comparison toolboxes/FullBNT-1.0.7/bnt/inference/dynamic/@bk_ff_hmm_inf_engine/enter_evidence.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function [engine, loglik] = enter_evidence(engine, evidence, varargin)
+% ENTER_EVIDENCE Add the specified evidence to the network (bk_ff_hmm)
+% [engine, loglik] = enter_evidence(engine, evidence, ...)
+%
+% evidence{i,t} = [] if if X(i,t) 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]
+%
+% maximize - if 1, does max-product (not yet supported), else sum-product [0]
+% filter -   if 1, do filtering, else smoothing [0]
+%
+% e.g., engine = enter_evidence(engine, ev, 'maximize', 1)
+
+maximize = 0;
+filter = 0;
+
+% parse optional params
+args = varargin;
+nargs = length(args);
+if nargs > 0
+  for i=1:2:nargs
+    switch args{i},
+     case 'maximize', maximize = args{i+1}; 
+     case 'filter', filter = args{i+1}; 
+     otherwise,  
+      error(['invalid argument name ' args{i}]);       
+    end
+  end
+end
+
+assert(~maximize);
+
+bnet = bnet_from_engine(engine);
+ss = length(bnet.intra);
+onodes = bnet.observed;
+hnodes = mysetdiff(1:ss, onodes);
+T = size(evidence, 2);
+assertBNT(~any(isemptycell(evidence(onodes,:))));
+
+obslik = mk_hmm_obs_lik_mat(bnet, onodes, evidence);
+
+ns = bnet.node_sizes_slice;
+ns(onodes) = 1;
+
+[gamma, loglik, marginals, marginalsT] = bk_ff_fb(engine.prior, engine.transmat, obslik, filter, hnodes, ns);
+  
+for t=1:T
+  for i=hnodes(:)'
+    engine.marginals{i,t} = pot_to_marginal(marginalsT{i,t});
+  end
+  for i=onodes(:)'
+    m.domain = i + (t-1)*ss;
+    m.T = 1;
+    engine.marginals{i,t} = m;
+  end
+end
+
+
+