EVOLUTION-MANAGER

Edit File: hrg.R

pause <- function() {} ### Construct the Zachary Karate Club network karate <- make_graph("zachary") karate pause() ### Optimalize modularity optcom <- cluster_optimal(karate) V(karate)$comm <- membership(optcom) plot(optcom, karate) pause() ### Fit a HRG model to the network hrg <- fit_hrg(karate) hrg pause() ### The fitted model, more details print(hrg, level=5) pause() ### Plot the full hierarchy, as an igraph graph ihrg <- as.igraph(hrg) ihrg$layout <- layout.reingold.tilford plot(ihrg, vertex.size=10, edge.arrow.size=0.2) pause() ### Customize the plot a bit, show probabilities and communities vn <- sub("Actor ", "", V(ihrg)$name) colbar <- rainbow(length(optcom)) vc <- ifelse(is.na(V(ihrg)$prob), colbar[V(karate)$comm], "darkblue") V(ihrg)$label <- ifelse(is.na(V(ihrg)$prob), vn, round(V(ihrg)$prob, 2)) par(mar=c(0,0,3,0)) plot(ihrg, vertex.size=10, edge.arrow.size=0.2, vertex.shape="none", vertex.label.color=vc, main="Hierarchical network model of the Karate Club") pause() ### Plot it as a dendrogram, looks better if the 'ape' package is installed plot_dendrogram(hrg) pause() ### Make a very hierarchical graph g1 <- make_full_graph(5) g2 <- make_ring(5) g <- g1 + g2 g <- g + edge(1, vcount(g1)+1) plot(g) pause() ### Fit HRG ghrg <- fit_hrg(g) plot_dendrogram(ghrg) pause() ### Create a consensus dendrogram from multiple samples, takes longer... hcons <- consensus_tree(g) hcons$consensus pause() ### Predict missing edges pred <- predict_edges(g) pred pause() ### Add some the top 5 predicted edges to the graph, colored red E(g)$color <- "grey" lay <- layout_nicely(g) g2 <- add_edges(g, t(pred$edges[1:5,]), color="red") plot(g2, layout=lay) pause() ### Add four more predicted edges, colored orange g3 <- add_edges(g2, t(pred$edges[6:9,]), color="orange") plot(g3, layout=lay)