enter_soft_evidence.m

来自「Bayes网络工具箱」· M 代码 · 共 50 行

function [clpot, loglik] = enter_soft_evidence(engine, CPDpot, observed, filter)
% ENTER_SOFT_EVIDENCE Add the specified evidence to the network (jtree_dbn_fast)
% [clpot, loglik] = enter_soft_evidence(engine, CPDpot, observed, filter)

assert(filter == 0); % this code is designed for smoothing

[ss T] = size(CPDpot);  

% Forwards
alpha = cell(1,T);
t = 1;
[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);

% Backwards
beta = cell(1,T);
t = T;
bnet = bnet_from_engine(engine);
ns = bnet.node_sizes(:);
ns(find(observed(:,t-1:t))) = 1;
dom = (1:ss) + ss;
beta{t} = myones(ns(dom));

clqs = [engine.back.clq_ass_to_cluster(:,2); engine.back.clq_ass_to_node(:,2)];
ndx = [engine.back.cluster_ndx(:,2); engine.back.CPD_ndx(:,2)];
for t=T-1:-1:1
  pots = [beta(:,t+1); CPDpot(:,t+1)];
  beta{t} = enter_soft_evidence(engine.back.engine, clqs, pots, ndx);
end

% Combine
Q = length(cliques_from_engine(engine.sub_engine));
clpot = cell(Q,T); % clpot{t} contains evidence from slices t-1, t for t > 1
clqs = [engine.fb.clq_ass_to_cluster(:); engine.fb.clq_ass_to_node(:,2)];
ndx = [engine.fb.cluster_ndx(:); engine.fb.CPD_ndx(:,2)];
for t=1:T-1
  pots = [alpha(:,t); beta(:,t+1); CPDpot(:,t+1)];
  clpot(:,t+1) = enter_soft_evidence(engine.sub_engine, clqs, pots, ndx);
end