Extra levels created by minimize_nested_blockmodel_dl


I am estimating a nested_block_model with bipartite data and am getting a
strange result. There are about 4,000 nodes in the network and I am
estimating a model by:

state_dc  = minimize_nested_blockmodel_dl(G, state_args=dict(deg_corr=True,

for i in range(1000): # this should be sufficiently large
    state_dc.multiflip_mcmc_sweep(beta=np.inf, niter=10)

The results find 13 nested levels, but after level 5 there are only 2
nonempty blocks found in each additional level. I'm not sure if this is
really a problem, or I can just ignore the levels where nothing really
changes. Any advice/help would be greatly appreciated. Thank you


Kevin Reuning
Assistant Professor, Political Science
Miami University

attachment.html (1.49 KB)

If you pass a bipartite pclabel, then this bi-partition gets reflected
in the upper levels of the hierarchy as well. This is normal.