diff --git a/activitysim/abm/models/non_mandatory_scheduling.py b/activitysim/abm/models/non_mandatory_scheduling.py index 22f555b42a..a0acc62daa 100644 --- a/activitysim/abm/models/non_mandatory_scheduling.py +++ b/activitysim/abm/models/non_mandatory_scheduling.py @@ -14,8 +14,6 @@ from .util.school_escort_tours_trips import create_pure_school_escort_tours from .util.vectorize_tour_scheduling import vectorize_tour_scheduling -from activitysim.core.util import assign_in_place - logger = logging.getLogger(__name__) DUMP = False diff --git a/activitysim/abm/models/trip_scheduling.py b/activitysim/abm/models/trip_scheduling.py index f8345650d8..dc5bfacef1 100644 --- a/activitysim/abm/models/trip_scheduling.py +++ b/activitysim/abm/models/trip_scheduling.py @@ -8,7 +8,15 @@ from activitysim.abm.models.util import estimation from activitysim.abm.models.util.trip import cleanup_failed_trips, failed_trip_cohorts -from activitysim.core import chunk, config, inject, logit, pipeline, tracing +from activitysim.core import ( + chunk, + config, + inject, + logit, + pipeline, + tracing, + expressions, +) from activitysim.core.util import reindex from .util.school_escort_tours_trips import split_out_school_escorting_trips @@ -36,6 +44,7 @@ DEPARTURE_MODE = "departure" DURATION_MODE = "stop_duration" +RELATIVE_MODE = "relative" PROBS_JOIN_COLUMNS_DEPARTURE_BASED = [ "primary_purpose", "outbound", @@ -43,6 +52,7 @@ "trip_num", ] PROBS_JOIN_COLUMNS_DURATION_BASED = ["outbound", "stop_num"] +PROBS_JOIN_COLUMNS_RELATIVE_BASED = ["outbound", "periods_left"] def set_tour_hour(trips, tours): @@ -181,6 +191,7 @@ def schedule_trips_in_leg( failfix = model_settings.get(FAILFIX, FAILFIX_DEFAULT) depart_alt_base = model_settings.get("DEPART_ALT_BASE", 0) scheduling_mode = model_settings.get("scheduling_mode", "departure") + preprocessor_settings = model_settings.get("preprocessor", None) if scheduling_mode == "departure": probs_join_cols = model_settings.get( @@ -190,10 +201,14 @@ def schedule_trips_in_leg( probs_join_cols = model_settings.get( "probs_join_cols", PROBS_JOIN_COLUMNS_DURATION_BASED ) + elif scheduling_mode == "relative": + probs_join_cols = model_settings.get( + "probs_join_cols", PROBS_JOIN_COLUMNS_RELATIVE_BASED + ) else: logger.error( "Invalid scheduling mode specified: {0}.".format(scheduling_mode), - "Please select one of ['departure', 'stop_duration'] and try again.", + "Please select one of ['departure', 'stop_duration', 'relative'] and try again.", ) # logger.debug("%s scheduling %s trips" % (trace_label, trips.shape[0])) @@ -232,18 +247,35 @@ def schedule_trips_in_leg( ADJUST_NEXT_DEPART_COL = "latest" trips.next_trip_id = trips.next_trip_id.where(~is_final, NO_TRIP_ID) + network_los = inject.get_injectable("network_los") + locals_dict = {"network_los": network_los} + locals_dict.update(config.get_model_constants(model_settings)) + first_trip_in_leg = True for i in range(trips.trip_num.min(), trips.trip_num.max() + 1): - if outbound or scheduling_mode == DURATION_MODE: + nth_trace_label = tracing.extend_trace_label(trace_label, "num_%s" % i) + + # - annotate trips + if preprocessor_settings: + expressions.assign_columns( + df=trips, + model_settings=preprocessor_settings, + locals_dict=locals_dict, + trace_label=nth_trace_label, + ) + + if ( + outbound + or (scheduling_mode == DURATION_MODE) + or (scheduling_mode == RELATIVE_MODE) + ): # iterate in ascending trip_num order nth_trips = trips[trips.trip_num == i] else: # iterate over inbound trips in descending trip_num order, skipping the final trip nth_trips = trips[trips.trip_num == trips.trip_count - i] - nth_trace_label = tracing.extend_trace_label(trace_label, "num_%s" % i) - choices = ps.make_scheduling_choices( nth_trips, scheduling_mode, @@ -265,6 +297,12 @@ def schedule_trips_in_leg( ) choices = choices.fillna(trips[ADJUST_NEXT_DEPART_COL]) + if scheduling_mode == RELATIVE_MODE: + # choices are relative to the previous departure time + choices = nth_trips.earliest + choices + # need to update the departure time based on the choice + update_tour_earliest(trips, choices) + # adjust allowed depart range of next trip has_next_trip = nth_trips.next_trip_id != NO_TRIP_ID if has_next_trip.any(): @@ -437,9 +475,9 @@ def