# 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.
# Contributors:
# INITIAL AUTHORS - API and implementation and/or documentation
# :author: Pierre-Jean Barjhoux
# OTHER AUTHORS - MACROSCOPIC CHANGES
"""A matrix of constraint history plots."""
from __future__ import annotations
from math import ceil
from typing import ClassVar
from matplotlib import pyplot
from matplotlib.colors import ListedColormap
from matplotlib.colors import SymLogNorm
from matplotlib.ticker import MaxNLocator
from numpy import abs as np_abs
from numpy import arange
from numpy import atleast_2d
from numpy import atleast_3d
from numpy import diff
from numpy import flip
from numpy import interp
from numpy import max as np_max
from numpy import sign
from gemseo.post.base_post import BasePost
from gemseo.post.constraints_history_settings import ConstraintsHistory_Settings
from gemseo.post.core.colormaps import RG_SEISMIC
[docs]
class ConstraintsHistory(BasePost[ConstraintsHistory_Settings]):
r"""A matrix of constraint history plots.
A blue line represents the values of a constraint w.r.t. the iterations.
A background color indicates whether the constraint is satisfied (green), active
(white) or violated (red).
A horizontal black line indicates the value for which an inequality constraint is
active or an equality constraint is satisfied, namely :math:`0`. A horizontal black
dashed line indicates the value below which an inequality constraint is satisfied
*with a tolerance level*, namely :math:`\varepsilon`.
For an equality constraint, the horizontal dashed black lines indicate the values
between which the constraint is satisfied *with a tolerance level*, namely
:math:`-\varepsilon` and :math:`\varepsilon`.
A vertical black line indicates the last iteration (or pseudo-iteration) where the
constraint is (or should be) active.
"""
Settings: ClassVar[type[ConstraintsHistory_Settings]] = ConstraintsHistory_Settings
def _plot(self, settings: ConstraintsHistory_Settings) -> None:
"""
Raises:
ValueError: When an item of ``constraint_names`` is not a constraint name.
""" # noqa: D205, D212, D415
constraint_names = settings.constraint_names
line_style = settings.line_style
add_points = settings.add_points
all_constraint_names = (
self.optimization_problem.constraints.original_to_current_names.keys()
)
for constraint_name in constraint_names:
if constraint_name not in all_constraint_names:
msg = (
"Cannot build constraints history plot, "
f"{constraint_name} is not a constraint name."
)
raise ValueError(msg)
constraint_names = self.optimization_problem.get_function_names(
constraint_names
)
constraint_histories, constraint_names, _ = self.database.get_history_array(
function_names=constraint_names, with_x_vect=False
)
# harmonization of tables format because constraints can be vectorial
# or scalars. *vals.shape[0] = iteration, *vals.shape[1] = cstr values
constraint_histories = atleast_3d(constraint_histories)
constraint_histories = constraint_histories.reshape((
constraint_histories.shape[0],
constraint_histories.shape[1] * constraint_histories.shape[2],
))
# prepare the main window
fig, axs = pyplot.subplots(
nrows=ceil(len(constraint_names) / 2),
ncols=2,
sharex=True,
figsize=settings.fig_size,
)
fig.suptitle("Evolution of the constraints w.r.t. iterations", fontsize=14)
iterations = arange(len(constraint_histories))
n_iterations = len(iterations)
eq_constraint_names = [
f.name
for f in self.optimization_problem.constraints.get_equality_constraints()
]
# for each subplot
for constraint_history, constraint_name, ax in zip(
constraint_histories.T, constraint_names, axs.ravel()
):
cmap: str | ListedColormap
f_name = constraint_name.split("[")[0]
is_eq_constraint = f_name in eq_constraint_names
if is_eq_constraint:
cmap = "seismic"
constraint_type = "equality"
tolerance = self.optimization_problem.tolerances.equality
else:
cmap = RG_SEISMIC
constraint_type = "inequality"
tolerance = self.optimization_problem.tolerances.inequality
# prepare the graph
ax.grid(True)
ax.set_title(f"{constraint_name} ({constraint_type})")
ax.set_xticks(range(n_iterations))
ax.set_xticklabels(range(1, n_iterations + 1))
ax.get_xaxis().set_major_locator(MaxNLocator(integer=True))
ax.axhline(tolerance, color="k", linestyle="--")
ax.axhline(0.0, color="k")
if is_eq_constraint:
ax.axhline(-tolerance, color="k", linestyle="--")
# Add line and points
ax.plot(iterations, constraint_history, linestyle=line_style)
if add_points:
ax.scatter(iterations, constraint_history)
# Plot color bars
maximum = np_max(np_abs(constraint_history))
margin = 2 * maximum * 0.05
ax.imshow(
atleast_2d(constraint_history),
cmap=cmap,
interpolation="nearest",
aspect="auto",
norm=SymLogNorm(vmin=-maximum, vmax=maximum, linthresh=1.0),
extent=[-0.5, n_iterations - 0.5, -maximum - margin, maximum + margin],
alpha=0.6,
)
# Plot a vertical line at the last iteration (or pseudo-iteration)
# where the constraint is (or should be) active.
indices_before_sign_change = diff(sign(constraint_history)).nonzero()[0]
if indices_before_sign_change.size != 0:
index_before_last_sign_change = indices_before_sign_change[-1]
indices = [
index_before_last_sign_change,
index_before_last_sign_change + 1,
]
constraint_values = constraint_history[indices]
iteration_values = iterations[indices]
if constraint_values[1] < constraint_values[0]:
constraint_values = flip(constraint_values)
iteration_values = flip(iteration_values)
ax.axvline(interp(0.0, constraint_values, iteration_values), color="k")
fig.tight_layout()
self._add_figure(fig)
