| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2008-2015 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 |
| |
| #include "./InternalHeaderCheck.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 TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_SPARSEVECTOR_PLUGIN. |
| */ |
| |
| namespace internal { |
| template<typename Scalar_, int Options_, typename StorageIndex_> |
| struct traits<SparseVector<Scalar_, Options_, StorageIndex_> > |
| { |
| typedef Scalar_ Scalar; |
| typedef StorageIndex_ StorageIndex; |
| 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) | CompressedAccessBit, |
| SupportedAccessPatterns = InnerRandomAccessPattern |
| }; |
| }; |
| |
| // Sparse-Vector-Assignment kinds: |
| enum { |
| SVA_RuntimeSwitch, |
| SVA_Inner, |
| SVA_Outer |
| }; |
| |
| template< typename Dest, typename Src, |
| int AssignmentKind = !bool(Src::IsVectorAtCompileTime) ? SVA_RuntimeSwitch |
| : Src::InnerSizeAtCompileTime==1 ? SVA_Outer |
| : SVA_Inner> |
| struct sparse_vector_assign_selector; |
| |
| } |
| |
| template<typename Scalar_, int Options_, typename StorageIndex_> |
| class SparseVector |
| : public SparseCompressedBase<SparseVector<Scalar_, Options_, StorageIndex_> > |
| { |
| typedef SparseCompressedBase<SparseVector> Base; |
| using Base::convert_index; |
| public: |
| EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector) |
| EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=) |
| EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=) |
| |
| typedef internal::CompressedStorage<Scalar,StorageIndex> Storage; |
| enum { IsColVector = internal::traits<SparseVector>::IsColVector }; |
| |
| enum { |
| Options = Options_ |
| }; |
| |
| 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.valuePtr(); } |
| EIGEN_STRONG_INLINE Scalar* valuePtr() { return m_data.valuePtr(); } |
| |
| EIGEN_STRONG_INLINE const StorageIndex* innerIndexPtr() const { return m_data.indexPtr(); } |
| EIGEN_STRONG_INLINE StorageIndex* innerIndexPtr() { return m_data.indexPtr(); } |
| |
| inline const StorageIndex* outerIndexPtr() const { return 0; } |
| inline StorageIndex* outerIndexPtr() { return 0; } |
| inline const StorageIndex* innerNonZeroPtr() const { return 0; } |
| inline StorageIndex* innerNonZeroPtr() { return 0; } |
| |
| /** \internal */ |
| inline Storage& data() { return m_data; } |
| /** \internal */ |
| inline const Storage& data() const { return m_data; } |
| |
| inline Scalar coeff(Index row, Index col) const |
| { |
| eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); |
| return coeff(IsColVector ? row : col); |
| } |
| inline Scalar coeff(Index i) const |
| { |
| eigen_assert(i>=0 && i<m_size); |
| return m_data.at(StorageIndex(i)); |
| } |
| |
| inline Scalar& coeffRef(Index row, Index col) |
| { |
| eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); |
| return coeffRef(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) |
| { |
| eigen_assert(i>=0 && i<m_size); |
| |
| return m_data.atWithInsertion(StorageIndex(i)); |
| } |
| |
| public: |
| |
| typedef typename Base::InnerIterator InnerIterator; |
| typedef typename Base::ReverseInnerIterator ReverseInnerIterator; |
| |
| inline void setZero() { m_data.clear(); } |
| |
| /** \returns the number of non zero coefficients */ |
| inline Index nonZeros() const { return 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); |
| } |
| |
| Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner) |
| { |
| EIGEN_UNUSED_VARIABLE(outer); |
| eigen_assert(outer==0); |
| return insertBackUnordered(inner); |
| } |
| inline Scalar& insertBackUnordered(Index i) |
| { |
| m_data.append(0, i); |
| return m_data.value(m_data.size()-1); |
| } |
| |
| inline Scalar& insert(Index row, Index col) |
| { |
| eigen_assert(IsColVector ? (col==0 && row>=0 && row<m_size) : (row==0 && col>=0 && col<m_size)); |
| |
| Index inner = IsColVector ? row : col; |
| Index outer = IsColVector ? col : row; |
| EIGEN_ONLY_USED_FOR_DEBUG(outer); |
| eigen_assert(outer==0); |
| return insert(inner); |
| } |
| Scalar& insert(Index i) |
| { |
