% We compare MCMC structure learning with exhaustive enumeration of all dags.N = 3;%N = 4;dag = mk_rnd_dag(N);ns = 2*ones(1,N);bnet = mk_bnet(dag, ns);for i=1:N  bnet.CPD{i} = tabular_CPD(bnet, i);endncases = 100;data = zeros(N, ncases);for m=1:ncases  data(:,m) = cell2num(sample_bnet(bnet));enddags = mk_all_dags(N);score = score_dags(data, ns, dags);post  = normalise(exp(score));[sampled_graphs, accept_ratio] = learn_struct_mcmc(data, ns, 'nsamples', 100, 'burnin', 10);mcmc_post = mcmc_sample_to_hist(sampled_graphs, dags);if 0  subplot(2,1,1)  bar(post)  subplot(2,1,2)  bar(mcmc_post)  print(gcf, '-djpeg', '/home/cs/murphyk/public_html/Bayes/Figures/mcmc_post.jpg')  clf  plot(accept_ratio)  print(gcf, '-djpeg', '/home/cs/murphyk/public_html/Bayes/Figures/mcmc_accept.jpg')end