Data Fits¶
Libraries for selecting and configuring the fitting procedure.
- Data Fits
DataFit
DataFit.approximate_model_distribution()
DataFit.batch_ids
DataFit.batches
DataFit.check_initial_guesses()
DataFit.compute_gradient()
DataFit.compute_hessian()
DataFit.compute_inverse_parameter_covariance()
DataFit.compute_jacobian()
DataFit.compute_parameter_covariance()
DataFit.compute_residuals()
DataFit.data_fit_runner
DataFit.estimate_variable_standard_deviations()
DataFit.explicit_initial_guesses
DataFit.get_batch()
DataFit.get_fit_results()
DataFit.initial_guess_distributions
DataFit.initial_guess_sampler
DataFit.is_parent
DataFit.job_ids
DataFit.linear_confidence_intervals()
DataFit.max_batch_size
DataFit.multistarts
DataFit.num_batches
DataFit.num_workers
DataFit.objective_function
DataFit.plot_fit_results()
DataFit.plot_sampler_results()
DataFit.plot_trace()
DataFit.process_cost()
DataFit.process_initial_guess_distributions()
DataFit.process_objectives()
DataFit.process_optimizer()
DataFit.run()
DataFit.sampler_confidence_intervals()
DataFit.set_initial_guesses()
DataFit.timeseries_preprocessing()
ArrayDataFit
CostLogger
CostLogger.argmin_costs()
CostLogger.argsort_costs()
CostLogger.children
CostLogger.clear_axes()
CostLogger.cost
CostLogger.fig_axes
CostLogger.finish()
CostLogger.finished
CostLogger.get_log()
CostLogger.is_parent
CostLogger.iteration
CostLogger.log()
CostLogger.multiprocessing
CostLogger.num_jobs
CostLogger.parent
CostLogger.plot()
CostLogger.plot_every
CostLogger.plot_flag
CostLogger.plot_refresh()
CostLogger.plot_variables
CostLogger.print_every
CostLogger.probabilistic
CostLogger.reset()
CostLogger.set_datafit_attributes()
CostLogger.set_multiprocessing()
CostLogger.set_parameters()
CostLogger.set_probabilistic()
CostLogger.show_plot_iterative
CostLogger.show_print_iterative
CostLogger.spawn_children()
CostLogger.start()
CostLogger.timer
- Objectives
Objective
SimulationObjective
- 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
Cost
Cost.__call__()
Cost.apply_weights()
Cost.array_output
Cost.combine()
Cost.combined_weights()
Cost.evaluate_to_array()
Cost.evaluate_to_scalar()
Cost.finalize_output()
Cost.get_objective_names()
Cost.initialize_output()
Cost.nan_values()
Cost.objective_names
Cost.objective_weights()
Cost.residuals_to_scalar()
Cost.scalar_output
Cost.scalarize()
Cost.scale()
Cost.set_objective_names()
Cost.set_scalar_output()
Cost.supports_array_output
Cost.supports_scalar_output
Cost.variable_weights()
MultiCost
MLE
Max
SSE
MSE
RMSE
MAE
ChiSquare
Difference
- Models
- Objective functions
ObjectiveFunction
ObjectiveFunction.add_regularization()
ObjectiveFunction.combine()
ObjectiveFunction.cost
ObjectiveFunction.eq_constraints
ObjectiveFunction.evaluate_full()
ObjectiveFunction.evaluate_inputs_and_outputs
ObjectiveFunction.finalize_output()
ObjectiveFunction.gradient()
ObjectiveFunction.hessian()
ObjectiveFunction.ineq_constraints
ObjectiveFunction.initialize_output()
ObjectiveFunction.jacobian()
ObjectiveFunction.likelihood()
ObjectiveFunction.penalties
ObjectiveFunction.priors
ObjectiveFunction.residuals()
ObjectiveFunction.scalar_output
ObjectiveFunction.scalarize()
ObjectiveFunction.set_cost()
ObjectiveFunction.set_eq_constraints()
ObjectiveFunction.set_evaluate_inputs_and_outputs()
ObjectiveFunction.set_ineq_constraints()
ObjectiveFunction.set_penalties()
ObjectiveFunction.set_priors()
ObjectiveFunction.set_scalar_output()
- Parameter Estimators
ParameterEstimator
ParameterEstimator.array_output
ParameterEstimator.cost
ParameterEstimator.custom_eq_constraints
ParameterEstimator.custom_ineq_constraints
ParameterEstimator.gradient
ParameterEstimator.objective_and_gradient
ParameterEstimator.probabilistic
ParameterEstimator.run()
ParameterEstimator.scalar_output
ParameterEstimator.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
Distribution
Normal
MultivariateNormal
MultivariateNormal.argmin
MultivariateNormal.cholesky_cov
MultivariateNormal.cholesky_inv_cov
MultivariateNormal.cov
MultivariateNormal.evaluate_to_array()
MultivariateNormal.evaluate_to_scalar()
MultivariateNormal.inv_cholesky_cov
MultivariateNormal.inv_cov
MultivariateNormal.mean
MultivariateNormal.multivariate
MultivariateNormal.ppf()
MultivariateNormal.rand()
Uniform
LogNormal
MultivariateLogNormal
MultivariateLogNormal.argmin
MultivariateLogNormal.cdf()
MultivariateLogNormal.cov
MultivariateLogNormal.evaluate_to_array()
MultivariateLogNormal.evaluate_to_scalar()
MultivariateLogNormal.mean
MultivariateLogNormal.multivariate
MultivariateLogNormal.pdf()
MultivariateLogNormal.ppf()
MultivariateLogNormal.rand()
PointMass
Dirichlet
- Regularizers
- Constraints
- Penalties
- Priors
- Parameter
Parameter
Parameter.base_parameter
Parameter.bounds
Parameter.create_copy()
Parameter.evaluate()
Parameter.get_bounds()
Parameter.get_initial_value()
Parameter.initial_value
Parameter.is_transformed
Parameter.normalized_bounds
Parameter.normalized_initial_value
Parameter.prior
Parameter.set_bounds()
Parameter.set_fitting_scale()
Parameter.set_prior()
Parameter.to_dict()
- Transforms
Transform
Transform.base_parameter
Transform.bounds
Transform.initial_value
Transform.inverse_transform()
Transform.is_monotonic_transform()
Transform.is_transformed
Transform.prior
Transform.to_dict()
Transform.transform()
Transform.transform_name()
Transform.transform_name_recursive()
Transform.transform_value()
Log
Exp
Log10
Pow10
Inverse
Negate
Identity
- 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()