V(hipaa.tc)$color <- ifelse(hipaa.tc.l_clusters>0, "green", "yellow")
plot(hipaa.tc, main=paste(hipaa.tc.netname, "Laplace Spectral Clustering"), vertex.label=NA)
pci.tc.eigs <- Re(eigen(pci.tc.Lap)$vectors[,pci.tc.n-1])
pci.tc.eig_val <- eigen(pci.tc.Lap)$values[pci.tc.n-1]
names(pci.tc.eigs) <- names(V(pci.tc))
pci.tc.l_clusters <- ifelse(pci.tc.eigs>0,1,-1)
tc_clusters[[3,1]] <- pci.tc.l_clusters
V(pci.tc)$color <- ifelse(pci.tc.l_clusters>0, "green", "yellow")
plot(pci.tc, main=paste(pci.tc.netname, "Laplace Spectral Clustering"), vertex.label=NA)
### Clemente and Grassi
tc_clusters[[1,2]] <- ClustBCG(as.matrix(car.tc.adj), "directed")$totalCC
tc_clusters[[2,2]] <- ClustBCG(as.matrix(hipaa.tc.adj), "directed")$totalCC
tc_clusters[[3,2]] <- ClustBCG(as.matrix(pci.tc.adj), "directed")$totalCC
######################### Dominant Tree Centralities #########################
dtree_centralities <- matrix(list(), nrow=3, ncol=5)
rownames(dtree_centralities) <- c(car.netname, hipaa.netname, pci.netname)
colnames(dtree_centralities) <- c("Degree", "Katz", "Page Rank", "K-path", "Betweenness")
# Get basic network attributes
car.dtree.adj <- get.adjacency(car.dtree)
car.dtree.deg <- rowSums(as.matrix(car.dtree.adj)) # degree
car.dtree.n <- length(V(car.dtree))
hipaa.dtree.adj <- get.adjacency(hipaa.dtree)
hipaa.dtree.deg <- rowSums(as.matrix(hipaa.dtree.adj)) # degree
hipaa.dtree.n <- length(V(hipaa.dtree))
pci.dtree.adj <- get.adjacency(pci.dtree)
pci.dtree.deg <- rowSums(as.matrix(pci.dtree.adj)) # degree
pci.dtree.n <- length(V(pci.dtree))
### Degree
dtree_centralities[[1,1]] <- car.dtree.deg %>% sort(decreasing = T)
dtree_centralities[[2,1]] <- hipaa.dtree.deg %>% sort(decreasing = T)
dtree_centralities[[3,1]] <- pci.dtree.deg %>% sort(decreasing = T)
#### Katz
car.dtree.katz <- katz.cent(car.dtree)
dtree_centralities[[1,2]] <- car.dtree.katz[rowSums(apply(car.dtree.katz,2,is.nan))==0,] %>% sort(decreasing = T)
dtree_centralities[[2,2]] <- katz.cent(hipaa.dtree) %>% sort(decreasing = T)
dtree_centralities[[3,2]] <- katz.cent(pci.dtree) %>% sort(decreasing = T)
### Page Rank
dtree_centralities[[1,3]] <- page.rank(car.dtree)$vector %>% sort(decreasing = T)
dtree_centralities[[2,3]] <- page.rank(hipaa.dtree)$vector %>% sort(decreasing = T)
dtree_centralities[[3,3]] <- page.rank(pci.dtree)$vector %>% sort(decreasing = T)
### K-path
dtree_centralities[[1,4]] <- geokpath(car.dtree, V(car.dtree), "out") %>% sort(decreasing = T)
dtree_centralities[[2,4]] <- geokpath(hipaa.dtree, V(hipaa.dtree), "out") %>% sort(decreasing = T)
dtree_centralities[[3,4]] <- geokpath(pci.dtree, V(pci.dtree), "out") %>% sort(decreasing = T)
### Betweenness
dtree_centralities[[1,5]] <- betweenness(car.dtree, TRUE) %>% sort(decreasing = T)
dtree_centralities[[2,5]] <- betweenness(hipaa.dtree, TRUE) %>% sort(decreasing = T)
dtree_centralities[[3,5]] <- betweenness(pci.dtree, TRUE) %>% sort(decreasing = T)
########################## Dominant Tree Clustering ##########################
