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Author SHA1 Message Date
junos bb1e1900a4 Add a note to think about. 2023-03-27 11:56:09 +02:00
junos c35c75682f Add todo to rename a column. 2023-03-27 11:46:04 +02:00
1 changed files with 3 additions and 1 deletions

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@ -47,12 +47,14 @@ def extract_ers_from_file(esm_df, device_id): # TODO: session_id groupby -> spre
# Extract time-relevant information # Extract time-relevant information
extracted_ers = esm_df.groupby(["device_id", "esm_session"])['timestamp'].apply(lambda x: math.ceil((x.max() - x.min()) / 1000)).reset_index() # in rounded up seconds extracted_ers = esm_df.groupby(["device_id", "esm_session"])['timestamp'].apply(lambda x: math.ceil((x.max() - x.min()) / 1000)).reset_index() # in rounded up seconds
extracted_ers = extracted_ers[extracted_ers["timestamp"] <= 15 * 60].reset_index(drop=True) # ensure that the longest duration of the questionnaire anwsering is 15 min extracted_ers = extracted_ers[extracted_ers["timestamp"] <= 15 * 60].reset_index(drop=True) # ensure that the longest duration of the questionnaire anwsering is 15 min
# TODO: Rename "timestamp" column meaningfully.
time_before_questionnaire = 30 * 60 # in seconds (30 minutes) time_before_questionnaire = 30 * 60 # in seconds (30 minutes)
extracted_ers["label"] = "straw_event_" + snakemake.params["pid"] + "_" + extracted_ers.index.astype(str).str.zfill(3) extracted_ers["label"] = "straw_event_" + snakemake.params["pid"] + "_" + extracted_ers.index.astype(str).str.zfill(3)
extracted_ers["event_timestamp"] = esm_df.groupby("esm_session")['timestamp'].min().reset_index()['timestamp'] extracted_ers["event_timestamp"] = esm_df.groupby("esm_session")['timestamp'].min().reset_index()['timestamp']
extracted_ers["length"] = (extracted_ers["timestamp"] + time_before_questionnaire).apply(lambda x: format_timestamp(x)) extracted_ers["length"] = (extracted_ers["timestamp"] + time_before_questionnaire).apply(lambda x: format_timestamp(x))
# TODO: Think about adding questionnaire duration.
extracted_ers["shift"] = time_before_questionnaire extracted_ers["shift"] = time_before_questionnaire
extracted_ers["shift"] = extracted_ers["shift"].apply(lambda x: format_timestamp(x)) extracted_ers["shift"] = extracted_ers["shift"].apply(lambda x: format_timestamp(x))
extracted_ers["shift_direction"] = -1 extracted_ers["shift_direction"] = -1