trip_scheduling(trips, tours, chunk_size, trace_hh_id): ] estimator.write_choosers(trips_df[chooser_cols_for_estimation]) - probs_spec = pd.read_csv( - config.config_file_path("trip_scheduling_probs.csv"), comment="#" - ) + probs_spec_file = model_settings.get("PROBS_SPEC", "trip_scheduling_probs.csv") + logger.debug(f"probs_spec_file: {config.config_file_path(probs_spec_file)}") + probs_spec = pd.read_csv(config.config_file_path(probs_spec_file), comment="#") # FIXME for now, not really doing estimation for probabilistic model - just overwriting choices # besides, it isn't clear that named coefficients would be helpful if we had some form of estimation # coefficients_df = simulate.read_model_coefficients(model_settings) @@ -499,6 +537,11 @@ def trip_scheduling(trips, tours, chunk_size, trace_hh_id): failed = choices.reindex(trips_chunk.index).isnull() logger.info("%s %s failed", trace_label_i, failed.sum()) + if (failed.sum() > 0) & ( + model_settings.get("scheduling_mode") == "relative" + ): + raise RuntimeError("failed trips with relative scheduling mode") + if not is_last_iteration: # boolean series of trips whose leg scheduling failed failed_cohorts = failed_trip_cohorts(trips_chunk, failed) diff --git a/activitysim/abm/models/util/probabilistic_scheduling.py b/activitysim/abm/models/util/probabilistic_scheduling.py index aab2e8d708..6fc7689a64 100644 --- a/activitysim/abm/models/util/probabilistic_scheduling.py +++ b/activitysim/abm/models/util/probabilistic_scheduling.py @@ -172,10 +172,22 @@ def _preprocess_scheduling_probs( ) elif scheduling_mode == "stop_duration": chooser_probs = _preprocess_stop_duration_probs(choosers) + elif scheduling_mode == "relative": + # creating a dataframe with just the trip_id as index and alternatives as columns + probs_cols = [ + c + for c in probs_spec.columns + if ((c not in probs_join_cols) & (c.isnumeric())) + ] + chooser_probs = choosers.loc[:, probs_cols] + chooser_probs = chooser_probs.div(chooser_probs.sum(axis=1), axis=0) + assert ( + ~chooser_probs.isna().values.any() + ), f"Missing probabilities for trips \n {chooser_probs[chooser_probs.isna().any(axis=1)].index}" else: logger.error( "Invalid scheduling mode specified: {0}.".format(scheduling_mode), - "Please select one of ['departure', 'stop_duration'] and try again.", + "Please select one of ['departure', 'stop_duration', 'relative'] and try again.", ) # probs should sum to 1 with residual probs resulting in choice of 'fail' @@ -196,6 +208,12 @@ def _postprocess_scheduling_choices( # convert alt choice index to depart time (setting failed choices to -1) failed = choices == choice_cols.get_loc("fail") + if scheduling_mode == "relative": + if failed.any(): + RuntimeError( + f"Failed trips in realtive mode for {failed.sum()} trips: {choosers[failed]}" + ) + # For the stop duration-based probabilities, the alternatives are offsets that # get applied to trip-specific departure and arrival times, so depart_alt_base # is a column/series rather than a scalar. @@ -334,7 +352,11 @@ def make_scheduling_choices( if failed.any(): choices = choices[~failed] - if all([check_col in choosers_df.columns for check_col in ["earliest", "latest"]]): + if all( + [check_col in choosers_df.columns for check_col in ["earliest", "latest"]] + ) & (scheduling_mode != "relative"): + # check to make sure choice does not come before previously scheduled trip or after end of tour + # does not apply if choices are relative to previous trip depart assert (choices >= choosers_df.earliest[~failed]).all() assert (choices <= choosers_df.latest[~failed]).all() diff --git a/activitysim/examples/prototype_mwcog/configs/trip_scheduling.yaml b/activitysim/examples/prototype_mwcog/configs/trip_scheduling.yaml index a006e7436b..5bca29c19e 100644 --- a/activitysim/examples/prototype_mwcog/configs/trip_scheduling.yaml +++ b/activitysim/examples/prototype_mwcog/configs/trip_scheduling.yaml @@ -1,10 +1,27 @@ # int to add to probs column index to get time period it represents. # e.g. depart_alt_base = 5 means first column (column 0) represents period 5 -DEPART_ALT_BASE: 1 +DEPART_ALT_BASE: 0 MAX_ITERATIONS: 100 #FAILFIX: drop_and_cleanup FAILFIX: choose_most_initial +# --- relative trip scheduling settings +PROBS_SPEC: trip_scheduling_probs_purpose_stops.csv + +scheduling_mode: relative + +probs_join_cols: + - periods_left_min + - periods_left_max + - outbound + - tour_purpose_grouped + - half_tour_stops_remaining_grouped + +preprocessor: + SPEC: trip_scheduling_preprocessor + DF: choosers + TABLES: + - tours \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/trip_scheduling_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/trip_scheduling_preprocessor.csv new file mode 100644 index 0000000000..732a58d473 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_scheduling_preprocessor.csv @@ -0,0 +1,8 @@ +Description,Target,Expression +,periods_left,(df.latest - df.earliest) +# binning the periods differently for inbound and outbound +,periods_left_min,"np.where(df['outbound'], periods_left.clip(upper=25), periods_left.clip(upper=34))" +,periods_left_max,"np.where(((periods_left >= 25) & (df['outbound'])) | ((periods_left >= 34) & (~df['outbound'])), 47, periods_left)" +,tour_purpose,"reindex(tours.tour_type, df.tour_id)" +,tour_purpose_grouped,"np.where(tour_purpose.isin(['work','school','univ']), 'mand', 'non_mand')" +,half_tour_stops_remaining_grouped,(df.trip_count - df.trip_num).clip(upper=1) \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/trip_scheduling_probs_purpose_stops.csv b/activitysim/examples/prototype_mwcog/configs/trip_scheduling_probs_purpose_stops.csv new file mode 100644 index 0000000000..411be00eb2 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_scheduling_probs_purpose_stops.csv @@ -0,0 +1,245 @@ +periods_left_min,periods_left_max,outbound,tour_purpose_grouped,half_tour_stops_remaining_grouped,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,All +0,0,True,non_mand,0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0 +0,0,True,non_mand,1,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0 +0,0,True,mand,0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0 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choice logsums. Alternatives: Available time periods in the tour window (i.e. tour start and end period). When processing stops on work tours, the available time periods is constrained by the at-work subtour start and end period as well. +In order to avoid trip failing, a new probabalisitic trip scheduling mode was developed named "relative". +When setting the _scheduling_mode_ option to relative, trips are scheduled relative to the previously scheduled trips. +The first trip still departs when the tour starts and for every subsequet trip, the choices are selected with respect to +the previous trip depart time. Inbound trips are no longer handled in reverse order. The key to this relative mode is to +index the probabilities based on how much time is remaining on the tour. For tours that include subtours, the time remaining will +be based on the subtour start time for outbound trips and will resume again for inbound trips after the subtour ends. +By indexing the probabilities based on time remaining and scheduling relative to the previous trip, scheduling trips in relative +mode will not fail. + +An example of trip scheduling in relative mode is included in the :ref:`prototype_mwcog` example. In this example, trip +scheduling probabilities are indexed by the following columns: + * periods_left_min: the minimum bin for the number of time periods left on the tour. + * periods_left_max: the maximum bin for the number of time periods left on the tour. This is the same as periods_left_min until the final time period bin. + * outbound: whether the trip occurs on the outbound leg of a tour. + * tour_purpose_grouped: Tour purpose grouped into mandatory and non-mandatory categories + * half_tour_stops_remaining_grouped: The number of stops remaining on the half tour with the categories of 0 and 1+ +Each of these variables are listed as merge columns in the trip_scheduling.yaml file and are declared in the trip scheduling preprocessor. +The variables above attempt to balance the statistics available for probability creation with the amount of segmentation of trip characteristics. + The main interface to the trip scheduling model is the :py:func:`~activitysim.abm.models.trip_scheduling.trip_scheduling` function. This function is registered as an Inject step in the example Pipeline.