Source code for gemseo.uncertainty.distributions.base_settings.triangular_settings

# 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 settings for defining a triangular distribution."""

from __future__ import annotations

from typing import TYPE_CHECKING
from typing import Final

from pydantic import Field
from pydantic import model_validator

from gemseo.uncertainty.distributions.base_distribution_settings import (
    BaseDistribution_Settings,
)

if TYPE_CHECKING:
    from typing_extensions import Self


_MAXIMUM: Final[float] = 1.0
"""The default value of maximum."""

_MINIMUM: Final[float] = 0.0
"""The default value of minimum."""

_MODE: Final[float] = 0.5
"""The default value of mode."""




class BaseTriangularDistribution_Settings(BaseDistribution_Settings):  # noqa: N801
    """The base settings of a triangular distribution."""

    minimum: float = Field(
        default=_MINIMUM,
        description="The minimum of the triangular random variable.",
    )

    maximum: float = Field(
        default=_MAXIMUM,
        description="The maximum of the triangular random variable.",
    )

    mode: float = Field(
        default=_MODE,
        description="The mode of the triangular random variable.",
    )

    @model_validator(mode="after")
    def __validate(self) -> Self:
        if not (self.minimum < self.mode < self.maximum):
            msg = (
                "The parameters of the triangular distribution do not satisfy "
                "the order: minimum < mode < maximum."
            )
            raise ValueError(msg)

        return self