Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/bnt/inference/static/@jtree_inf_engine/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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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;