code: def get_split_samples(self, id):
      samples = np.array(self.get_node_samples()[id])
      node_X_data = self.X_train[samples, self.get_node_feature(id)]
      split = self.get_node_split(id)
  
      left = np.nonzero(node_X_data <= split)[0]
      right = np.nonzero(node_X_data > split)[0]
  
      return left, right
  
imports: from collections import defaultdict
  from typing import List, Mapping
  import numpy
  from sklearn.utils import compute_class_weight
  from dtreeviz.models.shadow_decision_tree import ShadowDecTree
  from dtreeviz.utils import criterion_remapping
label_desc: Use image node_id 12 for calling the ShadowSKDTree obj's underlying member method code with example usage: obj.get_split_samples(id) and returns: left,  right