code: def entropy_calc(item, POP):
      
      try:
          result = 0
          for i in item.keys():
              likelihood = item[i] / POP[i]
              if likelihood != 0:
                  result += likelihood * math.log(likelihood, 2)
          return -result
      except Exception:
          return "None"
docs: Calculate reference and response likelihood.
  
      :param item : TOP or P
      :type item : dict
      :param POP: population
      :type POP : dict
      :return: reference or response likelihood as float