| eigen_assert(i>=0 && i<m_size); |
| |
| 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) = convert_index(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() {} |
| |
| /** \copydoc SparseMatrix::prune(const Scalar&,const RealScalar&) */ |
| Index prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) { |
| return prune([&](const Scalar& val){ return !internal::isMuchSmallerThan(val, reference, epsilon); }); |
| } |
| |
| /** |
| * \brief Prunes the entries of the vector based on a `predicate` |
| * \tparam F Type of the predicate. |
| * \param keep_predicate The predicate that is used to test whether a value should be kept. A callable that |
| * gets passed om a `Scalar` value and returns a boolean. If the predicate returns true, the value is kept. |
| * \return The new number of structural non-zeros. |
| */ |
| template<class F> |
| Index prune(F&& keep_predicate) |
| { |
| Index k = 0; |
| Index n = m_data.size(); |
| for (Index i = 0; i < n; ++i) |
| { |
| if (keep_predicate(m_data.value(i))) |
| { |
| m_data.value(k) = std::move(m_data.value(i)); |
| m_data.index(k) = m_data.index(i); |
| ++k; |
| } |
| } |
| m_data.resize(k); |
| return k; |
| } |
| |
| /** Resizes the sparse vector to \a rows x \a cols |
| * |
| * This method is provided for compatibility with matrices. |
| * For a column vector, \a cols must be equal to 1. |
| * For a row vector, \a rows must be equal to 1. |
| * |
| * \sa resize(Index) |
| */ |
| void resize(Index rows, Index cols) |
| { |
| eigen_assert((IsColVector ? cols : rows)==1 && "Outer dimension must equal 1"); |
| resize(IsColVector ? rows : cols); |
| } |
| |
| /** Resizes the sparse vector to \a newSize |
| * This method deletes all entries, thus leaving an empty sparse vector |
| * |
| * \sa conservativeResize(), setZero() */ |
| void resize(Index newSize) |
| { |
| m_size = newSize; |
| m_data.clear(); |
| } |
| |
| /** Resizes the sparse vector to \a newSize, while leaving old values untouched. |
| * |
| * If the size of the vector is decreased, then the storage of the out-of bounds coefficients is kept and reserved. |
| * Call .data().squeeze() to free extra memory. |
| * |
| * \sa reserve(), setZero() |
| */ |
| void conservativeResize(Index newSize) |
| { |
| if (newSize < m_size) |
| { |
| Index i = 0; |
| while (i<m_data.size() && m_data.index(i)<newSize) ++i; |
| m_data.resize(i); |
| } |
| m_size = newSize; |
| } |
| |
| void resizeNonZeros(Index size) { m_data.resize(size); } |
| |
| inline SparseVector() : m_size(0) { resize(0); } |
| |
| explicit 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) |
| { |
| #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN |
| EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN |
| #endif |
| *this = other.derived(); |
| } |
| |
| inline SparseVector(const SparseVector& other) |
| : Base(other), m_size(0) |
| { |
| *this = other.derived(); |
| } |
| |
| /** Swaps the values of \c *this and \a other. |
| * Overloaded for performance: this version performs a \em shallow swap by swapping pointers and attributes only. |
| * \sa SparseMatrixBase::swap() |
| */ |
| inline void swap(SparseVector& other) |
| { |
| std::swap(m_size, other.m_size); |
| m_data.swap(other.m_data); |
| } |
| |
| template<int OtherOptions> |
| inline void swap(SparseMatrix<Scalar,OtherOptions,StorageIndex>& other) |
| { |
| eigen_assert(other.outerSize()==1); |
| std::swap(m_size, other.m_innerSize); |
| 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) |
| { |
| SparseVector tmp(other.size()); |
| internal::sparse_vector_assign_selector<SparseVector,OtherDerived>::run(tmp,other.derived()); |
| this->swap(tmp); |
| return *this; |
| } |
| |
| #ifndef EIGEN_PARSED_BY_DOXYGEN |
| template<typename Lhs, typename Rhs> |
| inline SparseVector& operator=(const SparseSparseProduct<Lhs,Rhs>& product) |
| { |
| return Base::operator=(product); |
| } |
| #endif |
| |
| #ifndef EIGEN_NO_IO |
| 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; |
| } |
| #endif |
| |
| /** Destructor */ |
| inline ~SparseVector() {} |
| |
| /** Overloaded for performance */ |
