Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/bnt/inference/static/@belprop_fg_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, ll, niter] = enter_evidence(engine, evidence, varargin) % ENTER_EVIDENCE Propagate evidence using belief propagation % [engine, ll, niter] = enter_evidence(engine, evidence, ...) % % The log-likelihood is not computed; ll = 0. % niter contains the number of iterations used % % The following optional arguments can be specified in the form of name/value pairs: % [default value in brackets] % % maximize - 1 means use max-product, 0 means use sum-product [0] % % e.g., engine = enter_evidence(engine, ev, 'maximize', 1) ll = 0; maximize = 0; if nargin >= 3 args = varargin; nargs = length(args); for i=1:2:nargs switch args{i}, case 'maximize', maximize = args{i+1}; otherwise, error(['invalid argument name ' args{i}]); end end end verbose = 0; ns = engine.fgraph.node_sizes; onodes = find(~isemptycell(evidence)); hnodes = find(isemptycell(evidence)); cnodes = engine.fgraph.cnodes; pot_type = determine_pot_type(engine.fgraph, onodes); % prime each local kernel with evidence (if any) nfactors = engine.fgraph.nfactors; nvars = engine.fgraph.nvars; factors = cell(1,nfactors); for f=1:nfactors K = engine.fgraph.factors{engine.fgraph.equiv_class(f)}; factors{f} = convert_to_pot(K, pot_type, engine.fgraph.dom{f}(:), evidence); end % initialise msgs msg_var_to_fac = cell(nvars, nfactors); for x=1:nvars for f=engine.fgraph.dep{x} msg_var_to_fac{x,f} = mk_initial_pot(pot_type, x, ns, cnodes, onodes); end end msg_fac_to_var = cell(nfactors, nvars); dom = cell(1, nfactors); for f=1:nfactors %hdom{f} = myintersect(engine.fgraph.dom{f}, hnodes); dom{f} = engine.fgraph.dom{f}(:)'; for x=dom{f} msg_fac_to_var{f,x} = mk_initial_pot(pot_type, x, ns, cnodes, onodes); %msg_fac_to_var{f,x} = marginalize_pot(factors{f}, x); end end converged = 0; iter = 1; var_prod = cell(1, nvars); fac_prod = cell(1, nfactors); while ~converged & (iter <= engine.max_iter) if verbose, fprintf('iter %d\n', iter); end % absorb old_var_prod = var_prod; for x=1:nvars var_prod{x} = mk_initial_pot(pot_type, x, ns, cnodes, onodes); for f=engine.fgraph.dep{x} var_prod{x} = multiply_by_pot(var_prod{x}, msg_fac_to_var{f,x}); end end for f=1:nfactors fac_prod{f} = mk_initial_pot(pot_type, dom{f}, ns, cnodes, onodes); for x=dom{f} fac_prod{f} = multiply_by_pot(fac_prod{f}, msg_var_to_fac{x,f}); end end % send msgs to neighbors old_msg_var_to_fac = msg_var_to_fac; old_msg_fac_to_var = msg_fac_to_var; converged = 1; for x=1:nvars %if verbose, disp(['var ' num2str(x) ' sending to fac ' num2str(engine.fgraph.dep{x})]); end for f=engine.fgraph.dep{x} temp = divide_by_pot(var_prod{x}, old_msg_fac_to_var{f,x}); msg_var_to_fac{x,f} = normalize_pot(temp); if ~approxeq_pot(msg_var_to_fac{x,f}, old_msg_var_to_fac{x,f}, engine.tol), converged = 0; end end end for f=1:nfactors %if verbose, disp(['fac ' num2str(f) ' sending to var ' num2str(dom{f})]); end for x=dom{f} temp = divide_by_pot(fac_prod{f}, old_msg_var_to_fac{x,f}); temp2 = multiply_by_pot(factors{f}, temp); temp3 = marginalize_pot(temp2, x, maximize); msg_fac_to_var{f,x} = normalize_pot(temp3); if ~approxeq_pot(msg_fac_to_var{f,x}, old_msg_fac_to_var{f,x}, engine.tol), converged = 0; end end end if iter==1 converged = 0; end iter = iter + 1; end niter = iter - 1; engine.niter = niter; for x=1:nvars engine.marginal_nodes{x} = normalize_pot(var_prod{x}); end