On 09.08.2017 18:04, topinsky wrote:
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?"
Oh, the actual vertex labels are not meaningful. You can just re-label them in a contiguous range before computing the histogram.
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. ?
This is exactly what happens; this is why your histogram has many values of non-empty groups. (The number of total groups, including empty ones, will always grow as necessary.) Best, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>