comparison toolboxes/FullBNT-1.0.7/bnt/CPDs/@tabular_CPD/Old/sample_node.m @ 0:e9a9cd732c1e tip

first hg version after svn

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