camir-aes2014: toolboxes/FullBNT-1.0.7/bnt/general/Old/calc_mpe

first hg version after svn

rev	line source
wolffd@0	1 function [mpe, ll] = calc_mpe_dbn(engine, evidence, break_ties)
wolffd@0	2 % CALC_MPE Computes the most probable explanation of the evidence
wolffd@0	3 % [mpe, ll] = calc_mpe_dbn(engine, evidence, break_ties)
wolffd@0	4 %
wolffd@0	5 % INPUT
wolffd@0	6 % engine must support max-propagation
wolffd@0	7 % evidence{i,t} is the observed value of node i in slice t, or [] if hidden
wolffd@0	8 %
wolffd@0	9 % OUTPUT
wolffd@0	10 % mpe{i,t} is the most likely value of node i (cell array!)
wolffd@0	11 % ll is the log-likelihood of the globally best assignment
wolffd@0	12 %
wolffd@0	13 % This currently only works when all hidden nodes are discrete
wolffd@0	14
wolffd@0	15 if nargin < 3, break_ties = 0; end
wolffd@0	16
wolffd@0	17 if break_ties
wolffd@0	18 disp('warning: break ties is ignored')
wolffd@0	19 end
wolffd@0	20
wolffd@0	21 [engine, ll] = enter_evidence(engine, evidence, 'maximize', 1);
wolffd@0	22
wolffd@0	23 observed = ~isemptycell(evidence);
wolffd@0	24 [ss T] = size(evidence);
wolffd@0	25 scalar = 1;
wolffd@0	26 N = length(evidence);
wolffd@0	27 mpe = cell(ss,T);
wolffd@0	28 bnet = bnet_from_engine(engine);
wolffd@0	29 ns = bnet.node_sizes;
wolffd@0	30 for t=1:T
wolffd@0	31 for i=1:ss
wolffd@0	32 m = marginal_nodes(engine, i, t);
wolffd@0	33 % observed nodes are all set to 1 inside the inference engine, so we must undo this
wolffd@0	34 if observed(i,t)
wolffd@0	35 mpe{i,t} = evidence{i,t};
wolffd@0	36 else
wolffd@0	37 assert(length(m.T) == ns(i));
wolffd@0	38 mpe{i,t} = argmax(m.T);
wolffd@0	39 end
wolffd@0	40 end
wolffd@0	41 end

Mercurial > hg > camir-aes2014