Source code for gemseo.problems.scalable.data_driven.factory
# 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: Matthias De Lozzo
# OTHER AUTHORS - MACROSCOPIC CHANGES
"""Scalable model factory.
This module contains the :class:`.ScalableModelFactory` which is a factory
to create a :class:`.ScalableModel` from its class name by means of the
:meth:`.ScalableModelFactory.create` method. It is also possible to get a list
of available scalable models
(see :attr:`.ScalableModelFactory.scalable_models` method)
and to check is a type of scalable model is available
(see :meth:`.ScalableModelFactory.is_available` method)
"""
from __future__ import annotations
from gemseo.core.base_factory import BaseFactory
from gemseo.problems.scalable.data_driven.model import ScalableModel
[docs]
class ScalableModelFactory(BaseFactory):
"""This factory instantiates a class:`.ScalableModel` from its class name.
The class can be internal to |g| or located in an external module whose path is
provided to the constructor.
"""
_CLASS = ScalableModel
_MODULE_NAMES = ("gemseo.problems.scalable",)
[docs]
def create(self, model_name: str, data, sizes=None, **parameters):
"""Create a scalable model.
:param str model_name: name of the scalable model (its class name)
:param Dataset data: learning dataset.
:param dict sizes: sizes of input and output variables.
If ``None``, use the original sizes.
Default: None.
:param parameters: model parameters
:return: model_name scalable model
"""
return super().create(model_name, data=data, sizes=sizes, **parameters)
@property
def scalable_models(self) -> list[str]:
"""Lists the available classes for scalable models.
:returns: the list of classes names.
:rtype: list(str)
"""
return self.class_names