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 hiddenpot_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;