library("network")
set.seed(1)



# Various ways to initialize networks in statnet

net <- network.initialize(5)
net

nmat <- matrix(rbinom(25, 1, 0.5), nr = 5, nc = 5)
net <- network(nmat, loops = TRUE)
net

summary(net)

net <- as.network(nmat, loops = FALSE)
all(nmat == net[,])

net <- as.network(nmat, loops = TRUE)
all(nmat == net[,])

net <- network.initialize(5, loops = TRUE)
net[nmat>0] <- 1
all(nmat == net[,])

net[,] <- 0
net[,] <- nmat
all(nmat == net[,])


net[,] <- 0
network::add.edges(net, row(nmat)[nmat>0], col(nmat)[nmat>0])
all(nmat == net[,])

net[,] <- nmat[,]
all(nmat == net[,])

#diplay edgelist
as.matrix(net,matrix.type = "edgelist")

#Adding nodes and edges

net <- network.initialize(5)
network::add.edge(net, 2, 3)
net[,]

network::add.edges(net, c(3, 5), c(4, 4))
net[,]

net[,2] <- 1
net[,]

network::delete.vertices(net, 4)
net[,]

network::add.vertices(net, 2)
net[,]



#each edge can be thought of as a list made up of a vector
#of tail vertex IDs, a vector of head vertex IDs, and a vector of attributes. 
#The utility function get.edges retrieves edges in this form, 
#returning them as lists with elements 
#inl (tail), 
#outl (head)
#atl (attributes). get.edges allows for edges to be retrieved by endpoint(s)

?get.edges

network::get.edges(net, 1)
net[,]
network::get.edges(net, 2, neighborhood = "in")
get.edges(net, 1, alter = 2)
gplot(net)

get.neighborhood(net, 1)
get.neighborhood(net, 2, type = "in")

get.edgeIDs(net, 3, neighborhood = "out")

delete.edges(net, get.edgeIDs(net, 3, neighborhood = "out"))
net[,]  		      


#Other functions to test network structure

data("flo")

nflo <- network(flo, directed = FALSE)
nflo

is.adjacent(nflo, 9, 1)
is.adjacent(nflo, 9, 4)

has.loops(nflo)
is.bipartite(nflo)
is.directed(nflo)
is.hyper(nflo)
is.multiplex(nflo)

as.matrix(nflo, matrix.type = "edgelist")

plot(nflo, displaylabels = TRUE, boxed.labels = FALSE)
plot(nflo, displaylabels = TRUE, mode = "circle")


# create an hypergraph

hg_ex <- matrix(c(1,0,0, 1,0,1, 0,0,1, 0,0,1, 0,1,0, 0,1,1, 0,1,0), byrow = T, ncol=3)

p.names <- paste("v", 1:7)
rownames(hg_ex) <- p.names

a.names <- paste("e", 1:3)
colnames(hg_ex) <- a.names

HG <- network(hg_ex, matrix = "incidence", hyper = TRUE, directed = FALSE, loops = TRUE)

HG[,]

network::get.edges(HG, 1)

prova <- network.initialize(15, bipartite=10, directed=F)

bip <-network.initialize(5,bipartite=3)
bip[,1] <- 1
get.network.attribute(bip,'bipartite') # how many vertices in first mode?
add.vertices(bip,3,last.mode=FALSE)
get.network.attribute(bip,'bipartite')

?add.edge

library(statnet)
pp<- as.matrix(bip, matrix.type="bipartite")

pp <- as.edgelist.sna(bip, force.bipartite=TRUE)
pp


data("faux.magnolia.high")

fmh <- faux.magnolia.high

faux.magnolia.high

fmh %v% "Sex"

gplot(fmh)


#prova grafo slides 7 17 aprile 

x1=c(0, 1, 1, 0,0,0,0)

x2=c(1,0,0,1, 0, 0, 0)

x3=c(1,0,0,0,1,0,0)

x4=c(0,1,0,0,1,0,0)

x5=c(0,0,1, 1, 0, 1,1)

x6=c(0,0,0,0,1,0,1)

x7=c(0,0,0,0,1,1,0)

mm = matrix(c(x1,x2,x3,x4,x5,x6,x7), nrow=7)
gplot(mm)

bt <- betweenness(mm, gmode="graph", cmode="undirected")

?betweenness

star = network.initialize(10, directed=F)
?network.initialize
star[1,] <- 1 
gplot(star)

btstar <- betweenness(star, gmode="graph", cmode="undirected")

library(statnet)
gtrans(netgot[,])


save(enemy)