Explore low levels of luminance.

exploration/expl_light.py

@@ -6,7 +6,7 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.11.2
+#       jupytext_version: 1.11.4
 #   kernelspec:
 #     display_name: straw2analysis
 #     language: python
@@ -14,10 +14,13 @@
 # ---
 
 # %%
+# %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]
@@ -26,9 +29,14 @@ if nb_dir not in sys.path:
 
 import participants.query_db
 
+TZ_LJ = timezone("Europe/Ljubljana")
+
 # %%
 from features.light import *
 
+# %% [markdown]
+# # Basic characteristics
+
 # %%
 df_light_nokia = get_light_data(["nokia_0000003"])
 print(df_light_nokia)
@@ -40,6 +48,17 @@ df_light_inactive = get_light_data(participants_inactive_usernames)
 # %%
 df_light_inactive.accuracy.value_counts()
 
+# %% [markdown]
+# From [SensorManager](https://developer.android.com/reference/android/hardware/SensorManager.html#SENSOR_STATUS_ACCURACY_HIGH):
+#
+# ```java
+# public static final int SENSOR_STATUS_ACCURACY_HIGH
+# ```
+#
+# This sensor is reporting data with maximum accuracy
+#
+# Constant Value: 3 (0x00000003)
+
 # %%
 df_light_inactive.double_light_lux.describe()
 
@@ -71,3 +90,15 @@ df_light_low = df_light_inactive[df_light_inactive["double_light_lux"] <= 10]
 sns.displot(data=df_light_low, x="double_light_lux", binwidth=0.5, height=8)
 
 # %%
+df_light_very_low = df_light_low[df_light_low["double_light_lux"] < 0.5]
+df_light_very_low.double_light_lux.value_counts()
+
+# %%
+df_light_nokia["datetime_lj"] = df_light_nokia["timestamp"].apply(
+    lambda x: datetime.datetime.fromtimestamp(x / 1000.0, tz=TZ_LJ)
+)
+df_light_nokia.loc[df_light_nokia["double_light_lux"] == 0, ["datetime_lj"]]
+
+# %% [markdown]
+# Zeroes are present during the day. It does happens when the sensor is physically blocked.
+