R igraph manual pages

Use this if you are using igraph from R

Trait-based random generation


Generation of random graphs based on different vertex types.


sample_pref(nodes, types, type.dist = rep(1, types),
  fixed.sizes = FALSE, pref.matrix = matrix(1, types, types),
  directed = FALSE, loops = FALSE)


sample_asym_pref(nodes, types, type.dist.matrix = matrix(1, types,
  types), pref.matrix = matrix(1, types, types), loops = FALSE)




The number of vertices in the graphs.


The number of different vertex types.


The distribution of the vertex types, a numeric vector of length ‘types’ containing non-negative numbers. The vector will be normed to obtain probabilities.


Fix the number of vertices with a given vertex type label. The type.dist argument gives the group sizes (i.e. number of vertices with the different labels) in this case.


A square matrix giving the preferences of the vertex types. The matrix has ‘types’ rows and columns.


Logical constant, whether to create a directed graph.


Logical constant, whether self-loops are allowed in the graph.


Passed to the constructor, sample_pref or sample_asym_pref.


The joint distribution of the in- and out-vertex types.


Both models generate random graphs with given vertex types. For sample_pref the probability that two vertices will be connected depends on their type and is given by the ‘pref.matrix’ argument. This matrix should be symmetric to make sense but this is not checked. The distribution of the different vertes types is given by the ‘type.dist’ vector.

For sample_asym_pref each vertex has an in-type and an out-type and a directed graph is created. The probability that a directed edge is realized from a vertex with a given out-type to a vertex with a given in-type is given in the ‘pref.matrix’ argument, which can be asymmetric. The joint distribution for the in- and out-types is given in the ‘type.dist.matrix’ argument.


An igraph graph.


Tamas Nepusz ntamas@gmail.com and Gabor Csardi csardi.gabor@gmail.com for the R interface

See Also

sample_traits. sample_traits_callaway


pf <- matrix( c(1, 0, 0, 1), nr=2)
g <- sample_pref(20, 2, pref.matrix=pf)
## Not run: tkplot(g, layout=layout_with_fr)

pf <- matrix( c(0, 1, 0, 0), nr=2)
g <- sample_asym_pref(20, 2, pref.matrix=pf)
## Not run: tkplot(g, layout=layout_in_circle)

[Package igraph version Index]