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, 128 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/SLP/misc/dag_to_cpdag1.m b/sourcecodes/bnt-master/SLP/misc/dag_to_cpdag1.m
new file mode 100644
index 00000000..c3189a1d
--- /dev/null
+++ b/sourcecodes/bnt-master/SLP/misc/dag_to_cpdag1.m
@@ -0,0 +1,128 @@
+function  [cpdag] = dag_to_cpdag1(dags)
+% 2
+% (also works with a cell array of dags, returning a cell array of cpdags)
+% DAG_TO_CPDAG produce a N*N matrix which values respect :
+%
+% 	If the edge is compelled then 1 on the edge.
+%	If the edge is reversible then 1 on the edge and 1 in the reverse edge.
+%
+% Make sure that the entry is a DAG.
+%
+% See D.M. Chickering: "Learning Equivalence Classes of Bayesian-Network Structures".
+%
+% 
+% francois.olivier.c.h@gmail.com, philippe.leray@univ-nantes.fr
+
+if ~iscell(dags)
+    dag=cell(1,1);
+    dag{1}=dags;
+else
+    dag=dags;
+end
+
+for da=1:length(dag)
+    cpdags{da} = abs(label_edges(dag{da}));
+end
+
+if ~iscell(dags)
+    cpdag=cpdags{1};
+else
+    cpdag=cpdags;
+end
+
+%%==============================================================================
+
+function [label] = label_edges(dag)
+% LABEL-EDGES produce a N*N matrix which values are
+% 	+1 if the edge is compelled or
+%	-1 if the edge is reversible.
+% Make sure that the entry is a DAG.
+%
+% francois.olivier.c.h@gmail.com
+
+N=length(dag);
+[order xedge yedge] = order_edges(dag);
+label = 2*dag; % all edges as unknown
+
+NbEdges = length(xedge) ;
+%xedge=x, yedge=y, %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+
+for Edge=1:NbEdges,
+    xlow=xedge(Edge);
+    ylow=yedge(Edge);
+    if label(xlow,ylow)==2
+        fin = 0;
+
+        %wcompelled = find(label(:,xlow)~=2);
+        wcompelled = find(label(:,xlow)==1);
+
+        parenty = find(label(:,ylow)~=0);
+        %sonsy = find(label(ylow,:)~=0);
+
+        for s = 1:length(wcompelled)
+           w = wcompelled(s);
+           if ~ismember(w,parenty)
+                label(xlow,ylow)=1; 
+                label(ylow,xlow)=0; %
+                label(parenty,ylow)=1;
+                label(ylow,parenty)=0; %
+                %label(ylow,sonsy)=1; %
+                %label(sonsy,ylow)=0; %
+                fin = 1;
+
+            elseif fin == 0
+                label(w,ylow)=1;
+                %label(ylow,w)=0; %
+            end
+        end
+        if fin == 0
+            parentx = [xlow ; find(label(:,xlow)~=0)];
+            if ~isempty(mysetdiff(parenty,parentx))
+                %label(xlow,ylow)=1; %
+                %label(ylow,xlow)=0; %
+
+                label(find(label(:,ylow)==2),ylow)=1;
+                label(ylow,find(label(ylow,:)==2))=1; %
+            else	
+                label(xlow,ylow)=-1;
+                label(ylow,xlow)=-1; %
+                ttp = find(label(:,ylow)==2);
+                label(ttp,ylow)=-1;
+                label(ylow,ttp)=-1; %
+            end
+        end
+    end
+end
+
+%%%========================================================================================
+function [order, x, y] = order_edges(dag)
+% ORDER_EDGES produce a total (natural) ordering over the edges in a DAG.
+% Make sure that the entry is a DAG.
+%
+% francois.olivier.c.h@gmail.com
+%
+% 2 mai 2003
+
+if acyclic(dag)==0
+    error('Requires an acyclic graph');
+end
+
+N=length(dag);
+order = zeros(N,N);
+
+node_order = topological_sort(dag);
+[tmp oo] = sort(node_order);
+
+dag2=dag(node_order,node_order);
+[x y]=find(flipud(dag2)==1);
+nb_edges=length(x);
+
+if nb_edges~=0
+  order(sub2ind([N N],N+1-x,y))=1:nb_edges ;
+end
+
+order=order(oo,oo);
+x=node_order(N+1-x);
+y=node_order(y);
+