GeneralizedSelfAdjointEigenSolver.h

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
#ifndef EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H
#define EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H
 
#include "./Tridiagonalization.h"
 
#include "./InternalHeaderCheck.h"
 
namespace Eigen { 
 
template<typename MatrixType_>
class GeneralizedSelfAdjointEigenSolver : public SelfAdjointEigenSolver<MatrixType_>
{
    typedef SelfAdjointEigenSolver<MatrixType_> Base;
  public:
 
    typedef MatrixType_ MatrixType;
 
    GeneralizedSelfAdjointEigenSolver() : Base() {}
 
    explicit GeneralizedSelfAdjointEigenSolver(Index size)
        : Base(size)
    {}
 
    GeneralizedSelfAdjointEigenSolver(const MatrixType& matA, const MatrixType& matB,
                                      int options = ComputeEigenvectors|Ax_lBx)
      : Base(matA.cols())
    {
      compute(matA, matB, options);
    }
 
    GeneralizedSelfAdjointEigenSolver& compute(const MatrixType& matA, const MatrixType& matB,
                                               int options = ComputeEigenvectors|Ax_lBx);
 
  protected:
 
};
 
 
template<typename MatrixType>
GeneralizedSelfAdjointEigenSolver<MatrixType>& GeneralizedSelfAdjointEigenSolver<MatrixType>::
compute(const MatrixType& matA, const MatrixType& matB, int options)
{
  eigen_assert(matA.cols()==matA.rows() && matB.rows()==matA.rows() && matB.cols()==matB.rows());
  eigen_assert((options&~(EigVecMask|GenEigMask))==0
          && (options&EigVecMask)!=EigVecMask
          && ((options&GenEigMask)==0 || (options&GenEigMask)==Ax_lBx
           || (options&GenEigMask)==ABx_lx || (options&GenEigMask)==BAx_lx)
          && "invalid option parameter");
 
  bool computeEigVecs = ((options&EigVecMask)==0) || ((options&EigVecMask)==ComputeEigenvectors);
 
  // Compute the cholesky decomposition of matB = L L' = U'U
  LLT<MatrixType> cholB(matB);
 
  int type = (options&GenEigMask);
  if(type==0)
    type = Ax_lBx;
 
  if(type==Ax_lBx)
  {
    // compute C = inv(L) A inv(L')
    MatrixType matC = matA.template selfadjointView<Lower>();
    cholB.matrixL().template solveInPlace<OnTheLeft>(matC);
    cholB.matrixU().template solveInPlace<OnTheRight>(matC);
 
    Base::compute(matC, computeEigVecs ? ComputeEigenvectors : EigenvaluesOnly );
 
    // transform back the eigen vectors: evecs = inv(U) * evecs
    if(computeEigVecs)
      cholB.matrixU().solveInPlace(Base::m_eivec);
  }
  else if(type==ABx_lx)
  {
    // compute C = L' A L
    MatrixType matC = matA.template selfadjointView<Lower>();
    matC = matC * cholB.matrixL();
    matC = cholB.matrixU() * matC;
 
    Base::compute(matC, computeEigVecs ? ComputeEigenvectors : EigenvaluesOnly);
 
    // transform back the eigen vectors: evecs = inv(U) * evecs
    if(computeEigVecs)
      cholB.matrixU().solveInPlace(Base::m_eivec);
  }
  else if(type==BAx_lx)
  {
    // compute C = L' A L
    MatrixType matC = matA.template selfadjointView<Lower>();
    matC = matC * cholB.matrixL();
    matC = cholB.matrixU() * matC;
 
    Base::compute(matC, computeEigVecs ? ComputeEigenvectors : EigenvaluesOnly);
 
    // transform back the eigen vectors: evecs = L * evecs
    if(computeEigVecs)
      Base::m_eivec = cholB.matrixL() * Base::m_eivec;
  }
 
  return *this;
}
 
} // end namespace Eigen
 
#endif // EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H