Source code for

# -*- coding: utf-8 -*-
# Copyright 2021 IRT Saint Exupéry,
# 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
# 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
Surface plot

A :class:`.Surfaces` plot represents samples of a functional variable
:math:`z(x,y)` discretized over a 2D mesh. Both evaluations of :math:`z`
and mesh are stored in a :class:`.Dataset`, :math:`z` as a parameter
and the mesh as a metadata.
from __future__ import absolute_import, division, unicode_literals

import matplotlib.pyplot as plt
import matplotlib.tri as mtri
from future import standard_library

from import DatasetPlot


[docs]class Surfaces(DatasetPlot): """ Plot surfaces y_i over the mesh x. """ def _plot( self, mesh, variable, samples=None, colormap="Blues", add_points=False, color="blue", ): """Curve. :param mesh: name of the mesh stored in Dataset.metadata. :type mesh: str :param variable: variable name for the x-axis. :type variable: float :param samples: samples indices. If None, plot all samples. Default: None. :type samples: list(int) :param colormap: colormap. Default: 'Blues'. :type color: str :param add_points: display points over the surface plot. Default: False. :type add_points: bool :param color: point color. Default: blue. :type color: str """ x_data = self.dataset.metadata[mesh][:, 0] y_data = self.dataset.metadata[mesh][:, 1] if samples is not None: outputs = self.dataset[variable][variable][samples, :] else: outputs = self.dataset[variable][variable] sample = 0 fig = [] for z_data in outputs: fig.append(plt.figure()) axes = fig[-1].add_subplot(1, 1, 1) triang = mtri.Triangulation(x_data, y_data) tcf = axes.tricontourf(triang, z_data, cmap=colormap) if add_points: axes.scatter(x_data, y_data, color=color) axes.set_title(variable) fig[-1].colorbar(tcf) fig[-1] = plt.gcf() sample += 1 return fig