DIRECT_L

class DIRECT_L(max_evals=1000)

Bases: qiskit.algorithms.optimizers.nlopts.nloptimizer.NLoptOptimizer

DIviding RECTangles Locally-biased optimizer.

DIviding RECTangles (DIRECT) is a deterministic-search algorithms based on systematic division of the search domain into increasingly smaller hyper-rectangles. The DIRECT-L version is a “locally biased” variant of DIRECT that makes the algorithm more biased towards local search, so that it is more efficient for functions with few local minima.

NLopt global optimizer, derivative-free. For further detail, please refer to http://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/#direct-and-direct-l

Parameters

max_evals (int) – Maximum allowed number of function evaluations.

Raises

MissingOptionalLibraryError – NLopt library not installed.

Methods

get_nlopt_optimizer	Return NLopt optimizer type
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