Am 20.07.22 um 08:02 schrieb Siwei Zhang:
Hi Dr. Peixoto,I am using graph-tool version 2.45 and I have two questions. 1. I am trying to reproduce the script in the document 2. g = gt.collection.data["celegansneural"] state = gt.minimize_nested_blockmodel_dl(g, state_args=dict(overlap=True)) and have the error:/usr/lib/python3/dist-packages/graph_tool/inference/blockmodel.py:390: UserWarning: unrecognized keyword arguments: ['overlap']warnings.warn("unrecognized keyword arguments: " + It seems the argument of "overlap" is removed.
The proper way to use an overlapping model is to pass the option: state_args=dict(base_type=OverlapBlockState)
2. Regardless of the question1, I am trying to do a bipartite version stochastic block model and I define "clabel" to constraint labels on the vertices so that vertices with different label values will not be clustered in the same group. But I always have the error of "ValueError: cannot move vertex across clabel barriers". The below is the code:In order to understand what is happening you would need to send us a minimal but complete working example that shows the problem.node_types = g.vp['kind'] node_types.get_array() Output: PropertyArray([1, 1, 1, ..., 2, 2, 2], dtype=int32) state = gt.minimize_nested_blockmodel_dl( g, state_args=dict(clabel=node_types,pclabel=node_types,deg_corr=True), multilevel_mcmc_args = dict(niter=niter,beta=beta)) Could you please help me with these questions? Thanks!
Best, Tiago -- Tiago de Paula Peixoto <ti...@skewed.de>
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