code: def lc_score(value):
      
      rebased = 2 * (value - 0.5)
  
      if rebased == 0:
          return 0
      elif rebased > 0:
          compliment = 1.0 - rebased
          score = - np.log2(compliment)
      else:
          compliment = 1.0 + rebased
          score = np.log2(compliment)
      return score
docs: Evaluates the accuracy of a predictive measure (e.g. r-squared)
  
      :param value: float, between 0.0 and 1.0.
      :return: