279 lines
8.6 KiB
C++
279 lines
8.6 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Claire Maurice
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// Copyright (C) 2009 Gael Guennebaud <g.gael@free.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_COMPLEX_SCHUR_H
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#define EIGEN_COMPLEX_SCHUR_H
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/** \eigenvalues_module \ingroup Eigenvalues_Module
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* \nonstableyet
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*
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* \class ComplexSchur
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*
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* \brief Performs a complex Schur decomposition of a real or complex square matrix
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*
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* Given a real or complex square matrix A, this class computes the Schur decomposition:
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* \f$ A = U T U^*\f$ where U is a unitary complex matrix, and T is a complex upper
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* triangular matrix.
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*
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* The diagonal of the matrix T corresponds to the eigenvalues of the matrix A.
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*
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* \sa class RealSchur, class EigenSolver
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*/
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template<typename _MatrixType> class ComplexSchur
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{
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public:
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typedef _MatrixType MatrixType;
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enum {
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RowsAtCompileTime = MatrixType::RowsAtCompileTime,
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ColsAtCompileTime = MatrixType::ColsAtCompileTime,
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Options = MatrixType::Options,
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MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
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MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
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};
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typedef typename MatrixType::Scalar Scalar;
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typedef typename NumTraits<Scalar>::Real RealScalar;
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typedef std::complex<RealScalar> Complex;
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typedef Matrix<Complex, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime, MaxColsAtCompileTime> ComplexMatrixType;
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enum {
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Size = MatrixType::RowsAtCompileTime
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};
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/** \brief Default Constructor.
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*
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* The default constructor is useful in cases in which the user intends to
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* perform decompositions via ComplexSchur::compute().
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*/
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ComplexSchur(int size = Size==Dynamic ? 0 : Size)
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: m_matT(size,size), m_matU(size,size), m_isInitialized(false), m_matUisUptodate(false)
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{}
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/** Constructor computing the Schur decomposition of the matrix \a matrix.
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* If \a skipU is true, then the matrix U is not computed. */
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ComplexSchur(const MatrixType& matrix, bool skipU = false)
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: m_matT(matrix.rows(),matrix.cols()),
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m_matU(matrix.rows(),matrix.cols()),
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m_isInitialized(false),
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m_matUisUptodate(false)
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{
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compute(matrix, skipU);
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}
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/** \returns a const reference to the matrix U of the respective Schur decomposition. */
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const ComplexMatrixType& matrixU() const
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{
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ei_assert(m_isInitialized && "ComplexSchur is not initialized.");
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ei_assert(m_matUisUptodate && "The matrix U has not been computed during the ComplexSchur decomposition.");
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return m_matU;
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}
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/** \returns a const reference to the matrix T of the respective Schur decomposition.
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* Note that this function returns a plain square matrix. If you want to reference
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* only the upper triangular part, use:
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* \code schur.matrixT().triangularView<Upper>() \endcode. */
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const ComplexMatrixType& matrixT() const
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{
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ei_assert(m_isInitialized && "ComplexShur is not initialized.");
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return m_matT;
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}
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/** Computes the Schur decomposition of the matrix \a matrix.
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* If \a skipU is true, then the matrix U is not computed. */
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void compute(const MatrixType& matrix, bool skipU = false);
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protected:
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ComplexMatrixType m_matT, m_matU;
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bool m_isInitialized;
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bool m_matUisUptodate;
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};
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/** Computes the principal value of the square root of the complex \a z. */
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template<typename RealScalar>
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std::complex<RealScalar> ei_sqrt(const std::complex<RealScalar> &z)
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{
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RealScalar t, tre, tim;
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t = ei_abs(z);
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if (ei_abs(ei_real(z)) <= ei_abs(ei_imag(z)))
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{
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// No cancellation in these formulas
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tre = ei_sqrt(0.5*(t + ei_real(z)));
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tim = ei_sqrt(0.5*(t - ei_real(z)));
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}
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else
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{
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// Stable computation of the above formulas
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if (z.real() > 0)
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{
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tre = t + z.real();
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tim = ei_abs(ei_imag(z))*ei_sqrt(0.5/tre);
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tre = ei_sqrt(0.5*tre);
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}
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else
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{
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tim = t - z.real();
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tre = ei_abs(ei_imag(z))*ei_sqrt(0.5/tim);
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tim = ei_sqrt(0.5*tim);
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}
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}
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if(z.imag() < 0)
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tim = -tim;
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return (std::complex<RealScalar>(tre,tim));
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}
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template<typename MatrixType>
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void ComplexSchur<MatrixType>::compute(const MatrixType& matrix, bool skipU)
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{
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// this code is inspired from Jampack
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m_matUisUptodate = false;
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assert(matrix.cols() == matrix.rows());
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int n = matrix.cols();
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// Reduce to Hessenberg form
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// TODO skip Q if skipU = true
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HessenbergDecomposition<MatrixType> hess(matrix);
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m_matT = hess.matrixH();
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if(!skipU) m_matU = hess.matrixQ();
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// Reduce the Hessenberg matrix m_matT to triangular form by QR iteration.
