From f0238cfb6997c4acfc2bd200de7295f3fa36968f Mon Sep 17 00:00:00 2001 From: Stanislaw Halik Date: Sun, 3 Mar 2019 21:09:10 +0100 Subject: don't index Eigen --- .../IterativeLinearSolvers/IterativeSolverBase.h | 394 --------------------- 1 file changed, 394 deletions(-) delete mode 100644 eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h (limited to 'eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h') diff --git a/eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h b/eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h deleted file mode 100644 index 7c2326e..0000000 --- a/eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h +++ /dev/null @@ -1,394 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2011-2014 Gael Guennebaud -// -// 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_ITERATIVE_SOLVER_BASE_H -#define EIGEN_ITERATIVE_SOLVER_BASE_H - -namespace Eigen { - -namespace internal { - -template -struct is_ref_compatible_impl -{ -private: - template - struct any_conversion - { - template any_conversion(const volatile T&); - template any_conversion(T&); - }; - struct yes {int a[1];}; - struct no {int a[2];}; - - template - static yes test(const Ref&, int); - template - static no test(any_conversion, ...); - -public: - static MatrixType ms_from; - enum { value = sizeof(test(ms_from, 0))==sizeof(yes) }; -}; - -template -struct is_ref_compatible -{ - enum { value = is_ref_compatible_impl::type>::value }; -}; - -template::value> -class generic_matrix_wrapper; - -// We have an explicit matrix at hand, compatible with Ref<> -template -class generic_matrix_wrapper -{ -public: - typedef Ref ActualMatrixType; - template struct ConstSelfAdjointViewReturnType { - typedef typename ActualMatrixType::template ConstSelfAdjointViewReturnType::Type Type; - }; - - enum { - MatrixFree = false - }; - - generic_matrix_wrapper() - : m_dummy(0,0), m_matrix(m_dummy) - {} - - template - generic_matrix_wrapper(const InputType &mat) - : m_matrix(mat) - {} - - const ActualMatrixType& matrix() const - { - return m_matrix; - } - - template - void grab(const EigenBase &mat) - { - m_matrix.~Ref(); - ::new (&m_matrix) Ref(mat.derived()); - } - - void grab(const Ref &mat) - { - if(&(mat.derived()) != &m_matrix) - { - m_matrix.~Ref(); - ::new (&m_matrix) Ref(mat); - } - } - -protected: - MatrixType m_dummy; // used to default initialize the Ref<> object - ActualMatrixType m_matrix; -}; - -// MatrixType is not compatible with Ref<> -> matrix-free wrapper -template -class generic_matrix_wrapper -{ -public: - typedef MatrixType ActualMatrixType; - template struct ConstSelfAdjointViewReturnType - { - typedef ActualMatrixType Type; - }; - - enum { - MatrixFree = true - }; - - generic_matrix_wrapper() - : mp_matrix(0) - {} - - generic_matrix_wrapper(const MatrixType &mat) - : mp_matrix(&mat) - {} - - const ActualMatrixType& matrix() const - { - return *mp_matrix; - } - - void grab(const MatrixType &mat) - { - mp_matrix = &mat; - } - -protected: - const ActualMatrixType *mp_matrix; -}; - -} - -/** \ingroup IterativeLinearSolvers_Module - * \brief Base class for linear iterative solvers - * - * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner - */ -template< typename Derived> -class IterativeSolverBase : public SparseSolverBase -{ -protected: - typedef SparseSolverBase Base; - using Base::m_isInitialized; - -public: - typedef typename internal::traits::MatrixType MatrixType; - typedef typename internal::traits::Preconditioner Preconditioner; - typedef typename MatrixType::Scalar Scalar; - typedef typename MatrixType::StorageIndex StorageIndex; - typedef typename MatrixType::RealScalar RealScalar; - - enum { - ColsAtCompileTime = MatrixType::ColsAtCompileTime, - MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime - }; - -public: - - using Base::derived; - - /** Default constructor. */ - IterativeSolverBase() - { - init(); - } - - /** Initialize the solver with matrix \a A for further \c Ax=b solving. - * - * This constructor is a shortcut for the default constructor followed - * by a call to compute(). - * - * \warning this class stores a reference to the matrix A as well as some - * precomputed values that depend on it. Therefore, if \a A is changed - * this class becomes invalid. Call compute() to update it with the new - * matrix A, or modify a copy of A. - */ - template - explicit IterativeSolverBase(const EigenBase& A) - : m_matrixWrapper(A.derived()) - { - init(); - compute(matrix()); - } - - ~IterativeSolverBase() {} - - /** Initializes the iterative solver for the sparsity pattern of the matrix \a A for further solving \c Ax=b problems. - * - * Currently, this function mostly calls analyzePattern on the preconditioner. In the future - * we might, for instance, implement column reordering for faster matrix vector products. - */ - template - Derived& analyzePattern(const EigenBase& A) - { - grab(A.derived()); - m_preconditioner.analyzePattern(matrix()); - m_isInitialized = true; - m_analysisIsOk = true; - m_info = m_preconditioner.info(); - return derived(); - } - - /** Initializes the iterative solver with the numerical values of the matrix \a A for further solving \c Ax=b problems. - * - * Currently, this function mostly calls factorize on the