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 | |
| madness | |
| File holds all helper structures necessary for the CC_Operator and CC2 class. | |
Functions | |
| template<typename T > | |
| void | madness::cholesky (Tensor< T > &A) |
| Compute the Cholesky factorization. More... | |
| 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. More... | |
| 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. More... | |
| template<typename T > | |
| void | madness::geqp3 (Tensor< T > &A, Tensor< T > &tau, Tensor< integer > &jpvt) |
| Compute the QR factorization. More... | |
| 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. More... | |
| 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. More... | |
| void | madness::init_tensor_lapack () |
World/MRA initialization calls this before going multithreaded due to static data in dlamch. More... | |
| template<typename T > | |
| Tensor< T > | madness::inverse (const Tensor< T > &a_in) |
| invert general square matrix A More... | |
| template<typename T > | |
| void | madness::lq (Tensor< T > &A, Tensor< T > &R) |
| compute the LQ decomposition of the matrix A = L Q More... | |
| 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 More... | |
| template<typename T > | |
| void | madness::orgqr (Tensor< T > &A, const Tensor< T > &tau) |
| reconstruct the orthogonal matrix Q (e.g. from QR factorization) More... | |
| template<typename T > | |
| void | madness::qr (Tensor< T > &A, Tensor< T > &R) |
| compute the QR decomposition of the matrix A More... | |
| 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. More... | |
| template<typename T > | |
| std::tuple< Tensor< T >, Tensor< typename Tensor< T >::scalar_type >, Tensor< T > > | madness::svd (const Tensor< T > &A) |
| SVD - MATLAB syntax. More... | |
| 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. More... | |
| 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 More... | |
| 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. More... | |
| 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. More... | |
| 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. More... | |
| bool | madness::test_tensor_lapack () |
| Test the Tensor-LAPACK interface ... currently always returns true! More... | |
Detailed Description
Prototypes for a partial interface from Tensor to LAPACK.
