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, 197 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/CVS/Entries b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/CVS/Entries
new file mode 100644
index 00000000..dd45ee37
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/CVS/Entries
@@ -0,0 +1,4 @@
+/enter_soft_evidence.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/enter_soft_evidence1.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//
+D
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/CVS/Repository b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/CVS/Repository
new file mode 100644
index 00000000..5582c6dd
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/CVS/Repository
@@ -0,0 +1 @@
+FullBNT/BNT/inference/dynamic/@ff_inf_engine/Old
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/CVS/Root b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/CVS/Root
new file mode 100644
index 00000000..f3bd14a6
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_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/@ff_inf_engine/Old/enter_soft_evidence.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/enter_soft_evidence.m
new file mode 100644
index 00000000..1e2acffb
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/enter_soft_evidence.m
@@ -0,0 +1,59 @@
+function [marginals, loglik] = enter_soft_evidence(engine, CPDpot, observed, pot_type, filter)
+% ENTER_SOFT_EVIDENCE Add the specified soft evidence to the network (bk_ff)
+% [marginals, loglik] = enter_soft_evidence(engine, CPDpot, observed, pot_type, filter)
+
+assert(pot_type == 'd');
+[ss T] = size(CPDpot);
+fwd = cell(ss,T);
+hnodes = engine.hnodes(:)';
+onodes = engine.onodes(:)';
+bnet = bnet_from_engine(engine);
+ns = bnet.node_sizes;
+onodes2 = [onodes onodes+ss];
+ns(onodes2) = 1;
+
+logscale = zeros(1,T);
+local_logscale = zeros(1,length(hnodes));
+
+t = 1;
+for i=hnodes
+  fwd{i,t} = CPDpot{i,t};
+end
+for i=onodes
+  p = parents(bnet.dag, i);
+  assert(length(p)==1);
+  ev = marginalize_pot(CPDpot{i,t}, p);
+  fwd{p,t} = multiply_by_pot(fwd{p,t}, ev);
+end
+for i=hnodes
+  [fwd{i,t}, local_logscale(i)] = normalize_pot(fwd{i,t});
+end
+logscale(t) = sum(local_logscale);
+
+for t=2:T
+  for i=hnodes
+    ps = parents(bnet.dag, i+ss);
+    assert(all(ps<=ss)); % in previous slice
+    prior = CPDpot{i,t};
+    for p=ps(:)'
+      prior = multiply_by_pot(prior, fwd{p,t-1});
+    end
+    fwd{i,t} = marginalize_pot(prior, i+ss);
+    fwd{i,t} = set_domain_pot(fwd{i,t}, i);
+  end
+  for i=onodes
+    p = parents(bnet.dag, i);
+    assert(length(p)==1);
+    temp = pot_to_marginal(CPDpot{i,t}); 
+    ev = dpot(p, ns(p), temp.T);
+    fwd{p,t} = multiply_by_pot(fwd{p,t}, ev);
+  end
+  
+  for i=hnodes
+    [fwd{i,t}, local_logscale(i)] = normalize_pot(fwd{i,t});
+  end
+  logscale(t) = sum(local_logscale);
+end
+
+marginals = fwd;
+loglik = sum(logscale);
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/enter_soft_evidence1.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/enter_soft_evidence1.m
new file mode 100644
index 00000000..b4ff1a02
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/enter_soft_evidence1.m
@@ -0,0 +1,94 @@
+function [marginals, loglik] = enter_soft_evidence(engine, CPDpot, observed, pot_type, filter)
+% ENTER_SOFT_EVIDENCE Add the specified soft evidence to the network (ff)
+% [marginals, loglik] = enter_soft_evidence(engine, CPDpot, observed, pot_type, filter)
+
+assert(pot_type == 'd');
