RWSymPDQREigServer<T>, RWHermPDQREigServer<T>

Module:  Linear Algebra   Group:  Symmetric Eigenvalue Decomposition classes

Does not inherit

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• Synopsis
• Description
• Example
• Public Constructor
• Public Member Functions
• Public Member Operators

Members

RWHermPDQREigServer<DComplex>::computeEigenVectors() RWHermPDQREigServer<DComplex>::decompose ()

RWHermPDQREigServer<DComplex>::operator() () RWHermPDQREigServer()

RWSymPDQREigServer<T>::computeEigenVectors() RWSymPDQREigServer<T>::decompose ()

RWSymPDQREigServer<T>::operator() () RWSymPDQREigServer()

#include <rw/lapack/seigsrv.h>

RWSymPDQREigServer<double> server;
RWSymEigDecomp<double> eig = server(A);     // A is a
                              // RWSymBandMat<double>

#include <rw/lapack/heigsrv.h>

RWHermPDQREigServer<double> server;
RWHermEigDecomp<double> eig = server(A);    // A is a
                           // RWHermBandMat<DComplex>

The classes RWSymPDQREigServer<T> and RWHermPDQREigServer<T> are the servers for the positive definite QR method of computing eigenvalues. These servers apply only to matrices that you know are positive definite. Trying to use them on nonpositive definite matrices results in a decomposition with the incomplete flag set; you can test for this in the class RWSymEigDecomp<T>. Use of these servers with positive definite matrices can result in much more accurate eigenvalues and eigenvectors.

#include <iostream>
#include <rw/lapack/seigsrv.h>

int main()
{
    RWSymMat<double> A;               // input a matrix
    std::cin >> A;

    RWSymPDQREigServer<double> server;   // configure a
                                               server
    server.computeEigenVectors(false);   // turn off
                                           eigenvectors
    RWSymEigDecomp<double> eig = server(A);
      return 0;
}

RWSymPDQREigServer(bool computeVecs=true);
RWHermPDQREigServer(bool computeVecs=true);

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

void
RWSymPDQREigServer<T>::computeEigenVectors(bool);
void
RWHermPDQREigServer<DComplex>::computeEigenVectors(bool);

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

bool
RWSymPDQREigServer<T>::computeEigenVectors() const;
bool
RWHermPDQREigServer<DComplex>::computeEigenVectors()
       const;

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

RWSymEigDecomp<T>
RWSymPDQREigServer<T>::decompose
      (const RWSymTriDiagDecomp<T>& A) const
RWSymEigDecomp<double>
RWHermPDQREigServer<DComplex>::decompose
      (const RWSymTriDiagDecomp<double>& A) const

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

RWSymEigDecomp<T>   RWSymPDQREigServer<T>::operator()
                    (const RWSymMat<T>& A) const;
RWSymEigDecomp<T>   RWSymPDQREigServer<T>::operator()
                    (const RWSymBandMat<T>& A) const;
RWHermEigDecomp<DComplex>
            RWHermPDQREigServer<DComplex>::operator()
             (const RWHermMat<DComplex>& A) const;
RWHermEigDecomp<DComplex>
            RWHermPDQREigServer<DComplex>::operator()
            (const RWHermBandMat<DComplex>& A) const;

Computes a symmetric eigenvalue decomposition. The matrix you pass in must be positive definite.

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