example_random_network.R

#walk through the steps of creating a tree network for a sankey
#and assigning random weights to the base vertices(out degree = 1)
#and then summing so each edge weight is properly defined
#great exercise to learn the construction of a sankey
#and the conditions for a network to be drawn properly by sankey

#then plot our network with the rCharts implementation of d3.js sankey plugin

require(igraph)
require(rCharts)


g2 <- graph.tree(40,children=4)
#to construct a sankey the weight of each vertex should be the sum
#of its outgoing edges
#I believe the first step in creating a network that satisfies this condition
#is define a vertex weight for all vertexes with out degree = 0
#but first let's define 0 for all
V(g2)$weight = 0
#now for all vertexes with out degree = 0
V(g2)[degree(g2,mode="out")==0]$weight <- runif(n=length(V(g2)[degree(g2,mode="out")==0]),min=0,max=100)
#the lowest level of the heirarchy is defined with a random weight
#with the lowest level defined we should now be able to sum the vertex weights
#to define the edge weight
#E(g2)$weight = 0.1 #define all weights small to visually see as we build sankey
E(g2)[to(V(g2)$weight>0)]$weight <- V(g2)[V(g2)$weight>0]$weight
#and to find the neighbors to the 0 out degree vertex
#we could do V(g2)[nei(degree(g2,mode="out")==0)]
#we have everything we need to build the rest by summing
#these edge weights if there are edges still undefined
#so set up a loop to run until all edges have a defined weight
while(max(is.na(E(g2)$weight))) {
  #get.data.frame gives us from, to, and weight
  #we will get this to make an easier reference later
  df <- get.data.frame(g2)
  #now go through each edge and find the sum of all its subedges
  #we need to check to make sure out degree of its "to" vertex is not 0
  #or we will get 0 since there are no edges for vertex with out degree 0
  for (i in 1:nrow(df)) {
    x = df[i,]
    #sum only those with out degree > 0 or sum will be 0
    if(max(df$from==x$to)) {
      E(g2)[from(x$from) & to(x$to)]$weight = sum(E(g2)[from(x$to)]$weight)
    }
  }
}


#just a quick check on the adjacency
get.adjacency(g2,sparse = FALSE,attr="weight")




#E(g2)$weight <- runif(length(E(g2)))
edgelistWeight <- get.data.frame(g2)
colnames(edgelistWeight) <- c("source","target","value")
edgelistWeight$source <- as.character(edgelistWeight$source)
edgelistWeight$target <- as.character(edgelistWeight$target)

sankeyPlot2 <- rCharts$new()
sankeyPlot2$setLib('.')
sankeyPlot2$setTemplate(script = "layouts/chart.html")

sankeyPlot2$set(
  data = edgelistWeight,
  nodeWidth = 15,
  nodePadding = 10,
  layout = 32,
  width = 960,
  height = 500
)

sankeyPlot2


#now for fun, let's plot the network with igraph
plot(g2)