source("self_newman_mod.R")
dtree_clusters <- matrix(list(), nrow=3, ncol=2)
rownames(dtree_centralities) <- c(car.netname, hipaa.netname, pci.netname)
colnames(dtree_centralities) <- c("Laplace", "CG")
### Laplacian
car.dtree.Lap <- diag(car.dtree.deg) - car.dtree.adj # L = D-A
hipaa.dtree.Lap <- diag(hipaa.dtree.deg) - hipaa.dtree.adj
pci.dtree.Lap <- diag(pci.dtree.deg) - pci.dtree.adj
# get eigvals and vecs
car.dtree.eigs <- Re(eigen(car.dtree.Lap)$vectors[,car.dtree.n-1])
car.dtree.eig_val <- eigen(car.dtree.Lap)$values[car.dtree.n-1]
names(car.dtree.eigs) <- names(V(car.dtree))
car.dtree.l_clusters <- ifelse(car.dtree.eigs>0,1,-1)
dtree_clusters[[1,1]] <- car.dtree.l_clusters
V(car.dtree)$color <- ifelse(car.dtree.l_clusters>0, "green", "yellow")
plot(car.dtree, main=paste(car.dtree.netname, "Laplace Spectral Clustering"), vertex.label=NA)
hipaa.dtree.eigs <- Re(eigen(hipaa.dtree.Lap)$vectors[,hipaa.dtree.n-1])
hipaa.dtree.eig_val <- eigen(hipaa.dtree.Lap)$values[hipaa.dtree.n-1]
names(hipaa.dtree.eigs) <- names(V(hipaa.dtree))
hipaa.dtree.l_clusters <- ifelse(hipaa.dtree.eigs>0,1,-1)
dtree_clusters[[2,1]] <- hipaa.dtree.l_clusters
V(hipaa.dtree)$color <- ifelse(hipaa.dtree.l_clusters>0, "green", "yellow")
plot(hipaa.dtree, main=paste(hipaa.dtree.netname, "Laplace Spectral Clustering"), vertex.label=NA)
pci.dtree.eigs <- Re(eigen(pci.dtree.Lap)$vectors[,pci.dtree.n-1])
pci.dtree.eig_val <- eigen(pci.dtree.Lap)$values[pci.dtree.n-1]
names(pci.dtree.eigs) <- names(V(pci.dtree))
pci.dtree.l_clusters <- ifelse(pci.dtree.eigs>0,1,-1)
dtree_clusters[[3,1]] <- pci.dtree.l_clusters
V(pci.dtree)$color <- ifelse(pci.dtree.l_clusters>0, "green", "yellow")
plot(pci.dtree, main=paste(pci.dtree.netname, "Laplace Spectral Clustering"), vertex.label=NA)
### Clemente and Grassi
dtree_clusters[[1,2]] <- ClustBCG(as.matrix(car.dtree.adj), "directed")$totalCC
dtree_clusters[[2,2]] <- ClustBCG(as.matrix(hipaa.dtree.adj), "directed")$totalCC
dtree_clusters[[3,2]] <- ClustBCG(as.matrix(pci.dtree.adj), "directed")$totalCC
############################# Write Final Results #############################
write.table(base_centralities, file='results.csv')
write.table(tc_centralities, file='results.csv')
write.table(dtree_centralities, file='results.csv')
### Degree:
head(base_centralities[[1,1]], 15) #Car
head(tc_centralities[[1,1]],15)
head(dtree_centralities[[1,1]],15)
head(base_centralities[[2,1]], 15) #HIPAA
head(tc_centralities[[2,1]],15)
head(dtree_centralities[[2,1]],15)
head(base_centralities[[3,1]], 15) #PCI
head(tc_centralities[[3,1]],15)
head(dtree_centralities[[3,1]],15)
### Katz:
head(base_centralities[[1,2]], 15) #Car
head(tc_centralities[[1,2]],15)
head(dtree_centralities[[1,2]],15)
head(base_centralities[[2,2]], 15) #HIPAA
head(tc_centralities[[2,2]],15)
head(dtree_centralities[[2,2]],15)
head(base_centralities[[3,2]], 15) #PCI
head(tc_centralities[[3,2]],15)
head(dtree_centralities[[3,2]],15)
