LAPACK_utilities.hpp File Reference

#include "Eigen/Eigen"

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Classes
struct	LAPACK_utilities::QR_Factorization

Namespaces
namespace	LAPACK_utilities

Functions
void	LAPACK_utilities::svd (Eigen::MatrixXd A, Eigen::MatrixXd &U, Eigen::MatrixXd &V, Eigen::VectorXd &S)
	Given A = U * S * V' returns U, S and V'.
void	LAPACK_utilities::svd (Eigen::MatrixXd A, Eigen::MatrixXd &V, Eigen::VectorXd &S)
	Given A = U * S * V' returns only S and V'.
Eigen::VectorXd	LAPACK_utilities::svd (Eigen::MatrixXd A)
	Given A = U * S * V' returns only S.
double	LAPACK_utilities::cond (const Eigen::VectorXd &s)
	Compute condition number in norm 2 given singular values.
unsigned int	LAPACK_utilities::rank (const Eigen::VectorXd &s, const double &tolerance)
void	LAPACK_utilities::MGS (const Eigen::MatrixXd &X, Eigen::MatrixXd &Q, Eigen::MatrixXd &R)
	Compute the modified Gram-Schmidt factorization of matrix X.
QR_Factorization	LAPACK_utilities::MGS (const Eigen::MatrixXd &X, const double &tolerance=std::numeric_limits< double >::epsilon())
	Compute the modified Gram-Schmidt factorization of matrix X with no maximum rank.
QR_Factorization	LAPACK_utilities::QR (const Eigen::MatrixXd &X, const double &tolerance=std::numeric_limits< double >::epsilon())
	Compute the QR matrix based on Householder reflectors.
QR_Factorization	LAPACK_utilities::QRP (const Eigen::MatrixXd &X, const double &tolerance=std::numeric_limits< double >::epsilon())
	Compute the QR with pivoting matrix based on Householder reflectors.
Eigen::MatrixXd	LAPACK_utilities::triu (const Eigen::MatrixXd &X, const unsigned int &i)
	Extract upper triangular part of matrix X.
void	LAPACK_utilities::eig (const Eigen::MatrixXd A, Eigen::VectorXd &D, Eigen::MatrixXd &R)
	Compute eigenvalues and eigenvectors of A = R * D * R'.
void	LAPACK_utilities::inverseTri (const Eigen::MatrixXd A, Eigen::MatrixXd &InvA, const char &UPLO, const char &DIAG)
	Compute inverse of triangular matrix.
double	LAPACK_utilities::rcondest (const Eigen::SparseMatrix< double > &sparseA)