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)
