def get_mean_DRAT(sum_ptrm_checks, sum_abs_ptrm_checks, n_pTRM, L):
    """
    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)
    """
    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
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
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)