Random walk on a graph
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
as well). Multiple and loop edges are also observed.
random_walk(graph, start, steps, mode = c("out", "in", "all"), stuck = c("return", "error"))
- The input graph, might be undirected or directed.
- The start vertex.
- The number of steps to make.
- How to follow directed edges.
"out"steps along the edge direction,
"in"is opposite to that.
"all"ignores edge directions. This argument is ignored for directed graphs.
- What to do if the random walk gets stuck.
"return"returns the partial walk,
"error"raises an error.
- 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)