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

first hg version after svn

+function bnet = mk_water_dbn(discrete_obs, obs_leaves)
+% MK_WATER_DBN
+% bnet = mk_water_dbn(discrete_obs, obs_leaves)
+%
+% If discrete_obs = 1 (default), the leaves are binary, else scalar Gaussians
+% If obs_leaves = 1, all the leaves are observed, otherwise rnd nodes are observed
+%
+% This is a model of the biological processes of a water purification plant, developed
+% by Finn V. Jensen, Uffe Kjærulff, Kristian G. Olesen, and Jan Pedersen.
+% See http://www-nt.cs.berkeley.edu/home/nir/public_html/Repository/water.htm
+% See also Boyen and Koller, "Tractable Inference for Complex Stochastic Processes", UAI98
+
+if nargin < 1, discrete_obs = 1; end
+if nargin < 1, obs_leaves = 1; end
+
+ss = 12;
+intra = zeros(ss);
+intra(1,9) = 1;
+intra(3,10) = 1;
+intra(4,11) = 1;
+intra(8,12) = 1;
+
+inter = zeros(ss);
+inter(1, [1 3]) = 1;
+inter(2, [2 3 7]) = 1;
+inter(3, [3 4 5]) = 1;
+inter(4, [3 4 6]) = 1;
+inter(5, [3 5 6]) = 1;
+inter(6, [4 5 6]) = 1;
+inter(7, [7 8]) = 1;
+inter(8, [6 7 8]) = 1;
+
+if obs_leaves
+  onodes = 9:12; % leaves
+else
+  onodes = [1 5 9:12]; % throw in some other nodes
+end
+hnodes = 1:8;
+if discrete_obs
+  ns = 2*ones(1 ,ss);
+  dnodes = 1:ss;
+else
+  ns = [2*ones(1,length(hnodes)) 1*ones(length(onodes))];
+  dnodes = hnodes;
+end
+
+eclass1 = 1:12;
+eclass2 = [13:20 9:12];
+bnet = mk_dbn(intra, inter, ns, 'discrete', dnodes, 'eclass1', eclass1, 'eclass2', eclass2, ...
+	      'observed', onodes);
+if discrete_obs
+  for i=1:max(eclass2)
+    bnet.CPD{i} = tabular_CPD(bnet, i);
+  end
+else
+  for i=hnodes(:)'
+    bnet.CPD{i} = tabular_CPD(bnet, i);
+  end
+  for i=onodes(:)'
+    bnet.CPD{i} = gaussian_CPD(bnet, i);
+  end
+  for i=hnodes(:)'+ss
+    bnet.CPD{i} = tabular_CPD(bnet, i);
+  end
+end
+
+
+