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import os |
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from lib.utilities import serialize |
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from lib.data_helpers import data_utils |
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from lib.experiment_specs import study_config |
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def select_test_appcodes(mc): |
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""" |
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purpose: selects a set of appcodes whose data will be used to test the pipeline quickly. Specifically, |
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it selects 50 active appcodes (i.e. have use data in past 3 days) and 25 appcodes inactive appcodes |
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input: the clean master user df |
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""" |
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last_survey_complete = data_utils.get_last_survey() |
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code = study_config.surveys[last_survey_complete]["Code"] |
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print(f"\n Selecting test codes. last survey complete is {last_survey_complete}") |
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active_appcodes = list(mc.loc[(mc[f"{code}_Complete"]=="Complete")&(mc["ActiveStatus"]=="Normal"),"AppCode"]) |
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inactive_appcodes = list(mc.loc[(mc[f"R_Complete"]!="Complete"),"AppCode"]) |
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test_codes = {"AppCode":active_appcodes[50:100]+inactive_appcodes[25:50]} |
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serialize.save_pickle(test_codes, path = os.path.join("data","external","dropbox_confidential_test","TestCodes"),df_bool = False) |
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return test_codes |
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def save_test_df(df, path): |
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""" |
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subsets the df to include testcodes |
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Parameters |
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---------- |
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df - any df that is about to get saved |
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path - the path to save the df (in the test data folders) |
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""" |
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config_user_dict = serialize.open_yaml("config_user.yaml") |
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if config_user_dict["local"]["test"] == False: |
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test_codes = serialize.open_pickle(os.path.join("data", "external", "dropbox_confidential_test", "TestCodes"), df_bool=False) |
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test_appcodes = test_codes["AppCode"] |
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df = df.loc[df["AppCode"].isin(test_appcodes)] |
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serialize.save_pickle(df,path) |
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print(df.dtypes) |
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try: |
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serialize.save_hdf(df, path) |
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except: |
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print("couldn't save hdf!") |
