tensor_lapack.h File Reference

Prototypes for a partial interface from Tensor to LAPACK. More...

#include <madness/tensor/tensor.h>
#include <madness/fortran_ctypes.h>
#include <madness/tensor/elem.h>

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Namespaces
namespace	madness
	Namespace for all elements and tools of MADNESS.

Functions
template<typename T >
void	madness::cholesky (Tensor< T > &A)
	Compute the Cholesky factorization.
template<typename T >
void	madness::geev (const Tensor< T > &A, Tensor< T > &VR, Tensor< std::complex< T > > &e)
	Real non-symmetric or complex non-Hermitian eigenproblem.
template<typename T >
void	madness::gelss (const Tensor< T > &a, const Tensor< T > &b, double rcond, Tensor< T > &x, Tensor< typename Tensor< T >::scalar_type > &s, long &rank, Tensor< typename Tensor< T >::scalar_type > &sumsq)
	Solve Ax = b for general A using the LAPACK *gelss routines.
template<typename T >
void	madness::geqp3 (Tensor< T > &A, Tensor< T > &tau, Tensor< integer > &jpvt)
	Compute the QR factorization.
template<typename T >
void	madness::gesv (const Tensor< T > &a, const Tensor< T > &b, Tensor< T > &x)
	Solve Ax = b for general A using the LAPACK *gesv routines.
template<typename T >
void	madness::ggev (const Tensor< T > &A, Tensor< T > &B, Tensor< T > &VR, Tensor< std::complex< T > > &e)
	Generalized real-non-symmetric or complex-non-Hermitian eigenproblem.
void	madness::init_tensor_lapack ()
	World/MRA initialization calls this before going multithreaded due to static data in dlamch.
template<typename T >
Tensor< T >	madness::inverse (const Tensor< T > &a_in)
	invert general square matrix A
template<typename T >
void	madness::lq (Tensor< T > &A, Tensor< T > &R)
	compute the LQ decomposition of the matrix A = L Q
template<typename T >
void	madness::lq_result (Tensor< T > &A, Tensor< T > &R, Tensor< T > &tau, Tensor< T > &work, bool do_qr)
	compute the LQ decomposition of the matrix A = L Q
template<typename T >
void	madness::orgqr (Tensor< T > &A, const Tensor< T > &tau)
	reconstruct the orthogonal matrix Q (e.g. from QR factorization)
template<typename T >
void	madness::qr (Tensor< T > &A, Tensor< T > &R)
	compute the QR decomposition of the matrix A
template<typename T >
void	madness::rr_cholesky (Tensor< T > &A, typename Tensor< T >::scalar_type tol, Tensor< integer > &piv, int &rank)
	Compute the rank-revealing Cholesky factorization.
template<typename T >
std::tuple< Tensor< T >, Tensor< typename Tensor< T >::scalar_type >, Tensor< T > >	madness::svd (const Tensor< T > &A)
	SVD - MATLAB syntax.
template<typename T >
void	madness::svd (const Tensor< T > &a, Tensor< T > &U, Tensor< typename Tensor< T >::scalar_type > &s, Tensor< T > &VT)
	Compute the singluar value decomposition of an n-by-m matrix using *gesvd.
template<typename T >
void	madness::svd_result (Tensor< T > &a, Tensor< T > &U, Tensor< typename Tensor< T >::scalar_type > &s, Tensor< T > &VT, Tensor< T > &work)
	same as svd, but it optimizes away the tensor construction: a = U * diag(s) * VT
template<typename T >
std::tuple< Tensor< typename Tensor< T >::scalar_type >, Tensor< T > >	madness::syev (const Tensor< T > &A)
	Solves symmetric or Hermitian eigenvalue problem - MATLAB syntax.
template<typename T >
void	madness::syev (const Tensor< T > &A, Tensor< T > &V, Tensor< typename Tensor< T >::scalar_type > &e)
	Real-symmetric or complex-Hermitian eigenproblem.
template<typename T >
void	madness::sygv (const Tensor< T > &A, const Tensor< T > &B, int itype, Tensor< T > &V, Tensor< typename Tensor< T >::scalar_type > &e)
	Generalized real-symmetric or complex-Hermitian eigenproblem.
bool	madness::test_tensor_lapack ()
	Test the Tensor-LAPACK interface ... currently always returns true!

Detailed Description

Prototypes for a partial interface from Tensor to LAPACK.