wolffd@0: function CPD = maximize_params(CPD, temp)
wolffd@0: % MAXIMIZE_PARAMS Set the params of a tabular node to their ML/MAP values.
wolffd@0: % CPD = maximize_params(CPD, temp)
wolffd@0: 
wolffd@0: if ~adjustable_CPD(CPD), return; end
wolffd@0: 
wolffd@0: %assert(approxeq(sum(CPD.counts(:)), CPD.nsamples)); % false!
wolffd@0: switch CPD.prior_type
wolffd@0:  case 'none',
wolffd@0:   counts = reshape(CPD.counts, size(CPD.CPT));
wolffd@0:   CPD.CPT = mk_stochastic(counts);
wolffd@0:  case 'dirichlet',
wolffd@0:   counts = reshape(CPD.counts, size(CPD.CPT));
wolffd@0:   CPD.CPT = mk_stochastic(counts + CPD.dirichlet);
wolffd@0:  
wolffd@0:  % case 'entropic',
wolffd@0: %   % For an HMM,
wolffd@0: %   % CPT(i,j) = pr(X(t)=j | X(t-1)=i) = transprob(i,j)
wolffd@0: %   % counts(i,j) = E #(X(t-1)=i, X(t)=j) = exp_num_trans(i,j)
wolffd@0: %   Z = 1-temp;
wolffd@0: %   fam_sz = CPD.sizes;
wolffd@0: %   psz = prod(fam_sz(1:end-1));
wolffd@0: %   ssz = fam_sz(end);
wolffd@0: %   counts = reshape(CPD.counts, psz, ssz);
wolffd@0: %   CPT = zeros(psz, ssz);
wolffd@0: %   for i=CPD.entropic_pcases(:)'
wolffd@0: %     [CPT(i,:), logpost] = entropic_map_estimate(counts(i,:), Z);
wolffd@0: %   end
wolffd@0: %   non_entropic_pcases = mysetdiff(1:psz, CPD.entropic_pcases);
wolffd@0: %   for i=non_entropic_pcases(:)'
wolffd@0: %     CPT(i,:) = mk_stochastic(counts(i,:));
wolffd@0: %   end
wolffd@0: %   %for i=1:psz
wolffd@0: %   %  [CPT(i,:), logpost] = entropic_map(counts(i,:), Z);
wolffd@0: %   %end
wolffd@0: %   if CPD.trim & (temp < 2) % at high temps, we would trim everything!
wolffd@0: %     % grad(j) = d log lik / d theta(i ->j)
wolffd@0: %     % CPT(i,j) = 0 => counts(i,j) = 0
wolffd@0: %     % so we can safely replace 0s by 1s in the denominator
wolffd@0: %     denom = CPT(i,:) + (CPT(i,:)==0);
wolffd@0: %     grad = counts(i,:) ./ denom;
wolffd@0: %     trim = find(CPT(i,:) <= exp(-(1/Z)*grad)); % eqn 32
wolffd@0: %     if ~isempty(trim)
wolffd@0: %       CPT(i,trim) = 0;
wolffd@0: %       if all(CPD.trimmed_trans(i,trim)==0) % trimming for 1st time
wolffd@0: % 	disp(['trimming CPT(' num2str(i) ',' num2str(trim) ')']) 
wolffd@0: %       end
wolffd@0: %       CPD.trimmed_trans(i,trim) = 1;
wolffd@0: %     end
wolffd@0: %   end
wolffd@0: %   CPD.CPT = myreshape(CPT, CPD.sizes);
wolffd@0: end