public release 2.2.0 - see README.md and CHANGES.md for details
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@ -41,11 +41,11 @@ class TestPopulation(unittest.TestCase):
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def setUp(self):
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random.seed(0)
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self.test_dir = tempfile.mkdtemp()
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self.domain = project.Domain()
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self.model_space = project.ModelSpace()
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self.domain.add_param('A', 1.5, 1.0, 2.0, 0.1)
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self.domain.add_param('B', 2.5, 2.0, 3.0, 0.1)
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self.domain.add_param('C', 3.5, 3.0, 4.0, 0.1)
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self.model_space.add_param('A', 1.5, 1.0, 2.0, 0.1)
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self.model_space.add_param('B', 2.5, 2.0, 3.0, 0.1)
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self.model_space.add_param('C', 3.5, 3.0, 4.0, 0.1)
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self.expected_names = ('_gen', '_model', '_particle', '_rfac', 'A', 'B', 'C')
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self.size = POP_SIZE
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@ -115,7 +115,7 @@ class TestPopulation(unittest.TestCase):
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return r
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def test_setup(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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self.assertEqual(self.pop.pos.dtype.names, self.expected_names)
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self.assertEqual(self.pop.pos.shape, (POP_SIZE,))
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np.testing.assert_array_equal(np.arange(POP_SIZE), self.pop.pos['_particle'])
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@ -132,7 +132,7 @@ class TestPopulation(unittest.TestCase):
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def test_setup_with_results(self):
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data_dir = os.path.dirname(os.path.abspath(__file__))
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data_file = os.path.join(data_dir, "test_swarm.setup_with_results.1.dat")
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self.pop.setup(self.size, self.domain, seed_file=data_file, recalc_seed=False)
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self.pop.setup(self.size, self.model_space, seed_file=data_file, recalc_seed=False)
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self.assertEqual(self.pop.pos.dtype.names, self.expected_names)
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self.assertEqual(self.pop.pos.shape, (POP_SIZE,))
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@ -159,7 +159,7 @@ class TestPopulation(unittest.TestCase):
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def test_setup_with_results_recalc(self):
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data_dir = os.path.dirname(os.path.abspath(__file__))
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data_file = os.path.join(data_dir, "test_swarm.setup_with_results.1.dat")
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self.pop.setup(self.size, self.domain, seed_file=data_file, recalc_seed=True)
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self.pop.setup(self.size, self.model_space, seed_file=data_file, recalc_seed=True)
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self.assertEqual(self.pop.pos.dtype.names, self.expected_names)
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self.assertEqual(self.pop.pos.shape, (POP_SIZE,))
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@ -184,12 +184,12 @@ class TestPopulation(unittest.TestCase):
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self.assertAlmostEqual(3.5, self.pop.pos['C'][0], 3)
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def test_setup_with_partial_results(self):
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self.domain.add_param('D', 4.5, 4.0, 5.0, 0.1)
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self.model_space.add_param('D', 4.5, 4.0, 5.0, 0.1)
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self.expected_names = ('_gen', '_model', '_particle', '_rfac', 'A', 'B', 'C', 'D')
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data_dir = os.path.dirname(os.path.abspath(__file__))
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data_file = os.path.join(data_dir, "test_swarm.setup_with_results.1.dat")
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self.pop.setup(self.size, self.domain, seed_file=data_file, recalc_seed=False)
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self.pop.setup(self.size, self.model_space, seed_file=data_file, recalc_seed=False)
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self.assertEqual(self.pop.pos.dtype.names, self.expected_names)
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self.assertEqual(self.pop.pos.shape, (POP_SIZE,))
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@ -214,7 +214,7 @@ class TestPopulation(unittest.TestCase):
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self.assertAlmostEqual(3.5, self.pop.pos['C'][0], 3)
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def test_pos_gen(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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for index, item in enumerate(self.pop.pos_gen()):
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self.assertIsInstance(item, dict)
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self.assertEqual(set(item.keys()), set(self.expected_names))
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@ -242,19 +242,19 @@ class TestPopulation(unittest.TestCase):
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np.testing.assert_array_equal(result, expected)
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def test_randomize(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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self.pop.randomize()
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m = np.mean(self.pop.pos['A'])
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self.assertGreaterEqual(m, self.domain.min['A'])
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self.assertLessEqual(m, self.domain.max['A'])
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self.assertGreaterEqual(m, self.model_space.min['A'])
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self.assertLessEqual(m, self.model_space.max['A'])
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def test_seed(self):
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self.pop.setup(self.size, self.domain)
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self.pop.seed(self.domain.start)
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self.assertAlmostEqual(self.pop.pos['A'][0], self.domain.start['A'], delta=0.001)
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self.pop.setup(self.size, self.model_space)
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self.pop.seed(self.model_space.start)
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self.assertAlmostEqual(self.pop.pos['A'][0], self.model_space.start['A'], delta=0.001)
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def test_add_result(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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i_sample = 1
