# 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?

just do this:

``````import numpy as np

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

a * b
``````

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
``````
``````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

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)
``````
``````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):