# 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
"""A mixin for the probability distribution of a scalar random variable."""
from __future__ import annotations
from abc import abstractmethod
from collections.abc import Mapping
from typing import TYPE_CHECKING
from typing import ClassVar
from typing import Union
from matplotlib import pyplot as plt
from numpy import arange
from gemseo.utils.matplotlib_figure import save_show_figure
if TYPE_CHECKING:
from pathlib import Path
from matplotlib.figure import Figure
from gemseo.uncertainty.distributions.base_joint import BaseJointDistribution
StandardParametersType = Mapping[str, Union[str, int, float]]
ParametersType = Union[tuple[str, int, float], StandardParametersType]
[docs]
class ScalarDistributionMixin:
"""A mixin for the probability distribution of a scalar random variable."""
JOINT_DISTRIBUTION_CLASS: ClassVar[type[BaseJointDistribution]]
"""The class of the joint distribution associated with this distribution."""
[docs]
def plot(
self,
show: bool = True,
save: bool = False,
file_path: str | Path = "",
directory_path: str | Path = "",
file_name: str = "",
file_extension: str = "",
) -> Figure:
"""Plot both probability and cumulative density functions.
Args:
save: Whether to save the figure.
show: Whether to display the figure.
file_path: The path of the file to save the figure.
If the extension is missing, use ``file_extension``.
If empty,
create a file path
from ``directory_path``, ``file_name`` and ``file_extension``.
directory_path: The path of the directory to save the figures.
If empty, use the current working directory.
file_name: The name of the file to save the figures.
If empty, use a default one generated by the post-processing.
file_extension: A file extension, e.g. ``'png'``, ``'pdf'``, ``'svg'``, ...
If empty, use a default file extension.
Returns:
The figure.
"""
l_b = self.num_lower_bound
u_b = self.num_upper_bound
x_values = arange(l_b, u_b, (u_b - l_b) / 100)
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(6.4, 3.2))
fig.suptitle(repr(self))
ax1.plot(x_values, [self._pdf(x_value) for x_value in x_values])
ax1.grid()
ax1.set_ylabel("Probability density function")
ax1.set_box_aspect(1)
ax2.plot(x_values, [self._cdf(x_value) for x_value in x_values])
ax2.grid()
ax2.set_ylabel("Cumulative distribution function")
ax2.yaxis.tick_right()
ax2.set_box_aspect(1)
if save:
file_path = self._file_path_manager.create_file_path(
file_path=file_path,
file_name=file_name,
directory_path=directory_path,
file_extension=file_extension,
)
else:
file_path = ""
save_show_figure(fig, show, file_path)
return fig
@abstractmethod
def _pdf(
self,
value: float,
) -> float:
"""Probability density function (PDF).
Args:
value: An evaluation point.
Returns:
The PDF value at the evaluation point.
"""
@abstractmethod
def _cdf(
self,
level: float,
) -> float:
"""Cumulative distribution function (CDF).
Args:
level: A probability level.
Returns:
The CDF value for the probability level.
"""
