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

Name Type Description
pycalphad.Database
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