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-rw-r--r--sourcecodes/bnt-master/SLP/examples/test_ges.m45
1 files changed, 45 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/SLP/examples/test_ges.m b/sourcecodes/bnt-master/SLP/examples/test_ges.m
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+% test Greedy Equivalence Search with cache
+
+clear all;
+
+%add_BNT_to_path;
+
+fprintf('\n=== Structure Learning with Greedy Equivalence Search algorithm and cache implementation\n');
+
+
+bnet=mk_asia_bnet ;
+
+n=8;
+names={ 'A' , 'S' , 'T' , 'L' , 'B' , 'O' , 'X' , 'D' };
+carre=ones(1,n);
+node_type={'tabular','tabular','tabular','tabular','tabular','tabular','tabular','tabular'};
+
+m=10000;
+bnet=mk_asia2_bnet;
+data = cell(n,m);
+for l = 1:m, data(:,l) = sample_bnet(bnet); end
+data=cell2mat(data);
+fprintf('Complete data have been created.');
+
+seeddag = zeros(n,n);
+
+fprintf('\t- Greedy Search (with cache)\n');
+tmp=cputime;
+L=500;
+cache=score_init_cache(n,L);
+[dag1, best_score, cache] =learn_struct_ges(data,bnet.node_sizes,seeddag,'cache',cache,'scoring_fn','bic');
+%cache
+tmp=cputime-tmp;
+fprintf('\t- Execution time : %3.2f seconds\n',tmp);
+
+
+figure;[xx yy] = make_layout(bnet.dag);
+yy=(yy-0.2)*.8/.6+.1;
+xx=(xx-0.2833)*.8/.517+.1;
+subplot(1,3,1), [xx yy]=draw_graph(bnet.dag,names,carre,xx,yy); %,carre);
+title('ASIA original graph');
+subplot(1,3,2), draw_graph(dag1,names,carre,xx,yy); %,carre);
+title('GES CPDAG (cache)');
+subplot(1,3,3), draw_graph(cpdag_to_dag(dag1),names,carre,xx,yy); %,carre);
+title('GES DAG (cache)');
+drawnow;
\ No newline at end of file