Re: [graph-tool] Which state should I copy when doing merge-split on model with weight transformation

Thanks for the quick reply! Great, happy to be of some help. This means that we now get the following: ```python L1 = -state.entropy() L2 = -state_ln.entropy() - np.log(g.ep.weight.a).sum() print("Exponential model:\t", L1) # Exponential model: 7201.52 print("Log-normal model:\t", L2) #

[graph-tool] Which state should I copy when doing merge-split on model with weight transformation

Hi all, In the following section: https://graph-tool.skewed.de/static/doc/demos/inference/inference.html#edge-weights-and-covariates Tiago shows how to infer the best model of `foodweb_baywet`