diff toolboxes/FullBNT-1.0.7/bnt/inference/dynamic/@bk_ff_hmm_inf_engine/private/dbn_to_hmm.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/inference/dynamic/@bk_ff_hmm_inf_engine/private/dbn_to_hmm.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,41 @@
+function [prior, transmat] = dbn_to_hmm(bnet)
+% DBN_TO_HMM Compute the discrete HMM matrices from a simple DBN
+% [prior, transmat] = dbn_to_hmm(bnet)
+
+onodes = bnet.observed;
+ss = length(bnet.intra);
+evidence = cell(1,2*ss);
+hnodes = mysetdiff(1:ss, onodes);
+prior = multiply_CPTs(bnet, [], hnodes, evidence);
+transmat = multiply_CPTs(bnet, hnodes, hnodes+ss, evidence);
+%obsmat1 = multiply_CPTs(bnet, hnodes, onodes, evidence);
+%obsmat = multiply_CPTs(bnet, hnodes+ss, onodes+ss, evidence);
+%obsmat1 = obsmat if the observation matrices are tied across slices
+
+
+
+%%%%%%%%%%%%
+
+function mat = multiply_CPTs(bnet, pdom, cdom, evidence)
+
+% MULTIPLY_CPTS Make a matrix Pr(Y|X), where X represents all the parents, and Y all the children
+% We assume the children have no intra-connections.
+%
+% e.g., Consider the DBN with interconnectivity i->i', j->j',k', k->i',k'
+% Then transition matrix = Pr(i,j,k -> i',j',k') = Pr(i,k->i') Pr(j->j') Pr(j,k->k')
+
+dom = [pdom cdom];
+ns = bnet.node_sizes;
+bigpot = dpot(dom, ns(dom));
+for j=cdom(:)'
+  e = bnet.equiv_class(j);
+  fam = family(bnet.dag, j);
+  pot = convert_to_pot(bnet.CPD{e}, 'd', fam(:), evidence);
+  bigpot = multiply_by_pot(bigpot, pot);
+end
+psize = prod(ns(pdom));
+csize = prod(ns(cdom));
+T = pot_to_marginal(bigpot);
+mat = reshape(T.T, [psize csize]);
+
+