DIRECT_L

class DIRECT_L(max_evals=1000)

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

NameError – NLopt library not installed.

Attributes

DIRECT_L.bounds_support_level	Returns bounds support level
DIRECT_L.gradient_support_level	Returns gradient support level
DIRECT_L.initial_point_support_level	Returns initial point support level
DIRECT_L.is_bounds_ignored	Returns is bounds ignored
DIRECT_L.is_bounds_required	Returns is bounds required
DIRECT_L.is_bounds_supported	Returns is bounds supported
DIRECT_L.is_gradient_ignored	Returns is gradient ignored
DIRECT_L.is_gradient_required	Returns is gradient required
DIRECT_L.is_gradient_supported	Returns is gradient supported
DIRECT_L.is_initial_point_ignored	Returns is initial point ignored
DIRECT_L.is_initial_point_required	Returns is initial point required
DIRECT_L.is_initial_point_supported	Returns is initial point supported
DIRECT_L.setting	Return setting

Methods

DIRECT_L.get_nlopt_optimizer()	Return NLopt optimizer type
DIRECT_L.get_support_level()	return support level dictionary
DIRECT_L.gradient_num_diff(x_center, f, epsilon)	We compute the gradient with the numeric differentiation in the parallel way, around the point x_center.
DIRECT_L.optimize(num_vars, objective_function)	Perform optimization.
DIRECT_L.print_options()	Print algorithm-specific options.
DIRECT_L.set_max_evals_grouped(limit)	Set max evals grouped
DIRECT_L.set_options(**kwargs)	Sets or updates values in the options dictionary.
DIRECT_L.wrap_function(function, args)	Wrap the function to implicitly inject the args at the call of the function.