Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/bnt/inference/static/@jtree_inf_engine/Old/enter_evidence.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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-1:000000000000 | 0:e9a9cd732c1e |
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1 function [engine, loglik] = enter_evidence(engine, evidence, varargin) | |
2 % ENTER_EVIDENCE Add the specified evidence to the network (jtree) | |
3 % [engine, loglik] = enter_evidence(engine, evidence, ...) | |
4 % | |
5 % evidence{i} = [] if X(i) is hidden, and otherwise contains its observed value (scalar or column vector). | |
6 % | |
7 % The following optional arguments can be specified in the form of name/value pairs: | |
8 % [default value in brackets] | |
9 % | |
10 % maximize - if 1, does max-product instead of sum-product [0] | |
11 % soft - a cell array of soft/virtual evidence; | |
12 % soft{i} is a prob. distrib. over i's values, or [] [ cell(1,N) ] | |
13 % | |
14 % e.g., engine = enter_evidence(engine, ev, 'soft', soft_ev) | |
15 % | |
16 % For backwards compatibility with BNT2, you can also specify the parameters in the following order | |
17 % engine = enter_evidence(engine, ev, soft_ev) | |
18 | |
19 bnet = bnet_from_engine(engine); | |
20 ns = bnet.node_sizes(:); | |
21 N = length(bnet.dag); | |
22 | |
23 % set default params | |
24 exclude = []; | |
25 soft_evidence = cell(1,N); | |
26 maximize = 0; | |
27 | |
28 % parse optional params | |
29 args = varargin; | |
30 nargs = length(args); | |
31 if nargs > 0 | |
32 if iscell(args{1}) | |
33 soft_evidence = args{1}; | |
34 else | |
35 for i=1:2:nargs | |
36 switch args{i}, | |
37 case 'soft', soft_evidence = args{i+1}; | |
38 case 'maximize', maximize = args{i+1}; | |
39 otherwise, | |
40 error(['invalid argument name ' args{i}]); | |
41 end | |
42 end | |
43 end | |
44 end | |
45 | |
46 engine.maximize = maximize; | |
47 | |
48 onodes = find(~isemptycell(evidence)); | |
49 hnodes = find(isemptycell(evidence)); | |
50 pot_type = determine_pot_type(bnet, onodes); | |
51 if strcmp(pot_type, 'cg') | |
52 check_for_cd_arcs(onodes, bnet.cnodes, bnet.dag); | |
53 end | |
54 | |
55 | |
56 hard_nodes = 1:N; | |
57 soft_nodes = find(~isemptycell(soft_evidence)); | |
58 S = length(soft_nodes); | |
59 if S > 0 | |
60 assert(pot_type == 'd'); | |
61 assert(mysubset(soft_nodes, bnet.dnodes)); | |
62 end | |
63 | |
64 % Evaluate CPDs with evidence, and convert to potentials | |
65 pot = cell(1, N+S); | |
66 for n=1:N | |
67 fam = family(bnet.dag, n); | |
68 e = bnet.equiv_class(n); | |
69 pot{n} = convert_to_pot(bnet.CPD{e}, pot_type, fam(:), evidence); | |
70 end | |
71 | |
72 for i=1:S | |
73 n = soft_nodes(i); | |
74 pot{N+i} = dpot(n, ns(n), soft_evidence{n}); | |
75 end | |
76 | |
77 %clqs = engine.clq_ass_to_node([hard_nodes soft_nodes]); | |
78 %[clpot, loglik] = enter_soft_evidence(engine, clqs, pot, onodes, pot_type); | |
79 %engine.clpot = clpot; % save the results for marginal_nodes | |
80 | |
81 | |
82 clique = engine.clq_ass_to_node([hard_nodes soft_nodes]); | |
83 potential = pot; | |
84 | |
85 | |
86 % Set the clique potentials to all 1s | |
87 C = length(engine.cliques); | |
88 for i=1:C | |
89 engine.clpot{i} = mk_initial_pot(pot_type, engine.cliques{i}, ns, bnet.cnodes, onodes); | |
90 end | |
91 | |
92 % Multiply on specified potentials | |
93 for i=1:length(clique) | |
94 c = clique(i); | |
95 engine.clpot{c} = multiply_by_pot(engine.clpot{c}, potential{i}); | |
96 end | |
97 | |
98 root = 1; % arbitrary | |
99 engine = collect_evidence(engine, root); | |
100 engine = distribute_evidence(engine, root); | |
101 | |
102 ll = zeros(1, C); | |
103 for i=1:C | |
104 [engine.clpot{i}, ll(i)] = normalize_pot(engine.clpot{i}); | |
105 end | |
106 loglik = ll(1); % we can extract the likelihood from any clique | |
107 |