code: def create_single_method(self, estimator_index, estimator):
          
          feature_indices = []
          for i in estimator.tree_.feature:
              n_features = estimator.n_features_
              if self.n_features > 1 or (self.n_features == 1 and i >= 0):
                  feature_indices.append([str(j) for j in range(n_features)][i])
  
          tree_branches = self.create_branches(
              estimator.tree_.children_left, estimator.tree_.children_right,
              estimator.tree_.threshold, estimator.tree_.value,
              feature_indices, 0, 1, init=True)
  
          temp_tree = self.temp('embedded.tree')
          return temp_tree.format(method_name=self.method_name,
                                  method_index=str(estimator_index),
                                  methods=tree_branches,
                                  n_classes=self.n_classes)
docs: Port a method for a single tree.
  
          Parameters
          ----------
          :param estimator_index : int
              The estimator index.
          :param estimator : AdaBoostClassifier
              The estimator itself.
  
          Returns
          -------
          :return : string
              The created method as string.