使用字典理解归一化概率

Question

我的python字典看起来像

probabilities = {'harry': {'gene': {0: 0.23, 1: 0.09, 2: 0.13}, 'trait': {False: 0.23, True: 0.32}},
 'jim': {'gene': {0: 0.12, 1: 0.15, 2: 0.56}, 'trait': {False: 0.67, True: 0.12}}}

我通过编写像

这样的代码来规范化它

for person in probabilities:
        for attribute in probabilities[person]:
            denominator = sum(probabilities[person][attribute].values())
            for value in probabilities[person][attribute]:
                probabilities[person][attribute][value] /= denominator

代码很好，因为它完美地标准化了概率。但是我可以使用字典理解来做同样的事情吗？如果是这样，如何？如果不是，为什么？

Answer 1

一点努力让我得到：

probabilities = {'harry': {'gene': {0: 0.23, 1: 0.09, 2: 0.13}, 'trait': {False: 0.23, True: 0.32}},
                 'jim': {'gene': {0: 0.12, 1: 0.15, 2: 0.56}, 'trait': {False: 0.67, True: 0.12}}}

probabilities_new = {
    p: {
        k: {
            k_inn: v_inn / sum(v.values())
            for k_inn, v_inn in v.items()
        }
        for k, v in a.items()
    }
    for p, a in probabilities.items()
}

使用字典理解归一化概率

Normalize Probability using Dictionary Comprehension

dictionary-comprehension

normalize