@classmethod
def summary(cls, excl_fpath, gen_fpath, tm_dset, excl_dict=None,
    area_filter_kernel='queen', min_area=None, check_excl_layers=False,
    resolution=64, gids=None, res_class_dset=None, res_class_bins=None,
    cf_dset='cf_mean-means', lcoe_dset='lcoe_fcr-means', data_layers=None,
    power_density=None, friction_fpath=None, friction_dset=None, args=None,
    excl_area=0.0081, max_workers=None, offshore_capacity=600,
    offshore_gid_counts=494, offshore_pixel_area=4):
    """Get the supply curve points aggregation summary.

        Parameters
        ----------
        excl_fpath : str
            Filepath to exclusions h5 with techmap dataset.
        gen_fpath : str
            Filepath to .h5 reV generation output results.
        tm_dset : str
            Dataset name in the techmap file containing the
            exclusions-to-resource mapping data.
        excl_dict : dict | None
            Dictionary of exclusion LayerMask arugments {layer: {kwarg: value}}
        area_filter_kernel : str
            Contiguous area filter method to use on final exclusions mask
        min_area : float | None
            Minimum required contiguous area filter in sq-km
        check_excl_layers : bool
            Run a pre-flight check on each exclusion layer to ensure they
            contain un-excluded values
        resolution : int | None
            SC resolution, must be input in combination with gid. Prefered
            option is to use the row/col slices to define the SC point instead.
        gids : list | None
            List of gids to get summary for (can use to subset if running in
            parallel), or None for all gids in the SC extent.
        res_class_dset : str | None
            Dataset in the generation file dictating resource classes.
            None if no resource classes.
        res_class_bins : list | None
            List of floats or ints (bin edges) to convert to list of two-entry
            bin boundaries or list of two-entry bind boundaries in final format
        cf_dset : str
            Dataset name from f_gen containing capacity factor mean values.
        lcoe_dset : str
            Dataset name from f_gen containing LCOE mean values.
        data_layers : None | dict
            Aggregation data layers. Must be a dictionary keyed by data label
            name. Each value must be another dictionary with "dset", "method",
            and "fpath".
        power_density : float | str | None
            Power density in MW/km2 or filepath to variable power
            density file. None will attempt to infer a constant
            power density from the generation meta data technology
        friction_fpath : str | None
            Filepath to friction surface data (cost based exclusions).
            Must be paired with friction_dset.
        friction_dset : str | None
            Dataset name in friction_fpath for the friction surface data.
            Must be paired with friction_fpath. Must be same shape as
            exclusions.
        args : tuple | list | None
            List of summary arguments to include. None defaults to all
            available args defined in the class attr.
        excl_area : float
            Area of an exclusion cell (square km).
        max_workers : int | None
            Number of cores to run summary on. None is all
            available cpus.
        offshore_capacity : int | float
            Offshore resource pixel generation capacity in MW.
        offshore_gid_counts : int
            Approximate number of exclusion pixels that would fall into an
            offshore pixel area.
        offshore_pixel_area : int | float
            Approximate area of offshore resource pixels in km2.

        Returns
        -------
        summary : DataFrame
            Summary of the SC points.
        """
    agg = cls(excl_fpath, gen_fpath, tm_dset, excl_dict, res_class_dset=
        res_class_dset, res_class_bins=res_class_bins, cf_dset=cf_dset,
        lcoe_dset=lcoe_dset, data_layers=data_layers, resolution=resolution,
        power_density=power_density, gids=gids, friction_fpath=
        friction_fpath, friction_dset=friction_dset, area_filter_kernel=
        area_filter_kernel, min_area=min_area, check_excl_layers=
        check_excl_layers)
    summary = agg.summarize(args=args, excl_area=excl_area, max_workers=
        max_workers, offshore_capacity=offshore_capacity,
        offshore_gid_counts=offshore_gid_counts, offshore_pixel_area=
        offshore_pixel_area)
    return summary
