Merge pull request #1 from ziejd2/octave_php_separate

Octave php separate

1 files changed, 55 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/eigdec.m b/sourcecodes/bnt-master/netlab3.3/eigdec.m
new file mode 100644
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+++ b/sourcecodes/bnt-master/netlab3.3/eigdec.m
@@ -0,0 +1,55 @@
+function [evals, evec] = eigdec(x, N)
+%EIGDEC	Sorted eigendecomposition
+%
+%	Description
+%	 EVALS = EIGDEC(X, N computes the largest N eigenvalues of the
+%	matrix X in descending order.  [EVALS, EVEC] = EIGDEC(X, N) also
+%	computes the corresponding eigenvectors.
+%
+%	See also
+%	PCA, PPCA
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+if nargout == 1
+   evals_only = logical(1);
+else
+   evals_only = logical(0);
+end
+
+if N ~= round(N) | N < 1 | N > size(x, 2)
+   error('Number of PCs must be integer, >0, < dim');
+end
+
+% Find the eigenvalues of the data covariance matrix
+if evals_only
+   % Use eig function as always more efficient than eigs here
+   temp_evals = eig(x);
+else
+   % Use eig function unless fraction of eigenvalues required is tiny
+   if (N/size(x, 2)) > 0.04
+      [temp_evec, temp_evals] = eig(x);
+   else
+      options.disp = 0;
+      [temp_evec, temp_evals] = eigs(x, N, 'LM', options);
+   end
+   temp_evals = diag(temp_evals);
+end
+
+% Eigenvalues nearly always returned in descending order, but just
+% to make sure.....
+[evals perm] = sort(-temp_evals);
+evals = -evals(1:N);
+if ~evals_only
+   if evals == temp_evals(1:N)
+      % Originals were in order
+      evec = temp_evec(:, 1:N);
+      return
+   else
+      % Need to reorder the eigenvectors
+      for i=1:N
+         evec(:,i) = temp_evec(:,perm(i));
+      end
+   end
+end
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