Oh yes, and something else about your benchmark : try to avoid using "rand" methods when you are doing one, especially when you test such low-level methods, because often the rand() method represents an important part of the time.
The best would be to compute all the random number you need in a first phase, then run %timeit on the add_edge part. Well, it probably will not reflect well on Sage because it should increase the differences between the libraries, but I think that it is very important in your benchmark, To give you an idea : sage: from numpy import random as rnd sage: sage: g = Graph(500) sage: def rand_entry(G): ....: ... n = G.order() ....: ... i = rnd.randint(0,n-1) ....: ... j = rnd.randint(0,n-1) ....: ... G.add_edge(i,j) ....: ... G.delete_edge(i,j) ....: sage: def just_rand(G): ....: ... n = G.order() ....: ... i = rnd.randint(0,n-1) ....: ... j = rnd.randint(0,n-1) ....: ... return i*j ....: sage: %timeit rand_entry(g) 625 loops, best of 3: 20.4 µs per loop sage: %timeit just_rand(g) 625 loops, best of 3: 4.93 µs per loop So 20% of the time used by this test method is actualy used by calls to "random()" :-) Nathann -- To post to this group, send email to sage-support@googlegroups.com To unsubscribe from this group, send email to sage-support+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sage-support URL: http://www.sagemath.org
