code: def parameters_changed(self):
          
          # Get the model matrices from the kernel
          (F,L,Qc,H,Pinf,dF,dQc,dPinf) = self.kern.sde()
  
          # Use the Kalman filter to evaluate the likelihood
          self._log_marginal_likelihood = self.kf_likelihood(F,L,Qc,H,self.sigma2,Pinf,self.X.T,self.Y.T)
          gradients  = self.compute_gradients()
          self.sigma2.gradient_full[:] = gradients[-1]
          self.kern.gradient_full[:] = gradients[:-1]
docs: Parameters have now changed