numpy:a [i] [j]和a [i，j]之间的差异 [英] Numpy: Difference between a[i][j] and a[i,j]

问题描述

来自Python的Lists背景以及C ++/Java等编程语言的背景，人们习惯于使用a[i][j]方法提取元素.但是在NumPy中，通常会执行a[i,j].两者都会返回相同的结果.

Coming from a Lists background in Python and that of programming languages like C++/Java, one is used to the notation of extracting elements using a[i][j] approach. But in NumPy, one usually does a[i,j]. Both of these would return the same result.

两者之间的根本区别是什么?应该优先选择哪个?

What is the fundamental difference between the two and which should be preferred?

推荐答案

主要区别在于a[i][j]首先在a[i]上创建一个视图，然后在该视图中建立索引.另一方面，a[i,j]直接索引到a中，从而使其更快:

The main difference is that a[i][j] first creates a view onto a[i] and then indexes into that view. On the other hand, a[i,j] indexes directly into a, making it faster:

In [9]: a = np.random.rand(1000,1000)

In [10]: %timeit a[123][456]
1000000 loops, best of 3: 586 ns per loop

In [11]: %timeit a[123,456]
1000000 loops, best of 3: 234 ns per loop

基于这个原因，我希望后者.

For this reason, I'd prefer the latter.

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