Trigger computation in constituent dask arrays

        This keeps them as dask arrays but encourages them to keep data in
        memory.  This is particularly useful when on a distributed machine.
        When on a single machine consider using ``.compute()`` instead.

        Parameters
        ----------
        **kwargs : dict
            Additional keyword arguments passed on to ``dask.persist``.

        See Also
        --------
        dask.persist

def persist(self, **kwargs):
        """ Trigger computation in constituent dask arrays

        This keeps them as dask arrays but encourages them to keep data in
        memory.  This is particularly useful when on a distributed machine.
        When on a single machine consider using ``.compute()`` instead.

        Parameters
        ----------
        **kwargs : dict
            Additional keyword arguments passed on to ``dask.persist``.

        See Also
        --------
        dask.persist
        """
        ds = self._to_temp_dataset().persist(**kwargs)
        return self._from_temp_dataset(ds)