Pro3

R Markdown

edge_density(g, loops = F)

## [1] 0.06060606

eigen_centrality(g)$vector

##         3        54       108       152       178       182       214       271 
## 1.0000000 0.3244157 0.2071806 0.2071806 0.2071806 0.2071806 0.2071806 0.2071806 
##       286       300       348       349       371       567       581       584 
## 0.2071806 0.2071806 0.2071806 0.2071806 0.2071806 0.2071806 0.2071806 0.2071806 
##       586       590       604       611      8283        25         6         8 
## 0.2071806 0.2071806 0.2071806 0.2071806 0.2071806 0.5658592 0.1172351 0.1172351 
##        19        23        28        29        30        33        35        50 
## 0.1172351 0.1172351 0.1172351 0.1172351 0.1172351 0.1172351 0.1172351 0.1172351 
##        55        56 
## 0.1172351 0.1172351

E(g)[[inc('54')]]

## + 2/34 edges from 88cbac9 (vertex names):
##   tail head tid hid
## 1    3   54   1   2
## 2   54   25   2  22

V(g)$color <- ifelse((V(g)$name =="54"), "red", "white")
plot(g, vertex.label.color = "black")

V(g)$color <- ifelse((V(g)$name =="25"), "pink", "white")
plot(g, vertex.label.color = "black")

Including Plots

You can also embed plots, for example:

## $res
##  [1] 21  2  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1 14  1  1  1
## [26]  1  1  1  1  1  1  1  1  1
## 
## $centralization
## [1] 0.5757576
## 
## $theoretical_max
## [1] 1122

edges <- graph_from_data_frame(d=dfdata, directed = F)
plot(edges)

density<- edge_density(edges)
density

## [1] 0.06060606

centrality <- centralization.betweenness(edges)
centrality

## $res
##  [1] 437 318   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## [20]   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## 
## $centralization
## [1] 0.8094008
## 
## $theoretical_max
## [1] 17424

’’’{r}

dfdata.mat <- as.matrix(data) g <- graph.edgelist(dfdata.mat, directed=FALSE) plot(g)

edge_density(g, loops = F)

eigen_centrality(g)$vector

E(g)[[inc(‘54’)]]

V(g)\(color <- ifelse((V(g)\)name ==“54”), “red”, “white”) plot(g, vertex.label.color = “black”)

V(g)\(color <- ifelse((V(g)\)name ==“25”), “pink”, “white”) plot(g, vertex.label.color = “black”)

’’’

’’’{r}m <- graph_from_adjacency_matrix(matrix(0:1), 5, 5), mode=“undirected”) plot(m)

inc.edges <- incident(m, V(m)[2], mode=“all”)

Set colors to plot the selected edges.

ecol <- rep(“gray80”, ecount(m))

ecol[inc.edges] <- “orange”

vcol <- rep(“grey40”, vcount(m)) vcol[V(m)[2]] <- “gold” plot(m,vertex.color=vcol,edge.color=ecol) ’’’