Data Fits¶
Libraries for selecting and configuring the fitting procedure.
- Data Fits
DataFitDataFit.approximate_model_distribution()DataFit.batch_idsDataFit.batchesDataFit.check_initial_guesses()DataFit.compute_hessian()DataFit.data_fit_runnerDataFit.estimate_variable_standard_deviations()DataFit.explicit_initial_guessesDataFit.get_batch()DataFit.get_fit_results()DataFit.hessianDataFit.initial_guess_distributionsDataFit.initial_guess_samplerDataFit.is_parentDataFit.job_idsDataFit.linear_confidence_intervals()DataFit.max_batch_sizeDataFit.multistartsDataFit.num_batchesDataFit.num_workersDataFit.objective_functionDataFit.plot_fit_results()DataFit.plot_sampler_results()DataFit.plot_trace()DataFit.process_initial_guess_distributions()DataFit.process_objectives()DataFit.run()DataFit.sampler_confidence_intervals()DataFit.set_initial_guesses()DataFit.timeseries_preprocessing()
ArrayDataFitCostLoggerCostLogger.argmin_costs()CostLogger.argsort_costs()CostLogger.childrenCostLogger.clear_axes()CostLogger.costCostLogger.fig_axesCostLogger.finish()CostLogger.finishedCostLogger.get_log()CostLogger.is_parentCostLogger.iterationCostLogger.log()CostLogger.multiprocessingCostLogger.num_jobsCostLogger.parentCostLogger.plot()CostLogger.plot_everyCostLogger.plot_flagCostLogger.plot_refresh()CostLogger.plot_variablesCostLogger.print_everyCostLogger.probabilisticCostLogger.reset()CostLogger.set_datafit_attributes()CostLogger.set_multiprocessing()CostLogger.set_parameters()CostLogger.set_probabilistic()CostLogger.show_plot_iterativeCostLogger.show_print_iterativeCostLogger.spawn_children()CostLogger.start()CostLogger.timer
- Objectives
ObjectiveSimulationObjective- Open-circuit potential objectives
- Open-circuit potential objectives with MSMR model
- Objectives
- Utility functions
get_msmr_params_for_fit()default_msmr_bounds_function()get_msmr_capacity_params_for_fit()default_msmr_capacity_bounds_function()msmr_half_cell_initial_guess()get_initial_capacity_and_lower_excess_capacity()get_theta_half_cell_msmr()get_q_half_cell_msmr()plot_each_species_msmr()plot_half_cell_ocp()plot_full_cell_ocv()msmr_Qj_to_Xj()msmr_Xj_to_Qj()msmr_sort_params()
- Callbacks
- Resistance objective
- Pulse objective
- Current-driven objective
- EIS objective
- Calendar ageing objective
- Cycle ageing objective
- Cost Functions
- Models
- Objective functions
ObjectiveFunctionObjectiveFunction.add_regularization()ObjectiveFunction.combine()ObjectiveFunction.costObjectiveFunction.eq_constraintsObjectiveFunction.evaluate_full()ObjectiveFunction.evaluate_inputs_and_outputsObjectiveFunction.finalize_output()ObjectiveFunction.ineq_constraintsObjectiveFunction.initialize_output()ObjectiveFunction.likelihood()ObjectiveFunction.penaltiesObjectiveFunction.priorsObjectiveFunction.scalar_outputObjectiveFunction.set_cost()ObjectiveFunction.set_eq_constraints()ObjectiveFunction.set_evaluate_inputs_and_outputs()ObjectiveFunction.set_ineq_constraints()ObjectiveFunction.set_penalties()ObjectiveFunction.set_priors()
- Parameter Estimators
ParameterEstimatorParameterEstimator.array_outputParameterEstimator.costParameterEstimator.custom_eq_constraintsParameterEstimator.custom_ineq_constraintsParameterEstimator.gradientParameterEstimator.objective_and_gradientParameterEstimator.probabilisticParameterEstimator.run()ParameterEstimator.scalar_outputParameterEstimator.set_bounds()ParameterEstimator.set_eq_constraints()ParameterEstimator.set_gradient()ParameterEstimator.set_ineq_constraints()ParameterEstimator.set_objective()ParameterEstimator.set_objective_and_gradient()
Chain
- Optimizers
- Samplers
- Distribution Samplers
- Statistics
DistributionNormalMultivariateNormalMultivariateNormal.argminMultivariateNormal.cholesky_covMultivariateNormal.cholesky_inv_covMultivariateNormal.covMultivariateNormal.evaluate_to_array()MultivariateNormal.evaluate_to_scalar()MultivariateNormal.inv_cholesky_covMultivariateNormal.inv_covMultivariateNormal.meanMultivariateNormal.multivariateMultivariateNormal.ppf()
UniformLogNormalMultivariateLogNormalMultivariateLogNormal.argminMultivariateLogNormal.cdf()MultivariateLogNormal.covMultivariateLogNormal.evaluate_to_array()MultivariateLogNormal.evaluate_to_scalar()MultivariateLogNormal.meanMultivariateLogNormal.multivariateMultivariateLogNormal.pdf()MultivariateLogNormal.ppf()MultivariateLogNormal.rand()
PointMassDirichlet
- Regularizers
- Constraints
- Penalties
- Priors
- Parameter
ParameterParameter.boundsParameter.create_copy()Parameter.evaluate()Parameter.get_bounds()Parameter.get_initial_value()Parameter.initial_valueParameter.is_transformedParameter.normalized_boundsParameter.normalized_initial_valueParameter.priorParameter.set_bounds()Parameter.set_fitting_scale()Parameter.set_prior()Parameter.to_dict()
- Transforms
- Result
- Callbacks
- Custom Parameters
- Data utilities
load_data_metadata()write_data_metadata()get_current_function_from_data()get_current_steps_from_data()get_time_in_seconds()calculate_dUdQ_cutoff()calculate_dQdU_cutoff()calculate_differential_cutoff_explicit()calculate_differential_cutoff_quantile()calculate_differential_cutoff_peaks()check_ocv_data_format()negative_to_positive_half_cell()calculate_stoichiometry_data_msmr()generate_msmr_ocp_data()generate_pulse_diffusivity_data_from_csv()