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
"""Draw surfaces from a :class:`.Dataset`.

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 division, unicode_literals

from typing import List, Mapping, Optional, Sequence

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

from import DatasetPlot

[docs]class Surfaces(DatasetPlot): """Plot surfaces y_i over the mesh x.""" def _plot( self, properties, # type: Mapping mesh, # type: str variable, # type: str samples=None, # type:Optional[Sequence[int]] add_points=False, # type: bool ): # 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 samples. add_points: If True then display the samples over the surface plot. """ color = properties.get(self.COLOR) or "blue" colormap = properties.get(self.COLORMAP) or "Blues" 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, variable_component in zip(outputs, self.dataset.row_names): fig.append(plt.figure()) axes = fig[-1].add_subplot(1, 1, 1) triangle = mtri.Triangulation(x_data, y_data) tcf = axes.tricontourf(triangle, z_data, cmap=colormap) if add_points: axes.scatter(x_data, y_data, color=color) axes.set_title("{} - {}".format(variable, variable_component)) fig[-1].colorbar(tcf) fig[-1] = plt.gcf() sample += 1 return fig