Python矩阵乘法变体 [英] Python Matrix Multiplication Variations

问题描述

刚刚问了一个关于矩阵乘法的问题，可以在

just asked a question about multiplying matrices and that can be found here, I have one more question though about multiplying matrices. Say I have the following matrices:

matrix_a = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

matrix_b = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

我怎么能得到这样的结果:

How could I get a result like this:

[[1, 4, 9], [16, 25, 36], [49, 64, 81]]

...以便每个元素基本上都与另一个数组的单个对应元素相乘.有人知道怎么做吗?

...so that each element is basically being multiplied by the single corresponding element of the other array. Does anyone know how to do that?

谢谢大家！

推荐答案

您可以使用 zip 和

You could express the element-wise product (and matrix product) using list comprehensions, zip, and the * argument-unpacking operator:

matrix_a = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]    
matrix_b = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

elementwise_product = [[ai*bi for ai, bi in zip(*rows)] 
                       for rows in zip(matrix_a, matrix_b)]    
print(elementwise_product)
# [[1, 4, 9], [16, 25, 36], [49, 64, 81]]

matrix_product = [[sum([ai*bi for ai, bi in zip(row_a, col_b)])
                   for col_b in zip(*matrix_b)]
                  for row_a in matrix_a]
print(matrix_product)
# [[30, 36, 42], [66, 81, 96], [102, 126, 150]]

这篇关于Python矩阵乘法变体的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！