New parameter learning options

The main change here is in the parameter learning methods.  The parameters that are learned at first (i.e., if there is no evidence) are the distributions that are found directly in the data. I had to create or significantly modify several BNT files for this.

If there is evidence, the parameters are learned using a Dirichlet prior. This only required a couple of small changes to the BNW parameter learning files.

4 files changed, 154 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_pot_orig.m b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_pot_orig.m
new file mode 100644
index 00000000..dadcb033
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_pot_orig.m
@@ -0,0 +1,62 @@
+function pot = convert_to_pot_orig(CPD, pot_type, domain, evidence, n, ns_current)
+% CONVERT_TO_POT Convert discrete CPD with original distribution to a potential
+% pot = convert_to_pot_orig(CPD, pot_type, domain, evidence, n, ns_current)
+%
+% 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',
+  CPT_orig = CPD_to_CPT_orig(CPD);
+  pot = dpot(n, ns_current, CPT_orig);          
+ 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
+
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_pot_orig.m~ b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_pot_orig.m~
new file mode 100644
index 00000000..ecc57d49
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_pot_orig.m~
@@ -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
+
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_table_orig.m b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_table_orig.m
new file mode 100644
index 00000000..92aacc0d
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_table_orig.m
@@ -0,0 +1,15 @@
+function T = convert_to_table(CPD, domain, evidence)
+% CONVERT_TO_TABLE Convert a discrete CPD to a table with original distribution
+% T = convert_to_table(CPD, domain, evidence)
+%
+% We convert the CPD to a CPT, and then lookup the evidence on the discrete parents.
+% The resulting table can easily be converted to a potential.
+
+domain = domain(:);
+CPT = CPD_to_CPT_orig(CPD);
+odom = domain(~isemptycell(evidence(domain)));
+vals = cat(1, evidence{odom});
+map = find_equiv_posns(odom, domain);
+index = mk_multi_index(length(domain), map, vals);
+T = CPT(index{:});
+T = T(:);
diff --git a/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_table_orig.m~ b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_table_orig.m~
new file mode 100644
index 00000000..dc5bcd40
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_table_orig.m~
@@ -0,0 +1,15 @@
+function T = convert_to_table(CPD, domain, evidence)
+% CONVERT_TO_TABLE Convert a discrete CPD to a table
+% T = convert_to_table(CPD, domain, evidence)
+%
+% We convert the CPD to a CPT, and then lookup the evidence on the discrete parents.
+% The resulting table can easily be converted to a potential.
+
+domain = domain(:);
+CPT = CPD_to_CPT(CPD);
+odom = domain(~isemptycell(evidence(domain)));
+vals = cat(1, evidence{odom});
+map = find_equiv_posns(odom, domain);
+index = mk_multi_index(length(domain), map, vals);
+T = CPT(index{:});
+T = T(:);