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

def test_clip_box__one_dimension_error(modis_clip):
    with modis_clip["open"](modis_clip["input"]) as xdi:
        var_match = ""
        if hasattr(xdi, "name") and xdi.name:
            var_match = " Data variable: __xarray_dataarray_variable__"
        # test exception after raster clipped
        with pytest.raises(
            OneDimensionalRaster,
            match=(
                "At least one of the clipped raster x,y coordinates has "
                f"only one point.{var_match}"
            ),
        ):
            xdi.rio.clip_box(
                minx=-7272735.53951584,  # xdi.x[5].values
                miny=5048834.500182299,  # xdi.y[5].values
                maxx=-7272735.53951584,  # xdi.x[5].values
                maxy=5048834.500182299,  # xdi.y[5].values
            )
        # test exception before raster clipped
        with pytest.raises(OneDimensionalRaster):
            xdi.isel(x=slice(5, 6), y=slice(5, 6)).rio.clip_box(
                minx=-7272735.53951584,  # xdi.x[5].values
                miny=5048371.187465771,  # xdi.y[7].values

# test exception after raster clipped
        with pytest.raises(
            OneDimensionalRaster,
            match=(
                "At least one of the clipped raster x,y coordinates has "
                f"only one point.{var_match}"
            ),
        ):
            xdi.rio.clip_box(
                minx=-7272735.53951584,  # xdi.x[5].values
                miny=5048834.500182299,  # xdi.y[5].values
                maxx=-7272735.53951584,  # xdi.x[5].values
                maxy=5048834.500182299,  # xdi.y[5].values
            )
        # test exception before raster clipped
        with pytest.raises(OneDimensionalRaster):
            xdi.isel(x=slice(5, 6), y=slice(5, 6)).rio.clip_box(
                minx=-7272735.53951584,  # xdi.x[5].values
                miny=5048371.187465771,  # xdi.y[7].values
                maxx=-7272272.226799311,  # xdi.x[7].values
                maxy=5048834.500182299,  # xdi.y[5].values
            )

resolution_y = transform.e
            return resolution_x, resolution_y

        # if the coordinates of the spatial dimensions are missing
        # use the cached transform resolution
        try:
            left, bottom, right, top = self._internal_bounds()
        except DimensionMissingCoordinateError:
            if transform is None:
                raise
            resolution_x = transform.a
            resolution_y = transform.e
            return resolution_x, resolution_y

        if self.width == 1 or self.height == 1:
            raise OneDimensionalRaster(
                "Only 1 dimenional array found. Cannot calculate the resolution."
                f"{_get_data_var_message(self._obj)}"
            )

        resolution_x = (right - left) / (self.width - 1)
        resolution_y = (bottom - top) / (self.height - 1)
        return resolution_x, resolution_y

Maximum bound for x coordinate.
        maxy: float
            Maximum bound for y coordinate.
        auto_expand: bool
            If True, it will expand clip search if only 1D raster found with clip.
        auto_expand_limit: int
            maximum number of times the clip will be retried before raising
            an exception.

        Returns
        -------
        :obj:`xarray.DataArray`:
            The clipped object.
        """
        if self.width == 1 or self.height == 1:
            raise OneDimensionalRaster(
                "At least one of the raster x,y coordinates has only one point."
                f"{_get_data_var_message(self._obj)}"
            )

        # make sure that if the coordinates are
        # in reverse order that it still works
        resolution_x, resolution_y = self.resolution()
        if resolution_y < 0:
            top = maxy
            bottom = miny
        else:
            top = miny
            bottom = maxy
        if resolution_x < 0:
            left = maxx
            right = minx