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Diffstat (limited to 'eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h')
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diff --git a/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h b/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h new file mode 100644 index 0000000..1f3c060 --- /dev/null +++ b/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h @@ -0,0 +1,149 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr> +// +// 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_BASIC_PRECONDITIONERS_H +#define EIGEN_BASIC_PRECONDITIONERS_H + +namespace Eigen { + +/** \ingroup IterativeLinearSolvers_Module + * \brief A preconditioner based on the digonal entries + * + * This class allows to approximately solve for A.x = b problems assuming A is a diagonal matrix. + * In other words, this preconditioner neglects all off diagonal entries and, in Eigen's language, solves for: + * \code + * A.diagonal().asDiagonal() . x = b + * \endcode + * + * \tparam _Scalar the type of the scalar. + * + * This preconditioner is suitable for both selfadjoint and general problems. + * The diagonal entries are pre-inverted and stored into a dense vector. + * + * \note A variant that has yet to be implemented would attempt to preserve the norm of each column. + * + */ +template <typename _Scalar> +class DiagonalPreconditioner +{ + typedef _Scalar Scalar; + typedef Matrix<Scalar,Dynamic,1> Vector; + typedef typename Vector::Index Index; + + public: + // this typedef is only to export the scalar type and compile-time dimensions to solve_retval + typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType; + + DiagonalPreconditioner() : m_isInitialized(false) {} + + template<typename MatType> + DiagonalPreconditioner(const MatType& mat) : m_invdiag(mat.cols()) + { + compute(mat); + } + + Index rows() const { return m_invdiag.size(); } + Index cols() const { return m_invdiag.size(); } + + template<typename MatType> + DiagonalPreconditioner& analyzePattern(const MatType& ) + { + return *this; + } + + template<typename MatType> + DiagonalPreconditioner& factorize(const MatType& mat) + { + m_invdiag.resize(mat.cols()); + for(int j=0; j<mat.outerSize(); ++j) + { + typename MatType::InnerIterator it(mat,j); + while(it && it.index()!=j) ++it; + if(it && it.index()==j && it.value()!=Scalar(0)) + m_invdiag(j) = Scalar(1)/it.value(); + else + m_invdiag(j) = Scalar(1); + } + m_isInitialized = true; + return *this; + } + + template<typename MatType> + DiagonalPreconditioner& compute(const MatType& mat) + { + return factorize(mat); + } + + template<typename Rhs, typename Dest> + void _solve(const Rhs& b, Dest& x) const + { + x = m_invdiag.array() * b.array() ; + } + + template<typename Rhs> inline const internal::solve_retval<DiagonalPreconditioner, Rhs> + solve(const MatrixBase<Rhs>& b) const + { + eigen_assert(m_isInitialized && "DiagonalPreconditioner is not initialized."); + eigen_assert(m_invdiag.size()==b.rows() + && "DiagonalPreconditioner::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval<DiagonalPreconditioner, Rhs>(*this, b.derived()); + } + + protected: + Vector m_invdiag; + bool m_isInitialized; +}; + +namespace internal { + +template<typename _MatrixType, typename Rhs> +struct solve_retval<DiagonalPreconditioner<_MatrixType>, Rhs> + : solve_retval_base<DiagonalPreconditioner<_MatrixType>, Rhs> +{ + typedef DiagonalPreconditioner<_MatrixType> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template<typename Dest> void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +} + +/** \ingroup IterativeLinearSolvers_Module + * \brief A naive preconditioner which approximates any matrix as the identity matrix + * + * \sa class DiagonalPreconditioner + */ +class IdentityPreconditioner +{ + public: + + IdentityPreconditioner() {} + + template<typename MatrixType> + IdentityPreconditioner(const MatrixType& ) {} + + template<typename MatrixType> + IdentityPreconditioner& analyzePattern(const MatrixType& ) { return *this; } + + template<typename MatrixType> + IdentityPreconditioner& factorize(const MatrixType& ) { return *this; } + + template<typename MatrixType> + IdentityPreconditioner& compute(const MatrixType& ) { return *this; } + + template<typename Rhs> + inline const Rhs& solve(const Rhs& b) const { return b; } +}; + +} // end namespace Eigen + +#endif // EIGEN_BASIC_PRECONDITIONERS_H |