Examples for 'GGally::ggnetworkmap'

### ** Examples

# small function to display plots only if it's interactive
p_ <- GGally::print_if_interactive

invisible(lapply(c("ggplot2", "maps", "network", "sna"), base::library, character.only = TRUE))

## Example showing great circles on a simple map of the USA
## http://flowingdata.com/2011/05/11/how-to-map-connections-with-great-circles/
## No test: 
airports <- read.csv("http://datasets.flowingdata.com/tuts/maparcs/airports.csv", header = TRUE)
rownames(airports) <- airports$iata

# select some random flights
set.seed(123)
flights <- data.frame(
  origin = sample(airports[200:400, ]$iata, 200, replace = TRUE),
  destination = sample(airports[200:400, ]$iata, 200, replace = TRUE)
)

# convert to network
flights <- network(flights, directed = TRUE)

# add geographic coordinates
flights %v% "lat" <- airports[ network.vertex.names(flights), "lat" ]

flights %v% "lon" <- airports[ network.vertex.names(flights), "long" ]

# drop isolated airports
delete.vertices(flights, which(degree(flights) < 2))

# compute degree centrality
flights %v% "degree" <- degree(flights, gmode = "digraph")

# add random groups
flights %v% "mygroup" <- sample(letters[1:4], network.size(flights), replace = TRUE)

# create a map of the USA
usa <- ggplot(map_data("usa"), aes(x = long, y = lat)) +
  geom_polygon(aes(group = group), color = "grey65",
               fill = "#f9f9f9", size = 0.2)

# overlay network data to map
p <- ggnetworkmap(
  usa, flights, size = 4, great.circles = TRUE,
  node.group = mygroup, segment.color = "steelblue",
  ring.group = degree, weight = degree
)

p_(p)

## Exploring a community of spambots found on Twitter
## Data by Amos Elberg: see ?twitter_spambots for details

data(twitter_spambots)

# create a world map
world <- fortify(map("world", plot = FALSE, fill = TRUE))
world <- ggplot(world, aes(x = long, y = lat)) +
  geom_polygon(aes(group = group), color = "grey65",
               fill = "#f9f9f9", size = 0.2)

# view global structure
p <- ggnetworkmap(world, twitter_spambots)

p_(p)

# domestic distribution
p <- ggnetworkmap(net = twitter_spambots)

p_(p)

# topology
p <- ggnetworkmap(net = twitter_spambots, arrow.size = 0.5)

p_(p)

# compute indegree and outdegree centrality
twitter_spambots %v% "indegree" <- degree(twitter_spambots, cmode = "indegree")

twitter_spambots %v% "outdegree" <- degree(twitter_spambots, cmode = "outdegree")

p <- ggnetworkmap(
  net = twitter_spambots,
  arrow.size = 0.5,
  node.group = indegree,
  ring.group = outdegree, size = 4
) +
  scale_fill_continuous("Indegree", high = "red", low = "yellow") +
  labs(color = "Outdegree")

p_(p)

# show some vertex attributes associated with each account
p <- ggnetworkmap(
  net = twitter_spambots,
  arrow.size = 0.5,
  node.group = followers,
  ring.group = friends,
  size = 4,
  weight = indegree,
  label.nodes = TRUE, vjust = -1.5
) +
  scale_fill_continuous("Followers", high = "red", low = "yellow") +
  labs(color = "Friends") +
  scale_color_continuous(low = "lightgreen", high = "darkgreen")

p_(p)

## End(No test)