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

4 files changed, 62 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Entries b/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Entries
new file mode 100644
index 00000000..c7e92b5c
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Entries
@@ -0,0 +1,2 @@
+/mk_hmm_bnet.m/1.1.1.1/Wed May 29 15:59:54 2002//
+D
diff --git a/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Repository b/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Repository
new file mode 100644
index 00000000..fdee291b
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Repository
@@ -0,0 +1 @@
+FullBNT/BNT/examples/static/Models/Old
diff --git a/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Root b/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Root
new file mode 100644
index 00000000..f3bd14a6
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/examples/static/Models/Old/CVS/Root
@@ -0,0 +1 @@
+:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt
diff --git a/sourcecodes/bnt-master/BNT/examples/static/Models/Old/mk_hmm_bnet.m b/sourcecodes/bnt-master/BNT/examples/static/Models/Old/mk_hmm_bnet.m
new file mode 100644
index 00000000..1179c6d8
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/examples/static/Models/Old/mk_hmm_bnet.m
@@ -0,0 +1,58 @@
+function [bnet, onodes] = mk_hmm_bnet(T, Q, O, cts_obs, param_tying)
+% MK_HMM_BNET Make a (static( bnet to represent a hidden Markov model
+% [bnet, onodes] = mk_hmm_bnet(T, Q, O, cts_obs, param_tying)
+%
+% T = num time slices
+% Q = num hidden states
+% O = size of the observed node (num discrete values or length of vector)
+% cts_obs - 1 means the observed node is a continuous-valued vector, 0 means it's discrete
+% param_tying - 1 means we create 3 CPDs, 0 means we create 1 CPD per node
+
+N = 2*T;
+dag = zeros(N);
+for i=1:T-1
+  dag(i,i+1)=1;
+end
+onodes = T+1:N;
+for i=1:T
+  dag(i, onodes(i)) = 1;
+end
+
+if cts_obs
+  dnodes = 1:T;
+else
+  dnodes = 1:N;
+end
+ns = [Q*ones(1,T) O*ones(1,T)];
+
+if param_tying
+  eclass = [1 2*ones(1,T-1) 3*ones(1,T)];
+else
+  eclass = 1:N;
+end
+
+bnet = mk_bnet(dag, ns, dnodes, eclass);
+
+hnodes = mysetdiff(1:N, onodes);
+if ~param_tying
+  for i=hnodes(:)'
+    bnet.CPD{i} = tabular_CPD(bnet, i);
+  end
+  if cts_obs
+    for i=onodes(:)'
+      bnet.CPD{i} = gaussian_CPD(bnet, i);
+    end
+  else
+    for i=onodes(:)'
+      bnet.CPD{i} = tabular_CPD(bnet, i);
+    end
+  end
+else
+  bnet.CPD{1} = tabular_CPD(bnet, 1);
+  bnet.CPD{2} = tabular_CPD(bnet, 2);
+  if cts_obs
+    bnet.CPD{3} = gaussian_CPD(bnet, 3);
+  else
+    bnet.CPD{3} = tabular_CPD(bnet, 3);
+  end
+end