add test_g3pcx.py

pypop7/optimizers/ga/test_g3pcx.py

@@ -0,0 +1,14 @@
+def test_optimize():
+    import numpy  # engine for numerical computing
+    from pypop7.benchmarks.base_functions import rosenbrock  # function to be minimized
+    from pypop7.optimizers.ga.g3pcx import G3PCX
+    problem = {'fitness_function': rosenbrock,  # to define problem arguments
+               'ndim_problem': 2,
+               'lower_boundary': -5.0 * numpy.ones((2,)),
+               'upper_boundary': 5.0 * numpy.ones((2,))}
+    options = {'max_function_evaluations': 5000,  # to set optimizer options
+               'seed_rng': 2022}
+    g3pcx = G3PCX(problem, options)  # to initialize the black-box optimizer class
+    results = g3pcx.optimize()  # to run the optimization/evolution process
+    assert results['n_function_evaluations'] == 5000
+    assert results['best_so_far_y'] < 1.0