Thanks you very much for taking the time to reply. I have had joy in implementing the Bayesian inference framework for empirical cascades (on Windows via WSL!), I have one small query which I cannot find an answer for in the documentation. Namely, if I implement similar to the example in the cookbook in my own case the final graph object obtained has a number of edge properties including the eprob, but it also has another property 'x' - is this the inferred transmission probabilities for each edge? I have so far been collecting the probabilities via the 'get_x()' approach described in the cookbook during the MCMC sweep however the final such call results in an array of length apparently (?) unrelated to the final graph object. Any guidance would be greatly appreciated.
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