comparison toolboxes/FullBNT-1.0.7/bnt/examples/static/gibbs_test1.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function gibbs_test1()
+
+disp('gibbs test 1')
+
+rand('state', 0);
+randn('state', 0);
+
+%[bnet onodes hnodes qnodes] = gibbs_ex_1;
+[bnet onodes hnodes qnodes] = gibbs_ex_2;
+
+je = jtree_inf_engine(bnet);
+ge = gibbs_sampling_inf_engine (bnet, 'T', 50, 'burnin', 0, ...
+				'order', [2 2 1 2 1]);
+
+ev = sample_bnet(bnet);
+
+evidence = cell(length(bnet.dag), 1);
+evidence(onodes) = ev(onodes);
+[je lj] = enter_evidence(je, evidence);
+[ge lg] = enter_evidence(ge, evidence);
+
+
+mj = marginal_nodes(je, qnodes);
+
+[mg ge] = marginal_nodes (ge, qnodes);
+for t = 1:100
+  [mg ge] = marginal_nodes (ge, qnodes, 'reset_counts', 0);
+  diff = mj.T - mg.T;
+  err(t) = norm (diff(:), 1);
+end
+clf
+plot(err);
+%title('error vs num. Gibbs samples')
+
+
+%%%%%%%
+
+function [bnet, onodes, hnodes, qnodes] = gibbs_ex_1
+% bnet = gibbs_ex_1
+% a simple network to test the gibbs sampling engine
+%    1
+%  / | \
+% 2  3  4
+% |  |  |
+% 5  6  7
+%  \/ \/
+%  8   9
+% where all arcs point downwards
+
+N = 9;
+dag = zeros(N,N);
+dag(1,2)=1; dag(1,3)=1; dag(1,4)=1;
+dag(2,5)=1; dag(3,6)=1; dag(4,7)=1;
+dag(5,8)=1; dag(6,8)=1; dag(6,9)=1; dag(7,9) = 1;
+
+onodes = 8:9;
+hnodes = 1:7;
+qnodes = [1 2 6];
+ns = [2 3 4 3 5 2 4 3 2];
+
+eclass = [1 2 3 2 4 5 6 7 8];
+
+bnet = mk_bnet (dag, ns, 'equiv_class', eclass);
+
+for i = 1:3
+  bnet.CPD{i} = tabular_CPD(bnet, i);
+end
+
+for i = 4:8
+  bnet.CPD{i} = tabular_CPD(bnet, i+1);
+end
+
+
+
+%%%%%%%
+
+function [bnet, onodes, hnodes, qnodes] = gibbs_ex_2
+% bnet = gibbs_ex_2
+% a very simple network
+%
+% 1   2
+%  \ /
+%   3
+
+N = 3;
+dag = zeros(N,N);
+dag(1,3)=1; dag(2,3)=1;
+
+onodes = 3;
+hnodes = 1:2;
+qnodes = 1:2;
+ns = [2 4 3];
+
+eclass = [1 2 3];
+
+bnet = mk_bnet (dag, ns, 'equiv_class', eclass);
+
+for i = 1:3
+  bnet.CPD{i} = tabular_CPD(bnet, i);
+end
+
+
+
+
+
+
+