lambda_lanczos::tridiagonal_impl Namespace Reference

Functions
template<typename T >
size_t	num_of_eigs_smaller_than (T c, const std::vector< T > &alpha, const std::vector< T > &beta)
	Finds the number of eigenvalues of given tridiagonal matrix smaller than c. More...
template<typename T >
T	tridiagonal_eigen_limit (const std::vector< T > &alpha, const std::vector< T > &beta)
	Computes the upper bound of the absolute value of eigenvalues by Gerschgorin theorem. More...
template<typename T >
T	find_mth_eigenvalue (const std::vector< T > &alpha, const std::vector< T > &beta, const size_t m)
	Finds the mth smaller eigenvalue of given tridiagonal matrix. More...
template<typename T >
std::vector< T >	compute_tridiagonal_eigenvector_from_eigenvalue (const std::vector< T > &alpha, const std::vector< T > &beta, const size_t index, const T ev)
	Computes an eigenvector corresponding to given eigenvalue for given tri-diagonal matrix. More...
template<typename T >
void	tridiagonal_eigenpairs_bisection (const std::vector< T > &alpha, const std::vector< T > &beta, std::vector< T > &eigenvalues, std::vector< std::vector< T > > &eigenvectors)
	Computes all eigenpairs (eigenvalues and eigenvectors) for given tri-diagonal matrix. More...
template<typename T >
std::pair< T, T >	calc_givens_cs (T a, T b)
	Calculates the cosine and sine of Givens rotation that eliminates a specific element (see detail). More...
template<typename T >
void	isqr_step (std::vector< T > &alpha, std::vector< T > &beta, std::vector< std::vector< T > > &q, size_t offset, size_t nsub, bool rotate_matrix)
	Performs an implicit shift QR step A = Z^T A Z on given sub tridiagonal matrix A. More...
template<typename T >
void	find_subspace (const std::vector< T > &alpha, std::vector< T > &beta, size_t &submatrix_first, size_t &submatrix_last)
	Find sub-tridiagonal matrix that remains non-diagonal. More...
template<typename T >
size_t	tridiagonal_eigenpairs (const std::vector< T > &alpha, const std::vector< T > &beta, std::vector< T > &eigenvalues, std::vector< std::vector< T > > &eigenvectors, bool compute_eigenvector=true)
	Computes all eigenpairs (eigenvalues and eigenvectors) for given tri-diagonal matrix using the Implicitly Shifted QR algorithm. More...
template<typename T >
size_t	tridiagonal_eigenvalues (const std::vector< T > &alpha, const std::vector< T > &beta, std::vector< T > &eigenvalues)
	Computes all eigenvalues for given tri-diagonal matrix using the Implicitly Shifted QR algorithm. More...

Function Documentation

calc_givens_cs()

template<typename T >

std::pair< T, T > lambda_lanczos::tridiagonal_impl::calc_givens_cs ( T  a, T  b  )

inline

Calculates the cosine and sine of Givens rotation that eliminates a specific element (see detail).

This function calculates the cosine and sine that eliminate the element b, i.e. that satisfy

  ( c  s)(a) = (x)
  (-s  c)(b) = (0),
* 

where x >= 0.

Parameters

[in]	a	Input element to remain non-zero.
[in]	b	Input element to be eliminated.

Returns

Pair (c, s).

compute_tridiagonal_eigenvector_from_eigenvalue()

template<typename T >

std::vector< T > lambda_lanczos::tridiagonal_impl::compute_tridiagonal_eigenvector_from_eigenvalue ( const std::vector< T > &  alpha, const std::vector< T > &  beta, const size_t  index, const T  ev  )

inline

Computes an eigenvector corresponding to given eigenvalue for given tri-diagonal matrix.

find_mth_eigenvalue()

template<typename T >

T lambda_lanczos::tridiagonal_impl::find_mth_eigenvalue ( const std::vector< T > &  alpha, const std::vector< T > &  beta, const size_t  m  )

inline

Finds the mth smaller eigenvalue of given tridiagonal matrix.

find_subspace()

template<typename T >

void lambda_lanczos::tridiagonal_impl::find_subspace ( const std::vector< T > &  alpha, std::vector< T > &  beta, size_t &  submatrix_first, size_t &  submatrix_last  )

inline

Find sub-tridiagonal matrix that remains non-diagonal.

This function does the following two things:

1. Overwrite small elements with zero,
2. Find subspace that remains non-diagonal. The dimension of the resulting sub-matrix is submatrix_last - submatrix_first + 1.

