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Add device_id column for sleep intraday episodes

pull/130/head v1.0.1
Meng Li 2021-04-08 11:21:28 -04:00
parent 286d317af4
commit 00a3335623
1 changed files with 3 additions and 3 deletions
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6
src/features/fitbit_sleep_intraday/episodes/sleep_intraday_episodes.py
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@ -3,7 +3,7 @@ import numpy as np
def mergeSleepEpisodes(sleep_data, cols_for_groupby): def mergeSleepEpisodes(sleep_data, cols_for_groupby):
sleep_episodes = pd.DataFrame(columns=["type_episode_id", "level_episode_id", "level", "unified_level", "is_main_sleep", "type", "timestamp", "duration"]) sleep_episodes = pd.DataFrame(columns=["device_id", "type_episode_id", "level_episode_id", "level", "unified_level", "is_main_sleep", "type", "timestamp", "duration"])
if not sleep_data.empty: if not sleep_data.empty:
sleep_data = sleep_data.groupby(by=cols_for_groupby) sleep_data = sleep_data.groupby(by=cols_for_groupby)
sleep_episodes = sleep_data[["timestamp"]].first() sleep_episodes = sleep_data[["timestamp"]].first()
@ -15,7 +15,7 @@ def mergeSleepEpisodes(sleep_data, cols_for_groupby):
sleep_intraday = pd.read_csv(snakemake.input["sleep_intraday"]) sleep_intraday = pd.read_csv(snakemake.input["sleep_intraday"])
# discard useless columns # discard useless columns
for col in ["device_id", "local_timezone", "local_date_time", "local_date", "local_time", "local_hour", "local_minute", "assigned_segments"]: for col in ["local_timezone", "local_date_time", "local_date", "local_time", "local_hour", "local_minute", "assigned_segments"]:
del sleep_intraday[col] del sleep_intraday[col]
# Extract "unified_level" based on "level" field # Extract "unified_level" based on "level" field
@ -25,7 +25,7 @@ sleep_intraday["unified_level"] = np.where(sleep_intraday["level"].isin(["awake"
# Put consecutive rows with the same "level" field together and merge episodes # Put consecutive rows with the same "level" field together and merge episodes
sleep_intraday.insert(2, "level_episode_id", (sleep_intraday[["type_episode_id", "level"]] != sleep_intraday[["type_episode_id", "level"]].shift()).any(axis=1).cumsum()) sleep_intraday.insert(2, "level_episode_id", (sleep_intraday[["type_episode_id", "level"]] != sleep_intraday[["type_episode_id", "level"]].shift()).any(axis=1).cumsum())
sleep_intraday_episodes = mergeSleepEpisodes(sleep_intraday, ["type_episode_id", "level_episode_id", "level", "unified_level", "is_main_sleep", "type"]) sleep_intraday_episodes = mergeSleepEpisodes(sleep_intraday, ["device_id", "type_episode_id", "level_episode_id", "level", "unified_level", "is_main_sleep", "type"])
# Generate "start_timestamp" and "end_timestamp" # Generate "start_timestamp" and "end_timestamp"