On Wed, Apr 23, 2014 at 10:02 AM, Aaron Meurer <[email protected]> wrote: > Just use x = Poly(x**x). That's the dense representation. No idea how > to do this with ring(). Mateusz will have to show us. But the > polynomials you're creating in this benchmark are univariate and dense > anyway.
We should also be plotting the dependence on N, as different data structures have different behaviors, for example hash table (unordered_map, or dict in Python) vs. red-black trees (std::map). Ultimately though, and that's the main issue, instead of concentrating on these artificial benchmarks, I am concentrating on real world applications, thus PyDy. If PyDy could be done with sympy.polys, then that would be good, but I am afraid it can't, as it has stuff like sin, cos, unevaluated functions like f1(t), and so on. Ondrej -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/CADDwiVBUr%3DTGqE8OdfUQSnPqP-6Udb_98iuP2iXpCYyNwMMhKw%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
