def test_factorize_result_classes():
data = [1, 2, 3]
labels, cats = cudf.factorize(cudf.Series(data))
assert isinstance(labels, cp.ndarray)
assert isinstance(cats, cudf.BaseIndex)
labels, cats = cudf.factorize(cudf.Index(data))
assert isinstance(labels, cp.ndarray)
assert isinstance(cats, cudf.BaseIndex)
labels, cats = cudf.factorize(cp.array(data))
assert isinstance(labels, cp.ndarray)
assert isinstance(cats, cp.ndarray)
def test_cudf_factorize_index():
data = [1, 2, 3, 4, 5]
pi = pd.Index(data)
gi = cudf.Index(data)
expect = pd.factorize(pi)
got = cudf.factorize(gi)
assert len(expect) == len(got)
np.testing.assert_array_equal(expect[0], got[0].get())
np.testing.assert_array_equal(expect[1], got[1].values.get())
def test_cudf_factorize_series():
data = [1, 2, 3, 4, 5]
psr = pd.Series(data)
gsr = cudf.Series(data)
expect = pd.factorize(psr)
got = cudf.factorize(gsr)
assert len(expect) == len(got)
np.testing.assert_array_equal(expect[0], got[0].get())
np.testing.assert_array_equal(expect[1], got[1].values.get())
def test_cudf_factorize_array():
data = [1, 2, 3, 4, 5]
parr = np.array(data)
garr = cp.array(data)
expect = pd.factorize(parr)
got = cudf.factorize(garr)
assert len(expect) == len(got)
np.testing.assert_array_equal(expect[0], got[0].get())
np.testing.assert_array_equal(expect[1], got[1].get())