Good day,
Thank you for the reply.
I want to demonstrate the relevant confusing observation.
I ran the example from cookbook:

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I attached the plots. As you can see the model always use a few (nonempty)
blocks from 6 to 9.
But at the same time amount of different marginal states (with positive
probabilities)
for some vertices are around 70 (almost the all potential 77 =
g.num_vertices()).
Which means that during independent runs model can get new set of 6 to 9
blocks but
just with some other labels of it. This is what I meant by:
"May be it's just the result of independent launches of mcmc algorithm and
random nature of groups labelling?"
Is there any way how to do sampling without specifying exact B?
But rather with sampling of B as it described in
https://arxiv.org/pdf/1705.10225.pdf Ch. IV. ?
<http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027334/lesmis-1.png>
<http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4027334/lesmis-2.png>
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