knitr::opts_chunk$set( collapse = TRUE, comment = "#>", warning = FALSE ) library(sigmajs)

Since v3.0.0 you can color the nodes by cluster. Simply use sg_cluster with your igraph clustering algorithm of choice.

nodes <- sg_make_nodes() edges <- sg_make_edges(nodes, 17) sigmajs() %>% sg_nodes(nodes, id, size) %>% sg_edges(edges, id, source, target) %>% sg_layout() %>% sg_cluster()

Clustering is brilliant, in part, because (most) are bottom-up approaches; the number of cluster is not pre-defined. However, this might make the above approach somewhat awkward as the node colors should be discrete. In an interactive environment sg_cluster prints the number of clusters identified to the console, so you could then set the exact number of colors needed then re-run the graph.

Perhaps a better approach is to use the helper function sg_get_cluster to return nodes with an added column, the group they belong to. The helper also lets you set (or re-set) the node colors according to the group they belong to.

Let's take a look at an example

set.seed(19880525) # for reproducability # make a slightly larger graph nodes <- sg_make_nodes(50) edges <- sg_make_edges(nodes, 100) # use the helper # first run showed 11 clusters nodes <- sg_get_cluster( nodes, edges, colors = c( "#331A00", "#663000", "#996136", "#CC9B7A", "#D9AF98", "#F2DACE", "#CCFDFF", "#99F8FF", "#66F0FF", "#33E4FF", "#00AACC") ) sigmajs() %>% sg_nodes(nodes, id, size, color) %>% sg_edges(edges, id, source, target) %>% sg_layout() %>% sg_neighbours()