Use this if you are using igraph from R
Do a random walk. From the given start vertex, take the given number of
steps, choosing an edge from the actual vertex uniformly randomly. Edge
directions are observed in directed graphs (see the mode
argument
as well). Multiple and loop edges are also observed.
random_walk(graph, start, steps, mode = c("out", "in", "all"), stuck = c("return", "error"))
graph |
The input graph, might be undirected or directed. |
start |
The start vertex. |
steps |
The number of steps to make. |
mode |
How to follow directed edges. |
stuck |
What to do if the random walk gets stuck. |
A vertex sequence containing the vertices along the walk.
## Stationary distribution of a Markov chain g <- make_ring(10, directed = TRUE) %u% make_star(11, center = 11) + edge(11, 1) ec <- eigen_centrality(g, directed = TRUE)$vector pg <- page_rank(g, damping = 0.999)$vector w <- random_walk(g, start = 1, steps = 10000) ## These are similar, but not exactly the same cor(table(w), ec) ## But these are (almost) the same cor(table(w), pg)