Mercurial > hg > camir-aes2014
diff toolboxes/FullBNT-1.0.7/bnt/inference/static/@jtree_inf_engine/enter_evidence.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
---|---|
date | Tue, 10 Feb 2015 15:05:51 +0000 |
parents | |
children |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/bnt/inference/static/@jtree_inf_engine/enter_evidence.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,88 @@ +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] +% +% 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) + +bnet = bnet_from_engine(engine); +ns = bnet.node_sizes(:); +N = length(bnet.dag); + +engine.evidence = evidence; % store this for marginal_nodes with add_ev option +engine.maximize = 0; + +% set default params +exclude = []; +soft_evidence = cell(1,N); + +% parse optional params +args = varargin; +nargs = length(args); +for i=1:2:nargs + switch args{i}, + case 'soft', soft_evidence = args{i+1}; + case 'maximize', engine.maximize = args{i+1}; + otherwise, + error(['invalid argument name ' args{i}]); + end +end + +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 + +if is_mnet(bnet) + pot = engine.user_pot; + clqs = engine.nums_ass_to_user_clqs; +else + % Evaluate CPDs with evidence, and convert to potentials + pot = cell(1, N); + for n=1:N + fam = family(bnet.dag, n); + e = bnet.equiv_class(n); + if isempty(bnet.CPD{e}) + error(['must define CPD ' num2str(e)]) + else + pot{n} = convert_to_pot(bnet.CPD{e}, pot_type, fam(:), evidence); + end + end + clqs = engine.clq_ass_to_node(1:N); +end + +% soft evidence +soft_nodes = find(~isemptycell(soft_evidence)); +S = length(soft_nodes); +if S > 0 + assert(pot_type == 'd'); + assert(mysubset(soft_nodes, bnet.dnodes)); +end +for i=1:S + n = soft_nodes(i); + pot{end+1} = dpot(n, ns(n), soft_evidence{n}); +end +clqs = [clqs engine.clq_ass_to_node(soft_nodes)]; + + +[clpot, seppot] = init_pot(engine, clqs, pot, pot_type, onodes); +[clpot, seppot] = collect_evidence(engine, clpot, seppot); +[clpot, seppot] = distribute_evidence(engine, clpot, seppot); + +C = length(clpot); +ll = zeros(1, C); +for i=1:C + [clpot{i}, ll(i)] = normalize_pot(clpot{i}); +end +loglik = ll(1); % we can extract the likelihood from any clique + +engine.clpot = clpot;