### Page Rank:
head(base_centralities[[1,3]], 15) #Car
head(tc_centralities[[1,3]],15)
head(dtree_centralities[[1,3]],15)
head(base_centralities[[2,3]], 15) #HIPAA
head(tc_centralities[[2,3]],15)
head(dtree_centralities[[2,3]],15)
head(base_centralities[[3,3]], 15) #PCI
head(tc_centralities[[3,3]],15)
head(dtree_centralities[[3,3]],15)
### K-Path:
head(base_centralities[[1,4]], 15) #Car
head(tc_centralities[[1,4]],15)
head(dtree_centralities[[1,4]],15)
head(base_centralities[[2,4]], 15) #HIPAA
head(tc_centralities[[2,4]],15)
head(dtree_centralities[[2,4]],15)
head(base_centralities[[3,4]], 15) #PCI
head(tc_centralities[[3,4]],15)
head(dtree_centralities[[3,4]],15)
### Betweenness:
head(base_centralities[[1,5]], 15) #Car
head(tc_centralities[[1,5]],15)
head(dtree_centralities[[1,5]],15)
head(base_centralities[[2,5]], 15) #HIPAA
head(tc_centralities[[2,5]],15)
head(dtree_centralities[[2,5]],15)
head(base_centralities[[3,5]], 15) #PCI
head(tc_centralities[[3,5]],15)
head(dtree_centralities[[3,5]],15)
### Laplacian:
head(base_clusters[[1,1]], 15) #Car
head(tc_centralities[[1,1]],15)
head(dtree_centralities[[1,1]],15)
head(base_clusters[[2,1]], 15) #HIPAA
head(tc_centralities[[2,1]],15)
head(dtree_centralities[[2,1]],15)
head(base_clusters[[3,1]], 15) #PCI
head(tc_centralities[[3,1]],15)
head(dtree_centralities[[3,1]],15)
### CG:
head(base_clusters[[1,2]], 15) #Car
head(tc_centralities[[1,2]],15)
head(dtree_centralities[[1,2]],15)
head(base_clusters[[2,2]], 15) #HIPAA
head(tc_centralities[[2,2]],15)
head(dtree_centralities[[2,2]],15)
head(base_clusters[[3,2]], 15) #PCI
head(tc_centralities[[3,2]],15)
head(dtree_centralities[[3,2]],15)
head(base_centralities[[2,2]], 15) #HIPAA
### Page Rank:
head(base_centralities[[1,3]], 15) #Car
### Page Rank:
as.matrix(head(base_centralities[[1,3]], 15) #Car)
)
### Page Rank:
as.matrix(head(base_centralities[[1,3]], 15))[2]
### Page Rank:
as.matrix(head(base_centralities[[1,3]], 15))
### Page Rank:
as.matrix(head(base_centralities[[1,3]], 15))[,1]
### Page Rank:
as.matrix(head(base_centralities[[1,3]], 15))[,2]
### Page Rank:
as.matrix(head(base_centralities[[1,3]], 15))[1,]
### Page Rank:
as.matrix(head(base_centralities[[1,3]], 15))[2,]
### Page Rank:
as.matrix(head(base_centralities[[1,3]], 15))
### Page Rank:
as.matrix(head(tc_centralities[[1,3]], 15))
### Page Rank:
as.matrix(head(base_centralities[[2,3]], 15))
### Page Rank:
as.matrix(head(tc_centralities[[2,3]], 15))
### Page Rank:
as.matrix(head(dtree_centralities[[2,3]], 15))
### Page Rank:
as.matrix(head(dtree_centralities[[3,3]], 15))
### Page Rank:
as.matrix(head(tc_centralities[[3,3]], 15))
### Page Rank:
as.matrix(head(base_centralities[[3,3]], 15))
head(tc_centralities[[1,4]],15)
### Page Rank:
as.matrix(as.matrix(head(base_centralities[[3,3]], 15)))
as.matrix(head(tc_centralities[[1,4]],15))
as.matrix(head(base_centralities[[2,4]],15))
as.matrix(head(tc_centralities[[2,4]],15))
as.matrix(head(dtree_centralities[[2,4]],15))
