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[Toon-members] TooN/doc Choleskydoc.h
From: |
Tom Drummond |
Subject: |
[Toon-members] TooN/doc Choleskydoc.h |
Date: |
Tue, 06 Mar 2007 22:47:25 +0000 |
CVSROOT: /sources/toon
Module name: TooN
Changes by: Tom Drummond <twd20> 07/03/06 22:47:25
Modified files:
doc : Choleskydoc.h
Log message:
Choleskydoc.h fixed so that it appears in the list of decompositions
CVSWeb URLs:
http://cvs.savannah.gnu.org/viewcvs/TooN/doc/Choleskydoc.h?cvsroot=toon&r1=1.1&r2=1.2
Patches:
Index: Choleskydoc.h
===================================================================
RCS file: /sources/toon/TooN/doc/Choleskydoc.h,v
retrieving revision 1.1
retrieving revision 1.2
diff -u -b -r1.1 -r1.2
--- Choleskydoc.h 15 Jan 2007 18:00:54 -0000 1.1
+++ Choleskydoc.h 6 Mar 2007 22:47:25 -0000 1.2
@@ -12,9 +12,9 @@
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
-// A proxy version of the LU class,
+// A proxy version of the Cholesky class,
// cleaned up to present a comprehensible
-// version of the LU interface
+// version of the Cholesky interface
#ifdef DOXYGEN_INCLUDE_ONLY_FOR_DOCS
@@ -27,38 +27,42 @@
#include <TooN/helpers.h>
#include <limits>
-namespace TooN {
-/// @class Cholesky Choleskydoc.h TooN/Cholesky.h
-/// Decomposes a positive-semidefinite symmetric matrix A (such as a
covariance) into L*D*L^T, where L is lower-triangular and D is diagonal.
-/// Also can compute A = S*S^T, with S lower triangular. The LDL^T form is
faster to compute than the class Cholesky decomposition.
-/// The decomposition can be used to compute A^-1*x, A^-1*M, M*A^-1*M^T, and
A^-1 itself, though the latter rarely needs to be explicitly represented.
-/// Also efficiently computes det(A) and rank(A).
-/// It can be used as follows:
-/// @code
-/// // Declare some matrices.
-/// Matrix<3> A = ...; // we'll pretend it is pos-def
-/// Matrix<2,3> M;
-/// Matrix<2> B;
-/// Vector<3> y = (make_Vector, 2,3,4);
-/// // create the Cholesky decomposition of A
-/// Cholesky<3> chol(A);
-/// // compute x = A^-1 * y
-/// Vector<3> x = cholA.inverse_times(y);
-/// Identical to above
-/// x = cholA.backsub(y);
-/// // compute B = M*A^-1*M^T
-/// B = cholA.transform_inverse(M);
-/// //compute A^-1
-/// Matrix<3> Ainv = cholA.get_inverse();
-/// Matrix<3> C = ... // again, C is pos-def
-/// //compute the 'square-root' of C
-/// Matrix<3> L = Cholesky<3>::sqrt(C);
-/// @endcode
-/// @ingroup gDecomps
+/// All classes and functions are within this namespace
+namespace TooN
+{
+/**
address@hidden Cholesky Choleskydoc.h TooN/Cholesky.h
+Decomposes a positive-semidefinite symmetric matrix A (such as a covariance)
into L*D*L^T, where L is lower-triangular and D is diagonal.
+Also can compute A = S*S^T, with S lower triangular. The LDL^T form is faster
to compute than the class Cholesky decomposition.
+The decomposition can be used to compute A^-1*x, A^-1*M, M*A^-1*M^T, and A^-1
itself, though the latter rarely needs to be explicitly represented.
+Also efficiently computes det(A) and rank(A).
+It can be used as follows:
address@hidden
+// Declare some matrices.
+Matrix<3> A = ...; // we'll pretend it is pos-def
+Matrix<2,3> M;
+Matrix<2> B;
+Vector<3> y = (make_Vector, 2,3,4);
+// create the Cholesky decomposition of A
+Cholesky<3> chol(A);
+// compute x = A^-1 * y
+Vector<3> x = cholA.inverse_times(y);
+// Identical to above
+x = cholA.backsub(y);
+// compute B = M*A^-1*M^T
+B = cholA.transform_inverse(M);
+//compute A^-1
+Matrix<3> Ainv = cholA.get_inverse();
+Matrix<3> C = ... // again, C is pos-def
+//compute the 'square-root' of C
+Matrix<3> L = Cholesky<3>::sqrt(C);
address@hidden
address@hidden gDecomps
+**/
+
template <int N>
class Cholesky {
public:
-
/// Construct the Cholesky-ish decomposition of a matrix. This initialises
the class, and
/// performs the decomposition immediately.
/// Run time is O(N^3)
@@ -165,4 +169,6 @@
template <class A> void update(const FixedVector<N,A>& v);
};
+};
+
#endif
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