code: def invert_differencing(self, initial_part, differenced_rest, order=None):
          
  
          if order is None: order = self.diff_order
  
          # compute the differenced values of the initial part:
          starting_points = [ self.apply_differencing(initial_part, order=order)[-1] for order in range(self.diff_order)]
          
          actual_predictions = differenced_rest
          import pdb
          pdb.set_trace()
          for s in starting_points[::-1]:
              actual_predictions = np.cumsum(np.hstack([s, actual_predictions]))[1:]
  
          return(actual_predictions)
docs: function to invert the differencing