索引对之间的子数组中数值的总和 [英] Numpy sum of values in subarrays between pairs of indices
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问题描述
假设我有一个数组A.我有一系列的索引对(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
假定索引对存储在形状为(n, 2)
且n
的NumPy数组indices
中,则最好避免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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