Eigen/src/SparseCore/SparseVector.h - platform/external/eigen - Git at Google

 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2008-2009 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_SPARSEVECTOR_H
 #define EIGEN_SPARSEVECTOR_H

 namespace Eigen {

 /** \ingroup SparseCore_Module
   * \class SparseVector
   *
   * \brief a sparse vector class
   *
   * \tparam _Scalar the scalar type, i.e. the type of the coefficients
   *
   * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
   * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
   */

 namespace internal {
 template<typename _Scalar, int _Options, typename _Index>
 struct traits<SparseVector<_Scalar, _Options, _Index> >
 {
   typedef _Scalar Scalar;
   typedef _Index Index;
   typedef Sparse StorageKind;
   typedef MatrixXpr XprKind;
   enum {
     IsColVector = (_Options & RowMajorBit) ? 0 : 1,

     RowsAtCompileTime = IsColVector ? Dynamic : 1,
     ColsAtCompileTime = IsColVector ? 1 : Dynamic,
     MaxRowsAtCompileTime = RowsAtCompileTime,
     MaxColsAtCompileTime = ColsAtCompileTime,
     Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit),
     CoeffReadCost = NumTraits<Scalar>::ReadCost,
     SupportedAccessPatterns = InnerRandomAccessPattern
   };
 };
 }

 template<typename _Scalar, int _Options, typename _Index>
 class SparseVector
   : public SparseMatrixBase<SparseVector<_Scalar, _Options, _Index> >
 {
   public:
     EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
     EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
     EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)

   protected:
   public:

     typedef SparseMatrixBase<SparseVector> SparseBase;
     enum { IsColVector = internal::traits<SparseVector>::IsColVector };

     enum {
       Options = _Options
     };

     internal::CompressedStorage<Scalar,Index> m_data;
     Index m_size;

     internal::CompressedStorage<Scalar,Index>& _data() { return m_data; }
     internal::CompressedStorage<Scalar,Index>& _data() const { return m_data; }

   public:

     EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; }
     EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; }
     EIGEN_STRONG_INLINE Index innerSize() const { return m_size; }
     EIGEN_STRONG_INLINE Index outerSize() const { return 1; }

     EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return &m_data.value(0); }
     EIGEN_STRONG_INLINE Scalar* valuePtr() { return &m_data.value(0); }

     EIGEN_STRONG_INLINE const Index* innerIndexPtr() const { return &m_data.index(0); }
     EIGEN_STRONG_INLINE Index* innerIndexPtr() { return &m_data.index(0); }

     inline Scalar coeff(Index row, Index col) const
     {
       eigen_assert((IsColVector ? col : row)==0);
       return coeff(IsColVector ? row : col);
     }
     inline Scalar coeff(Index i) const { return m_data.at(i); }

     inline Scalar& coeffRef(Index row, Index col)
     {
       eigen_assert((IsColVector ? col : row)==0);
       return coeff(IsColVector ? row : col);
     }

     /** \returns a reference to the coefficient value at given index \a i
       * This operation involes a log(rho*size) binary search. If the coefficient does not
       * exist yet, then a sorted insertion into a sequential buffer is performed.
       *
       * This insertion might be very costly if the number of nonzeros above \a i is large.
       */
     inline Scalar& coeffRef(Index i)
     {
       return m_data.atWithInsertion(i);
     }

   public:

     class InnerIterator;
     class ReverseInnerIterator;

     inline void setZero() { m_data.clear(); }

     /** \returns the number of non zero coefficients */
     inline Index nonZeros() const  { return static_cast<Index>(m_data.size()); }

     inline void startVec(Index outer)
     {
       EIGEN_UNUSED_VARIABLE(outer);
       eigen_assert(outer==0);
     }

     inline Scalar& insertBackByOuterInner(Index outer, Index inner)
     {
       EIGEN_UNUSED_VARIABLE(outer);
       eigen_assert(outer==0);
       return insertBack(inner);
     }
     inline Scalar& insertBack(Index i)
     {
       m_data.append(0, i);
       return m_data.value(m_data.size()-1);
     }

     inline Scalar& insert(Index row, Index col)
     {
       Index inner = IsColVector ? row : col;
       Index outer = IsColVector ? col : row;
       eigen_assert(outer==0);
       return insert(inner);
     }
     Scalar& insert(Index i)
     {
       Index startId = 0;
       Index p = Index(m_data.size()) - 1;
       // TODO smart realloc
       m_data.resize(p+2,1);

       while ( (p >= startId) && (m_data.index(p) > i) )
       {
         m_data.index(p+1) = m_data.index(p);
         m_data.value(p+1) = m_data.value(p);
         --p;
       }
       m_data.index(p+1) = i;
       m_data.value(p+1) = 0;
       return m_data.value(p+1);
     }

