#13730: Speed up some graph iterations
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Reporter: dcoudert | Owner: jason, ncohen, rlm
Type: enhancement | Status: needs_work
Priority: major | Milestone: sage-5.10
Component: graph theory | Resolution:
Keywords: | Work issues:
Report Upstream: N/A | Reviewers:
Authors: | Merged in:
Dependencies: | Stopgaps:
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Comment (by slani):
Replying to [comment:23 vdelecroix]:
> Replying to [comment:22 slani]:
> Hello,
>
> > I don't know, but I came to the conclusion that we have tow problems:
> > 1. conversion from vertex ints to vertex lables
>
> This should not slow down too much (not x4). It is a lookup in an array.
Did you make some timings to see whether this is slow ? Perhaps we have to
dig the way it is implemented.
>
> > 2. how to faster return vertex ints from data structure we have for
nbrs
>
> It might be a good idea to see whether iterator over int vertices are
faster compared to the labeled one.
>
> Other possibilities
>
> 3. There are 3 levels in a graph: the `GenericGraph` class, the
`backend` (stored at `my_graph._backend`) and then the datastructure
(stored at `my_graph._backend._cg` for c graphs or
`my_graph._backend._nxg` for networkx).
>
> 4. Possibly #14690 might be a good speedup (if it works one day ;-)
[[BR]]
I modified data structure for saving nbrs. I implemented linked list and
save all nbrs for vertex on one place in vertices (not on 16 different
places). Obvious this is nod good for adds and removes nbrs.
{{{
sage: %timeit E = [(u,v) for u in G for v in G.neighbor_iterator(u)]
625 loops, best of 3: 871 µs per loop
}}}
Very small improvements.
How can networkX data structure (python dict) return data so fast?
Best, [[BR]]
Uros
--
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/13730#comment:25>
Sage <http://www.sagemath.org>
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