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? 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)) Thanks for your attention. Leonardo