// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2009 Gael Guennebaud // // 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 . #ifndef EIGEN_SELFADJOINTMATRIX_H #define EIGEN_SELFADJOINTMATRIX_H /** \class SelfAdjointView * \ingroup Core_Module * * * \brief Expression of a selfadjoint matrix from a triangular part of a dense matrix * * \param MatrixType the type of the dense matrix storing the coefficients * \param TriangularPart can be either \c Lower or \c Upper * * This class is an expression of a sefladjoint matrix from a triangular part of a matrix * with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView() * and most of the time this is the only way that it is used. * * \sa class TriangularBase, MatrixBase::selfAdjointView() */ template struct ei_traits > : ei_traits { typedef typename ei_nested::type MatrixTypeNested; typedef typename ei_unref::type _MatrixTypeNested; typedef MatrixType ExpressionType; enum { Mode = UpLo | SelfAdjoint, Flags = _MatrixTypeNested::Flags & (HereditaryBits) & (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)), // FIXME these flags should be preserved CoeffReadCost = _MatrixTypeNested::CoeffReadCost }; }; template struct SelfadjointProductMatrix; // FIXME could also be called SelfAdjointWrapper to be consistent with DiagonalWrapper ?? template class SelfAdjointView : public TriangularBase > { public: typedef TriangularBase Base; /** \brief The type of coefficients in this matrix */ typedef typename ei_traits::Scalar Scalar; typedef typename MatrixType::Index Index; enum { Mode = ei_traits::Mode }; typedef typename MatrixType::PlainObject PlainObject; inline SelfAdjointView(const MatrixType& matrix) : m_matrix(matrix) { ei_assert(ei_are_flags_consistent::ret); } inline Index rows() const { return m_matrix.rows(); } inline Index cols() const { return m_matrix.cols(); } inline Index outerStride() const { return m_matrix.outerStride(); } inline Index innerStride() const { return m_matrix.innerStride(); } /** \sa MatrixBase::coeff() * \warning the coordinates must fit into the referenced triangular part */ inline Scalar coeff(Index row, Index col) const { Base::check_coordinates_internal(row, col); return m_matrix.coeff(row, col); } /** \sa MatrixBase::coeffRef() * \warning the coordinates must fit into the referenced triangular part */ inline Scalar& coeffRef(Index row, Index col) { Base::check_coordinates_internal(row, col); return m_matrix.const_cast_derived().coeffRef(row, col); } /** \internal */ const MatrixType& _expression() const { return m_matrix; } const MatrixType& nestedExpression() const { return m_matrix; } MatrixType& nestedExpression() { return const_cast(m_matrix); } /** Efficient self-adjoint matrix times vector/matrix product */ template SelfadjointProductMatrix operator*(const MatrixBase& rhs) const { return SelfadjointProductMatrix (m_matrix, rhs.derived()); } /** Efficient vector/matrix times self-adjoint matrix product */ template friend SelfadjointProductMatrix operator*(const MatrixBase& lhs, const SelfAdjointView& rhs) { return SelfadjointProductMatrix (lhs.derived(),rhs.m_matrix); } /** Perform a symmetric rank 2 update of the selfadjoint matrix \c *this: * \f$ this = this + \alpha ( u v^* + v u^*) \f$ * \returns a reference to \c *this * * The vectors \a u and \c v \b must be column vectors, however they can be * a adjoint expression without any overhead. Only the meaningful triangular * part of the matrix is updated, the rest is left unchanged. * * \sa rankUpdate(const MatrixBase&, Scalar) */ template SelfAdjointView& rankUpdate(const MatrixBase& u, const MatrixBase& v, Scalar alpha = Scalar(1)); /** Perform a symmetric rank K update of the selfadjoint matrix \c *this: * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix. * * \returns a reference to \c *this * * Note that to perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply * call this function with u.adjoint(). * * \sa rankUpdate(const MatrixBase&, const MatrixBase&, Scalar) */ template SelfAdjointView& rankUpdate(const MatrixBase& u, Scalar alpha = Scalar(1)); /////////// Cholesky module /////////// const LLT llt() const; const LDLT ldlt() const; /////////// Eigenvalue module /////////// /** Real part of #Scalar */ typedef typename NumTraits::Real RealScalar; /** Return type of eigenvalues() */ typedef Matrix::ColsAtCompileTime, 1> EigenvaluesReturnType; EigenvaluesReturnType eigenvalues() const; RealScalar operatorNorm() const; protected: const typename MatrixType::Nested m_matrix; }; // template // ei_selfadjoint_matrix_product_returntype > // operator*(const MatrixBase& lhs, const SelfAdjointView& rhs) // { // return ei_matrix_selfadjoint_product_returntype >(lhs.derived(),rhs); // } // selfadjoint to dense matrix template struct ei_triangular_assignment_selector { enum { col = (UnrollCount-1) / Derived1::RowsAtCompileTime, row = (UnrollCount-1) % Derived1::RowsAtCompileTime }; inline static void run(Derived1 &dst, const Derived2 &src) { ei_triangular_assignment_selector::run(dst, src); if(row == col) dst.coeffRef(row, col) = ei_real(src.coeff(row, col)); else if(row < col) dst.coeffRef(col, row) = ei_conj(dst.coeffRef(row, col) = src.coeff(row, col)); } }; template struct ei_triangular_assignment_selector { inline static void run(Derived1 &, const Derived2 &) {} }; template struct ei_triangular_assignment_selector { enum { col = (UnrollCount-1) / Derived1::RowsAtCompileTime, row = (UnrollCount-1) % Derived1::RowsAtCompileTime }; inline static void run(Derived1 &dst, const Derived2 &src) { ei_triangular_assignment_selector::run(dst, src); if(row == col) dst.coeffRef(row, col) = ei_real(src.coeff(row, col)); else if(row > col) dst.coeffRef(col, row) = ei_conj(dst.coeffRef(row, col) = src.coeff(row, col)); } }; template struct ei_triangular_assignment_selector { inline static void run(Derived1 &, const Derived2 &) {} }; template struct ei_triangular_assignment_selector { typedef typename Derived1::Index Index; inline static void run(Derived1 &dst, const Derived2 &src) { for(Index j = 0; j < dst.cols(); ++j) { for(Index i = 0; i < j; ++i) { dst.copyCoeff(i, j, src); dst.coeffRef(j,i) = ei_conj(dst.coeff(i,j)); } dst.copyCoeff(j, j, src); } } }; template struct ei_triangular_assignment_selector { inline static void run(Derived1 &dst, const Derived2 &src) { typedef typename Derived1::Index Index; for(Index i = 0; i < dst.rows(); ++i) { for(Index j = 0; j < i; ++j) { dst.copyCoeff(i, j, src); dst.coeffRef(j,i) = ei_conj(dst.coeff(i,j)); } dst.copyCoeff(i, i, src); } } }; /*************************************************************************** * Implementation of MatrixBase methods ***************************************************************************/ template template const SelfAdjointView MatrixBase::selfadjointView() const { return derived(); } template template SelfAdjointView MatrixBase::selfadjointView() { return derived(); } #endif // EIGEN_SELFADJOINTMATRIX_H