comparison toolboxes/FullBNT-1.0.7/bnt/examples/static/softev1.m @ 0:e9a9cd732c1e tip

first hg version after svn

+% Check that adding soft evidence to a hidden node is equivalent to evaluating its leaf CPD.
+
+% Make an HMM
+T = 3; Q = 2; O = 2; cts_obs = 0; param_tying = 0;
+bnet = mk_hmm_bnet(T, Q, O, cts_obs, param_tying);
+N = 2*T;
+onodes = bnet.observed;
+hnodes = mysetdiff(1:N, onodes);
+for i=1:N
+  bnet.CPD{i} = tabular_CPD(bnet, i);
+end
+
+ev = sample_bnet(bnet);
+evidence = cell(1,N);
+evidence(onodes) = ev(onodes);
+
+engine = jtree_inf_engine(bnet);
+
+[engine, ll] = enter_evidence(engine, evidence);
+query = 1;
+m = marginal_nodes(engine, query);
+
+
+% Make a Markov chain with the same backbone
+bnet2 = mk_markov_chain_bnet(T, Q);
+for i=1:T
+  S = struct(bnet.CPD{hnodes(i)}); % violate object privacy
+  bnet2.CPD{i} = tabular_CPD(bnet2, i, S.CPT);
+end
+
+% Evaluate the observed leaves of the HMM
+soft_ev = cell(1,T);
+for i=1:T
+  S = struct(bnet.CPD{onodes(i)}); % violate object privacy
+  dist = S.CPT(:, evidence{onodes(i)});
+  soft_ev{i} = dist;
+end
+
+% Use the leaf potentials as soft evidence
+engine2 = jtree_inf_engine(bnet2);
+[engine2, ll2] = enter_evidence(engine2, cell(1,T), 'soft', soft_ev);
+m2 = marginal_nodes(engine2, query);
+
+assert(approxeq(m2.T, m.T))
+assert(approxeq(ll2, ll))
+
+
+
+% marginal on node 1 without evidence
+[engine2, ll2] = enter_evidence(engine2, cell(1,T));
+m2 = marginal_nodes(engine2, 1);
+
+% add soft evidence
+soft_ev=cell(1,T);
+soft_ev{1}=[0.7 0.3]; 
+[engine2, ll2] = enter_evidence(engine2, cell(1,T), 'soft', soft_ev);
+m3 = marginal_nodes(engine2, 1);
+
+assert(approxeq(normalise(m2.T .* [0.7 0.3]'), m3.T))
+