code: def score_linked_tree(tree, neighbor_indices):
      result = 0.0
      n_nodes = len(tree.children)
      for i in range(n_nodes):
          node = numba.int32(i)
          left_child = tree.children[node][0]
          right_child = tree.children[node][1]
          if left_child == -1 and right_child == -1:
              for j in range(tree.indices[node].shape[0]):
                  idx = tree.indices[node][j]
                  intersection = arr_intersect(
                      neighbor_indices[idx], tree.indices[node]
                  )
                  result += numba.float32(intersection.shape[0] > 1)
      return result / numba.float32(neighbor_indices.shape[0])
  
imports: from warnings import warn
  import locale
  import numpy
  import numba
  import scipy.sparse
  from pynndescent.sparse import sparse_mul, sparse_diff, sparse_sum, arr_intersect, sparse_dot_product
  from pynndescent.utils import tau_rand_int, norm
  import joblib
  from collections import namedtuple
label_desc: Use image node_id 26 for calling a global function with example usage: score_linked_tree(tree, neighbor_indices) and returns: unknown