def notify(self, algorithm):
problem = algorithm.problem
pcp = PCP(title=("Gen %s" % algorithm.n_gen, {
'pad': 30
}),
bounds=(problem.xl, problem.xu),
labels=["$x_%s$" % k for k in range(problem.n_var)])
pcp.set_axis_style(color="grey", alpha=0.5)
pcp.add(algorithm.pop.get("X"),
color="black",
alpha=0.8,
linewidth=1.5)
if algorithm.off is not None:
pcp.add(algorithm.off.get("X"),
color="blue",
alpha=0.8,
linewidth=0.5)
pcp.add(algorithm.opt.get("X"), color="red", linewidth=4)
pcp.do()
self.video.record()
verbose=False)
print(ret.F)
with Video(GIF("animation.gif")) as vid:
for algorithm in ret.history:
if algorithm.n_gen % 5 == 0:
X, F = algorithm.pop.get("X", "F")
nds = NonDominatedSorting().do(F, only_non_dominated_front=True)
other = [k for k in range(len(F)) if k not in nds]
fig, (ax1, ax2) = plt.subplots(2, figsize=(8, 6))
fig.suptitle("%s - %s - Gen %s" %
("ZDT1", "NSGA2", algorithm.n_gen),
fontsize=16)
pcp = PCP(ax=ax1, bounds=(problem.xl, problem.xu))
pcp.set_axis_style(color="black", alpha=0.7)
pcp.add(X[other], color="blue", linewidth=0.5)
pcp.add(X[nds], color="red", linewidth=2)
pcp.do()
sc = Scatter(ax=ax2)
sc.add(F[other], color="blue")
sc.add(F[nds], color="red")
sc.add(problem.pareto_front(), plot_type="line", color="black")
sc.do()
vid.record()
from pymoo.factory import get_problem, get_reference_directions
from pymoo.visualization.pcp import PCP
ref_dirs = get_reference_directions("das-dennis", 6, n_partitions=5) * [2, 4, 8, 16, 32, 64]
F = get_problem("dtlz1").pareto_front(ref_dirs)
PCP().add(F).show()
plot = PCP()
plot.set_axis_style(color="grey", alpha=0.5)
plot.add(F, color="grey", alpha=0.3)
plot.add(F[50], linewidth=5, color="red")
plot.add(F[75], linewidth=5, color="blue")
plot.show()
plot.reset()
plot.normalize_each_axis = False
plot.bounds = [[1, 1, 1, 2, 2, 5], [32, 32, 32, 32, 32, 32]]
plot.show()