2010/11/22 Gael Varoquaux <gael.varoqu...@normalesup.org>: > On Mon, Nov 22, 2010 at 11:12:26PM +0100, Matthieu Brucher wrote: >> It seems that a simplex is what you need. It uses the barycenter (more >> or less) to find a new point in the simplex. And it works well only in >> convex functions (but in fact almost all functions have an issue with >> this :D) > > One last question, now that I know that what I am looking for is a > simplex algorithm (it indeed corresponds to what I was after), is there a > reason not to use optimize.fmin? It implements a Nelder-Mead. I must > admit that I don't see how I can use it to specify the convex hull of the > parameters in which it operates, or restrict it to work only on integers, > which are two things that I may want to do.
optimize.fmin can be enough, I don't know it well enough. Nelder-Mead is not a constrained optimization algorithm, so you can't specify an outer hull. As for the integer part, I don't know if optimize.fmin is type consistent, I don't know if scikits.optimization is either, but I can check it. It should, as there is nothing impeding it. Matthieu -- Information System Engineer, Ph.D. Blog: http://matt.eifelle.com LinkedIn: http://www.linkedin.com/in/matthieubrucher _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
