[SciPy-user] Inverse of complex matrix

Roger Herikstad roger.herikstad@gmail....
Sat Nov 10 04:09:20 CST 2007


Dear all,
 Thanks. I can get away with not inverting the matrix, actually, I
just wanted to confirm a calculation via a different route, and I was
momentarily surprised by my result. I realise my mistake though.
Thanks for pointing it out for me!

~ Roger

On Nov 10, 2007 4:11 PM, David Cournapeau <david@ar.media.kyoto-u.ac.jp> wrote:
>
> Roger Herikstad wrote:
> > Dear scipy users,
> >  I am trying to invert a 12 by 12 complex matrix R using
> > scipy.linalg.inv(), but the round-off errors seem a bit too big. If I
> > do scipy.dot(Ri,R), the first row of the resulting matrix looks like
> > this:
> >
> > array([ 0.953125  +0.j        ,  0.06542969+0.01171875j,
> >         0.08154297+0.15234375j, -0.078125  -0.09375j   ,
> >         0.19140625-0.0859375j ,  0.08203125+0.140625j  ,
> >        -0.08398438+0.0078125j , -0.02539062-0.03125j   ,
> >        -0.06738281+0.015625j  , -0.04736328+0.15820312j,
> >        -0.09057617+0.02832031j,  0.109375  -0.0625j    ])
> >
> >
> > Is this normal? Inverting a 2x2 matrix produces the expected result.
> > I've attached a pickle of my matrix. Thanks!
> As a rule, you should not invert a matrix unless you *really* need it.
> For example, if you want X in
> A X = B, with A a matrix, B and X vectors, inverting A should be
> avoided. Some other methods are better suited (numerically speaking),
> depending on A and what you are trying to do.
>
> The mathworks have good introduction on this topic, if you look for
> online help on inv, pinv and so on:
>
> http://www.mathworks.com/access/helpdesk/help/techdoc/ref/inv.html
>
> cheers,
>
> David
>
>
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