def test_same():
y = [1, 2, 3]
trans = BoxCoxEndogTransformer(lmbda=0)
log_trans = LogEndogTransformer()
y_t, _ = trans.fit_transform(y)
log_y_t, _ = log_trans.fit_transform(y)
assert_array_almost_equal(log_y_t, y_t)
def test_invertible_when_lam2(self):
y = self.y
trans = BoxCoxEndogTransformer(lmbda=2., lmbda2=2.)
y_t, _ = trans.fit_transform(y)
# When we invert, it will not be the same
y_prime, _ = trans.inverse_transform(y_t)
assert_array_almost_equal(y, y_prime)
def test_no_warning_on_ignore(self):
y = self.y
trans = BoxCoxEndogTransformer(lmbda=2., neg_action="ignore")
y_t, _ = trans.fit_transform(y)
# When we invert, it will not be the same
y_prime, _ = trans.inverse_transform(y_t)
assert not np.allclose(y_prime, y)
def test_expected_warning(self):
y = self.y
trans = BoxCoxEndogTransformer(lmbda=2., neg_action="warn")
with pytest.warns(UserWarning):
y_t, _ = trans.fit_transform(y)
# When we invert, it will not be the same
y_prime, _ = trans.inverse_transform(y_t)
assert not np.allclose(y_prime, y)
def test_invertible(X):
trans = BoxCoxEndogTransformer()
y_t, e_t = trans.fit_transform(loggamma, X=X)
y_prime, e_prime = trans.inverse_transform(y_t, X=e_t)
assert_array_almost_equal(loggamma, y_prime)
# X should all be the same too
if X is None:
assert X is e_t is e_prime is None
else:
assert_array_almost_equal(X, e_t)
assert_array_almost_equal(X, e_prime)
def test_invertible(exog):
trans = BoxCoxEndogTransformer()
y_t, e_t = trans.fit_transform(loggamma, exogenous=exog)
y_prime, e_prime = trans.inverse_transform(y_t, exogenous=e_t)
assert_array_almost_equal(loggamma, y_prime)
# exog should all be the same too
if exog is None:
assert exog is e_t is e_prime is None
else:
assert_array_almost_equal(exog, e_t)
assert_array_almost_equal(exog, e_prime)
def test_expected_error(self):
y = self.y
trans = BoxCoxEndogTransformer(lmbda=2.)
with pytest.raises(ValueError):
trans.fit_transform(y)
def test_value_error_on_neg_lambda():
trans = BoxCoxEndogTransformer(lmbda2=-4.)
with pytest.raises(ValueError) as ve:
trans.fit_transform([1, 2, 3])
assert 'lmbda2 must be a non-negative' in pytest_error_str(ve)
def test_invertible_when_lambda_is_0():
y = [1, 2, 3]
trans = BoxCoxEndogTransformer(lmbda=0.)
y_t, _ = trans.fit_transform(y)
y_prime, _ = trans.inverse_transform(y_t)
assert_array_almost_equal(y, y_prime)