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Cleaning documentation pass in ordering and ILUT

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This commit is contained in:
Gael Guennebaud 2013-01-12 11:56:56 +01:00
parent 38fa432e07
commit 7262cf783c
3 changed files with 104 additions and 97 deletions
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8
Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
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@ -15,7 +15,7 @@ namespace Eigen {
namespace internal { namespace internal {
/** /** \internal
* Compute a quick-sort split of a vector * Compute a quick-sort split of a vector
* On output, the vector row is permuted such that its elements satisfy * On output, the vector row is permuted such that its elements satisfy
* abs(row(i)) >= abs(row(ncut)) if i<ncut * abs(row(i)) >= abs(row(ncut)) if i<ncut
@ -60,8 +60,11 @@ int QuickSplit(VectorV &row, VectorI &ind, int ncut)
} }
}// end namespace internal }// end namespace internal
/**
/** \ingroup IterativeLinearSolvers_Module
* \class IncompleteLUT
* \brief Incomplete LU factorization with dual-threshold strategy * \brief Incomplete LU factorization with dual-threshold strategy
*
* During the numerical factorization, two dropping rules are used : * During the numerical factorization, two dropping rules are used :
* 1) any element whose magnitude is less than some tolerance is dropped. * 1) any element whose magnitude is less than some tolerance is dropped.
* This tolerance is obtained by multiplying the input tolerance @p droptol * This tolerance is obtained by multiplying the input tolerance @p droptol
@ -462,4 +465,3 @@ struct solve_retval<IncompleteLUT<_MatrixType>, Rhs>
} // end namespace Eigen } // end namespace Eigen
#endif // EIGEN_INCOMPLETE_LUT_H #endif // EIGEN_INCOMPLETE_LUT_H

1
Eigen/src/OrderingMethods/Amd.h
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@ -86,6 +86,7 @@ Index cs_tdfs(Index j, Index k, Index *head, const Index *next, Index *post, Ind
/** \internal /** \internal
* \ingroup OrderingMethods_Module
* Approximate minimum degree ordering algorithm. * Approximate minimum degree ordering algorithm.
* \returns the permutation P reducing the fill-in of the input matrix \a C * \returns the permutation P reducing the fill-in of the input matrix \a C
* The input matrix \a C must be a selfadjoint compressed column major SparseMatrix object. Both the upper and lower parts have to be stored, but the diagonal entries are optional. * The input matrix \a C must be a selfadjoint compressed column major SparseMatrix object. Both the upper and lower parts have to be stored, but the diagonal entries are optional.

42
Eigen/src/OrderingMethods/Ordering.h
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@ -33,13 +33,14 @@ namespace Eigen {
namespace internal { namespace internal {
/** /** \internal
* Get the symmetric pattern A^T+A from the input matrix A. * \ingroup OrderingMethods_Module
* \returns the symmetric pattern A^T+A from the input matrix A.
* FIXME: The values should not be considered here * FIXME: The values should not be considered here
*/ */
template<typename MatrixType> template<typename MatrixType>
void ordering_helper_at_plus_a(const MatrixType& mat, MatrixType& symmat) void ordering_helper_at_plus_a(const MatrixType& mat, MatrixType& symmat)
{ {
MatrixType C; MatrixType C;
C = mat.transpose(); // NOTE: Could be costly C = mat.transpose(); // NOTE: Could be costly
for (int i = 0; i < C.rows(); i++) for (int i = 0; i < C.rows(); i++)
@ -48,14 +49,17 @@ namespace internal {
it.valueRef() = 0.0; it.valueRef() = 0.0;
} }
symmat = C + mat; symmat = C + mat;
} }
} }
/** /** \ingroup OrderingMethods_Module
* Get the approximate minimum degree ordering * \class AMDOrdering
*
* Functor computing the \em approximate \em minimum \em degree ordering
* If the matrix is not structurally symmetric, an ordering of A^T+A is computed * If the matrix is not structurally symmetric, an ordering of A^T+A is computed
* \tparam Index The type of indices of the matrix * \tparam Index The type of indices of the matrix
* \sa COLAMDOrdering
*/ */
template <typename Index> template <typename Index>
class AMDOrdering class AMDOrdering
@ -90,10 +94,12 @@ class AMDOrdering
} }
}; };
/** /** \ingroup OrderingMethods_Module
* Get the natural ordering * \class NaturalOrdering
* *
*NOTE Returns an empty permutation matrix * Functor computing the natural ordering (identity)
*
* \note Returns an empty permutation matrix
* \tparam Index The type of indices of the matrix * \tparam Index The type of indices of the matrix
*/ */
template <typename Index> template <typename Index>
@ -111,20 +117,19 @@ class NaturalOrdering
}; };
/** /** \ingroup OrderingMethods_Module
* Get the column approximate minimum degree ordering * \class COLAMDOrdering
*
* Functor computing the \em column \em approximate \em minimum \em degree ordering
* The matrix should be in column-major format * The matrix should be in column-major format
*/ */
template<typename Index>
class COLAMDOrdering;
#include "Eigen_Colamd.h"
template<typename Index> template<typename Index>
class COLAMDOrdering class COLAMDOrdering
{ {
public: public:
typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType; typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
typedef Matrix<Index, Dynamic, 1> IndexVector; typedef Matrix<Index, Dynamic, 1> IndexVector;
/** Compute the permutation vector form a sparse matrix */ /** Compute the permutation vector form a sparse matrix */
template <typename MatrixType> template <typename MatrixType>
void operator() (const MatrixType& mat, PermutationType& perm) void operator() (const MatrixType& mat, PermutationType& perm)
@ -149,10 +154,9 @@ class COLAMDOrdering
perm.resize(n); perm.resize(n);
for (int i = 0; i < n; i++) perm.indices()(p(i)) = i; for (int i = 0; i < n; i++) perm.indices()(p(i)) = i;
} }
}; };
} // end namespace Eigen } // end namespace Eigen
#endif #endif