code: def _init_classes(self, y):
          
          self.classes_ = unique_labels(utils.concatenate_not_none(y))
          new_y = [None] * len(y)
          for s in range(len(y)):
              new_y[s] = np.digitize(y[s], self.classes_) - 1
          return new_y
docs: Map all possible classes to the range [0,..,C-1]
  
          Parameters
          ----------
  
          y : list of arrays of int, each element has shape=[samples_i,]
              Labels of the samples for each subject
  
  
          Returns
          -------
          new_y : list of arrays of int, each element has shape=[samples_i,]
              Mapped labels of the samples for each subject
  
          Note
          ----
              The mapping of the classes is saved in the attribute classes_.