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

21 files changed, 1115 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Entries b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Entries
new file mode 100644
index 00000000..0afc5821
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Entries
@@ -0,0 +1,7 @@
+/hhmmQ_CPD.m/1.1.1.1/Tue Sep 24 04:19:26 2002//
+/log_prior.m/1.1.1.1/Wed May 29 15:59:54 2002//
+/maximize_params.m/1.1.1.1/Tue Sep 24 13:10:18 2002//
+/reset_ess.m/1.1.1.1/Wed May 29 15:59:54 2002//
+/update_CPT.m/1.1.1.1/Tue Sep 24 02:58:18 2002//
+/update_ess.m/1.1.1.1/Thu Jul 24 13:41:34 2003//
+D/Old////
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Repository b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Repository
new file mode 100644
index 00000000..f226b7fc
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Repository
@@ -0,0 +1 @@
+FullBNT/BNT/CPDs/@hhmmQ_CPD
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Root b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Root
new file mode 100644
index 00000000..f3bd14a6
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/CVS/Root
@@ -0,0 +1 @@
+:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Entries b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Entries
new file mode 100644
index 00000000..06bd5c8c
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Entries
@@ -0,0 +1,10 @@
+/hhmmQ_CPD.m/1.1.1.1/Mon Jun 24 18:19:00 2002//
+/log_prior.m/1.1.1.1/Mon Jun 24 18:19:00 2002//
+/maximize_params.m/1.1.1.1/Mon Jun 24 18:19:00 2002//
+/reset_ess.m/1.1.1.1/Mon Jun 24 18:19:00 2002//
+/update_CPT.m/1.1.1.1/Tue Sep 24 02:30:32 2002//
+/update_ess.m/1.1.1.1/Mon Jun 24 18:19:00 2002//
+/update_ess2.m/1.1.1.1/Mon Jun 24 21:20:52 2002//
+/update_ess3.m/1.1.1.1/Mon Jun 24 22:08:08 2002//
+/update_ess4.m/1.1.1.1/Mon Jun 24 22:23:32 2002//
+D
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Repository b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Repository
new file mode 100644
index 00000000..8e7c978a
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Repository
@@ -0,0 +1 @@
+FullBNT/BNT/CPDs/@hhmmQ_CPD/Old
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Root b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Root
new file mode 100644
index 00000000..f3bd14a6
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/CVS/Root
@@ -0,0 +1 @@
+:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/hhmmQ_CPD.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/hhmmQ_CPD.m
new file mode 100644
index 00000000..24ef464b
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/hhmmQ_CPD.m
@@ -0,0 +1,126 @@
+function CPD = hhmmQ_CPD(bnet, self, Qnodes, d, D, varargin)
+% HHMMQ_CPD Make the CPD for a Q node at depth D of a D-level hierarchical HMM
+% CPD = hhmmQ_CPD(bnet, self, Qnodes, d, D, ...)
+%
+%  Fd(t-1) \   Q1:d-1(t)
+%           \  |
+%            \ v
+%  Qd(t-1) -> Qd(t)
+%            /
+%           /
+%  Fd+1(t-1) 
+%
+% We assume parents are ordered (numbered) as follows:
+% Qd(t-1), Fd+1(t-1), Fd(t-1), Q1(t), ..., Qd(t)
+%
+% The parents of Qd(t) can either be just Qd-1(t) or the whole stack Q1:d-1(t) (allQ)
+% In either case, we will call them Qps.
+% If d=1, Qps does not exist. Also, the F1(t-1) -> Q1(t) arc is optional.
+% If the arc is missing, startprob does not need to be specified,
+% since the toplevel is assumed to never reset (F1 does not exist).
+% If d=D, Fd+1(t-1) does not exist (there is no signal from below).
+%
+% optional args [defaults]
+%
+% transprob - transprob(i,k,j) = prob transition from i to j given Qps = k ['leftright']
+% selfprob  - prob of a transition from i to i given Qps=k [0.1]
+% startprob - startprob(k,j) = prob start in j given Qps = k ['leftstart']
+% startargs - other args to be passed to the sub tabular_CPD for learning startprob
+% transargs - other args will be passed to the sub tabular_CPD for learning transprob
+% allQ      - 1 means use all Q nodes above d as parents, 0 means just level d-1 [0]
+% F1toQ1    - 1 means add F1(t-1) -> Q1(t) arc, 0 means level 1 never resets [0]
+%
+% For d=1, startprob(1,j) is only needed if F1toQ1=1
+% Also, transprob(i,j) can be used instead of transprob(i,1,j).
+%
+% hhmmQ_CPD is a subclass of tabular_CPD so we inherit inference methods like CPD_to_pot, etc.
+%
+% We create isolated tabular_CPDs with no F parents to learn transprob/startprob
+% so we can avail of e.g., entropic or Dirichlet priors.
+% In the future, we will be able to represent the transprob using a tree_CPD.
+%
+% For details, see "Linear-time inference in hierarchical HMMs", Murphy and Paskin, NIPS'01.
+
+
+ss = bnet.nnodes_per_slice;
+%assert(self == Qnodes(d)+ss);
+ns = bnet.node_sizes(:);
+CPD.Qsizes = ns(Qnodes);
+CPD.d = d;
+CPD.D = D;
+allQ = 0;
+
+% find out which parents to use, to get right size
+for i=1:2:length(varargin)
+  switch varargin{i},
+   case 'allQ', allQ = varargin{i+1}; 
+  end
+end
+
+if d==1
+  CPD.Qps = [];
+else
+  if allQ
+    CPD.Qps = Qnodes(1:d-1);
+  else
+    CPD.Qps = Qnodes(d-1);
+  end
+end
+
+Qsz = ns(self);
+Qpsz = prod(ns(CPD.Qps));
+
+% set default arguments
+startprob = 'leftstart';
+transprob = 'leftright';
+startargs = {};
+transargs = {};
+CPD.F1toQ1 = 0;
+selfprob = 0.1;
+
+for i=1:2:length(varargin)
+  switch varargin{i},
+   case 'transprob', transprob = varargin{i+1}; 
+   case 'selfprob',  selfprob = varargin{i+1}; 
+   case 'startprob', startprob = varargin{i+1}; 
+   case 'startargs', startargs = varargin{i+1}; 
+   case 'transargs', transargs = varargin{i+1}; 
+   case 'F1toQ1',    CPD.F1toQ1 = varargin{i+1}; 
+  end
+end
+
+Qps = CPD.Qps + ss;
+old_self = self-ss;
+
+if strcmp(transprob, 'leftright')
+  LR = mk_leftright_transmat(Qsz, selfprob);
+  transprob = repmat(reshape(LR, [1 Qsz Qsz]), [Qpsz 1 1]); % transprob(k,i,j)
+  transprob = permute(transprob, [2 1 3]); % now transprob(i,k,j)
+end
+transargs{end+1} = 'CPT';
+transargs{end+1} = transprob;
+CPD.sub_CPD_trans = mk_isolated_tabular_CPD([old_self Qps], ns([old_self Qps self]), transargs);
+S = struct(CPD.sub_CPD_trans);
+CPD.transprob = myreshape(S.CPT, [Qsz Qpsz Qsz]);
+
+
+if strcmp(startprob, 'leftstart')
+  startprob = zeros(Qpsz, Qsz);
+  startprob(:,1) = 1;
+end
+
+if (d==1) & ~CPD.F1toQ1
+  CPD.sub_CPD_start = [];
+  CPD.startprob = [];
+else
+  startargs{end+1} = 'CPT';
+  startargs{end+1} = startprob;
+  CPD.sub_CPD_start = mk_isolated_tabular_CPD(Qps, ns([Qps self]), startargs);
+  S = struct(CPD.sub_CPD_start);
+  CPD.startprob = myreshape(S.CPT, [Qpsz Qsz]);
+end
+
+CPD = class(CPD, 'hhmmQ_CPD', tabular_CPD(bnet, self));
+
+CPD = update_CPT(CPD);
+
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/log_prior.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/log_prior.m
new file mode 100644
index 00000000..d44bec5e
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/log_prior.m
@@ -0,0 +1,8 @@
+function L = log_prior(CPD)
+% LOG_PRIOR Return log P(theta) for a hhmm CPD 
+% L = log_prior(CPD)
+
+L = log_prior(CPD.sub_CPD_trans);
+if ~isempty(CPD.sub_CPD_start)
+  L = L + log_prior(CPD.sub_CPD_start);
+end
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/maximize_params.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/maximize_params.m
new file mode 100644
index 00000000..0e4632aa
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/maximize_params.m
@@ -0,0 +1,40 @@
+function CPD = maximize_params(CPD, temp)
+% MAXIMIZE_PARAMS Set the params of a hhmmQ node to their ML/MAP values.
