| // This file is part of Eigen, a lightweight C++ template library | 
 | // for linear algebra. | 
 | // | 
 | // Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr> | 
 | // Copyright (C) 2010 Daniel Lowengrub <lowdanie@gmail.com> | 
 | // | 
 | // 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_SPARSEVIEW_H | 
 | #define EIGEN_SPARSEVIEW_H | 
 |  | 
 | #include "./InternalHeaderCheck.h" | 
 |  | 
 | namespace Eigen {  | 
 |  | 
 | namespace internal { | 
 |  | 
 | template<typename MatrixType> | 
 | struct traits<SparseView<MatrixType> > : traits<MatrixType> | 
 | { | 
 |   typedef typename MatrixType::StorageIndex StorageIndex; | 
 |   typedef Sparse StorageKind; | 
 |   enum { | 
 |     Flags = int(traits<MatrixType>::Flags) & (RowMajorBit) | 
 |   }; | 
 | }; | 
 |  | 
 | } // end namespace internal | 
 |  | 
 | /** \ingroup SparseCore_Module | 
 |   * \class SparseView | 
 |   * | 
 |   * \brief Expression of a dense or sparse matrix with zero or too small values removed | 
 |   * | 
 |   * \tparam MatrixType the type of the object of which we are removing the small entries | 
 |   * | 
 |   * This class represents an expression of a given dense or sparse matrix with | 
 |   * entries smaller than \c reference * \c epsilon are removed. | 
 |   * It is the return type of MatrixBase::sparseView() and SparseMatrixBase::pruned() | 
 |   * and most of the time this is the only way it is used. | 
 |   * | 
 |   * \sa MatrixBase::sparseView(), SparseMatrixBase::pruned() | 
 |   */ | 
 | template<typename MatrixType> | 
 | class SparseView : public SparseMatrixBase<SparseView<MatrixType> > | 
 | { | 
 |   typedef typename MatrixType::Nested MatrixTypeNested; | 
 |   typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested; | 
 |   typedef SparseMatrixBase<SparseView > Base; | 
 | public: | 
 |   EIGEN_SPARSE_PUBLIC_INTERFACE(SparseView) | 
 |   typedef typename internal::remove_all<MatrixType>::type NestedExpression; | 
 |  | 
 |   explicit SparseView(const MatrixType& mat, const Scalar& reference = Scalar(0), | 
 |                       const RealScalar &epsilon = NumTraits<Scalar>::dummy_precision()) | 
 |     : m_matrix(mat), m_reference(reference), m_epsilon(epsilon) {} | 
 |  | 
 |   inline Index rows() const { return m_matrix.rows(); } | 
 |   inline Index cols() const { return m_matrix.cols(); } | 
 |  | 
 |   inline Index innerSize() const { return m_matrix.innerSize(); } | 
 |   inline Index outerSize() const { return m_matrix.outerSize(); } | 
 |    | 
 |   /** \returns the nested expression */ | 
 |   const typename internal::remove_all<MatrixTypeNested>::type& | 
 |   nestedExpression() const { return m_matrix; } | 
 |    | 
 |   Scalar reference() const { return m_reference; } | 
 |   RealScalar epsilon() const { return m_epsilon; } | 
 |    | 
 | protected: | 
 |   MatrixTypeNested m_matrix; | 
 |   Scalar m_reference; | 
 |   RealScalar m_epsilon; | 
 | }; | 
 |  | 
 | namespace internal { | 
 |  | 
 | // TODO find a way to unify the two following variants | 
 | // This is tricky because implementing an inner iterator on top of an IndexBased evaluator is | 
 | // not easy because the evaluators do not expose the sizes of the underlying expression. | 
 |    | 
 | template<typename ArgType> | 
 | struct unary_evaluator<SparseView<ArgType>, IteratorBased> | 
 |   : public evaluator_base<SparseView<ArgType> > | 
 | { | 
 |     typedef typename evaluator<ArgType>::InnerIterator EvalIterator; | 
 |   public: | 
 |     typedef SparseView<ArgType> XprType; | 
 |      | 
 |     class InnerIterator : public EvalIterator | 
 |     { | 
 |       protected: | 
 |         typedef typename XprType::Scalar Scalar; | 
 |       public: | 
 |  | 
 |         EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer) | 
 |           : EvalIterator(sve.m_argImpl,outer), m_view(sve.m_view) | 
 |         { | 
 |           incrementToNonZero(); | 
 |         } | 
 |  | 
 |         EIGEN_STRONG_INLINE InnerIterator& operator++() | 
 |         { | 
 |           EvalIterator::operator++(); | 
 |           incrementToNonZero(); | 
 |           return *this; | 
 |         } | 
 |  | 
 |         using EvalIterator::value; | 
 |  | 
 |       protected: | 
 |         const XprType &m_view; | 
 |  | 
 |       private: | 
 |         void incrementToNonZero() | 
 |         { | 
 |           while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.reference(), m_view.epsilon())) | 
 |           { | 
 |             EvalIterator::operator++(); | 
 |           } | 
 |         } | 
 |     }; | 
 |      | 
 |     enum { | 
 |       CoeffReadCost = evaluator<ArgType>::CoeffReadCost, | 
 |       Flags = XprType::Flags | 
 |     }; | 
 |      | 
 |     explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {} | 
 |  | 
 |   protected: | 
 |     evaluator<ArgType> m_argImpl; | 
 |     const XprType &m_view; | 
 | }; | 
 |  | 
 | template<typename ArgType> | 
 | struct unary_evaluator<SparseView<ArgType>, IndexBased> | 
 |   : public evaluator_base<SparseView<ArgType> > | 
 | { | 
 |   public: | 
 |     typedef SparseView<ArgType> XprType; | 
 |   protected: | 
 |     enum { IsRowMajor = (XprType::Flags&RowMajorBit)==RowMajorBit }; | 
 |     typedef typename XprType::Scalar Scalar; | 
 |     typedef typename XprType::StorageIndex StorageIndex; | 
 |   public: | 
 |      | 
 |     class InnerIterator | 
 |     { | 
 |       public: | 
 |  | 
 |         EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer) | 
 |           : m_sve(sve), m_inner(0), m_outer(outer), m_end(sve.m_view.innerSize()) | 
 |         { | 
 |           incrementToNonZero(); | 
 |         } | 
 |  | 
 |         EIGEN_STRONG_INLINE InnerIterator& operator++() | 
 |         { | 
 |           m_inner++; | 
 |           incrementToNonZero(); | 
 |           return *this; | 
 |         } | 
 |  | 
 |         EIGEN_STRONG_INLINE Scalar value() const | 
 |         { | 
 |           return (IsRowMajor) ? m_sve.m_argImpl.coeff(m_outer, m_inner) | 
 |                               : m_sve.m_argImpl.coeff(m_inner, m_outer); | 
 |         } | 
 |  | 
 |         EIGEN_STRONG_INLINE StorageIndex index() const { return m_inner; } | 
 |         inline Index row() const { return IsRowMajor ? m_outer : index(); } | 
 |         inline Index col() const { return IsRowMajor ? index() : m_outer; } | 
 |  | 
 |         EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; } | 
 |  | 
 |       protected: | 
 |         const unary_evaluator &m_sve; | 
 |         Index m_inner; | 
 |         const Index m_outer; | 
 |         const Index m_end; | 
 |  | 
 |       private: | 
 |         void incrementToNonZero() | 
 |         { | 
 |           while((bool(*this)) && internal::isMuchSmallerThan(value(), m_sve.m_view.reference(), m_sve.m_view.epsilon())) | 
 |           { | 
 |             m_inner++; | 
 |           } | 
 |         } | 
 |     }; | 
 |      | 
 |     enum { | 
 |       CoeffReadCost = evaluator<ArgType>::CoeffReadCost, | 
 |       Flags = XprType::Flags | 
 |     }; | 
 |      | 
 |     explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {} | 
 |  | 
 |   protected: | 
 |     evaluator<ArgType> m_argImpl; | 
 |     const XprType &m_view; | 
 | }; | 
 |  | 
 | } // end namespace internal | 
 |  | 
 | /** \ingroup SparseCore_Module | 
 |   * | 
 |   * \returns a sparse expression of the dense expression \c *this with values smaller than | 
 |   * \a reference * \a epsilon removed. | 
 |   * | 
 |   * This method is typically used when prototyping to convert a quickly assembled dense Matrix \c D to a SparseMatrix \c S: | 
 |   * \code | 
 |   * MatrixXd D(n,m); | 
 |   * SparseMatrix<double> S; | 
 |   * S = D.sparseView();             // suppress numerical zeros (exact) | 
 |   * S = D.sparseView(reference); | 
 |   * S = D.sparseView(reference,epsilon); | 
 |   * \endcode | 
 |   * where \a reference is a meaningful non zero reference value, | 
 |   * and \a epsilon is a tolerance factor defaulting to NumTraits<Scalar>::dummy_precision(). | 
 |   * | 
 |   * \sa SparseMatrixBase::pruned(), class SparseView */ | 
 | template<typename Derived> | 
 | const SparseView<Derived> MatrixBase<Derived>::sparseView(const Scalar& reference, | 
 |                                                           const typename NumTraits<Scalar>::Real& epsilon) const | 
 | { | 
 |   return SparseView<Derived>(derived(), reference, epsilon); | 
 | } | 
 |  | 
 | /** \returns an expression of \c *this with values smaller than | 
 |   * \a reference * \a epsilon removed. | 
 |   * | 
 |   * This method is typically used in conjunction with the product of two sparse matrices | 
 |   * to automatically prune the smallest values as follows: | 
 |   * \code | 
 |   * C = (A*B).pruned();             // suppress numerical zeros (exact) | 
 |   * C = (A*B).pruned(ref); | 
 |   * C = (A*B).pruned(ref,epsilon); | 
 |   * \endcode | 
 |   * where \c ref is a meaningful non zero reference value. | 
 |   * */ | 
 | template<typename Derived> | 
 | const SparseView<Derived> | 
 | SparseMatrixBase<Derived>::pruned(const Scalar& reference, | 
 |                                   const RealScalar& epsilon) const | 
 | { | 
 |   return SparseView<Derived>(derived(), reference, epsilon); | 
 | } | 
 |  | 
 | } // end namespace Eigen | 
 |  | 
 | #endif |