为什么用括号和逗号对索引的numpy数组的行为有所不同？ [英] Why does indexing numpy arrays with brackets and commas differ in behavior?

问题描述

我倾向于使用括号来索引numpy数组（矩阵），但我注意到当我想切片数组（矩阵）时我必须使用逗号表示法。为什么是这样？例如，

I tend to index numpy arrays (matrices) with brackets, but I've noticed when I want to slice an array (matrix) I must use the comma notation. Why is this? For example,

>>> x = numpy.array([[1, 2], [3, 4], [5, 6]])
>>> x
array([[1, 2],
       [3, 4],
       [5, 6]])
>>> x[1][1]
4                 # expected behavior
>>> x[1,1]
4                 # expected behavior
>>> x[:][1]
array([3, 4])     # huh?
>>> x[:,1]
array([2, 4, 6])  # expected behavior

推荐答案

这：

x[:, 1]

表示沿第一轴取 x 的所有指数，但仅限索引1沿着第二个。

means "take all indices of x along the first axis, but only index 1 along the second".

这个：

x[:][1]

表示取所有 x 沿着第一个轴（所有 x ），然后沿着结果的第一个轴取下索引1。您将 1 应用于错误的轴。

means "take all indices of x along the first axis (so all of x), then take index 1 along the first axis of the result". You're applying the 1 to the wrong axis.

x [1] [ 2] 和 x [1,2] 只是等价的，因为用整数索引数组会将所有剩余的轴移向形状的前面，所以 x [1] 的第一个轴是 x 的第二个轴。这根本没有概括;你应该几乎总是使用逗号而不是多个索引步骤。

x[1][2] and x[1, 2] are only equivalent because indexing an array with an integer shifts all remaining axes towards the front of the shape, so the first axis of x[1] is the second axis of x. This doesn't generalize at all; you should almost always use commas instead of multiple indexing steps.

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