Method test_combine_first

xarray/tests/test_units.py:4497–4538

(self, variant, unit, error, dtype)

        ),
    )
    def test_combine_first(self, variant, unit, error, dtype):
        variants = {
            "data": (unit_registry.m, unit, 1, 1),
            "dims": (1, 1, unit_registry.m, unit),
        }
        data_unit, other_data_unit, dims_unit, other_dims_unit = variants[variant]

        array1 = (
            create_nan_array([1.4, np.nan, 2.3, np.nan, np.nan, 9.1], dtype) * data_unit
        )
        array2 = (
            create_nan_array([4.3, 9.8, 7.5, np.nan, 8.2, np.nan], dtype) * data_unit
        )
        x = np.arange(len(array1)) * dims_unit
        ds = xr.Dataset(
            data_vars={"a": ("x", array1), "b": ("x", array2)},
            coords={"x": x},
        )
        units = extract_units(ds)

        other_array1 = np.ones_like(array1) * other_data_unit
        other_array2 = np.full_like(array2, fill_value=-1) * other_data_unit
        other_x = (np.arange(array1.shape[0]) + 5) * other_dims_unit
        other = xr.Dataset(
            data_vars={"a": ("x", other_array1), "b": ("x", other_array2)},
            coords={"x": other_x},
        )

        if error is not None:
            with pytest.raises(error):
                ds.combine_first(other)

            return

        expected = attach_units(
            strip_units(ds).combine_first(strip_units(convert_units(other, units))),
            units,
        )
        actual = ds.combine_first(other)

        assert_units_equal(expected, actual)
        assert_equal(expected, actual)

    @pytest.mark.parametrize(
        "unit",