如何在numpy中获得元素矩阵乘法(Hadamard乘积)?

I have two matrices

我有两个矩阵

a = np.matrix([[1,2], [3,4]])
b = np.matrix([[5,6], [7,8]])

and I want to get the element-wise product, [[1*5,2*6], [3*7,4*8]], equaling

我想要得到元素的乘积，[1*5,2*6]，[3*7,4*8]，等于

[[5,12], [21,32]]

[[5,12],[21日32]]

I have tried

我有试过

print(np.dot(a,b))

and

和

print(a*b)

but both give the result

但两者都给出了结果。

[[19 22], [43 50]]

22[[19],[43 50]]

which is the matrix product, not the element-wise product. How can I get the the element-wise product (aka Hadamard product) using built-in functions?

它是矩阵的乘积，而不是元素的乘积。如何使用内置函数获得元素级产品(又名Hadamard产品)?

4 个解决方案

#1

Try this,

试试这个,

import numpy as np
a = np.array([[1,2],[3,4]])
b = np.array([[5,6],[7,8]])
np.multiply(a,b)

Result

结果

array([[ 5, 12],
       [21, 32]])

#2

just do this:

只是这样做:

import numpy as np

a = np.array([[1,2],[3,4]])
b = np.array([[5,6],[7,8]])

a * b

#3

import numpy as np
x = np.array([[1,2,3], [4,5,6]])
y = np.array([[-1, 2, 0], [-2, 5, 1]])

x*y
Out: 
array([[-1,  4,  0],
       [-8, 25,  6]])

%timeit x*y
1000000 loops, best of 3: 421 ns per loop

np.multiply(x,y)
Out: 
array([[-1,  4,  0],
       [-8, 25,  6]])

%timeit np.multiply(x, y)
1000000 loops, best of 3: 457 ns per loop

Both np.multiply and * would yield element wise multiplication known as the Hadamard Product

np。乘法和*会产生元素智慧乘法，称为哈达玛乘积

%timeit is ipython magic

%时间是ipython魔法

#4

Try this:

试试这个:

a = np.matrix([[1,2], [3,4]])
b = np.matrix([[5,6], [7,8]])

#This would result a 'numpy.ndarray'
result = np.array(a) * np.array(b)

Here, np.array(a) returns a 2D array of type ndarray and multiplication of two ndarray would result element wise multiplication. So the result would be:

在这里，np.array(a)返回一个二维数组ndarray，并且两个ndarray的乘法将会得到元素wise乘法。结果是:

result = [[5, 12], [21, 32]]

If you wanna get a matrix, the do it with this:

如果你想要一个矩阵，用这个来做:

result = np.mat(result)

#1