Refactor screen features: replace "metrics" with "features"

Co-authored-by: Meng Li <AnnieLM1996@gmail.com>

config.yaml

@@ -89,7 +89,7 @@ BATTERY:
 SCREEN:
   DAY_SEGMENTS: *day_segments
   REFERENCE_HOUR_FIRST_USE: 0
-  METRICS_DELTAS: ["countepisode", "episodepersensedminutes", "sumduration", "maxduration", "minduration", "avgduration", "stdduration", "firstuseafter"]
+  FEATURES_DELTAS: ["countepisode", "episodepersensedminutes", "sumduration", "maxduration", "minduration", "avgduration", "stdduration", "firstuseafter"]
   EPISODE_TYPES: ["unlock"]
 
 LIGHT:

docs/features/extracted.rst

@@ -885,7 +885,7 @@ See `Screen Config Code`_
       - Apply readable dateime to Screen dataset: ``expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["SENSORS"]),``
       - Extract the deltas from the Screen dataset: expand("data/processed/{pid}/screen_deltas.csv", pid=config["PIDS"]),
     
-- Extract Screen Metrics:
+- Extract Screen Features:
     
       | ``expand("data/processed/{pid}/screen_{day_segment}.csv",``
       |                      ``pid=config["PIDS"],`` 
@@ -905,9 +905,9 @@ See `Screen Config Code`_
 
     - **Script:** ``src/features/screen_deltas.R`` - See the screen_deltas.R_ script.
 
-- **Rule:** ``rules/features.snakefile/screen_metrics`` - See the screen_metrics_ rule.
+- **Rule:** ``rules/features.snakefile/screen_features`` - See the screen_features_ rule.
 
-    - **Script:** ``src/features/screen_metrics.py`` - See the screen_metrics.py_ script.
+    - **Script:** ``src/features/screen_features.py`` - See the screen_features.py_ script.
 
 .. _screen-parameters:
 
@@ -917,16 +917,16 @@ See `Screen Config Code`_
 Name	           Description
 ===============    ===================
 day_segment        The particular ``day_segments`` that will be analyzed. The available options are ``daily``, ``morning``, ``afternoon``, ``evening``, ``night``
-metrics_events     The different measures that can be retrieved from the events in the Screen dataset. See :ref:`Available Screen Events Metrics <screen-events-available-metrics>` Table below
+features_events     The different measures that can be retrieved from the events in the Screen dataset. See :ref:`Available Screen Events Features <screen-events-available-features>` Table below
-metrics_deltas     The different measures that can be retrieved from the episodes extracted from the Screen dataset. See :ref:`Available Screen Episodes Metrics <screen-episodes-available-metrics>` Table below
+features_deltas     The different measures that can be retrieved from the episodes extracted from the Screen dataset. See :ref:`Available Screen Episodes Features <screen-episodes-available-features>` Table below
 episodes           The action that defines an episode
 ===============    ===================
 
-.. _screen-events-available-metrics:
+.. _screen-events-available-features:
 
 .. 
-    **Available Screen Events Metrics**
+    **Available Screen Events Features**
-    The following table shows a list of the available metrics for Screen Events. 
+    The following table shows a list of the available features for Screen Events. 
         =================   ==============    =============
         Name                Units             Description
         =================   ==============    =============
@@ -935,11 +935,11 @@ episodes           The action that defines an episode
         unlocksperminute    Unlock events     Unlock events per minute: The average of the number of unlock events that occur in a minute 
         =================   ==============    =============
 
-.. _screen-episodes-available-metrics:
+.. _screen-episodes-available-features:
 
-**Available Screen Episodes Metrics**
+**Available Screen Episodes Features**
 
-The following table shows a list of the available metrics for Screen Episodes. 
+The following table shows a list of the available features for Screen Episodes. 
 
 =============   =========    =============
 Name            Units        Description
@@ -1187,8 +1187,8 @@ stddurationactivebout       minutes       Std duration active bout: The standard
 .. _`Screen Config Code`: https://github.com/carissalow/rapids/blob/765bb462636d5029a05f54d4c558487e3786b90b/config.yaml#L88
 .. _screen_deltas: https://github.com/carissalow/rapids/blob/765bb462636d5029a05f54d4c558487e3786b90b/rules/features.snakefile#L33
 .. _screen_deltas.R: https://github.com/carissalow/rapids/blob/master/src/features/screen_deltas.R
-.. _screen_metrics: https://github.com/carissalow/rapids/blob/765bb462636d5029a05f54d4c558487e3786b90b/rules/features.snakefile#L97
+.. _screen_features: https://github.com/carissalow/rapids/blob/765bb462636d5029a05f54d4c558487e3786b90b/rules/features.snakefile#L97
-.. _screen_metrics.py: https://github.com/carissalow/rapids/blob/master/src/features/screen_metrics.py
+.. _screen_features.py: https://github.com/carissalow/rapids/blob/master/src/features/screen_features.py
 .. _`Fitbit: Heart Rate Config Code`: https://github.com/carissalow/rapids/blob/765bb462636d5029a05f54d4c558487e3786b90b/config.yaml#L113
 .. _fitbit_with_datetime: https://github.com/carissalow/rapids/blob/765bb462636d5029a05f54d4c558487e3786b90b/rules/preprocessing.snakefile#L94
 .. _fitbit_readable_datetime.py: https://github.com/carissalow/rapids/blob/master/src/data/fitbit_readable_datetime.py

rules/features.snakefile

@@ -96,20 +96,20 @@ rule battery_metrics:
     script:
         "../src/features/battery_metrics.py"
 
