def test_inverse_transform(orig_label, ord_label, expected_reverted,
bad_ord_label):
# prepare LabelEncoder
le = LabelEncoder()
le.fit(orig_label)
assert (le._fitted is True)
# test if inverse_transform is correct
reverted = le.inverse_transform(ord_label)
assert (len(reverted) == len(expected_reverted))
assert (len(reverted) == len(reverted[reverted == expected_reverted]))
# test if correctly raies ValueError
with pytest.raises(ValueError, match='y contains previously unseen label'):
le.inverse_transform(bad_ord_label)
def test_empty_input(empty, ord_label):
# prepare LabelEncoder
le = LabelEncoder()
le.fit(empty)
assert (le._fitted is True)
# test if correctly raies ValueError
with pytest.raises(ValueError, match='y contains previously unseen label'):
le.inverse_transform(ord_label)
# check fit_transform()
le = LabelEncoder()
transformed = le.fit_transform(empty)
assert (le._fitted is True)
assert (len(transformed) == 0)