I am working on a graph, where each node has an attribute "group" of the following: "Baby Product", "Book" "CE" "DVD" "Music" "Software" "Toy" "Video" "Video Games".
I would like to know how to plot a graph reppresenting those communities: there shall be 9 verticies, one for each group, and a link (possibly weighted) each time two nodes of two categories are connected.
I have tried using the igraph contract function, but this is the result:
> contract(fullnet, mapping=as.factor(products$group), vertex.attr.comb = products$group)
Error in FUN(X[[i]], ...) :
Unknown/unambigous attribute combination specification
Inoltre: Warning message:
In igraph.i.attribute.combination(vertex.attr.comb) :
Some attributes are duplicated
I guess I have misunderstood what this function is used for.
Now I am thinking about creating a new edgelist, made like the one before but instead of the Id of each vertex the name of the group. Sadly, I do not know how to do this in a fast way on an edgelist of over 1200000 elements.
Thank you very much in advance.
I think using contract() should be correct. In the example code below, I added an anonymous function to vertex.attr.comb to combine the vertices by group. Then, simplify() removes loop edges and calculate the sum of edge weight.
# Create example graph
set.seed(1)
g <- random.graph.game(10, 0.2)
V(g)$group <- rep(letters[1:3], times = c(3, 3, 4))
E(g)$weight <- 1:length(E(g))
E(g)
# + 9/9 edges from 7017c6a:
# [1] 2-- 3 3-- 4 4-- 7 5-- 7 5-- 8 7-- 8 3-- 9 2--10 9--10
E(g)$weight
# [1] 1 2 3 4 5 6 7 8 9
# Contract graph by `group` attribute of vertices
g1 <- contract(g, factor(V(g)$group),
vertex.attr.comb = function(x) levels(factor(x)))
# Remove loop edges and compute the sum of edge weight by group
g1 <- simplify(g1, edge.attr.comb = "sum")
E(g1)
# + 3/3 edges from a852397:
# [1] 1--2 1--3 2--3
E(g1)$weight
# [1] 2 15 12