+% CPD = maximize_params(CPD, temperature)
+
+Qsz = CPD.Qsizes(CPD.d);
+Qpsz = prod(CPD.Qsizes(CPD.Qps));
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = maximize_params(CPD.sub_CPD_start, temp);
+  S = struct(CPD.sub_CPD_start);
+  CPD.startprob = myreshape(S.CPT, [Qpsz Qsz]);
+  %CPD.startprob = S.CPT;
+end
+
+if 1
+  % If we are in a state that can only go the end state,
+  % we will never see a transition to another (non-end) state,
+  % so counts(i,k,j)=0 (and termprob(k,i)=1).
+  % We set counts(i,k,i)=1 in this case.
+  % This will cause remove_hhmm_end_state to return a
+  % stochastic matrix, but otherwise has no effect on EM.
+  counts = get_field(CPD.sub_CPD_trans, 'counts');
+  counts = reshape(counts, [Qsz Qpsz Qsz]);
+  for k=1:Qpsz
+    for i=1:Qsz
+      if sum(counts(i,k,:))==0 % never witnessed a transition out of i
+	counts(i,k,i)=1; % add self loop 
+	%fprintf('CPDQ d=%d i=%d k=%d\n', CPD.d, i, k);
+      end
+    end
+  end
+  CPD.sub_CPD_trans = set_fields(CPD.sub_CPD_trans, 'counts', counts(:)); 
+end
+ 
+CPD.sub_CPD_trans = maximize_params(CPD.sub_CPD_trans, temp);
+S = struct(CPD.sub_CPD_trans);
+%CPD.transprob = S.CPT;
+CPD.transprob = myreshape(S.CPT, [Qsz Qpsz Qsz]);
+
+CPD = update_CPT(CPD);
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/reset_ess.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/reset_ess.m
new file mode 100644
index 00000000..45a70ad7
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/reset_ess.m
@@ -0,0 +1,8 @@
+function CPD = reset_ess(CPD)
+% RESET_ESS Reset the Expected Sufficient Statistics of a hhmm Q node.
+% CPD = reset_ess(CPD)
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = reset_ess(CPD.sub_CPD_start);
+end
+CPD.sub_CPD_trans = reset_ess(CPD.sub_CPD_trans);   
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_CPT.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_CPT.m
new file mode 100644
index 00000000..503c225b
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_CPT.m
@@ -0,0 +1,74 @@
+function CPD = update_CPT(CPD)
+% Compute the big CPT for an HHMM Q node (including F parents) given internal transprob and startprob
+% function CPD = update_CPT(CPD)
+
+Qsz = CPD.Qsz;
+Qpsz = CPD.Qpsz;
+
+if ~isempty(CPD.Fbelow_ndx)
+  if ~isempty(CPD.Fself_ndx) % general case
+    % Fb(t-1) Fself(t-1)  P(Q(t)=j| Q(t-1)=i, Qps(t)=k)
+    % ------------------------------------------------------
+    % 1        1         delta(i,j)
+    % 2        1         transprob(i,k,j)
+    % 1        2         impossible
+    % 2        2         startprob(k,j)
+    CPT = zeros(Qsz, 2, 2, Qpsz, Qsz);
+    I = repmat(eye(Qsz), [1 1 Qpsz]); % i,j,k
+    I = permute(I, [1 3 2]); % i,k,j
+    CPT(:, 1, 1, :, :) = I;
+    CPT(:, 2, 1, :, :) = CPD.transprob;
+    CPT(:, 1, 2, :, :) = I;
+    CPT(:, 2, 2, :, :) = repmat(reshape(CPD.startprob, [1 Qpsz Qsz]), [Qsz 1 1]); % replicate over i
+  else % no F from self, hence no startprob
+    % Fb(t-1) P(Q(t)=j| Q(t-1)=i, Qps(t)=k)
+    % ------------------------------------------------------
+    % 1       delta(i,j)
+    % 2       transprob(i,k,j)
+    
+    nps = length(CPD.dom_sz)-1; % num parents
+    CPT = 0*myones(CPD.dom_sz);
+    %CPT = zeros(Qsz, 2, Qpsz, Qsz); % assumes CPT(Q(t-1), F(t-1), Qps, Q(t))
+    % but a member of Qps may preceed Q(t-1) or F(t-1) in the ordering
+    
+    I = repmat(eye(Qsz), [1 1 Qpsz]); % i,j,k
+    I = permute(I, [1 3 2]); % i,k,j
+
+    % the following fails if there is a member of Qps with a lower
+    % number than F
+    %CPT(:, 1, :, :) = I;
+    %CPT(:, 2, :, :) = CPD.transprob;
+
+    ndx = mk_multi_index(nps+1, CPD.Fbelow_ndx, 1);
+    CPT(ndx{:}) = I;
+    ndx = mk_multi_index(nps+1, CPD.Fbelow_ndx, 2);
+    CPT(ndx{:}) = CPD.transprob;
+    keyboard
+  end
+else % no F signal from below
+  if ~isempty(CPD.Fself_ndx)
+    % Q(t-1), Fself(t-1), Qps, Q(t)
+    
+    % if condition start on previous concrete state (as in map learning),
+    % CPT(:, 1, :, :, :) = CPD.transprob(Q(t-1), Qps, Q(t))
+    % CPT(:, 2, :, :, :) = CPD.startprob(Q(t-1), Qps, Q(t))
+    
+    % Fself(t-1)  P(Q(t-1)=i, Qps(t)=k -> Q(t)=j)
+    % ------------------------------------------------------
+    % 1         transprob(i,k,j)
+    % 2         startprob(k,j)
+    CPT = zeros(Qsz, 2, Qpsz, Qsz);
+    I = repmat(eye(Qsz), [1 1 Qpsz]); % i,j,k
+    I = permute(I, [1 3 2]); % i,k,j
+    CPT(:, 1, :, :) = CPD.transprob;
+    if CPD.fullstartprob
+      CPT(:, 2, :, :) = CPD.startprob;
+    else
+      CPT(:, 2, :, :) = repmat(reshape(CPD.startprob, [1 Qpsz Qsz]), [Qsz 1 1]); % replicate over i
+    end
+    else % no F from self
+    error('An hhmmQ node without any F parents is just a tabular_CPD')
+  end
+end
+
+CPD = set_fields(CPD, 'CPT', CPT);          
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess.m
new file mode 100644
index 00000000..51c2bd1f
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess.m
@@ -0,0 +1,141 @@
+function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
+% UPDATE_ESS Update the Expected Sufficient Statistics of a hhmm Q node.
