# Source code for gemseo.uncertainty.distributions.scipy.triangular

# Copyright 2021 IRT Saint Exupéry, https://www.irt-saintexupery.com
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# Lesser General Public License for more details.
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# You should have received a copy of the GNU Lesser General Public License
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# 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 triangular 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 SPTriangularDistribution(SPDistribution): """Create a triangular distribution. Example: >>> from gemseo.uncertainty.distributions.scipy.triangular import ( ... SPTriangularDistribution ... ) >>> distribution = SPTriangularDistribution('x', -1, 0, 1) >>> print(distribution) triang(lower=-1, mode=0, upper=1) """ def __init__( self, variable: str, minimum: float = 0.0, mode: float = 0.5, maximum: float = 1.0, dimension: int = 1, ) -> None: """ Args: variable: The name of the triangular random variable. minimum: The minimum of the triangular random variable. mode: The mode of the triangular random variable. maximum: The maximum of the triangular random variable. dimension: The dimension of the triangular random variable. """ # noqa: D205,D212,D415 parameters = { "loc": minimum, "scale": maximum - minimum, "c": (mode - minimum) / float(maximum - minimum), } standard_parameters = { self._LOWER: minimum, self._MODE: mode, self._UPPER: maximum, } super().__init__(variable, "triang", parameters, dimension, standard_parameters)