Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/graph/triangulate_2Dlattice_demo.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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% Consider a 3x3 lattice with 4-nearest neighbor connectivity % 1 - 2 - 3 % | | | % 4 - 5 - 6 % | | | % 7 - 8 - 9 N = 3; G = mk_2D_lattice(N,N,4); G0 = G; % Now add in the diagonal edges if 0 % 1 - 2 - 3 % | x | x | % 4 - 5 - 6 % | x | x | % 7 - 8 - 9 G(1,5)=1; G(5,1)=1; G(2,6)=1; G(6,2)=1; G(4,2)=1; G(2,4)=1; G(5,3)=1; G(3,5)=1; G(4,8)=1; G(8,4)=1; G(5,9)=1; G(9,5)=1; G(7,5)=1; G(5,7)=1; G(8,6)=1; G(6,8)=1; end % 1 - 2 - 3 % | / | \ | % 4 - 5 - 6 % | \ | / | % 7 - 8 - 9 G(2,6)=1; G(6,2)=1; G(4,2)=1; G(2,4)=1; G(4,8)=1; G(8,4)=1; G(8,6)=1; G(6,8)=1; % Is this a chordal (triangulated) graph? No! assert(~check_triangulated(G)) % The reason is that there is a chordless cycle around the outside nodes. % To see this, imagine "picking up" node 5, leaving the rest on the plane % (like a hoop skirt, or a tent), as shown below % 1 - 2 - 3 % | / \ | % 4 6 % | \ / | % 7 - 8 - 9 % However, if we add in the 4-6 arc, it will be chordal. G2 = G; G2(4,6)=1; G2(6,4)=1; assert(check_triangulated(G2)) % Or we can add in the 2-8 arc G2 = G; G2(2,8)=1; G2(8,2)=1; assert(check_triangulated(G2)) if 0 % 4x4 lattice with cross arcs N=4;G0 = mk_2D_lattice(N,N,4); vs = [1 6; 2 5; 2 7; 3 6; 3 8; 4 7; ... 5 10; 6 9; 6 11; 7 10; 7 12; 8 11;... 9 14; 10 13; 10 15; 11 14; 11 16; 12 15]; for i=1:size(vs,1) u = vs(i,1); v= vs(i,2); G0(u,v) = 1; G0(v,u) = 1; end end % Here is how we can discover which edges to fill in automatically % (although possibly sub-optimally) weights = 2*ones(1,N*N); % all nodes are binar % fill-ins = 2-4, 2-6, 4-8, 6-8 and 4-6 % cliques = 124, etc and 2456 4568 greedy_order = best_first_elim_order(G0, weights); [GT, cliques, fill_ins] = triangulate(G0, greedy_order) assert(check_triangulated(GT)) greedy_order = best_first_elim_order(G, weights); [GT, cliques, fill_ins] = triangulate(G, greedy_order) assert(check_triangulated(GT)) % fill-ins = [4 6] % Cliques are the overlapping squares [1,2,4,5], [2 3 5 6], [4 5 7 8], [5 6 8 9] % and the following caused by the fill-in: [2 4 5 6], [4 5 6 8] % Connect the maximal cliques of the triangulate graph into a junction tree [jtree, root, B, clq_weights] = cliques_to_jtree(cliques, weights); % In this case, all cliques have weight 2^4 = 16 % Now consider size of max clique as a function of grid size % Note: this is not necessarily the optimal triangulation % N 5 10 15 16 17 18 % m 6 15 23 25 28 28 Ns = [5 10 15 16 17 18]; for i=1:length(Ns) N = Ns(i) G = mk_2D_lattice(N,N,4); weights = 2*ones(1,N*N); % all nodes are binary greedy_order = best_first_elim_order(G, weights); % slow! [GT, cliques, fill_ins] = triangulate(G, greedy_order); %assert(check_triangulated(GT)) [jtree, root, B, clq_weights] = cliques_to_jtree(cliques, weights); m(i) = log2(max(clq_weights)); end % plot distribution of clique sizes for fixed N for c=1:length(cliques) l(c) = length(cliques{c}); end hist(l)