def test_adjust_weight(self):
backpropagator = Backpropagator()
output = ReceiveAllNeuron()
hidden_1 = ReceiveAllNeuron()
hidden_2 = ReceiveAllNeuron()
hidden_1.connect_to(output)
hidden_1.out_connections_list[0].weight = -0.75
hidden_2.connect_to(output)
hidden_2.out_connections_list[0].weight = -0.25
hidden_1.receive_signal(0.434719)
hidden_2.receive_signal(0.434719)
output.error = 0.09754925
hidden_1.error = -0.01745285
hidden_2.error = -0.00581762
connection_1 = hidden_1.out_connections_list[0]
backpropagator.adjust_weight(connection_1, 1.1)
# -0.75 + (1.1 * 0.09754925 * -0.45525)
self.assertAlmostEqual(connection_1.weight, -0.68486637)
connection_2 = hidden_2.out_connections_list[0]
backpropagator.adjust_weight(connection_2, 1.1)
# -0.25 + (1.1 * 0.09754925 * -0.15175)
self.assertAlmostEqual(connection_2.weight, -0.18486637)
def test_hiddenError(self):
backpropagator = Backpropagator()
output = ReceiveAllNeuron()
hidden_1 = ReceiveAllNeuron()
hidden_2 = ReceiveAllNeuron()
hidden_1.connect_to(output)
hidden_1.out_connections_list[0].weight = -0.75
hidden_2.connect_to(output)
hidden_2.out_connections_list[0].weight = -0.25
# sigmoid(0.434719) == 0.6070000
hidden_1.receive_signal(0.434719)
hidden_2.receive_signal(0.434719)
# sigmoid(0.434719) * -0.75 + sigmoid(0.434719) * -0.25 == -0.607
# sigmoid(-0.607) == 0.352744
# 0.78 - 0.352744 == 0.3527438
output.error = backpropagator.output_error(output, 0.78)
self.assertAlmostEqual(output.error, 0.09754925)
hidden_1.error = backpropagator.hidden_error(hidden_1)
hidden_2.error = backpropagator.hidden_error(hidden_2)
# 0.6070000 * (1 - 0.6070000)*(-0.75 * 0.09754925)
self.assertAlmostEqual(hidden_1.error, -0.01745285)
# 0.6070000 * (1 - 0.6070000)*(-0.25 * 0.09754925)
self.assertAlmostEqual(hidden_2.error, -0.00581762)
def test_connection(self):
sender = ReceiveAllNeuron(self.simple_activation())
receiver = ReceiveAllNeuron(self.simple_activation())
connection = sender.connect_to(receiver)
self.assertEqual(connection.sender, sender)
self.assertEqual(connection.receiver, receiver)
self.assertEqual(connection.weight, 1.0)
self.assertEqual(connection.signal_sent, 0.0)
self.assertEqual(connection.signal_received, 0.0)
connection.weight = 0.5
sender.receive_signal(7.4)
self.assertEqual(connection.weight, 0.5)
self.assertEqual(connection.signal_sent, 3.7)
self.assertEqual(connection.signal_received, 7.4)
def test_wait_for_all_signals(self):
sender_1 = ReceiveAllNeuron(self.simple_activation())
sender_2 = ReceiveAllNeuron(self.simple_activation())
receiver = ReceiveAllNeuron(self.simple_activation())
sender_1.connect_to(receiver)
sender_2.connect_to(receiver)
sender_1.receive_signal(2.0)
self.assertEqual(receiver.output, 0.0)
self.assertFalse(receiver.allSignalsReceived())
sender_2.receive_signal(3.0)
self.assertEqual(receiver.output, 5.0)
self.assertTrue(receiver.allSignalsReceived())
sender_1.reset()
sender_2.reset()
receiver.reset()
self.assertEqual(sender_1.output, 0.0)
self.assertEqual(sender_2.output, 0.0)
self.assertEqual(receiver.output, 0.0)
self.assertFalse(receiver.allSignalsReceived())
def test_sigmoid_activation(self):
neuron = ReceiveAllNeuron()
neuron.receive_signal(-0.607)
self.assertAlmostEqual(neuron.output, 0.3527438)
def test_outputError(self):
backpropagator = Backpropagator()
neuron = ReceiveAllNeuron()
neuron.receive_signal(-0.607)
error = backpropagator.output_error(neuron, 0.78)
self.assertAlmostEqual(error, 0.09754925)