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i_result = 0
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result = self.pop.pos[i_sample]
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@ -264,12 +264,12 @@ class TestPopulation(unittest.TestCase):
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self.assertEqual(self.pop.best[i_sample], result)
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def test_save_population(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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filename = os.path.join(self.test_dir, "test_save_population.pop")
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self.pop.save_population(filename)
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def test_save_results(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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i_sample = 1
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result = self.pop.pos[i_sample]
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self.pop.add_result(result, 1.0)
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@ -277,17 +277,17 @@ class TestPopulation(unittest.TestCase):
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self.pop.save_results(filename)
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def test_save_array(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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filename = os.path.join(self.test_dir, "test_save_array.pos")
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self.pop.save_array(filename, self.pop.pos)
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def test_load_array(self):
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n = 3
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filename = os.path.join(self.test_dir, "test_load_array")
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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# expected array
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dt_exp = self.pop.get_pop_dtype(self.domain.start)
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dt_exp = self.pop.get_pop_dtype(self.model_space.start)
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a_exp = np.zeros((n,), dtype=dt_exp)
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a_exp['A'] = np.linspace(0, 1, n)
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a_exp['B'] = np.linspace(1, 2, n)
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@ -395,7 +395,7 @@ class TestPopulation(unittest.TestCase):
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self.assertRaises(ValueError, population.Population.constrain_position, pos1, vel1, min1, max1, 'error')
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def test_patch_from_file(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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data_dir = os.path.dirname(os.path.abspath(__file__))
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data_file = os.path.join(data_dir, "test_swarm.setup_with_results.1.dat")
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@ -411,7 +411,7 @@ class TestPopulation(unittest.TestCase):
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np.testing.assert_array_almost_equal(self.pop.pos_patch['C'], expected_pos['C'])
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def test_apply_patch(self):
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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expected_pos = self.pop.pos.copy()
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dt_test = [('A', 'f4'), ('_particle', 'i4'), ('_rfac', 'f4'), ('C', 'f4'), ('_model', 'i4')]
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patch_size = 3
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@ -436,14 +436,14 @@ class TestPopulation(unittest.TestCase):
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self.assert_pop_array_equal(self.pop.pos, expected_pos)
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def test_find_result(self):
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self.domain.min['A'] = -0.1
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self.domain.max['A'] = 0.1
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self.domain.min['B'] = 0.0
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self.domain.max['B'] = 1000.
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self.domain.min['C'] = 9.
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self.domain.max['C'] = 9.001
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self.model_space.min['A'] = -0.1
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self.model_space.max['A'] = 0.1
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self.model_space.min['B'] = 0.0
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self.model_space.max['B'] = 1000.
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self.model_space.min['C'] = 9.
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self.model_space.max['C'] = 9.001
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self.size = 100
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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self.pop.results = self.pop.pos.copy()
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expected_index = 77
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@ -472,7 +472,7 @@ class TestPopulation(unittest.TestCase):
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check the different type conversions.
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the main work is in test_import_positions_array.
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"""
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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source_type = [('A', 'f4'), ('B', 'f4'), ('C', 'f4'), ('D', 'f4'),
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('_model', 'i4'), ('_particle', 'i4'), ('_gen', 'i4'), ('_rfac', 'f4')]
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@ -548,7 +548,7 @@ class TestPopulation(unittest.TestCase):
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- no range or duplicate checking.
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- missing parameter.
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"""
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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source_type = [('A', 'f4'), ('B', 'f4'), ('C', 'f4'), ('D', 'f4'),
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('_model', 'i4'), ('_particle', 'i4'), ('_gen', 'i4'), ('_rfac', 'f4')]
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source = np.array([(1.0, 0.0, 0.0, 0.0, 0, 0, 0, 0.0),
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@ -584,7 +584,7 @@ class TestPopulation(unittest.TestCase):
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- range checks.
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- de-duplication.
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"""
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self.pop.setup(self.size, self.domain)
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self.pop.setup(self.size, self.model_space)
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self.pop.position_constrain_mode = 'error'
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source_type = [('A', 'f8'), ('B', 'f8'), ('C', 'f8'),
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('_model', 'i8'), ('_particle', 'i8'), ('_gen', 'i8'), ('_rfac', 'f8')]
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