preconditioner. - * - * \warning this class stores a reference to the matrix A as well as some - * precomputed values that depend on it. Therefore, if \a A is changed - * this class becomes invalid. Call compute() to update it with the new - * matrix A, or modify a copy of A. - */ - template - Derived& factorize(const EigenBase& A) - { - eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); - grab(A.derived()); - m_preconditioner.factorize(matrix()); - m_factorizationIsOk = true; - m_info = m_preconditioner.info(); - return derived(); - } - - /** Initializes the iterative solver with the matrix \a A for further solving \c Ax=b problems. - * - * Currently, this function mostly initializes/computes the preconditioner. In the future - * we might, for instance, implement column reordering for faster matrix vector products. - * - * \warning this class stores a reference to the matrix A as well as some - * precomputed values that depend on it. Therefore, if \a A is changed - * this class becomes invalid. Call compute() to update it with the new - * matrix A, or modify a copy of A. - */ - template - Derived& compute(const EigenBase& A) - { - grab(A.derived()); - m_preconditioner.compute(matrix()); - m_isInitialized = true; - m_analysisIsOk = true; - m_factorizationIsOk = true; - m_info = m_preconditioner.info(); - return derived(); - } - - /** \internal */ - Index rows() const { return matrix().rows(); } - - /** \internal */ - Index cols() const { return matrix().cols(); } - - /** \returns the tolerance threshold used by the stopping criteria. - * \sa setTolerance() - */ - RealScalar tolerance() const { return m_tolerance; } - - /** Sets the tolerance threshold used by the stopping criteria. - * - * This value is used as an upper bound to the relative residual error: |Ax-b|/|b|. - * The default value is the machine precision given by NumTraits::epsilon() - */ - Derived& setTolerance(const RealScalar& tolerance) - { - m_tolerance = tolerance; - return derived(); - } - - /** \returns a read-write reference to the preconditioner for custom configuration. */ - Preconditioner& preconditioner() { return m_preconditioner; } - - /** \returns a read-only reference to the preconditioner. */ - const Preconditioner& preconditioner() const { return m_preconditioner; } - - /** \returns the max number of iterations. - * It is either the value setted by setMaxIterations or, by default, - * twice the number of columns of the matrix. - */ - Index maxIterations() const - { - return (m_maxIterations<0) ? 2*matrix().cols() : m_maxIterations; - } - - /** Sets the max number of iterations. - * Default is twice the number of columns of the matrix. - */ - Derived& setMaxIterations(Index maxIters) - { - m_maxIterations = maxIters; - return derived(); - } - - /** \returns the number of iterations performed during the last solve */ - Index iterations() const - { - eigen_assert(m_isInitialized && "ConjugateGradient is not initialized."); - return m_iterations; - } - - /** \returns the tolerance error reached during the last solve. - * It is a close approximation of the true relative residual error |Ax-b|/|b|. - */ - RealScalar error() const - { - eigen_assert(m_isInitialized && "ConjugateGradient is not initialized."); - return m_error; - } - - /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A - * and \a x0 as an initial solution. - * - * \sa solve(), compute() - */ - template - inline const SolveWithGuess - solveWithGuess(const MatrixBase& b, const Guess& x0) const - { - eigen_assert(m_isInitialized && "Solver is not initialized."); - eigen_assert(derived().rows()==b.rows() && "solve(): invalid number of rows of the right hand side matrix b"); - return SolveWithGuess(derived(), b.derived(), x0); - } - - /** \returns Success if the iterations converged, and NoConvergence otherwise. */ - ComputationInfo info() const - { - eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized."); - return m_info; - } - - /** \internal */ - template - void _solve_impl(const Rhs& b, SparseMatrixBase &aDest) const - { - eigen_assert(rows()==b.rows()); - - Index rhsCols = b.cols(); - Index size = b.rows(); - DestDerived& dest(aDest.derived()); - typedef typename DestDerived::Scalar DestScalar; - Eigen::Matrix tb(size); - Eigen::Matrix tx(cols()); - // We do not directly fill dest because sparse expressions have to be free of aliasing issue. - // For non square least-square problems, b and dest might not have the same size whereas they might alias each-other. - typename DestDerived::PlainObject tmp(cols(),rhsCols); - for(Index k=0; k::epsilon(); - } - - typedef internal::generic_matrix_wrapper MatrixWrapper; - typedef typename MatrixWrapper::ActualMatrixType ActualMatrixType; - - const ActualMatrixType& matrix() const - { - return m_matrixWrapper.matrix(); - } - - template - void grab(const InputType &A) - { - m_matrixWrapper.grab(A); - } - - MatrixWrapper m_matrixWrapper; - Preconditioner m_preconditioner; - - Index m_maxIterations; - RealScalar m_tolerance; - - mutable RealScalar m_error; - mutable Index m_iterations; - mutable ComputationInfo m_info; - mutable bool m_analysisIsOk, m_factorizationIsOk; -}; - -} // end namespace Eigen - -#endif // EIGEN_ITERATIVE_SOLVER_BASE_H -- cgit v1.2.3