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, 112 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/graph/dag_to_essential_graph.m b/sourcecodes/bnt-master/graph/dag_to_essential_graph.m
new file mode 100644
index 00000000..84dd8ee5
--- /dev/null
+++ b/sourcecodes/bnt-master/graph/dag_to_essential_graph.m
@@ -0,0 +1,112 @@
+
+function [eg] = dag_to_essential_graph(dag)
+cpdag = dag_to_cpdag(dag);
+eg = dag + dag .* (cpdag + cpdag');
+
+return;
+
+
+
+
+% Coverts a DAG into Essential Graph where edges are coded by 2 and 3, 2 is
+% directed edge and 3 is bidirected edge and is at one (the same as the original DAG) of the two
+% symetrical places. 
+
+% Is implemented by the algorithm of Max Chickering in D.M.Chickering (1995). 
+% A transformational characterization of equivalent Bayesian network structures. 
+% In Proceedings of Eleventh Conference on Uncertainty in Artificial Intelligence, Montreal, QU,
+% pages 87-98. Morgan Kaufmann 
+% http://research.microsoft.com/~dmax/publications/uai95.pdf 
+
+% Implemented by Tomas Kocka, AAU.
+
+function [eg] = dag_to_essential_graph(dagx)
+
+%print_dag(dagx); % Just checking input
+
+order = topological_sort(dagx); % get the topological order of nodes and their number
+
+% fprintf('the topological order is: %d',order);
+% fprintf('\n');
+
+[nx,ny] = size(dagx); % gets the number of nodes, note that nx == ny
+[I,J] = find(dagx); % finds all nonzero elements in the adjacency matrix, i.e. arcs in the DAG - however we will overwrite it in a special order
+% we will sort the arcs from lowest possible y and highest possible x, arcs are x->y
+e = 1;
+for y = 1:ny
+    for x = nx:-1:1
+        %fprintf('x %d ',order(x)); fprintf('y %d ',order(y));
+        if dagx(order(x),order(y)) == 1 
+            I(e) = order(x);
+            J(e) = order(y);
+            e = e + 1;
+            %fprintf('x order %d',x);
+            %fprintf('y order %d',y);
+            %fprintf('\n');
+        end
+    end
+end
+
+
+% fprintf('the arcs are: %d',I);
+% fprintf('\n');
+% fprintf('the arcs are: %d',J);
+% fprintf('\n');
+
+
+% Now we have to decide which arcs are part of the essential graph and
+% which are undirected edges in the essential graph.
+% Undecided arc in the DAG are 1, directed in EG are 2 and undirected in EG
+% are 3.
+
+
+for e = 1:length(I)
+    if dagx(I(e),J(e)) == 1
+        cont = true;
+        for w = 1:nx 
+            if dagx(w,I(e)) == 2
+                if dagx(w,J(e)) ~= 0
+                    dagx(w,J(e)) = 2;
+                else
+                    for ww = 1:nx
+                        if dagx(ww,J(e)) ~= 0
+                           dagx(ww,J(e)) = 2;
+                        end
+                    end % and now skip the rest and start with another arc from the list
+                    w = nx;
+                    cont = false;
+                end
+            end
+        end
+        if cont
+           exists = false;
+           for z = 1:nx
+               %fprintf('test %d',dagx(z,J(e)));
+               if dagx(z,J(e)) ~= 0 & z ~= I(e) & dagx(z,I(e)) == 0
+                  exists = true; 
+                  for ww = 1:nx
+                        if dagx(ww,J(e)) == 1
+                           dagx(ww,J(e)) = 2;
+                        end 
+                  end
+               end
+           end
+           if ~ exists
+               for ww = 1:nx
+                   if dagx(ww,J(e)) == 1
+                      dagx(ww,J(e)) = 3;
+                   end 
+               end  
+           end
+        end
+    end            
+end
+
+%print_dag(dagx); % Just checking output
+
+
+
+
+
+
+