Casi di studio: analisi di reti in R
Edmund Hart
Instructor
library(HiveR) library(igraph) # Crea un grafo casuale rand_g <- erdos.renyi.game(18, 0.3, "gnp", directed = TRUE) # Disegna il grafo casuale plot(rand_g, vertex.size = 7)
# Converti in dataframe per hive plot e aggiungi pesi rand_g_df <- as.data.frame(get.edgelist(rand_g)) rand_g_df$weight <- 1 # Converti in oggetto hive rand_hive <- edge2HPD(edge_df = rand_g_df) # Imposta asse e raggio di ogni nodo rand_hive$nodes$axis <- sort(rep(1:3, 6)) rand_hive$nodes$radius <- as.double(rep(1:6, 3))
# Converti in dataframe per hive plot e aggiungi pesi rand_g_df <- as.data.frame(get.edgelist(rand_g)) rand_g_df$weight <- 1
# Converti in oggetto hive rand_hive <- edge2HPD(edge_df = rand_g_df)
# Imposta asse e raggio di ogni nodo rand_hive$nodes$axis <- sort(rep(1:3, 6)) rand_hive$nodes$radius <- as.double(rep(1:6, 3))
# Vedi come cambiano i nodi rand_hive$nodes
id lab axis radius size color 1 2 1 1 1 black 2 8 1 2 1 black 3 9 1 3 1 black 4 3 1 4 1 black 5 4 1 5 1 black 6 7 1 6 1 black 7 11 2 1 1 black 8 14 2 2 1 black 9 18 2 3 1 black
# Mostra l'hive plot plotHive(rand_hive, method = "abs", bkgnd = "white")
# Imposta la posizione di ogni nodo rand_hive$nodes$axis <- sort(rep(1:3, 6)) rand_hive$nodes$radius <- as.double(rep(1:6, 3)) # Aggiungi pesi a ogni arco rand_hive$edges$weight <- as.double( rpois(length(rand_hive$edges$weight), 5) ) # Colora in base all'origine dell'arco rand_hive$edges$color[rand_hive$edges$id1 %in% 1:6] <- 'red' rand_hive$edges$color[rand_hive$edges$id1 %in% 7:12] <- 'blue' rand_hive$edges$color[rand_hive$edges$id1 %in% 13:18] <- 'green' # Disegna plotHive(rand_hive, method = "abs", bkgnd = "white")
# Imposta la posizione di ogni nodo rand_hive$nodes$axis <- sort(rep(1:3, 6)) rand_hive$nodes$radius <- as.double(rep(1:6, 3))
# Aggiungi pesi a ogni arco rand_hive$edges$weight <- as.double( rpois(length(rand_hive$edges$weight), 5) ) # Colora in base all'origine dell'arco rand_hive$edges$color[rand_hive$edges$id1 %in% 1:6] <- 'red' rand_hive$edges$color[rand_hive$edges$id1 %in% 7:12] <- 'blue' rand_hive$edges$color[rand_hive$edges$id1 %in% 13:18] <- 'green'
# Disegna plotHive(rand_hive, method = "abs", bkgnd = "white")
# Crea un grafo casuale rand_g <- erdos.renyi.game(10, 0.3, "gnp", directed = FALSE) rand_g <- simplify(rand_g) # Aggiungi nomi ai vertici V(rand_g)$name <- LETTERS[1:length(V(rand_g))] # Crea un biofabric plot biofbc <- bioFabric(rand_g) bioFabric_htmlwidget(biofbc)
# Crea un grafo casuale rand_g <- erdos.renyi.game(10, 0.3, "gnp", directed = FALSE) rand_g <- simplify(rand_g)
# Aggiungi nomi ai vertici V(rand_g)$name <- LETTERS[1:length(V(rand_g))]
# Crea un biofabric plot biofbc <- bioFabric(rand_g) bioFabric_htmlwidget(biofbc)
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