+% function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, idden_bitv)
+
+% Figure out the node numbers associated with each parent
+% e.g., D=4, d=3, Qps = all Qs above, so dom = [Q3(t-1) F4(t-1) F3(t-1) Q1(t) Q2(t) Q3(t)].
+% so self = Q3(t), old_self = Q3(t-1), CPD.Qps = [1 2], Qps = [Q1(t) Q2(t)]
+dom = fmarginal.domain;
+self = dom(end);
+old_self = dom(1);
+Qps = dom(length(dom)-length(CPD.Qps):end-1);
+
+Qsz = CPD.Qsizes(CPD.d);
+Qpsz = prod(CPD.Qsizes(CPD.Qps));
+
+% If some of the Q nodes are observed (which happens during supervised training)
+% the counts will only be non-zero in positions
+% consistent with the evidence. We put the computed marginal responsibilities
+% into the appropriate slots of the big counts array.
+% (Recall that observed discrete nodes only have a single effective value.)
+% (A more general, but much slower, way is to call add_evidence_to_dmarginal.)
+% We assume the F nodes are never observed.
+
+obs_self = ~hidden_bitv(self);
+obs_Qps = (~isempty(Qps)) & (~any(hidden_bitv(Qps))); % we assume that all or none of the Q parents are observed
+
+if obs_self
+  self_val = evidence{self};
+  oldself_val = evidence{old_self};
+end
+
+if obs_Qps
+  Qps_val = subv2ind(Qpsz, cat(1, evidence{Qps}));
+  if Qps_val == 0
+    keyboard
+  end
+end
+
+if CPD.d==1 % no Qps from above
+  if ~CPD.F1toQ1 % no F from self
+    % marg(Q1(t-1), F2(t-1), Q1(t))                            
+    % F2(t-1) P(Q1(t)=j | Q1(t-1)=i)
+    % 1       delta(i,j)
+    % 2       transprob(i,j)
+    if obs_self
+      hor_counts = zeros(Qsz, Qsz);
+      hor_counts(oldself_val, self_val) = fmarginal.T(2);
+    else
+      marg = reshape(fmarginal.T, [Qsz 2 Qsz]);
+      hor_counts = squeeze(marg(:,2,:));
+    end
+  else
+    % marg(Q1(t-1), F2(t-1), F1(t-1), Q1(t))                            
+    % F2(t-1) F1(t-1)  P(Qd(t)=j| Qd(t-1)=i)
+    % ------------------------------------------------------
+    % 1        1         delta(i,j)
+    % 2        1         transprob(i,j)
+    % 1        2         impossible
+    % 2        2         startprob(j)
+    if obs_self
+      marg = myreshape(fmarginal.T, [1 2 2 1]);
+      hor_counts = zeros(Qsz, Qsz);
+      hor_counts(oldself_val, self_val) = marg(1,2,1,1);
+      ver_counts = zeros(Qsz, 1);
+      %ver_counts(self_val) = marg(1,2,2,1);
+      ver_counts(self_val) = marg(1,2,2,1) + marg(1,1,2,1);
+    else
+      marg = reshape(fmarginal.T, [Qsz 2 2 Qsz]);
+      hor_counts = squeeze(marg(:,2,1,:));
+      %ver_counts = squeeze(sum(marg(:,2,2,:),1)); % sum over i
+      ver_counts = squeeze(sum(marg(:,2,2,:),1)) + squeeze(sum(marg(:,1,2,:),1)); % sum i,b
+    end
+  end % F1toQ1
+else % d ~= 1
+  if CPD.d < CPD.D % general case
+    % marg(Qd(t-1), Fd+1(t-1), Fd(t-1), Qps(t), Qd(t))                            
+    % Fd+1(t-1) Fd(t-1)  P(Qd(t)=j| Qd(t-1)=i, Qps(t)=k)
+    % ------------------------------------------------------
+    % 1        1         delta(i,j)
+    % 2        1         transprob(i,k,j)
+    % 1        2         impossible
+    % 2        2         startprob(k,j)
+    if obs_Qps & obs_self
+      marg = myreshape(fmarginal.T, [1 2 2 1 1]);
+      k = 1;
+      hor_counts = zeros(Qsz, Qpsz, Qsz);
+      hor_counts(oldself_val, Qps_val, self_val) = marg(1, 2,1, k,1);
+      ver_counts = zeros(Qpsz, Qsz);
+      %ver_counts(Qps_val, self_val) = marg(1, 2,2, k,1);
+      ver_counts(Qps_val, self_val) = marg(1, 2,2, k,1) + marg(1, 1,2, k,1);
+    elseif obs_Qps & ~obs_self
+      marg = myreshape(fmarginal.T, [Qsz 2 2 1 Qsz]);
+      k = 1;
+      hor_counts = zeros(Qsz, Qpsz, Qsz);
+      hor_counts(:, Qps_val, :) = marg(:, 2,1, k,:);
+      ver_counts = zeros(Qpsz, Qsz);
+      %ver_counts(Qps_val, :) = sum(marg(:, 2,2, k,:), 1);
+      ver_counts(Qps_val, :) = sum(marg(:, 2,2, k,:), 1) + sum(marg(:, 1,2, k,:), 1);
+    elseif ~obs_Qps & obs_self
+      error('not yet implemented')
+    else % everything is hidden
+      marg = reshape(fmarginal.T, [Qsz 2 2 Qpsz Qsz]);
+      hor_counts = squeeze(marg(:,2,1,:,:)); % i,k,j
+      %ver_counts = squeeze(sum(marg(:,2,2,:,:),1)); % sum over i
+      ver_counts = squeeze(sum(marg(:,2,2,:,:),1)) + squeeze(sum(marg(:,1,2,:,:),1)); % sum over i,b
+    end
+  else % d == D, so no F from below
+    % marg(QD(t-1), FD(t-1), Qps(t), QD(t))                            
+    % FD(t-1) P(QD(t)=j | QD(t-1)=i, Qps(t)=k)
+    % 1      transprob(i,k,j) 
+    % 2      startprob(k,j)
+    if obs_Qps & obs_self
+      marg = myreshape(fmarginal.T, [1 2 1 1]);
+      k = 1;
+      hor_counts = zeros(Qsz, Qpsz, Qsz);
+      hor_counts(oldself_val, Qps_val, self_val) = marg(1, 1, k,1);
+      ver_counts = zeros(Qpsz, Qsz);
+      ver_counts(Qps_val, self_val) = marg(1, 2, k,1);
+    elseif obs_Qps & ~obs_self
+      marg = myreshape(fmarginal.T, [Qsz 2 1 Qsz]);
+      k = 1;
+      hor_counts = zeros(Qsz, Qpsz, Qsz);
+      hor_counts(:, Qps_val, :) = marg(:, 1, k,:);
+      ver_counts = zeros(Qpsz, Qsz);
+      ver_counts(Qps_val, :) = sum(marg(:, 2, k, :), 1);
+    elseif ~obs_Qps & obs_self
+      error('not yet implemented')
+    else % everything is hidden
+      marg = reshape(fmarginal.T, [Qsz 2 Qpsz Qsz]);
+      hor_counts = squeeze(marg(:,1,:,:));
+      ver_counts = squeeze(sum(marg(:,2,:,:),1)); % sum over i
+    end
+  end
+end
+
+CPD.sub_CPD_trans = update_ess_simple(CPD.sub_CPD_trans, hor_counts);
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = update_ess_simple(CPD.sub_CPD_start, ver_counts);
+end
+
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess2.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess2.m
new file mode 100644
index 00000000..41fc7380
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess2.m
@@ -0,0 +1,178 @@
+function CPD = update_ess2(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
+% UPDATE_ESS Update the Expected Sufficient Statistics of a hhmm Q node.
