Optimizer

class glotaran.optimization.optimizer.Optimizer(scheme: Scheme, verbose: bool = True, raise_exception: bool = False)

Bases: object

A class to optimize a scheme.

Initialize an optimization group for a dataset group.

Parameters:

• scheme (Scheme) – The optimization scheme.

• verbose (bool) – Deactivate printing of logs if False.

• raise_exception (bool) – Raise exceptions during optimizations instead of gracefully exiting if True.

Raises:

• MissingDatasetsError – Raised if datasets are missing.

• ParameterNotInitializedError – Raised if the scheme parameters are None.

• UnsupportedMethodError – Raised if the optimization method is unsupported.

Methods Summary

calculate_covariance_matrix_and_standard_errors	Calculate the covariance matrix and standard errors of the optimization.
calculate_penalty	Calculate the penalty of the scheme.
create_result	Create the result of the optimization.
get_current_optimization_iteration	Extract current iteration from optimize_stdout.
objective_function	Calculate the objective for the optimization.
optimize	Perform the optimization.

Methods Documentation

calculate_covariance_matrix_and_standard_errors(jacobian: ArrayLike, root_mean_square_error: float) → ArrayLike

Calculate the covariance matrix and standard errors of the optimization.

Parameters:

• jacobian (ArrayLike) – The jacobian matrix.

• root_mean_square_error (float) – The root mean square error.

Returns:

The covariance matrix.

Return type:

ArrayLike

calculate_penalty() → ArrayLike

Calculate the penalty of the scheme.

Returns:

The penalty.

Return type:

ArrayLike

create_result() → Result

Create the result of the optimization.

Returns:

The result of the optimization.

Return type:

Result

Raises:

InitialParameterError – Raised if the initial parameters could not be evaluated.

static get_current_optimization_iteration(optimize_stdout: str) → int

Extract current iteration from optimize_stdout.

Parameters:

optimize_stdout (str) – SciPy optimization stdout string, read out via TeeContext.read().

Returns:

Current iteration (0 if pattern did not match).

Return type:

int

objective_function(parameters: ArrayLike) → ArrayLike

Calculate the objective for the optimization.

Parameters:

parameters (ArrayLike) – the parameters provided by the optimizer.

Returns:

The objective for the optimizer.

Return type:

ArrayLike

optimize()

Perform the optimization.

Raises:

Exception – Raised if an exception occurs during optimization and raise_exception is True.