Source code for gemseo_umdo.estimators.estimator

# 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.
"""Base estimator of statistic associated with a U-MDO formulation."""
from __future__ import annotations

from abc import ABC
from abc import abstractmethod
from typing import Any
from typing import TYPE_CHECKING

from gemseo.core.base_factory import BaseFactory
from numpy import ndarray

if TYPE_CHECKING:
    from gemseo_umdo.formulations.formulation import UMDOFormulation


[docs]class BaseStatisticEstimator(ABC): """The base estimator of statistics associated with a U-MDO formulation.""" _formulation: UMDOFormulation """The U-MDO formulation.""" def __init__(self, formulation: UMDOFormulation) -> None: """ Args: formulation: The U-MDO formulation. """ # noqa: D205 D212 D415 self._formulation = formulation @abstractmethod def __call__(self, *args: Any, **kwargs: Any) -> float | ndarray: # noqa: D102 ...
[docs]class BaseStatisticEstimatorFactory(BaseFactory): """The factory of :class:`.BaseStatisticEstimator`.""" _CLASS = BaseStatisticEstimator _MODULE_NAMES = ("gemseo_umdo.estimators",)
[docs] def create( self, name: str, formulation: UMDOFormulation, **options: Any, ) -> BaseStatisticEstimator: """Create a statistic estimator. Args: name: The class name of the statistic estimator. formulation: The U-MDO formulation. **options: The options of the statistic estimator. """ return self.create(name, formulation=formulation, **options)