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TWEET # Untitled a guest Mar 29th, 2020 70 Never
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1. library("igraph")
2. library(gplots)
4. setwd("E:/R/lab3")
7. graph<-graph.data.frame(df)
8. #plot(graph)
9.
10. #Wznaczyc srednice sieci i srednia najkrotsza sciezke dla grafow nieskierowanych
11.
12. srednica_gns <- diameter(graph, directed = F, weights = NA)
13.
14. #Najkrotsze sciezki
15. x1 <- shortest.paths(graph)
16. y2 <- shortest.paths(graph, 1, 10)
17. c1 <- average.path.length(graph)
18. #path.length.hist(graph)
19.
20.
21. #Wyznaczyc srednice sieci i srednia najkrotsza sciezke dla grafow skierowanych
22.
23. srednica_gs <- diameter(graph, directed = T, weights = NA)
24. sredbuca_gs2 <- get.diameter(graph, directed = TRUE)
25. x <- shortest.paths(graph, mode = "out")
26. y <- shortest.paths(graph, mode = "in")
27. z <- shortest.paths(graph, mode = "all")
28. shortest.paths(graph, 8, 10, mode="out")
29. c <- average.path.length(graph, directed = TRUE)
30. w <- shortest.paths(graph, 27, 304, mode="out")
31.
32. #Wyznaczyc degree, between, closeness
33. #degree
34. d<-degree(graph, mode="all")
35. dsort <- tail(sort(d), 5)
36. plot(dsort)
37. plot(d, main="Degree")
39. plot(degree.distribution(graph, cumulative = T), pch=20, xlab="degree", ylab="cumulative frequency", type="l", main="Rozklad Stopni wierzcholkow")
40.
41. #Closeness dla grafów skierowanych i wazonych
42. o <- closeness(graph)
43. op <- closeness(graph, vids=c("1","2"))
44. close <- closeness(graph ,normalized = TRUE,mode="all")
45. dsort2 <- tail(sort(close), 5)
46. plot(close, main="Closeness")
47.
48. #Between
49. between <- betweenness(graph)
50. dsort3 <- tail(sort(between), 5)
51. plot(between, main="Betweenness")
52.
53. #top5 wspolne wierzcholki
54. print(names(dsort))
55. print(names(dsort2))
56. print(names(dsort3))
57.
58. names_nodes = names(dsort)
59. M <- matrix(c(0:0), nrow = 5, ncol = 5)
60. for (i in 1:5){
61.   this_node = as.numeric(names_nodes[i])
62.   for (j in 1:5){
63.     test_against = as.numeric(names_nodes[j])
64.     if (i != j){
65.       M[i, j] = shortest.paths(graph, this_node, test_against)
66.     }
67.   }
68. }
69.
70. names_nodes = names(dsort2)
71. M2 <- matrix(c(0:0), nrow = 5, ncol = 5)
72. for (i in 1:5){
73.   this_node = as.numeric(names_nodes[i])
74.   for (j in 1:5){
75.     test_against = as.numeric(names_nodes[j])
76.     if (i != j){
77.       M2[i, j] = shortest.paths(graph, this_node, test_against)
78.     }
79.   }
80. }
81.
82. names_nodes = names(dsort2)
83. M3 <- matrix(c(0:0), nrow = 5, ncol = 5)
84. for (i in 1:5){
85.   this_node = as.numeric(names_nodes[i])
86.   for (j in 1:5){
87.     test_against = as.numeric(names_nodes[j])
88.     if (i != j){
89.       M3[i, j] = shortest.paths(graph, this_node, test_against)
90.     }
91.   }
92. }
93.
94. heatmap.2(M, cellnote = M, notecol="black", dendrogram='none', Rowv=TRUE, Colv=TRUE, trace='none')
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