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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