| Scalar sum() const; |
| |
| public: |
| |
| /** \internal \deprecated use setZero() and reserve() */ |
| EIGEN_DEPRECATED void startFill(Index reserve) |
| { |
| setZero(); |
| m_data.reserve(reserve); |
| } |
| |
| /** \internal \deprecated use insertBack(Index,Index) */ |
| EIGEN_DEPRECATED Scalar& fill(Index r, Index c) |
| { |
| eigen_assert(r==0 || c==0); |
| return fill(IsColVector ? r : c); |
| } |
| |
| /** \internal \deprecated use insertBack(Index) */ |
| EIGEN_DEPRECATED Scalar& fill(Index i) |
| { |
| m_data.append(0, i); |
| return m_data.value(m_data.size()-1); |
| } |
| |
| /** \internal \deprecated use insert(Index,Index) */ |
| EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c) |
| { |
| eigen_assert(r==0 || c==0); |
| return fillrand(IsColVector ? r : c); |
| } |
| |
| /** \internal \deprecated use insert(Index) */ |
| EIGEN_DEPRECATED Scalar& fillrand(Index i) |
| { |
| return insert(i); |
| } |
| |
| /** \internal \deprecated use finalize() */ |
| EIGEN_DEPRECATED void endFill() {} |
| |
| // These two functions were here in the 3.1 release, so let's keep them in case some code rely on them. |
| /** \internal \deprecated use data() */ |
| EIGEN_DEPRECATED Storage& _data() { return m_data; } |
| /** \internal \deprecated use data() */ |
| EIGEN_DEPRECATED const Storage& _data() const { return m_data; } |
| |
| # ifdef EIGEN_SPARSEVECTOR_PLUGIN |
| # include EIGEN_SPARSEVECTOR_PLUGIN |
| # endif |
| |
| protected: |
| EIGEN_STATIC_ASSERT(NumTraits<StorageIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE) |
| EIGEN_STATIC_ASSERT((Options_&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS) |
| |
| Storage m_data; |
| Index m_size; |
| }; |
| |
| namespace internal { |
| |
| template<typename Scalar_, int Options_, typename Index_> |
| struct evaluator<SparseVector<Scalar_,Options_,Index_> > |
| : evaluator_base<SparseVector<Scalar_,Options_,Index_> > |
| { |
| typedef SparseVector<Scalar_,Options_,Index_> SparseVectorType; |
| typedef evaluator_base<SparseVectorType> Base; |
| typedef typename SparseVectorType::InnerIterator InnerIterator; |
| typedef typename SparseVectorType::ReverseInnerIterator ReverseInnerIterator; |
| |
| enum { |
| CoeffReadCost = NumTraits<Scalar_>::ReadCost, |
| Flags = SparseVectorType::Flags |
| }; |
| |
| evaluator() : Base() {} |
| |
| explicit evaluator(const SparseVectorType &mat) : m_matrix(&mat) |
| { |
| EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); |
| } |
| |
| inline Index nonZerosEstimate() const { |
| return m_matrix->nonZeros(); |
| } |
| |
| operator SparseVectorType&() { return m_matrix->const_cast_derived(); } |
| operator const SparseVectorType&() const { return *m_matrix; } |
| |
| const SparseVectorType *m_matrix; |
| }; |
| |
| template< typename Dest, typename Src> |
| struct sparse_vector_assign_selector<Dest,Src,SVA_Inner> { |
| static void run(Dest& dst, const Src& src) { |
| eigen_internal_assert(src.innerSize()==src.size()); |
| typedef internal::evaluator<Src> SrcEvaluatorType; |
| SrcEvaluatorType srcEval(src); |
| for(typename SrcEvaluatorType::InnerIterator it(srcEval, 0); it; ++it) |
| dst.insert(it.index()) = it.value(); |
| } |
| }; |
| |
| template< typename Dest, typename Src> |
| struct sparse_vector_assign_selector<Dest,Src,SVA_Outer> { |
| static void run(Dest& dst, const Src& src) { |
| eigen_internal_assert(src.outerSize()==src.size()); |
| typedef internal::evaluator<Src> SrcEvaluatorType; |
| SrcEvaluatorType srcEval(src); |
| for(Index i=0; i<src.size(); ++i) |
| { |
| typename SrcEvaluatorType::InnerIterator it(srcEval, i); |
| if(it) |
| dst.insert(i) = it.value(); |
| } |
| } |
| }; |
| |
| template< typename Dest, typename Src> |
| struct sparse_vector_assign_selector<Dest,Src,SVA_RuntimeSwitch> { |
| static void run(Dest& dst, const Src& src) { |
| if(src.outerSize()==1) sparse_vector_assign_selector<Dest,Src,SVA_Inner>::run(dst, src); |
| else sparse_vector_assign_selector<Dest,Src,SVA_Outer>::run(dst, src); |
| } |
| }; |
| |
| } |
| |
| } // end namespace Eigen |
| |
| #endif // EIGEN_SPARSEVECTOR_H |