numpy:使用2D索引数组进行2D数组访问 [英] Numpy: 2D array access with 2D array of indices

问题描述

我有两个数组，一个是索引对的矩阵，

I have two arrays, one is a matrix of index pairs,

a = array([[[0,0],[1,1]],[[2,0],[2,1]]], dtype=int)

和另一个是要在这些索引处访问的数据矩阵

and another which is a matrix of data to access at these indices

b = array([[1,2,3],[4,5,6],[7,8,9]])

，并且我希望能够使用a的索引来获取b的条目.只是在做:

and I want to able to use the indices of a to get the entries of b. Just doing:

>>> b[a]

不起作用，因为它为a中的每个条目给出了一行b，即

does not work, as it gives one row of b for each entry in a, i.e.

array([[[[1,2,3],
         [1,2,3]],

        [[4,5,6],
         [4,5,6]]],


       [[[7,8,9],
         [1,2,3]],

        [[7,8,9],
         [4,5,6]]]])

当我想使用a的最后一个轴上的索引对给出b的两个索引时:

when I would like to use the index pair in the last axis of a to give the two indices of b:

array([[1,5],[7,8]])

是否有一种干净的方法?还是需要重塑b的形状并以相应的方式组合a的列?

Is there a clean way of doing this, or do I need to reshape b and combine the columns of a in a corresponding manner?

在我的实际问题中，a大约有500万个条目，而b是100 x 100，我想避免for循环.

In my actual problem a has about 5 million entries, and b is 100-by-100, I'd like to avoid for loops.

推荐答案

实际上，这可行:

b[a[:, :, 0],a[:, :, 1]]

给予array([[1, 5], [7, 8]]).

Gives array([[1, 5], [7, 8]]).

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