annotate toolboxes/FullBNT-1.0.7/bnt/general/Old/calc_mpe.m @ 0:e9a9cd732c1e tip

first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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wolffd@0 1 function [mpe, ll] = calc_mpe(engine, evidence, break_ties)
wolffd@0 2 % CALC_MPE Computes the most probable explanation of the evidence
wolffd@0 3 % [mpe, ll] = calc_mpe_given_inf_engine(engine, evidence, break_ties)
wolffd@0 4 %
wolffd@0 5 % INPUT
wolffd@0 6 % engine must support max-propagation
wolffd@0 7 % evidence{i} is the observed value of node i, or [] if hidden
wolffd@0 8 % break_ties is optional. If 1, we will force ties to be broken consistently
wolffd@0 9 % by calling enter_evidence N times.
wolffd@0 10 %
wolffd@0 11 % OUTPUT
wolffd@0 12 % mpe{i} is the most likely value of node i (cell array!)
wolffd@0 13 % ll is the log-likelihood of the globally best assignment
wolffd@0 14 %
wolffd@0 15 % This currently only works when all hidden nodes are discrete
wolffd@0 16
wolffd@0 17 if nargin < 3, break_ties = 0; end
wolffd@0 18
wolffd@0 19
wolffd@0 20 [engine, ll] = enter_evidence(engine, evidence, 'maximize', 1);
wolffd@0 21
wolffd@0 22 observed = ~isemptycell(evidence);
wolffd@0 23
wolffd@0 24 if 0 % fgraphs don't support bnet_from_engine
wolffd@0 25 onodes = find(observed);
wolffd@0 26 bnet = bnet_from_engine(engine);
wolffd@0 27 pot_type = determine_pot_type(bnet, onodes);
wolffd@0 28 assert(pot_type == 'd');
wolffd@0 29 end
wolffd@0 30
wolffd@0 31 scalar = 1;
wolffd@0 32 evidence = evidence(:); % hack to handle unrolled DBNs
wolffd@0 33 N = length(evidence);
wolffd@0 34 mpe = cell(1,N);
wolffd@0 35 for i=1:N
wolffd@0 36 m = marginal_nodes(engine, i);
wolffd@0 37 % observed nodes are all set to 1 inside the inference engine, so we must undo this
wolffd@0 38 if observed(i)
wolffd@0 39 mpe{i} = evidence{i};
wolffd@0 40 else
wolffd@0 41 mpe{i} = argmax(m.T);
wolffd@0 42 % Bug fix by Ron Zohar, 8/15/01
wolffd@0 43 % If there are ties, we must break them as follows (see Jensen96, p106)
wolffd@0 44 if break_ties
wolffd@0 45 evidence{i} = mpe{i};
wolffd@0 46 [engine, ll] = enter_evidence(engine, evidence, 'maximize', 1);
wolffd@0 47 end
wolffd@0 48 end
wolffd@0 49 if length(mpe{i}) > 1, scalar = 0; end
wolffd@0 50 end
wolffd@0 51
wolffd@0 52 if nargout >= 2
wolffd@0 53 bnet = bnet_from_engine(engine);
wolffd@0 54 ll = log_lik_complete(bnet, mpe(:));
wolffd@0 55 end
wolffd@0 56 if 0 % scalar
wolffd@0 57 mpe = cell2num(mpe);
wolffd@0 58 end