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How to use merge_file_data method in autotest

Best Python code snippet using autotest_python

generate_preprocessed_data.py

Source:generate_preprocessed_data.py

...124        processed_file_data[filename] = file_data125    return processed_file_data126# processed_file_data = process_generic_file_data()127# %%128def merge_file_data(processed_file_data):129    dfs = [130        filedata.df131        for filedata in processed_file_data.values()132        if filedata.granularity == ["ACCIDENT_NO"]133    ]134    df_merged = reduce(135        lambda left, right: pd.merge(left, right, on=["ACCIDENT_NO"], how="outer"), dfs136    )137    vehicle_df = processed_file_data["VEHICLE.csv"].df138    df_merged = pd.merge(vehicle_df, df_merged, on=["ACCIDENT_NO"], how="outer")139    person_df = processed_file_data["PERSON.csv"].df140    df_merged = pd.merge(141        person_df, df_merged, on=["ACCIDENT_NO", "VEHICLE_ID"], how="outer"142    )143    return df_merged144# Some specific treatment for that feature145# %%146def categorise_helmet_belt_worn(df):147    df = df.astype({"HELMET_BELT_WORN": int})148    conversion = {149        1: "security_worn",150        3: "security_worn",151        6: "security_worn",152        8: "other",153        2: "security_not_worn ",154        4: "security_not_worn ",155        5: "security_not_worn ",156        7: "security_not_worn ",157    }158    df.loc[:, "HELMET_BELT_WORN"] = df.HELMET_BELT_WORN.apply(lambda x: conversion[x])159    return df160# %%161def main():162    processed_file_data = process_generic_file_data()163    merged = merge_file_data(processed_file_data)164    merged = merged.dropna()  # we can come back later on that choice165    merged = categorise_helmet_belt_worn(merged)166    # putting labels at the end167    merged = merged[168        [column for column in merged.columns if column != "INJ_LEVEL"] + ["INJ_LEVEL"]169    ]170    merged.to_csv(PROCESSED_DATA_FOLDER, index=False)171    return merged172# %%173if __name__ == "__main__":174    df = main()...

2.extract_feature_px4.py

Source:2.extract_feature_px4.py

...4Train LSTM Model5"""6if __name__ == '__main__':7    toolConfig.select_mode("PX4")8    # pd_csv = CyLSTM.merge_file_data(f"{toolConfig.ARDUPILOT_LOG_PATH}/logs/ulg_changed/csv")9    # CyLSTM.fit_trans(pd_csv)10    lstm = CyLSTM(100, 512)11    feature = lstm.extract_feature(f"{toolConfig.ARDUPILOT_LOG_PATH}/logs/ulg_changed/csv")12    # Save...

2.extract_feature.py

Source:2.extract_feature.py

...3"""4Train LSTM Model5"""6if __name__ == '__main__':7    # pd_csv = CyLSTM.merge_file_data(f"{toolConfig.ARDUPILOT_LOG_PATH}/logs/bin_ga/csv")8    # CyLSTM.fit_trans(pd_csv)9    lstm = CyLSTM(100, 512)10    feature = lstm.extract_feature(f"{toolConfig.ARDUPILOT_LOG_PATH}/logs/bin_ga/csv")11    # Save...

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