Source code for gemseo.algos.linear_solvers.linear_solvers_factory

# -*- coding: utf-8 -*-
# Copyright 2021 IRT Saint Exupéry,
# 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
# 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 - API and implementation and/or documentation
#        :author: Francois Gallard

"""A factory to instantiate linear solvers from their class names."""

from __future__ import division, unicode_literals

import logging
from typing import Any, List

from numpy import ndarray

from gemseo.algos.driver_factory import DriverFactory
from gemseo.algos.linear_solvers.linear_problem import LinearProblem
from gemseo.algos.linear_solvers.linear_solver_lib import LinearSolverLib

LOGGER = logging.getLogger(__name__)

[docs]class LinearSolversFactory(DriverFactory): """MDA factory to create the MDA from a name or a class.""" def __init__(self): # type: (...) -> None super(LinearSolversFactory, self).__init__( LinearSolverLib, "gemseo.algos.linear_solvers" ) @property def linear_solvers(self): # type: (...) -> List[str] """Return the available classes names. Returns: The names of the classes. """ return self.factory.classes
[docs] def is_available( self, solver_name # type: str ): """Check the availability of a LinearSolver. Args: solver_name: The name of the LinearSolver. Returns: Whether the LinearSolver is available. """ return super(LinearSolversFactory, self).is_available(solver_name)
[docs] def execute( self, problem, # type: LinearProblem algo_name, # type: str **options # type: Any ): # type: (...) -> ndarray """Execute the driver. Find the appropriate library and execute the driver on the problem to solve the linear system LHS.x = RHS. Args: problem: The linear equations and right hand side (lhs, rhs) that defines the linear problem. XXX is a tuple expected? algo_name: The algorithm name. options: The options for the algorithm, see associated JSON file. Returns: The solution. """ lib = self.create(algo_name) return lib.execute(problem, algo_name=algo_name, **options)