generate_parameters

generate_parameters(phase_models, datasets, ref_state, excess_model, ridge_alpha=None, aicc_penalty_factor=None, dbf=None, fitting_description=gibbs_energy_fitting_description)

Generate parameters from given phase models and datasets

Parameters

Name	Type	Description	Default
phase_models	dict	Dictionary of components and phases to fit.	required
datasets	PickleableTinyDB	database of single- and multi-phase to fit.	required
ref_state	str	String of the reference data to use, e.g. ‘SGTE91’ or ‘SR2016’	required
excess_model	str	String of the type of excess model to fit to, e.g. ‘linear’	required
ridge_alpha	float	Value of the :math:\alpha hyperparameter used in ridge regression. Defaults to None, which falls back to ordinary least squares regression. For now, the parameter is applied to all features.	None
aicc_penalty_factor	dict	Map of phase name to feature to a multiplication factor for the AICc’s parameter penalty.	None
dbf	Database	Initial pycalphad Database that can have parameters that would not be fit by ESPEI	None
fitting_description	Type[ModelFittingDescription]	ModelFittingDescription object describing the fitting steps and model	gibbs_energy_fitting_description

Returns

Type	Description
pycalphad.Database