Source code for gemseo.post.topology_view

# 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.
"""View of the solution of a 2D topology optimization problem."""

from __future__ import annotations

from typing import TYPE_CHECKING

from matplotlib import colors
from matplotlib import pyplot as plt

from gemseo.post.opt_post_processor import OptPostProcessor

if TYPE_CHECKING:
    from collections.abc import Iterable


[docs] class TopologyView(OptPostProcessor): """Visualization of the solution of a 2D topology optimization problem.""" DEFAULT_FIG_SIZE = (11.0, 6.0) def _plot( self, n_x: int, n_y: int, observable: str | None = None, iterations: int | Iterable[int] | None = None, ) -> None: """Plot the design variable or an observable field patch plot. Args: n_x: The number of elements in the horizontal direction. n_y: The number of elements in the vertical direction. observable: The name of the observable to be plotted. It should be of size ``n_x*n_y``. iterations: The iterations of the optimization history. If ``None``, the last iteration is taken. """ if iterations is None: iterations = [len(self.database)] elif isinstance(iterations, int): iterations = [iterations] for iteration in iterations: plt.ion() # Ensure that redrawing is possible design = self.database.get_x_vect(iteration) fig, ax = plt.subplots() if observable: data = ( -self.database.get_function_value(observable, design) .reshape((n_x, n_y)) .T ) else: data = -design.reshape((n_x, n_y)).T im = ax.imshow( data, cmap="gray", interpolation="none", norm=colors.Normalize(vmin=-1, vmax=0), ) im.set_array(data) plt.axis("off") self._add_figure(fig, f"configuration_{iteration}")