Spectra
1.0.1
Headeronly C++ Library for Large Scale Eigenvalue Problems

#include <Spectra/SymGEigsSolver.h>
Public Member Functions  
SymGEigsSolver (OpType &op, BOpType &Bop, Index nev, Index ncv)  
Public Member Functions inherited from Spectra::SymEigsBase< SymGEigsRegInvOp< OpType, BOpType >, BOpType >  
void  init (const Scalar *init_resid) 
void  init () 
Index  compute (SortRule selection=SortRule::LargestMagn, Index maxit=1000, Scalar tol=1e10, SortRule sorting=SortRule::LargestAlge) 
CompInfo  info () const 
Index  num_iterations () const 
Index  num_operations () const 
Vector  eigenvalues () const 
virtual Matrix  eigenvectors (Index nvec) const 
virtual Matrix  eigenvectors () const 
This class implements the generalized eigen solver for real symmetric matrices in the regular inverse mode, i.e., to solve \(Ax=\lambda Bx\) where \(A\) is symmetric, and \(B\) is positive definite with the operations defined below.
This solver requires two matrix operation objects: one for \(A\) that implements the matrix multiplication \(Av\), and one for \(B\) that implements the matrixvector product \(Bv\) and the linear equation solving operation \(B^{1}v\).
If \(A\) and \(B\) are stored as Eigen matrices, then the first operation can be created using the DenseSymMatProd or SparseSymMatProd classes, and the second operation can be created using the SparseRegularInverse class. There is no wrapper class for a dense \(B\) matrix since in this case the Cholesky mode is always preferred. If the users need to define their own operation classes, then they should implement all the public member functions as in those builtin classes.
OpType  The name of the matrix operation class for \(A\). Users could either use the wrapper classes such as DenseSymMatProd and SparseSymMatProd, or define their own that implements the type definition Scalar and all the public member functions as in DenseSymMatProd. 
BOpType  The name of the matrix operation class for \(B\). Users could either use the wrapper class SparseRegularInverse, or define their own that implements all the public member functions as in SparseRegularInverse. 
Mode  Mode of the generalized eigen solver. In this solver it is Spectra::GEigsMode::RegularInverse. 
Definition at line 251 of file SymGEigsSolver.h.

inline 
Constructor to create a solver object.
op  The \(A\) matrix operation object that implements the matrixvector multiplication operation of \(A\): calculating \(Av\) for any vector \(v\). Users could either create the object from the wrapper classes such as DenseSymMatProd, or define their own that implements all the public members as in DenseSymMatProd. 
Bop  The \(B\) matrix operation object that implements the multiplication operation \(Bv\) and the linear equation solving operation \(B^{1}v\) for any vector \(v\). Users could either create the object from the wrapper class SparseRegularInverse, or define their own that implements all the public member functions as in SparseRegularInverse. \(B\) needs to be positive definite. 
nev  Number of eigenvalues requested. This should satisfy \(1\le nev \le n1\), where \(n\) is the size of matrix. 
ncv  Parameter that controls the convergence speed of the algorithm. Typically a larger ncv means faster convergence, but it may also result in greater memory use and more matrix operations in each iteration. This parameter must satisfy \(nev < ncv \le n\), and is advised to take \(ncv \ge 2\cdot nev\). 
Definition at line 283 of file SymGEigsSolver.h.