code: def get_mean_DRAT(sum_ptrm_checks, sum_abs_ptrm_checks, n_pTRM, L):
      
      if not n_pTRM:
          return float('nan'), float('nan')
      mean_DRAT = ((old_div(1., n_pTRM)) * (old_div(sum_ptrm_checks, L))) * 100
      mean_DRAT_prime = ((old_div(1., n_pTRM)) * (old_div(sum_abs_ptrm_checks, L))) * 100
      return mean_DRAT, mean_DRAT_prime
docs: input: sum_ptrm_checks, sum_abs_ptrm_checks, n_pTRM, L
      output: mean DRAT (the average difference produced by a pTRM check,
      normalized by the length of the best-fit line)