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

# update incident energy, required for XANES
        if incident_energy is not None:
            param_sum['coherent_sct_energy']['value'] = incident_energy
            print("Using incident beam energy passed as the function parameter.")
        elif mdata.is_metadata_available() and "instrument_mono_incident_energy" in mdata \
                and not ignore_datafile_metadata:
            param_sum['coherent_sct_energy']['value'] = mdata["instrument_mono_incident_energy"]
            print(f"Using incident beam energy from the data file '{file_name}'.")
        else:
            print(f"Using incident beam energy from the parameter file '{param_path}'.")

        # The value of incident energy that is used for processing
        incident_energy_used = param_sum['coherent_sct_energy']['value']
        print(f"Incident beam energy: {incident_energy_used}.")

        result_map_sum, calculation_info = single_pixel_fitting_controller(
            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)

param_det['coherent_sct_energy']['value'] = incident_energy
                print("Using incident beam energy passed as the function parameter.")
            elif mdata.is_metadata_available() and "instrument_mono_incident_energy" in mdata \
                    and not ignore_datafile_metadata:
                param_det['coherent_sct_energy']['value'] = mdata["instrument_mono_incident_energy"]
                print(f"Using incident beam energy from the data file '{file_name}'.")
            else:
                print(f"Using incident beam energy from the parameter file '{param_path}'.")

            # The value of incident energy that is used for processing
            incident_energy_used = param_det['coherent_sct_energy']['value']
            print(f"Incident beam energy: {incident_energy_used}.")

            data_all_det = data_sets[det_channels[i]].raw_data

            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):