pybop.problems.fitting_problem#

Classes#

FittingProblem

Problem class for fitting (parameter estimation) problems.

Module Contents#

class pybop.problems.fitting_problem.FittingProblem(model, parameters, dataset, check_model=True, signal=['Voltage [V]'], additional_variables=[], init_soc=None)[source]#

Bases: pybop.BaseProblem

Problem class for fitting (parameter estimation) problems.

Extends BaseProblem with specifics for fitting a model to a dataset.

Parameters:

model (object) – The model to fit.
parameters (pybop.Parameter or pybop.Parameters) – An object or list of the parameters for the problem.
dataset (Dataset) – Dataset object containing the data to fit the model to.
signal (str, optional) – The variable used for fitting (default: “Voltage [V]”).
additional_variables (List[str], optional) – Additional variables to observe and store in the solution (default additions are: [“Time [s]”]).
init_soc (float, optional) – Initial state of charge (default: None).

evaluate(inputs: pybop.parameters.parameter.Inputs)[source]#

Evaluate the model with the given parameters and return the signal.

Parameters:: inputs (Inputs) – Parameters for evaluation of the model.
Returns:: y – The model output y(t) simulated with given inputs.
Return type:: np.ndarray

evaluateS1(inputs: pybop.parameters.parameter.Inputs)[source]#

Evaluate the model with the given parameters and return the signal and its derivatives.

Parameters:: inputs (Inputs) – Parameters for evaluation of the model.
Returns:: A tuple containing the simulation result y(t) and the sensitivities dy/dx(t) evaluated with given inputs.
Return type:: tuple