[SciPy-User] using an optimizer/solver to solve f(x)=0

[Paweł Kwaśniewski]

If you do have a minimization problem, as it seems, you can try using
optimize. You can find pretty a good description of the available algorithms
here: http://docs.scipy.org/doc/scipy/reference/tutorial/optimize.html (if
you haven't found it already). If this doesn't work for some reason, you can
try PyMinuit (http://code.google.com/p/pyminuit/) - it worked for me. I can
also recommend the website of Douglas Applegate:
http://sites.google.com/site/applegatearchive/software/python-model-fittingHe
has there some nice wrap around PyMinuit functions, designed for
fitting,
but can be very helpful in understanding how it works.

Hope this can help.

2011/1/6 jordan <jordan.nickerson at gmail.com>

>
> I'm trying to solve an objective function to get an answer as close to zero
> as
> possible. However, the function is not terribly well behaved and takes 4
> parameters as inputs. So far I've been using fmin and returning the
> absolute
> value of the function to try to get close to zero.
>
> I was wondering if there is a better approach? I looked into solvers but it
> seems like they only solve for a univariate case, or they expect the
> function to
> return an array of the same dimension as that of the set of parameters.
>
> Thanks
> jordan
>
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-- 
Paweł
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