Add a useful package (from Source forge) for octave

[CreaPhase.git] / octave_packages / octgpr-1.2.0 / rbf_centers.m

diff --git a/octave_packages/octgpr-1.2.0/rbf_centers.m b/octave_packages/octgpr-1.2.0/rbf_centers.m
new file mode 100644 (file)
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+++ b/octave_packages/octgpr-1.2.0/rbf_centers.m
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+% Copyright (C) 2008  VZLU Prague, a.s., Czech Republic
+% 
+% Author: Jaroslav Hajek <highegg@gmail.com>
+% 
+% This file is part of OctGPR.
+% 
+% OctGPR is free software; you can redistribute it and/or modify
+% it under the terms of the GNU General Public License as published by
+% the Free Software Foundation; either version 3 of the License, or
+% (at your option) any later version.
+% 
+% This program is distributed in the hope that it will be useful,
+% but WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+% GNU General Public License for more details.
+% 
+% You should have received a copy of the GNU General Public License
+% along with this software; see the file COPYING.  If not, see
+% <http://www.gnu.org/licenses/>.
+% 
+
+% -*- texinfo -*-
+% @deftypefn {Function File} {[U, ur, iu]} = rbf_centers (@var{X}, @var{nu}, @var{theta})
+% Selects a given number of RBF centers based on Lloyd's clustering algorithm.
+% 
+% @end deftypefn
+function [U, ur, iu] = rbf_centers (X, nu, theta)
+
+  if (nargin == 3)
+    X *= diag (theta);
+  elseif (nargin != 2)
+    print_usage ();
+  endif
+
+  % the D^2 weighting initialization
+
+  D = Inf;
+  kk = 1:rows (X);
+  cp = kk;
+
+  for i = 1:nu
+    jj = sum (rand() * cp(end) < cp);
+    k(i) = kk(jj);
+    kk(jj) = [];
+    U = X(k(i),:);
+    D = min (D, pdist2_mw(X, U, 'ssq')');
+    cp = cumsum (D(kk));
+  endfor
+
+  
+  % now perform the k-means algorithm
+
+  U = X(k,:);
+  D = pdist2_mw (U, X, 'ssq');
+  [xx, j] = min (D);
+
+  it = 0;
+  do
+    for i = 1:columns (X)
+      U(:,i) = accumarray (j.', X(:,i), [nu, 1]);
+    endfor
+    N = accumarray (j.', ones (1, length (j)), [nu, 1]);
+    U = diag (N) \ U;
+    i = find (all (U == 0, 2));
+    U(i,:) = X(ceil (rand (1, length (i)) * rows (X)), :);
+    j1 = j;
+    D = pdist2_mw (U, X, 'ssq');
+    [xx, j] = min (D);
+    fprintf (stderr, "k-means iteration %d\r", ++it);
+  until (all (j == j1))
+  fprintf (stderr, "\n");
+
+  if (nargout > 2)
+    iu = j;
+  endif
+
+  if (nargout > 1)
+    ur = zeros (nu, 1);
+    for i = 1:nu
+      ij = (j == i);
+      ur(i) = sqrt (max (D(i,ij)));
+    endfor
+  endif
+
+  if (nargin == 3)
+    U = dmult (U, 1./theta);
+    if (any(theta == 0))
+      U(:,theta == 0) = 0;
+    endif
+  endif
+
+endfunction