3. Applying calibration models: Useful features
3.1. Saving & Loading
After fitting, calibration models can be saved to JSON files with calibrationmodel.save("my_calibration.json")
.
This facilitates their re-use across different notebooks and analysis sessions.
To load a calibration model, you’ll need to reference the class
definition of the model:
cmodel = MyCustomCalibrationModel.load("my_calibration.json")
The loading routine checks the name of the calibration model class to prevent accidentally instantiating models from the wrong parameter sets.
3.2. Numerical Inference
A fitted calibration model may be used to convert from one or many measurement observations into a prediction about the independent variable. While the predict_independent gives a point estimate, we recommend to use infer_independent.
infer_independent takes one or more measurement observations as the input and returns a NumericPosterior that describes the uncertainty about the independent variable.