updated links in README and tests

BXYMartin · BXYMartin · commit 5f7dc3de4a72 · 2020-02-14T10:10:44.000+08:00
diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
-# ClearSkyPy
-[![Build Status](https://travis-ci.org/BXYMartin/Python-ClearSkyPy.svg?branch=master)](https://travis-ci.org/BXYMartin/Python-ClearSkyPy)
-[![Latest Version](https://img.shields.io/github/v/release/bxymartin/python-clearskypy)](https://test.pypi.org/project/ClearSkyPy/)
+# IrradPy
+[![Build Status](https://travis-ci.org/BXYMartin/Python-irradpy.svg?branch=master)](https://travis-ci.org/BXYMartin/Python-irradpy)
+[![Latest Version](https://img.shields.io/github/v/release/bxymartin/python-irradpy)](https://test.pypi.org/project/irradpy/)
 
 Python script to download data from gesdisc.eosdis.nasa.gov for Clear Sky Model, extract variables from the MERRA-2 reanalysis database and model of clear-sky irradiance.
 
@@ -30,26 +30,26 @@ Python script to download data from gesdisc.eosdis.nasa.gov for Clear Sky Model,
 #### Use inside Python Script
 ``` python
 # Linux and Unix Users
-import clearskypy
+import irradpy
 # Run Downloader
-clearskypy.downloader.run(auth={"uid":"USERNAME", "password": "PASSWORD"})
+irradpy.downloader.run(auth={"uid":"USERNAME", "password": "PASSWORD"})
 # Run Model
-clearskypy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, dataset_dir).REST2v5()
-clearskypy.model.ClearSkyMAC2(latitudes, longitudes, elevations, time, dataset_dir).MAC2()
+irradpy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, dataset_dir).REST2v5()
+irradpy.model.ClearSkyMAC2(latitudes, longitudes, elevations, time, dataset_dir).MAC2()
 
 
 # Windows Users Only:
-import clearskypy
+import irradpy
 import multiprocessing
 # Important Note: If you're using windows, make sure to wrap the function.
 if __name__ == "__main__":
     multiprocessing.freeze_support()
-    clearskypy.downloader.run(auth={"uid":"USERNAME", "password": "PASSWORD"})
+    irradpy.downloader.run(auth={"uid":"USERNAME", "password": "PASSWORD"})
     
 # More Examples
 
 # Download All Data From 2018-01-01 To 2018-01-02
-clearskypy.downloader.run(auth={"uid":"USERNAME", "password": "PASSWORD"},
+irradpy.downloader.run(auth={"uid":"USERNAME", "password": "PASSWORD"},
     initial_year=2018, final_year=2018,
     initial_month=1, final_month=1,
     initial_day=1, final_day=2,
@@ -62,8 +62,8 @@ clearskypy.downloader.run(auth={"uid":"USERNAME", "password": "PASSWORD"},
 # Run clear sky model from 2018-01-01 To 2018-01-02
 time_delta = 10  # minute
 timedef = [('2018-01-01T00:00:00', '2018-01-02T0:00:00')]
-time = clearskypy.model.timeseries_builder(timedef, time_delta, np.size(latitudes))
-clearskypy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, dataset_dir).REST2v5()
+time = irradpy.model.timeseries_builder(timedef, time_delta, np.size(latitudes))
+irradpy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, dataset_dir).REST2v5()
 ```
 
 ``` python
@@ -117,7 +117,7 @@ clearskypy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, datase
     connection_num : Optional[int]
         Number of Connections for each file to be downloaded simutanously.
         
-    #clearskypy.model.timeseries_builder:
+    #irradpy.model.timeseries_builder:
     timedef: list [(start time , end time)], optional — specify the start 
         time(s) and end time(s) of the location(s) of interest.
     time_delta: integer, optional — specify the temporal resolution of the 
@@ -126,7 +126,7 @@ clearskypy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, datase
         if timedef less than num_station, timeseries_builder will expand it 
         for every station.
     
-    #clearskypy.model.clearSkyRadiation_MAC2.py && clearskypy.model.clearSkyRadiation_REST2v5.py:
+    #irradpy.model.clearSkyRadiation_MAC2.py && irradpy.model.clearSkyRadiation_REST2v5.py:
     
     latitudes: numpy.ndarray, float, compulsory — Define the latitude(s) of the 
         location(s) of interest, size must match longitudes. 
@@ -144,7 +144,7 @@ clearskypy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, datase
 
 #### Run Package From Shell
 ``` bash
-python -m clearskypy.downloader.socket --uid USERNAME --password PASSWORD
+python -m irradpy.downloader.socket --uid USERNAME --password PASSWORD
 