+% function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, idden_bitv)
+
+% Figure out the node numbers associated with each parent
+dom = fmarginal.domain;
+self = dom(end); % by assumption
+old_self = dom(CPD.old_self_ndx);
+Fself = dom(CPD.Fself_ndx);
+Fbelow = dom(CPD.Fbelow_ndx);
+Qps = dom(CPD.Qps_ndx);
+
+Qsz = CPD.Qsz;
+Qpsz = CPD.Qpsz;
+
+
+fmarg = add_ev_to_dmarginal(fmarginal, evidence, ns);
+
+
+
+% hor_counts(old_self, Qps, self),
+% fmarginal(old_self, Fbelow, Fself, Qps, self)
+% hor_counts(i,k,j) = fmarginal(i,2,1,k,j) % below has finished, self has not
+% ver_counts(i,k,j) = fmarginal(i,2,2,k,j) % below has finished, and so has self (reset)
+% Since any of i,j,k may be observed, we write
+% hor_counts(counts_ndx{:}) = fmarginal(fmarg_ndx{:})
+% where e.g., counts_ndx = {1, ':', 2} if Qps is hidden but we observe old_self=1, self=2.
+% To create this counts_ndx, we write counts_ndx = mk_multi_ndx(3, obs_dim, obs_val)
+% where counts_obs_dim = [1 3], counts_obs_val = [1 2] specifies the values of dimensions 1 and 3.
+
+counts_obs_dim = [];
+fmarg_obs_dim = [];
+obs_val = []; 
+if hidden_bitv(self)
+  effQsz = Qsz;
+else
+  effQsz = 1;
+  counts_obs_dim = [counts_obs_dim 3];
+  fmarg_obs_dim = [fmarg_obs_dim 5];
+  obs_val = [obs_val evidence{self}];
+end
+  
+% e.g., D=4, d=3, Qps = all Qs above, so dom = [Q3(t-1) F4(t-1) F3(t-1) Q1(t) Q2(t) Q3(t)].
+% so self = Q3(t), old_self = Q3(t-1), CPD.Qps = [1 2], Qps = [Q1(t) Q2(t)]
+dom = fmarginal.domain;
+self = dom(end);
+old_self = dom(1);
+Qps = dom(length(dom)-length(CPD.Qps):end-1);
+
+Qsz = CPD.Qsizes(CPD.d);
+Qpsz = prod(CPD.Qsizes(CPD.Qps));
+
+% If some of the Q nodes are observed (which happens during supervised training)
+% the counts will only be non-zero in positions
+% consistent with the evidence. We put the computed marginal responsibilities
+% into the appropriate slots of the big counts array.
+% (Recall that observed discrete nodes only have a single effective value.)
+% (A more general, but much slower, way is to call add_evidence_to_dmarginal.)
+% We assume the F nodes are never observed.
+
+obs_self = ~hidden_bitv(self);
+obs_Qps = (~isempty(Qps)) & (~any(hidden_bitv(Qps))); % we assume that all or none of the Q parents are observed
+
+if obs_self
+  self_val = evidence{self};
+  oldself_val = evidence{old_self};
+end
+
+if obs_Qps
+  Qps_val = subv2ind(Qpsz, cat(1, evidence{Qps}));
+  if Qps_val == 0
+    keyboard
+  end
+end
+
+if CPD.d==1 % no Qps from above
+  if ~CPD.F1toQ1 % no F from self
+    % marg(Q1(t-1), F2(t-1), Q1(t))                            
+    % F2(t-1) P(Q1(t)=j | Q1(t-1)=i)
+    % 1       delta(i,j)
+    % 2       transprob(i,j)
+    if obs_self
+      hor_counts = zeros(Qsz, Qsz);
+      hor_counts(oldself_val, self_val) = fmarginal.T(2);
+    else
+      marg = reshape(fmarginal.T, [Qsz 2 Qsz]);
+      hor_counts = squeeze(marg(:,2,:));
+    end
+  else
+    % marg(Q1(t-1), F2(t-1), F1(t-1), Q1(t))                            
+    % F2(t-1) F1(t-1)  P(Qd(t)=j| Qd(t-1)=i)
+    % ------------------------------------------------------
+    % 1        1         delta(i,j)
+    % 2        1         transprob(i,j)
+    % 1        2         impossible
+    % 2        2         startprob(j)
+    if obs_self
+      marg = myreshape(fmarginal.T, [1 2 2 1]);
+      hor_counts = zeros(Qsz, Qsz);
+      hor_counts(oldself_val, self_val) = marg(1,2,1,1);
+      ver_counts = zeros(Qsz, 1);
+      %ver_counts(self_val) = marg(1,2,2,1);
+      ver_counts(self_val) = marg(1,2,2,1) + marg(1,1,2,1);
+    else
+      marg = reshape(fmarginal.T, [Qsz 2 2 Qsz]);
+      hor_counts = squeeze(marg(:,2,1,:));
+      %ver_counts = squeeze(sum(marg(:,2,2,:),1)); % sum over i
+      ver_counts = squeeze(sum(marg(:,2,2,:),1)) + squeeze(sum(marg(:,1,2,:),1)); % sum i,b
+    end
+  end % F1toQ1
+else % d ~= 1
+  if CPD.d < CPD.D % general case
+    % marg(Qd(t-1), Fd+1(t-1), Fd(t-1), Qps(t), Qd(t))                            
+    % Fd+1(t-1) Fd(t-1)  P(Qd(t)=j| Qd(t-1)=i, Qps(t)=k)
+    % ------------------------------------------------------
+    % 1        1         delta(i,j)
+    % 2        1         transprob(i,k,j)
+    % 1        2         impossible
+    % 2        2         startprob(k,j)
+    if obs_Qps & obs_self
+      marg = myreshape(fmarginal.T, [1 2 2 1 1]);
+      k = 1;
+      hor_counts = zeros(Qsz, Qpsz, Qsz);
+      hor_counts(oldself_val, Qps_val, self_val) = marg(1, 2,1, k,1);
+      ver_counts = zeros(Qpsz, Qsz);
+      %ver_counts(Qps_val, self_val) = marg(1, 2,2, k,1);
+      ver_counts(Qps_val, self_val) = marg(1, 2,2, k,1) + marg(1, 1,2, k,1);
+    elseif obs_Qps & ~obs_self
+      marg = myreshape(fmarginal.T, [Qsz 2 2 1 Qsz]);
+      k = 1;
+      hor_counts = zeros(Qsz, Qpsz, Qsz);
+      hor_counts(:, Qps_val, :) = marg(:, 2,1, k,:);
+      ver_counts = zeros(Qpsz, Qsz);
+      %ver_counts(Qps_val, :) = sum(marg(:, 2,2, k,:), 1);
+      ver_counts(Qps_val, :) = sum(marg(:, 2,2, k,:), 1) + sum(marg(:, 1,2, k,:), 1);
