code: def create_from_tables(cls, norm_type='eflux',
                             tab_s="SCANDATA",
                             tab_e="EBOUNDS"):
          
          if norm_type in ['flux', 'eflux', 'dnde']:
              norm_vals = np.array(tab_s['norm_scan'] *
                                   tab_e['ref_%s' % norm_type][:, np.newaxis])
          elif norm_type == "norm":
              norm_vals = np.array(tab_s['norm_scan'])
          else:
              raise Exception('Unrecognized normalization type: %s' % norm_type)
  
          nll_vals = -np.array(tab_s['dloglike_scan'])
  
          rs = ReferenceSpec.create_from_table(tab_e)
          return cls(norm_vals, nll_vals, rs, norm_type)
docs: Create a CastroData object from two tables
  
          Parameters
          ----------
          norm_type : str
              Type of normalization to use.  Valid 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 )
  
          tab_s : str
             table scan data
  
          tab_e : str
             table energy binning and normalization data
  
          Returns
          -------
          castro : `~fermipy.castro.CastroData`