Inflation: the first will enable inflation - provided a list of clinical parameters and standard deviations it will add the corresponding Gaussian noise.
add_noise_to_clinical_parameters(parameter_names, sds_of_noise )
Transforms: the second allows us to work with transformed clinical_parameters.
TransitionRates are optionally created with a transform string (implemented are 'None' (default), and 'log'). If for example lp_transform='log' is selected then one assumes that the latent_periods we work with are log transformed for data assimilation. When performing the calc_from_clinical() function we will now first call the transform_clinical_parameters function to (in this case) exponentiate the latent_periods.
These are all optional features, and will not affect the current implementations or examples
Added 2 features to transition rates,
Inflation: the first will enable inflation - provided a list of clinical parameters and standard deviations it will add the corresponding Gaussian noise.
add_noise_to_clinical_parameters(parameter_names, sds_of_noise )Transforms: the second allows us to work with transformed clinical_parameters.
TransitionRatesare optionally created with a transform string (implemented are'None'(default), and'log'). If for examplelp_transform='log'is selected then one assumes that thelatent_periodswe work with are log transformed for data assimilation. When performing thecalc_from_clinical()function we will now first call thetransform_clinical_parametersfunction to (in this case) exponentiate thelatent_periods.These are all optional features, and will not affect the current implementations or examples