diff toolboxes/FullBNT-1.0.7/bnt/inference/static/@gibbs_sampling_inf_engine/private/compute_posterior_dbn.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/static/@gibbs_sampling_inf_engine/private/compute_posterior_dbn.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,59 @@
+function post = compute_posterior_dbn(bnet, state, i, n, strides, families, ...
+				  CPT)
+% COMPUTE_POSTERIOR
+%
+% post = compute_posterior(bnet, state, i, n, strides, families,
+% cpts)
+%
+% Compute the posterior distribution on node X_i^n of a DBN,
+% conditional on evidence in the cell array state
+%
+% strides is the cached result of compute_strides(bnet)
+% families is the cached result of compute_families(bnet)
+% cpt is the cached result of get_cpts(bnet)
+%
+% post is a one-dimensional table
+
+
+
+% First multiply in the cpt of the node itself
+post = get_slice_dbn(bnet, state, i, n, i, n, strides, families, CPT);
+post = post(:);
+
+% Then multiply in CPTs of children that are in this slice
+for j = children(bnet.intra, i)
+  slice = get_slice_dbn(bnet, state, j, n, i, n, strides, families, CPT);
+  post = post.*slice(:);
+end
+
+% Finally, if necessary, multiply in CPTs of children in the next
+% slice 
+if (n < size(state,2))
+  for j = children(bnet.inter, i)
+    slice = get_slice_dbn(bnet, state, j, n+1, i, n, strides, families, ...
+			    CPT);
+    post = post.*slice(:);
+  end
+end
+
+post = normalise(post);
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