# COBYLA¶

class COBYLA(maxiter=1000, disp=False, rhobeg=1.0, tol=None)[source]

Bases : qiskit.aqua.components.optimizers.optimizer.Optimizer

Constrained Optimization By Linear Approximation optimizer.

COBYLA is a numerical optimization method for constrained problems where the derivative of the objective function is not known.

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

Paramètres
• maxiter (int) – Maximum number of function evaluations.

• disp (bool) – Set to True to print convergence messages.

• rhobeg (float) – Reasonable initial changes to the variables.

• tol (Optional[float]) – Final accuracy in the optimization (not precisely guaranteed). This is a lower bound on the size of the trust region.

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

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

is_gradient_required

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