# 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
"""Module with a factory to create an instance of :class:`.SensitivityAnalysis`."""
from __future__ import annotations
from typing import Any
from typing import Collection
from typing import Iterable
from typing import Mapping
from gemseo.algos.doe.doe_lib import DOELibraryOptionType
from gemseo.algos.parameter_space import ParameterSpace
from gemseo.core.discipline import MDODiscipline
from gemseo.core.factory import Factory
from gemseo.uncertainty.sensitivity.analysis import SensitivityAnalysis
[docs]class SensitivityAnalysisFactory:
"""Factory to build instances of :class:`.SensitivityAnalysis`.
At initialization, this factory scans the following modules
to search for subclasses of this class:
- the modules located in ``gemseo.uncertainty.sensitivity`` and its sub-packages,
- the modules referenced in the ``GEMSEO_PATH,``
- the modules referenced in the ``PYTHONPATH`` and starting with ``gemseo_``.
Then, it can check if a class is present or return the list of available classes.
Lastly, it can create an instance of a class.
Examples:
>>> from numpy import pi
>>> from gemseo.api import create_discipline, create_parameter_space
>>> from gemseo.uncertainty.sensitivity.factory import (
... SensitivityAnalysisFactory
... )
>>>
>>> expressions = {"y": "sin(x1)+7*sin(x2)**2+0.1*x3**4*sin(x1)"}
>>> discipline = create_discipline(
... "AnalyticDiscipline", expressions=expressions
... )
>>>
>>> parameter_space = create_parameter_space()
>>> parameter_space.add_random_variable(
... "x1", "OTUniformDistribution", minimum=-pi, maximum=pi
... )
>>> parameter_space.add_random_variable(
... "x2", "OTUniformDistribution", minimum=-pi, maximum=pi
... )
>>> parameter_space.add_random_variable(
... "x3", "OTUniformDistribution", minimum=-pi, maximum=pi
... )
>>>
>>> factory = SensitivityAnalysisFactory()
>>> analysis = factory.create(
... "MorrisIndices", discipline, parameter_space, n_replicates=5
... )
>>> indices = analysis.compute_indices()
"""
def __init__(self) -> None: # noqa: D107
self.factory = Factory(SensitivityAnalysis, ("gemseo.uncertainty.sensitivity",))
[docs] def create(
self,
sensitivity_analysis: str,
disciplines: Collection[MDODiscipline],
parameter_space: ParameterSpace,
n_samples: int | None = None,
output_names: Iterable[str] = None,
algo: str | None = None,
algo_options: Mapping[str, DOELibraryOptionType] | None = None,
formulation: str = "MDF",
**formulation_options: Any,
) -> SensitivityAnalysis:
"""Create the sensitivity analysis.
Args:
sensitivity_analysis: The name of a class
defining a sensitivity analysis.
disciplines: The discipline or disciplines to use for the analysis.
parameter_space: A parameter space.
n_samples: A number of samples.
If ``None``, the number of samples is computed by the algorithm.
output_names: The disciplines' outputs to be considered for the analysis.
If ``None``, use all the outputs.
algo: The name of the DOE algorithm.
If ``None``, use the :attr:`.SensitivityAnalysis.DEFAULT_DRIVER`.
algo_options: The options of the DOE algorithm.
formulation: The name of the :class:`.MDOFormulation` to sample the
disciplines.
**formulation_options: The options of the :class:`.MDOFormulation`.
Returns:
A sensitivity analysis.
"""
return self.factory.create(
sensitivity_analysis,
disciplines=disciplines,
parameter_space=parameter_space,
n_samples=n_samples,
output_names=output_names,
algo=algo,
algo_options=algo_options,
formulation=formulation,
**formulation_options,
)
@property
def available_sensitivity_analyses(self) -> list[str]:
"""The available classes for sensitivity analysis."""
return self.factory.classes
[docs] def is_available(
self,
sensitivity_analysis: str,
) -> bool:
"""Check the availability of a SensitivityAnalysis child.
Args:
sensitivity_analysis: The name of the sensitivity analysis.
Returns:
Whether the type of sensitivity analysis is available.
"""
return self.factory.is_available(sensitivity_analysis)
