code: def ranker(self, X, meta):
          
          # total score is just a sum of each row
          total_score = X.sum(axis=1).transpose()
          total_score = np.squeeze(np.asarray(total_score))  # matrix to array
          ranks = total_score.argsort()
          ranks = ranks[::-1]
          # sort the list of dicts according to ranks
          sorted_meta = [meta[r] for r in ranks]
          sorted_X = X[ranks]
          return (sorted_X, sorted_meta)
docs: Sort the place features list by the score of its relevance.