diff toolboxes/FullBNT-1.0.7/bnt/general/Old/calc_mpe_dbn.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/bnt/general/Old/calc_mpe_dbn.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,41 @@
+function [mpe, ll] = calc_mpe_dbn(engine, evidence, break_ties)
+% CALC_MPE Computes the most probable explanation of the evidence
+% [mpe, ll] = calc_mpe_dbn(engine, evidence, break_ties)
+%
+% INPUT
+% engine must support max-propagation
+% evidence{i,t} is the observed value of node i in slice t, or [] if hidden
+%
+% OUTPUT
+% mpe{i,t} is the most likely value of node i (cell array!)
+% ll is the log-likelihood of the globally best assignment
+%
+% This currently only works when all hidden nodes are discrete
+
+if nargin < 3, break_ties = 0; end
+
+if break_ties
+  disp('warning: break ties is ignored')
+end
+
+[engine, ll] = enter_evidence(engine, evidence, 'maximize', 1);
+
+observed = ~isemptycell(evidence);
+[ss T] = size(evidence);
+scalar = 1;
+N = length(evidence);
+mpe = cell(ss,T);
+bnet = bnet_from_engine(engine);
+ns = bnet.node_sizes;
+for t=1:T
+  for i=1:ss
+    m = marginal_nodes(engine, i, t);
+    % observed nodes are all set to 1 inside the inference engine, so we must undo this
+    if observed(i,t)
+      mpe{i,t} = evidence{i,t};
+    else
+      assert(length(m.T) == ns(i));
+      mpe{i,t} = argmax(m.T);
+    end
+  end
+end