as.matrix(head(base_centralities[[3,4]],15))
as.matrix(head(tc_centralities[[3,4]],15))
as.matrix(head(dtree_centralities[[3,4]],15))
as.matrix(head(base_centralities[[1,5]], 15))
as.matrix(head(tc_centralities[[1,5]], 15))
as.matrix(head(dtree_centralities[[1,5]], 15))
as.matrix(head(dtree_centralities[[2,5]], 15))
as.matrix(head(tc_centralities[[2,5]], 15))
as.matrix(head(base_centralities[[2,5]], 15))
as.matrix(head(base_centralities[[3,5]], 15))
as.matrix(head(base_centralities[[2,5]], 15))
as.matrix(head(tc_centralities[[3,5]], 15))
as.matrix(head(dtree_centralities[[3,5]], 15))
edge_connectivity(car)
edge_connectivity(hipaa)
edge_connectivity(pci)
edge_connectivity(car, "0", "2490")
Vcount(car)
ecount(car)
vcount(car)
ecount(hipaa)
vcount(hipaa)
vcount(pci)
ecount(pci\)
ecount(pci)
mean(base_centralities[[1,1]])
mean(base_centralities[[1,1]])/vcount(car)
100*mean(base_centralities[[1,1]])/vcount(car)
100*mean(base_centralities[[2,1]])/vcount(hipaa)
100*mean(base_centralities[[3,1]])/vcount(pci)
katzcent(car,,0.9)
katzcent(car,,0.1)
as.matrix(head(katzcent(car,,0.1) %>% sort(decreasing=T), 15))
as.matrix(head(katzcent(car.tc,,0.1) %>% sort(decreasing=T), 15))
as.matrix(head(katzcent(car.dtree,,0.1) %>% sort(decreasing=T), 15))
as.matrix(head(katzcent(car.dtree,,0.1) %>% sort(decreasing=T), 45))
as.matrix(head(katzcent(hipaa,,0.1) %>% sort(decreasing=T), 15))
as.matrix(head(Re(katzcent(hipaa,,0.1)) %>% sort(decreasing=T), 15))
katzcent(hipaa,,0.1)
as.matrix(head(katzcent(pci,,0.1) %>% sort(decreasing=T), 15))
katzcent(pci,,0.1)
katz.cent(pci)
katz.cent(pci) %>% sort(decreasing = %)
katz.cent(pci) %>% sort(decreasing = T)
head(base_centralities[[2,2]], 15) #HIPAA
base_centralities[[2,2]]
order(base_centralities[[2,2]],decreasing=T)
order(tc_centralities[[2,2]],decreasing=T)
tc_centralities[[2,2]]
katz.cent(pci)
order(katz.cent(pci))
sort(katz.cent(pci))[60]
sort(katz.cent(pci))[47]
sort(katz.cent(pci))[61]
sort(katz.cent(pci))[56]
sort(katz.cent(pci))[54]
sort(katz.cent(pci))[58]
sort(katz.cent(pci))[53]
sort(katz.cent(pci))[57]
sort(katz.cent(pci))[45]
sort(katz.cent(pci))[44]
sort(katz.cent(pci))[32]
sort(katz.cent(pci))
order(katz.pci, decreasing=T)
order(katz.cent(pci), decreasing=T)
head(order(katz.cent(pci), decreasing=T), 15)
katz.cent(pci)[1]
katz.cent(pci)[2]
katz.cent(pci)[5]
katz.cent(pci)[12]
katz.cent(pci)[23]
katz.cent(pci)[4]
katz.cent(pci)[11]
katz.cent(pci)[22]
katz.cent(pci)[36]
katz.cent(pci)[3]
katz.cent(pci)[9]
katz.cent(pci)[20]
katz.cent(pci)[34]
katz.cent(pci)[39]
katz.cent(pci)[26]
order(katz.cent(pci.tc), decreasing=T)
order(katz.cent(pci.tc), decreasing=T) %>% sort()
order(katz.cent(pci.tc), decreasing=T) %>% sort(katz.cent(pci.tc),decreasing=T)[]
order(katz.cent(pci.tc), decreasing=T) %>%katz.cent[]
order(katz.cent(pci.tc), decreasing=T) %>%katz.cent(pci.tc)[]
order(katz.cent(pci.tc), decreasing=T)
katz.cent(pci.tc)[0]
katz.cent(pci.tc)[1]
katz.cent(pci.tc)[2]
katz.cent(pci.tc)[6]
katz.cent(pci.tc)[5]
