def test_scale_paretto(random_df): data = random_df scaled = utils.scale(data, "pareto") assert np.isclose(scaled.mean(), 0).all() # in pareto scaling the std of x is equal to the variance of x scaled assert np.isclose(scaled.var(), data.std()).all()
def test_scale_autoscaling(random_df): data = random_df scaled = utils.scale(data, "autoscaling") assert np.isclose(scaled.mean(), 0).all() assert np.isclose(scaled.var(), 1).all()
def test_scale_rescaling(): data = np.random.normal(size=(200, 50), loc=10) data = pd.DataFrame(data) scaled = utils.scale(data, "rescaling") assert np.isclose(scaled.min(), 0).all() assert np.isclose(scaled.max(), 1).all()
def test_scale_invalid_mode(random_df): data = random_df with pytest.raises(ValueError): utils.scale(data, "invalid_mode")