diff toolboxes/FullBNT-1.0.7/bnt/examples/static/qmr2.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/bnt/examples/static/qmr2.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,77 @@
+% Test jtree_compiled on a toy QMR network.
+
+rand('state', 0);
+randn('state', 0);
+pMax = 0.01;
+Nfindings = 10;
+Ndiseases = 5;
+
+N=Nfindings+Ndiseases;
+findings = Ndiseases+1:N;
+diseases = 1:Ndiseases;
+
+G = zeros(Ndiseases, Nfindings);
+for i=1:Nfindings
+  v= rand(1,Ndiseases);
+  rents = find(v<0.8);
+  if (length(rents)==0)
+    rents=ceil(rand(1)*Ndiseases);
+  end
+  G(rents,i)=1;
+end       
+
+prior = pMax*rand(1,Ndiseases);
+leak = 0.5*rand(1,Nfindings); % in real QMR, leak approx exp(-0.02) = 0.98     
+%leak = ones(1,Nfindings); % turns off leaks, which makes inference much harder
+inhibit = rand(Ndiseases, Nfindings);
+inhibit(not(G)) = 1;
+
+% first half of findings are +ve, second half -ve
+% The very first and last findings are hidden
+pos = 2:floor(Nfindings/2);
+neg = (pos(end)+1):(Nfindings-1);
+
+big = 1;
+
+if big
+  % Make the bnet in the straightforward way
+  tabular_leaves = 1;
+  obs_nodes = myunion(pos, neg) + Ndiseases;
+  bnet = mk_qmr_bnet(G, inhibit, leak, prior, tabular_leaves, obs_nodes);
+  evidence = cell(1, N);
+  evidence(findings(pos)) = num2cell(repmat(2, 1, length(pos)));
+  evidence(findings(neg)) = num2cell(repmat(1, 1, length(neg)));
+else
+  % Marginalize out hidden leaves apriori
+  positive_leaves_only = 1;
+  [bnet, vals] = mk_minimal_qmr_bnet(G, inhibit, leak, prior, pos, neg, positive_leaves_only);
+  obs_nodes = bnet.observed;
+  evidence = cell(1, Ndiseases + length(obs_nodes));
+  evidence(obs_nodes) = num2cell(vals);
+end
+
+engine = {};
+engine{end+1} = jtree_inf_engine(bnet);
+
+E = length(engine);
+exact = 1:E;
+ll = zeros(1,E);
+for e=1:E
+  tic; [engine{e}, ll(e)] = enter_evidence(engine{e}, evidence); toc
+end
+
+assert(all(approxeq(ll(exact), ll(exact(1)))))
+
+post = zeros(E, Ndiseases);
+for e=1:E
+  for i=diseases(:)'
+    m = marginal_nodes(engine{e}, i);
+    post(e, i) = m.T(2);
+  end
+end
+for e=exact(:)'
+  for i=diseases(:)'
+    assert(approxeq(post(1, i), post(e, i)));
+  end
+end
+