If a normal or uniform quantification error distribution cannot be assumed as the data indicates otherwise, there is a need to be able to accurately represent the quantification error distribution.
What was changed
The sampling quantification predictor can be used to predict the quantification error distribution based on the available data by applying quantification error through randomly sampling possible quantification errors from the data.
Intended Purpose
Added a new class to predict quantification error distribution: sampling_quantification_predictor.py
Manually tested with updated simple test case 1, where program emissions summary was observed to ensure measured rates differed both as larger and smaller than true rates/
Pull Request Key Information
Reason for change
If a normal or uniform quantification error distribution cannot be assumed as the data indicates otherwise, there is a need to be able to accurately represent the quantification error distribution.
What was changed
The sampling quantification predictor can be used to predict the quantification error distribution based on the available data by applying quantification error through randomly sampling possible quantification errors from the data.
Intended Purpose
Added a new class to predict quantification error distribution: sampling_quantification_predictor.py
Level of version change required
Patch
Testing Completed
All unit tests pass: unit_test_results.txt
All E2E tests pass: V4_simple_non_repairable_emissions_4110d4aa19ed44801ab142c08a2e36820a359044.log V4-simple_repairable_emissions_4110d4aa19ed44801ab142c08a2e36820a359044.log
Manually tested with updated simple test case 1, where program emissions summary was observed to ensure measured rates differed both as larger and smaller than true rates/
Target Issue
N/A
Additional Information
N/A