+    elseif ~obs_Qps & obs_self
+      error('not yet implemented')
+    else % everything is hidden
+      marg = reshape(fmarginal.T, [Qsz 2 2 Qpsz Qsz]);
+      hor_counts = squeeze(marg(:,2,1,:,:)); % i,k,j
+      %ver_counts = squeeze(sum(marg(:,2,2,:,:),1)); % sum over i
+      ver_counts = squeeze(sum(marg(:,2,2,:,:),1)) + squeeze(sum(marg(:,1,2,:,:),1)); % sum over i,b
+    end
+  else % d == D, so no F from below
+    % marg(QD(t-1), FD(t-1), Qps(t), QD(t))                            
+    % FD(t-1) P(QD(t)=j | QD(t-1)=i, Qps(t)=k)
+    % 1      transprob(i,k,j) 
+    % 2      startprob(k,j)
+    if obs_Qps & obs_self
+      marg = myreshape(fmarginal.T, [1 2 1 1]);
+      k = 1;
+      hor_counts = zeros(Qsz, Qpsz, Qsz);
+      hor_counts(oldself_val, Qps_val, self_val) = marg(1, 1, k,1);
+      ver_counts = zeros(Qpsz, Qsz);
+      ver_counts(Qps_val, self_val) = marg(1, 2, k,1);
+    elseif obs_Qps & ~obs_self
+      marg = myreshape(fmarginal.T, [Qsz 2 1 Qsz]);
+      k = 1;
+      hor_counts = zeros(Qsz, Qpsz, Qsz);
+      hor_counts(:, Qps_val, :) = marg(:, 1, k,:);
+      ver_counts = zeros(Qpsz, Qsz);
+      ver_counts(Qps_val, :) = sum(marg(:, 2, k, :), 1);
+    elseif ~obs_Qps & obs_self
+      error('not yet implemented')
+    else % everything is hidden
+      marg = reshape(fmarginal.T, [Qsz 2 Qpsz Qsz]);
+      hor_counts = squeeze(marg(:,1,:,:));
+      ver_counts = squeeze(sum(marg(:,2,:,:),1)); % sum over i
+    end
+  end
+end
+
+CPD.sub_CPD_trans = update_ess_simple(CPD.sub_CPD_trans, hor_counts);
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = update_ess_simple(CPD.sub_CPD_start, ver_counts);
+end
+
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess3.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess3.m
new file mode 100644
index 00000000..da7ab6bd
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess3.m
@@ -0,0 +1,80 @@
+function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
+% UPDATE_ESS Update the Expected Sufficient Statistics of a hhmm Q node.
+% function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, idden_bitv)
+%
+% we assume if one of the Qps is observed, all of them are 
+% We assume the F nodes are already hidden 
+
+% Figure out the node numbers associated with each parent
+dom = fmarginal.domain;
+self = dom(CPD.self_ndx);
+old_self = dom(CPD.old_self_ndx);
+%Fself = dom(CPD.Fself_ndx);
+%Fbelow = dom(CPD.Fbelow_ndx);
+Qps = dom(CPD.Qps_ndx);
+
+Qsz = CPD.Qsz;
+Qpsz = CPD.Qpsz;
+
+
+% hor_counts(old_self, Qps, self),
+% fmarginal(old_self, Fbelow, Fself, Qps, self)
+% hor_counts(i,k,j) = fmarginal(i,2,1,k,j) % below has finished, self has not
+% ver_counts(i,k,j) = fmarginal(i,2,2,k,j) % below has finished, and so has self (reset)
+% Since any of i,j,k may be observed, we write
+% hor_counts(ndx{:}) = fmarginal(...)
+% where e.g., ndx = {1, ':', 2} if Qps is hidden but we observe old_self=1, self=2.
+
+% ndx{i,k,j}
+if hidden_bitv(old_self)
+  ndx{1} = ':';
+else
+  ndx{1} = evidence{old_self};
+end
+if hidden_bitv(Qps)
+  ndx{2} = ':';
+else
+  ndx{2} = subv2ind(Qpsz, cat(1, evidence{Qps}));
+end
+if hidden_bitv(self)
+  ndx{3} = ':';
+else
+  ndx{3} = evidence{self};
+end
+
+fmarg = add_ev_to_dmarginal(fmarginal, evidence, ns);
+% marg(Qold(t-1), Fbelow(t-1), Fself(t-1), Qps(t), Qself(t))                            
+hor_counts = zeros(Qsz, Qpsz, Qsz);
+ver_counts = zeros(Qpsz, Qsz);
+    
+if ~isempty(CPD.Fbelow_ndx)
+  if ~isempty(CPD.Fself_ndx) % general case
+    fmarg.T = myreshape(fmarg.T, [Qsz 2 2 Qpsz Qsz]);
+    marg_ndx = {ndx{1}, 2, 1, ndx{2}, ndx{3}};
+    hor_counts(ndx{:}) = fmarg.T(marg_ndx{:});
+    ver_counts(ndx{2:3}) = ... % sum over Fbelow and Qold=i
+	sum(fmarg.T({ndx{1}, 1, 2, ndx{2}, ndx{3}}),1) + ..
+	sum(fmarg.T({ndx{1}, 2, 2, ndx{2}, ndx{3}}),1);
+  else % no F from self, hence no startprob
+    fmarg.T = myreshape(fmarg.T, [Qsz 2 Qpsz Qsz]);
+    hor_counts(ndx{:}) = fmarg.T({ndx{1}, 2, ndx{2}, ndx{3}});
+  end
+else % no F signal from below
+  if ~isempty(CPD.Fself_ndx) % self F
+    fmarg.T = myreshape(fmarg.T, [Qsz 2 Qpsz Qsz]);
+    hor_counts(ndx{:}) = fmarg.T({ndx{1}, 1, ndx{2}, ndx{3}});
+    ver_counts(ndx{2:3}) = ... % sum over Qold=i
+	sum(fmarg.T({ndx{1}, 2, ndx{2}, ndx{3}}),1);
+  else % no F from self
+    error('An hhmmQ node without any F parents is just a tabular_CPD')
+  end
+end
+
+
+CPD.sub_CPD_trans = update_ess_simple(CPD.sub_CPD_trans, hor_counts);
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = update_ess_simple(CPD.sub_CPD_start, ver_counts);
+end
+
+
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess4.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess4.m
new file mode 100644
index 00000000..c826da1c
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/Old/update_ess4.m
@@ -0,0 +1,95 @@
+function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
+% UPDATE_ESS Update the Expected Sufficient Statistics of a hhmm Q node.
