Hi all,
I used cluster_leading_eigen() to generate a community object, and then used cut_at() in order to find the cluster assignment under specified number of communities.
The cut_at() worked quite well when I use other algorithms like walktrap and edgebetweenness in igraph. But for leading eigenvector method when I use cut_at, and specify the number of community to be 10 (which is larger than the optimal number of clusters the cluster_leading_eigen function provides), it gives me a warning that
"In cut_at(tempLE, no = 10) : Cannot have that few communities".
Below please see my codes: Y is an adajacency matrix.
diag(Y)=0
n=dim(Y)[1]
g1=graph.adjacency(Y)
g2=as.undirected(g1)
tempLE=cluster_leading_eigen(g2)
cut_at(tempLE,no=10)
In my initial investigation, I found that the number of rows the merges(tempLE) provides is only 3, while for walktrap or edgebetweenness method, merges() yields an n by 2 matrix. I think the reason I have that warning is because merges(tempLE) has too few rows, but I don't know why?
Since leading eigenvector is a hiearchical method, the cut_at function should work for it. Anyone has any thoughts on it?
Thanks,
Qiwen