NumPy中的axis参数如何工作? [英] How does the axis parameter from NumPy work?

问题描述

有人可以确切解释NumPy中的axis参数做什么吗?

Can someone explain exactly what the axis parameter in NumPy does?

我非常困惑.

我正在尝试使用功能myArray.sum(axis=num)

起初，我以为如果数组本身是3维，则axis=0将返回三个元素，由位于同一位置的所有嵌套项的总和组成.如果每个维度包含五个维度，则我期望axis=1返回五个项目的结果，依此类推.

At first I thought if the array is itself 3 dimensions, axis=0 will return three elements, consisting of the sum of all nested items in that same position. If each dimension contained five dimensions, I expected axis=1 to return a result of five items, and so on.

但是事实并非如此，文档不能很好地帮助我(他们使用3x3x3数组，因此很难说出正在发生的事情)

However this is not the case, and the documentation does not do a good job helping me out (they use a 3x3x3 array so it's hard to tell what's happening)

这就是我所做的:

>>> e
array([[[1, 0],
        [0, 0]],

       [[1, 1],
        [1, 0]],

       [[1, 0],
        [0, 1]]])
>>> e.sum(axis = 0)
array([[3, 1],
       [1, 1]])
>>> e.sum(axis=1)
array([[1, 0],
       [2, 1],
       [1, 1]])
>>> e.sum(axis=2)
array([[1, 0],
       [2, 1],
       [1, 1]])
>>>

显然结果不直观.

推荐答案

很显然，

e.shape == (3, 2, 2)

轴上的总和是归约运算，因此指定的轴消失.因此，

Sum over an axis is a reduction operation so the specified axis disappears. Hence,

e.sum(axis=0).shape == (2, 2)
e.sum(axis=1).shape == (3, 2)
e.sum(axis=2).shape == (3, 2)

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