wolffd@0: function bnet = mk_qmr_bnet(G, inhibit, leak, prior, tabular_findings, onodes)
wolffd@0: % MK_QMR_BNET Make a QMR model
wolffd@0: % bnet = mk_qmr_bnet(G, inhibit, leak, prior)
wolffd@0: %
wolffd@0: % G(i,j) = 1 iff there is an arc from disease i to finding j
wolffd@0: % inhibit(i,j) = inhibition probability on i->j arc
wolffd@0: % leak(j) = inhibition prob. on leak->j arc
wolffd@0: % prior(i) = prob. disease i is on
wolffd@0: % tabular_findings = 1 means multinomial leaves (ignores leak/inhibit params)
wolffd@0: %   = 0 means noisy-OR leaves (default = 0)
wolffd@0: 
wolffd@0: if nargin < 5, tabular_findings = 0; end
wolffd@0: 
wolffd@0: [Ndiseases Nfindings] = size(inhibit);
wolffd@0: N = Ndiseases + Nfindings;
wolffd@0: finding_node = Ndiseases+1:N;
wolffd@0: ns = 2*ones(1,N);
wolffd@0: dag = zeros(N,N);
wolffd@0: dag(1:Ndiseases, finding_node) = G;
wolffd@0: if nargin < 6, onodes = finding_node; end
wolffd@0: bnet = mk_bnet(dag, ns, 'observed', onodes);
wolffd@0: 
wolffd@0: for d=1:Ndiseases
wolffd@0:   CPT = [1-prior(d) prior(d)];
wolffd@0:   bnet.CPD{d} = tabular_CPD(bnet, d, CPT');
wolffd@0: end
wolffd@0: 
wolffd@0: for i=1:Nfindings
wolffd@0:   fnode = finding_node(i);
wolffd@0:   ps = parents(G, i);
wolffd@0:   if tabular_findings
wolffd@0:     bnet.CPD{fnode} = tabular_CPD(bnet, fnode); 
wolffd@0:   else
wolffd@0:     bnet.CPD{fnode} = noisyor_CPD(bnet, fnode, leak(i), inhibit(ps, i));
wolffd@0:   end
wolffd@0: end
wolffd@0: 
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