comparison toolboxes/FullBNT-1.0.7/bnt/examples/dynamic/jtree_clq_test.m @ 0:e9a9cd732c1e tip

first hg version after svn

+% Construct various DBNs and examine their clique structure.
+% This was used to generate various figures in chap 3-4 of my thesis.
+
+% Examine the cliques in the unrolled mildew net
+
+%dbn = mk_mildew_dbn;
+dbn = mk_chmm(4);
+ss = dbn.nnodes_per_slice;
+T = 7;
+N = ss*T;
+bnet = dbn_to_bnet(dbn, T);
+
+constrained = 0;
+if constrained
+  stages = num2cell(unroll_set(1:ss, ss, T), 1);
+else
+  stages = { 1:N; };
+end
+clusters = {};
+%[jtree, root, cliques, B, w, elim_order, moral_edges, fill_in_edges] = ...
+%    dag_to_jtree(bnet, bnet.observed, stages, clusters);
+[jtree, root, cliques] =  graph_to_jtree(moralize(bnet.dag), ones(1,N), stages, clusters);
+
+flip=1;
+clf;[dummyx, dummyy, h] = draw_dbn(dbn.intra, dbn.inter, flip, T, -1);
+dir = '/home/eecs/murphyk/WP/Thesis/Figures/Inf/MildewUnrolled';
+mk_ps_from_clqs(dbn, T, cliques, [])
+%mk_collage_from_clqs(dir, cliques)
+
+
+% Examine the cliques in the cascade DBN
+
+% A-A
+%  \
+% B B
+%  \
+% C C
+%  \
+% D D
+ss = 4;
+intra = zeros(ss);
+inter = zeros(ss);
+inter(1, [1 2])=1;
+for i=2:ss-1
+  inter(i,i+1)=1;
+end
+
+
+% 2 coupled HMMs 1,3  and 2,4
+ss = 4;
+intra = zeros(ss);
+inter = zeros(ss); % no persistent edges
+%inter = diag(ones(ss,1)); % persitence edges
+inter(1,3)=1; inter(3,1)=1;
+inter(2,4)=1; inter(4,2)=1;
+
+%bnet = mk_fhmm(3);
+bnet = mk_chmm(4);
+intra = bnet.intra;
+inter = bnet.inter;
+
+clqs = compute_minimal_interface(intra, inter);
+celldisp(clqs)
+
+
+
+
+% A A
+%  \
+% B B
+%  \
+% C C
+%  \
+% D-D
+ss = 4;
+intra = zeros(ss);
+inter = zeros(ss);
+for i=1:ss-1
+  inter(i,i+1)=1;
+end
+inter(4,4)=1;
+
+
+
+ns = 2*ones(1,ss);
+dbn = mk_dbn(intra, inter, ns);
+for i=2*ss
+  dbn.CPD{i} = tabular_CPD(bnet, i);
+end
+
+T = 4;
+N = ss*T;
+bnet = dbn_to_bnet(dbn, T);
+
+constrained = 1;
+if constrained
+  % elim first 3 slices first in any order
+  stages = {1:12, 13:16};
+  %stages = num2cell(unroll_set(1:ss, ss, T), 1);
+else
+  stages = { 1:N; };
+end
+clusters = {};
+%[jtree, root, cliques, B, w, elim_order, moral_edges, fill_in_edges] = ...
+%    dag_to_jtree(bnet, bnet.observed, stages, clusters);
+[jtree, root, cliques] =  graph_to_jtree(moralize(bnet.dag), ones(1,N), stages, clusters);
+
+
+
+
+
+% Examine the cliques in the 1.5 slice DBN
+
+%dbn = mk_mildew_dbn;
+dbn = mk_water_dbn;
+%dbn = mk_bat_dbn;
+ss = dbn.nnodes_per_slice;
+int = compute_fwd_interface(dbn);
+bnet15 = mk_slice_and_half_dbn(dbn, int);
+N = length(bnet15.dag);
+stages = {1:N};
+
+% bat
+%cl1 = [16 17 19 7 14];
+%cl2 = [27 25 21 23 20];
+%clusters = {cl1, cl2, cl1+ss, cl2+ss};
+
+% water
+%cl1 = 1:2; cl2 = 3:6; cl3 = 7:8;
+%clusters = {cl1, cl2, cl3, cl1+ss, cl2+ss, cl3+ss};
+
+%clusters = {};
+clusters = {int, int+ss};
+%[jtree, root, cliques, B, w, elim_order, moral_edges, fill_in_edges] = ...
+%    dag_to_jtree(bnet15, bnet.observed, stages, clusters);
+[jtree, root, cliques] =  graph_to_jtree(moralize(bnet15.dag), ones(1,N), stages, clusters);
+
+clq_len = [];
+for c=1:length(cliques)
+  clq_len(c) = length(cliques{c});
+end
+hist(clq_len, 1:max(clq_len));
+h=hist(clq_len, 1:max(clq_len));
+axis([1 max(clq_len)+1 0 max(h)+1])
+xlabel('clique size','fontsize',16)
+ylabel('number','fontsize',16)
+
+
+
+