katz.cent(pci.tc)[12]
katz.cent(pci.tc)[23]
katz.cent(pci.tc)[3]
katz.cent(pci.tc)[4]
katz.cent(pci.tc)[9]
katz.cent(pci.tc)[20]
katz.cent(pci.tc)[34]
katz.cent(pci.tc)[11]
katz.cent(pci.tc)[22]
katz.cent(pci.tc)[36]
katz.cent(pci.tc)[8]
katz.cent(pci.tc)[39]
order(katz.cent(pci.dtree), decreasing=T
)
order(katz.cent(pci.dtree), decreasing=T)
order(katz.cent(pci.tc), decreasing=T)
order(katz.cent(pci.dtree), decreasing=T)
katz.cent(pci.dtree)
katzcent(pci.dtree)
katzcent(pci.dtree,,0.1)
katzcent(pci.dtree,,0.9)
katzcent(pci.dtree,,0.2)
katzcent(pci.dtree,,0.1)
katz.cent(pci.dtree)
katz.cent.adj
pci.dtree.adj
eigen(pci.dtree.adj)$values[1]
katz.cent(pci.dtree, 0.9)
katz.cent(pci.tc, 0.9)
katz.cent(pci.tc, 0.1)
katz.cent(pci.dtree, 0.1)
sort(katz.cent(pci.dtree, 0.1), decreasing=T)
sort(katz.cent(pci.dtree, 0.1), decreasing=T, index.return=T)
sort(katz.cent(pci.dtree, 0.1), decreasing=T, index.return=T)$x
sort(katz.cent(pci.dtree, 0.1), decreasing=T, index.return=T)$ix
sort(katz.cent(pci.dtree, 0.1), decreasing=T, index.return=TRUE)
sort(katz.cent(pci.dtree, 0.1), decreasing=T, index.return=TRUE)$x
sort.index(katz.cent(pci.dtree,0.1),decreasing=T)
tmp <- katz.cent(pci.dtree,0.1)
sort(tmp, decreasing=T, index.return=T)
tmp$x
tmp2 <- sort(tmp, decreasing=T, index.return=T)
tmp2
tmp2$x
tmp2$ix
tmp2[1]
tmp2 <- sort(tmp, decreasing=T, index.return=TRUE)
tmp2$ix
tmp2
tmp2 <- sort(tmp, index.return=TRUE, decreasing=T)
tmp21
tmp2
tmp2$ix
tmp2 <- sort(tmp, index.return=TRUE)
tmp2
tmp2$ix
tmp2$x
tmp <- matrix(list(), nrow=vcount(car), ncol=2)
tmp[,1] <- car.katz %>% sort(,decreasing=T)
tmp[,1] <- car.katz %>% sort(decreasing=T)
tmp[1] <- car.katz %>% sort(decreasing=T)
tmp[[,1]] <- car.katz %>% sort(decreasing=T)
nodes <- car.katz %>% sort(decreasing=T)
car.katz
car.katz(car,.9)
car.katz<- katz.cent(car,.9)
car.katz[2488]
car.katz[1]
car.katz[5]
car.katz
is.na(eigen(car.adj)$values[1])
eigen(car.adj)$values[1]
eigen(car.adj)$values[1] == 0
############################# Base Centralities #############################
source("centralities.R")
############################# Base Centralities #############################
source("centralities.R")
katz.cent(car)
############################# Base Centralities #############################
source("centralities.R")
katz.cent(car)
#### Katz
car.katz <- katz.cent(car)
nodes <- car.katz %>% sort(decreasing=T)
vals <- car.katz %>% order(decreasing=T)
head(nodes,15)
as.matrix(head(nodes,15))
as.matrix(head(nodes,15), head(vals, 15))
as.matrix(head(vals,15))
as.matrix(head(vals,15)-1)
as.data.frame(head(vals,15)-1, head(nodes,15))
as.data.frame(head(vals,15), head(nodes,15))
nodes <- car.katz %>% sort(decreasing=T)
nodes <- car.katz %>% order(decreasing=T)
vals <- car.katz %>% sort(decreasing=T)
head(nodes,15)
head(vals,15)
as.data.frame(head(nodes,15), head(vals, 15))
nodes <- car.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)
nodes
nodes <- car.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
