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():
evolver_L_opt.iterate()
evolver_L = RVEA(problem, use_surrogates=True)
while evolver_L.continue_evolution():
evolver_L.iterate()
evolver_L_robust = robust_RVEA(problem, use_surrogates=True)
while evolver_L_robust.continue_evolution():
evolver_L_robust.iterate()
problem.train(GaussianProcessRegressor)
evolver_G_opt = oRVEA(problem, use_surrogates=True)
while evolver_G_opt.continue_evolution():
evolver_G_opt.iterate()
evolver_G = RVEA(problem, use_surrogates=True)
while evolver_G.continue_evolution():
evolver_G.iterate()
from desdeo_problem.testproblems.TestProblems import test_problem_builder
from desdeo_emo.EAs.RVEA import RVEA
from desdeo_emo.EAs.NSGAIII import NSGAIII
from desdeo_emo.othertools.plotlyanimate import animate_init_, animate_next_
dtlz3 = test_problem_builder("DTLZ3", n_of_variables=12, n_of_objectives=11)
evolver = RVEA(dtlz3, n_iterations=10)
figure = animate_init_(evolver.population.objectives, filename="dtlz3.html")
while evolver.continue_evolution():
evolver.iterate()
figure = animate_next_(
evolver.population.objectives,
figure,
filename="dtlz3.html",
generation=evolver._iteration_counter,
)