RWSymQREigServer< TypeT > Class Template Reference

Default server for the QR method of computing eigenvalues. More...

#include <rw/lapack/seigsrv.h>

Inheritance diagram for RWSymQREigServer< TypeT >:

Public Member Functions
	RWSymQREigServer (bool computeVecs=true)
virtual bool	computeEigenVectors () const
void	computeEigenVectors (bool computeVecs)
virtual RWSymEigDecomp< TypeT >	decompose (const RWTriDiagDecomp< TypeT > &A)
Public Member Functions inherited from RWSymEigServer< TypeT >
virtual RWSymEigDecomp< TypeT >	operator() (const RWSymBandMat< TypeT > &A)
virtual RWSymEigDecomp< TypeT >	operator() (const RWSymMat< TypeT > &A)

Detailed Description

template<class TypeT>
class RWSymQREigServer< TypeT >

The class RWSymQREigServer is the server for the QR method of computing eigenvalues. This is the default server.

Synopsis

#include <rw/lapack/seigsrv.h>
 
RWSymQREigServer<double> server;
RWSymEigDecomp<double> eig = server(A);  // A is a RWSymBandMat<double>

Example

#include <rw/lapack/seigsrv.h>
#include <iostream>
 
int main() {
  RWSymMat<double> A;  // input a matrix
  std::cin >> A;
 
  RWSymQREigServer<double> server;    // configure a server
  server.computeEigenVectors(false);  // turn off eigenvectors
  RWSymEigDecomp<double> eig = server(A);
 
  return 0;
}

Constructor & Destructor Documentation

RWSymQREigServer()

template<class TypeT >

RWSymQREigServer< TypeT >::RWSymQREigServer

(

bool

computeVecs = true

)

Constructs a server. The parameter indicates whether this server should be configured to compute eigenvectors as well as eigenvalues.

Member Function Documentation

computeEigenVectors() [1/2]

template<class TypeT >

virtual bool RWSymQREigServer< TypeT >::computeEigenVectors ( ) const

virtual

Returns true if this server is configured to compute eigenvectors as well as eigenvalues.

Implements RWSymEigServer< TypeT >.

computeEigenVectors() [2/2]

template<class TypeT >

void RWSymQREigServer< TypeT >::computeEigenVectors

(

bool

computeVecs

)

Sets whether or not the server should compute eigenvectors as well as eigenvalues.

decompose()

template<class TypeT >

virtual RWSymEigDecomp< TypeT > RWSymQREigServer< TypeT >::decompose ( const RWTriDiagDecomp< TypeT > & A )

virtual

Computes the eigenvalue decomposition of the tridiagonal matrix inside the tridiagonal decomposition.

Implements RWSymEigServer< TypeT >.