-rule screen_metrics:
+rule screen_features:
     input:
         screen_deltas = "data/processed/{pid}/screen_deltas.csv",
         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"],
+        features_deltas = config["SCREEN"]["FEATURES_DELTAS"],
         episode_types = config["SCREEN"]["EPISODE_TYPES"],
         bin_size = config["PHONE_VALID_SENSED_DAYS"]["BIN_SIZE"]
     output:
         "data/processed/{pid}/screen_{day_segment}.csv"
     script:
-        "../src/features/screen_metrics.py"
+        "../src/features/screen_features.py"
 
 rule light_metrics:
     input:

src/features/screen_features.py

@@ -5,27 +5,27 @@ 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, reference_hour_first_use):
+def getEpisodeDurationFeatures(screen_deltas, episode, features, 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:
+    if "countepisode" in features:
         duration_helper = pd.concat([duration_helper, screen_deltas_episode.groupby(["local_start_date"]).count()[["time_diff"]].rename(columns = {"time_diff": "screen_" + day_segment + "_countepisode" + episode})], axis = 1)
-    if "episodepersensedminutes" in metrics:
+    if "episodepersensedminutes" in features:
         for date, row in screen_deltas_episode.groupby(["local_start_date"]).count()[["time_diff"]].iterrows():
             sensed_minutes = phone_sensed_bins.loc[date, :].sum() * bin_size
             episode_per_sensedminutes = row["time_diff"] / (1 if sensed_minutes == 0 else sensed_minutes)
             duration_helper.loc[date, "screen_" + day_segment + "_episodepersensedminutes" + episode] = episode_per_sensedminutes
-    if "sumduration" in metrics:
+    if "sumduration" in features:
         duration_helper = pd.concat([duration_helper, screen_deltas_episode.groupby(["local_start_date"]).sum()[["time_diff"]].rename(columns = {"time_diff": "screen_" + day_segment + "_sumduration" + episode})], axis = 1)
-    if "maxduration" in metrics:
+    if "maxduration" in features:
         duration_helper = pd.concat([duration_helper, screen_deltas_episode.groupby(["local_start_date"]).max()[["time_diff"]].rename(columns = {"time_diff": "screen_" + day_segment + "_maxduration" + episode})], axis = 1)        
-    if "minduration" in metrics:
+    if "minduration" in features:
         duration_helper = pd.concat([duration_helper, screen_deltas_episode.groupby(["local_start_date"]).min()[["time_diff"]].rename(columns = {"time_diff": "screen_" + day_segment + "_minduration" + episode})], axis = 1)
-    if "avgduration" in metrics:
+    if "avgduration" in features:
         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:
+    if "stdduration" in features:
         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)
-    if "firstuseafter" + "{0:0=2d}".format(reference_hour_first_use) in metrics:
+    if "firstuseafter" + "{0:0=2d}".format(reference_hour_first_use) in features:
         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
 
@@ -36,15 +36,15 @@ 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"]
+features_deltas = snakemake.params["features_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]
+features_deltas = ["firstuseafter" + "{0:0=2d}".format(reference_hour_first_use) if feature_name == "firstuseafter" else feature_name for feature_name in features_deltas]
 
-metrics_deltas_name = ["".join(metric) for metric in itertools.product(metrics_deltas, episode_types)]
+features_deltas_name = ["".join(feature) for feature in itertools.product(features_deltas, episode_types)]
 
-screen_features = pd.DataFrame(columns=["local_date"]+["screen_" + day_segment + "_" + x for x in metrics_deltas_name])
+screen_features = pd.DataFrame(columns=["local_date"]+["screen_" + day_segment + "_" + x for x in features_deltas_name])
 if not screen_deltas.empty:
     # preprocess day_segment and episodes
     screen_deltas = splitOvernightEpisodes(screen_deltas, [], ["episode"])
@@ -55,7 +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, reference_hour_first_use)], axis=1)
+            screen_features = pd.concat([screen_features, getEpisodeDurationFeatures(screen_deltas, episode, features_deltas, phone_sensed_bins, bin_size, reference_hour_first_use)], axis=1)
 
     if not screen_features.empty:
         screen_features = screen_features.rename_axis("local_date").reset_index()