def non_dominated(self):
"""Fix this. check if nd2 and nds mean the same thing"""
obj = self.objectives
num_obj = obj.shape[1]
if num_obj == 2:
non_dom_front = nd2(obj)
else:
non_dom_front = nds(obj)
if isinstance(non_dom_front, tuple):
self.non_dom = self.objectives[non_dom_front[0][0]]
elif isinstance(non_dom_front, np.ndarray):
self.non_dom = self.objectives[non_dom_front]
else:
print("Non Dom error Line 285 in population.py")
return non_dom_front
from pyDOE import lhs
from desdeo_emo.EAs.RVEA import RVEA, oRVEA, robust_RVEA
from pygmo import non_dominated_front_2d as nd2
problem_names = ["ZDT1", "ZDT2", "ZDT3", "ZDT4", "ZDT6"]
num_var = {"ZDT1": 30, "ZDT2": 30, "ZDT3": 30, "ZDT4": 10, "ZDT6": 10}
for problem_name in problem_names:
prob = test_problem_builder(problem_name)
x = lhs(num_var[problem_name], 250)
y = prob.evaluate(x)
data_pareto = nd2(y.objectives)
data_pareto = y.objectives[data_pareto]
x_names = [f"x{i}" for i in range(1, num_var[problem_name] + 1)]
y_names = ["f1", "f2"]
data = pd.DataFrame(np.hstack((x, y.objectives)),
columns=x_names + y_names)
problem = DataProblem(data=data,
variable_names=x_names,
objective_names=y_names)
problem.train(LipschitzianRegressor)
evolver_L_opt = oRVEA(problem, use_surrogates=True)
while evolver_L_opt.continue_evolution():