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1 function [engine, loglik] = enter_evidence(engine, evidence, varargin)
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2 % ENTER_EVIDENCE Add the specified evidence to the network (jtree)
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3 % [engine, loglik] = enter_evidence(engine, evidence, ...)
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4 %
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5 % evidence{i} = [] if X(i) is hidden, and otherwise contains its observed value (scalar or column vector).
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6 %
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7 % The following optional arguments can be specified in the form of name/value pairs:
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8 % [default value in brackets]
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9 %
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10 % soft - a cell array of soft/virtual evidence;
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11 % soft{i} is a prob. distrib. over i's values, or [] [ cell(1,N) ]
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12 %
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13 % e.g., engine = enter_evidence(engine, ev, 'soft', soft_ev)
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14
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15 bnet = bnet_from_engine(engine);
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16 ns = bnet.node_sizes(:);
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17 N = length(bnet.dag);
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18
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19 engine.evidence = evidence; % store this for marginal_nodes with add_ev option
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20 engine.maximize = 0;
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21
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22 % set default params
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23 exclude = [];
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24 soft_evidence = cell(1,N);
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25
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26 % parse optional params
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27 args = varargin;
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28 nargs = length(args);
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29 for i=1:2:nargs
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30 switch args{i},
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31 case 'soft', soft_evidence = args{i+1};
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32 case 'maximize', engine.maximize = args{i+1};
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33 otherwise,
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34 error(['invalid argument name ' args{i}]);
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35 end
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36 end
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37
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38 onodes = find(~isemptycell(evidence));
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39 hnodes = find(isemptycell(evidence));
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40 pot_type = determine_pot_type(bnet, onodes);
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41 if strcmp(pot_type, 'cg')
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42 check_for_cd_arcs(onodes, bnet.cnodes, bnet.dag);
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43 end
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44
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45 if is_mnet(bnet)
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46 pot = engine.user_pot;
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47 clqs = engine.nums_ass_to_user_clqs;
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48 else
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49 % Evaluate CPDs with evidence, and convert to potentials
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50 pot = cell(1, N);
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51 for n=1:N
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52 fam = family(bnet.dag, n);
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53 e = bnet.equiv_class(n);
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54 if isempty(bnet.CPD{e})
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55 error(['must define CPD ' num2str(e)])
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56 else
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57 pot{n} = convert_to_pot(bnet.CPD{e}, pot_type, fam(:), evidence);
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58 end
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59 end
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60 clqs = engine.clq_ass_to_node(1:N);
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61 end
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62
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63 % soft evidence
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64 soft_nodes = find(~isemptycell(soft_evidence));
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65 S = length(soft_nodes);
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66 if S > 0
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67 assert(pot_type == 'd');
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68 assert(mysubset(soft_nodes, bnet.dnodes));
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69 end
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70 for i=1:S
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71 n = soft_nodes(i);
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72 pot{end+1} = dpot(n, ns(n), soft_evidence{n});
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73 end
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74 clqs = [clqs engine.clq_ass_to_node(soft_nodes)];
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75
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76
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77 [clpot, seppot] = init_pot(engine, clqs, pot, pot_type, onodes);
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78 [clpot, seppot] = collect_evidence(engine, clpot, seppot);
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79 [clpot, seppot] = distribute_evidence(engine, clpot, seppot);
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80
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81 C = length(clpot);
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82 ll = zeros(1, C);
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83 for i=1:C
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84 [clpot{i}, ll(i)] = normalize_pot(clpot{i});
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85 end
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86 loglik = ll(1); % we can extract the likelihood from any clique
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87
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88 engine.clpot = clpot;
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