Method test_unique_array_api_functions

numpy/lib/tests/test_arraysetops.py:1208–1249

(self)

        assert_array_equal(not_unq, np.array([1, np.nan, np.nan, np.nan]))

    def test_unique_array_api_functions(self):
        arr = np.array(
            [
                np.nan, 1.0, 0.0, 4.0, -np.nan,
                -0.0, 1.0, 3.0, 4.0, np.nan,
                5.0, -0.0, 1.0, -np.nan, 0.0,
            ],
        )

        for res_unique_array_api, res_unique in [
            (
                np.unique_values(arr),
                np.unique(arr, equal_nan=False)
            ),
            (
                np.unique_counts(arr),
                np.unique(arr, return_counts=True, equal_nan=False)
            ),
            (
                np.unique_inverse(arr),
                np.unique(arr, return_inverse=True, equal_nan=False)
            ),
            (
                np.unique_all(arr),
                np.unique(
                    arr,
                    return_index=True,
                    return_inverse=True,
                    return_counts=True,
                    equal_nan=False
                )
            )
        ]:
            assert len(res_unique_array_api) == len(res_unique)
            if not isinstance(res_unique_array_api, tuple):
                res_unique_array_api = (res_unique_array_api,)
            if not isinstance(res_unique, tuple):
                res_unique = (res_unique,)

            for actual, expected in zip(res_unique_array_api, res_unique):
                # Order of output is not guaranteed
                assert_equal(np.sort(actual), np.sort(expected))

    def test_unique_inverse_shape(self):
        # Regression test for https://github.com/numpy/numpy/issues/25552