SciPyOptimizer

class SciPyOptimizer(method, options=None, max_evals_grouped=1, **kwargs)

Bases: qiskit.algorithms.optimizers.optimizer.Optimizer

A general Qiskit Optimizer wrapping scipy.optimize.minimize.

For further detail, please refer to https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html

Parameters

• method (Union[str, Callable]) – Type of solver.

• options (Optional[Dict[str, Any]]) – A dictionary of solver options.

• kwargs – additional kwargs for scipy.optimize.minimize.

• max_evals_grouped (int) – Max number of default gradient evaluations performed simultaneously.

Methods

get_support_level	Return support level dictionary
gradient_num_diff	We compute the gradient with the numeric differentiation in the parallel way, around the point x_center.
optimize	Perform optimization.
print_options	Print algorithm-specific options.
set_max_evals_grouped	Set max evals grouped
set_options	Sets or updates values in the options dictionary.
wrap_function	Wrap the function to implicitly inject the args at the call of the function.

Attributes

bounds_support_level

Returns bounds support level

gradient_support_level

Returns gradient support level

initial_point_support_level

Returns initial point support level

is_bounds_ignored

Returns is bounds ignored

is_bounds_required

Returns is bounds required

is_bounds_supported

Returns is bounds supported

is_gradient_ignored

Returns is gradient ignored

is_gradient_required

Returns is gradient required

is_gradient_supported

Returns is gradient supported

is_initial_point_ignored

Returns is initial point ignored

is_initial_point_required

Returns is initial point required

is_initial_point_supported

Returns is initial point supported

setting

Return setting

settings

Return type

Dict[str, Any]