From 0b3e9226b3c683e87ef758756f0d83350642a716 Mon Sep 17 00:00:00 2001 From: Primoz Date: Tue, 8 Nov 2022 14:44:24 +0000 Subject: [PATCH] Make small corrections in ERS file. --- .../straw/process_user_event_related_segments.py | 13 +++---------- 1 file changed, 3 insertions(+), 10 deletions(-) diff --git a/src/features/phone_esm/straw/process_user_event_related_segments.py b/src/features/phone_esm/straw/process_user_event_related_segments.py index 3762d59a..fd0e8b6f 100644 --- a/src/features/phone_esm/straw/process_user_event_related_segments.py +++ b/src/features/phone_esm/straw/process_user_event_related_segments.py @@ -37,18 +37,11 @@ def extract_ers_from_file(esm_df, device_id): classified = classify_sessions_by_completion_time(esm_preprocessed) esm_filtered_sessions = classified[classified["session_response"] == 'ema_completed'].reset_index()[['device_id', 'esm_session']] esm_df = esm_preprocessed.loc[(esm_preprocessed['device_id'].isin(esm_filtered_sessions['device_id'])) & (esm_preprocessed['esm_session'].isin(esm_filtered_sessions['esm_session']))] + - - # Problem ne bo ekstrahiranje posameznih začetkov in trajanj stresnih dogodkov - večji problem je pridobitev ustreznega targeta, - # tako da bo poravnan s tem dogodkom, saj se lahko zgodi, da je timestamp zabeležene intenzitete stresnega dogodka ne pade v okno stresnega dogodka. - # Edina izjema tega so, če je označen odgovor "1 - Še vedno traja" pri vprašanju appraisal_event_duration - - # Extract time-relevant information targets_method = config["TIME_SEGMENTS"]["TAILORED_EVENTS"]["TARGETS_METHOD"] - - if targets_method in ["30_before", "90_before"]: # takes 30-minute peroid before the questionnaire + the duration of the questionnaire - + # 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() # is rounded up in seconds extracted_ers["label"] = f"straw_event_{targets_method}_" + snakemake.params["pid"] + "_" + extracted_ers.index.astype(str).str.zfill(3) extracted_ers[['event_timestamp', 'device_id']] = esm_df.groupby(["device_id", "esm_session"])['timestamp'].min().reset_index()[['timestamp', 'device_id']] @@ -75,7 +68,7 @@ def extract_ers_from_file(esm_df, device_id): extracted_ers["length"] = (extracted_ers["timestamp"] + extracted_ers["diffs"]).apply(lambda x: format_timestamp(x)) extracted_ers["shift"] = extracted_ers["diffs"].apply(lambda x: format_timestamp(x)) - elif targets_method == "stress_events": + elif targets_method == "stress_event": pass # VV Testiranje različnih povpraševanj za VV # print(esm_df[esm_df.questionnaire_id == 87])