diff toolboxes/FullBNT-1.0.7/bnt/CPDs/@discrete_CPD/convert_to_pot.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/bnt/CPDs/@discrete_CPD/convert_to_pot.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,62 @@
+function pot = convert_to_pot(CPD, pot_type, domain, evidence)
+% CONVERT_TO_POT Convert a discrete CPD to a potential
+% pot = convert_to_pot(CPD, pot_type, domain, evidence)
+%
+% pots = CPD evaluated using evidence(domain)
+
+ncases = size(domain,2);
+assert(ncases==1); % not yet vectorized
+
+sz = dom_sizes(CPD);
+ns = zeros(1, max(domain));
+ns(domain) = sz;
+
+CPT1 = CPD_to_CPT(CPD);
+spar = issparse(CPT1);
+odom = domain(~isemptycell(evidence(domain)));
+if spar
+   T = convert_to_sparse_table(CPD, domain, evidence);
+else 
+   T = convert_to_table(CPD, domain, evidence);
+end
+
+switch pot_type
+ case 'u',
+  pot = upot(domain, sz, T, 0*myones(sz));  
+ case 'd',
+  ns(odom) = 1;
+  pot = dpot(domain, ns(domain), T);          
+ case {'c','g'},
+  % Since we want the output to be a Gaussian, the whole family must be observed.
+  % In other words, the potential is really just a constant.
+  p = T;
+  %p = prob_node(CPD, evidence(domain(end)), evidence(domain(1:end-1)));
+  ns(domain) = 0;
+  pot = cpot(domain, ns(domain), log(p));       
+
+ case 'cg',
+  T = T(:);
+  ns(odom) = 1;
+  can = cell(1, length(T));
+  for i=1:length(T)
+    if T(i) == 0 
+      can{i} = cpot([], [], -Inf); % bug fix by Bob Welch 20/2/04
+    else
+      can{i} = cpot([], [], log(T(i)));
+    end;
+  end
+  pot = cgpot(domain, [], ns, can); 
+  
+ case 'scg'
+  T = T(:);
+  ns(odom) = 1;
+  pot_array = cell(1, length(T));
+  for i=1:length(T)
+    pot_array{i} = scgcpot([], [], T(i));
+  end
+  pot = scgpot(domain, [], [], ns, pot_array);   
+
+ otherwise,
+  error(['unrecognized pot type ' pot_type])
+end
+