def normalize_training_inputs(training_inputs):
m_training_inputs_only = np.array(training_inputs)
m_dimensions = m_training_inputs_only.transpose()
m_dimensions_normalized = np.array([
Normalizer.normalize_to_stdev(dimension_set)
for dimension_set in m_dimensions
])
m_training_inputs_normalized = m_dimensions_normalized.transpose()
return m_training_inputs_normalized
def test_normalize_to_stdev_2():
inputs = [9, 2, 5, 4]
results = [round(x, 2) for x in Normalizer.normalize_to_stdev(inputs)]
assert results == [1.57, -1.18, 0.0, -0.39]
def test_normalize_to_stdev_1():
inputs = [900, 200, 500, 400]
results = [round(x, 2) for x in Normalizer.normalize_to_stdev(inputs)]
assert results == [1.57, -1.18, 0.0, -0.39]
