使用数组作为索引增加numpy数组元素 [英] Increase numpy array elements using array as index

问题描述

我正在尝试使用另一个数组b来指示要更新的A元素的索引，从而有效地更新numpy数组A的某些元素.但是b可以包含被忽略的重复项，而我希望将其考虑在内.我想避免循环b.为了说明这一点:

I am trying to efficiently update some elements of a numpy array A, using another array b to indicate the indexes of the elements of A to be updated. However b can contain duplicates which are ignored whereas I would like to be taken into account. I would like to avoid for looping b. To illustrate it:

>>> A = np.arange(10).reshape(2,5)
>>> A[0, np.array([1,1,1,2])] += 1
>>> A
array([[0, 2, 3, 3, 4],
       [5, 6, 7, 8, 9]])

我希望输出为:

array([[0, 3, 3, 3, 4],
       [5, 6, 7, 8, 9]])

有什么想法吗?

推荐答案

要正确处理重复的索引，您需要使用np.add.at而不是+=.因此，要更新A的第一行，最简单的方法可能是执行以下操作:

To correctly handle the duplicate indices, you'll need to use np.add.at instead of +=. Therefore to update the first row of A, the simplest way would probably be to do the following:

>>> np.add.at(A[0], [1,1,1,2], 1)
>>> A
array([[0, 4, 3, 3, 4],
       [5, 6, 7, 8, 9]])

ufunc.at方法的文档可以在此处.

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