Mauch MIREX 2010

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);