# Source code for gemseo.post.dataset.curves

# -*- coding: utf-8 -*-
# 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
"""Draw curves from a :class:.Dataset.

A :class:.Curves plot represents samples of a functional variable
:math:y(x) discretized over a 1D mesh. Both evaluations of :math:y
and mesh are stored in a :class:.Dataset, :math:y as a parameter
and the mesh as a metadata.
"""
from __future__ import division, unicode_literals

from typing import List, Mapping, Optional, Sequence

import matplotlib.pyplot as plt
from matplotlib.figure import Figure

from gemseo.post.dataset.dataset_plot import DatasetPlot

[docs]class Curves(DatasetPlot):
"""Plot curves y_i over the mesh x."""

def _plot(
self,
properties,  # type: Mapping
mesh,  # type: str
variable,  # type: str
samples=None,  # type: Optional[Sequence[int]]
):  # type: (...) -> List[Figure]
"""
Args:
mesh: The name of the dataset metadata corresponding to the mesh.
variable: The name of the variable for the x-axis.
samples: The indices of the samples to plot.
If None, plot all the samples.
"""

def lines_gen():
"""Linestyle generator."""
yield "-"
for i in range(1, self.dataset.n_samples):
yield 0, (i, 1, 1, 1)

if samples is not None:
output = self.dataset[variable][variable][samples, :].T
else:
output = self.dataset[variable][variable].T
samples = range(output.shape[1])
n_samples = output.shape[1]

self._set_color(properties, n_samples)
self._set_linestyle(properties, n_samples, [line for line in lines_gen()])

data = (output.T, self.linestyle, self.color, samples)
for output, line_style, color, sample in zip(*data):
plt.plot(