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

23 files changed, 391 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Entries b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Entries
new file mode 100644
index 00000000..5cd139de
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Entries
@@ -0,0 +1,10 @@
+/bk_ff_hmm_inf_engine.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/dbn_init_bel.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/dbn_marginal_from_bel.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/dbn_predict_bel.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/dbn_update_bel.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/dbn_update_bel1.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/enter_evidence.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/@bk_ff_hmm_inf_engine/CVS/Entries.Log b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Entries.Log
new file mode 100644
index 00000000..b2cd71e0
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Entries.Log
@@ -0,0 +1 @@
+A D/private////
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Repository b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Repository
new file mode 100644
index 00000000..af5c9df5
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Repository
@@ -0,0 +1 @@
+FullBNT/BNT/inference/dynamic/@bk_ff_hmm_inf_engine
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Root b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Root
new file mode 100644
index 00000000..f3bd14a6
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/CVS/Root
@@ -0,0 +1 @@
+:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/bk_ff_hmm_inf_engine.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/bk_ff_hmm_inf_engine.m
new file mode 100644
index 00000000..c726a1fd
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/bk_ff_hmm_inf_engine.m
@@ -0,0 +1,21 @@
+function engine = bk_ff_hmm_inf_engine(bnet)
+% BK_FF_HMM_INF_ENGINE Naive (HMM-based) implementation of fully factored form of Boyen-Koller 
+% engine = bk_ff_hmm_inf_engine(bnet)
+%
+% This is implemented on top of the forwards-backwards algo for HMMs,
+% so it is *less* efficient than exact inference! However, it is good for educational purposes,
+% because it illustrates the BK algorithm very clearly.
+
+[persistent_nodes, transient_nodes] = partition_dbn_nodes(bnet.intra, bnet.inter);
+assert(isequal(sort(bnet.observed), transient_nodes));
+[engine.prior, engine.transmat] = dbn_to_hmm(bnet);
+
+ss = length(bnet.intra);
+
+engine.bel = [];
+engine.bel_marginals = [];
+engine.marginals = [];
+
+
+engine = class(engine, 'bk_ff_hmm_inf_engine', inf_engine(bnet));
+
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_init_bel.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_init_bel.m
new file mode 100644
index 00000000..2ab39d37
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_init_bel.m
@@ -0,0 +1,5 @@
+function engine = dbn_init_bel(engine)
+% DBN_INIT_BEL Compute the initial belief state (bk_ff_hmm)
+% engine = dbn_init_bel(engine)
+
+engine.bel = engine.prior(:);
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_marginal_from_bel.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_marginal_from_bel.m
new file mode 100644
index 00000000..a40d43b9
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_marginal_from_bel.m
@@ -0,0 +1,5 @@
+function marginal = dbn_marginal_from_bel(engine, i)
+% DBN_MARGINAL_FROM_BEL Compute the marginal on a node given the current belief state (bk_ff_hmm)
+% marginal = dbn_marginal_from_bel(engine, i)
+
+marginal = pot_to_marginal(engine.bel_marginals{i});
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_predict_bel.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_predict_bel.m
new file mode 100644
index 00000000..5195e53f
