将嵌套列表理解转换为常规 for 循环

Convert a nested list-comprehension to regular for loops

我想知道如何用常规循环编写这个列表理解:

sep_class = [[x for x, t in zip(X_train, y_train) if t==c] for c in np.unique(y_train)]

我这样试过:

sep_class = []
for c in np.unique(y_train):
    for x, t in zip(X_train, y_train):
        if t == c:
            sep_class.append(x)

但输出结果不同。我做错了什么?

sep_class = []
for c in np.unique(y_train):
    sep_class.append([])
    for x, t in zip(X_train, y_train):
        if t ==c:
            sep_class[c].append(x)

现在它们完全相同了。

将 list-comprehension 转换为常规循环的最通用方法如下:

l = [f(x) for x in iter]

# converts to:

l = []
for x in iter:
    l.append(f(x))

当您在理解中创建嵌套列表时,这会变得有点复杂,但遵循相同的逻辑,现在 f(x) 是 list-comp 本身的翻译。所以我们有:

l = [[g(x) for x in sub] for sub in iter]

# converts to:

l = []
for sub in iter:
    temp = []
    for x in sub:
        temp.append(g(x))
    l.append(temp)

所以在你的情况下,只需添加条件,list-comp 就变成了:

sep_class = [[x for x, t in zip(X_train, y_train)if t ==c] for c in np.unique(y_train)]

# converts to:

sep_class = []
for c in np.unique(y_train):
    sub = []
    for x, t in zip(X_train, y_train):
        if t == c:
            sub.append(x)
    sep_class.append(sub)