Merge pull request #1 from ziejd2/octave_php_separate

Octave php separate

1 files changed, 37 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/CPDs/@tabular_kernel/convert_to_pot.m b/sourcecodes/bnt-master/BNT/CPDs/@tabular_kernel/convert_to_pot.m
new file mode 100644
index 00000000..8f9adff1
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@tabular_kernel/convert_to_pot.m
@@ -0,0 +1,37 @@
+function pot = convert_to_pot(CPD, pot_type, domain, evidence)
+% CONVERT_TO_POT Convert a tabular CPD to one or more potentials
+% pot = convert_to_pot(CPD, pot_type, domain, evidence)
+
+% This is the same as discrete_CPD/convert_to_pot,
+% except we didn't want to the kernel to inherit methods like sample_node etc.
+
+sz = CPD.sz;
+ns = zeros(1, max(domain));
+ns(domain) = sz;
+
+odom = domain(~isemptycell(evidence(domain)));
+T = convert_to_table(CPD, domain, evidence);
+
+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',
+  % 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;
+  %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)
+    can{i} = cpot([], [], log(T(i)));
+  end
+  pot = cgpot(domain, [], ns, can);   
+end
+