On Sep 8, 6:19 pm, KvS <[email protected]> wrote: > Dear all, > > I am trying to implement a recursive algorithm that is rather complex, > in the sense that it uses a high number of variables and (elementary) > computations. The output in Sage looks fine but it gets quite slow, so > I am thinking of ways to speed it up. Given that it is mainly a lot of > looping and a lot of elementary computations, I would guess > translating it to Cython could help a lot. > > However I am afraid that doubles won't have enough precision to avoid > too much numerical noise in the end result of the algorithm. So I > would like to use a higher precision real number representation. The > question is whether this is possible, and if so what is a sensible > choice? Could/Should I use mpmath e.g. or rather something else? What > I need to be doing, next to elementary computations, is: > > - compute exponentials > - perform find_root's > - being able to store those real numbers in a few big Numpy-arrays. > > I am very grateful for any hint! > > Many thanks, Kees
Why don't using mpmath for the critical numerical steps? It supports the features you need, is quite efficient, and also has multi precision vectors and matrices. And after the problematic steps, getting back to numpy arrays isn't really a problem. If you really want to get out the every tiny bit of efficiency out of your code, then you have to stick to cython and mpfr. But I'm not sure if this is really necessary. greez maldun -- To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/sage-support URL: http://www.sagemath.org
