@classmethod
def get_region_rep_profile(cls, gen_fpath, rev_summary, gid_col='gen_gids',
    cf_dset='cf_profile', rep_method='meanoid', err_method='rmse', weight=
    'gid_counts', n_profiles=1):
    """Class method for parallelization of rep profile calc.

        Parameters
        ----------
        gen_fpath : str
            Filepath to reV gen output file to extract "cf_profile" from.
        rev_summary : pd.DataFrame
            Aggregated rev supply curve summary file trimmed to just one
            region to get a rep profile for.
        gid_col : str
            Column label in rev_summary that contains the generation gids
            (data index in gen_fpath).
        cf_dset : str
            Dataset name to pull generation profiles from.
        rep_method : str
            Method identifier for calculation of the representative profile.
        err_method : str
            Method identifier for calculation of error from the representative
            profile.
        weight : str | None
            Column in rev_summary used to apply weighted mean to profiles.
            The supply curve table data in the weight column should have
            weight values corresponding to the gid_col in the same row.
        n_profiles : int
            Number of representative profiles to retrieve.

        Returns
        -------
        rep_profile : np.ndarray
            (time, n_profiles) array for the most representative profile(s)
        i_rep : list
            Column Index in profiles of the representative profile(s).
        gen_gid_reps : list
            Generation gid(s) of the representative profile(s).
        res_gid_reps : list
            Resource gid(s) of the representative profile(s).
        """
    r = cls(gen_fpath, rev_summary, gid_col=gid_col, cf_dset=cf_dset,
        rep_method=rep_method, err_method=err_method, weight=weight,
        n_profiles=n_profiles)
    return r.rep_profiles, r.i_reps, r.rep_gen_gids, r.rep_res_gids
