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

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




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?

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]])


    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


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