code: def create_from_sedfile(cls, fitsfile, norm_type='eflux'):
          
          tab_s = Table.read(fitsfile, hdu=1)
          tab_s = convert_sed_cols(tab_s)
  
          if norm_type in ['flux', 'eflux', 'dnde']:
              ref_colname = 'ref_%s' % norm_type
              norm_vals = np.array(tab_s['norm_scan'] *
                                   tab_s[ref_colname][:, np.newaxis])
          elif norm_type == "norm":
              norm_vals = np.array(tab_s['norm_scan'])
          else:
              raise ValueError('Unrecognized normalization type: %s' % norm_type)
  
          nll_vals = -np.array(tab_s['dloglike_scan'])
          ref_spec = ReferenceSpec.create_from_table(tab_s)
          spec_data = SpecData(ref_spec, tab_s['norm'], tab_s['norm_err'])
          return cls(norm_vals, nll_vals, spec_data, norm_type)
docs: Create a CastroData object from an SED fits file
  
          Parameters
          ----------
          fitsfile  : str 
              Name of the fits file
  
          norm_type : str
              Type of normalization to use, options are:
  
              * norm : Normalization w.r.t. to test source
              * flux : Flux of the test source ( ph cm^-2 s^-1 )
              * eflux: Energy Flux of the test source ( MeV cm^-2 s^-1 )
              * npred: Number of predicted photons (Not implemented)
              * dnde : Differential flux of the test source ( ph cm^-2 s^-1
                MeV^-1 )
  
          Returns
          -------
          castro : `~fermipy.castro.CastroData`