Remove obsolete comments.
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6b487fcf7b
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3c0585a566
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@ -14,7 +14,6 @@ from src.features import empatica_data_yield as edy
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pd.set_option('display.max_columns', 20)
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def straw_cleaning(sensor_data_files, provider):
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# TODO (maybe): reorganize the script based on the overall
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features = pd.read_csv(sensor_data_files["sensor_data"][0])
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@ -23,7 +23,7 @@ def format_timestamp(x):
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return tstring
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def extract_ers_from_file(esm_df, device_id): # TODO: session_id groupby -> spremeni naziv segmenta
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def extract_ers_from_file(esm_df, device_id):
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pd.set_option("display.max_rows", None)
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pd.set_option("display.max_columns", None)
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@ -60,9 +60,7 @@ def extract_ers_from_file(esm_df, device_id): # TODO: session_id groupby -> spre
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return extracted_ers[["label", "event_timestamp", "length", "shift", "shift_direction", "device_id"]]
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# TODO: potrebno preveriti kako se izvaja iskanje prek device_id -> na tem temelji tudi proces ekstrahiranja ERS
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if snakemake.params["stage"] == "extract": # TODO: najprej preveri ustreznost umeščenosti v RAPIDS pipelineu
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if snakemake.params["stage"] == "extract":
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esm_df = pd.read_csv(input_data_files['esm_raw_input'])
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with open(input_data_files['pid_file'], 'r') as stream:
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