Statistical Methods

The statistical methods discussed below populate various performance evaluation data structures accessed via the user’s SensorEvaluation instance. Simultaneously, data files (both .csv and .json format) are written to the user’s /data/eval_stats/[sensor_name] directory (where [sensor_name] is the name of the air sensor make and model) if the write_to_file argument specified during instantiation of the SensorEvaluation object is set to True.

Note

This section provides a brief overview of the statistical methods accessed via instances of the SensorEvaluation class. For more detail on calling these methods, click on the link to the API documentation indicated below each method header.


SensorEvaluation.add_deploy_dict_stats()

API Documentation for add_deploy_dict_stats()

Description

Calculates:

  • CV for 1-hour averaged sensor datasets

  • CV for 24-hour averaged sensor datasets

  • RMSE for 1-hour averaged sensor datasets

  • RMSE for 24-hour averaged sensor datasets

  • Reference monitor concentration range, mean concentration during testing period for 1-hour averaged measurements

  • Reference monitor concentration range, mean concentration during testing period for 24-hour averaged measurements

  • Meteorological monitor measurement range, mean value for temperature and/or relative humidity measurements at 1-hour intervals

  • Meteorological monitor measurement range, mean value for temperature and/or relative humidity measurements at 24-hour intervals

Populates:

  • SensorEvaluation.deploy_dict

Writes Files:

Example

>>> evaluation.add_deploy_dict_stats()
Computing CV for 1-Hour averaged PM25
..N excluded: 20 out of 756 total
..N concurrent: 736
..Concurrent measurement timeframe: 2019-08-01 13:00:00+00:00 - 2019-09-02 00:00:00+00:00
Computing CV for 24-Hour averaged PM25
..N excluded: 2 out of 32 total
..N concurrent: 30
..Concurrent measurement timeframe: 2019-08-02 00:00:00+00:00 - 2019-09-01 00:00:00+00:00

SensorEvaluation.calculate_metrics()

API Documentation for calculate_metrics()

Description

Note

calculate_metrics() will check whether SensorEvaluation.deploy_dict has been populated with statistics via the add_deploy_dict_stats() method and will call this method if the dictionary has not been populated yet.

Calculates:

  • 1-hour averaged sensor vs. reference regression statistics for each sensor

  • 24-hour averaged sensor vs. reference regression statistics for each sensor

  • 1-hour averaged sensor vs. intersensor average regression statistics for each sensor

  • 24-hour averaged sensor vs. intersensor average regression statistics for each sensor

Populates:

  • SensorEvaluation.stats_df

  • SensorEvaluation.avg_stats_df

Writes Files:

Example

Below is an example for the Toco Toucan Quickstart Guide example

>>> evaluation.calculate_metrics()
Computing 1-hour regression statistics for Toco_Toucan vs. T-API T640X at 16.67 LPM
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Computing 24-hour regression statistics for Toco_Toucan vs. T-API T640X at 16.67 LPM
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Computing 1-hour regression statistics for Toco_Toucan vs. T-API T640X at 16.67 LPM
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Computing 24-hour regression statistics for Toco_Toucan vs. T-API T640X at 16.67 LPM
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