nodes
vals <- head(vals, 15)
as.data.frame(nodes, vals)
as.matrix(nodes, vals)
print(cbind(nodes, vals))
print(cbind(nodes, vals))$nodes
tmp <- (cbind(nodes, vals))
tmp
prmatrix(tmp)
nodes
as.matrix(nodes)
as.matrix(nodes)[1]
as.matrix(nodes)[,1]
vals
as.matrix(vals)
#### Katz
car.katz <- katz.cent(car)
nodes <- car.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- car.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
nodes
vals
as.matrix(vals)
############################# Base Centralities #############################
source("centralities.R")
#### Katz
car.katz <- katz.cent(car)
nodes <- car.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- car.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
nodes
vals
as.matrix(nodes)
as.matrix(vals)
hipaa.katz <- katz.cent(hipaa)
nodes <- hipaa.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- hipaa.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
as.matrix(vals)
pci.katz <- katz.cent(pci)
nodes <- pci.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- pci.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
as.matrix(vals)
car.tc.katz <- katz.cent(car.tc)
nodes <- car.tc.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- car.tc.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
as.matrix(vals)
hipaa.tc.katz <- katz.cent(hipaa.tc)
plot(pci.dtree)
V(pci.dtree)$color <- "yellow"
plot(pci.dtree)
hipaa.tc.katz <- katz.cent(hipaa.tc)
nodes <- hipaa.tc.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- hipaa.tc.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
as.matrix(vals)
pci.tc.katz <- katz.cent(pci.tc)
nodes <- pci.tc.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- pci.tc.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
as.matrix(vals)
car.dtree.katz <- katz.cent(car.dtree)
nodes <- car.dtree.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- car.dtree.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
as.matrix(vals)
hipaa.dtree.katz <- katz.cent(hipaa.dtree)
nodes <- hipaa.dtree.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- hipaa.dtree.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
as.matrix(vals)
pci.dtree.katz <- katz.cent(pci.dtree)
nodes <- pci.dtree.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
nodes <- head(nodes, 15)-1
vals <- pci.dtree.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
nodes <- pci.dtree.katz %>% order(decreasing=T)
pci.dtree.katz <- katz.cent(pci.dtree)
nodes <- pci.dtree.katz %>% order(decreasing=T)
nodes <- head(nodes, 15)-1
vals <- pci.dtree.katz %>% sort(decreasing=T)
vals <- head(vals, 15)
as.matrix(nodes)
as.matrix(vals)
plot(pci)
V(pci)$color <- "yellow"
plot(pci)
plot(pci.tc)
V(pci.tc)$color <- "yellow"
plot(pci.tc)
plot(dtree_clusters[[1,2]])
base_clusters[[1,2]]
which(base_clusters[[1,2]] > 1)
which(base_clusters[[1,2]] > 0)
which(base_clusters[[2,2]] > 0)
which(base_clusters[[3,2]] > 0)
plot(base_clusters[[3,2]]
)
pci.dtree.deg