diff toolboxes/FullBNT-1.0.7/bnt/CPDs/@gaussian_CPD/CPD_to_lambda_msg.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/@gaussian_CPD/CPD_to_lambda_msg.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,59 @@
+function lam_msg = CPD_to_lambda_msg(CPD, msg_type, n, ps, msg, p, evidence)
+% CPD_TO_LAMBDA_MSG Compute lambda message (gaussian)
+% lam_msg = compute_lambda_msg(CPD, msg_type, n, ps, msg, p, evidence)
+% Pearl p183 eq 4.52
+
+switch msg_type
+ case 'd',
+  error('gaussian_CPD can''t create discrete msgs')
+ case 'g',
+  cps = ps(CPD.cps);
+  cpsizes = CPD.sizes(CPD.cps);
+  self_size = CPD.sizes(end);
+  i = find_equiv_posns(p, cps); % p is n's i'th cts parent
+  psz = cpsizes(i);
+  if all(msg{n}.lambda.precision == 0) % no info to send on
+    lam_msg.precision = zeros(psz, psz);
+    lam_msg.info_state = zeros(psz, 1);
+    return;
+  end
+  [m, Q, W] = gaussian_CPD_params_given_dps(CPD, [ps n], evidence);
+  Bmu = m;
+  BSigma = Q;
+  for k=1:length(cps) % only get pi msgs from cts parents
+    pk = cps(k);
+    if pk ~= p
+      %bk = block(k, cpsizes);
+      bk = CPD.cps_block_ndx{k};
+      Bk = W(:, bk);
+      m = msg{n}.pi_from_parent{k}; 
+      BSigma = BSigma + Bk * m.Sigma * Bk';
+      Bmu = Bmu + Bk * m.mu;
+    end
+  end
+  % BSigma = Q + sum_{k \neq i} B_k Sigma_k B_k'
+  %bi = block(i, cpsizes);
+  bi = CPD.cps_block_ndx{i};
+  Bi = W(:,bi);
+  P = msg{n}.lambda.precision;
+  if (rcond(P) > 1e-3) | isinf(P)
+    if isinf(P) % Y is observed
+      Sigma_lambda = zeros(self_size, self_size); % infinite precision => 0 variance
+      mu_lambda = msg{n}.lambda.mu; % observed_value;
+    else
+      Sigma_lambda = inv(P);
+      mu_lambda = Sigma_lambda * msg{n}.lambda.info_state;
+    end
+    C = inv(Sigma_lambda + BSigma);
+    lam_msg.precision = Bi' * C * Bi;
+    lam_msg.info_state = Bi' * C * (mu_lambda - Bmu);
+  else
+    % method that uses matrix inversion lemma to avoid inverting P
+    A = inv(P + inv(BSigma));
+    C = P - P*A*P;
+    lam_msg.precision = Bi' * C * Bi;
+    D = eye(self_size) - P*A;
+    z = msg{n}.lambda.info_state;
+    lam_msg.info_state = Bi' * (D*z - D*P*Bmu);
+  end
+end