Hi all,
I have run into a runtime/complexity question where I am wondering if
someone can give me insights into why this might happen.
I have conducted the following steps:
1.) Create some random network
2.) Calculate eigenvector centrality
3.) Sample 10% random nodes
4.) Filter graph by nodes
5.) Calculate eigenvector centrality on sample
I have observed that for the sample, the eigenvector centrality
calculation takes much longer, in some cases (dependent e.g., on block
structure) it takes way longer (like 30 times longer).
I am now trying to figure out why this is the case. I assume it has
something to do with the convergence which might be probably because
links are missing in the sample. If I do the same for e.g., PageRank the
difference is not that drastic (it still takes longer in the sample).
Does anyone have an idea what is going on here?
Thanks,
Philipp
_______________________________________________
graph-tool mailing list
[email protected]
https://lists.skewed.de/mailman/listinfo/graph-tool
