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, 24 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/SLP/learning/@jtree_inf_engine2/clq_containing_nodes.m b/sourcecodes/bnt-master/SLP/learning/@jtree_inf_engine2/clq_containing_nodes.m
new file mode 100644
index 00000000..8904fa49
--- /dev/null
+++ b/sourcecodes/bnt-master/SLP/learning/@jtree_inf_engine2/clq_containing_nodes.m
@@ -0,0 +1,24 @@
+function c = clq_containing_nodes(engine, nodes, fam)
+% CLQ_CONTAINING_NODES Find the lightest clique (if any) that contains the set of nodes
+% c = clq_containing_nodes(engine, nodes, family)
+%
+% If the optional 'family' argument is specified, it means nodes = family(nodes(end)).
+% (This is useful since clq_ass_to_node is not accessible to outsiders.)
+% Returns c=-1 if there is no such clique.
+
+if nargin < 3, fam = 0; else fam = 1; end
+
+if length(nodes)==1
+  c = engine.clq_ass_to_node(nodes(1));
+%elseif fam
+%  c = engine.clq_ass_to_node(nodes(end));
+else
+  B = engine.cliques_bitv;
+  w = engine.clique_weight;
+  clqs = find(all(B(:,nodes), 2)); % all selected columns must be 1
+  if isempty(clqs)
+    c = -1;
+  else
+    c = clqs(argmin(w(clqs)));     
+  end
+end