Description

Compute (complex) eigenvalues and eigenvectors using the Krylov-Schur algorithm.

Adapted from Matlab code at https://github.com/dingxiong/KrylovSchur Use one of the chrono::modal::callback_Ax provided above depending on the type of problem that you must solve.

#include <ChKrylovSchurEig.h>

Public Member Functions
	ChKrylovSchurEig (ChMatrixDynamic< std::complex< double >> &v, ChVectorDynamic< std::complex< double >> &eig, bool &isC, bool &flag, int &nc, int &ni, callback_Ax *Ax_function, ChVectorDynamic< std::complex< double >> &v1, const int n, const int k, const int m, const int maxIt, const double tol)

Constructor & Destructor Documentation

chrono::modal::ChKrylovSchurEig::ChKrylovSchurEig	(	ChMatrixDynamic< std::complex< double >> &	v,
		ChVectorDynamic< std::complex< double >> &	eig,
		bool &	isC,
		bool &	flag,
		int &	nc,
		int &	ni,
		callback_Ax *	Ax_function,
		ChVectorDynamic< std::complex< double >> &	v1,
		const int	n,
		const int	k,
		const int	m,
		const int	maxIt,
		const double	tol
	)

Parameters

v	output matrix with eigenvectors as columns, will be resized
eig	output vector with eigenvalues (real part not zero if some damping), will be resized
isC	0 = k-th eigenvalue is real, 1= k-th and k-th+1 are complex conjugate pairs
flag	0 = has converged, 1 = hasn't converged
nc	number of converged eigenvalues
ni	number of used iterations
Ax_function	compute the Ax operation, assuming standard eigenvalue problem Av=lambda*v.
v1	initial approx of eigenvector, or random
n	size of A
k	number of needed eigenvalues
m	Krylov restart threshold (largest dimension of krylov subspace)
maxIt	max iteration number
tol	tolerance

The documentation for this class was generated from the following files: