以零开头的numpy形状是什么意思 [英] What does a numpy shape starting with zero mean

问题描述

好吧，所以我发现可以有形状为0的数组.
对于您只有0作为唯一尺寸的情况，这对我来说很有意义.这是一个空数组.

Okay, so I found out that you can have arrays with 0s in their shape.
For the case where you have 0 as the only dimension, this makes sense to me. It is an empty array.

np.zeros(0)

但是如果您有这样的情况:

But the case where you have something like this:

np.zeros((0, 100))

让我感到困惑.为什么这样定义?

Is confusing for me. Why is it defined like this?

推荐答案

据我所知，这只是表示空数组的一种多余方法.如果您有空"行，对于python似乎并不重要.

As far as I know it's just a redundant way to express an empty array. It doesn't seems to matter for python if you have rows of "emptiness".

假设我们有一个给定数组a:

Let's say we have a give array a:

import numpy as np

a = np.zeros((0,100))

如果我们打印出全部，我们得到的就是空数组本身:

If we print a all we get is the empty array itself:

print(a)

>>> []

此外，我们实际上可以看到，尽管保持了它的形状，

Moreover we can actually see that despite this a maintain it's shape"

np.shape(a)

>>> (0, 100)

但是，如果您尝试按位置访问给定的元素，例如:

But if you try to access a given element by position, e.g:

print(a[0])

或

print(a[0][0])

您收到IndexError:

You get an IndexError :

IndexError: index 0 is out of bounds for axis 0 with size 0

因此，我相信，尽管您为空数组指定了形状，但它们的数学含义是相同的.

Therefore I believe that the mathematical meaning of the empty arrays, despite the shape you assign to them, is the same.

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