def test_update_neural_network_against_values(self):
# Create and initialize neural net
input = [3, 3, 3, 0.3]
myNeuralNetwork = NeuralNetwork(input)
myNeuralNetwork.init_neural_network()
# overwrite arrays with book values
default_input_vector_list = [0.9, 0.1, 0.8]
default_input_vector = numpy.array(default_input_vector_list).reshape(len(default_input_vector_list), 1)
myNeuralNetwork.set_array(myNeuralNetwork.get_input_vector(), default_input_vector)
default_weight_input_hidden = numpy.array([[0.9, 0.3, 0.4], [0.2, 0.8, 0.2], [0.1, 0.5, 0.6]])
myNeuralNetwork.set_array(myNeuralNetwork.get_weight_input_hidden(), default_weight_input_hidden)
default_weight_hidden_output = numpy.array([[0.3, 0.7, 0.5], [0.6, 0.5, 0.2], [0.8, 0.1, 0.9]])
myNeuralNetwork.set_array(myNeuralNetwork.get_weight_hidden_output(), default_weight_hidden_output)
# Call function under test
output = myNeuralNetwork.query(myNeuralNetwork.input_vector)
# Validate results
expected_output = [0.726,0.708,0.778]
expected_output_array = numpy.array(expected_output).reshape(len(expected_output), 1)
for n in range(0,expected_output_array.shape[0]):
for m in range(0,expected_output_array.shape[1]):
self.assertTrue(expected_output_array[n,m] == output[n,m],msg="output value is not equal as expected!".format(expected_output,output))
def create_neural_net():
input = [3, 3, 3, 0.3]
myNeuralNetwork = NeuralNetwork(input)
myNeuralNetwork.init_neural_network()
default_input_vector_list = [0.9,0.1,0.8]
default_input_vector = numpy.array(default_input_vector_list).reshape(len(default_input_vector_list), 1)
myNeuralNetwork.set_array(myNeuralNetwork.get_input_vector(),default_input_vector)
default_weight_input_hidden = numpy.array([[0.9,0.3,0.4],[0.2,0.8,0.2],[0.1,0.5,0.6]])
myNeuralNetwork.set_array(myNeuralNetwork.get_weight_input_hidden(),default_weight_input_hidden)
default_weight_hidden_output = numpy.array([[0.3, 0.7, 0.5], [0.6, 0.5, 0.2], [0.8, 0.1, 0.9]])
myNeuralNetwork.set_array(myNeuralNetwork.get_weight_hidden_output(), default_weight_hidden_output)
return myNeuralNetwork