library("network")
set.seed(1702)

data("flo")
data("emon")

net <- network.initialize(5)
net

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

summary(net)

all(nmat == net[,])

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

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

nflo[9,]
nflo[9,1]
nflo[9,4]

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

network.size(nflo)
network.edgecount(nflo)
network.density(nflo)
has.loops(nflo)
is.bipartite(nflo)
is.directed(nflo)
is.hyper(nflo)
is.multiplex(nflo)
as.sociomatrix(nflo)

all(nflo[,] == as.sociomatrix(nlflo))
all(as.matrix(nflo) == as.sociomatrix(nflo))
as.matrix(nflo,matrix.type = "edgelist")

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

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

net[,] <- 0
for(i in 1:5)
  for(j in 1:5)
    if(nmat[i,j])
      net[i,j] <- 1
all(nmat == net[,])

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

net[,] <- as.numeric(nmat[,])
all(nmat == net[,])

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

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

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

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

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

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

net[2,3] <- 0
net[2,3] == 0

delete.edges(net, get.edgeIDs(net, 2, neighborhood = "in"))
net[,]  		      

net <- network.initialize(5)
set.network.attribute(net, "boo", 1:10)
net %n% "hoo" <- letters[1:7]

list.network.attributes(net)
get.network.attribute(net, "boo")
net %n% "hoo"
delete.network.attribute(net, "boo")
list.network.attributes(net)
set.vertex.attribute(net, "boo", 1:5)
net %v% "hoo" <- letters[1:5]
list.vertex.attributes(net)
get.vertex.attribute(net, "boo")
net %v% "hoo"
delete.vertex.attribute(net, "boo")
list.vertex.attributes(net)

net <- network(nmat)
set.edge.attribute(net, "boo", sum(nmat):1)
set.edge.value(net, "hoo", matrix(1:25, 5, 5))
net %e% "woo" <- matrix(rnorm(25), 5, 5)
net[,, names.eval = "zoo"] <- nmat * 6
list.edge.attributes(net)

get.edge.attribute(get.edges(net, 1), "boo")
get.edge.value(net, "hoo")
net %e% "woo"
as.sociomatrix(net, "zoo")
delete.edge.attribute(net, "boo")
list.edge.attributes(net)

MtSHloc <- emon$MtStHelens %v% "Location"
MtSHimat <- cbind(MtSHloc %in% c("L", "B"), MtSHloc %in% c("NL", "B"))
MtSHbyloc <- network(MtSHimat, matrix = "incidence", hyper = TRUE, 
  directed = FALSE, loops = TRUE)
MtSHbyloc %v% "vertex.names" <- emon$MtStHelens %v% "vertex.names"
MtSHbyloc

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

plot(emon$MtSi)

library("sna")
network.layout.degree <- function(d, layout.par){
    id <- degree(d, cmode = "indegree")
    od <- degree(d, cmode = "outdegree")
    cbind(id, od)
  }
plot(emon$MtStHelens, mode = "degree", displaylabels = TRUE, 
  boxed.labels = FALSE, suppress.axes = FALSE, label.cex = 0.5,
  xlab = "Indegree", ylab = "Outdegree", label.col = 3)

plot(MtSHbyloc, displaylabels = TRUE, label = 
  c(network.vertex.names(MtSHbyloc), "Local", "Non-Local"), 
  boxed.labels = FALSE, label.cex = rep(c(0.5, 1), each = c(27, 2)),
  label.col = rep(c(3, 4), each = c(27, 2)), vertex.col = rep(c(2, 5),
  each = c(27, 2)))

rnbernexp <- function(n, nv, p = 0.5, onset.hazard = 1, 
  termination.hazard = 1){
    nets <- list()
    for(i in 1:n)
      nets[[i]] <- .Call("rnbernexp_R", network.initialize(nv, 
	directed = FALSE), p, onset.hazard, termination.hazard, 
	PACKAGE = "networkapi.example")
    if(i > 1)
      nets
    else
      nets[[1]]
  }