问：在 Python 中，预计连续抛硬币 N 次正面朝上的次数。我的代码给出的答案与已发布的正确答案不匹配，但不确定为什么

Question

我正在尝试编写 Python 代码来查看平均需要抛多少次硬币才能获得连续 N 个正面的序列。

我感到困惑的是，我的代码生成的答案与在线给出的答案不匹配，例如这里（以及许多其他地方）https://math.stackexchange.com/questions/364038/expected-连续五次正面朝上的抛硬币次数

据此，我需要连续获得不同数量的正面的预期抛掷次数为：E(1) = 2、E(2) = 6、E(3) = 14、E(4) = 30，E(5) = 62。但我没有得到这些答案！例如，我得到 E(3) = 8，而不是 14。运行下面的代码可以给出该答案，但您可以更改 n 来测试连续的其他目标正面数量。

出了什么问题？想必我的代码逻辑存在一些错误，但我承认我无法弄清楚它是什么。

您可以在此处查看、运行并制作我的代码的修改副本：https ://trinket.io/python/17154b2cbd

下面是代码本身，位于可运行的 trinket.io 页面之外。任何帮助找出问题所在的帮助将不胜感激！

非常感谢，

Raj PS 我能找到的最接近的相关问题是这个：Monte-Carlo Analog of Expected tosses for Two Continuous Heads in python 然而，据我所知，该问题中的代码实际上并没有测试两个连续的头，而是测试从一个头开始，然后在稍后（可能不连续）时间得到另一个头的序列。

# Click here to run and/or modify this code:
# https://trinket.io/python/17154b2cbd

import random
# n is  the target number of heads in a row
# Change the value of n, for different target heads-sequences
n = 3  
possible_tosses = [ 'h', 't' ]
num_trials = 1000
target_seq = ['h' for i in range(0,n)]
toss_sequence = []
seq_lengths_rec = []

for trial_num in range(0,num_trials):

    if (trial_num % 100) == 0:
        print 'Trial num', trial_num, 'out of', num_trials
        # (The free version of trinket.io uses Python2)

    target_reached = 0
    toss_num = 0

    while target_reached == 0:

        toss_num += 1
        random.shuffle(possible_tosses)
        this_toss = possible_tosses[0]
        #print([toss_num, this_toss])
        toss_sequence.append(this_toss)
        last_n_tosses = toss_sequence[-n:]
        #print(last_n_tosses)
    if last_n_tosses == target_seq:
        #print('Reached target at toss', toss_num)
        target_reached = 1
        seq_lengths_rec.append(toss_num)

print 'Average', sum(seq_lengths_rec) / len(seq_lengths_rec)

Answer 1

您不需要为每个实验重新初始化toss_sequence，因此您可以使用预先存在的头部序列开始每个实验，在每个新实验的第一次尝试中都有二分之一的机会击中目标序列。

toss_sequence在外循环内部初始化将解决您的问题：

import random
# n is  the target number of heads in a row
# Change the value of n, for different target heads-sequences
n = 4
possible_tosses = [ 'h', 't' ]
num_trials = 1000
target_seq = ['h' for i in range(0,n)]
seq_lengths_rec = []

for trial_num in range(0,num_trials):

    if (trial_num % 100) == 0:
        print('Trial num {} out of {}'.format(trial_num, num_trials))
        # (The free version of trinket.io uses Python2)

    target_reached = 0
    toss_num = 0
    toss_sequence = []

    while target_reached == 0:

        toss_num += 1
        random.shuffle(possible_tosses)
        this_toss = possible_tosses[0]
        #print([toss_num, this_toss])
        toss_sequence.append(this_toss)
        last_n_tosses = toss_sequence[-n:]
        #print(last_n_tosses)
        if last_n_tosses == target_seq:
            #print('Reached target at toss', toss_num)
            target_reached = 1
            seq_lengths_rec.append(toss_num)

print(sum(seq_lengths_rec) / len(seq_lengths_rec))

您可以稍微简化一下代码，并使其不易出错：

import random
# n is  the target number of heads in a row
# Change the value of n, for different target heads-sequences
n = 3
possible_tosses = [ 'h', 't' ]
num_trials = 1000
seq_lengths_rec = []

for trial_num in range(0, num_trials):

    if (trial_num % 100) == 0:
        print('Trial num {} out of {}'.format(trial_num, num_trials))
        # (The free version of trinket.io uses Python2)

    heads_counter = 0
    toss_counter = 0

    while heads_counter < n:
        toss_counter += 1

        this_toss = random.choice(possible_tosses)

        if this_toss == 'h':
            heads_counter += 1
        else:
            heads_counter = 0
    seq_lengths_rec.append(toss_counter)


print(sum(seq_lengths_rec) / len(seq_lengths_rec))