self_adjoint_eigh.hpp File Reference

In-place and value-producing dense self-adjoint eigensystems. More...

#include <uni20/common/trace.hpp>
#include <uni20/linalg/backends/lapack/self_adjoint_eigh.hpp>
#include <uni20/linalg/blas/mdspan_matrix.hpp>
#include <uni20/linalg/decomposition_precision.hpp>
#include <uni20/linalg/dispatch.hpp>
#include <uni20/linalg/operation_tags.hpp>
#include <uni20/tensor/conjugate_inplace.hpp>
#include <uni20/tensor/copy.hpp>
#include <uni20/tensor/output.hpp>
#include <uni20/tensor/tensor.hpp>
#include <array>
#include <concepts>
#include <type_traits>
#include <utility>

Include dependency graph for ops/self_adjoint_eigh.hpp:

This graph shows which files directly or indirectly include this file:

Go to the source code of this file.

Classes
struct	uni20::linalg::SelfAdjointEighResult< EigenvalueTensor, EigenvectorTensor >
	Owning eigenvalues and eigenvectors returned by eigh. More...

Namespaces
namespace	uni20
namespace	uni20::linalg

Functions
template<KernelBackendSelector BackendSelector, class MatrixTensor > requires uni20::OwningTensor<MatrixTensor> && uni20::MutableRankedImmediateTensorView<MatrixTensor, 2> && (!std::is_lvalue_reference_v<MatrixTensor>) && (!std::is_const_v<std::remove_reference_t<MatrixTensor>>)
auto	uni20::linalg::eigh (BackendSelector &&selector, MatrixTensor &&matrix, MatrixTriangle triangle=MatrixTriangle::Upper, std::optional< Precision > requested={})
	Consume an owning matrix and return its complete self-adjoint eigensystem through an explicit selector.
template<KernelBackendSelector BackendSelector, uni20::RankedTensorView< 2 > MatrixTensor>
auto	uni20::linalg::eigh (BackendSelector &&selector, MatrixTensor const &matrix, MatrixTriangle triangle=MatrixTriangle::Upper, std::optional< Precision > requested={})
	Preserve a matrix and return its complete self-adjoint eigensystem through an explicit selector.
template<RankedTensorView< 2 > Matrix>
auto	uni20::linalg::eigh (Matrix &&matrix, Precision p, MatrixTriangle triangle=MatrixTriangle::Upper)
	Compute a self-adjoint eigensystem at explicit working precision with optional output settings.
template<class MatrixTensor > requires uni20::OwningTensor<MatrixTensor> && uni20::MutableRankedImmediateTensorView<MatrixTensor, 2> && (!std::is_lvalue_reference_v<MatrixTensor>) && (!std::is_const_v<std::remove_reference_t<MatrixTensor>>)
auto	uni20::linalg::eigh (MatrixTensor &&matrix, MatrixTriangle triangle=MatrixTriangle::Upper, std::optional< Precision > requested={})
	Consume an owning matrix and return its complete self-adjoint eigensystem.
template<uni20::RankedTensorView< 2 > MatrixTensor>
auto	uni20::linalg::eigh (MatrixTensor const &matrix, MatrixTriangle triangle=MatrixTriangle::Upper, std::optional< Precision > requested={})
	Preserve a matrix and return its complete self-adjoint eigensystem.
template<KernelBackendSelector Selector, RankedTensorView< 2 > Matrix>
auto	uni20::linalg::eigh (Selector &&selector, Matrix &&matrix, Precision p, MatrixTriangle triangle=MatrixTriangle::Upper)
	Compute a self-adjoint eigensystem at explicit working precision with optional output settings.
template<KernelBackendSelector BackendSelector, uni20::MutableRankedTensorView< 1 > EigenvalueTensor, uni20::MutableRankedTensorView< 2 > MatrixTensor>
void	uni20::linalg::self_adjoint_eigh (BackendSelector &&selector, EigenvalueTensor &&eigenvalues, MatrixTensor &&matrix_work, SelfAdjointEighOptions options={}, std::optional< Precision > requested={})
	Compute an in-place self-adjoint eigensystem through an explicit selector.
template<uni20::MutableRankedTensorView< 1 > EigenvalueTensor, uni20::MutableRankedTensorView< 2 > MatrixTensor>
void	uni20::linalg::self_adjoint_eigh (EigenvalueTensor &&eigenvalues, MatrixTensor &&matrix_work, SelfAdjointEighOptions options={}, std::optional< Precision > requested={})
	Compute an in-place self-adjoint eigensystem using tensor storage policy.
template<KernelBackendSelector Selector, MutableRankedTensorView< 1 > V, MutableRankedTensorView< 2 > A>
void	uni20::linalg::self_adjoint_eigh (Selector &&selector, V &&eigenvalues, A &&matrix_work, Precision p, SelfAdjointEighOptions options={})
	Compute a destructive decomposition at explicit precision with optional output settings.
template<MutableRankedTensorView< 1 > V, MutableRankedTensorView< 2 > A>
void	uni20::linalg::self_adjoint_eigh (V &&eigenvalues, A &&matrix_work, Precision p, SelfAdjointEighOptions options={})
	Compute a destructive decomposition at explicit precision with optional output settings.

Detailed Description

In-place and value-producing dense self-adjoint eigensystems.

Precision may be inferred from the input matrix or supplied explicitly. Fixed results require their native precision; runtime decompositions require finite precision. Owning results record the selected default.