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夏天快到了，又是吃小龙虾的季节。白富美学姐前两天约我吃最爱的小龙虾，席间向来开心的她却显得心事重重。

Python学习交流群：1004391443，有大牛答疑，有资源共享！有想学习python编程的，想提升自己能力的，欢迎加入讨论学习。

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“你肿么啦？”我仔细地掰开虾壳，问道。

“十一假期好多朋友办婚礼，可我男票一点要求婚的意思都没有，我都想考虑备胎了。”

“你自己和他说嘛！”我放下了油亮亮的小龙虾。

“我可是个妹子，这样多不好。”学姐叹了口气。

看着学姐犹犹豫豫的样子就知道她需要鼓励了~我眉头一皱，计上心来：

学姐呀，我来给你讲个故事~

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有一座城市，当地风俗是，想结婚的男子必须先向心仪的女子求婚，而女子则需要等待求婚。

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牧师每年会邀请人数相同的适婚男女参与一次集体相亲。一次相亲活动可能有很多轮，男子会首先向自己最爱的女子求婚，女子则会在所有的追求者中选择她的最爱；如果男子被拒绝，下一轮会向他第二喜欢的女子求婚；上一轮已经订婚的女子如果得到她更爱的人的求婚，则会毫不留情地抛弃未婚夫，和更爱的人在一起。被抛弃的男子需要重新参与求婚。

如此反复，等大家都订婚，就举办集体婚礼。

假设：1)参加求婚的男女数量保持一致2)每个男子都按喜爱程度对女子进行排序，比如最爱a，其次爱b，再次爱c3)每个女子也同样给每个男子排序

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*此方法名为Gale-Shapley算法。优点如下：

1. 总有大家都订了婚的一天，不可能无限循环2. 中止后所有的婚姻是稳定婚姻（不稳定婚姻：比如有两对夫妇M1&F1和M2&F2, M1的老婆是F1，但他更爱F2；而F2的老公虽说是M2，但她更爱M1。这样的婚姻就是不稳定婚姻）有兴趣的读者可以自行搜索证明过程。

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学姐的眼睛开始放光了：

坐在家里等求婚，下辈子请让我生在这个城市吧！

我神秘一笑：

是不是女孩子的天堂，让我们用Python来看一看最后的匹配满意度吧！

（此处展示部分代码，完整源文件请看文末）

一、样本生成

为了完成模拟过程，我们首先需要一些样本，即随机生成数量相等（可设置数量）的男性和女性，同时生成他们对每个异性个体的喜爱排名

。

设置男女生喜好样本

print('==============================生成样本数据==============================')

man = pd.DataFrame( [['w'+str(i) for i in random.sample(range(1,women_num+1),women_num)] \

for i in range(man_num)],

index = ['m'+str(i) for i in range(1,man_num+1)],

columns = ['level'+str(i) for i in range(1,women_num+1)]

)

women = pd.DataFrame( [['m'+str(i) for i in random.sample(range(1,man_num+1),man_num)] \

for i in range(women_num)],

index = ['w'+str(i) for i in range(1,women_num+1)],

columns = ['level'+str(i) for i in range(1,man_num+1)]

)

return (man,women)

二、模拟男性求婚过程

每天上午，每位还没订婚的男子，会向还没拒绝过他的女子中，他最爱的那一个求婚。

print('==============================测试集{}模拟开始=============================='.format(i))

print('==============================开始模拟求婚过程==============================')

level_num = 0

while man_ismapping['love_level'].min() == 0:

level_num += 1

print('==============================开始第{}天婚姻配对=============================='.format(level_num))

u_mapping_man = man_ismapping[man_ismapping.target == 'n'].index.tolist()

if level_num < 2:

level_col = 'level' + str(level_num)

man_choose = man[man.index.isin(u_mapping_man)][level_col].to_frame().reset_index()

man_choose.columns = ['man_id', 'women_id']

man_choose['range'] = 1

else:

m_id = u_mapping_man

l = []

for man_id in m_id:

col_n = int(man_ismapping[man_ismapping.index == man_id].range[0])

level_col = 'level' + str(col_n + 1)

women_id = man[man.index == man_id][level_col][0]

rg = col_n + 1

l.append([man_id, women_id, rg])

man_choose = pd.DataFrame(l, columns=['man_id', 'women_id', 'range'])

