wolffd@0: % Test jtree_compiled on a toy QMR network.
wolffd@0: 
wolffd@0: rand('state', 0);
wolffd@0: randn('state', 0);
wolffd@0: pMax = 0.01;
wolffd@0: Nfindings = 10;
wolffd@0: Ndiseases = 5;
wolffd@0: 
wolffd@0: N=Nfindings+Ndiseases;
wolffd@0: findings = Ndiseases+1:N;
wolffd@0: diseases = 1:Ndiseases;
wolffd@0: 
wolffd@0: G = zeros(Ndiseases, Nfindings);
wolffd@0: for i=1:Nfindings
wolffd@0:   v= rand(1,Ndiseases);
wolffd@0:   rents = find(v<0.8);
wolffd@0:   if (length(rents)==0)
wolffd@0:     rents=ceil(rand(1)*Ndiseases);
wolffd@0:   end
wolffd@0:   G(rents,i)=1;
wolffd@0: end       
wolffd@0: 
wolffd@0: prior = pMax*rand(1,Ndiseases);
wolffd@0: leak = 0.5*rand(1,Nfindings); % in real QMR, leak approx exp(-0.02) = 0.98     
wolffd@0: %leak = ones(1,Nfindings); % turns off leaks, which makes inference much harder
wolffd@0: inhibit = rand(Ndiseases, Nfindings);
wolffd@0: inhibit(not(G)) = 1;
wolffd@0: 
wolffd@0: % first half of findings are +ve, second half -ve
wolffd@0: % The very first and last findings are hidden
wolffd@0: pos = 2:floor(Nfindings/2);
wolffd@0: neg = (pos(end)+1):(Nfindings-1);
wolffd@0: 
wolffd@0: big = 1;
wolffd@0: 
wolffd@0: if big
wolffd@0:   % Make the bnet in the straightforward way
wolffd@0:   tabular_leaves = 1;
wolffd@0:   obs_nodes = myunion(pos, neg) + Ndiseases;
wolffd@0:   bnet = mk_qmr_bnet(G, inhibit, leak, prior, tabular_leaves, obs_nodes);
wolffd@0:   evidence = cell(1, N);
wolffd@0:   evidence(findings(pos)) = num2cell(repmat(2, 1, length(pos)));
wolffd@0:   evidence(findings(neg)) = num2cell(repmat(1, 1, length(neg)));
wolffd@0: else
wolffd@0:   % Marginalize out hidden leaves apriori
wolffd@0:   positive_leaves_only = 1;
wolffd@0:   [bnet, vals] = mk_minimal_qmr_bnet(G, inhibit, leak, prior, pos, neg, positive_leaves_only);
wolffd@0:   obs_nodes = bnet.observed;
wolffd@0:   evidence = cell(1, Ndiseases + length(obs_nodes));
wolffd@0:   evidence(obs_nodes) = num2cell(vals);
wolffd@0: end
wolffd@0: 
wolffd@0: engine = {};
wolffd@0: engine{end+1} = jtree_inf_engine(bnet);
wolffd@0: 
wolffd@0: E = length(engine);
wolffd@0: exact = 1:E;
wolffd@0: ll = zeros(1,E);
wolffd@0: for e=1:E
wolffd@0:   tic; [engine{e}, ll(e)] = enter_evidence(engine{e}, evidence); toc
wolffd@0: end
wolffd@0: 
wolffd@0: assert(all(approxeq(ll(exact), ll(exact(1)))))
wolffd@0: 
wolffd@0: post = zeros(E, Ndiseases);
wolffd@0: for e=1:E
wolffd@0:   for i=diseases(:)'
wolffd@0:     m = marginal_nodes(engine{e}, i);
wolffd@0:     post(e, i) = m.T(2);
wolffd@0:   end
wolffd@0: end
wolffd@0: for e=exact(:)'
wolffd@0:   for i=diseases(:)'
wolffd@0:     assert(approxeq(post(1, i), post(e, i)));
wolffd@0:   end
wolffd@0: end
wolffd@0: