diff toolboxes/FullBNT-1.0.7/bnt/examples/static/Belprop/gmux1.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/gmux1.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,90 @@
+% Test gmux.
+% The following model, where Y is a gmux node,
+% and M is set to 1, should be equivalent to X1 -> Y
+%
+% X1 Xn M
+% \ |  /
+%   Y
+
+n = 3;
+N = n+2;
+Xs = 1:n;
+M = n+1; 
+Y = n+2;
+dag = zeros(N,N);
+dag([Xs M], Y)=1; 
+
+dnodes = M;
+ns = zeros(1, N);
+sz = 2;
+ns(Xs) = sz;
+ns(M) = n;
+ns(Y) = sz;
+
+bnet = mk_bnet(dag, ns, 'discrete', M, 'observed', [M Y]);
+
+psz = ns(Xs(1));
+selfsz = ns(Y);
+
+W = randn(selfsz, psz);
+mu = randn(selfsz, 1);
+Sigma = eye(selfsz, selfsz);
+
+bnet.CPD{M} = root_CPD(bnet, M);
+for i=Xs(:)'
+  bnet.CPD{i} = gaussian_CPD(bnet, i, 'mean', zeros(psz, 1), 'cov', eye(psz, psz));
+end
+bnet.CPD{Y} = gmux_CPD(bnet, Y, 'mean', mu, 'weights', W, 'cov', Sigma);
+  
+evidence = cell(1,N);
+yval = randn(selfsz, 1);
+evidence{Y} = yval;
+m = 2;
+%notm = not(m-1)+1; % only valid for n=2
+notm = mysetdiff(1:n, m);
+evidence{M} = m;
+
+engines = {};
+engines{end+1} = jtree_inf_engine(bnet);
+engines{end+1} = pearl_inf_engine(bnet, 'protocol', 'parallel');
+
+for e=1:length(engines)
+  engines{e} = enter_evidence(engines{e}, evidence);
+  mXm{e} = marginal_nodes(engines{e}, Xs(m));
+
+  % Since M=m, only Xm was updated.
+  % Hence the posterior on Xnotm should equal the prior.
+  for i=notm(:)'
+    mXnotm = marginal_nodes(engines{e}, Xs(i));
+    assert(approxeq(mXnotm.mu, zeros(psz,1)))
+    assert(approxeq(mXnotm.Sigma, eye(psz, psz)))
+  end
+end
+
+% Check that all engines give the same posterior
+for e=2:length(engines)
+  assert(approxeq(mXm{e}.mu, mXm{1}.mu))
+  assert(approxeq(mXm{e}.Sigma, mXm{1}.Sigma))
+end
+
+
+% Compute the correct posterior by building Xm -> Y
+
+N = 2;
+dag = zeros(N,N);
+dag(1, 2)=1;
+ns = [psz selfsz];
+bnet = mk_bnet(dag, ns, 'discrete', [], 'observed', 2);
+
+bnet.CPD{1} = gaussian_CPD(bnet, 1, 'mean', zeros(psz, 1), 'cov', eye(psz, psz));
+bnet.CPD{2} = gaussian_CPD(bnet, 2, 'mean', mu, 'cov', Sigma, 'weights', W);
+
+jengine  = jtree_inf_engine(bnet);
+evidence = {[], yval};
+jengine = enter_evidence(jengine, evidence); % apply Bayes rule to invert the arc
+mX = marginal_nodes(jengine, 1);
+
+for e=1:length(engines)
+  assert(approxeq(mX.mu, mXm{e}.mu))
+  assert(approxeq(mX.Sigma, mXm{e}.Sigma))
+end