Re: [Numpy-discussion] Bug? Product of complex arrays

[Tim H. <tim...@ie...>]

From: "Aureli Soria Frisch" <Aur...@ip...>



> Hi,
>
> It seems there is a problem when multiplying complex arrays, but maybe
that
> is already solved for the new NumPy 17.3, is it?
>
> The product of complex arrays does not seem to be right.
>
> Code lines:
>
> >>> a=a_conj[:]

This is your problem here. Array's differ from lists and such in that
slicing does not produce a copy. 'a' and 'a_conj' point to the same data
after this operation. One way to produce a copy is to use 'a =
Numeric.array(a_conj)'

> >>> a
> array([[ 1.-0.j,  1.-1.j,  1.-2.j],
>        [ 1.-3.j,  1.-4.j,  1.-5.j],
>        [ 1.-6.j,  1.-7.j,  1.-8.j]])
> >>> a.imag=a.imag*-1
> >>> a
> array([[ 1.+0.j,  1.+1.j,  1.+2.j],
>        [ 1.+3.j,  1.+4.j,  1.+5.j],
>        [ 1.+6.j,  1.+7.j,  1.+8.j]])

If you look at a_conj  now, you should see that it is the same as a.

> >>> Numeric.multiply(a,a_conj)
> array([[  1. +0.j,   0. +2.j,  -3. +4.j],
>        [ -8. +6.j, -15. +8.j, -24.+10.j],
>        [-35.+12.j, -48.+14.j, -63.+16.j]])

So what you have here is really a squared.

So, you could get this to work by replacing slicing with array(a_conf). A
much simpler way is:

a = Numeric.conjugate(a_conj)
a*a_conj
#...

Hope that clears things up for you.

-tim



> where the answer should be [[1+0j,2+0j,5+0j][10+0j,...
>
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> Fraunhofer IPK
> Dept. Pattern Recognition
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