Am 13.03.20 um 15:40 schrieb Leonardo Morelli: > Hi! > I'm a beginner in this field, so I do apologize if my vocabulary isn't > precise enough. > Basically, I'm trying to use graph-tool library in order to perform the > unsupervised clustering step of biological samples (10³-10⁴ _nodes > _networks). > > The following Is my current workflow: > 1) state=minimize_nested_blockmodel_dl(g) > 2) state.mcmc_sweep(niter=10,000) > 3) mcmc__equilibrate(_state_)_ > > Question 1) > Since I'm performing the equilibration with mcmc_equilibrate; is the > mcmc_sweep step necessary in my workflow? Or I can just skip it?
No, it is not. > Question 2) > This question concerns β parameter. > I'm wondering if performing 2 rounds of equilibration sequentially, > changing the value of β, does make any sense. In other words: > 1) state=minimize_nested_blockmodel_dl(g) > 2) mcmc_equilibrate(state, mcmc_args=dict(niter=10, β=1)) > 3)mcmc_equilibrate(state, mcmc_args=dict(niter=10, β=1,000,000)) This is a kind of abrupt simulated anealing, and it can improve the minimization in some cases. However, I would recommend using the function mcmc_anneal() which achieves the same but slowly, which should behave better. Best, Tiago -- Tiago de Paula Peixoto <ti...@skewed.de>
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