     /**
       */
     inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }


     inline void finalize() {}

     void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
     {
       m_data.prune(reference,epsilon);
     }

     void resize(Index rows, Index cols)
     {
       eigen_assert(rows==1 || cols==1);
       resize(IsColVector ? rows : cols);
     }

     void resize(Index newSize)
     {
       m_size = newSize;
       m_data.clear();
     }

     void resizeNonZeros(Index size) { m_data.resize(size); }

     inline SparseVector() : m_size(0) { resize(0); }

     inline SparseVector(Index size) : m_size(0) { resize(size); }

     inline SparseVector(Index rows, Index cols) : m_size(0) { resize(rows,cols); }

     template<typename OtherDerived>
     inline SparseVector(const SparseMatrixBase<OtherDerived>& other)
       : m_size(0)
     {
       *this = other.derived();
     }

     inline SparseVector(const SparseVector& other)
       : m_size(0)
     {
       *this = other.derived();
     }

     inline void swap(SparseVector& other)
     {
       std::swap(m_size, other.m_size);
       m_data.swap(other.m_data);
     }

     inline SparseVector& operator=(const SparseVector& other)
     {
       if (other.isRValue())
       {
         swap(other.const_cast_derived());
       }
       else
       {
         resize(other.size());
         m_data = other.m_data;
       }
       return *this;
     }

     template<typename OtherDerived>
     inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other)
     {
       if (int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime))
         return assign(other.transpose());
       else
         return assign(other);
     }

     #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename Lhs, typename Rhs>
     inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
     {
       return Base::operator=(product);
     }
     #endif

     friend std::ostream & operator << (std::ostream & s, const SparseVector& m)
     {
       for (Index i=0; i<m.nonZeros(); ++i)
         s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
       s << std::endl;
       return s;
     }

     /** Destructor */
     inline ~SparseVector() {}

     /** Overloaded for performance */
     Scalar sum() const;

   public:

     /** \deprecated use setZero() and reserve() */
     EIGEN_DEPRECATED void startFill(Index reserve)
     {
       setZero();
       m_data.reserve(reserve);
     }

     /** \deprecated use insertBack(Index,Index) */
     EIGEN_DEPRECATED Scalar& fill(Index r, Index c)
     {
       eigen_assert(r==0 || c==0);
       return fill(IsColVector ? r : c);
     }

     /** \deprecated use insertBack(Index) */
     EIGEN_DEPRECATED Scalar& fill(Index i)
     {
       m_data.append(0, i);
       return m_data.value(m_data.size()-1);
     }

     /** \deprecated use insert(Index,Index) */
     EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c)
     {
       eigen_assert(r==0 || c==0);
       return fillrand(IsColVector ? r : c);
     }

     /** \deprecated use insert(Index) */
     EIGEN_DEPRECATED Scalar& fillrand(Index i)
     {
       return insert(i);
     }

     /** \deprecated use finalize() */
     EIGEN_DEPRECATED void endFill() {}

 #   ifdef EIGEN_SPARSEVECTOR_PLUGIN
 #     include EIGEN_SPARSEVECTOR_PLUGIN
 #   endif

 protected:
     template<typename OtherDerived>
     EIGEN_DONT_INLINE SparseVector& assign(const SparseMatrixBase<OtherDerived>& _other)
     {
       const OtherDerived& other(_other.derived());
       const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
       if(needToTranspose)
       {
         Index size = other.size();
         Index nnz = other.nonZeros();
         resize(size);
         reserve(nnz);
         for(Index i=0; i<size; ++i)
         {
           typename OtherDerived::InnerIterator it(other, i);
           if(it)
               insert(i) = it.value();
         }
         return *this;
       }
       else
       {
         // there is no special optimization
         return Base::operator=(other);
       }
     }
 };

 template<typename Scalar, int _Options, typename _Index>
 class SparseVector<Scalar,_Options,_Index>::InnerIterator
 {
   public:
     InnerIterator(const SparseVector& vec, Index outer=0)
       : m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size()))
     {
       EIGEN_UNUSED_VARIABLE(outer);
       eigen_assert(outer==0);
     }

     InnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
       : m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size()))
     {}

     inline InnerIterator& operator++() { m_id++; return *this; }

     inline Scalar value() const { return m_data.value(m_id); }
     inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id)); }

     inline Index index() const { return m_data.index(m_id); }
     inline Index row() const { return IsColVector ? index() : 0; }
     inline Index col() const { return IsColVector ? 0 : index(); }

     inline operator bool() const { return (m_id < m_end); }

   protected:
     const internal::CompressedStorage<Scalar,Index>& m_data;
     Index m_id;
     const Index m_end;
 };

 template<typename Scalar, int _Options, typename _Index>
 class SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator
 {
   public:
     ReverseInnerIterator(const SparseVector& vec, Index outer=0)
       : m_data(vec.m_data), m_id(static_cast<Index>(m_data.size())), m_start(0)
     {
       EIGEN_UNUSED_VARIABLE(outer);
       eigen_assert(outer==0);
     }

     ReverseInnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
       : m_data(data), m_id(static_cast<Index>(m_data.size())), m_start(0)
     {}

     inline ReverseInnerIterator& operator--() { m_id--; return *this; }

     inline Scalar value() const { return m_data.value(m_id-1); }
     inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id-1)); }

     inline Index index() const { return m_data.index(m_id-1); }
     inline Index row() const { return IsColVector ? index() : 0; }
     inline Index col() const { return IsColVector ? 0 : index(); }

     inline operator bool() const { return (m_id > m_start); }

   protected:
     const internal::CompressedStorage<Scalar,Index>& m_data;
     Index m_id;
     const Index m_start;
 };

 } // end namespace Eigen

 #endif // EIGEN_SPARSEVECTOR_H
	// This file is part of Eigen, a lightweight C++ template library
	// for linear algebra.
	//
	// Copyright (C) 2008-2009 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_SPARSEVECTOR_H
	#define EIGEN_SPARSEVECTOR_H

	namespace Eigen {

	/** \ingroup SparseCore_Module
	* \class SparseVector
	*
	* \brief a sparse vector class
	*
	* \tparam _Scalar the scalar type, i.e. the type of the coefficients
	*
	* See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
	*
	* This class can be extended with the help of the plugin mechanism described on the page
	* \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN.
	*/

	namespace internal {
	template<typename _Scalar, int _Options, typename _Index>
	struct traits<SparseVector<_Scalar, _Options, _Index> >
	{
	typedef _Scalar Scalar;
	typedef _Index Index;
	typedef Sparse StorageKind;
	typedef MatrixXpr XprKind;
	enum {
	IsColVector = (_Options & RowMajorBit) ? 0 : 1,

	RowsAtCompileTime = IsColVector ? Dynamic : 1,
	ColsAtCompileTime = IsColVector ? 1 : Dynamic,
	MaxRowsAtCompileTime = RowsAtCompileTime,
	MaxColsAtCompileTime = ColsAtCompileTime,
	Flags = _Options \| NestByRefBit \| LvalueBit \| (IsColVector ? 0 : RowMajorBit),
	CoeffReadCost = NumTraits<Scalar>::ReadCost,
	SupportedAccessPatterns = InnerRandomAccessPattern
	};
	};
	}

	template<typename _Scalar, int _Options, typename _Index>
	class SparseVector
	: public SparseMatrixBase<SparseVector<_Scalar, _Options, _Index> >
	{
	public:
	EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
	EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
	EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)

	protected:
	public:

	typedef SparseMatrixBase<SparseVector> SparseBase;
	enum { IsColVector = internal::traits<SparseVector>::IsColVector };

	enum {
	Options = _Options
	};

	internal::CompressedStorage<Scalar,Index> m_data;
	Index m_size;

	internal::CompressedStorage<Scalar,Index>& _data() { return m_data; }
	internal::CompressedStorage<Scalar,Index>& _data() const { return m_data; }

	public:

	EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; }
	EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; }
	EIGEN_STRONG_INLINE Index innerSize() const { return m_size; }
	EIGEN_STRONG_INLINE Index outerSize() const { return 1; }

	EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return &m_data.value(0); }
	EIGEN_STRONG_INLINE Scalar* valuePtr() { return &m_data.value(0); }

	EIGEN_STRONG_INLINE const Index* innerIndexPtr() const { return &m_data.index(0); }
	EIGEN_STRONG_INLINE Index* innerIndexPtr() { return &m_data.index(0); }

	inline Scalar coeff(Index row, Index col) const
	{
	eigen_assert((IsColVector ? col : row)==0);
	return coeff(IsColVector ? row : col);
	}
	inline Scalar coeff(Index i) const { return m_data.at(i); }

	inline Scalar& coeffRef(Index row, Index col)
	{
	eigen_assert((IsColVector ? col : row)==0);
	return coeff(IsColVector ? row : col);
	}

	/** \returns a reference to the coefficient value at given index \a i
	* This operation involes a log(rho*size) binary search. If the coefficient does not
	* exist yet, then a sorted insertion into a sequential buffer is performed.
	*
	* This insertion might be very costly if the number of nonzeros above \a i is large.
	*/
	inline Scalar& coeffRef(Index i)
	{
	return m_data.atWithInsertion(i);
	}

	public:

	class InnerIterator;
	class ReverseInnerIterator;

	inline void setZero() { m_data.clear(); }

	/** \returns the number of non zero coefficients */
	inline Index nonZeros() const { return static_cast<Index>(m_data.size()); }

	inline void startVec(Index outer)
	{
	EIGEN_UNUSED_VARIABLE(outer);
	eigen_assert(outer==0);
	}

	inline Scalar& insertBackByOuterInner(Index outer, Index inner)
	{
	EIGEN_UNUSED_VARIABLE(outer);
	eigen_assert(outer==0);
	return insertBack(inner);
	}
	inline Scalar& insertBack(Index i)
	{
	m_data.append(0, i);
	return m_data.value(m_data.size()-1);
	}

	inline Scalar& insert(Index row, Index col)
	{
	Index inner = IsColVector ? row : col;
	Index outer = IsColVector ? col : row;
	eigen_assert(outer==0);
	return insert(inner);
	}
	Scalar& insert(Index i)
	{
	Index startId = 0;
	Index p = Index(m_data.size()) - 1;
	// TODO smart realloc
	m_data.resize(p+2,1);

	while ( (p >= startId) && (m_data.index(p) > i) )
	{
	m_data.index(p+1) = m_data.index(p);
	m_data.value(p+1) = m_data.value(p);
	--p;
	}
	m_data.index(p+1) = i;
	m_data.value(p+1) = 0;
	return m_data.value(p+1);
	}

	/**
	*/
	inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }


	inline void finalize() {}

	void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
	{
	m_data.prune(reference,epsilon);
	}

	void resize(Index rows, Index cols)
	{
	eigen_assert(rows==1 \|\| cols==1);
	resize(IsColVector ? rows : cols);
	}

	void resize(Index newSize)
	{
	m_size = newSize;
	m_data.clear();
	}

	void resizeNonZeros(Index size) { m_data.resize(size); }

	inline SparseVector() : m_size(0) { resize(0); }

	inline SparseVector(Index size) : m_size(0) { resize(size); }

	inline SparseVector(Index rows, Index cols) : m_size(0) { resize(rows,cols); }

	template<typename OtherDerived>
	inline SparseVector(const SparseMatrixBase<OtherDerived>& other)
	: m_size(0)
	{
	*this = other.derived();
	}

	inline SparseVector(const SparseVector& other)
	: m_size(0)
	{
	*this = other.derived();
	}

	inline void swap(SparseVector& other)
	{
	std::swap(m_size, other.m_size);
	m_data.swap(other.m_data);
	}

	inline SparseVector& operator=(const SparseVector& other)
	{
	if (other.isRValue())
	{
	swap(other.const_cast_derived());
	}
	else
	{
	resize(other.size());
	m_data = other.m_data;
	}
	return *this;
	}

	template<typename OtherDerived>
	inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other)
	{
	if (int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime))
	return assign(other.transpose());
	else
	return assign(other);
	}

