Add pypop7/optimizers/cc/test_cosyne.py

pypop7/optimizers/cc/test_cosyne.py

@@ -0,0 +1,15 @@
+def test_optimize():
+    import numpy  # engine for numerical computing
+    from pypop7.benchmarks.base_functions import rosenbrock  # function to be minimized
+    from pypop7.optimizers.cc.cosyne import COSYNE
+    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,
+               'sigma': 1.0}
+    cosyne = COSYNE(problem, options)  # to initialize the black-box optimizer class
+    results = cosyne.optimize()  # to run its optimization/evolution process
+    assert results['n_function_evaluations'] == 5000
+    assert results['best_so_far_y'] < 1.0