def ergodic_chain(args):
    (burnin, run_length, alpha_count_slow, alpha_count_fast,
     alpha_mu_slow, alpha_mu_fast, buckets_slow, buckets_fast) = args

    np.random.seed((os.getpid() << 16) | (int(time.time()) & 0xFFFF))
    rh_slow = create_rolling_histogram_class(
            Bucket=create_bucket_class(
                alpha_mu=alpha_mu_slow, alpha_count=alpha_count_slow),
            target_buckets=buckets_slow)()
    rh_fast = create_rolling_histogram_class(
            Bucket=create_bucket_class(
                alpha_mu=alpha_mu_fast, alpha_count=alpha_count_fast),
            target_buckets=buckets_fast)()

    jagged = [stats.uniform(x, x + 1) for x in range(200)]
    #for val in gen_value(jagged, burnin):
    #for val in gen_value([stats.uniform(0, 1)], burnin):
    for val in gen_value([stats.norm(0, 1)], burnin):
    #for val in gen_value([stats.cauchy(0)], burnin):
        rh_slow.update(val)
        rh_fast.update(val)
    data = [[] for _ in range(len(FUNC_LIST))]
    #for val in gen_value(jagged, run_length):
    #for val in gen_value([stats.uniform(0, 1)], run_length):
    for val in gen_value([stats.norm(0, 1)], run_length):
    #for val in gen_value([stats.cauchy(0)], run_length):
        rh_slow.update(val)
        rh_fast.update(val)
        cdf_long = rh_slow.get_CDF()
        cdf_short = rh_fast.get_CDF()
        for i, func in enumerate(FUNC_LIST):
            data[i].append(func(cdf_short, cdf_long))
    return data