How to use the pyxrf.model.fit_spectrum.save_fitdata_to_hdf function in pyxrf

data_all_sum,
            param_sum,
            incident_energy=incident_energy,
            method=method,
            pixel_bin=pixel_bin,
            raise_bg=raise_bg,
            comp_elastic_combine=comp_elastic_combine,
            linear_bg=linear_bg,
            use_snip=use_snip,
            bin_energy=bin_energy,
            dask_client=dask_client)

        # output to .h5 file
        inner_path = 'xrfmap/detsum'
        # fit_name = prefix_fname+'_fit'
        save_fitdata_to_hdf(fpath, result_map_sum, datapath=inner_path)

        def get_scaler_set(img_dict):
            sc_set_names = [_ for _ in img_dict if _.endswith("_scaler")]
            if sc_set_names:
                return img_dict[sc_set_names[0]]
            else:
                return {}

        def get_positions_set(img_dict):
            if "positions" in img_dict:
                return img_dict["positions"]
            else:
                return {}

        scaler_dict = get_scaler_set(img_dict)
        scaler_name_list = list(scaler_dict.keys())

result_map_det, calculation_info = single_pixel_fitting_controller(
                data_all_det,
                param_det,
                incident_energy=incident_energy,
                method=method,
                pixel_bin=pixel_bin,
                raise_bg=raise_bg,
                comp_elastic_combine=comp_elastic_combine,
                linear_bg=linear_bg,
                use_snip=use_snip,
                bin_energy=bin_energy,
                dask_client=dask_client)

            # output to .h5 file
            save_fitdata_to_hdf(fpath, result_map_det, datapath=inner_path)

            def get_scaler_set(img_dict):
                sc_set_names = [_ for _ in img_dict if _.endswith("_scaler")]
                if sc_set_names:
                    return img_dict[sc_set_names[0]]
                else:
                    return {}

            def get_positions_set(img_dict):
                if "positions" in img_dict:
                    return img_dict["positions"]
                else:
                    return {}

            scaler_dict = get_scaler_set(img_dict)
            scaler_name_list = list(scaler_dict.keys())