    def __recompose_cascade_to_rainfall_field(self, j, worker_state):
        """
        Recompose the blended cascade into a precipitation field using the blended
        means and standard deviations. If using the spectral domain, apply inverse
        FFT for reconstruction.
        """
        worker_state.final_blended_forecast_recomposed = (
            blending.utils.recompose_cascade(
                combined_cascade=worker_state.final_blended_forecast_cascades,
                combined_mean=worker_state.final_blended_forecast_means,
                combined_sigma=worker_state.final_blended_forecast_stds,
            )
        )
        # The recomposed cascade without the extrapolation (for NaN filling
        # outside the radar domain)
        worker_state.final_blended_forecast_recomposed_mod_only = (
            blending.utils.recompose_cascade(
                combined_cascade=worker_state.final_blended_forecast_cascades_mod_only,
                combined_mean=worker_state.final_blended_forecast_means_mod_only,
                combined_sigma=worker_state.final_blended_forecast_stds_mod_only,
            )
        )
        if self.__config.domain == "spectral":
            # TODO: Check this! (Only tested with domain == 'spatial')
            worker_state.final_blended_forecast_recomposed = self.__params.fft_objs[
                j
            ].irfft2(worker_state.final_blended_forecast_recomposed)
            worker_state.final_blended_forecast_recomposed_mod_only = (
                self.__params.fft_objs[j].irfft2(
                    worker_state.final_blended_forecast_recomposed_mod_only
                )
            )
Recompose the blended cascade into a precipitation field using the blended
means and standard deviations. If using the spectral domain, apply inverse
FFT for reconstruction.
pysteps/blending/steps.py