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]