On May 31, 2011, at 11:11 AM, Ronan Lamy wrote: > Le mardi 31 mai 2011 à 09:43 -0700, Vinzent Steinberg a écrit : >> On May 30, 9:52 pm, Mateusz Paprocki <matt...@gmail.com> wrote: >>> That could work: >>> >>> ZZ.sum([1, 2, 3]) -> sum([1, 2, 3]) >>> RR.sum([1.0, 2.0]) -> mpmath.fsum([1.0, 2.0]) >>> EX.sum([x, y, z]) -> Add(*[x, y, z]) >>> >>> etc. >> >> This is exactly what I have been thinking of. > > But do we really need lots of different sum() functions? Is there a > difference between ZZ.sum([1, 2, 3]) and EX.sum([1, 2, 3])?
Yes. You can sum integers perfectly efficiently just by passing them to the built-in sum() (also remember that ZZ(1) != S(1) in general because of the ground types, but EX(1) == S(1) always). But something like Add(*(x, -x, x, x, -x)) is almost two times faster than sum((x, -x, x, x, -x)): In [1]: Add(*(x, -x, x, x, -x)) Out[1]: x In [2]: %timeit Add(*(x, -x, x, x, -x)) 1000 loops, best of 3: 170 us per loop In [3]: sum((x, -x, x, x, -x)) Out[3]: x In [4]: %timeit sum((x, -x, x, x, -x)) 1000 loops, best of 3: 313 us per loop In [16]: b = map(S, range(100)) In [24]: %timeit Add(*b) 1000 loops, best of 3: 546 us per loop In [25]: %timeit sum(b) 1000 loops, best of 3: 268 us per loop (all run without the cache, as suggested above). Note that [16] ensures that sum(b) goes through Add. Otherwise, you get In [26]: %timeit Add(*range(100)) 1000 loops, best of 3: 1.45 ms per loop In [27]: %timeit sum(range(100)) 100000 loops, best of 3: 2.7 us per loop which just proves what we already know, which is that Python ints are (apparently 10x) faster than SymPy Integers. Aaron Meurer -- 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.