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// The matrix m_matT is divided in three parts.
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// Rows 0,...,il-1 are decoupled from the rest because m_matT(il,il-1) is zero.
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// Rows il,...,iu is the part we are working on (the active submatrix).
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// Rows iu+1,...,end are already brought in triangular form.
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int iu = m_matT.cols() - 1;
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int il;
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RealScalar d,sd,sf;
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Complex c,b,disc,r1,r2,kappa;
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RealScalar eps = NumTraits<RealScalar>::epsilon();
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int iter = 0;
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while(true)
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{
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// find iu, the bottom row of the active submatrix
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while(iu > 0)
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{
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d = ei_norm1(m_matT.coeff(iu,iu)) + ei_norm1(m_matT.coeff(iu-1,iu-1));
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sd = ei_norm1(m_matT.coeff(iu,iu-1));
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if(!ei_isMuchSmallerThan(sd,d,eps))
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break;
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m_matT.coeffRef(iu,iu-1) = Complex(0);
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iter = 0;
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--iu;
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}
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if(iu==0) break;
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iter++;
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if(iter >= 30)
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{
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// FIXME : what to do when iter==MAXITER ??
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//std::cerr << "MAXITER" << std::endl;
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return;
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}
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// find il, the top row of the active submatrix
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il = iu-1;
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while(il > 0)
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{
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// check if the current 2x2 block on the diagonal is upper triangular
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d = ei_norm1(m_matT.coeff(il,il)) + ei_norm1(m_matT.coeff(il-1,il-1));
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sd = ei_norm1(m_matT.coeff(il,il-1));
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if(ei_isMuchSmallerThan(sd,d,eps))
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break;
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--il;
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}
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if( il != 0 ) m_matT.coeffRef(il,il-1) = Complex(0);
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// compute the shift kappa as one of the eigenvalues of the 2x2
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// diagonal block on the bottom of the active submatrix
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Matrix<Scalar,2,2> t = m_matT.template block<2,2>(iu-1,iu-1);
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sf = t.cwiseAbs().sum();
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t /= sf; // the normalization by sf is to avoid under/overflow
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b = t.coeff(0,1) * t.coeff(1,0);
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c = t.coeff(0,0) - t.coeff(1,1);
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disc = ei_sqrt(c*c + RealScalar(4)*b);
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c = t.coeff(0,0) * t.coeff(1,1) - b;
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b = t.coeff(0,0) + t.coeff(1,1);
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r1 = (b+disc)/RealScalar(2);
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r2 = (b-disc)/RealScalar(2);
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if(ei_norm1(r1) > ei_norm1(r2))
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r2 = c/r1;
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else
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r1 = c/r2;
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if(ei_norm1(r1-t.coeff(1,1)) < ei_norm1(r2-t.coeff(1,1)))
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kappa = sf * r1;
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else
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kappa = sf * r2;
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if (iter == 10 || iter == 20)
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{
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// exceptional shift, taken from http://www.netlib.org/eispack/comqr.f
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kappa = ei_abs(ei_real(m_matT.coeff(iu,iu-1))) + ei_abs(ei_real(m_matT.coeff(iu-1,iu-2)));
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}
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// perform the QR step using Givens rotations
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PlanarRotation<Complex> rot;
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rot.makeGivens(m_matT.coeff(il,il) - kappa, m_matT.coeff(il+1,il));
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for(int i=il ; i<iu ; i++)
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{
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m_matT.block(0,i,n,n-i).applyOnTheLeft(i, i+1, rot.adjoint());
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m_matT.block(0,0,std::min(i+2,iu)+1,n).applyOnTheRight(i, i+1, rot);
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if(!skipU) m_matU.applyOnTheRight(i, i+1, rot);
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if(i != iu-1)
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{
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int i1 = i+1;
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int i2 = i+2;
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rot.makeGivens(m_matT.coeffRef(i1,i), m_matT.coeffRef(i2,i), &m_matT.coeffRef(i1,i));
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m_matT.coeffRef(i2,i) = Complex(0);
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}
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}
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}
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m_isInitialized = true;
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m_matUisUptodate = !skipU;
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}
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#endif // EIGEN_COMPLEX_SCHUR_H
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