wolffd@0: function y = sample_node(CPD, pev, nsamples)
wolffd@0: % SAMPLE_NODE Draw a random sample from P(Xi | x(pi_i), theta_i)  (tabular)
wolffd@0: % Y = SAMPLE_NODE(CPD, PEV, NSAMPLES)
wolffd@0: %
wolffd@0: % pev(i,m) is the value of the i'th parent in sample m (if there are any parents).
wolffd@0: % y(m) is the m'th sampled value (a row vector).
wolffd@0: % (If pev is a cell array, so is y.)
wolffd@0: % nsamples defaults to 1.
wolffd@0: 
wolffd@0: if nargin < 3, nsamples = 1; end
wolffd@0: 
wolffd@0: %if nargin < 4, usecell = 0; end
wolffd@0: if iscell(pev), usecell = 1; else usecell = 0; end
wolffd@0: 
wolffd@0: if nsamples == 1, pev = pev(:); end
wolffd@0: 
wolffd@0: sz = CPD.sizes; 
wolffd@0: nparents = length(sz)-1;
wolffd@0: if nparents==0
wolffd@0:   y = sample_discrete(CPD.CPT, 1, nsamples);
wolffd@0:   if usecell
wolffd@0:     y = num2cell(y);
wolffd@0:   end
wolffd@0:   return;
wolffd@0: end
wolffd@0: 
wolffd@0: sz = CPD.sizes; 
wolffd@0: [nparents nsamples] = size(pev);
wolffd@0: 
wolffd@0: if usecell
wolffd@0:   pvals = cell2num(pev)'; % each row is a case
wolffd@0: else
wolffd@0:   pvals = pev';
wolffd@0: end
wolffd@0: 
wolffd@0: psz = sz(1:end-1);
wolffd@0: ssz = sz(end);
wolffd@0: ndx = subv2ind(psz, pvals);
wolffd@0: T = reshape(CPD.CPT, [prod(psz) ssz]);
wolffd@0: T2 = T(ndx,:); % each row is a distribution selected by the parents
wolffd@0: C = cumsum(T2, 2); % sum across columns
wolffd@0: R = rand(nsamples, 1);
wolffd@0: y = ones(nsamples, 1);
wolffd@0: for i=1:ssz-1
wolffd@0:   y = y + (R > C(:,i));
wolffd@0: end
wolffd@0: y = y(:)';
wolffd@0: if usecell
wolffd@0:   y = num2cell(y);
wolffd@0: end
wolffd@0: 
wolffd@0: 
wolffd@0: