Mauch MIREX 2010

function CPD = hhmmF_CPD(bnet, self, Qself, Fbelow, varargin)

% HHMMF_CPD Make the CPD for an F node in a hierarchical HMM

% CPD = hhmmF_CPD(bnet, self, Qself,  Fbelow, ...)

%

%        Qps

%          \

%           \

%           Fself

%         /   |

%        /    |

%       Qself Fbelow

%

% We assume nodes are ordered (numbered) as follows: Qps, Q, Fbelow, F

% All nodes numbers should be from slice 1.

%

% If Fbelow if missing, this becomes a regular tabular_CPD.

% Qps may be omitted.

%

% optional args [defaults]

% 

% Qps - node numbers.

% termprob - termprob(k,i,2) = prob finishing given Q(d)=i and Q(1:d-1)=k [ finish in last state wp 0.9]

%

% hhmmF_CPD is a subclass of tabular_CPD so we inherit inference methods like CPD_to_pot, etc.

%

% We create an isolated tabular_CPD with no F parent to learn termprob

% so we can avail of e.g., entropic or Dirichlet priors.

%

% For details, see "Linear-time inference in hierarchical HMMs", Murphy and Paskin, NIPS'01.

Qps = [];

% get parents

for i=1:2:length(varargin)

  switch varargin{i},

   case 'Qps', Qps = varargin{i+1}; 

  end

end

ns = bnet.node_sizes(:);

Qsz = ns(Qself);

Qpsz = prod(ns(Qps));

CPD.Qsz = Qsz;

CPD.Qpsz = Qpsz;

ps = parents(bnet.dag, self);

CPD.Fbelow_ndx = find_equiv_posns(Fbelow, ps);

CPD.Qps_ndx = find_equiv_posns(Qps, ps);

CPD.Qself_ndx = find_equiv_posns(Qself, ps);

% set default arguments

p = 0.9;

%termprob(k,i,t) Might terminate if i=Qsz; will not terminate if i<Qsz

termprob = zeros(Qpsz, Qsz, 2);

termprob(:, Qsz, 2) = p; 

termprob(:, Qsz, 1) = 1-p; 

termprob(:, 1:(Qsz-1), 1) = 1; 

for i=1:2:length(varargin)

  switch varargin{i},

   case 'termprob', termprob = varargin{i+1}; 

  end

end

CPD.sub_CPD_term = mk_isolated_tabular_CPD([Qpsz Qsz 2], {'CPT', termprob});

S = struct(CPD.sub_CPD_term);

CPD.termprob = S.CPT;

CPD = class(CPD, 'hhmmF_CPD', tabular_CPD(bnet, self));

CPD = update_CPT(CPD);