How to use the rioxarray.exceptions.MissingCRS function in rioxarray

def test_crs_writer__missing():
    test_da = xarray.DataArray(
        numpy.zeros((5, 5)),
        dims=("y", "x"),
        coords={"y": numpy.arange(1, 6), "x": numpy.arange(2, 7)},
    )
    with pytest.raises(MissingCRS):
        test_da.rio.write_crs()
    with pytest.raises(MissingCRS):
        test_da.to_dataset(name="test").rio.write_crs()

def test_crs_writer__missing():
    test_da = xarray.DataArray(
        numpy.zeros((5, 5)),
        dims=("y", "x"),
        coords={"y": numpy.arange(1, 6), "x": numpy.arange(2, 7)},
    )
    with pytest.raises(MissingCRS):
        test_da.rio.write_crs()
    with pytest.raises(MissingCRS):
        test_da.to_dataset(name="test").rio.write_crs()

else:
            data_obj = self._get_obj(inplace=inplace)

        # get original transform
        transform = self._cached_transform()
        # remove old grid maping coordinate if exists
        grid_mapping_name = (
            self.grid_mapping if grid_mapping_name is None else grid_mapping_name
        )
        try:
            del data_obj.coords[grid_mapping_name]
        except KeyError:
            pass

        if data_obj.rio.crs is None:
            raise MissingCRS(
                "CRS not found. Please set the CRS with 'set_crs()' or 'write_crs()'."
            )
        # add grid mapping coordinate
        data_obj.coords[grid_mapping_name] = xarray.Variable((), 0)
        grid_map_attrs = pyproj.CRS.from_user_input(data_obj.rio.crs).to_cf()
        # spatial_ref is for compatibility with GDAL
        crs_wkt = crs_to_wkt(data_obj.rio.crs)
        grid_map_attrs["spatial_ref"] = crs_wkt
        grid_map_attrs["crs_wkt"] = crs_wkt
        if transform is not None:
            grid_map_attrs["GeoTransform"] = " ".join(
                [str(item) for item in transform.to_gdal()]
            )
        data_obj.coords[grid_mapping_name].rio.set_attrs(grid_map_attrs, inplace=True)

        return data_obj.rio.write_grid_mapping(

together with resolution.
        transform: optional
            The destination transform.
        resampling: Resampling method, optional
            See rasterio.warp.reproject for more details.


        Returns
        -------
        :obj:`xarray.DataArray`:
            The reprojected DataArray.
        """
        if resolution is not None and (shape is not None or transform is not None):
            raise RioXarrayError("resolution cannot be used with shape or transform.")
        if self.crs is None:
            raise MissingCRS(
                "CRS not found. Please set the CRS with 'set_crs()' or 'write_crs()'."
                f"{_get_data_var_message(self._obj)}"
            )
        src_affine = self.transform(recalc=True)
        if transform is None:
            dst_affine, dst_width, dst_height = _make_dst_affine(
                self._obj, self.crs, dst_crs, resolution, shape
            )
        else:
            dst_affine = transform
            if shape is not None:
                dst_height, dst_width = shape
            else:
                dst_height, dst_width = self.shape

        extra_dim = self._check_dimensions()

drop: bool, optional
            If True, drop the data outside of the extent of the mask geoemtries
            Otherwise, it will return the same raster with the data masked.
            Default is True.
        invert: boolean, optional
            If False, pixels that do not overlap shapes will be set as nodata.
            Otherwise, pixels that overlap the shapes will be set as nodata.
            False by default.

        Returns
        -------
        :obj:`xarray.DataArray`:
            The clipped object.
        """
        if self.crs is None:
            raise MissingCRS(
                "CRS not found. Please set the CRS with 'set_crs()' or 'write_crs()'."
                f"{_get_data_var_message(self._obj)}"
            )
        crs = CRS.from_wkt(crs_to_wkt(crs)) if crs is not None else self.crs
        if self.crs != crs:
            geometries = [
                rasterio.warp.transform_geom(crs, self.crs, geometry)
                for geometry in geometries
            ]

        clip_mask_arr = geometry_mask(
            geometries=geometries,
            out_shape=(int(self.height), int(self.width)),
            transform=self.transform(recalc=True),
            invert=not invert,
            all_touched=all_touched,