I am trying to recreate figure 2 from Hric, Peixoto, and Fortunato (2016): https://arxiv.org/abs/1604.00255 and would appreciate some assistance. The data come from the college football network and can be pulled directly from an online repository using graph-tool: g = gt.collection.data["football"] I can recreate figure 2a simply by estimating a nested blockmodel and graphing it as follow: state = minimize_nested_blockmodel_dl(g, deg_corr=True) draw_hierarchy(state, output="./results/test.png") However, I am stuck on figure 2b, which graphs the bipartite network of conferences and teams. Does this figure plot the output of estimating the blockmodel on layered data? If so, how should I extract the metadata, which are stored as the vertex property "label"? Do I need to create a second edge list linking the original vertices to the metadata? And if so, is there a way of doing this without a long loop? Eventually I want to run this code on a much larger network so I would like to write code that is as efficient as possible. Thanks for your help, Jamie -- Sent from: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/