload-time = "2025-06-17T08:59:13.453Z" }, +] + [[package]] name = "xmle" version = "0.1.26" From 744fc3c63a91fa8ced5e78c9afb6abb551d0bdec Mon Sep 17 00:00:00 2001 From: David Hensle Date: Tue, 23 Sep 2025 13:29:31 -0700 Subject: [PATCH 56/56] Update scheduling.py --- activitysim/estimation/larch/scheduling.py | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/activitysim/estimation/larch/scheduling.py b/activitysim/estimation/larch/scheduling.py index f398baf2d2..e0adb34e56 100644 --- a/activitysim/estimation/larch/scheduling.py +++ b/activitysim/estimation/larch/scheduling.py @@ -272,6 +272,17 @@ def mandatory_tour_scheduling_school_model( ) +def mandatory_tour_scheduling_univ_model( + edb_directory="output/estimation_data_bundle/{name}/", return_data=False +): + return schedule_choice_model( + name="mandatory_tour_scheduling_univ", + edb_directory=edb_directory, + return_data=return_data, + coefficients_file="tour_scheduling_univ_coefficients.csv", + ) + + def non_mandatory_tour_scheduling_model( edb_directory="output/estimation_data_bundle/{name}/", return_data=False ):