don't index Eigen

1 files changed, 0 insertions, 394 deletions

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 <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_ITERATIVE_SOLVER_BASE_H
-#define EIGEN_ITERATIVE_SOLVER_BASE_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename MatrixType>
-struct is_ref_compatible_impl
-{
-private:
-  template <typename T0>
-  struct any_conversion
-  {
-    template <typename T> any_conversion(const volatile T&);
-    template <typename T> any_conversion(T&);
-  };
-  struct yes {int a[1];};
-  struct no  {int a[2];};
-
-  template<typename T>
-  static yes test(const Ref<const T>&, int);
-  template<typename T>
-  static no  test(any_conversion<T>, ...);
-
-public:
-  static MatrixType ms_from;
-  enum { value = sizeof(test<MatrixType>(ms_from, 0))==sizeof(yes) };
-};
-
-template<typename MatrixType>
-struct is_ref_compatible
-{
-  enum { value = is_ref_compatible_impl<typename remove_all<MatrixType>::type>::value };
-};
-
-template<typename MatrixType, bool MatrixFree = !internal::is_ref_compatible<MatrixType>::value>
-class generic_matrix_wrapper;
-
-// We have an explicit matrix at hand, compatible with Ref<>
-template<typename MatrixType>
-class generic_matrix_wrapper<MatrixType,false>
-{
-public:
-  typedef Ref<const MatrixType> ActualMatrixType;
-  template<int UpLo> struct ConstSelfAdjointViewReturnType {
-    typedef typename ActualMatrixType::template ConstSelfAdjointViewReturnType<UpLo>::Type Type;
-  };
-
-  enum {
-    MatrixFree = false
-  };
-
-  generic_matrix_wrapper()
-    : m_dummy(0,0), m_matrix(m_dummy)
-  {}
-
-  template<typename InputType>
-  generic_matrix_wrapper(const InputType &mat)
-    : m_matrix(mat)
-  {}
-
-  const ActualMatrixType& matrix() const
-  {
-    return m_matrix;
-  }
-
-  template<typename MatrixDerived>
-  void grab(const EigenBase<MatrixDerived> &mat)
-  {
-    m_matrix.~Ref<const MatrixType>();
-    ::new (&m_matrix) Ref<const MatrixType>(mat.derived());
-  }
-
-  void grab(const Ref<const MatrixType> &mat)
-  {
-    if(&(mat.derived()) != &m_matrix)
-    {
-      m_matrix.~Ref<const MatrixType>();
-      ::new (&m_matrix) Ref<const MatrixType>(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<typename MatrixType>
-class generic_matrix_wrapper<MatrixType,true>
-{
-public:
-  typedef MatrixType ActualMatrixType;
-  template<int UpLo> 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<Derived>
-{
-protected:
-  typedef SparseSolverBase<Derived> Base;
-  using Base::m_isInitialized;
-  
-public:
-  typedef typename internal::traits<Derived>::MatrixType MatrixType;
-  typedef typename internal::traits<Derived>::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<typename MatrixDerived>
-  explicit IterativeSolverBase(const EigenBase<MatrixDerived>& 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<typename MatrixDerived>
-  Derived& analyzePattern(const EigenBase<MatrixDerived>& 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<typename MatrixDerived>
-  Derived& factorize(const EigenBase<MatrixDerived>& 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<typename MatrixDerived>
-  Derived& compute(const EigenBase<MatrixDerived>& 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<Scalar>::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<typename Rhs,typename Guess>
-  inline const SolveWithGuess<Derived, Rhs, Guess>
-  solveWithGuess(const MatrixBase<Rhs>& 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, Rhs, Guess>(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<typename Rhs, typename DestDerived>
-  void _solve_impl(const Rhs& b, SparseMatrixBase<DestDerived> &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<DestScalar,Dynamic,1> tb(size);
-    Eigen::Matrix<DestScalar,Dynamic,1> 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<rhsCols; ++k)
-    {
-      tb = b.col(k);
-      tx = derived().solve(tb);
-      tmp.col(k) = tx.sparseView(0);
-    }
-    dest.swap(tmp);
-  }
-
-protected:
-  void init()
-  {
-    m_isInitialized = false;
-    m_analysisIsOk = false;
-    m_factorizationIsOk = false;
-    m_maxIterations = -1;
-    m_tolerance = NumTraits<Scalar>::epsilon();
-  }
-
-  typedef internal::generic_matrix_wrapper<MatrixType> MatrixWrapper;
-  typedef typename MatrixWrapper::ActualMatrixType ActualMatrixType;
-
-  const ActualMatrixType& matrix() const
-  {
-    return m_matrixWrapper.matrix();
-  }
-  
-  template<typename InputType>
-  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