speedup add_simplices_from #223
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As a result, S = xgi.SimplicialComplex()
S.add_nodes_from(nodes) # instantaneous
S.add_simplices_from(edges) # 7 s for 18624 edges
S.add_simplices_from(triangles) # 2 min for 61642 triangles |
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Removed unnecessary generator expression in Timings, wrt to previous speedup. For S = xgi.SimplicialComplex()
simplices = [{0, 1, 2, 3}, {4}, {5, 6}, {6, 7, 8}]%timeit S.add_simplices_from(simplices, max_order=2)
# old -> 7.45 µs ± 10.9 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)
# new -> 4.72 µs ± 16.9 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)%timeit xgi.random_simplicial_complex(250, [0.1, 0.001])
# old -> 2.92 s ± 65.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
# new -> 1.72 s ± 42.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)%timeit S.add_simplices_from(triangles) # 61712 triangles
# old -> 2min 20s ± 331 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
# new -> 1min 17s ± 801 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)So we get an additional 2x speedup (especially when adding more simplices). |
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add_simplices_fromis slow, see #221. Profiling showed about 90% of the time is spent in the line checking existence of the simplex:has_simplex()now access members throughS._edgerather thanS.edges.members(s)which is significantly faster (see #221 for timings).Here, adding 100 triangles seems about 10x faster:
The
add_simplices_fromcan probably be improved even more, by rewriting it it without recursion for example. I have written a version but not pushed it because the seped improvement seems negligible in my case (it might not be with larger simplices). Also, it modifies the method much more, so has a larger chance of new bugs. And it changes the order in which simplices are added, so tests would need to be udpated. I would start with this minimal update at first, and maybe use the other version for a second step.