Start exploring proximity.

exploration/expl_proximity.py

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+# ---
+# jupyter:
+#   jupytext:
+#     formats: ipynb,py:percent
+#     text_representation:
+#       extension: .py
+#       format_name: percent
+#       format_version: '1.3'
+#       jupytext_version: 1.11.4
+#   kernelspec:
+#     display_name: straw2analysis
+#     language: python
+#     name: straw2analysis
+# ---
+
+# %%
+# %matplotlib inline
+import datetime
+import os
+import sys
+
+import seaborn as sns
+from pytz import timezone
+from tabulate import tabulate
+
+nb_dir = os.path.split(os.getcwd())[0]
+if nb_dir not in sys.path:
+    sys.path.append(nb_dir)
+
+import participants.query_db
+
+TZ_LJ = timezone("Europe/Ljubljana")
+
+# %%
+from features.proximity import *
+
+# %% [markdown]
+# # Basic characteristics
+
+# %%
+df_proximity_nokia = get_proximity_data(["nokia_0000003"])
+print(df_proximity_nokia)
+
+# %%
+df_proximity_nokia.double_proximity.value_counts()
+
+# %% [markdown]
+# `double_proximity` is "the distance to an object in front of the mobile device or binary presence (**manufacturer dependent**)."
+#
+# "Most proximity sensors return [the absolute distance, in cm](https://developer.android.com/guide/topics/sensors/sensors_position#sensors-pos-prox), but some return only near and far values.
+#
+# Note: Some proximity sensors return binary values that represent "near" or "far." In this case, the sensor usually reports its maximum range value in the far state and a lesser value in the near state. Typically, the far value is a value > 5 cm, but this can vary from sensor to sensor. You can determine a sensor's maximum range by using the getMaximumRange() method."
+
+# %%
+participants_inactive_usernames = participants.query_db.get_usernames()
+df_proximity_inactive = get_proximity_data(participants_inactive_usernames)
+
+# %%
+df_proximity_inactive.double_proximity.describe()
+
+# %%
+sns.displot(
+    data=df_proximity_inactive, x="double_proximity", binwidth=0.2, height=8,
+)
+
+# %%
+df_proximity_inactive.double_proximity.value_counts()
+
+# %%

features/proximity.py

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+from collections.abc import Collection
+
+import pandas as pd
+
+from config.models import Participant, Proximity
+from setup import db_engine, session
+
+
+def get_proximity_data(usernames: Collection) -> pd.DataFrame:
+    """
+    Read the data from the proximity sensor table and return it in a dataframe.
+
+    Parameters
+    ----------
+    usernames: Collection
+        A list of usernames to put into the WHERE condition.
+
+    Returns
+    -------
+    df_proximity: pd.DataFrame
+        A dataframe of proximity data.
+    """
+    query_proximity = (
+        session.query(Proximity, Participant.username)
+        .filter(Participant.id == Proximity.participant_id)
+        .filter(Participant.username.in_(usernames))
+    )
+    with db_engine.connect() as connection:
+        df_proximity = pd.read_sql(query_proximity.statement, connection)
+    return df_proximity