function engine = cond_gauss_inf_engine(bnet)% COND_GAUSS_INF_ENGINE Conditional Gaussian inference engine% engine = cond_gauss_inf_engine(bnet)%% Enumerates all the discrete roots, and runs jtree on the remaining Gaussian nodes.dnodes = mysetdiff(1:length(bnet.dag), bnet.cnodes);%onodes = dnodes; % all the discrete ndoes will be observed%engine.sub_engine = jtree_inf_engine(bnet, onodes);bnet2 = bnet;bnet2.observed = dnodes;engine.sub_engine = jtree_inf_engine(bnet2);% This is where we will store the results between enter_evidence and marginal_nodesengine.T = [];engine.mu = [];engine.Sigma = [];engine.joint_dmarginal = [];engine.onodes = []; % needed for marginal_nodesengine.evidence = []; % needed for marginal_nodes add_evengine = class(engine, 'cond_gauss_inf_engine', inf_engine(bnet));