class HopfieldNetworkCreationTests(unittest.TestCase):
def setUp(self):
self.net = HopfieldNetwork(10)
def test_change_network_weights(self):
new_weights = np.ones((10, 10))
self.net.set_weights(new_weights)
self.assertTrue(np.array_equal(self.net.get_weights(), new_weights), "The network weights have not been updated")
def test_fail_to_change_weights_when_shape_not_same_as_input_vector(self):
new_weights = np.ones((5, 5))
self.assertRaises(InvalidWeightsException, self.net.set_weights, new_weights)
def test_network_creation(self):
self.assertEqual(self.net.get_weights().shape, (10, 10), "The networks weight array has wrong shape")
class HopfieldNetworkCreationTests(unittest.TestCase):
def setUp(self):
self.net = HopfieldNetwork(10)
def test_change_network_weights(self):
new_weights = np.ones((10, 10))
self.net.set_weights(new_weights)
self.assertTrue(np.array_equal(self.net.get_weights(), new_weights),
"The network weights have not been updated")
def test_fail_to_change_weights_when_shape_not_same_as_input_vector(self):
new_weights = np.ones((5, 5))
self.assertRaises(InvalidWeightsException, self.net.set_weights,
new_weights)
def test_network_creation(self):
self.assertEqual(self.net.get_weights().shape, (10, 10),
"The networks weight array has wrong shape")
class HebbianTrainingTest(unittest.TestCase):
def setUp(self):
self.input_patterns = np.array([[1, -1, 1],
[-1, 1, -1]])
self.net = HopfieldNetwork(3)
def test_calculate_weight(self):
w = calculate_weight(0, 1, self.input_patterns)
expected_weight = -1.0
self.assertAlmostEqual(w, expected_weight)
w = calculate_weight(1, 2, self.input_patterns)
expected_weight = -1.0
self.assertAlmostEqual(w, expected_weight)
w = calculate_weight(0, 2, self.input_patterns)
expected_weight = 1.0
self.assertAlmostEqual(w, expected_weight)
def test_calculate_neuron_weights(self):
w = calculate_neuron_weights(0, self.input_patterns)
expected_weights = np.array([0.0, -1.0, 1.0])
self.assertTrue(np.array_equal(w, expected_weights))
def test_hebbian_training(self):
hebbian_training(self.net, self.input_patterns)
expected_weights = np.array([[0, -1, 1],
[-1, 0, -1],
[1, -1, 0]])
weights = self.net.get_weights()
self.assertTrue(np.array_equal(weights, expected_weights), "Test weights not equal")
class HebbianTrainingTest(unittest.TestCase):
def setUp(self):
self.input_patterns = np.array([[1, -1, 1], [-1, 1, -1]])
self.net = HopfieldNetwork(3)
def test_calculate_weight(self):
w = calculate_weight(0, 1, self.input_patterns)
expected_weight = -1.0
self.assertAlmostEqual(w, expected_weight)
w = calculate_weight(1, 2, self.input_patterns)
expected_weight = -1.0
self.assertAlmostEqual(w, expected_weight)
w = calculate_weight(0, 2, self.input_patterns)
expected_weight = 1.0
self.assertAlmostEqual(w, expected_weight)
def test_calculate_neuron_weights(self):
w = calculate_neuron_weights(0, self.input_patterns)
expected_weights = np.array([0.0, -1.0, 1.0])
self.assertTrue(np.array_equal(w, expected_weights))
def test_hebbian_training(self):
hebbian_training(self.net, self.input_patterns)
expected_weights = np.array([[0, -1, 1], [-1, 0, -1], [1, -1, 0]])
weights = self.net.get_weights()
self.assertTrue(np.array_equal(weights, expected_weights),
"Test weights not equal")
