RWSymSomeEigServer< TypeT > Class Template Reference
[Symmetric Eigenvalue Decomposition]

Server for symmetric eigenvalues that allows the computation of a subset of the eigenvalues and (optionally) their corresponding eigenvectors. More...

#include <rw/lapack/seigsrv.h>

Inheritance diagram for RWSymSomeEigServer< TypeT >:

List of all members.

Public Member Functions
	RWSymSomeEigServer (bool computeVecs=true)
virtual RWSymEigDecomp< TypeT >	decompose (const RWTriDiagDecomp< TypeT > &A)
TypeT	setTolerance (TypeT tolerance)
RWSlice	setRange (const RWSlice &range)
virtual bool	computeEigenVectors () const
void	computeEigenVectors (bool computeVecs)

---

Detailed Description

template<class TypeT>
class RWSymSomeEigServer< TypeT >

The symmetric eigenvalue server class, RWSymSomeEigServer<T> , allows the computation of a subset of the eigenvalues and (optionally) their corresponding eigenvectors. The computation uses the bisection method to find the eigenvalues, followed by inverse iteration to find the eigenvectors. The subset of eigenvalues to be computed is specified using the RWSlice class, or one of its subclasses, RWRange or RWToEnd. This provides the flexibility to specify either the smallest eigenvalues, the largest, or a selection in between. The eigenvalue ordering is smallest to largest.

Synopsis

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

Examples

 #include <iostream>
 #include <rw/lapack/seigsrv.h>
 
 int main()
 {
     RWSymMat<double> A;                     // input a matrix
     std::cin >> A;
 
     RWSymSomeEigServer<double> server;      // configure a server
     server.setRange(RWSlice(0,5));          // the 5 smallest eigenvalues
     RWSymEigDecomp<double> eig = server(A);

     return 0;
 }

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Constructor & Destructor Documentation

template<class TypeT>

RWSymSomeEigServer< TypeT >::RWSymSomeEigServer

(

bool

computeVecs = true

)

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

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Member Function Documentation

template<class TypeT>

void RWSymSomeEigServer< TypeT >::computeEigenVectors

(

bool

computeVecs

)

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

template<class TypeT>

virtual bool RWSymSomeEigServer< TypeT >::computeEigenVectors

(

)

const [virtual]

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

Implements RWSymEigServer< TypeT >.

template<class TypeT>

virtual RWSymEigDecomp<TypeT> RWSymSomeEigServer< TypeT >::decompose

(

const RWTriDiagDecomp< TypeT > &

A

)

[virtual]

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

Implements RWSymEigServer< TypeT >.

template<class TypeT>

RWSlice RWSymSomeEigServer< TypeT >::setRange

(

const RWSlice &

range

)

Sets the range of eigenvalues to be computed. Returns the previous range.

template<class TypeT>

TypeT RWSymSomeEigServer< TypeT >::setTolerance

(

TypeT

tolerance

)

Sets the tolerance to which we have to compute the eigenvalues. Returns the previous tolerance.