library("igraph")
library(gplots)
#Zadanie 2
setwd("E:/R/lab3")
#graph <- read.graph("reachability.txt", format="edgelist")
df <- read.table("reachability.txt", sep = " ", header = FALSE)
graph<-graph.data.frame(df)
#plot(graph)

#Wznaczyc srednice sieci i srednia najkrotsza sciezke dla grafow nieskierowanych

srednica_gns <- diameter(graph, directed = F, weights = NA)

#Najkrotsze sciezki
x1 <- shortest.paths(graph)
y2 <- shortest.paths(graph, 1, 10)
c1 <- average.path.length(graph)
#path.length.hist(graph)


#Wyznaczyc srednice sieci i srednia najkrotsza sciezke dla grafow skierowanych

srednica_gs <- diameter(graph, directed = T, weights = NA)
sredbuca_gs2 <- get.diameter(graph, directed = TRUE)
x <- shortest.paths(graph, mode = "out")
y <- shortest.paths(graph, mode = "in")
z <- shortest.paths(graph, mode = "all")
shortest.paths(graph, 8, 10, mode="out")
c <- average.path.length(graph, directed = TRUE)
w <- shortest.paths(graph, 27, 304, mode="out")

#Wyznaczyc degree, between, closeness
#degree
d<-degree(graph, mode="all")
dsort <- tail(sort(d), 5)
plot(dsort)
plot(d, main="Degree")
rozklad_degree_node <- degree(graph, mode="all")
plot(degree.distribution(graph, cumulative = T), pch=20, xlab="degree", ylab="cumulative frequency", type="l", main="Rozklad Stopni wierzcholkow")

#Closeness dla grafów skierowanych i wazonych
o <- closeness(graph)
op <- closeness(graph, vids=c("1","2"))
close <- closeness(graph ,normalized = TRUE,mode="all")
dsort2 <- tail(sort(close), 5)
plot(close, main="Closeness")

#Between
between <- betweenness(graph)
dsort3 <- tail(sort(between), 5)
plot(between, main="Betweenness")

#top5 wspolne wierzcholki
print(names(dsort))
print(names(dsort2))
print(names(dsort3))

names_nodes = names(dsort)
M <- matrix(c(0:0), nrow = 5, ncol = 5)
for (i in 1:5){
  this_node = as.numeric(names_nodes[i])
  for (j in 1:5){
    test_against = as.numeric(names_nodes[j])
    if (i != j){
      M[i, j] = shortest.paths(graph, this_node, test_against)
    }
  }
}

names_nodes = names(dsort2)
M2 <- matrix(c(0:0), nrow = 5, ncol = 5)
for (i in 1:5){
  this_node = as.numeric(names_nodes[i])
  for (j in 1:5){
    test_against = as.numeric(names_nodes[j])
    if (i != j){
      M2[i, j] = shortest.paths(graph, this_node, test_against)
    }
  }
}

names_nodes = names(dsort2)
M3 <- matrix(c(0:0), nrow = 5, ncol = 5)
for (i in 1:5){
  this_node = as.numeric(names_nodes[i])
  for (j in 1:5){
    test_against = as.numeric(names_nodes[j])
    if (i != j){
      M3[i, j] = shortest.paths(graph, this_node, test_against)
    }
  }
}

heatmap.2(M, cellnote = M, notecol="black", dendrogram='none', Rowv=TRUE, Colv=TRUE, trace='none')