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Add firstuseafterTIME feature for screen sensor

pull/95/head
Meng Li 2020-03-04 12:21:36 -05:00
parent 85f4ec2ab6
commit c8b7275084
3 changed files with 10 additions and 5 deletions
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3
config.yaml
View File

@ -87,7 +87,8 @@ BATTERY:
SCREEN:
DAY_SEGMENTS: *day_segments
METRICS_DELTAS: ["countepisode", "episodepersensedminutes", "sumduration", "maxduration", "minduration", "avgduration", "stdduration"]
REFERENCE_HOUR_FIRST_USE: 0
METRICS_DELTAS: ["countepisode", "episodepersensedminutes", "sumduration", "maxduration", "minduration", "avgduration", "stdduration", "firstuseafter"]
EPISODE_TYPES: ["unlock"]
LIGHT:

1
rules/features.snakefile
View File

@ -101,6 +101,7 @@ rule screen_metrics:
phone_sensed_bins = "data/interim/{pid}/phone_sensed_bins.csv"
params:
day_segment = "{day_segment}",
reference_hour_first_use = config["SCREEN"]["REFERENCE_HOUR_FIRST_USE"],
metrics_deltas = config["SCREEN"]["METRICS_DELTAS"],
episode_types = config["SCREEN"]["EPISODE_TYPES"],
bin_size = config["PHONE_VALID_SENSED_DAYS"]["BIN_SIZE"]

11
src/features/screen_metrics.py
View File

@ -5,7 +5,7 @@ import itertools
from datetime import datetime, timedelta, time
from features_utils import splitOvernightEpisodes, splitMultiSegmentEpisodes
def getEpisodeDurationFeatures(screen_deltas, episode, metrics, phone_sensed_bins, bin_size):
def getEpisodeDurationFeatures(screen_deltas, episode, metrics, phone_sensed_bins, bin_size, reference_hour_first_use):
screen_deltas_episode = screen_deltas[screen_deltas["episode"] == episode]
duration_helper = pd.DataFrame()
if "countepisode" in metrics:
@ -25,8 +25,8 @@ def getEpisodeDurationFeatures(screen_deltas, episode, metrics, phone_sensed_bin
duration_helper = pd.concat([duration_helper, screen_deltas_episode.groupby(["local_start_date"]).mean()[["time_diff"]].rename(columns = {"time_diff":"screen_" + day_segment + "_avgduration" + episode})], axis = 1)
if "stdduration" in metrics:
duration_helper = pd.concat([duration_helper, screen_deltas_episode.groupby(["local_start_date"]).std()[["time_diff"]].rename(columns = {"time_diff":"screen_" + day_segment + "_stdduration" + episode})], axis = 1)
duration_helper = duration_helper.fillna(0)
if "firstuseafter" + "{0:0=2d}".format(reference_hour_first_use) in metrics:
duration_helper = pd.concat([duration_helper, pd.DataFrame(screen_deltas_episode.groupby(["local_start_date"]).first()[["local_start_date_time"]].local_start_date_time.apply(lambda x: (x.to_pydatetime().hour - reference_hour_first_use) * 3600 + x.to_pydatetime().minute * 60 + x.to_pydatetime().second)).rename(columns = {"local_start_date_time":"screen_" + day_segment + "_firstuseafter" + "{0:0=2d}".format(reference_hour_first_use) + episode})], axis = 1)
return duration_helper
@ -35,10 +35,13 @@ phone_sensed_bins = pd.read_csv(snakemake.input["phone_sensed_bins"], parse_date
phone_sensed_bins[phone_sensed_bins > 0] = 1
day_segment = snakemake.params["day_segment"]
reference_hour_first_use = snakemake.params["reference_hour_first_use"]
metrics_deltas = snakemake.params["metrics_deltas"]
episode_types = snakemake.params["episode_types"]
bin_size = snakemake.params["bin_size"]
metrics_deltas = ["firstuseafter" + "{0:0=2d}".format(reference_hour_first_use) if feature_name == "firstuseafter" else feature_name for feature_name in metrics_deltas]
metrics_deltas_name = ["".join(metric) for metric in itertools.product(metrics_deltas, episode_types)]
screen_features = pd.DataFrame(columns=["local_date"]+["screen_" + day_segment + "_" + x for x in metrics_deltas_name])
@ -52,7 +55,7 @@ if not screen_deltas.empty:
if not screen_deltas.empty:
screen_features = pd.DataFrame()
for episode in episode_types:
screen_features = pd.concat([screen_features, getEpisodeDurationFeatures(screen_deltas, episode, metrics_deltas, phone_sensed_bins, bin_size)], axis=1)
screen_features = pd.concat([screen_features, getEpisodeDurationFeatures(screen_deltas, episode, metrics_deltas, phone_sensed_bins, bin_size, reference_hour_first_use)], axis=1)
screen_features = screen_features.rename_axis("local_date").reset_index()