[SciPy-user] NNLS in scipy

Peter Skomoroch peter.skomoroch@gmail....
Sun Jun 15 16:45:08 CDT 2008


Christian,

I was just going to do a blog post on this same topic next week.  I have a
few different versions of python NMF code I used a few years ago, including
sparse, parallel, and memmap versions.

Until I post my examples, you can find a basic implementation based on scipy
here (from Toby Segaran):

http://examples.oreilly.com/9780596529321/

These guys also did an implementation in python:

http://www.ma.utexas.edu/users/zmccoy/plsinmf.html
http://www.ma.utexas.edu/users/zmccoy/nmf.py

Some more NMF related links here:

http://del.icio.us/pskomoroch/nmf

-Pete


On Sun, Jun 15, 2008 at 12:07 PM, Christian Meesters <meesters@uni-mainz.de>
wrote:

> Hi,
>
> I'd like to perform some "non-negatively constraint least squares"
> algorithm to fit my data, like this:
>
> Signal = SUM a_i C_i
>
> where C_i is some simulated signal and a_i the amplitude contributed by
> that simulated signal. Or in terms of arrays, I will have one reference
> array and several arrays of simulated signals. How can find the
> (non-negative) coefficients a_i for each simulated signal array? (All
> negative contributions should be discarded.)
>
> Is there anything like that in scipy (which I couldn't find)? Or any
> other code doing that?
>
> Else I could write it myself and contribute, but having some working
> code would be nice, of course.
>
> TIA
> Christian
>
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-- 
Peter N. Skomoroch
peter.skomoroch@gmail.com
http://www.datawrangling.com
http://del.icio.us/pskomoroch
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