Re: [igraph] Running time

[Tamas Nepusz]

Dear Albert,

fastgreedy.community() returns a dendrogram, not a membership vector like 
spinglass.community, so com$membership is NULL, that's why the code does not 
work for you. After executing fastgreedy.community, the result will have two 
parts: com$merges is a merge matrix that encodes the dendrogram and 
com$modularity stores the modularity scores after each merge. First, you have 
to figure out where the maximal modularity is reached 
(which.max(com$modularity)) and pass that to community.to.membership to perform 
the merges in the dendrogram and obtain the membership vector. See the 
following wiki page for examples:

http://igraph.wikidot.com/community-detection-in-r#toc3

-- 
Tamas

On 2010.07.30., at 18:09, Soós Albert wrote:

> Hello!
> 
> Thanks for the fast reply. I have another question, how can i draw the result 
> of a clustering? I found an example int he tutorial:
> g <- graph.full(5) %du% graph.full(5) %du% graph.full(5)
> g <- add.edges(g, c(0,5, 0,10, 5,10))
> com <- spinglass.community(g, spins=5)
> V(g)$color <- com$membership+1
> g <- set.graph.attribute(g, "layout", layout.kamada.kawai(g))
> plot(g, vertex.label.dist=1.5)
> 
> I read my input graphs, and i use the fastgreedy or the edge betweenness 
> algorithm so i modified the code:
> 
> graph<- read.graph(file=C:/g, format=”edgelist”, directed=FALSE)
> com <- fastgreedy.community(graph, merges=TRUE, modularity=TRUE, weights=NULL)
> V(graph)$color <- com$membership+1
> graph <- set.graph.attribute(graph, "layout", layout.kamada.kawai(graph))
> plot(graph, vertex.label.dist=1.5)
> It draws the graph with the given layout, but it doesn’t color the 
> communities.
> 
> Albert  
> 
> 
> 
> -- Eredeti üzenet --
> Feladó: Tamas Nepusz <address@hidden>
> Címzett: Help for igraph users <address@hidden>
> Elküldve: 2010. július 30. 14:21
> Tárgy : Re: [igraph] Running time
> 
> 
> Hi Albert,
> 
> > Hello! If i run a clustering algorithm in R, how can i get the
> > running time?
> Use system.time, e.g.:
> 
> > system.time(fastgreedy.community(graph))
> 
> 
> > I tried to run the CNM algorithm, and i got this error message: At
> > fast_community.c:525 : fast greedy community detection works for
> > undirected graphs only, Unimplemented function
> As the message says above, this algorithm works for undirected graphs
> only, and your graph is directed. Please convert it to an undirected one
> first using to.undirected(). If you load your graph from an external
> file, the loader function might also have a directed=... parameter where
> you can explicitly specify that you want the graph to be undirected.
> (This works only for formats such as edgelist, NCOL and LGL where the
> file itself does not contain whether the graph is directed or
> undirected).
> 
> -- 
> Tamas
> 
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