Source code for

# 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
r"""Draw a variable versus two others from a :class:`.Dataset`.

A :class:`.ZvsXY` plot represents the variable :math:`z` with respect to
:math:`x` and :math:`y` as a surface plot, based on a set of points
:points :math:`\{x_i,y_i,z_i\}_{1\leq i \leq n}`. This interpolation is
relies on the Delaunay triangulation of :math:`\{x_i,y_i\}_{1\leq i \leq n}`
from __future__ import annotations

from typing import Iterable
from typing import Sequence

import matplotlib.tri as mtri
from matplotlib.axes import Axes
from matplotlib.figure import Figure

from gemseo.core.dataset import Dataset
from import DatasetPlot

[docs]class ZvsXY(DatasetPlot): """Plot surface z versus x,y.""" def __init__( self, dataset: Dataset, x: str, y: str, z: str, x_comp: int = 0, y_comp: int = 0, z_comp: int = 0, add_points: bool = False, fill: bool = True, levels: int | Sequence[int] = None, other_datasets: Iterable[Dataset] = None, ) -> None: """ Args: x: The name of the variable on the x-axis. y: The name of the variable on the y-axis. z: The name of the variable on the z-axis. x_comp: The component of x. y_comp: The component of y. z_comp: The component of z. add_points: Whether to display the entries of the dataset as points above the surface. fill: Whether to generate a filled contour plot. levels: Either the number of contour lines or the values of the contour lines in increasing order. If ``None``, select them automatically. other_datasets: Additional datasets to be plotted as points above the surface. """ # noqa: D205, D212, D415 super().__init__( dataset=dataset, x=x, y=y, z=z, x_comp=x_comp, y_comp=y_comp, z_comp=z_comp, add_points=add_points, other_datasets=other_datasets, fill=fill, levels=levels, ) def _plot( self, fig: None | Figure = None, axes: None | Axes = None, ) -> list[Figure]: other_datasets = self._param.other_datasets x = self._param.x y = self._param.y z = self._param.z x_comp = self._param.x_comp y_comp = self._param.y_comp z_comp = self._param.z_comp n_series = 1 if other_datasets: n_series += len(other_datasets) self._set_color(n_series) x_data = self.dataset[x][:, x_comp] y_data = self.dataset[y][:, y_comp] z_data = self.dataset[z][:, z_comp] fig, axes = self._get_figure_and_axes(fig, axes) grid = mtri.Triangulation(x_data, y_data) levels = self._param.levels options = {"cmap": self.colormap} if levels is not None: options["levels"] = levels if self._param.fill: tcf = axes.tricontourf(grid, z_data, **options) else: tcf = axes.tricontour(grid, z_data, **options) if self._param.add_points: axes.scatter(x_data, y_data, color=self.color[0]) if other_datasets: for index, dataset in enumerate(other_datasets): x_data = dataset[x][:, x_comp] y_data = dataset[y][:, y_comp] axes.scatter(x_data, y_data, color=self.color[index + 1]) if not self.xlabel: self.xlabel = self._get_component_name(x, x_comp, self.dataset.sizes) if not self.ylabel: self.ylabel = self._get_component_name(y, y_comp, self.dataset.sizes) if not self.zlabel: self.zlabel = self._get_component_name(z, z_comp, self.dataset.sizes) if not self.title: self.title = self.zlabel axes.set_xlabel(self.xlabel) axes.set_ylabel(self.ylabel) axes.set_title(self.title) fig.colorbar(tcf, ax=axes) return [fig]