diff toolboxes/FullBNT-1.0.7/bnt/CPDs/@hhmmQ_CPD/Old/hhmmQ_CPD.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/bnt/CPDs/@hhmmQ_CPD/Old/hhmmQ_CPD.m	Tue Feb 10 15:05:51 2015 +0000
@@ -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);
+