COBYLA¶

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

Bases: qiskit.algorithms.optimizers.scipy_optimizer.SciPyOptimizer

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.

Parameters

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.
options (Optional[dict]) – A dictionary of solver options.
kwargs – additional kwargs for scipy.optimize.minimize.

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

settings¶