Hi Federico, Have you checked your gradients using finite differences in both cases?
Regards, James On 3 Oct 2013, at 20:27, Jaap Kroes <[email protected]> wrote: > Hi, > > Most likely there is a problem in the calculation of your gradients. > Did you perhaps forget to initialize them to zero before every update? > From the numbers the python gradient is very small on the second step > while the nlopt gradients look like the old ones + something small. > > Best, > Jaap > > 2013/10/3 federico vaggi <[email protected]>: >> Hi everyone, >> >> I've been using NLopt to estimate the parameters of a system of differential >> equations by minimizing the least squares between my simulations and a set >> of experimental data. >> >> The non-gradient based optimizations have worked very well. I started >> experimenting with using gradient based methods and estimating the jacobian >> from the sensitivity equations calculated by sundials, and I found that >> using the SciPy fmin_l_bfgs_b I'm able to obtain a local minima very >> quickly. All NLopt algorithms, however, quickly throw an NLopt error. >> >> The system I am working with is quite gnarly - some parameters are very, >> very sensitive, while others are completely robust. >> >> SciPy bfgs: >> >> http://pastie.org/8374252 >> >> NLopt bfgs: >> >> http://pastie.org/8374254 >> >> I've tried changing NLopt algorithms, but every single gradient based method >> I tried eventually throws an error. Any clue what might be causing it? I >> am happy to share the code, but this is a fairly large wrapper around SciPy >> and Assimulo ODEINT solvers, so posting a minimal example is not very easy. >> >> Federico >> >> _______________________________________________ >> NLopt-discuss mailing list >> [email protected] >> http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss >> > > _______________________________________________ > NLopt-discuss mailing list > [email protected] > http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss > _______________________________________________ NLopt-discuss mailing list [email protected] http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss
