Hi,

OK. Thank you!

On Wed, Feb 20, 2013 at 1:19 PM, Tamás Nepusz <[email protected]> wrote:

> Hi,
>
> So I've checked our implementation of community_label_propagation() and it
> is indeed quadratic, not linear. The reason is that we are using a dense
> vector to count the number of occurrences of labels in the neighborhood of
> a node, and clearing this vector takes O(n) time, while it would be O(1)
> with a proper sparse vector. I will come up with a better implementation
> soon(ish).
>
> --
> T.
>
> On 14 Feb 2013, at 00:44, Zhige Xin <[email protected]> wrote:
>
> > Hi dear all,
> >
> > I have tested two community detection methods for some data sets. One is
> community_multilevel() and
> >
> > the other one is community_label_propagation(). The results surprised me
> because the LPA is very slower
> >
> > than the multilevel algorithm but theoretically the LPA is superior
> since it is linear. I do not get it.
> >
> > The following is my testing results:
> >
> > data set:         Internet(nodes:22963,edges:48436)
> collaboration(40421,175692)
> > Multilevel:       0.5454 seconds
>  2.3077 seconds
> > LPA:               29.4948 seconds
>  184.7579 seconds
> >
> > BTW, all the data sets are gml file format and can be downloaded from
> Mark Newman's homepage.
> >
> > And the following is my testing platform:
> >
> > Cpu: intel core2    1.7 GHz
> > Memory: 2GB
> > Hard drive: 320GB 5400rpm
> > OS: Linux Mint 14
> > Language: python 2.7
> > Library: igraph
> >
> > Thanks!
> >
> >
> >
> >
> > Isaiah
> >
> > _______________________________________________
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> > [email protected]
> > https://lists.nongnu.org/mailman/listinfo/igraph-help
>
>
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