comparison toolboxes/FullBNT-1.0.7/bnt/CPDs/@gaussian_CPD/maximize_params.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function CPD = maximize_params(CPD, temp)
+% MAXIMIZE_PARAMS Set the params of a CPD to their ML values (Gaussian)
+% CPD = maximize_params(CPD, temperature)
+%
+% Temperature is currently ignored.
+
+if ~adjustable_CPD(CPD), return; end
+
+
+if CPD.clamped_mean
+  cl_mean = CPD.mean;
+else
+  cl_mean = [];
+end
+
+if CPD.clamped_cov
+  cl_cov = CPD.cov;
+else
+  cl_cov = [];
+end
+
+if CPD.clamped_weights
+  cl_weights = CPD.weights;
+else
+  cl_weights = [];
+end
+
+[ssz psz Q] = size(CPD.weights);
+
+[ss cpsz dpsz] = size(CPD.weights); % ss = self size = ssz
+if cpsz > CPD.nsamples
+  fprintf('gaussian_CPD/maximize_params: warning: input dimension (%d) > nsamples (%d)\n', ...
+	  cpsz, CPD.nsamples);
+end
+
+prior =  repmat(CPD.cov_prior_weight*eye(ssz,ssz), [1 1 Q]);
+
+
+[CPD.mean, CPD.cov, CPD.weights] = ...
+    clg_Mstep(CPD.Wsum, CPD.WYsum, CPD.WYYsum, [], CPD.WXsum, CPD.WXXsum, CPD.WXYsum, ...
+	      'cov_type', CPD.cov_type, 'clamped_mean', cl_mean, ...
+	      'clamped_cov', cl_cov, 'clamped_weights', cl_weights, ...
+	      'tied_cov', CPD.tied_cov, ...
+	      'cov_prior', prior);
+
+if 0
+CPD.mean = reshape(CPD.mean, [ss dpsz]);
+CPD.cov = reshape(CPD.cov, [ss ss dpsz]);
+CPD.weights = reshape(CPD.weights, [ss cpsz dpsz]);
+end
+
+% Bug fix 11 May 2003 KPM
+% clg_Mstep collapses all discrete parents into one mega-node
+% but convert_to_CPT needs access to each parent separately
+sz = CPD.sizes;
+ss = sz(end);
+
+% Bug fix KPM 20 May 2003: 
+cpsz = sum(sz(CPD.cps));
+%if isempty(CPD.cps)
+%  cpsz = 0;
+%else
+%  cpsz = sz(CPD.cps);
+%end
+dpsz = sz(CPD.dps);
+CPD.mean = myreshape(CPD.mean, [ss dpsz]);
+CPD.cov = myreshape(CPD.cov, [ss ss dpsz]);
+CPD.weights = myreshape(CPD.weights, [ss cpsz dpsz]);