# 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
r"""Draw Andrews curves from a :class:`.Dataset`.
The :class:`.AndrewsCurves` class implements the Andrew plot, a.k.a. Andrews curves,
which is a way to visualize :math:`n` samples of a high-dimensional vector
.. math::
x=(x_1,x_2,\ldots,x_d)\in\mathbb{R}^d
in a 2D referential by projecting each sample
.. math::
x^{(i)}=(x_1^{(i)},x_2^{(i)},\ldots,x_d^{(i)})
onto the vector
.. math::
\left(\frac{1}{\sqrt{2}},\sin(t),\cos(t),\sin(2t),\cos(2t), \ldots\right)
which is composed of the :math:`d` first elements of the Fourier series:
.. math::
f_i(t)=\left(\frac{x_1^{(i)}}{\sqrt{2}},x_2^{(i)}\sin(t),x_3^{(i)}\cos(t),
x_4^{(i)}\sin(2t),x_5^{(i)}\cos(2t),\ldots\right)
Each curve :math:`t\mapsto f_i(t)` is plotted
over the interval :math:`[-\pi,\pi]`
and structure in the data may be visible in these :math:`n` Andrews curves.
A variable name can be passed to the :meth:`.DatasetPlot.execute` method
by means of the :code:`classifier` keyword
in order to color the curves according to the value of the variable name.
This is useful when the data is labeled.
"""
from __future__ import annotations
import matplotlib.pyplot as plt
from matplotlib.axes import Axes
from matplotlib.figure import Figure
from pandas.plotting import andrews_curves
from gemseo.core.dataset import Dataset
from gemseo.post.dataset.dataset_plot import DatasetPlot
[docs]class AndrewsCurves(DatasetPlot):
"""Andrews curves."""
def __init__(
self,
dataset: Dataset,
classifier: str,
) -> None:
"""
Args:
classifier: The name of the variable to group the data.
"""
super().__init__(dataset, classifier=classifier)
def _plot(
self,
fig: None | Figure = None,
axes: None | Axes = None,
) -> list[Figure]:
classifier = self._param.classifier
if classifier not in self.dataset.variables:
raise ValueError(
"Classifier must be one of these names: "
+ ", ".join(self.dataset.variables)
)
dataframe = self.dataset.export_to_dataframe()
label, varname = self._get_label(classifier)
fig, axes = self._get_figure_and_axes(fig, axes)
if self.dataset.strings_encoding[label]:
for comp, codes in self.dataset.strings_encoding[label].items():
column = (self.dataset.get_group(label), label, str(comp))
for key, value in codes.items():
dataframe.loc[dataframe[column] == key, column] = value
andrews_curves(dataframe, varname, ax=axes)
plt.xlabel(self.xlabel)
plt.ylabel(self.ylabel)
plt.title(self.title)
return [fig]
