def generate_wfg_pareto_samples(n_samples):
y = np.zeros((n_samples, n_obj))
for n in range(n_samples):
z = wfg.random_soln(k, l, func.__name__)
y[n, :] = func(z, k, n_obj)
p = Pareto_split(y)[0]
return p
#
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import wfg
N = 500 # Number of points to plot
M = 3 # Number of objectives
kfactor = 2
lfactor = 2
k = kfactor*(M-1)
l = lfactor*2
func = wfg.WFG1
y = np.zeros((N, M))
for n in range(N):
z = wfg.random_soln(k, l, func.__name__)
y[n,:] = func(z, k, M)
fig = plt.figure()
ax = Axes3D(fig)
ax.scatter(y[:,0], y[:,1], y[:,2])
plt.suptitle(func.__name__)
plt.show(block=True)
