脾气暴躁:点乘积以最大值代替总和 [英] Numpy: Dot product with max instead of sum

问题描述

numpy中是否有一种方法可以执行以下操作(或者是否有通用的数学术语):

Is there a way in numpy to do the following (or is there a general mathematical term for this):

假定普通点积:

M3[i,k] = sum_j(M1[i,j] * M2[j,k])

现在，我想用其他运算总和来代替总和，即最大值:

Now I would like to replace the sum by sum other operation, say the maximum:

M3[i,k] = max_j(M1[i,j] * M2[j,k])

如您所见，它与上面的内容完全平行，只是我们对所有j取了max而不是总和.

As you can see it is completely parallel to the above, just we take max over all j and not the sum.

其他选项可能是min，prod，以及将序列/集合转换为值的任何其他操作.

Other options could be min, prod, and whatever other operation that turns a sequence/set into a value.

推荐答案

正常的点积应为(使用numpy广播)

Normal dot product would be (using numpy broadcasting)

M3 = np.sum(M1[:, :, None] * M2[None, :, :], axis = 1)

您可以对具有axis关键字的任何功能执行相同的操作.

You can do the same thing with any function you want that has an axis keyword.

M3 = np.max(M1[:, :, None] * M2[None, :, :], axis = 1)

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