def test_set_error_output_layer(self):
neuron = Neuron(0, 0, [0.05, 0.05], [1, 1])
neuron.output = 0.518979
neuron.is_output_layer = True
neuron.set_output_layer_error(0)
self.assertEquals(-0.12955, round_to(neuron.delta_val, 5))
def _create_neurons(self, neuron_count_vec, weight_counts):
neuron_count_vec_length = len(neuron_count_vec)
for i in range(0, neuron_count_vec_length):
self.neurons.append([])
for j in range(0, neuron_count_vec[i]):
weights = Network.get_initial_neuron_weights(weight_counts[i]+1)
inputs = [0] * (len(weights)-1)
inputs.append(1)
neuron = Neuron(i, j, weights, inputs)
if i == neuron_count_vec_length-1:
neuron.is_output_layer = True
self.neurons[i].append(neuron)
