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_outputError(self):
backpropagator = Backpropagator()
neuron = ReceiveAllNeuron()
neuron.receive_signal(-0.607)
error = backpropagator.output_error(neuron, 0.78)
self.assertAlmostEqual(error, 0.09754925)
