Hi Tiago and the list,



my algorithm is still _infeasibly_ slow and > 90 % of the run-time results from shortest_path().


Do you have any idea on how this could be sped up?


I have the graph G, the set of all nodes V and a sub-set B ⊂ V.


I want to calculate or approximate the mean shortest distance between all pairs V\B x V\B but on the complete graph - or in other words, calculate the mean of all pairs shortest distance ( mean(shortest_distance()) ) but exclude n∈B from being source or target.

Sub-sampling would be okay as well.


I currently don't see a way to do this fast with graph-tool besides writing a custom function but that probably exceeds my capacities. Am I missing something? Do you have any ideas?


Ideal would be something like a multi-threaded shortest_distance(g=G, source=V\B, target=V\B, weights=G.edge_properties['weight'], samples=N) with N pairs random sub-sampling and source / target being lists.



Thanks a ton!

Stephan

Von: Monecke, Stephan <stephan.monecke@ds.mpg.de>
Gesendet: Donnerstag, 18. November 2021 14:59
An: Main discussion list for the graph-tool project
Betreff: [graph-tool] Re: All Pairs Shortest Path with limitations
 
This works like a charm!

With it, I'm down to 228 ms ± 1.31 ms from 3.6 s ( 82.9 ms ± 2.45 ms for shortest_distance(G) ).

It's still very very expensive as it's 2.75 times APSP but approaching reasonability. The costly remaining part is the manual B x B.*

I tried to speed it up by the approximation to limit G to B since I know that B is connected but graph-tool segfaults right away (I wrote another ticket for that). :/

If anyone else has any ideas on how to speed this up, I'd be very grateful!


Cheers,
Stephan

- - - o - - -

*Since  the graph is directed, we have the following: Say V is the set of all vertices and B a subset of V I want to exclude as sources / targets from APSP. Then the set of points is
(V\B) x (V\B) = [ (V x V) \ [ (V x B) + (B x V) ] ] U (B x B).

Or in graph-tool terms:
 - (V x V): shortest_distance(G)
 - (B x V): shortest_distance(G, b, _) for b in B
 - (V x B): shortest_distance(GraphView(G, reversed=True), b, _) for b in B
 - (B x B): shortest_distance(G, u, v) for u,v in B x B




Von: Stephan Monecke <smoneck@ds.mpg.de>
Gesendet: Mittwoch, 17. November 2021 20:24
An: Main discussion list for the graph-tool project
Betreff: [graph-tool] Re: All Pairs Shortest Path with limitations
   
🥳 I didn't know that existed!

Thanks a ton, I'm really looking forward to test it out tomorrow!

Cheers,
Stephan
--
Sent from my mobile device. Please excuse my brevity.

Am 17. November 2021 19:27:37 MEZ schrieb Tiago de Paula Peixoto <tiago@skewed.de>:
>Am 17.11.21 um 19:22 schrieb Monecke, Stephan:
>> The main reason is that shortest_distance() has a "single source, all targets" mode but no "single target, all sources" mode (the reverse) - as soon as "source" is empty, it defaults to APSP, neglecting "target".
>>
>
>Of course it does. Just reverse the graph with:
>
>     GraphView(g, reversed=True)
>
>
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