def test_label_encoder_empty_array(values):
le = LabelEncoder()
le.fit(values)
# test empty transform
transformed = le.transform([])
assert_array_equal(np.array([]), transformed)
# test empty inverse transform
inverse_transformed = le.inverse_transform([])
assert_array_equal(np.array([]), inverse_transformed)
def test_label_encoder_negative_ints():
le = LabelEncoder()
le.fit([1, 1, 4, 5, -1, 0])
assert_array_equal(le.classes_, [-1, 0, 1, 4, 5])
assert_array_equal(le.transform([0, 1, 4, 4, 5, -1, -1]),
[1, 2, 3, 3, 4, 0, 0])
assert_array_equal(le.inverse_transform([1, 2, 3, 3, 4, 0, 0]),
[0, 1, 4, 4, 5, -1, -1])
with pytest.raises(ValueError):
le.transform([0, 6])
def test_label_encoder(values, classes, unknown):
# Test LabelEncoder's transform, fit_transform and
# inverse_transform methods
le = LabelEncoder()
le.fit(values)
assert_array_equal(le.classes_, classes)
assert_array_equal(le.transform(values), [1, 0, 2, 0, 2])
assert_array_equal(le.inverse_transform([1, 0, 2, 0, 2]), values)
le = LabelEncoder()
ret = le.fit_transform(values)
assert_array_equal(ret, [1, 0, 2, 0, 2])
with pytest.raises(ValueError, match="unseen labels"):
le.transform(unknown)
def test_label_encoder_errors():
# Check that invalid arguments yield ValueError
le = LabelEncoder()
with pytest.raises(ValueError):
le.transform([])
with pytest.raises(ValueError):
le.inverse_transform([])
# Fail on unseen labels
le = LabelEncoder()
le.fit([1, 2, 3, -1, 1])
msg = "contains previously unseen labels"
with pytest.raises(ValueError, match=msg):
le.inverse_transform([-2])
with pytest.raises(ValueError, match=msg):
le.inverse_transform([-2, -3, -4])
# Fail on inverse_transform("")
msg = "bad input shape ()"
with pytest.raises(ValueError, match=msg):
le.inverse_transform("")
def test_label_encoder_str_bad_shape(dtype):
le = LabelEncoder()
le.fit(np.array(["apple", "orange"], dtype=dtype))
msg = "bad input shape"
with pytest.raises(ValueError, match=msg):
le.transform("apple")