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

6 files changed, 101 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Entries b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Entries
new file mode 100644
index 00000000..528b5843
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Entries
@@ -0,0 +1,4 @@
+/dhmm_inf_engine.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/marginal_family.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/marginal_nodes.m/1.1.1.1/Wed May 29 15:59:56 2002//
+D
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Repository b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Repository
new file mode 100644
index 00000000..f82b2bea
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Repository
@@ -0,0 +1 @@
+FullBNT/BNT/inference/dynamic/@hmm_inf_engine/Old
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Root b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Root
new file mode 100644
index 00000000..f3bd14a6
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/CVS/Root
@@ -0,0 +1 @@
+:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/dhmm_inf_engine.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/dhmm_inf_engine.m
new file mode 100644
index 00000000..2b0c8810
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/dhmm_inf_engine.m
@@ -0,0 +1,34 @@
+function engine = dhmm_inf_engine(bnet, onodes)
+% DHMM_INF_ENGINE Inference engine for discrete DBNs which uses the forwards-backwards algorithm.
+% engine = dhmm_inf_engine(bnet, onodes)
+%
+% 'onodes' specifies which nodes are observed; these must be leaves, and can be discrete or continuous.
+% The remaining nodes are all hidden, and must be discrete.
+% The DBN is converted to an HMM, with a single meganode, but which may have factored obs.
+
+ss = length(bnet.intra);
+hnodes = mysetdiff(1:ss, onodes);
+evidence = cell(ss, 2);
+ns = bnet.node_sizes;
+Q = prod(ns(hnodes));
+tmp = dpot_to_table(compute_joint_pot(bnet, hnodes, evidence));
+engine.startprob = reshape(tmp, Q, 1);
+tmp = dpot_to_table(compute_joint_pot(bnet, [hnodes hnodes+ss], evidence));
+engine.transprob = mk_stochastic(reshape(tmp, Q, Q));
+engine.obsprob = cell(1, length(onodes));
+for i=1:length(onodes)
+  tmp = dpot_to_table(compute_joint_pot(bnet, [hnodes onodes(i)], evidence));
+  O = ns(onodes(i));
+  engine.obsprob{i} = mk_stochastic(reshape(tmp, Q, O));
+end
+
+% This is where we will store the results between enter_evidence and marginal_nodes
+engine.gamma = [];
+engine.xi = [];
+
+engine.onodes = onodes;
+engine.hnodes = hnodes;
+engine.maximize = [];
+
+engine = class(engine, 'dhmm_inf_engine', inf_engine(bnet));
+
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/marginal_family.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/marginal_family.m
new file mode 100644
index 00000000..681e1591
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/marginal_family.m
@@ -0,0 +1,31 @@
+function marginal = marginal_family(engine, i, t, add_ev)
+% MARGINAL_FAMILY Compute the marginal on the specified family  (hmm)
+% marginal = marginal_nodes(engine, i, t, add_ev)
+%
+
+if nargin < 3, t = 1; end
+if nargin < 4, add_ev = 0; end
+
+bnet = bnet_from_engine(engine);
+ss = length(bnet.intra);
+if t==1
+ fam = family(bnet.dag, i);
+ bigpot = engine.one_slice_marginal{t};
+ nodes = fam;
+else
+  fam = family(bnet.dag, i+ss);
+  if any(fam <= ss) % family spans 2 slices
+    bigpot = engine.two_slice_marginal{t-1}; % t-1 and t
+    nodes = fam + (t-2)*ss;
+  else
+    bigpot = engine.one_slice_marginal{t};
+    nodes = fam-ss + (t-1)*ss;
+  end
+end
+
+marginal = pot_to_marginal(marginalize_pot(bigpot, nodes, engine.maximize));
+
+if add_ev
+  marginal = add_ev_to_dmarginal(marginal, engine.evidence, engine.node_sizes);
+end    
+
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/marginal_nodes.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/marginal_nodes.m
new file mode 100644
index 00000000..4b8d6008
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@hmm_inf_engine/Old/marginal_nodes.m
@@ -0,0 +1,30 @@
+function marginal = marginal_nodes(engine, nodes, t, add_ev)
+% MARGINAL_NODES Compute the marginal on the specified query nodes (hmm)
+% marginal = marginal_nodes(engine, nodes, t, add_ev)
+%
+% 't' specifies the time slice of the earliest node in 'nodes'.
+% 'nodes' cannot span more than 2 time slices.
+%
+% Example:
+% Consider a DBN with 2 nodes per slice.
+% Then t=2, nodes=[1 3] refers to node 1 in slice 2 and node 1 in slice 3,
+% i.e., nodes 3 and 5 in the unrolled network,
+
+if nargin < 3, t = 1; end
+if nargin < 4, add_ev = 0; end
+
+bnet = bnet_from_engine(engine);
+ss = length(bnet.intra);
+if all(nodes <= ss)
+  bigpot = engine.one_slice_marginal{t};
+else
+  bigpot = engine.two_slice_marginal{t};
+end
+
+nodes = nodes + (t-1)*ss;
+marginal = pot_to_marginal(marginalize_pot(bigpot, nodes, engine.maximize));
+
+if add_ev
+  marginal = add_ev_to_dmarginal(marginal, engine.evidence, engine.node_sizes);
+end    
+