# 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
#
# 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
"""Class to create a normal distribution from the SciPy library.

This class inherits from :class:.SPDistribution.
"""
from __future__ import annotations

from gemseo.uncertainty.distributions.scipy.distribution import SPDistribution

[docs]class SPNormalDistribution(SPDistribution):
"""Create a normal distribution.

Example:
>>> 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,
mu: float = 0.0,
sigma: float = 1.0,
dimension: int = 1,
) -> None:
""".. # noqa: D205,D212,D415
Args:
variable: The name of the normal random variable.
mu: The mean of the normal random variable.
sigma: The standard deviation of the normal random variable.
dimension: The dimension of the normal random variable.
"""
standard_parameters = {self._MU: mu, self._SIGMA: sigma}
parameters = {"loc": mu, "scale": sigma}
super().__init__(variable, "norm", parameters, dimension, standard_parameters)