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_predict_bel.m
@@ -0,0 +1,19 @@
+function engine = dbn_predict_bel(engine, lag)
+% DBN_PREDICT_BEL Predict the belief state 'lag' steps into the future (bk_ff_hmm)
+% engine = dbn_predict_bel(engine, lag)
+% 'lag' defaults to 1
+
+if nargin < 2, lag = 1; end
+
+for d=1:lag
+  %newbel = engine.transmat' * engine.bel;
+  newbel = normalise(engine.transmat' * engine.bel); 
+  
+  hnodes = engine.hnodes;
+  bnet = bnet_from_engine(engine);
+  ns = bnet.node_sizes;
+  [marginals, marginalsT] = project_joint_onto_marginals(newbel, hnodes, ns);
+  newbel = combine_marginals_into_joint(marginalsT, hnodes, ns);          
+  engine.bel_marginals = marginalsT;
+  engine.bel = newbel;
+end
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_update_bel.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_update_bel.m
new file mode 100644
index 00000000..8323b38a
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_update_bel.m
@@ -0,0 +1,19 @@
+function [engine, loglik] = dbn_update_bel(engine, evidence)
+% DBN_UPDATE_BEL Update the belief state (bk_ff_hmm)
+% [engine, loglik] = dbn_update_bel(engine, evidence)
+%
+% evidence{i,1} contains the evidence on node i in slice t-1
+% evidence{i,2} contains the evidence on node i in slice t
+
+oldbel = engine.bel;
+bnet = bnet_from_engine(engine);
+obslik = mk_hmm_obs_lik_vec(bnet, evidence);
+[newbel, lik] = normalise((engine.transmat' * oldbel) .* obslik);
+loglik = log(lik);
+
+hnodes = engine.hnodes;
+ns = bnet.node_sizes;
+[marginals, marginalsT] = project_joint_onto_marginals(newbel, hnodes, ns);
+newbel = combine_marginals_into_joint(marginalsT, hnodes, ns);          
+engine.bel_marginals = marginalsT;
+engine.bel = newbel;
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_update_bel1.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_update_bel1.m
new file mode 100644
index 00000000..6280ee77
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/dbn_update_bel1.m
@@ -0,0 +1,18 @@
+function [engine, loglik] = dbn_update_bel1(engine, evidence)
+% DBN_UPDATE_BEL Update the initial belief state (bk_ff_hmm)
+% [engine, loglik] = dbn_update_bel(engine, evidence)
+%
+%  evidence{i} contains the evidence on node i in slice 1
+
+oldbel = engine.bel;
+bnet = bnet_from_engine(engine);
+obslik = mk_hmm_obs_lik_vec1(bnet, evidence);
+[newbel, lik] = normalise(oldbel .* obslik);
+loglik = log(lik);
+
+hnodes = engine.hnodes;
+ns = bnet.node_sizes;
+[marginals, marginalsT] = project_joint_onto_marginals(newbel, hnodes, ns);
+newbel = combine_marginals_into_joint(marginalsT, hnodes, ns);          
+engine.bel_marginals = marginalsT;
+engine.bel = newbel;
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/enter_evidence.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/enter_evidence.m
new file mode 100644
index 00000000..4719e0e9
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/enter_evidence.m
@@ -0,0 +1,60 @@
+function [engine, loglik] = enter_evidence(engine, evidence, varargin)
+% ENTER_EVIDENCE Add the specified evidence to the network (bk_ff_hmm)
+% [engine, loglik] = enter_evidence(engine, evidence, ...)
+%
+% evidence{i,t} = [] if if X(i,t) is hidden, and otherwise contains its observed value (scalar or column vector)
+%
+% The following optional arguments can be specified in the form of name/value pairs:
+% [default value in brackets]
+%
+% maximize - if 1, does max-product (not yet supported), else sum-product [0]
+% filter -   if 1, do filtering, else smoothing [0]
+%
+% e.g., engine = enter_evidence(engine, ev, 'maximize', 1)
+
+maximize = 0;
+filter = 0;
+
+% parse optional params
+args = varargin;
+nargs = length(args);
+if nargs > 0
+  for i=1:2:nargs
+    switch args{i},
+     case 'maximize', maximize = args{i+1}; 