+[ss T] = size(CPDpot);
+fwd = cell(ss,T);
+hnodes = engine.hnodes(:)';
+onodes = engine.onodes(:)';
+bnet = bnet_from_engine(engine);
+ns = bnet.node_sizes;
+onodes2 = [onodes onodes+ss];
+ns(onodes2) = 1;
+
+logscale = zeros(1,T);
+H = length(hnodes);
+local_logscale = zeros(1,ss);
+
+obschild = zeros(1,ss);
+for i=hnodes
+  ocs = myintersect(children(bnet.dag, i), onodes);
+  assert(length(ocs)==1);
+  obschild(i) = ocs(1);
+end  
+  
+t = 1;
+for i=hnodes
+  fwd{i,t} = CPDpot{i,t};
+  c = obschild(i);
+  temp = pot_to_marginal(CPDpot{c,t}); 
+  ev = dpot(i, ns(i), temp.T);
+  fwd{i,t} = multiply_by_pot(fwd{i,t}, ev);
+  [fwd{i,t}, local_logscale(i)] = normalize_pot(fwd{i,t});
+end
+logscale(t) = sum(local_logscale);
+
+for t=2:T
+  for i=hnodes
+    ps = parents(bnet.dag, i+ss);
+    assert(all(ps<=ss)); % in previous slice
+    prior = CPDpot{i,t};
+    for p=ps(:)'
+      prior = multiply_by_pot(prior, fwd{p,t-1});
+    end
+    fwd{i,t} = marginalize_pot(prior, i+ss);
+    fwd{i,t} = set_domain_pot(fwd{i,t}, i);
+    c = obschild(i);
+    temp = pot_to_marginal(CPDpot{c,t});
+    ev = dpot(i, ns(i), temp.T);
+    fwd{i,t} = multiply_by_pot(fwd{i,t}, ev);
+    [fwd{i,t}, local_logscale(i)] = normalize_pot(fwd{i,t});
+  end
+  logscale(t) = sum(local_logscale);
+end
+
+loglik = sum(logscale);
+
+
+if filter
+  marginals = fwd;
+  return;
+end
+
+back = cell(ss,T);
+t = T;
+for i=hnodes
+  back{i,t} = dpot(i, ns(i));
+  back{i,t} = set_domain_pot(back{i,t}, i+ss);
+end
+for t=T-1:-1:1
+  for i=hnodes
+    pot = CPDpot{i,t+1};
+    pot = multiply_by_pot(pot, back{i,t+1});
+    c = obschild(i);
+    temp = pot_to_marginal(CPDpot{c,t+1});
+    ev = dpot(i, ns(i), temp.T);
+    pot = multiply_by_pot(pot, ev);
+    back{i,t} = marginalize_pot(pot, i);
+    back{i,t} = normalize_pot(back{i,t});
+    back{i,t} = set_domain_pot(back{i,t}, i+ss);
+  end
+end
+
+
+
+% COMBINE
+for t=1:T
+  for i=hnodes
+    back{i,t} = set_domain_pot(back{i,t}, i);
+    fwd{i,t} = multiply_by_pot(fwd{i,t}, back{i,t});
+    marginals{i,t} = normalize_pot(fwd{i,t});
+    %fwdback{i,t} = normalize_pot(multiply_pots(fwd{i,t}, back{i,t}));
+  end
+end
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/marginal_family.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/marginal_family.m
new file mode 100644
index 00000000..99813571
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@ff_inf_engine/Old/marginal_family.m
@@ -0,0 +1,38 @@
+function marginal = marginal_family(engine, i, t)
+% MARGINAL_FAMILY Compute the marginal on the specified family (ff)
+% marginal = marginal_family(engine, i, t)
+
+if nargin < 3, t = 1; end
+
+% The method is similar to the following HMM equation:
+% xi(i,j,t) = normalise( alpha(i,t) * transmat(i,j) * obsmat(j,t+1) * beta(j,t+1) )
+% where xi(i,j,t) = Pr(Q(t)=i, Q(t+1)=j | y(1:T))
+
+bnet = bnet_from_engine(engine);
+
+if myismember(i, engine.onodes)
+  ps = parents(bnet.dag, i);
+  p = ps(1);
+  marginal = pot_to_marginal(engine.marginals{p,t});
+  marginal.domain = [p i];
+  return;
+end
+
+if t==1
+  marginal = pot_to_marginal(engine.marginals{i,t});
+  return;
+end
+
+bnet = bnet_from_engine(engine);
+ss = length(bnet.intra);
+pot = engine.CPDpot{i,t};
+c = engine.obschild(i);
+pot = multiply_by_pot(pot, engine.CPDpot{c,t});
+pot = multiply_by_pot(pot, engine.back{i,t});
+ps = parents(bnet.dag, i+ss);
+for p=ps(:)'
+  pot = multiply_by_pot(pot, engine.fwd{p,t-1});
+end
+marginal = pot_to_marginal(normalize_pot(pot));
+
+