Also, it looks like the SymPy version of Tuples (if I am correct in what Sage's Tuples does) is buried in sympy.utilities.iterables:
In [1]: from sympy.utilities.iterables import variations In [2]: time len(variations((E, pi, sqrt(2)), 3, repetition=True)) CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s Wall time: 0.00 s Out[3]: 27 In [4]: %timeit len(variations((E, pi, sqrt(2)), 3, repetition=True)) 10000 loops, best of 3: 68.7 us per loop In [5]: %timeit len(variations((1, 2, 3), 3, repetition=True)) 10000 loops, best of 3: 57.8 us per loop In [6]: %timeit len(variations((S(1), S(2), S(3)), 3, repetition=True)) 10000 loops, best of 3: 71.4 us per loop I'm not sure if it is counted as implemented, as it is not imported into the global namespace with "from sympy import *", but the code is definitely there. It looks like we don't suffer from the slow down of Sage with non-integer objects. Aaron Meurer On Aug 17, 9:09 pm, "Aaron S. Meurer" <asmeu...@gmail.com> wrote: > Hi. You might look at SymPy's built in benchmarks (run ./bin/py.bench). > > As for factor, you might look at Mateusz's branch where he has the new > Polys module (http://github.com/mattpap/sympy-polys/commits/polys). > I ran the test in his branch and got: > > In [1]: time factor(x**20 - pi**5*y**20) > CPU times: user 0.23 s, sys: 0.00 s, total: 0.24 s > Wall time: 0.27 s > Out[2]: > ⎛ 4 4⎞ ⎛ 12 4 2 8 8 3 4 12 16 4 16⎞ > -⎝- x + π⋅y ⎠⋅⎝π⋅x ⋅y + π ⋅x ⋅y + π ⋅x > ⋅y + x + π ⋅y ⎠ > > So it is faster (considerably) than Sage, at least according that the > wiki you linked to. This isn't in SymPy yet, but it hopefully will > make it to the git trunk soon. > > Also, you might look into using a tool like py.bench instead of naive > clock deltas. > > As for the best thing to use for a benchmark, I think it should be > something that takes long enough to run that it has a low margin of > error, but is able to finish in all systems that you try it in. Also, > some tests will show you more of the speed differences of the > algorithm implemented (like probably the factor example), while others > will likely show you more the difference in what the engine is running > on (like Python vs. a C implementation). > > Aaron Meurer > On Aug 17, 2009, at 4:15 PM, fijal wrote: > > > > > > > Hi. > > > I've been looking for some sympy benchmarks as a potential target for > > pypy's jit. I've found this:http://wiki.sympy.org/wiki/Symbench > > > What's the reasonable small, yet telling something benchmark that > > makes > > sense? We're basically trying to collect some that are both simple and > > yet > > real-world enough. Any quick thoughts? > > > Cheers, > > fijal > > > PS. I really like the fact that sympy is pure python, that makes it a > > good > > target. --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "sympy" group. To post to this group, send email to sympy@googlegroups.com To unsubscribe from this group, send email to sympy+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sympy?hl=en -~----------~----~----~----~------~----~------~--~---
