devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

Add QR and Cholesky module instantiations in the lib.

Browse Source 
To try it with the unit tests set the cmake variable TEST_LIB to ON.
This commit is contained in:
Gael Guennebaud
2008-06-14 13:02:41 +00:00
parent 53289a8b64
commit f07f907810
15 changed files with 205 additions and 71 deletions
Download Patch File Download Diff File Expand all files Collapse all files

91
Eigen/src/QR/Tridiagonalization.h
View File

@@ -60,11 +60,11 @@ template<typename _MatrixType> class Tridiagonalization
NestByValue<Block<
MatrixType,SizeMinusOne,SizeMinusOne> > > >::RealReturnType SubDiagonalReturnType;
Tridiagonalization()
{}
Tridiagonalization(int rows, int cols)
: m_matrix(rows,cols), m_hCoeffs(rows-1)
/** This constructor initializes a Tridiagonalization object for
* further use with Tridiagonalization::compute()
*/
Tridiagonalization(int size = Size==Dynamic ? 2 : Size)
: m_matrix(size,size), m_hCoeffs(size-1)
{}
Tridiagonalization(const MatrixType& matrix)
@@ -90,7 +90,7 @@ template<typename _MatrixType> class Tridiagonalization
*
* \sa packedMatrix()
*/
CoeffVectorType householderCoefficients(void) const { return m_hCoeffs; }
inline CoeffVectorType householderCoefficients(void) const { return m_hCoeffs; }
/** \returns the internal result of the decomposition.
*
@@ -108,7 +108,7 @@ template<typename _MatrixType> class Tridiagonalization
*
* See LAPACK for further details on this packed storage.
*/
const MatrixType& packedMatrix(void) const { return m_matrix; }
inline const MatrixType& packedMatrix(void) const { return m_matrix; }
MatrixType matrixQ(void) const;
MatrixType matrixT(void) const;
@@ -128,6 +128,44 @@ template<typename _MatrixType> class Tridiagonalization
CoeffVectorType m_hCoeffs;
};
/** \returns an expression of the diagonal vector */
template<typename MatrixType>
const typename Tridiagonalization<MatrixType>::DiagonalReturnType
Tridiagonalization<MatrixType>::diagonal(void) const
{
return m_matrix.diagonal().nestByValue().real();
}
/** \returns an expression of the sub-diagonal vector */
template<typename MatrixType>
const typename Tridiagonalization<MatrixType>::SubDiagonalReturnType
Tridiagonalization<MatrixType>::subDiagonal(void) const
{
int n = m_matrix.rows();
return Block<MatrixType,SizeMinusOne,SizeMinusOne>(m_matrix, 1, 0, n-1,n-1)
.nestByValue().diagonal().nestByValue().real();
}
/** constructs and returns the tridiagonal matrix T.
* Note that the matrix T is equivalent to the diagonal and sub-diagonal of the packed matrix.
* Therefore, it might be often sufficient to directly use the packed matrix, or the vector
* expressions returned by diagonal() and subDiagonal() instead of creating a new matrix.
*/
template<typename MatrixType>
typename Tridiagonalization<MatrixType>::MatrixType
Tridiagonalization<MatrixType>::matrixT(void) const
{
// FIXME should this function (and other similar) rather take a matrix as argument
// and fill it (avoids temporaries)
int n = m_matrix.rows();
MatrixType matT = m_matrix;
matT.corner(TopRight,n-1, n-1).diagonal() = subDiagonal().conjugate();
matT.corner(TopRight,n-2, n-2).template part<Upper>().setZero();
matT.corner(BottomLeft,n-2, n-2).template part<Lower>().setZero();
return matT;
}
#ifndef EIGEN_HIDE_HEAVY_CODE
/** \internal
* Performs a tridiagonal decomposition of \a matA in place.
@@ -235,43 +273,6 @@ Tridiagonalization<MatrixType>::matrixQ(void) const
return matQ;
}
/** \returns an expression of the diagonal vector */
template<typename MatrixType>
const typename Tridiagonalization<MatrixType>::DiagonalReturnType
Tridiagonalization<MatrixType>::diagonal(void) const
{
return m_matrix.diagonal().nestByValue().real();
}
/** \returns an expression of the sub-diagonal vector */
template<typename MatrixType>
const typename Tridiagonalization<MatrixType>::SubDiagonalReturnType
Tridiagonalization<MatrixType>::subDiagonal(void) const
{
int n = m_matrix.rows();
return Block<MatrixType,SizeMinusOne,SizeMinusOne>(m_matrix, 1, 0, n-1,n-1)
.nestByValue().diagonal().nestByValue().real();
}
/** constructs and returns the tridiagonal matrix T.
* Note that the matrix T is equivalent to the diagonal and sub-diagonal of the packed matrix.
* Therefore, it might be often sufficient to directly use the packed matrix, or the vector
* expressions returned by diagonal() and subDiagonal() instead of creating a new matrix.
*/
template<typename MatrixType>
typename Tridiagonalization<MatrixType>::MatrixType
Tridiagonalization<MatrixType>::matrixT(void) const
{
// FIXME should this function (and other similar) rather take a matrix as argument
// and fill it (avoids temporaries)
int n = m_matrix.rows();
MatrixType matT = m_matrix;
matT.corner(TopRight,n-1, n-1).diagonal() = subDiagonal().conjugate();
matT.corner(TopRight,n-2, n-2).template part<Upper>().setZero();
matT.corner(BottomLeft,n-2, n-2).template part<Lower>().setZero();
return matT;
}
/** Performs a full decomposition in place */
template<typename MatrixType>
void Tridiagonalization<MatrixType>::decomposeInPlace(MatrixType& mat, DiagonalType& diag, SubDiagonalType& subdiag, bool extractQ)
@@ -337,4 +338,6 @@ void Tridiagonalization<MatrixType>::_decomposeInPlace3x3(MatrixType& mat, Diago
}
}
#endif // EIGEN_HIDE_HEAVY_CODE
#endif // EIGEN_TRIDIAGONALIZATION_H