Python 如何在numpy中获得逐元素矩阵乘法（Hadamard积）？
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/40034993/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
How to get element-wise matrix multiplication (Hadamard product) in numpy?
提问by Malintha
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
我想得到元素明智的产品[[1*5,2*6], [3*7,4*8]]，等于
[[5,12], [21,32]]
[[5,12], [21,32]]
I have tried
我试过了
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]]
[[19 22], [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?
这是矩阵乘积，而不是逐元素乘积。如何使用内置函数获得元素级产品（又名 Hadamard 产品）？
回答by Rahul K P
For elementwise multiplication of matrixobjects, you can use numpy.multiply:
对于matrix对象的元素乘法，您可以使用numpy.multiply：
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]])
However, you should really use arrayinstead of matrix. matrixobjects have all sorts of horrible incompatibilities with regular ndarrays. With ndarrays, you can just use *for elementwise multiplication:
但是，您确实应该使用array代替matrix. matrix对象与常规 ndarray 有各种可怕的不兼容。使用 ndarrays，您可以只*用于元素乘法：
a * b
If you're on Python 3.5+, you don't even lose the ability to perform matrix multiplication with an operator, because @does matrix multiplication now:
如果您使用的是 Python 3.5+，您甚至不会失去使用运算符执行矩阵乘法的能力，因为@现在矩阵乘法是：
a @ b # matrix multiplication
回答by jtitusj
just do this:
只需这样做：
import numpy as np
a = np.array([[1,2],[3,4]])
b = np.array([[5,6],[7,8]])
a * b
回答by 4rshdeep
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.multiplyand *would yield element wise multiplication known as the Hadamard Product
双方np.multiply并*会产生被称为阿达玛产品元素方式乘法
%timeitis ipython magic
%timeit是 ipython 的魔法吗
回答by Amir Rezazadeh
Try this:
尝试这个：
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 ndarrayand multiplication of two ndarraywould result element wise multiplication. So the result would be:
在这里，np.array(a)返回一个 2D 类型的数组ndarray，两个的乘法ndarray将导致元素乘法。所以结果将是：
result = [[5, 12], [21, 32]]
If you wanna get a matrix, the do it with this:
如果你想得到一个矩阵，用这个做：
result = np.mat(result)
