63 lines
2.6 KiB
Python
63 lines
2.6 KiB
Python
from collections.abc import Collection
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import pandas as pd
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from config.models import Barometer, BarometerSensor, LightSensor, Participant, Temperature, TemperatureSensor
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from setup import db_engine, session
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def get_ambient_data(usernames: Collection, sensor=None) -> pd.DataFrame:
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"""
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Read the data from any of the ambient sensor tables and return it in a dataframe.
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Parameters
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----------
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usernames: Collection
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A list of usernames to put into the WHERE condition.
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sensor: str
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One of: barometer, barometer_sensor, light, temperature, temperature_sensor.
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Here, the _sensor tables describe the phone sensors, such as their range, dela, resolution, vendor etc.,
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whereas barometer, light, and temperature describe the measured characteristics of the environment.
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Returns
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-------
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df_ambient: pd.DataFrame
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A dataframe of ambient sensor data.
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"""
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if sensor == "barometer":
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query_ambient = (
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session.query(Barometer, Participant.username)
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.filter(Participant.id == Barometer.participant_id)
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)
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elif sensor == "barometer_sensor":
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query_ambient = (
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session.query(BarometerSensor, Participant.username)
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.filter(Participant.id == BarometerSensor.participant_id)
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)
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elif sensor == "light":
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query_ambient = (
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session.query(LightSensor, Participant.username)
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.filter(Participant.id == LightSensor.participant_id)
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)
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# Note that LightSensor and its light_sensor table are incorrectly named.
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# In this table, we actually find light data, i.e. double_light_lux, the ambient luminance in lux,
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# and NOT light sensor data (its range, dela, resolution, vendor etc.) as the name suggests.
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# We do not have light sensor data saved in the database.
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elif sensor == "temperature":
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query_ambient = (
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session.query(Temperature, Participant.username)
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.filter(Participant.id == Temperature.participant_id)
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)
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elif sensor == "temperature_sensor":
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query_ambient = (
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session.query(TemperatureSensor, Participant.username)
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.filter(Participant.id == TemperatureSensor.participant_id)
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)
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else:
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raise KeyError("Specify one of the ambient sensors: barometer, barometer_sensor, light, temperature, or temperature_sensor.")
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query_ambient = query_ambient.filter(Participant.username.in_(usernames))
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with db_engine.connect() as connection:
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df_ambient = pd.read_sql(query_ambient.statement, connection)
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return df_ambient
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