How to use the aicsimageio.transforms.reshape_data function in aicsimageio

>>> img = AICSImage("s_1_t_1_c_10_z_20.ome.tiff")
        ... every_other = img.get_image_dask_data("CZYX", C=slice(0, -1, 2))

        Notes
        -----
        * If a requested dimension is not present in the data the dimension is
          added with a depth of 1.

        See `aicsimageio.transforms.reshape_data` for more details.
        """
        # If no out orientation, simply return current data as dask array
        if out_orientation is None:
            return self.dask_data

        # Transform and return
        return transforms.reshape_data(
            data=self.dask_data,
            given_dims=self.dims,
            return_dims=out_orientation,
            **kwargs,
        )

>>> img = AICSImage("s_1_t_1_c_10_z_20.ome.tiff")
        ... every_other = img.get_image_dask_data("CZYX", C=slice(0, -1, 2))

        Notes
        -----
        * If a requested dimension is not present in the data the dimension is
          added with a depth of 1.

        See `aicsimageio.transforms.reshape_data` for more details.
        """
        # If no out orientation, simply return current data as dask array
        if out_orientation is None:
            return self.dask_data

        # Transform and return
        return transforms.reshape_data(
            data=self.dask_data,
            given_dims=self.dims,
            return_dims=out_orientation,
            **kwargs,
        )

>>> img = Reader("s_1_t_1_c_10_z_20.ome.tiff")
        ... every_other = img.get_image_dask_data("CZYX", C=slice(0, -1, 2))

        Notes
        -----
        * If a requested dimension is not present in the data the dimension is
          added with a depth of 1.

        See `aicsimageio.transforms.reshape_data` for more details.
        """
        # If no out orientation, simply return current data as dask array
        if out_orientation is None:
            return self.dask_data

        # Transform and return
        return transforms.reshape_data(
            data=self.dask_data,
            given_dims=self.dims,
            return_dims=out_orientation,
            **kwargs,
        )

def dask_data(self) -> da.core.Array:
        """
        Returns a dask array with dimension ordering "STCZYX".
        """
        # Construct dask array if never before constructed
        if self._dask_data is None:
            reader_data = self.reader.dask_data

            # Read and reshape and handle delayed known dims reshape
            self._dask_data = transforms.reshape_data(
                data=reader_data,
                given_dims=self._known_dims or self.reader.dims,
                return_dims=self.dims,
            )

        return self._dask_data

def dask_data(self) -> da.core.Array:
        """
        Returns a dask array with dimension ordering "STCZYX".
        """
        # Construct dask array if never before constructed
        if self._dask_data is None:
            reader_data = self.reader.dask_data

            # Read and reshape and handle delayed known dims reshape
            self._dask_data = transforms.reshape_data(
                data=reader_data,
                given_dims=self._known_dims or self.reader.dims,
                return_dims=self.dims,
            )

        return self._dask_data

def data(self) -> np.ndarray:
        """
        Return the entire image as a numpy array with dimension ordering "STCZYX".
        """
        if self._data is None:
            self._data = transforms.reshape_data(
                data=self.reader.data,
                given_dims=self._known_dims or self.reader.dims,
                return_dims=self.dims,
            )

        return self._data