Source code for gemseo.uncertainty.distributions.scipy.normal
# 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
"""The SciPy-based normal distribution."""
from __future__ import annotations
from gemseo.uncertainty.distributions.scipy.distribution import SPDistribution
[docs]
class SPNormalDistribution(SPDistribution):
"""The SciPy-based normal distribution.
Examples:
>>> from gemseo.uncertainty.distributions.scipy.normal import (
... SPNormalDistribution,
... )
>>> distribution = SPNormalDistribution("x", -1, 2)
>>> print(distribution)
norm(mu=-1, sigma=2)
"""
def __init__(
self,
variable: str = SPDistribution.DEFAULT_VARIABLE_NAME,
mu: float = 0.0,
sigma: float = 1.0,
dimension: int = 1,
) -> None:
"""
Args:
mu: The mean of the normal random variable.
sigma: The standard deviation of the normal random variable.
""" # noqa: D205,D212,D415
super().__init__(
variable,
"norm",
{"loc": mu, "scale": sigma},
dimension,
{self._MU: mu, self._SIGMA: sigma},
)