+     case 'filter', filter = args{i+1}; 
+     otherwise,  
+      error(['invalid argument name ' args{i}]);       
+    end
+  end
+end
+
+assert(~maximize);
+
+bnet = bnet_from_engine(engine);
+ss = length(bnet.intra);
+onodes = bnet.observed;
+hnodes = mysetdiff(1:ss, onodes);
+T = size(evidence, 2);
+assertBNT(~any(isemptycell(evidence(onodes,:))));
+
+obslik = mk_hmm_obs_lik_mat(bnet, onodes, evidence);
+
+ns = bnet.node_sizes_slice;
+ns(onodes) = 1;
+
+[gamma, loglik, marginals, marginalsT] = bk_ff_fb(engine.prior, engine.transmat, obslik, filter, hnodes, ns);
+  
+for t=1:T
+  for i=hnodes(:)'
+    engine.marginals{i,t} = pot_to_marginal(marginalsT{i,t});
+  end
+  for i=onodes(:)'
+    m.domain = i + (t-1)*ss;
+    m.T = 1;
+    engine.marginals{i,t} = m;
+  end
+end
+
+
+
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/marginal_family.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/marginal_family.m
new file mode 100644
index 00000000..fe58a0f8
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/marginal_family.m
@@ -0,0 +1,5 @@
+function m = marginal_family(engine, i, t)
+% MARGINAL_FAMILY Compute the marginal on the specified family (bk_ff_hmm)
+% marginal = marginal_family(engine, i, t)
+
+error('bk_ff_hmm doesn''t support marginal_family');
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/marginal_nodes.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/marginal_nodes.m
new file mode 100644
index 00000000..8c2f9e81
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/marginal_nodes.m
@@ -0,0 +1,11 @@
+function marginal = marginal_nodes(engine, nodes, t)
+% MARGINAL_NODES Compute the marginal on the specified query nodes (bk_ff_hmm)
+% marginal = marginal_nodes(engine, i, t)
+
+assert(length(nodes)==1);
+i = nodes(end);
+%assert(myismember(i, engine.hnodes));
+marginal = engine.marginals{i,t};
+bnet = bnet_from_engine(engine);
+ss = length(bnet.intra);
+marginal.domain = i + (t-1)*ss;
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Entries b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Entries
new file mode 100644
index 00000000..b4ab4b45
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Entries
@@ -0,0 +1,8 @@
+/bk_ff_fb.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/combine_marginals_into_joint.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/dbn_to_hmm.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/mk_hmm_obs_lik_mat.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/mk_hmm_obs_lik_vec.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/mk_hmm_obs_lik_vec1.m/1.1.1.1/Wed May 29 15:59:56 2002//
+/project_joint_onto_marginals.m/1.1.1.1/Wed May 29 15:59:56 2002//
+D
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Repository b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Repository
new file mode 100644
index 00000000..3b0b141c
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Repository
@@ -0,0 +1 @@
+FullBNT/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Root b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Root
new file mode 100644
index 00000000..f3bd14a6
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/CVS/Root
@@ -0,0 +1 @@
+:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/bk_ff_fb.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/bk_ff_fb.m
new file mode 100644
index 00000000..ca41f77c
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/bk_ff_fb.m
@@ -0,0 +1,59 @@
+function [gamma, loglik, marginals, marginalsT] = bk_ff_fb(prior, transmat, obslik, filter_only, hnodes, ns)
+% BK_FF_FB Fully factored Boyen-Koller version of forwards-backwards
+% [gamma, loglik, marginals, marginalsT] = bk_ff_hmm(prior, transmat, obslik, filter_only, hnodes, ns)
+
+ss  = length(ns);
+S = length(prior);
+T = size(obslik, 2);
+marginals = cell(ss,T);