+% function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, idden_bitv)
+%
+% we assume if one of the Qps is observed, all of them are 
+% We assume the F nodes are already hidden 
+
+% Figure out the node numbers associated with each parent
+dom = fmarginal.domain;
+self = dom(CPD.self_ndx);
+old_self = dom(CPD.old_self_ndx);
+%Fself = dom(CPD.Fself_ndx);
+%Fbelow = dom(CPD.Fbelow_ndx);
+Qps = dom(CPD.Qps_ndx);
+
+Qsz = CPD.Qsz;
+Qpsz = CPD.Qpsz;
+
+
+% hor_counts(old_self, Qps, self),
+% fmarginal(old_self, Fbelow, Fself, Qps, self)
+% hor_counts(i,k,j) = fmarginal(i,2,1,k,j) % below has finished, self has not
+% ver_counts(i,k,j) = fmarginal(i,2,2,k,j) % below has finished, and so has self (reset)
+% Since any of i,j,k may be observed, we write
+% hor_counts(i_counts_ndx, kndx, jndx) = fmarginal(i_fmarg_ndx...)
+% where i_fmarg_ndx = 1 and i_counts_ndx = i if old_self is observed to have value i,
+% i_fmarg_ndx = 1:Qsz and i_counts_ndx = 1:Qsz if old_self is hidden, etc.
+
+
+if hidden_bitv(old_self)
+  i_counts_ndx = 1:Qsz;
+  i_fmarg_ndx = 1:Qsz;
+  eff_oldQsz = Qsz;
+else
+  i_counts_ndx = evidence{old_self};
+  i_fmarg_ndx = 1;
+  eff_oldQsz = 1;
+end
+
+if all(hidden_bitv(Qps)) % we assume all are hidden or all are observed
+  k_counts_ndx = 1:Qpsz;
+  k_fmarg_ndx = 1:Qpsz;
+  eff_Qpsz = Qpsz;
+else
+  k_counts_ndx = subv2ind(Qpsz, cat(1, evidence{Qps}));
+  k_fmarg_ndx = 1;
+  eff_Qpsz = 1;
+end
+
+if hidden_bitv(self)
+  j_counts_ndx = 1:Qsz;
+  j_fmarg_ndx = 1:Qsz;
+  eff_Qsz = Qsz;
+else
+  j_counts_ndx = evidence{self};
+  j_fmarg_ndx = 1;
+  eff_Qsz = 1;
+end
+
+hor_counts = zeros(Qsz, Qpsz, Qsz);
+ver_counts = zeros(Qpsz, Qsz);
+    
+if ~isempty(CPD.Fbelow_ndx)
+  if ~isempty(CPD.Fself_ndx) % general case
+    fmarg.T = myreshape(fmarg.T, [eff_oldQsz 2 2 eff_Qpsz eff_Qsz]);
+    hor_counts(i_counts_ndx, k_counts_ndx, j_counts_ndx) = ...
+	fmarg.T(:, i_fmarg_ndx, 2, 1, k_fmarg_ndx, j_fmarg_ndx);
+    ver_counts(k_counts_ndx, j_counts_ndx) = ... % sum over Fbelow and Qold
+	sum(fmarg.T(:, 1, 2, k_fmarg_ndx, j_fmarg_ndx), 1) + ...
+	sum(fmarg.T(:, 2, 2, k_fmarg_ndx, j_fmarg_ndx), 1); 
+  else % no F from self, hence no startprob
+    fmarg.T = myreshape(fmarg.T, [eff_oldQsz 2 eff_Qpsz eff_Qsz]);
+    hor_counts(i_counts_ndx, k_counts_ndx, j_counts_ndx) = ...
+	fmarg.T(i_fmarg_ndx, 2, k_fmarg_ndx, j_fmarg_ndx);
+  end
+else % no F signal from below
+  if ~isempty(CPD.Fself_ndx) % self F
+    fmarg.T = myreshape(fmarg.T, [eff_oldQsz 2 eff_Qpsz eff_Qsz]);
+    hor_counts(i_counts_ndx, k_counts_ndx, j_counts_ndx) = ...
+	fmarg.T(i_fmarg_ndx, 1, k_fmarg_ndx, j_fmarg_ndx);
+    ver_counts(k_counts_ndx, j_counts_ndx) = ... % sum over Qold
+	sum(fmarg.T(:, 2, k_fmarg_ndx, j_fmarg_ndx), 1);
+  else % no F from self
+    error('An hhmmQ node without any F parents is just a tabular_CPD')
+  end
+end
+
+
+CPD.sub_CPD_trans = update_ess_simple(CPD.sub_CPD_trans, hor_counts);
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = update_ess_simple(CPD.sub_CPD_start, ver_counts);
+end
+
+
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/hhmmQ_CPD.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/hhmmQ_CPD.m
new file mode 100644
index 00000000..6f289602
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/hhmmQ_CPD.m
@@ -0,0 +1,132 @@
+function CPD = hhmmQ_CPD(bnet, self, varargin)
+% HHMMQ_CPD Make the CPD for a Q node in a hierarchical HMM
+% CPD = hhmmQ_CPD(bnet, self, ...)
+%
+%  Fself(t-1)   Qps(t)
+%           \    |
+%            \   v
+%  Qold(t-1) ->  Q(t)
+%            /
+%           /
+%  Fbelow(t-1) 
+%
+% Let ss = slice size = num. nodes per slice.
+% This node is Q(t), and has mandatory parents Qold(t-1) (assumed to be numbered Q(t)-ss)
+% and optional parents Fbelow, Fself, Qps.
+% We require parents to be ordered (numbered) as follows:
+% Qold, Fbelow, Fself, Qps, Q.
+%
+% If Fself=2, we use the transition matrix, else we use the prior matrix.
+% If Fself node is omitted (eg. top level), we always use the transition matrix.
+% If Fbelow=2, we may change state, otherwise we must stay in the same state.
+% If Fbelow node is omitted (eg., bottom level), we may change state at every step.
+% If Qps (Q parents) are specified, all parameters are conditioned on their joint value.
+% We may choose any subset of nodes to condition on, as long as they as numbered lower than self.
+%
+% optional args [defaults]
+%
+% Fself - node number <= ss
+% Fbelow  - node number  <= ss
+% Qps - node numbers (all <= 2*ss) - uses 2TBN indexing
+% transprob - transprob(i,k,j) = prob transition from i to j given Qps = k ['leftright']
+% selfprob  - prob of a transition from i to i given Qps=k [0.1]
+% startprob - startprob(k,j) = prob start in j given Qps = k ['leftstart']
+% startargs - other args to be passed to the sub tabular_CPD for learning startprob
+% transargs - other args will be passed to the sub tabular_CPD for learning transprob
+% fullstartprob - 1 means startprob depends on Q(t-1) [0]
+% hhmmQ_CPD is a subclass of tabular_CPD so we inherit inference methods like CPD_to_pot, etc.
+%
+% We create isolated tabular_CPDs with no F parents to learn transprob/startprob
+% so we can avail of e.g., entropic or Dirichlet priors.
+% In the future, we will be able to represent the transprob using a tree_CPD.
+%
+% For details, see "Linear-time inference in hierarchical HMMs", Murphy and Paskin, NIPS'01.
