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1 function [m, pot] = marginal_family(engine, query)
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2 % MARGINAL_NODES Compute the marginal on the family of the specified node (jtree_limid)
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3 % [m, pot] = marginal_family(engine, query)
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4 %
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5 % query should be a single decision node, or [] (to compute global max expected utility)
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6
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7 bnet = bnet_from_engine(engine);
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8 if isempty(query)
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9 compute_meu = 1;
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10 d = bnet.decision_nodes(1); % pick an arbitrary root to collect to
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11 fam = []; % marginalize root pot down to a point
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12 else
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13 compute_meu = 0;
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14 d = query;
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15 assert(myismember(d, bnet.decision_nodes));
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16 fam = family(bnet.dag, d);
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17 end
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18
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19 clpot = init_clpot(bnet, engine.cliques, engine.clq_ass_to_node, engine.evidence, engine.exclude);
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20
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21 % collect to root (clique containing d)
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22 C = length(engine.cliques);
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23 seppot = cell(C, C); % separators are implicitely initialized to 1s
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24 for n=engine.postorder{d}(1:end-1)
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25 for p=parents(engine.rooted_jtree{d}, n)
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26 %clpot{p} = divide_by_pot(clpot{n}, seppot{p,n}); % dividing by 1 is redundant
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27 seppot{p,n} = marginalize_pot(clpot{n}, engine.separator{p,n});
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28 clpot{p} = multiply_by_pot(clpot{p}, seppot{p,n});
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29 end
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30 end
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31
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32 root = engine.clq_ass_to_node(d);
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33 assert(root == engine.postorder{d}(end));
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34 pot = marginalize_pot(clpot{root}, fam);
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35 m = pot_to_marginal(pot);
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36
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37 %%%%%%%%%%%
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38
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39
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40 function clpot = init_clpot(bnet, cliques, clq_ass_to_node, evidence, exclude)
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41
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42 % Set the clique potentials to all 1s
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43 C = length(cliques);
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44 clpot = cell(1, C);
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45 ns = bnet.node_sizes;
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46 for i=1:C
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47 clpot{i} = upot(cliques{i}, ns(cliques{i}));
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48 end
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49
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50 N = length(bnet.dag);
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51 nodes = mysetdiff(1:N, exclude);
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52
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53 for n=nodes(:)'
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54 fam = family(bnet.dag, n);
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55 e = bnet.equiv_class(n);
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56 c = clq_ass_to_node(n);
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57 pot = convert_to_pot(bnet.CPD{e}, 'u', ns, fam, evidence);
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58 clpot{c} = multiply_by_pot(clpot{c}, pot);
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59 end
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