def test_backtransform(self): transf_mean = Transform(d=0, mean=1, box_cox=0.5) data_sqrt = np.array([0, 1, 4, 2, 9]) data_sqrt_transf = [-3, -1, 1, (2 ** 0.5 - 1) * 2 - 1, 3] empty = np.array([]) np.testing.assert_almost_equal(transf_mean.backtransform(data_sqrt_transf), data_sqrt) np.testing.assert_almost_equal(transf_mean.backtransform(empty), empty)
def test_transform(self): transf_mean = Transform(d=0, mean=1, box_cox=0.5) data_sqrt = [0, 1, 4, 2, 9] empty = [] np.testing.assert_almost_equal( transf_mean.transform(data_sqrt).tolist(), [-3, -1, 1, (2 ** 0.5 - 1) * 2 - 1, 3] ) np.testing.assert_almost_equal(transf_mean.transform(empty).tolist(), [])
def test_box_cox_backtransform(self): transf_ln = Transform(d=0, mean=0, box_cox=0) transf_sqrt = Transform(d=0, mean=0, box_cox=0.5) transf_mean = Transform(d=0, mean=1, box_cox=0.5) data_ln = [1, 2, 4.2, 0.002] data_ln_transf = np.array([np.log(x) for x in data_ln]) data_sqrt = [0, 1, 4, 2, 9] data_sqrt_transf = np.array([-2, 0, 2, (2 ** 0.5 - 1) * 2, 4]) empty = np.array([]) np.testing.assert_almost_equal(transf_ln._box_cox_backtransform(data_ln_transf).tolist(), data_ln) np.testing.assert_almost_equal(transf_ln._box_cox_backtransform(empty).tolist(), []) np.testing.assert_almost_equal(transf_sqrt._box_cox_backtransform(data_sqrt_transf).tolist(), data_sqrt)