[SciPy-user] NNLS in scipy
Sun Jun 15 14:07:23 CDT 2008
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.
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