+
+
+ss = bnet.nnodes_per_slice;
+ns = bnet.node_sizes(:);
+
+% set default arguments
+Fself = [];
+Fbelow = [];
+Qps = [];
+startprob = 'leftstart';
+transprob = 'leftright';
+startargs = {};
+transargs = {};
+selfprob = 0.1;
+fullstartprob = 0;
+
+for i=1:2:length(varargin)
+  switch varargin{i},
+   case 'Fself', Fself = varargin{i+1};
+   case 'Fbelow', Fbelow = varargin{i+1};
+   case 'Qps', Qps = varargin{i+1};
+   case 'transprob', transprob = varargin{i+1}; 
+   case 'selfprob',  selfprob = varargin{i+1}; 
+   case 'startprob', startprob = varargin{i+1}; 
+   case 'startargs', startargs = varargin{i+1}; 
+   case 'transargs', transargs = varargin{i+1}; 
+   case 'fullstartprob', fullstartprob = varargin{i+1}; 
+  end
+end
+
+CPD.fullstartprob = fullstartprob;
+
+ps = parents(bnet.dag, self);
+ndsz = ns(:)';
+CPD.dom_sz = [ndsz(ps) ns(self)];
+CPD.Fself_ndx = find_equiv_posns(Fself, ps);
+CPD.Fbelow_ndx = find_equiv_posns(Fbelow, ps);
+%CPD.Qps_ndx = find_equiv_posns(Qps+ss, ps);
+CPD.Qps_ndx = find_equiv_posns(Qps, ps);
+old_self = self-ss;
+CPD.old_self_ndx = find_equiv_posns(old_self, ps);
+
+Qps = ps(CPD.Qps_ndx);
+CPD.Qsz = ns(self);
+CPD.Qpsz = prod(ns(Qps));
+CPD.Qpsizes = ns(Qps);
+Qsz = CPD.Qsz;
+Qpsz = CPD.Qpsz;
+
+if strcmp(transprob, 'leftright')
+  LR = mk_leftright_transmat(Qsz, selfprob);
+  transprob = repmat(reshape(LR, [1 Qsz Qsz]), [Qpsz 1 1]); % transprob(k,i,j)
+  transprob = permute(transprob, [2 1 3]); % now transprob(i,k,j)
+end
+transargs{end+1} = 'CPT';
+transargs{end+1} = transprob;
+CPD.sub_CPD_trans = mk_isolated_tabular_CPD(ns([old_self Qps self]), transargs);
+S = struct(CPD.sub_CPD_trans);
+%CPD.transprob = myreshape(S.CPT, [Qsz Qpsz Qsz]);
+CPD.transprob = S.CPT;
+
+
+if strcmp(startprob, 'leftstart')
+  startprob = zeros(Qpsz, Qsz);
+  startprob(:,1) = 1;
+end
+if isempty(CPD.Fself_ndx)
+  CPD.sub_CPD_start = [];
+  CPD.startprob = [];
+else
+  startargs{end+1} = 'CPT';
+  startargs{end+1} = startprob;
+  if CPD.fullstartprob
+    CPD.sub_CPD_start = mk_isolated_tabular_CPD(ns([self Qps self]), startargs);
+    S = struct(CPD.sub_CPD_start);
+    %CPD.startprob = myreshape(S.CPT, [Qsz Qpsz Qsz]);
+    CPD.startprob = S.CPT;
+  else
+    CPD.sub_CPD_start = mk_isolated_tabular_CPD(ns([Qps self]), startargs);
+    S = struct(CPD.sub_CPD_start);
+    %CPD.startprob = myreshape(S.CPT, [CPD.Qpsizes Qsz]);
+    CPD.startprob = S.CPT;
+  end
+end
+
+CPD = class(CPD, 'hhmmQ_CPD', tabular_CPD(bnet, self));
+
+CPD = update_CPT(CPD);
+
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/log_prior.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/log_prior.m
new file mode 100644
index 00000000..d44bec5e
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/log_prior.m
@@ -0,0 +1,8 @@
+function L = log_prior(CPD)
+% LOG_PRIOR Return log P(theta) for a hhmm CPD 
+% L = log_prior(CPD)
+
+L = log_prior(CPD.sub_CPD_trans);
+if ~isempty(CPD.sub_CPD_start)
+  L = L + log_prior(CPD.sub_CPD_start);
+end
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/maximize_params.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/maximize_params.m
new file mode 100644
index 00000000..541a50be
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/maximize_params.m
@@ -0,0 +1,40 @@
+function CPD = maximize_params(CPD, temp)
+% MAXIMIZE_PARAMS Set the params of a hhmmQ node to their ML/MAP values.
+% CPD = maximize_params(CPD, temperature)
+
+Qsz = CPD.Qsz;
+Qpsz = CPD.Qpsz;
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = maximize_params(CPD.sub_CPD_start, temp);
+  S = struct(CPD.sub_CPD_start);
+  CPD.startprob = myreshape(S.CPT, [Qpsz Qsz]);
+  %CPD.startprob = S.CPT;
+end
+
+if 1
+  % If we are in a state that can only go the end state,
+  % we will never see a transition to another (non-end) state,
+  % so counts(i,k,j)=0 (and termprob(k,i)=1).
+  % We set counts(i,k,i)=1 in this case.
+  % This will cause remove_hhmm_end_state to return a
+  % stochastic matrix, but otherwise has no effect on EM.
+  counts = get_field(CPD.sub_CPD_trans, 'counts');
+  counts = reshape(counts, [Qsz Qpsz Qsz]);
+  for k=1:Qpsz
+    for i=1:Qsz
+      if sum(counts(i,k,:))==0 % never witnessed a transition out of i
+	counts(i,k,i)=1; % add self loop 
+	%fprintf('CPDQ d=%d i=%d k=%d\n', CPD.d, i, k);
+      end
+    end
+  end
+  CPD.sub_CPD_trans = set_fields(CPD.sub_CPD_trans, 'counts', counts(:)); 
+end
+ 
+CPD.sub_CPD_trans = maximize_params(CPD.sub_CPD_trans, temp);
+S = struct(CPD.sub_CPD_trans);
+%CPD.transprob = S.CPT;
+CPD.transprob = myreshape(S.CPT, [Qsz Qpsz Qsz]);
+
+CPD = update_CPT(CPD);
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/reset_ess.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/reset_ess.m
new file mode 100644
index 00000000..45a70ad7
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/reset_ess.m
@@ -0,0 +1,8 @@
+function CPD = reset_ess(CPD)
+% RESET_ESS Reset the Expected Sufficient Statistics of a hhmm Q node.
+% CPD = reset_ess(CPD)
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = reset_ess(CPD.sub_CPD_start);
+end
+CPD.sub_CPD_trans = reset_ess(CPD.sub_CPD_trans);   
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/update_CPT.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/update_CPT.m
new file mode 100644
index 00000000..9ed1a352
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/update_CPT.m
@@ -0,0 +1,70 @@
+function CPD = update_CPT(CPD)
+% Compute the big CPT for an HHMM Q node (including F parents) given internal transprob and startprob
+% function CPD = update_CPT(CPD)
+
+Qsz = CPD.Qsz;
+Qpsz = CPD.Qpsz;
+
+if ~isempty(CPD.Fbelow_ndx)
+  if ~isempty(CPD.Fself_ndx) % general case
+    % Fb(t-1) Fself(t-1)  P(Q(t)=j| Q(t-1)=i, Qps(t)=k)
+    % ------------------------------------------------------
+    % 1        1         delta(i,j)
+    % 2        1         transprob(i,k,j)
+    % 1        2         impossible
+    % 2        2         startprob(k,j)
+    CPT = zeros(Qsz, 2, 2, Qpsz, Qsz);
+    I = repmat(eye(Qsz), [1 1 Qpsz]); % i,j,k
+    I = permute(I, [1 3 2]); % i,k,j
+    CPT(:, 1, 1, :, :) = I;
+    CPT(:, 2, 1, :, :) = CPD.transprob;
+    CPT(:, 1, 2, :, :) = I;
+    CPT(:, 2, 2, :, :) = repmat(reshape(CPD.startprob, [1 Qpsz Qsz]), ...
