class TaskTestCase(TestCase): r"""Test case for testing the Task class. Date: April 2019 Author: Klemen Berkovič See Also: * :class:`niapy.util.Task` """ def setUp(self): self.D, self.nFES, self.nGEN = 10, 10, 10 self.Lower, self.Upper = [2, 1, 1], [10, 10, 5] self.task = Task(dimension=self.D, lower=self.Lower, upper=self.Upper, problem='sphere', max_evals=self.nFES, max_iters=self.nGEN, cutoff_value=0.0) def test_dim_ok(self): self.assertEqual(self.D, self.task.dimension) self.assertEqual(self.D, self.task.dimension) def test_lower(self): self.assertTrue( np.array_equal(full_array(self.Lower, self.D), self.task.lower)) self.assertTrue( np.array_equal(full_array(self.Lower, self.D), self.task.lower)) def test_upper(self): self.assertTrue( np.array_equal(full_array(self.Upper, self.D), self.task.upper)) self.assertTrue( np.array_equal(full_array(self.Upper, self.D), self.task.upper)) def test_range(self): self.assertTrue( np.array_equal( full_array(self.Upper, self.D) - full_array(self.Lower, self.D), self.task.range)) self.assertTrue( np.array_equal( full_array(self.Upper, self.D) - full_array(self.Lower, self.D), self.task.range)) def test_max_iters(self): self.assertEqual(self.nGEN, self.task.max_iters) def test_max_evals(self): self.assertEqual(self.nFES, self.task.max_evals) def test_is_feasible(self): x = np.full(self.D, 2) self.assertTrue(self.task.is_feasible(x)) x = np.full(self.D, 3) self.assertTrue(self.task.is_feasible(x)) x = default_rng().uniform(self.task.lower, self.task.upper, self.D) self.assertTrue(self.task.is_feasible(x)) x = np.full(self.D, -20) self.assertFalse(self.task.is_feasible(x)) x = np.full(self.D, 20) self.assertFalse(self.task.is_feasible(x)) def test_next_iter(self): for i in range(self.nGEN): self.assertFalse(self.task.stopping_condition()) self.task.next_iter() self.assertTrue(self.task.stopping_condition()) def test_stop_cond_iter(self): for i in range(self.nGEN): self.assertFalse(self.task.stopping_condition_iter(), msg='Error at %s iteration!!!' % i) self.assertTrue(self.task.stopping_condition_iter()) def test_eval(self): x = np.ones(self.D) for i in range(self.nFES): self.assertAlmostEqual(self.task.eval(x), self.D, msg='Error at %s iteration!!!' % i) self.assertTrue(self.task.stopping_condition()) def test_eval_over_max_evals(self): x = np.ones(self.D) for i in range(self.nFES): self.task.eval(x) self.assertEqual(np.inf, self.task.eval(x)) self.assertTrue(self.task.stopping_condition()) def test_eval_over_max_iters(self): x = np.ones(self.D) for i in range(self.nGEN): self.task.next_iter() self.assertEqual(np.inf, self.task.eval(x)) self.assertTrue(self.task.stopping_condition()) def test_evals_count(self): x = np.ones(self.D) for i in range(self.nFES): self.task.eval(x) self.assertEqual(self.task.evals, i + 1, 'Error at %s. evaluation' % (i + 1)) def test_iters_count(self): for i in range(self.nGEN): self.task.next_iter() self.assertEqual(self.task.iters, i + 1, 'Error at %s. iteration' % (i + 1)) def test_stop_cond_evals(self): x = np.ones(self.D) for i in range(self.nFES - 1): self.task.eval(x) self.assertFalse(self.task.stopping_condition()) self.task.eval(x) self.assertTrue(self.task.stopping_condition()) def test_stop_cond_iters(self): for i in range(self.nGEN - 1): self.task.next_iter() self.assertFalse(self.task.stopping_condition()) self.task.next_iter() self.assertTrue(self.task.stopping_condition()) def test_stop_cond_cutoff_value(self): x = np.ones(self.D) for i in range(self.nGEN - 5): self.assertFalse(self.task.stopping_condition()) self.assertEqual(self.D, self.task.eval(x)) self.task.next_iter() x = np.zeros(self.D) self.assertEqual(0, self.task.eval(x)) self.assertTrue(self.task.stopping_condition()) self.assertEqual(self.nGEN - 5, self.task.iters) def test_print_conv_one(self): r1, r2 = [], [] for i in range(self.nFES): x = np.full(self.D, 10 - i) r1.append(i + 1), r2.append(self.task.eval(x)) t_r1, t_r2 = self.task.return_conv() self.assertTrue(np.array_equal(r1, t_r1)) self.assertTrue(np.array_equal(r2, t_r2)) def test_print_conv_two(self): r1, r2 = [], [] for i in range(self.nFES): x = np.full(self.D, 10 - i if i not in (3, 4, 5) else 4) r1.append(i + 1), r2.append(self.task.eval(x)) t_r1, t_r2 = self.task.return_conv() self.assertTrue(np.array_equal(r2, t_r2)) self.assertTrue(np.array_equal(r1, t_r1))
# encoding=utf8 # This is temporary fix to import module from parent folder # It will be removed when package is published on PyPI import sys sys.path.append('../') # End of fix from niapy.task import Task from niapy.problems import Sphere from niapy.algorithms.basic import DifferentialEvolution # Storing improvements during the evolutionary cycle task = Task(max_evals=10000, problem=Sphere(dimension=10)) algo = DifferentialEvolution(population_size=40, crossover_probability=0.9, differential_weight=0.5) best = algo.run(task) evals, x_f = task.return_conv() print(evals) # print function evaluations print(x_f) # print values