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view toolboxes/FullBNT-1.0.7/bnt/inference/dynamic/@pearl_dbn_inf_engine/Old/correct_smooth.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 [marginal, msg, loglik] = smooth_evidence(engine, evidence) % [marginal, msg, loglik] = smooth_evidence(engine, evidence) (pearl_dbn) disp('warning: broken'); [ss T] = size(evidence); bnet = bnet_from_engine(engine); bnet2 = dbn_to_bnet(bnet, T); ns = bnet2.node_sizes; hnodes = mysetdiff(1:ss, engine.onodes); hnodes = hnodes(:)'; onodes2 = unroll_set(engine.onodes(:), ss, T); onodes2 = onodes2(:)'; hnodes2 = unroll_set(hnodes(:), ss, T); hnodes2 = hnodes2(:)'; [engine.parent_index, engine.child_index] = mk_pearl_msg_indices(bnet2); msg = init_msgs(bnet2.dag, ns, evidence, bnet2.equiv_class, bnet2.CPD); verbose = 0; niter = 1; for iter=1:niter % FORWARD for t=1:T if verbose, fprintf('t=%d\n', t); end % observed leaves send lambda to parents for i=engine.onodes(:)' n = i + (t-1)*ss; ps = parents(bnet2.dag, n); for p=ps(:)' j = engine.child_index{p}(n); % n is p's j'th child if t > 1 e = bnet.equiv_class(i, 2); else e = bnet.equiv_class(i, 1); end lam_msg = normalise(compute_lambda_msg(bnet.CPD{e}, n, ps, msg, p)); msg{p}.lambda_from_child{j} = lam_msg; if verbose, fprintf('%d sends lambda to %d\n', n, p); disp(lam_msg); end end end % update pi for i=hnodes n = i + (t-1)*ss; ps = parents(bnet2.dag, n); if t==1 e = bnet.equiv_class(i,1); else e = bnet.equiv_class(i,2); end msg{n}.pi = compute_pi(bnet.CPD{e}, n, ps, msg); if verbose, fprintf('%d computes pi\n', n); disp(msg{n}.pi); end end % send pi msg to children for i=hnodes n = i + (t-1)*ss; %cs = myintersect(children(bnet2.dag, n), hnodes2); cs = children(bnet2.dag, n); for c=cs(:)' j = engine.parent_index{c}(n); % n is c's j'th parent pi_msg = normalise(compute_pi_msg(n, cs, msg, c, ns)); msg{c}.pi_from_parent{j} = pi_msg; if verbose, fprintf('%d sends pi to %d\n', n, c); disp(pi_msg); end end end end % BACKWARD for t=T:-1:1 if verbose, fprintf('t = %d\n', t); end % update lambda for i=hnodes n = i + (t-1)*ss; cs = children(bnet2.dag, n); msg{n}.lambda = compute_lambda(n, cs, msg, ns); if verbose, fprintf('%d computes lambda\n', n); disp(msg{n}.lambda); end end % send lambda msgs to parents for i=hnodes n = i + (t-1)*ss; %ps = myintersect(parents(bnet2.dag, n), hnodes2); ps = parents(bnet2.dag, n); for p=ps(:)' j = engine.child_index{p}(n); % n is p's j'th child if t > 1 e = bnet.equiv_class(i, 2); else e = bnet.equiv_class(i, 1); end lam_msg = normalise(compute_lambda_msg(bnet.CPD{e}, n, ps, msg, p)); msg{p}.lambda_from_child{j} = lam_msg; if verbose, fprintf('%d sends lambda to %d\n', n, p); disp(lam_msg); end end end end end marginal = cell(ss,T); lik = zeros(1,ss*T); for t=1:T for i=1:ss n = i + (t-1)*ss; [bel, lik(n)] = normalise(msg{n}.pi .* msg{n}.lambda); marginal{i,t} = bel; end end loglik = sum(log(lik)); %%%%%%% function lambda = compute_lambda(n, cs, msg, ns) % Pearl p183 eq 4.50 lambda = prod_lambda_msgs(n, cs, msg, ns); %%%%%%% function pi_msg = compute_pi_msg(n, cs, msg, c, ns) % Pearl p183 eq 4.53 and 4.51 pi_msg = msg{n}.pi .* prod_lambda_msgs(n, cs, msg, ns, c); %%%%%%%%% function lam = prod_lambda_msgs(n, cs, msg, ns, except) if nargin < 5, except = -1; end lam = msg{n}.lambda_from_self(:); lam = ones(ns(n), 1); for i=1:length(cs) c = cs(i); if c ~= except lam = lam .* msg{n}.lambda_from_child{i}; end end %%%%%%%%% function msg = init_msgs(dag, ns, evidence, eclass, CPD) % INIT_MSGS Initialize the lambda/pi message and state vectors (pearl_dbn) % msg = init_msgs(dag, ns, evidence) N = length(dag); msg = cell(1,N); observed = ~isemptycell(evidence(:)); for n=1:N ps = parents(dag, n); msg{n}.pi_from_parent = cell(1, length(ps)); for i=1:length(ps) p = ps(i); msg{n}.pi_from_parent{i} = ones(ns(p), 1); end cs = children(dag, n); msg{n}.lambda_from_child = cell(1, length(cs)); for i=1:length(cs) c = cs(i); msg{n}.lambda_from_child{i} = ones(ns(n), 1); end msg{n}.lambda = ones(ns(n), 1); msg{n}.lambda_from_self = ones(ns(n), 1); msg{n}.pi = ones(ns(n), 1); % Initialize the lambdas with any evidence if observed(n) v = evidence{n}; %msg{n}.lambda_from_self = zeros(ns(n), 1); %msg{n}.lambda_from_self(v) = 1; % delta function msg{n}.lambda = zeros(ns(n), 1); msg{n}.lambda(v) = 1; % delta function end end %%%%%%%% function msg = init_ev_msgs(engine, evidence, msg) [ss T] = size(evidence); bnet = bnet_from_engine(engine); pot_type = 'd'; t = 1; hnodes = mysetdiff(1:ss, engine.onodes); for i=engine.onodes(:)' fam = family(bnet.dag, i); e = bnet.equiv_class(i, 1); CPDpot = CPD_to_pot(pot_type, bnet.CPD{e}, fam, bnet.node_sizes(:), bnet.cnodes(:), evidence(:,1)); temp = pot_to_marginal(CPDpot); msg{i}.lambda_from_self = temp.T; end for t=2:T for i=engine.onodes(:)' fam = family(bnet.dag, i, 2); % extract from slice t e = bnet.equiv_class(i, 2); CPDpot = CPD_to_pot(pot_type, bnet.CPD{e}, fam, bnet.node_sizes(:), bnet.cnodes(:), evidence(:,t-1:t)); temp = pot_to_marginal(CPDpot); n = i + (t-1)*ss; msg{n}.lambda_from_self = temp.T; end end %%%%%%%%%%% function msg = init_ev_msgs2(engine, evidence, msg) [ss T] = size(evidence); bnet = bnet_from_engine(engine); pot_type = 'd'; t = 1; hnodes = mysetdiff(1:ss, engine.onodes); for i=engine.onodes(:)' fam = family(bnet.dag, i); e = bnet.equiv_class(i, 1); CPDpot = CPD_to_pot(pot_type, bnet.CPD{e}, fam, bnet.node_sizes(:), bnet.cnodes(:), evidence(:,1)); temp = pot_to_marginal(CPDpot); msg{i}.lambda_from_self = temp.T; end for t=2:T for i=engine.onodes(:)' fam = family(bnet.dag, i, 2); % extract from slice t e = bnet.equiv_class(i, 2); CPDpot = CPD_to_pot(pot_type, bnet.CPD{e}, fam, bnet.node_sizes(:), bnet.cnodes(:), evidence(:,t-1:t)); temp = pot_to_marginal(CPDpot); n = i + (t-1)*ss; msg{n}.lambda_from_self = temp.T; end end