 usage: socket.py [-h] [--collection_names VAR_NAMES]
                  [--download_dir DOWNLOAD_DIR] [--initial_year INITIAL_YEAR]
@@ -208,7 +208,7 @@ python setup.py test
 #### Package
 ```
 .
-├── clearskypy
+├── irradpy
 │   ├── __init__.py
 │   ├── downloader
 │   │   ├── __init__.py
@@ -248,5 +248,5 @@ python setup.py install
 ```
 With python package:
 ``` bash
-pip install -i https://test.pypi.org/simple/ ClearSkyPy
+pip install -i https://test.pypi.org/simple/ irradpy
 ```
diff --git a/example/example_clearsky.py b/example/example_clearsky.py
@@ -1,5 +1,5 @@
 import numpy as np
-import clearskypy
+import irradpy
 import os
 # dependency on matplotlib >=3.1
 import matplotlib
@@ -16,31 +16,31 @@
     # set some example latitudes, longitudes and elevations
     # latitudes range from -90 (south pole) to +90 (north pole) in degrees
     latitudes = np.array([[1.300341, 39.97937]])
-    
+
     # longitudes range from -180 (west) through 0 at prime meridian to +180 (east)
     longitudes = np.array([[103.771663, 116.34653]])
-    
+
     # elevations are in metres, this influences some solar elevation angles and scale height corrections
     elevations = np.array([[43, 53]])
 
     # timedef is a list of pandas time series definition for each location defined.
     # Note that an individual time series can be specified per site
     timedef = [pd.date_range(start='2018-01-01T20:00:00', end='2018-01-02T15:00:00', freq='10T'),
                pd.date_range(start='2018-01-02T20:00:00', end='2018-01-03T15:00:00', freq='10T')]
-    
+
     # use timeseries_builder to build time series for different station
-    time = clearskypy.model.timeseries_builder(timedef, np.size(latitudes))
+    time = irradpy.model.timeseries_builder(timedef, np.size(latitudes))
 
     # specify where the downloaded dataset is. It is best to use the os.path.join function
     dataset_dir = os.path.join(os.getcwd(), 'MERRA2_data', '2018-1-1~2018-1-3 rad-slv-aer-asm [-90,-180]~[90,180]', '')
 
     # build the clear-sky REST2v5 model object
-    test_rest2 = clearskypy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, dataset_dir, pandas=True)
+    test_rest2 = irradpy.model.ClearSkyREST2v5(latitudes, longitudes, elevations, time, dataset_dir, pandas=True)
     # run the REST2v5 clear-sky model  output is a list of pandas.Dataframe for each station. col: GHI, DNI, DIF, row: time
     rest2_output = test_rest2.REST2v5()
 
     # create the MAC2 model class object
-    test_mac = clearskypy.model.ClearSkyMAC2(latitudes, longitudes, elevations, time, dataset_dir, pandas=True)
+    test_mac = irradpy.model.ClearSkyMAC2(latitudes, longitudes, elevations, time, dataset_dir, pandas=True)
     # run the MAC2 model  output is a list of pandas.Dataframe for each station  col: GHI, DNI, DIF, row: time
     mac2_output = test_mac.MAC2()
 
diff --git a/example/example_downloader.py b/example/example_downloader.py
@@ -1,5 +1,5 @@
 from multiprocessing import freeze_support
-import clearskypy
+import irradpy
 import os
 from getpass import getpass
 
