comparison toolboxes/FullBNT-1.0.7/netlab3.3/gmmunpak.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function mix = gmmunpak(mix, p)
+%GMMUNPAK Separates a vector of Gaussian mixture model parameters into its components.
+%
+%	Description
+%	MIX = GMMUNPAK(MIX, P) takes a GMM data structure MIX and  a single
+%	row vector of parameters P and returns a mixture data structure
+%	identical to the input MIX, except that the mixing coefficients
+%	PRIORS, centres CENTRES and covariances COVARS  (and, for PPCA, the
+%	lambdas and U (PCA sub-spaces)) are all set to the corresponding
+%	elements of P.
+%
+%	See also
+%	GMM, GMMPAK
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+errstring = consist(mix, 'gmm');
+if ~errstring
+  error(errstring);
+end
+if mix.nwts ~= length(p)
+  error('Invalid weight vector length')
+end
+
+mark1 = mix.ncentres;
+mark2 = mark1 + mix.ncentres*mix.nin;
+
+mix.priors = reshape(p(1:mark1), 1, mix.ncentres);
+mix.centres = reshape(p(mark1 + 1:mark2), mix.ncentres, mix.nin);
+switch mix.covar_type
+  case 'spherical'
+    mark3 = mix.ncentres*(2 + mix.nin);
+    mix.covars = reshape(p(mark2 + 1:mark3), 1, mix.ncentres);
+  case 'diag'
+    mark3 = mix.ncentres*(1 + mix.nin + mix.nin);
+    mix.covars = reshape(p(mark2 + 1:mark3), mix.ncentres, mix.nin);
+  case 'full'
+    mark3 = mix.ncentres*(1 + mix.nin + mix.nin*mix.nin);
+    mix.covars = reshape(p(mark2 + 1:mark3), mix.nin, mix.nin, ...
+      mix.ncentres);
+  case 'ppca'
+    mark3 = mix.ncentres*(2 + mix.nin);
+    mix.covars = reshape(p(mark2 + 1:mark3), 1, mix.ncentres);
+    % Now also extract k and eigenspaces
+    mark4 = mark3 + mix.ncentres*mix.ppca_dim;
+    mix.lambda = reshape(p(mark3 + 1:mark4), mix.ncentres, ...
+      mix.ppca_dim);
+    mix.U = reshape(p(mark4 + 1:end), mix.nin, mix.ppca_dim, ...
+      mix.ncentres);
+  otherwise
+    error(['Unknown covariance type ', mix.covar_type]);
+end
+