[graph-tool] Re: bipartite minimize_nested_blockmodel_dl() error: cannot move vertex across clabel barriers

[Tiago de Paula Peixoto]

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:

warnings.warn("unrecognized keyword arguments: " +

           It seems the argument of "overlap" is removed.

/usr/lib/python3/dist-packages/graph_tool/inference/blockmodel.py:390: UserWarning: unrecognized keyword arguments: ['overlap']

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:

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!

In order to understand what is happening you would need to send us a minimal but complete working example that shows the problem.

Best,
Tiago


--
Tiago de Paula Peixoto <ti...@skewed.de>

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