Source code for qiskit_algorithms.optimizers.powell

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"""Powell optimizer."""
from __future__ import annotations

from .scipy_optimizer import SciPyOptimizer


[docs]class POWELL(SciPyOptimizer): """ Powell optimizer. The Powell algorithm performs unconstrained optimization; it ignores bounds or constraints. Powell is a *conjugate direction method*: it performs sequential one-dimensional minimization along each directional vector, which is updated at each iteration of the main minimization loop. The function being minimized need not be differentiable, and no derivatives are taken. Uses scipy.optimize.minimize Powell. For further detail, please refer to See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html """ _OPTIONS = ["maxiter", "maxfev", "disp", "xtol"] # pylint: disable=unused-argument, too-many-positional-arguments def __init__( self, maxiter: int | None = None, maxfev: int = 1000, disp: bool = False, xtol: float = 0.0001, tol: float | None = None, options: dict | None = None, **kwargs, ) -> None: """ Args: maxiter: Maximum allowed number of iterations. If both maxiter and maxfev are set, minimization will stop at the first reached. maxfev: Maximum allowed number of function evaluations. If both maxiter and maxfev are set, minimization will stop at the first reached. disp: Set to True to print convergence messages. xtol: Relative error in solution xopt acceptable for convergence. tol: Tolerance for termination. 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__("Powell", options=options, tol=tol, **kwargs)