code: def updateModel(self, X_all, Y_all, X_new, Y_new):
          
          if self.model is None:
              self._create_model(X_all, Y_all)
          else:
              self.model.set_XY(X_all, Y_all)
  
          # WARNING: Even if self.max_iters=0, the hyperparameters are bit modified...
          if self.max_iters > 0:
              # --- update the model maximizing the marginal likelihood.
              if self.optimize_restarts==1:
                  self.model.optimize(optimizer=self.optimizer, max_iters = self.max_iters, messages=False, ipython_notebook=False)
              else:
                  self.model.optimize_restarts(num_restarts=self.optimize_restarts, optimizer=self.optimizer, max_iters = self.max_iters, verbose=self.verbose)
docs: Updates the model with new observations.