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Fix sleep episodes bug

feature/plugin_sentimental
Meng Li 2021-02-18 23:54:02 -05:00
parent 8377c12efb
commit bedf7106e5
1 changed files with 3 additions and 3 deletions
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6
src/features/fitbit_sleep_intraday/rapids/main.py
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@ -28,7 +28,7 @@ def featuresFullNames(intraday_features_to_compute, sleep_levels_to_compute, sle
def mergeSleepEpisodes(sleep_data, cols_for_groupby):
sleep_episodes = pd.DataFrame(columns=["local_segment", "duration", "start_timestamp", "end_timestamp", "local_start_date_time", "local_end_date_time", "start_minutes"])
sleep_episodes = pd.DataFrame(columns=["local_segment", "duration", "start_timestamp", "end_timestamp", "local_start_date_time", "local_end_date_time"])
if cols_for_groupby and (not sleep_data.empty):
sleep_data = sleep_data.groupby(by=cols_for_groupby)
@ -37,7 +37,6 @@ def mergeSleepEpisodes(sleep_data, cols_for_groupby):
sleep_episodes["end_timestamp"] = sleep_data["end_timestamp"].last()
sleep_episodes["local_start_date_time"] = sleep_data["local_start_date_time"].first()
sleep_episodes["local_end_date_time"] = sleep_data["local_end_date_time"].last()
sleep_episodes["start_minutes"] = sleep_data["start_minutes"].first()
sleep_episodes.reset_index(inplace=True, drop=False)
@ -174,7 +173,7 @@ def singleSleepTypeRoutineFeatures(sleep_intraday_data, routine, reference_time,
if "starttimefirst" + sleep_type in routine:
grouped_first = sleep_intraday_data.groupby(["local_segment"]).first()
if reference_time == "MIDNIGHT":
sleep_intraday_features["starttimefirst" + sleep_type] = grouped_first["start_minutes"]
sleep_intraday_features["starttimefirst" + sleep_type] = grouped_first["local_start_date_time"].apply(lambda x: x.hour * 60 + x.minute + x.second / 60)
elif reference_time == "START_OF_THE_SEGMENT":
sleep_intraday_features["starttimefirst" + sleep_type] = (grouped_first["start_timestamp"] - grouped_first["segment_start_timestamp"]) / (60 * 1000)
else:
@ -237,6 +236,7 @@ def rapids_features(sensor_data_files, time_segment, provider, filter_data_by_se
start_minutes = sleep_intraday_data.groupby("start_timestamp").first()["local_time"].apply(lambda x: int(x.split(":")[0]) * 60 + int(x.split(":")[1]) + int(x.split(":")[2]) / 60).to_frame().rename(columns={"local_time": "start_minutes"}).reset_index()
sleep_intraday_data = sleep_intraday_data.merge(start_minutes, on="start_timestamp", how="left")
sleep_intraday_data = sleep_intraday_data[sleep_intraday_data["start_minutes"] >= include_sleep_later_than]
del sleep_intraday_data["start_minutes"]
sleep_intraday_data = filter_data_by_segment(sleep_intraday_data, time_segment)