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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Claire Maurice
// Copyright (C) 2009 Gael Guennebaud <g.gael@free.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_COMPLEX_SCHUR_H
#define EIGEN_COMPLEX_SCHUR_H
/** \eigenvalues_module \ingroup Eigenvalues_Module
* \nonstableyet
*
* \class ComplexShur
*
* \brief Performs a complex Shur decomposition of a real or complex square matrix
*
*/
template<typename _MatrixType> class ComplexSchur
{
public:
typedef _MatrixType MatrixType;
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef std::complex<RealScalar> Complex;
typedef Matrix<Complex, MatrixType::RowsAtCompileTime,MatrixType::ColsAtCompileTime> ComplexMatrixType;
/**
* \brief Default Constructor.
*
* The default constructor is useful in cases in which the user intends to
* perform decompositions via ComplexSchur::compute(const MatrixType&).
*/
ComplexSchur() : m_matT(), m_matU(), m_isInitialized(false)
{}
ComplexSchur(const MatrixType& matrix)
: m_matT(matrix.rows(),matrix.cols()),
m_matU(matrix.rows(),matrix.cols()),
m_isInitialized(false)
{
compute(matrix);
}
ComplexMatrixType matrixU() const
{
ei_assert(m_isInitialized && "ComplexSchur is not initialized.");
return m_matU;
}
ComplexMatrixType matrixT() const
{
ei_assert(m_isInitialized && "ComplexShur is not initialized.");
return m_matT;
}
void compute(const MatrixType& matrix);
protected:
ComplexMatrixType m_matT, m_matU;
bool m_isInitialized;
};
/** Computes the principal value of the square root of the complex \a z. */
template<typename RealScalar>
std::complex<RealScalar> ei_sqrt(const std::complex<RealScalar> &z)
{
RealScalar t, tre, tim;
t = ei_abs(z);
if (ei_abs(ei_real(z)) <= ei_abs(ei_imag(z)))
{
// No cancellation in these formulas
tre = ei_sqrt(0.5*(t + ei_real(z)));
tim = ei_sqrt(0.5*(t - ei_real(z)));
}
else
{
// Stable computation of the above formulas
if (z.real() > 0)
{
tre = t + z.real();
tim = ei_abs(ei_imag(z))*ei_sqrt(0.5/tre);
tre = ei_sqrt(0.5*tre);
}
else
{
tim = t - z.real();
tre = ei_abs(ei_imag(z))*ei_sqrt(0.5/tim);
tim = ei_sqrt(0.5*tim);
}
}
if(z.imag() < 0)
tim = -tim;
return (std::complex<RealScalar>(tre,tim));
}
template<typename MatrixType>
void ComplexSchur<MatrixType>::compute(const MatrixType& matrix)
{
// this code is inspired from Jampack
assert(matrix.cols() == matrix.rows());
int n = matrix.cols();
// Reduce to Hessenberg form
HessenbergDecomposition<MatrixType> hess(matrix);
m_matT = hess.matrixH();
m_matU = hess.matrixQ();
int iu = m_matT.cols() - 1;
int il;
RealScalar d,sd,sf;
Complex c,b,disc,r1,r2,kappa;
RealScalar eps = epsilon<RealScalar>();
int iter = 0;
while(true)
{
//locate the range in which to iterate
while(iu > 0)
{
d = ei_norm1(m_matT.coeffRef(iu,iu)) + ei_norm1(m_matT.coeffRef(iu-1,iu-1));
sd = ei_norm1(m_matT.coeffRef(iu,iu-1));
if(sd >= eps * d) break; // FIXME : precision criterion ??
m_matT.coeffRef(iu,iu-1) = Complex(0);
iter = 0;
--iu;
}
if(iu==0) break;
iter++;
if(iter >= 30)
{
// FIXME : what to do when iter==MAXITER ??
std::cerr << "MAXITER" << std::endl;
return;
}
il = iu-1;
while( il > 0 )
{
// check if the current 2x2 block on the diagonal is upper triangular
d = ei_norm1(m_matT.coeffRef(il,il)) + ei_norm1(m_matT.coeffRef(il-1,il-1));
sd = ei_norm1(m_matT.coeffRef(il,il-1));
if(sd < eps * d) break; // FIXME : precision criterion ??
--il;
}
if( il != 0 ) m_matT.coeffRef(il,il-1) = Complex(0);
// compute the shift (the normalization by sf is to avoid under/overflow)
Matrix<Scalar,2,2> t = m_matT.template block<2,2>(iu-1,iu-1);
sf = t.cwise().abs().sum();
t /= sf;
c = t.determinant();
b = t.diagonal().sum();
disc = ei_sqrt(b*b - RealScalar(4)*c);
r1 = (b+disc)/RealScalar(2);
r2 = (b-disc)/RealScalar(2);
if(ei_norm1(r1) > ei_norm1(r2))
r2 = c/r1;
else
r1 = c/r2;
if(ei_norm1(r1-t.coeff(1,1)) < ei_norm1(r2-t.coeff(1,1)))
kappa = sf * r1;
else
kappa = sf * r2;
// perform the QR step using Givens rotations
PlanarRotation<Complex> rot;
rot.makeGivens(m_matT.coeff(il,il) - kappa, m_matT.coeff(il+1,il));
for(int i=il ; i<iu ; i++)
{
m_matT.block(0,i,n,n-i).applyOnTheLeft(i, i+1, rot.adjoint());
m_matT.block(0,0,std::min(i+2,iu)+1,n).applyOnTheRight(i, i+1, rot);
m_matU.applyOnTheRight(i, i+1, rot);
if(i != iu-1)
{
int i1 = i+1;
int i2 = i+2;
rot.makeGivens(m_matT.coeffRef(i1,i), m_matT.coeffRef(i2,i), &m_matT.coeffRef(i1,i));
m_matT.coeffRef(i2,i) = Complex(0);
}
}
}
// FIXME : is it necessary ?
/*
for(int i=0 ; i<n ; i++)
for(int j=0 ; j<n ; j++)
{
if(ei_abs(ei_real(m_matT.coeff(i,j))) < eps)
ei_real_ref(m_matT.coeffRef(i,j)) = 0;
if(ei_imag(ei_abs(m_matT.coeff(i,j))) < eps)
ei_imag_ref(m_matT.coeffRef(i,j)) = 0;
}
*/
m_isInitialized = true;
}
#endif // EIGEN_COMPLEX_SCHUR_H
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