Parameters

[in]	alpha	Diagonal elements of the full tridiagonal matrix.
[in,out]	beta	Sub-diagonal elements of the full tridiagonal matrix.
[out]	submatrix_first	Index to point the first element of the sub-tridiagonal matrix.
[in,out]	submatrix_last	Index to point the last element of the sub-tridiagonal matrix.

isqr_step()

template<typename T >

void lambda_lanczos::tridiagonal_impl::isqr_step ( std::vector< T > &  alpha, std::vector< T > &  beta, std::vector< std::vector< T > > &  q, size_t  offset, size_t  nsub, bool  rotate_matrix  )

inline

Performs an implicit shift QR step A = Z^T A Z on given sub tridiagonal matrix A.

Parameters

[in,out]	alpha	Diagonal elements of the full tridiagonal matrix.
[in,out]	beta	Subdiagonal elements of the full tridiagonal matrix.
[in,out]	q	A "matrix" Q that will be overwritten as Q = QZ if rotate_matrix is true. See note for details.
	offset	The first index of the submatrix.
	nsub	The size of the submatrix.
	rotate_matrix	True to apply Given's rotations to the matrix q. If false, the matrix q won't be accessed.

Note

A series of the QR steps produces an eigenvector "matrix" q that stores the k-th eigenvector as q[k][:]. This definition differs from a usual mathematical sense (i.e., Q_{:,k} specifies the k-th eigenvector).

num_of_eigs_smaller_than()

template<typename T >

size_t lambda_lanczos::tridiagonal_impl::num_of_eigs_smaller_than ( T  c, const std::vector< T > &  alpha, const std::vector< T > &  beta  )

inline

Finds the number of eigenvalues of given tridiagonal matrix smaller than c.

Algorithm from Peter Arbenz et al. / "High Performance Algorithms for Structured Matrix Problems" / Nova Science Publishers, Inc.

tridiagonal_eigen_limit()

template<typename T >

T lambda_lanczos::tridiagonal_impl::tridiagonal_eigen_limit ( const std::vector< T > &  alpha, const std::vector< T > &  beta  )

inline

Computes the upper bound of the absolute value of eigenvalues by Gerschgorin theorem.

This routine gives a rough upper bound, but it is sufficient because the bisection routine using the upper bound converges exponentially.

tridiagonal_eigenpairs()

template<typename T >

size_t lambda_lanczos::tridiagonal_impl::tridiagonal_eigenpairs ( const std::vector< T > &  alpha, const std::vector< T > &  beta, std::vector< T > &  eigenvalues, std::vector< std::vector< T > > &  eigenvectors, bool  compute_eigenvector = true  )

inline

Computes all eigenpairs (eigenvalues and eigenvectors) for given tri-diagonal matrix using the Implicitly Shifted QR algorithm.

Parameters

[in]	alpha	Diagonal elements of the full tridiagonal matrix.
[in]	beta	Sub-diagonal elements of the full tridiagonal matrix.
[out]	eigenvalues	Eigenvalues.
[out]	eigenvectors	Eigenvectors. The k-th eigenvector will be stored in eigenvectors[k].
[in]	compute_eigenvector	True to calculate eigenvectors. If false, eigenvectors won't be accessed.

Returns

Count of forced breaks due to unconvergence.

tridiagonal_eigenpairs_bisection()

template<typename T >

void lambda_lanczos::tridiagonal_impl::tridiagonal_eigenpairs_bisection ( const std::vector< T > &  alpha, const std::vector< T > &  beta, std::vector< T > &  eigenvalues, std::vector< std::vector< T > > &  eigenvectors  )

inline

Computes all eigenpairs (eigenvalues and eigenvectors) for given tri-diagonal matrix.

tridiagonal_eigenvalues()

template<typename T >

size_t lambda_lanczos::tridiagonal_impl::tridiagonal_eigenvalues ( const std::vector< T > &  alpha, const std::vector< T > &  beta, std::vector< T > &  eigenvalues  )

inline

Computes all eigenvalues for given tri-diagonal matrix using the Implicitly Shifted QR algorithm.

Parameters

[in]	alpha	Diagonal elements of the full tridiagonal matrix.
[in]	beta	Sub-diagonal elements of the full tridiagonal matrix.
[out]	eigenvalues	Eigenvalues.

Returns

Count of forced breaks due to unconvergence.