code: def entropy_score(kmer):
      
      l = len(kmer) - 2
      k = l if l < 64 else 64
      counts = defaultdict(int)
      for i in range(l):
          trinuc = kmer[i: i + 3]
          counts[trinuc] += 1
  
      logk = math.log(k)
      res = 0
      for k, v in counts.items():
          f = v * 1. / l
          res += f * math.log(f) / logk
      return res * -100
docs: Schmieder and Edwards. Quality control and preprocessing of metagenomic datasets. (2011) Bioinformatics
      https://academic.oup.com/bioinformatics/article/27/6/863/236283/Quality-control-and-preprocessing-of-metagenomic