Mercurial > hg > camir-aes2014
diff 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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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/bnt/inference/static/@jtree_inf_engine/Old/enter_evidence.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,107 @@ +function [engine, loglik] = enter_evidence(engine, evidence, varargin) +% ENTER_EVIDENCE Add the specified evidence to the network (jtree) +% [engine, loglik] = enter_evidence(engine, evidence, ...) +% +% evidence{i} = [] if X(i) is hidden, and otherwise contains its observed value (scalar or column vector). +% +% The following optional arguments can be specified in the form of name/value pairs: +% [default value in brackets] +% +% maximize - if 1, does max-product instead of sum-product [0] +% soft - a cell array of soft/virtual evidence; +% soft{i} is a prob. distrib. over i's values, or [] [ cell(1,N) ] +% +% e.g., engine = enter_evidence(engine, ev, 'soft', soft_ev) +% +% For backwards compatibility with BNT2, you can also specify the parameters in the following order +% engine = enter_evidence(engine, ev, soft_ev) + +bnet = bnet_from_engine(engine); +ns = bnet.node_sizes(:); +N = length(bnet.dag); + +% set default params +exclude = []; +soft_evidence = cell(1,N); +maximize = 0; + +% parse optional params +args = varargin; +nargs = length(args); +if nargs > 0 + if iscell(args{1}) + soft_evidence = args{1}; + else + for i=1:2:nargs + switch args{i}, + case 'soft', soft_evidence = args{i+1}; + case 'maximize', maximize = args{i+1}; + otherwise, + error(['invalid argument name ' args{i}]); + end + end + end +end + +engine.maximize = maximize; + +onodes = find(~isemptycell(evidence)); +hnodes = find(isemptycell(evidence)); +pot_type = determine_pot_type(bnet, onodes); + if strcmp(pot_type, 'cg') + check_for_cd_arcs(onodes, bnet.cnodes, bnet.dag); +end + + +hard_nodes = 1:N; +soft_nodes = find(~isemptycell(soft_evidence)); +S = length(soft_nodes); +if S > 0 + assert(pot_type == 'd'); + assert(mysubset(soft_nodes, bnet.dnodes)); +end + +% Evaluate CPDs with evidence, and convert to potentials +pot = cell(1, N+S); +for n=1:N + fam = family(bnet.dag, n); + e = bnet.equiv_class(n); + pot{n} = convert_to_pot(bnet.CPD{e}, pot_type, fam(:), evidence); +end + +for i=1:S + n = soft_nodes(i); + pot{N+i} = dpot(n, ns(n), soft_evidence{n}); +end + +%clqs = engine.clq_ass_to_node([hard_nodes soft_nodes]); +%[clpot, loglik] = enter_soft_evidence(engine, clqs, pot, onodes, pot_type); +%engine.clpot = clpot; % save the results for marginal_nodes + + +clique = engine.clq_ass_to_node([hard_nodes soft_nodes]); +potential = pot; + + +% Set the clique potentials to all 1s +C = length(engine.cliques); +for i=1:C + engine.clpot{i} = mk_initial_pot(pot_type, engine.cliques{i}, ns, bnet.cnodes, onodes); +end + +% Multiply on specified potentials +for i=1:length(clique) + c = clique(i); + engine.clpot{c} = multiply_by_pot(engine.clpot{c}, potential{i}); +end + +root = 1; % arbitrary +engine = collect_evidence(engine, root); +engine = distribute_evidence(engine, root); + +ll = zeros(1, C); +for i=1:C + [engine.clpot{i}, ll(i)] = normalize_pot(engine.clpot{i}); +end +loglik = ll(1); % we can extract the likelihood from any clique +