wolffd@0: % Compare different loopy belief propagation algorithms on a graph with a single loop.
wolffd@0: % LBP should give exact results if it converges.
wolffd@0: 
wolffd@0: N = 4;
wolffd@0: dag = zeros(N,N);
wolffd@0: C = 1; S = 2; R = 3; W = 4;
wolffd@0: dag(C,[R S]) = 1;
wolffd@0: dag(R,W) = 1;
wolffd@0: dag(S,W)=1;
wolffd@0: ns = 2*ones(1,N); 
wolffd@0: bnet = mk_bnet(dag, ns, 'discrete', []);
wolffd@0: for i=1:N
wolffd@0:   bnet.CPD{i} = gaussian_CPD(bnet, i);
wolffd@0: end
wolffd@0: 
wolffd@0: engines = {};
wolffd@0: engines{end+1} = jtree_inf_engine(bnet);
wolffd@0: engines{end+1} = pearl_inf_engine(bnet, 'protocol', 'parallel', 'max_iter', 20);
wolffd@0: %engines{end+1} = pearl_inf_engine(bnet, 'protocol', 'parallel', 'max_iter', 20, 'filename', ...
wolffd@0: %				  '/home/eecs/murphyk/matlab/gausspearl.txt', 'tol', 1e-5);
wolffd@0: 
wolffd@0: % pearl gaussian does not compute loglik
wolffd@0: [time, engines] = cmp_inference_static(bnet, engines, 'maximize', 0, 'exact', 1, 'observed', [2], ...
wolffd@0: 				   'check_ll', 0, 'singletons_only', 0, 'check_converged', [2]);
wolffd@0: