I have a question related to this The documentation example suggests a hierarchy set to 10 levels
bs = state.get_bs() # Get hierarchical partition. bs += [np.zeros(1)] * (10 - len(bs)) # Augment it to L = 10 with # single-group levels.
state = state.copy(bs=bs, sampling=True)
Is there some golden rule (which I obviously don’t know) to choose such dimension? Is 10 always a good choice? More important: why I need to modify the length before mcmc_equilibrate()?
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