mk_hmm_obs_lik_mat.m

来自「Bayes网络工具箱」· M 代码 · 共 44 行

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);
ns = repmat(bnet.node_sizes_slice(:), 1, T);
cnodes = repmat(bnet.cnodes_slice(:), ss, T);
t = 1;
for n=1:ss
  fam = family(bnet.dag, n);
  e = bnet.equiv_class(n, 1);
  CPDpot{n,t} = CPD_to_table(bnet.CPD{e}, fam, ns, cnodes, evidence(:,1));
end
for n=1:ss
  fam = family(bnet.dag, n, 2);
  doms = unroll_set(fam, ss, T-1);
  e = bnet.equiv_class(n, 2);
  CPDpot(n,2:T) = CPD_to_tables(bnet.CPD{e}, doms, ns, cnodes, evidence);
end



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(:)'
    fam = family(bnet.dag, i);
    pot = dpot(fam, ns(fam), CPDpot{i,t});
    bigpot = multiply_by_pot(bigpot, pot); % can speed this up
  end
  m = pot_to_marginal(bigpot);
  obslik(:,t) = m.T(:);
end