pybop._logging

Classes

Logger

Records the parameter values and corresponding cost values.

Module Contents

class pybop._logging.Logger(minimising: bool, verbose: bool = False, verbose_print_rate: int = 50)

Records the parameter values and corresponding cost values.

Parameters:

• verbose (bool) – If True, the optimisation progress and results are printed.

• verbose_print_rate (int) – The distance between iterations to print verbose output.

• iteration (int) – The current iteration number.

• x_model (list[np.ndarray]) – The history of model parameters.

• x_search (list[np.ndarray]) – The history of search parameters.

• cost (list[float]) – The history of the cost value.

• iteration_number (list[int]) – The history of the iteration number.

• evaluations (int) – The current number of evaluations.

• x_model_best (list[np.ndarray]) – The current best model parameters.

• cost_best (list[float]) – The current best cost value.

_print_verbose_output()

Print verbose optimisation information if enabled.

extend_log(x_model: list[numpy.ndarray], x_search: list[numpy.ndarray], cost: list[float])

Update the log with new values.

Parameters:

• x_model (list[np.ndarray]) – The model parameters.

• x_search (list[np.ndarray]) – The search parameters.

• cost (list[float]) – The cost associated with the parameters.

reset()

_minimising

property cost_convergence

Get the convergence of the cost during the optimisation.

iteration = None

verbose = False

verbose_print_rate = 50

property x0

Get the initial parameter values.