+marginalsT = cell(ss,T);
+scale = zeros(1,T);
+alpha = zeros(S, T);
+
+transmat2 = transmat';
+for t=1:T
+  if t==1
+    [alpha(:,t), scale(t)] = normalise(prior(:) .* obslik(:,t));
+  else
+    [alpha(:,t), scale(t)] = normalise((transmat2 * alpha(:,t-1)) .* obslik(:,t));
+  end
+  [marginals(:,t), marginalsT(:,t)] = project_joint_onto_marginals(alpha(:,t), hnodes, ns);
+  alpha(:,t) = combine_marginals_into_joint(marginalsT(:,t), hnodes, ns);
+  %fprintf('alpha t=%d\n', t);
+  %celldisp(marginals(1:8,t))
+end
+loglik = sum(log(scale));
+
+if filter_only
+  gamma = alpha;
+  return;
+end
+
+beta = zeros(S,T);
+gamma = zeros(S,T);
+t = T;
+beta(:,t) = ones(S,1);
+gamma(:,t) = normalise(alpha(:,t) .* beta(:,t));
+[marginals(:,t), marginalsT(:,t)] = project_joint_onto_marginals(gamma(:,t), hnodes, ns);
+
+for t=T-1:-1:1
+  b = beta(:,t+1) .* obslik(:,t+1); 
+  beta(:,t) = normalise((transmat * b));
+  [junk, tempT] = project_joint_onto_marginals(beta(:,t), hnodes, ns);
+  beta(:,t) = combine_marginals_into_joint(tempT, hnodes, ns);
+  %gamma(:,t) = normalise(alpha(:,t) .* beta(:,t));
+  %[marginals(:,t), marginalsT(:,t)] = project_joint_onto_marginals(gamma(:,t), hnodes, ns);
+end
+
+gamma2 = zeros(S,T);
+for t=T-1:-1:1
+  b = beta(:,t+1) .* obslik(:,t+1); 
+  xi(:,:,t) = normalise((transmat .* (alpha(:,t) * b')));      
+  if t==T-1
+    gamma2(:,T) = sum(xi(:,:,T-1), 1)';
+  end
+  gamma2(:,t) = sum(xi(:,:,t), 2);
+  [marginals(:,t), marginalsT(:,t)] = project_joint_onto_marginals(gamma2(:,t), hnodes, ns);
+end
+
+
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/combine_marginals_into_joint.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/combine_marginals_into_joint.m
new file mode 100644
index 00000000..74065662
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/combine_marginals_into_joint.m
@@ -0,0 +1,8 @@
+function joint = combine_marginals_into_joint(marginalsT, hnodes, ns)
+
+jointT = dpot(hnodes, ns(hnodes));
+for i=hnodes(:)'
+  jointT = multiply_by_pot(jointT, marginalsT{i});
+end
+m = pot_to_marginal(jointT);
+joint = m.T(:);           
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/dbn_to_hmm.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/dbn_to_hmm.m
new file mode 100644
index 00000000..4a921bfd
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/dbn_to_hmm.m
@@ -0,0 +1,41 @@
+function [prior, transmat] = dbn_to_hmm(bnet)
+% DBN_TO_HMM Compute the discrete HMM matrices from a simple DBN
+% [prior, transmat] = dbn_to_hmm(bnet)
+
+onodes = bnet.observed;
+ss = length(bnet.intra);
+evidence = cell(1,2*ss);
+hnodes = mysetdiff(1:ss, onodes);
+prior = multiply_CPTs(bnet, [], hnodes, evidence);
+transmat = multiply_CPTs(bnet, hnodes, hnodes+ss, evidence);
+%obsmat1 = multiply_CPTs(bnet, hnodes, onodes, evidence);
+%obsmat = multiply_CPTs(bnet, hnodes+ss, onodes+ss, evidence);
+%obsmat1 = obsmat if the observation matrices are tied across slices
+
+
+
+%%%%%%%%%%%%
+
+function mat = multiply_CPTs(bnet, pdom, cdom, evidence)
+
+% MULTIPLY_CPTS Make a matrix Pr(Y|X), where X represents all the parents, and Y all the children
+% We assume the children have no intra-connections.
+%
+% e.g., Consider the DBN with interconnectivity i->i', j->j',k', k->i',k'
+% Then transition matrix = Pr(i,j,k -> i',j',k') = Pr(i,k->i') Pr(j->j') Pr(j,k->k')
+
+dom = [pdom cdom];
+ns = bnet.node_sizes;
+bigpot = dpot(dom, ns(dom));
+for j=cdom(:)'
+  e = bnet.equiv_class(j);
+  fam = family(bnet.dag, j);
+  pot = convert_to_pot(bnet.CPD{e}, 'd', fam(:), evidence);
+  bigpot = multiply_by_pot(bigpot, pot);
+end
+psize = prod(ns(pdom));
+csize = prod(ns(cdom));
+T = pot_to_marginal(bigpot);
+mat = reshape(T.T, [psize csize]);
+
+          
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_mat.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_mat.m
