How to get element-wise matrix multiplication (Hadamard product) in numpy?

Question

I have two matrices

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

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

I have tried

print(np.dot(a,b))

and

print(a*b)

but both give the result

[[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?

Asked By: Malintha

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Source

Answer 1

just do this:

import numpy as np

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

a * b

Answered By: jtitusj

Answer 2

For elementwise multiplication of matrix objects, you can use 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

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

However, you should really use array instead of matrix. matrix objects have all sorts of horrible incompatibilities with regular ndarrays. With ndarrays, you can just use * for elementwise multiplication:

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:

a @ b  # matrix multiplication

Answered By: Rahul K P

Answer 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

%timeit is ipython magic

Answered By: 4rshdeep

Answer 4

Try this:

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:

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

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

result = np.mat(result)

Answered By: amrezzd

Answer 5

error: OpenCV(4.6.0) /io/opencv/modules/core/src/arithm.cpp:230: error: (-215:Assertion failed) (mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1) in function 'binary_op'

This is the error When I tried .Implemented the LOGIC

def masking_rgb(im_rgb,im_mask):
  r1,c1=im_mask.shape
  for i in range(r1):
    for j in range (c1):
      if im_mask[i,j]==0:
        im_rgb[i,j,:]=0
  return im_rgb

im_rgb=masking_rgb(im_rgb,im_mask)
plt.imshow(im_rgb)
plt.show()

Answered By: Aneesh R P Prakkulam

How to get element-wise matrix multiplication (Hadamard product) in numpy?

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