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154 lines
5.9 KiB
C++
154 lines
5.9 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) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
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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_BIDIAGONALIZATION_H
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#define EIGEN_BIDIAGONALIZATION_H
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template<typename _MatrixType> class UpperBidiagonalization
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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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ColsAtCompileTimeMinusOne = ei_decrement_size<ColsAtCompileTime>::ret
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};
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typedef typename MatrixType::Scalar Scalar;
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typedef typename MatrixType::RealScalar RealScalar;
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typedef typename MatrixType::Index Index;
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typedef Matrix<Scalar, 1, ColsAtCompileTime> RowVectorType;
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typedef Matrix<Scalar, RowsAtCompileTime, 1> ColVectorType;
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typedef BandMatrix<RealScalar, ColsAtCompileTime, ColsAtCompileTime, 1, 0> BidiagonalType;
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typedef Matrix<Scalar, ColsAtCompileTime, 1> DiagVectorType;
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typedef Matrix<Scalar, ColsAtCompileTimeMinusOne, 1> SuperDiagVectorType;
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typedef HouseholderSequence<
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MatrixType,
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CwiseUnaryOp<ei_scalar_conjugate_op<Scalar>, Diagonal<MatrixType,0> >
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> HouseholderUSequenceType;
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typedef HouseholderSequence<
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MatrixType,
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Diagonal<MatrixType,1>,
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OnTheRight
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> HouseholderVSequenceType;
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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 Bidiagonalization::compute(const MatrixType&).
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*/
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UpperBidiagonalization() : m_householder(), m_bidiagonal(), m_isInitialized(false) {}
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UpperBidiagonalization(const MatrixType& matrix)
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: m_householder(matrix.rows(), matrix.cols()),
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m_bidiagonal(matrix.cols(), matrix.cols()),
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m_isInitialized(false)
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{
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compute(matrix);
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}
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UpperBidiagonalization& compute(const MatrixType& matrix);
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const MatrixType& householder() const { return m_householder; }
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const BidiagonalType& bidiagonal() const { return m_bidiagonal; }
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HouseholderUSequenceType householderU() const
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{
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ei_assert(m_isInitialized && "UpperBidiagonalization is not initialized.");
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return HouseholderUSequenceType(m_householder, m_householder.diagonal().conjugate());
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}
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HouseholderVSequenceType householderV() // const here gives nasty errors and i'm lazy
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{
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ei_assert(m_isInitialized && "UpperBidiagonalization is not initialized.");
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return HouseholderVSequenceType(m_householder, m_householder.template diagonal<1>(),
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false, m_householder.cols()-1, 1);
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}
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protected:
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MatrixType m_householder;
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BidiagonalType m_bidiagonal;
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bool m_isInitialized;
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};
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template<typename _MatrixType>
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UpperBidiagonalization<_MatrixType>& UpperBidiagonalization<_MatrixType>::compute(const _MatrixType& matrix)
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{
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Index rows = matrix.rows();
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Index cols = matrix.cols();
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ei_assert(rows >= cols && "UpperBidiagonalization is only for matrices satisfying rows>=cols.");
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m_householder = matrix;
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ColVectorType temp(rows);
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for (Index k = 0; /* breaks at k==cols-1 below */ ; ++k)
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{
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Index remainingRows = rows - k;
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Index remainingCols = cols - k - 1;
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// construct left householder transform in-place in m_householder
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m_householder.col(k).tail(remainingRows)
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.makeHouseholderInPlace(m_householder.coeffRef(k,k),
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m_bidiagonal.template diagonal<0>().coeffRef(k));
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// apply householder transform to remaining part of m_householder on the left
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m_householder.bottomRightCorner(remainingRows, remainingCols)
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.applyHouseholderOnTheLeft(m_householder.col(k).tail(remainingRows-1),
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m_householder.coeff(k,k),
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temp.data());
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if(k == cols-1) break;
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// construct right householder transform in-place in m_householder
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m_householder.row(k).tail(remainingCols)
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.makeHouseholderInPlace(m_householder.coeffRef(k,k+1),
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m_bidiagonal.template diagonal<1>().coeffRef(k));
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// apply householder transform to remaining part of m_householder on the left
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m_householder.bottomRightCorner(remainingRows-1, remainingCols)
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.applyHouseholderOnTheRight(m_householder.row(k).tail(remainingCols-1).transpose(),
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m_householder.coeff(k,k+1),
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temp.data());
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}
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m_isInitialized = true;
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return *this;
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}
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#if 0
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/** \return the Householder QR decomposition of \c *this.
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*
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* \sa class Bidiagonalization
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*/
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template<typename Derived>
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const UpperBidiagonalization<typename MatrixBase<Derived>::PlainObject>
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MatrixBase<Derived>::bidiagonalization() const
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{
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return UpperBidiagonalization<PlainObject>(eval());
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}
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#endif
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#endif // EIGEN_BIDIAGONALIZATION_H
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