+				[Qsz 1 1]); % replicate  over i 
+  else % no F from self, hence no startprob
+    % Fb(t-1) P(Q(t)=j| Q(t-1)=i, Qps(t)=k)
+    % ------------------------------------------------------
+    % 1       delta(i,j)
+    % 2       transprob(i,k,j)
+    
+    nps = length(CPD.dom_sz)-1; % num parents
+    CPT = 0*myones(CPD.dom_sz);
+    %CPT = zeros(Qsz, 2, Qpsz, Qsz); % assumes CPT(Q(t-1), F(t-1), Qps, Q(t))
+    % but a member of Qps may preceed Q(t-1) or F(t-1) in the ordering
+
+    for k=1:CPD.Qpsz
+      Qps_vals = ind2subv(CPD.Qpsizes, k);
+      ndx = mk_multi_index(nps+1, [CPD.Fbelow_ndx CPD.Qps_ndx], [1 Qps_vals]);
+      CPT(ndx{:}) = eye(Qsz); % CPT(:,2,k,:) or CPT(:,k,2,:) etc
+    end
+    ndx = mk_multi_index(nps+1, CPD.Fbelow_ndx, 2);
+    CPT(ndx{:}) = CPD.transprob; % we assume transprob is in topo order
+  end
+else % no F signal from below
+  if ~isempty(CPD.Fself_ndx)
+    % Q(t-1), Fself(t-1), Qps, Q(t)
+    
+    % Fself(t-1)  P(Q(t-1)=i, Qps(t)=k -> Q(t)=j)
+    % ------------------------------------------------------
+    % 1         transprob(i,k,j)
+    % 2         startprob(k,j)
+    
+    nps = length(CPD.dom_sz)-1; % num parents
+    CPT = 0*myones(CPD.dom_sz);
+    ndx = mk_multi_index(nps+1, CPD.Fself_ndx, 1);
+    CPT(ndx{:}) = CPD.transprob;
+    if CPD.fullstartprob
+      ndx = mk_multi_index(nps+1, CPD.Fself_ndx, 2);
+      CPT(ndx{:}) = CPD.startprob;
+    else
+      for i=1:CPD.Qsz
+	ndx = mk_multi_index(nps+1, [CPD.Fself_ndx CPD.old_self_ndx], [2 i]);
+	CPT(ndx{:}) = CPD.startprob;
+      end
+    end
+  else % no F from self
+    error('An hhmmQ node without any F parents is just a tabular_CPD')
+  end
+end
+
+CPD = set_fields(CPD, 'CPT', CPT);          
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/update_ess.m b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/update_ess.m
new file mode 100644
index 00000000..07dfc72e
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@hhmmQ_CPD/update_ess.m
@@ -0,0 +1,86 @@
+function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, hidden_bitv)
+% UPDATE_ESS Update the Expected Sufficient Statistics of a hhmm Q node.
+% function CPD = update_ess(CPD, fmarginal, evidence, ns, cnodes, idden_bitv)
+%
+% we assume if one of the Qps is observed, all of them are 
+% We assume the F nodes are already hidden 
+
+% Figure out the node numbers associated with each parent
+dom = fmarginal.domain;
+self = dom(end);
+old_self = dom(CPD.old_self_ndx);
+%Fself = dom(CPD.Fself_ndx);
+%Fbelow = dom(CPD.Fbelow_ndx);
+Qps = dom(CPD.Qps_ndx);
+
+Qsz = CPD.Qsz;
+Qpsz = CPD.Qpsz;
+
+
+% hor_counts(old_self, Qps, self),
+% fmarginal(old_self, Fbelow, Fself, Qps, self)
+% hor_counts(i,k,j) = fmarginal(i,2,1,k,j) % below has finished, self has not
+% ver_counts(i,k,j) = fmarginal(i,2,2,k,j) % below has finished, and so has self (reset)
+% Since any of i,j,k may be observed, we write
+% hor_counts(i_counts_ndx, kndx, jndx) = fmarginal(i_fmarg_ndx...)
+% where i_fmarg_ndx = 1 and i_counts_ndx = i if old_self is observed to have value i,
+% i_fmarg_ndx = 1:Qsz and i_counts_ndx = 1:Qsz if old_self is hidden, etc.
+
+
+if hidden_bitv(old_self)
+  i_counts_ndx = 1:Qsz;
+  eff_oldQsz = Qsz;
+else
+  i_counts_ndx = evidence{old_self};
+  eff_oldQsz = 1;
+end
+
+if all(hidden_bitv(Qps)) % we assume all are hidden or all are observed
+  k_counts_ndx = 1:Qpsz;
+  eff_Qpsz = Qpsz;
+else
+  k_counts_ndx = subv2ind(Qpsz, cat(1, evidence{Qps}));
+  eff_Qpsz = 1;
+end
+
+if hidden_bitv(self)
+  j_counts_ndx = 1:Qsz;
+  eff_Qsz = Qsz;
+else
+  j_counts_ndx = evidence{self};
+  eff_Qsz = 1;
+end
+
+hor_counts = zeros(Qsz, Qpsz, Qsz);
+ver_counts = zeros(Qpsz, Qsz);
+    
+if ~isempty(CPD.Fbelow_ndx)
+  if ~isempty(CPD.Fself_ndx) % general case
+    fmarg = myreshape(fmarginal.T, [eff_oldQsz 2 2 eff_Qpsz eff_Qsz]);
+    hor_counts(i_counts_ndx, k_counts_ndx, j_counts_ndx) =  fmarg(:, 2, 1, :, :);
+    ver_counts(k_counts_ndx, j_counts_ndx) = ... % sum over Fbelow and Qold
+	sumv(fmarg(:, :,  2, :, :), [1 2]); % require Fself=2
+  else % no F from self, hence no startprob
+    fmarg = myreshape(fmarginal.T, [eff_oldQsz 2 eff_Qpsz eff_Qsz]);
+    hor_counts(i_counts_ndx, k_counts_ndx, j_counts_ndx) = ...
+	fmarg(:, 2, :, :); % require Fbelow = 2
+  end
+else % no F signal from below
+  if ~isempty(CPD.Fself_ndx) % self F
+    fmarg = myreshape(fmarginal.T, [eff_oldQsz 2 eff_Qpsz eff_Qsz]);
+    hor_counts(i_counts_ndx, k_counts_ndx, j_counts_ndx) =  fmarg(:, 1, :, :);
+    ver_counts(k_counts_ndx, j_counts_ndx) = ... % sum over Qold
+	squeeze(sum(fmarg(:, 2, :, :), 1)); % Fself=2
+  else % no F from self
+    error('An hhmmQ node without any F parents is just a tabular_CPD')
+  end
+end
+
+
+CPD.sub_CPD_trans = update_ess_simple(CPD.sub_CPD_trans, hor_counts);
+
+if ~isempty(CPD.sub_CPD_start)
+  CPD.sub_CPD_start = update_ess_simple(CPD.sub_CPD_start, ver_counts);
+end
+
+