BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02

1 files changed, 34 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/graph/test_strong_root.m b/sourcecodes/bnt-master/graph/test_strong_root.m
new file mode 100644
index 00000000..86e1117e
--- /dev/null
+++ b/sourcecodes/bnt-master/graph/test_strong_root.m
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+function strong = test_strong_root(jtree,cliques,dnodes,root)
+% This function tests, whether root is a strong root of jtree. 
+% The following parameters are used
+% Input:
+% jtree   An matrix with two colums. jtree(i,j) == jtree(j,i) is 1 if node 
+%         i is connected with node j
+% cliques Cells which contain the nodes in each clique
+% dnodes  An array with the discrete nodes of the juntion tree.
+% root    It is tested whether root is the strong root of the junction tree
+% Output:
+% strong  The output is 1 if root is the strong root of the junction tree jtree.
+%         Please note, that the running intersection property is not tested. 
+if isempty(dnodes)
+     strong = 1;
+     return;
+end
+
+children = find(jtree(root,:)==1);
+i = 1;
+strong = 1;
+while (i <= length(children)) & (strong==1)
+     child = children(i);
+     jtree(child,root) = 0;
+     jtree(root,child) = 0;
+     sep = myintersect(cliques{child},cliques{root});
+     diff = mysetdiff(cliques{child},cliques{root});
+     if (mysubset(sep,dnodes) | isempty(myintersect(diff,dnodes)))
+         strong = test_strong_root(jtree,cliques,dnodes,child);
+     else
+         strong = 0;
+     end;
+     i = i+1;
+end
+