code: def hierarchical_categorical_distance(x, y, cat_hierarchy=[{}]):
      n_levels = float(len(cat_hierarchy))
      for level, cats in enumerate(cat_hierarchy):
          if cats[x] == cats[y]:
              return float(level) / n_levels
      else:
          return 1.0
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 53 for calling a global function with example usage: hierarchical_categorical_distance(x, y, cat_hierarchy) and returns: int, unknown