code: def calc_top_av(sim_score_vec):
      """
      calc top average of scores vector
  
      Args:
          sim_score_vec(list(float)): vector of similarity scores
  
      Returns:
          float: av_score, average of top similarity scores in sim_score_vec
  
      """
      av_number_th = 3
      sim_score_vec_sorted = sorted(sim_score_vec, reverse=True)
      cntr = 0
      score_acc = 0
      for score in sim_score_vec_sorted:
          if score > -1:
              score_acc = score_acc + score
              cntr = cntr + 1
              if cntr >= av_number_th:
                  break
  
      if cntr > 0:
          av_score = score_acc / cntr
      else:
          av_score = 0
  
      return av_score
  
file_path: nlp-architect/examples/most_common_word_sense/feature_extraction.py
imports: import re
  import nltk
  import numpy
  from numpy import dot
  from numpy.linalg import norm
  from nlp_architect.utils.generic import license_prompt
label_desc: Use image node_id 11 for calling a global function with example usage: calc_top_av(sim_score_vec) and returns: av_score