@classmethod
def run(cls, gen_fpath, rev_summary, gid_col='gen_gids', cf_dset=
    'cf_profile', weight='gid_counts', fout=None, scaled_precision=False,
    max_workers=None):
    """Run representative profiles by calculating the weighted aggregate
        (meanoid) profile for each SC point.

        Parameters
        ----------
        gen_fpath : str
            Filepath to reV gen output file to extract "cf_profile" from.
        rev_summary : str | pd.DataFrame
            Aggregated rev supply curve summary file. Str filepath or full df.
        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.
        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.
        fout : str, optional
            filepath to output h5 file, by default None
        scaled_precision : bool, optional
            Flag to scale cf_profiles by 1000 and save as uint16.,
            by default False
        max_workers : int, optional
            Number of parallel workers. 1 will run serial, None will use all
            available., by default None

        Returns
        -------
        profiles : dict
            dict of n_profile-keyed arrays with shape (time, n) for the
            representative profiles for each supply curve point (n).
            For the AggregateRepProfile class, this only has one key: 0.
        meta : pd.DataFrame
            Meta dataframe (reV supply curve summary).
        time_index : pd.DatatimeIndex
            Datetime Index for represntative profiles
        """
    arp = cls(gen_fpath, rev_summary, gid_col=gid_col, cf_dset=cf_dset,
        weight=weight)
    arp._run(fout=fout, scaled_precision=scaled_precision, max_workers=
        max_workers)
    return arp._profiles, arp._meta, arp._time_index
