#Create some random graphs
g<-rgraph(10,20,tprob=c(rbeta(10,15,2),rbeta(10,2,15)))
#Find the Hamming distances between them
g.h<-hdist(g)
#Cluster the graphs via their Hamming distances
g.c<-hclust(as.dist(g.h))
#Now display boxplots of density by cluster for a two cluster solution
gclust.boxstats(g.c,2,gden(g))
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