diff toolboxes/FullBNT-1.0.7/bnt/examples/static/Belprop/belprop_loop1_gauss.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/examples/static/Belprop/belprop_loop1_gauss.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,25 @@
+% Compare different loopy belief propagation algorithms on a graph with a single loop.
+% LBP should give exact results if it converges.
+
+N = 4;
+dag = zeros(N,N);
+C = 1; S = 2; R = 3; W = 4;
+dag(C,[R S]) = 1;
+dag(R,W) = 1;
+dag(S,W)=1;
+ns = 2*ones(1,N); 
+bnet = mk_bnet(dag, ns, 'discrete', []);
+for i=1:N
+  bnet.CPD{i} = gaussian_CPD(bnet, i);
+end
+
+engines = {};
+engines{end+1} = jtree_inf_engine(bnet);
+engines{end+1} = pearl_inf_engine(bnet, 'protocol', 'parallel', 'max_iter', 20);
+%engines{end+1} = pearl_inf_engine(bnet, 'protocol', 'parallel', 'max_iter', 20, 'filename', ...
+%				  '/home/eecs/murphyk/matlab/gausspearl.txt', 'tol', 1e-5);
+
+% pearl gaussian does not compute loglik
+[time, engines] = cmp_inference_static(bnet, engines, 'maximize', 0, 'exact', 1, 'observed', [2], ...
+				   'check_ll', 0, 'singletons_only', 0, 'check_converged', [2]);
+