comparison toolboxes/FullBNT-1.0.7/bnt/inference/static/@cond_gauss_inf_engine/enter_evidence.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function [engine, loglik] = enter_evidence(engine, evidence, varargin)
+% ENTER_EVIDENCE Add the specified evidence to the network (cond_gauss)
+% [engine, loglik] = enter_evidence(engine, evidence, ...)
+%
+% evidence{i} = [] if if X(i) is hidden, and otherwise contains its observed value (scalar or column vector)
+
+bnet = bnet_from_engine(engine);
+ns = bnet.node_sizes(:);
+observed = ~isemptycell(evidence);
+onodes = find(observed);
+hnodes = find(isemptycell(evidence));
+engine.evidence = evidence;
+
+% check there are no C->D links where C is hidden
+pot_type = determine_pot_type(bnet, onodes);
+
+dhid = myintersect(hnodes, bnet.dnodes);
+S = prod(ns(dhid));
+T = zeros(S,1);
+
+N = length(bnet.dag);
+mu = cell(1,N);
+Sigma = cell(1,N); 
+cobs = myintersect(bnet.cnodes, onodes);
+chid = myintersect(bnet.cnodes, hnodes);
+ens = ns;
+ens(cobs) = 0;
+for j=chid(:)'
+  mu{j} = zeros(ens(j), S);
+  Sigma{j} = zeros(ens(j), ens(j), S);
+end
+ 
+for i=1:S
+  dvals = ind2subv(ns(dhid), i);
+  evidence(dhid) = num2cell(dvals);
+  [sub_engine, loglik] = enter_evidence(engine.sub_engine, evidence);
+  for j=chid(:)'
+    m = marginal_nodes(sub_engine, j);
+    mu{j}(:,i) = m.mu;
+    Sigma{j}(:,:,i) = m.Sigma;
+  end
+  T(i) = exp(loglik);
+end
+
+[T, lik] = normalise(T);
+loglik = log(lik);
+
+engine.T = T;
+engine.mu = mu;
+engine.Sigma = Sigma;
+
+dnodes = bnet.dnodes;
+dobs = myintersect(dnodes, onodes);
+ens(dobs) = 1;
+engine.joint_dmarginal = dpot(dnodes, ens(dnodes), myreshape(engine.T, ens(dnodes)));
+
+engine.onodes = onodes;