prob_evidence.m

来自「Bayes网络工具箱」· M 代码 · 共 41 行

function loglik = prob_evidence(engine, evidence)
% PROB_EVIDENCE Compute the likelihood of the observation sequence (fast_jtree_dbn)
% loglik = prob_evidence(engine, evidence)
%
% evidence{i,t} = [] if if X(i,t) is hidden, and otherwise contains its observed value (scalar or column vector)

[ss T] = size(evidence);
observed = ~isemptycell(evidence);
bnet = bnet_from_engine(engine);
pot_type = determine_pot_type(find(observed(:,1)), bnet.cnodes_slice, bnet.intra);
assert(pot_type == 'd');

% Convert CPDs of instantiated nodes to potential form
CPDpot = cell(ss,T);      
ns = repmat(bnet.node_sizes_slice(:), 1, T);
cnodes = repmat(bnet.cnodes_slice(:), ss, T);     
t = 1;
for n=1:ss
  fam = family(bnet.dag, n);
  e = bnet.equiv_class(n, 1);
  CPDpot{n,t} = CPD_to_table(bnet.CPD{e}, fam, ns, cnodes, evidence(:,1));
end
for n=1:ss
  fam = family(bnet.dag, n, 2);
  doms = unroll_set(fam, ss, T-1);
  e = bnet.equiv_class(n, 2);
  CPDpot(n,2:T) = CPD_to_tables(bnet.CPD{e}, doms, ns, cnodes, evidence);
end


alpha = cell(1,T);
[alpha{t}, logscale(t)] = enter_soft_evidence(engine.sub_engine1, engine.fwd1.clq_ass_to_node, ...
					   CPDpot(:,1), engine.fwd1.CPD_ndx);
clqs = [engine.fwd.clq_ass_to_cluster(:,1); engine.fwd.clq_ass_to_node(:,2)];
ndx = [engine.fwd.cluster_ndx(:,1); engine.fwd.CPD_ndx(:,2)];
for t=2:T
  pots = [alpha(:,t-1); CPDpot(:,t)];
  [alpha{t}, logscale(t)] = enter_soft_evidence(engine.fwd.engine, clqs, pots, ndx);
end
loglik = sum(logscale);