@@ -73,7 +73,7 @@ def setUp(self):
         }
 
     def download(self):
-        clearskypy.downloader.run(
+        irradpy.downloader.run(
             auth={"uid": self.username, "password": self.password},
             initial_year=self.initial_year,
             final_year=self.final_year,
diff --git a/example/example_extractor.py b/example/example_extractor.py
@@ -1,5 +1,5 @@
 import numpy as np
-import clearskypy
+import irradpy
 import os
 # dependency on matplotlib >=3.1
 import matplotlib
@@ -30,7 +30,7 @@
                pd.date_range(start='2018-01-02T20:00:00', end='2018-01-03T15:00:00', freq='10T')]
 
     # use timeseries_builder to build time series for different station
-    time = clearskypy.model.timeseries_builder(timedef, np.size(latitudes))
+    time = irradpy.model.timeseries_builder(timedef, np.size(latitudes))
 
     # specify where the downloaded dataset is. It is best to use the os.path.join function
     dataset_dir = os.path.join(os.getcwd(), 'MERRA2_data', '2018-1-1~2018-1-3 rad-slv-aer-asm [-90,-180]~[90,180]', '')
@@ -39,7 +39,7 @@
     variables = ['SWGDN', 'SWGDNCLR']
 
     # extract the variable from the dataset
-    MERRA2data = clearskypy.extractor.extractor(latitudes, longitudes, elevations, time, variables, dataset_dir, pandas=True)
+    MERRA2data = irradpy.extractor.extractor(latitudes, longitudes, elevations, time, variables, dataset_dir, pandas=True)
 
 
     # Save the data to file, each site = new file
diff --git a/test/test_downloader.py b/test/test_downloader.py
@@ -1,5 +1,5 @@
 from multiprocessing import freeze_support
-import clearskypy
+import irradpy
 import unittest
 import os
 
@@ -69,7 +69,7 @@ def setUp(self):
         }
 
     def test_download(self):
-        clearskypy.downloader.run(
+        irradpy.downloader.run(
             auth={"uid": self.username, "password": self.password},
             initial_year=self.initial_year,
             final_year=self.final_year,
diff --git a/test/test_extractor.py b/test/test_extractor.py
@@ -1,5 +1,5 @@
 import numpy as np
-import clearskypy
+import irradpy
 
 
 def test_extract_MERRA2(lats, lons, datavecs, elevs):
@@ -24,10 +24,10 @@ def test_extract_MERRA2(lats, lons, datavecs, elevs):
     slvpath = 'path to slv dataset'
     asmpath = 'path to asm dataset'
 
-    aer_var = clearskypy.extractor.extract_dataset(lats, lons, aerpath, aer_pool, datavecs)
-    rad_var = clearskypy.extractor.extract_dataset(lats, lons, radpath, rad_pool, datavecs)
-    slv_var = clearskypy.extractor.extract_dataset(lats, lons, slvpath, slv_pool, datavecs)
-    asm_var = clearskypy.extractor.extract_dataset(lats, lons, asmpath, asm_pool, datavecs, interpolate=False)
+    aer_var = irradpy.extractor.extract_dataset(lats, lons, aerpath, aer_pool, datavecs)
+    rad_var = irradpy.extractor.extract_dataset(lats, lons, radpath, rad_pool, datavecs)
+    slv_var = irradpy.extractor.extract_dataset(lats, lons, slvpath, slv_pool, datavecs)
+    asm_var = irradpy.extractor.extract_dataset(lats, lons, asmpath, asm_pool, datavecs, interpolate=False)
 
     tot_aer_ext = aer_var[1]
     AOD_550 = aer_var[0]
@@ -56,7 +56,7 @@ def test_extract_dataset_list():
     date = ['2019-01-01T12:30:00', '2019-01-04T11:45:00', '2019-01-05T01:30:00']
     datapathlist = ['path to dataset1', 'path to dataset2']
     rad_pool = ['ALBEDO']
-    test = clearskypy.extractor.extract_dataset_list(lats, lons, datapathlist, rad_pool, date, interpolate=True)
+    test = irradpy.extractor.extract_dataset_list(lats, lons, datapathlist, rad_pool, date, interpolate=True)
     print(test)
 
 