	#ifndef EIGEN_PARSED_BY_DOXYGEN
	template<typename Lhs, typename Rhs>
	inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
	{
	return Base::operator=(product);
	}
	#endif

	friend std::ostream & operator << (std::ostream & s, const SparseVector& m)
	{
	for (Index i=0; i<m.nonZeros(); ++i)
	s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
	s << std::endl;
	return s;
	}

	/** Destructor */
	inline ~SparseVector() {}

	/** Overloaded for performance */
	Scalar sum() const;

	public:

	/** \deprecated use setZero() and reserve() */
	EIGEN_DEPRECATED void startFill(Index reserve)
	{
	setZero();
	m_data.reserve(reserve);
	}

	/** \deprecated use insertBack(Index,Index) */
	EIGEN_DEPRECATED Scalar& fill(Index r, Index c)
	{
	eigen_assert(r==0 \|\| c==0);
	return fill(IsColVector ? r : c);
	}

	/** \deprecated use insertBack(Index) */
	EIGEN_DEPRECATED Scalar& fill(Index i)
	{
	m_data.append(0, i);
	return m_data.value(m_data.size()-1);
	}

	/** \deprecated use insert(Index,Index) */
	EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c)
	{
	eigen_assert(r==0 \|\| c==0);
	return fillrand(IsColVector ? r : c);
	}

	/** \deprecated use insert(Index) */
	EIGEN_DEPRECATED Scalar& fillrand(Index i)
	{
	return insert(i);
	}

	/** \deprecated use finalize() */
	EIGEN_DEPRECATED void endFill() {}

	# ifdef EIGEN_SPARSEVECTOR_PLUGIN
	# include EIGEN_SPARSEVECTOR_PLUGIN
	# endif

	protected:
	template<typename OtherDerived>
	EIGEN_DONT_INLINE SparseVector& assign(const SparseMatrixBase<OtherDerived>& _other)
	{
	const OtherDerived& other(_other.derived());
	const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
	if(needToTranspose)
	{
	Index size = other.size();
	Index nnz = other.nonZeros();
	resize(size);
	reserve(nnz);
	for(Index i=0; i<size; ++i)
	{
	typename OtherDerived::InnerIterator it(other, i);
	if(it)
	insert(i) = it.value();
	}
	return *this;
	}
	else
	{
	// there is no special optimization
	return Base::operator=(other);
	}
	}
	};

	template<typename Scalar, int _Options, typename _Index>
	class SparseVector<Scalar,_Options,_Index>::InnerIterator
	{
	public:
	InnerIterator(const SparseVector& vec, Index outer=0)
	: m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size()))
	{
	EIGEN_UNUSED_VARIABLE(outer);
	eigen_assert(outer==0);
	}

	InnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
	: m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size()))
	{}

	inline InnerIterator& operator++() { m_id++; return *this; }

	inline Scalar value() const { return m_data.value(m_id); }
	inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id)); }

	inline Index index() const { return m_data.index(m_id); }
	inline Index row() const { return IsColVector ? index() : 0; }
	inline Index col() const { return IsColVector ? 0 : index(); }

	inline operator bool() const { return (m_id < m_end); }

	protected:
	const internal::CompressedStorage<Scalar,Index>& m_data;
	Index m_id;
	const Index m_end;
	};

	template<typename Scalar, int _Options, typename _Index>
	class SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator
	{
	public:
	ReverseInnerIterator(const SparseVector& vec, Index outer=0)
	: m_data(vec.m_data), m_id(static_cast<Index>(m_data.size())), m_start(0)
	{
	EIGEN_UNUSED_VARIABLE(outer);
	eigen_assert(outer==0);
	}

	ReverseInnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
	: m_data(data), m_id(static_cast<Index>(m_data.size())), m_start(0)
	{}

	inline ReverseInnerIterator& operator--() { m_id--; return *this; }

	inline Scalar value() const { return m_data.value(m_id-1); }
	inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id-1)); }

	inline Index index() const { return m_data.index(m_id-1); }
	inline Index row() const { return IsColVector ? index() : 0; }
	inline Index col() const { return IsColVector ? 0 : index(); }

	inline operator bool() const { return (m_id > m_start); }

	protected:
	const internal::CompressedStorage<Scalar,Index>& m_data;
	Index m_id;
	const Index m_start;
	};

	} // end namespace Eigen

	#endif // EIGEN_SPARSEVECTOR_H