diff toolboxes/FullBNT-1.0.7/bnt/general/fgraph_to_bnet.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/fgraph_to_bnet.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,30 @@
+function bnet = fgraph_to_bnet(fg)
+% FGRAPH_TO_BNET Convert a factor graph to a Bayes net
+% bnet = fgraph_to_bnet(fg)
+%
+% We assume all factors are tabular_CPD.
+% We create 1 dummy observed node for every factor.
+
+N = fg.nvars + fg.nfactors;
+vnodes = 1:fg.nvars;
+fnodes = fg.nvars+1:N;
+dag = zeros(N);
+for x=1:fg.nvars
+  dag(x, fnodes(fg.dep{x})) = 1;
+end
+ns = [fg.node_sizes ones(1, fg.nfactors)];
+discrete = [fg.dnodes fnodes];
+bnet = mk_bnet(dag, ns, 'discrete', discrete);
+for x=1:fg.nvars
+  bnet.CPD{x} = tabular_CPD(bnet, x, 'CPT', 'unif');
+end
+ev = cell(1, fg.nvars); % no evidence
+for i=1:fg.nfactors
+  f = fnodes(i);
+  e = fg.equiv_class(i);
+  pot = convert_to_pot(fg.factors{e}, 'd', fg.dom{i}, ev);
+  m = pot_to_marginal(pot);
+  bnet.CPD{f} = tabular_CPD(bnet, f, 'CPT', m.T);
+end
+  
+