code: def profile_loglike(self, x):
          
          if self._prof_interp is None:
              # This calculates values and caches the spline
              return self._profile_loglike(x)[1]
  
          x = np.array(x, ndmin=1)
          return self._prof_interp(x)
docs: Profile log-likelihood.
  
          Returns ``L_prof(x,y=y_min|z')``  : where y_min is the 
                                              value of y that minimizes 
                                              L for a given x.
  
          This will used the cached '~fermipy.castro.Interpolator' object 
          if possible, and construct it if needed.