* Cosmetic changes, implemented a lot of debugging functions (display_subgraph, etc...)
* Found and fixed the crucial bug affecting message passing (which was induced by yesterday's fix). MP and Simple Gibbs now agree for MRFs !
* Started referring to MRFs as "pairwise graphs" since an MRF isn't (apparently) restricted to pairwise potentials
* Still bugs in Tree Gibbs. I found a *major one*: we need to allow the Potential on the nodes to be SingleDiscrete and not Constant!! Or we should find a better way of implementing that...
* New ideas for a better interface in RandomVariable (less friends, implementation better encapsulated). We could use each sample as "prior knowledge". There is still the problem of translating that prior knowledge into probabilities (that would have to be a public function). Maybe I'll spend some time thinking about it.
-> correct the Tree Gibbs Sampler
-> implement a random graph creation algorithm, that creates connected graphs (use Boost algrithms)
-> if time allows, learn more about C++ (Parashift FAQ)
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