new file mode 100644
index 00000000..b3e4c4cc
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_mat.m
@@ -0,0 +1,34 @@
+function obslik = mk_hmm_obs_lik_mat(bnet, onodes, evidence)
+% MK_HMM_OBS_LIK_MAT Make the observation likelihood matrix for all slices
+% obslik = mk_hmm_obs_lik_mat(bnet, onodes, evidence)
+%
+% obslik(i,t) = Pr(Y(t) | X(t)=i)
+
+[ss T] = size(evidence);
+
+hnodes = mysetdiff(1:ss, onodes);
+ns = bnet.node_sizes_slice;
+ns(onodes) = 1;
+Q = prod(ns(hnodes));
+obslik = zeros(Q,T);
+
+dom = 1:ss;
+for t=1:T
+  bigpot = dpot(dom, ns(dom));
+  for i=onodes(:)'
+    if t==1
+      e = bnet.equiv_class(i,1);
+      fam = family(bnet.dag, i);
+    else
+      e = bnet.equiv_class(i,2);
+      fam = family(bnet.dag, i, 2) + ss*(t-2);
+    end
+    pot = convert_to_pot(bnet.CPD{e}, 'd', fam(:), evidence);
+    pot = set_domain_pot(pot, family(bnet.dag, i));
+    bigpot = multiply_by_pot(bigpot, pot);
+  end
+  m = pot_to_marginal(bigpot);
+  obslik(:,t) = m.T(:);
+end
+
+
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_vec.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_vec.m
new file mode 100644
index 00000000..23247bd5
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_vec.m
@@ -0,0 +1,27 @@
+function obslik = mk_hmm_obs_lik_vec(bnet, evidence)
+% MK_HMM_OBS_LIK_VEC Make the observation likelihood vector for one slice
+% obslik = mk_obs_lik(bnet, evidence)
+%
+% obslik(i) = Pr(y(t) | X(t)=i)
+% evidence{i,1} contains the evidence on node i in slice t-1
+% evidence{i,2} contains the evidence on node i in slice t
+
+ns = bnet.node_sizes;
+ss = length(bnet.intra);
+onodes = find(~isemptycell(evidence(:)));
+hnodes = find(isemptycell(evidence(:)));
+ens = ns;
+ens(onodes) = 1;
+Q = prod(ens(hnodes));
+obslik = zeros(1,Q);
+dom = (1:ss)+ss;
+bigpot = dpot(dom, ens(dom));
+onodes1 = find(~isemptycell(evidence(:,1)));
+for i=onodes1(:)'
+  e = bnet.equiv_class(i,2);
+  fam = family(bnet.dag, i, 2);
+  pot = convert_to_pot(bnet.CPD{e}, 'd', fam, evidence);
+  bigpot = multiply_by_pot(bigpot, pot);
+end
+m = pot_to_marginal(bigpot);
+obslik = m.T(:);
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_vec1.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_vec1.m
new file mode 100644
index 00000000..6d0c1d35
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/mk_hmm_obs_lik_vec1.m
@@ -0,0 +1,25 @@
+function obslik = mk_hmm_obs_lik_vec1(bnet, evidence)
+% MK_HMM_OBS_LIK_VEC1 Make the observation likelihood vector for the first slice
+% obslik = mk_hmm_obs_lik_vec1(engine, evidence)
+%
+% obslik(i) = Pr(y(1) | X(1)=i)
+% evidence{i} contains the evidence on node i in slice 1
+
+ns = bnet.node_sizes;
+ss = length(ns);
+onodes = find(~isemptycell(evidence(:)));
+hnodes = find(isemptycell(evidence(:)));
+ens = ns;
+ens(onodes) = 1;
+Q = prod(ens(hnodes));
+obslik = zeros(1,Q);
+dom = (1:ss);
+bigpot = dpot(dom, ens(dom));
+for i=onodes(:)'
+  e = bnet.equiv_class(i,1);
+  fam = family(bnet.dag, i);
+  pot = convert_to_pot(bnet.CPD{e}, 'd', fam(:), evidence);
+  bigpot = multiply_by_pot(bigpot, pot);
+end
+m = pot_to_marginal(bigpot);
+obslik = m.T(:);
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/project_joint_onto_marginals.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/project_joint_onto_marginals.m
new file mode 100644
index 00000000..3f4036db
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@bk_ff_hmm_inf_engine/private/project_joint_onto_marginals.m
@@ -0,0 +1,11 @@
+function [marginals, marginalsT] = project_joint_onto_marginals(joint, hnodes, ns)
+
+ss = length(ns);
+jointT = dpot(hnodes, ns(hnodes), joint);
+marginalsT = cell(1, ss);
+marginals = cell(1,ss);
+for i=hnodes(:)'
+  marginalsT{i} = marginalize_pot(jointT, i);
+  m = pot_to_marginal(marginalsT{i});
+  marginals{i} = m.T(:);
+end