如何使用相同维度的两个矩阵执行逐元素的自定义函数 [英] How to perform element-wise custom function with two matrices of identical dimension

问题描述

未能找到任何有关此的信息.如果我有两个相同维度的m x n矩阵，有没有办法对它们应用numpty的逐个元素函数?为了说明我的意思:

Haven't been able to find any information on this. If I have two m x n matrices of identical dimension, is there a way to apply an element-wise function in numpty on them? To illustrate my meaning:

自定义函数为F(x，y)

Custom function is F(x,y)

第一矩阵:

array([[ a, b],
       [ c, d],
       [ e, f]])

第二矩阵:

array([[ g, h],
       [ i, j],
       [ k, l]])

是否可以使用numpy中的上述两个矩阵在下方获得所需的输出

Is there a way to use the above two matrices in numpy to get the desired output below

array([[ F(a,g), F(b,h)],
       [ F(c,i), F(d,j)],
       [ F(e,k), F(f,l)]])

我知道我可以为嵌套语句，但是我认为可能会有更简洁的方法

I know I could just do nested for statements, but I'm thinking there may be a cleaner way

推荐答案

对于常规函数 F(x，y)，您可以执行以下操作:

For a general function F(x,y), you can do:

out = [F(x,y) for x,y in zip(arr1.ravel(), arr2.ravel())]
out = np.array(out).reshape(arr1.shape)

但是，如果可能的话，我建议以可以向量化的方式重写 F(x，y):

However, if possible, I would recommend rewriting F(x,y) in such a way that it can be vectorized:

# non vectorized F
def F(x,y):
    return math.sin(x) + math.sin(y)

# vectorized F
def Fv(x,y):
    return np.sin(x) + np.sin(y)

# this would fail - need to go the route above
out = F(arr1, arr2)

# this would work
out = Fv(arr1, arr2)

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