Source code for gemseo.algos.sequence_transformer.relaxation.over_relaxation

# Copyright 2021 IRT Saint Exupéry, https://www.irt-saintexupery.com
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License version 3 as published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
# Contributors:
#    INITIAL AUTHORS - initial API and implementation and/or initial
#                           documentation
#        :author: Sebastien Bocquet, Alexandre Scotto Di Perrotolo
#    OTHER AUTHORS   - MACROSCOPIC CHANGES
"""The over-relaxation method."""

from __future__ import annotations

from typing import TYPE_CHECKING

from gemseo.algos.sequence_transformer.sequence_transformer import SequenceTransformer

if TYPE_CHECKING:
    from typing import ClassVar

    from numpy.typing import NDArray


[docs] class OverRelaxation(SequenceTransformer): """The over relaxation method.""" _MINIMUM_NUMBER_OF_ITERATES: ClassVar[int] = 2 _MINIMUM_NUMBER_OF_RESIDUALS: ClassVar[int] = 0 def __init__(self, factor: float = 1.0) -> None: """ Args: factor: The relaxation factor lying within ]0, 2]. Raises: ValueError if the provided relaxation factor lies outside ]0, 2]. """ # noqa:D205 D212 D415 super().__init__() self.factor = factor @property def factor(self) -> float: """The over-relaxation factor.""" return self.__factor @factor.setter def factor(self, factor: float) -> None: if not (0 < factor <= 2): msg = "Relax factor must lie within ]0, 2]." raise ValueError(msg) self.__factor = factor self.clear() def _compute_transformed_iterate(self) -> NDArray: gxn_1, gxn = self._iterates if self.__factor == 1.0: return gxn return self.__factor * gxn + (1.0 - self.__factor) * gxn_1