Avoid for loop using numpy matrices

Question

I'm wondering that must be a way of doing the following without the for loop:

import numpy
from itertools import product as itprod

a = np.arange(120.).reshape(3,2,5,2,2)
fact = np.linspace(1,1.4,15).reshape((3,5))

for i,j in itprod(range(3),range(5)):
    a[i,:,j]*= fact[i,j]

Any suggestions??

@That1Guy: A Python for loop is a rather slow way of operating on Numpy arrays. The idea of Numpy is to do vectorised high-level calls, so the actual looping can happen in optimised C code. — Sven Marnach
– Sven Marnach, Commented Sep 11, 2015 at 15:27

Sven Marnach · Accepted Answer · 2015-09-11 15:26:16Z

4

To take advantage of broadcasting, you have to insert new axes for fact at the right places:

a *= fact[:, np.newaxis, :, np.newaxis, np.newaxis]

answered Sep 11, 2015 at 15:26

Sven Marnach

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