索引对之间子数组中值的 Numpy 总和 [英] Numpy sum of values in subarrays between pairs of indices

问题描述

假设我有一个数组 A.我有一系列索引对 (a1, b1), (a2, b2) ... (an, bn)

Suppose I have an array A. I have a series of index pairs (a1, b1), (a2, b2) ... (an, bn)

我想获得这些对之间元素的所有总和.即

I want to obtain all the sums of the elements between those pairs. i.e.

sum(A[a1:b1]), sum(A[a2:b2]), sum(A[a3:b3]) ...

就运行时而言，最有效的方法是什么?

In terms of run-time, what's the most efficient way of doing this?

谢谢！

推荐答案

假设您的索引对存储在形状为 (n, 2) 的 NumPy 数组 indices 和n 相当大，最好避免任何 Python 循环:

Assuming your index pairs are stored in a NumPy array indices of shape (n, 2) and n is fairly large, it is probably best to avoid any Python loop:

c = numpy.r_[0, A.cumsum()][indices]
sums = c[:,1] - c[:,0]

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