code: def entropy_score(var,bins, w=None, decimate=True):
      '''Compute entropy scores, given a variance and # of bins
      
      '''
      if w is None:
          n = len(var)
          w = np.arange(0,n,n//bins) / float(n)
      if decimate:
          n = len(var)
          var = var[0:n:n//bins]
      score = w * np.log(var * w * np.sqrt(2*np.pi*np.exp(1)))
      score[np.isnan(score)]=np.Inf
      return scorf entropy_score(var,bins, w=None, decimate=True):
      '''Compute entropy scores, given a variance and # of bins
      
      '''
      if w is None:
          n = len(var)
          w = np.arange(0,n,n//bins) / float(n)
      if decimate:
          n = len(var)
          var = var[0:n:n//bins]
      score = w * np.log(var * w * np.sqrt(2*np.pi*np.exp(1)))
      score[np.isnan(score)]=np.Inf
      return score
docs: Compute entropy scores, given a variance and # of bins