三、模拟女性接受订婚的过程

每天下午，每位女性会在自己接到的求婚信中，选择她最中意的男子接受求婚；如果没接到求婚，就继续等待。

for r in range(0, len(man_choose)):

relationship = man_choose[man_choose.index == r]

m = [i for i in relationship['man_id']][0]

w = [i for i in relationship['women_id']][0]

find = women[women.index == w].unstack().reset_index()

find.columns = ['level', 'women_id', 'man_id']

find = int([i for i in find[find['man_id'] == m]['level']][0].split('level')[1])

o_love_level = [i for i in women_ismapping[women_ismapping.index == w]['love_level']][0]

rg = [i for i in relationship['range']][0]

if o_love_level == 0:

women_ismapping.loc[w, 'love_level'] = find

women_ismapping.loc[w, 'target'] = m

women_ismapping.loc[w, 'range'] = level_num

man_ismapping.loc[m, 'love_level'] = rg

man_ismapping.loc[m, 'target'] = w

man_ismapping.loc[m, 'range'] = rg

elif o_love_level > find:

m_o = women_ismapping.loc[w, 'target']

man_ismapping.loc[m_o, 'love_level'] = 0

man_ismapping.loc[m_o, 'target'] = 'n'

man_ismapping.loc[m, 'love_level'] = rg

man_ismapping.loc[m, 'target'] = w

man_ismapping.loc[m, 'range'] = rg

women_ismapping.loc[w, 'love_level'] = find

women_ismapping.loc[w, 'target'] = m

women_ismapping.loc[w, 'range'] = level_num

else:

man_ismapping.loc[m, 'range'] = rg

pass

四、运行代码，并导出结果

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学姐看着正在运行模拟过程有点着急了，我抽取其中一轮的结果先展示给她看：

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<input class="pgc-img-caption-ipt" placeholder="图片描述(最多50字)" value="" style="box-sizing: border-box; outline: 0px; color: rgb(102, 102, 102); position: absolute; left: 187.5px; transform: translateX(-50%); padding: 6px 7px; max-width: 100%; width: 375px; text-align: center; cursor: text; font-size: 12px; line-height: 1.5; background-color: rgb(255, 255, 255); background-image: none; border: 0px solid rgb(217, 217, 217); border-radius: 4px; transition: all 0.2s cubic-bezier(0.645, 0.045, 0.355, 1) 0s;"></tt-image>

纵轴代表该次模拟结果中，某位男性/女性的伴侣喜爱排名，即：匹配到的伴侣是他/她第X喜欢的异性。

显然，男性匹配到的伴侣离自己的最爱比女性更近——不止一点点！这可和“妹子天堂”的预期有点远啊！

学姐陷入了困惑：

明明女性才掌握着订婚的决定权，而且男性即使暂时订婚成功，也有被抛弃的可能啊！你看，随着匹配轮次增加，

男性的伴侣总是从自己最喜欢的对象慢慢变成不那么喜欢的对象

；

而女性伴侣却在一步步变好

。你这个会不会是偶然啊！

我：

是不是偶然，让我们来看看

100次模拟中，男性/女性匹配到的伴侣喜爱排名均值分布吧~

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<input class="pgc-img-caption-ipt" placeholder="图片描述(最多50字)" value="" style="box-sizing: border-box; outline: 0px; color: rgb(102, 102, 102); position: absolute; left: 187.5px; transform: translateX(-50%); padding: 6px 7px; max-width: 100%; width: 375px; text-align: center; cursor: text; font-size: 12px; line-height: 1.5; background-color: rgb(255, 255, 255); background-image: none; border: 0px solid rgb(217, 217, 217); border-radius: 4px; transition: all 0.2s cubic-bezier(0.645, 0.045, 0.355, 1) 0s;"></tt-image>

*纵轴代表其中一次模拟中，男性/女性的平均伴侣喜爱排名均值，即：匹配到的伴侣是他们/她们第X喜欢的异性。

可以明显看到，男性最终匹配到的伴侣的喜爱排名普遍高于女性。

学姐终于收起了质疑

：

原来主动出击真有这么大的作用！为什么呀~

我分析道

：学姐你看，女孩只能坐在家里等求婚，她喜欢的人可能连看到她的机会都没有。而

男性在主动做出选择之时，每次都能选择自己最喜欢的对象

。即使被拒绝，他的下一次求婚，也能送给可能接受他的、他最爱的女孩儿。这个游戏

保证男孩的伴侣是可能和他在一起的最好的那一个

，但对女孩就不是。

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学姐：

你说得对。

面对自己喜欢的人，我应该去争取，而不只是等待。

我：这就对啦！世界上有什么事不需要努力呢？你有喜欢的人，就要好好努力，提升自己，去吸引ta，爱ta~