numpy rollaxis-它是如何工作的? [英] numpy rollaxis - how exactly does it work?

问题描述

因此，我正在尝试numpy，并且在rollaxis方法中遇到了一个奇怪的(?)行为.

So I was experimenting with numpy and I ran across a strange (?) behavior in the rollaxis method.

In [81]: a = np.ones((4, 3, 2))

In [82]: a.shape
Out[82]: (4, 3, 2)

In [83]: x = np.rollaxis(a, 2)

In [84]: x.shape
Out[84]: (2, 4, 3)

In [85]: np.rollaxis(x, -2).shape
Out[85]: (4, 2, 3)

-2是否不能反转横滚轴?我想做的是应用一个仅在第2个坐标为第一个坐标时才能应用的矩阵.但是然后我想将数组放回其原始形式.我发现唯一起作用的是两次应用np.rollaxis(x, 2)或应用np.rollaxis(x, 0, start=3).我只是通过猜测发现它们，我不知道它们为什么起作用.他们似乎也掩盖了我真正想做的事情.有人可以解释一下我应该反向"滚动的方式，或者我做错了什么吗?

Shouldn't the -2 reverse the rollaxis? What I'm trying to do is apply a matrix that can only be applied when the 2 coordinate is first. But then I want to put my array back into its original form. The only things which I have found to work are applying np.rollaxis(x, 2) twice, or applying np.rollaxis(x, 0, start=3). I just found these by guessing and I have no idea why they work. They also seem to be obscuring what I'm really trying to do. Could somebody please explain the way that I should 'reverse' a roll, or what I'm doing wrong?

(是否有Python方式来做到这一点?)

(Is there a pythonic way to do this?)

推荐答案

方法rollaxis

def rollaxis(a, axis, start=0):

将选择的axis重新分配到start位置"

reallocates the chosen axis at the start "position"

按照您的示例:

a = np.ones((4, 3, 2))
x = np.rollaxis(a, 2)
# x.shape = (2, 4, 3)

关于形状:rollaxis会将最后一个axis=2中的数字2带到自start=0开始的第一个位置.

Concerning shapes: rollaxis will bring the number 2, which is in your last axis=2, to the the first position, since start=0.

通过使用

x2 = np.rollaxis(x, -2)
# x2.shape = (4,2,3)

rollaxis将带数字4，这是倒数第二个轴，axis=-2，并从start=0开始在第一个位置重新分配.这就解释了您的结果(4,2,3)，而不是(4,3,2).

rollaxis will bring the number 4, which is the second last axis, axis=-2, and reallocate at the first position, since start=0. That explains your result (4,2,3), instead of (4,3,2).

按照相同的逻辑，这解释了为什么两次应用rollaxis(a,2)会将数组形状恢复为初始形状. np.rollaxis(x, 0, start=3)也起作用，因为第一个轴转到最后一个轴，换句话说(2,4,3)中的数字2到达最后一个结果(4,3,2).

Following the same logic, this explains why applying rollaxis(a,2) twice brings the array shape back to the initial one. np.rollaxis(x, 0, start=3) also works because the first axis goes to the last one, in other words the number 2 in (2,4,3) goes to the last position resulting (4,3,2).

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