Source code for qiskit_algorithms.optimizers.cobyla

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"""Constrained Optimization By Linear Approximation optimizer."""

from __future__ import annotations

from .scipy_optimizer import SciPyOptimizer


[docs]class COBYLA(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. Uses scipy.optimize.minimize COBYLA. For further detail, please refer to https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html """ _OPTIONS = ["maxiter", "disp", "rhobeg"] # pylint: disable=unused-argument, too-many-positional-arguments def __init__( self, maxiter: int = 1000, disp: bool = False, rhobeg: float = 1.0, tol: float | None = None, options: dict | None = None, **kwargs, ) -> None: """ Args: maxiter: Maximum number of function evaluations. disp: Set to True to print convergence messages. rhobeg: Reasonable initial changes to the variables. tol: Final accuracy in the optimization (not precisely guaranteed). This is a lower bound on the size of the trust region. options: A dictionary of solver options. kwargs: additional kwargs for scipy.optimize.minimize. """ if options is None: options = {} for k, v in list(locals().items()): if k in self._OPTIONS: options[k] = v super().__init__(method="COBYLA", options=options, tol=tol, **kwargs)