code: def plot_sed(sed, showlnl=False, **kwargs):
          
  
          ax = kwargs.pop('ax', plt.gca())
          cmap = kwargs.get('cmap', 'BuGn')
  
          annotate_name(sed, ax=ax)
          SEDPlotter.plot_flux_points(sed, **kwargs)
  
          if np.any(sed['ts'] > 9.):
  
              if 'model_flux' in sed:
                  SEDPlotter.plot_model(sed['model_flux'],
                                        noband=showlnl, **kwargs)
  
          if showlnl:
              SEDPlotter.plot_lnlscan(sed, **kwargs)
  
          ax.set_yscale('log')
          ax.set_xscale('log')
          ax.set_xlabel('Energy [MeV]')
          ax.set_ylabel('E$^{2}$dN/dE [MeV cm$^{-2}$ s$^{-1}$]')
docs: Render a plot of a spectral energy distribution.
  
          Parameters
          ----------
          showlnl : bool        
              Overlay a map of the delta-loglikelihood values vs. flux
              in each energy bin.
  
          cmap : str        
              Colormap that will be used for the delta-loglikelihood
              map.
  
          llhcut : float
              Minimum delta-loglikelihood value.
  
          ul_ts_threshold : float        
              TS threshold that determines whether the MLE or UL
              is plotted in each energy bin.