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