def test_input_neurons_have_input_signal(self):
genome = GenomeMock([(2, 4, 0, True), (1, 3, 0, True), (2, 3, 0, True),
(1, 4, 0, True)], 2, 2)
nn = NeuralNetwork()
nn.generate_network(genome)
nn.forward([3, 22])
self.assertEqual(nn._input_neurons[1]._input_signals, [3])
self.assertEqual(nn._input_neurons[2]._input_signals, [22])
def test_input_length_exception(self):
genome = GenomeMock([(2, 4, 0, True), (1, 3, 0, True), (2, 3, 0, True),
(1, 4, 0, True)], 2, 2)
nn = NeuralNetwork()
nn.generate_network(genome)
with self.assertRaises(Exception) as e:
nn.forward([1])
self.assertEqual(str(e.exception), "Expected 2 inputs, got 1 instead")
def test_conections(self):
genome = GenomeMock([(2, 4, 0, True), (1, 3, 0, True), (2, 3, 0, True),
(1, 4, 0, True)], 2, 2)
nn = NeuralNetwork()
nn.generate_network(genome)
self.assertEqual(nn._genome.get_connections(), [(1, 3, 0, True),
(1, 4, 0, True),
(2, 3, 0, True),
(2, 4, 0, True)])
def test_connections_creation(self):
genome = GenomeMock([(2, 4, 0, True), (1, 3, -3, True),
(2, 3, 4, True), (1, 4, 22, True)], 2, 2)
nn = NeuralNetwork()
nn.generate_network(genome)
self.assertEqual(nn._connections, {
(2, 4): 0,
(1, 3): -3,
(2, 3): 4,
(1, 4): 22
})
def test_easy_forward_propagation(self):
genome = GenomeMock([(2, 4, 0, True), (1, 3, 0, True), (2, 3, 0, True),
(1, 4, 0, True)], 2, 2)
nn = NeuralNetwork()
nn.generate_network(genome)
y = nn.forward([3, 22])
self.assertEqual(len(y), 2)
self.assertEqual(y, [0.5, 0.5])
genome = GenomeMock([(2, 4, 1, True), (1, 3, 0, True), (2, 3, 0, True),
(1, 4, 0, True)], 2, 2)
nn.generate_network(genome)
y = nn.forward([3, 22])
self.assertEqual(y[0], 0.5)
self.assertAlmostEqual(y[1], 0.9926085)
genome = GenomeMock([(2, 4, 1, True), (1, 3, 0, True), (2, 3, 0, True),
(1, 4, -2, True)], 2, 2)
nn.generate_network(genome)
y = nn.forward([3, 22])
self.assertEqual(y[0], 0.5)
self.assertAlmostEqual(y[1], 0.00739157)
genome = GenomeMock([(2, 4, 1, True), (1, 3, 0, False),
(2, 3, 0, False), (1, 4, -2, True)], 2, 2)
nn.generate_network(genome)
y = nn.forward([3, 22])
self.assertEqual(y[0], 0.5)
self.assertAlmostEqual(y[1], 0.00739157)
def test_hard_forward_propagation(self):
genome = GenomeMock([(1, 5, 3, True), (2, 5, -2, True),
(1, 6, -1, True), (5, 6, -3.4, True),
(3, 6, 4, True), (6, 4, 5, True)], 3, 1)
nn = NeuralNetwork()
nn.generate_network(genome)
y = nn.forward([0.2, 2, -0.02])
self.assertAlmostEqual(y[0], 0.5144, places=4)
genome = GenomeMock([(1, 5, 3, True),
(2, 5, -2, True), (1, 7, -1, True),
(5, 7, -3.4, True), (3, 7, 4, True),
(7, 6, 2, True), (6, 4, 0.3, True)], 3, 1)
nn.generate_network(genome)
y = nn.forward([0.2, 2, -0.02])
self.assertAlmostEqual(y[0], 0.6778, places=4)
def test_node_creation(self):
genome = GenomeMock([(2, 4, 0, True), (1, 3, -3, True),
(2, 3, 4, True), (1, 4, 22, True),
(1, 5, 3, True)], 2, 2)
nn = NeuralNetwork()
nn.generate_network(genome)
self.assertEqual(1 in nn._neurons, True)
self.assertEqual(2 in nn._neurons, True)
self.assertEqual(3 in nn._neurons, True)
self.assertEqual(4 in nn._neurons, True)
self.assertEqual(5 in nn._neurons, True)
self.assertEqual(1 in nn._input_neurons, True)
self.assertEqual(2 in nn._input_neurons, True)
self.assertEqual(3 in nn._input_neurons, False)
self.assertEqual(4 in nn._input_neurons, False)
self.assertEqual(5 in nn._input_neurons, False)
self.assertEqual(1 in nn._output_neurons, False)
self.assertEqual(2 in nn._output_neurons, False)
self.assertEqual(3 in nn._output_neurons, True)
self.assertEqual(4 in nn._output_neurons, True)
self.assertEqual(5 in nn._output_neurons, False)