code: def create_functor(self, specType, initPars=None, scale=1E3):
          
  
          emin = self._refSpec.emin
          emax = self._refSpec.emax
  
          fn = SpectralFunction.create_functor(specType,
                                               self.norm_type,
                                               emin,
                                               emax,
                                               scale=scale)
  
          if initPars is None:
              if specType == 'PowerLaw':
                  initPars = np.array([5e-13, -2.0])
              elif specType == 'LogParabola':
                  initPars = np.array([5e-13, -2.0, 0.0])
              elif specType == 'PLExpCutoff':
                  initPars = np.array([5e-13, -1.0, 1E4])
  
          fn.params = initPars
          return fn
docs: Create a functor object that computes normalizations in a
          sequence of energy bins for a given spectral model.
  
          Parameters
          ----------
          specType : str        
              The type of spectrum to use.  This can be a string
              corresponding to the spectral model class name or a
              `~fermipy.spectrum.SpectralFunction` object.
  
          initPars : `~numpy.ndarray`        
              Arrays of parameter values with which the spectral
              function will be initialized.
  
          scale : float
              The 'pivot energy' or energy scale to use for the spectrum
  
          Returns
          -------
          fn : `~fermipy.spectrum.SEDFunctor`
              A functor object.