diff options
Diffstat (limited to 'runtimes/nn/depend/external/eigen/Eigen/src/SparseCore/SparseMatrix.h')
| -rw-r--r-- | runtimes/nn/depend/external/eigen/Eigen/src/SparseCore/SparseMatrix.h | 1403 |
1 files changed, 0 insertions, 1403 deletions
diff --git a/runtimes/nn/depend/external/eigen/Eigen/src/SparseCore/SparseMatrix.h b/runtimes/nn/depend/external/eigen/Eigen/src/SparseCore/SparseMatrix.h deleted file mode 100644 index 323c2323b..000000000 --- a/runtimes/nn/depend/external/eigen/Eigen/src/SparseCore/SparseMatrix.h +++ /dev/null @@ -1,1403 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2014 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_SPARSEMATRIX_H -#define EIGEN_SPARSEMATRIX_H - -namespace Eigen { - -/** \ingroup SparseCore_Module - * - * \class SparseMatrix - * - * \brief A versatible sparse matrix representation - * - * This class implements a more versatile variants of the common \em compressed row/column storage format. - * Each colmun's (resp. row) non zeros are stored as a pair of value with associated row (resp. colmiun) index. - * All the non zeros are stored in a single large buffer. Unlike the \em compressed format, there might be extra - * space inbetween the nonzeros of two successive colmuns (resp. rows) such that insertion of new non-zero - * can be done with limited memory reallocation and copies. - * - * A call to the function makeCompressed() turns the matrix into the standard \em compressed format - * compatible with many library. - * - * More details on this storage sceheme are given in the \ref TutorialSparse "manual pages". - * - * \tparam _Scalar the scalar type, i.e. the type of the coefficients - * \tparam _Options Union of bit flags controlling the storage scheme. Currently the only possibility - * is ColMajor or RowMajor. The default is 0 which means column-major. - * \tparam _StorageIndex the type of the indices. It has to be a \b signed type (e.g., short, int, std::ptrdiff_t). Default is \c int. - * - * \warning In %Eigen 3.2, the undocumented type \c SparseMatrix::Index was improperly defined as the storage index type (e.g., int), - * whereas it is now (starting from %Eigen 3.3) deprecated and always defined as Eigen::Index. - * Codes making use of \c SparseMatrix::Index, might thus likely have to be changed to use \c SparseMatrix::StorageIndex instead. - * - * 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_SPARSEMATRIX_PLUGIN. - */ - -namespace internal { -template<typename _Scalar, int _Options, typename _StorageIndex> -struct traits<SparseMatrix<_Scalar, _Options, _StorageIndex> > -{ - typedef _Scalar Scalar; - typedef _StorageIndex StorageIndex; - typedef Sparse StorageKind; - typedef MatrixXpr XprKind; - enum { - RowsAtCompileTime = Dynamic, - ColsAtCompileTime = Dynamic, - MaxRowsAtCompileTime = Dynamic, - MaxColsAtCompileTime = Dynamic, - Flags = _Options | NestByRefBit | LvalueBit | CompressedAccessBit, - SupportedAccessPatterns = InnerRandomAccessPattern - }; -}; - -template<typename _Scalar, int _Options, typename _StorageIndex, int DiagIndex> -struct traits<Diagonal<SparseMatrix<_Scalar, _Options, _StorageIndex>, DiagIndex> > -{ - typedef SparseMatrix<_Scalar, _Options, _StorageIndex> MatrixType; - typedef typename ref_selector<MatrixType>::type MatrixTypeNested; - typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested; - - typedef _Scalar Scalar; - typedef Dense StorageKind; - typedef _StorageIndex StorageIndex; - typedef MatrixXpr XprKind; - - enum { - RowsAtCompileTime = Dynamic, - ColsAtCompileTime = 1, - MaxRowsAtCompileTime = Dynamic, - MaxColsAtCompileTime = 1, - Flags = LvalueBit - }; -}; - -template<typename _Scalar, int _Options, typename _StorageIndex, int DiagIndex> -struct traits<Diagonal<const SparseMatrix<_Scalar, _Options, _StorageIndex>, DiagIndex> > - : public traits<Diagonal<SparseMatrix<_Scalar, _Options, _StorageIndex>, DiagIndex> > -{ - enum { - Flags = 0 - }; -}; - -} // end namespace internal - -template<typename _Scalar, int _Options, typename _StorageIndex> -class SparseMatrix - : public SparseCompressedBase<SparseMatrix<_Scalar, _Options, _StorageIndex> > -{ - typedef SparseCompressedBase<SparseMatrix> Base; - using Base::convert_index; - friend class SparseVector<_Scalar,0,_StorageIndex>; - public: - using Base::isCompressed; - using Base::nonZeros; - EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix) - using Base::operator+=; - using Base::operator-=; - - typedef MappedSparseMatrix<Scalar,Flags> Map; - typedef Diagonal<SparseMatrix> DiagonalReturnType; - typedef Diagonal<const SparseMatrix> ConstDiagonalReturnType; - typedef typename Base::InnerIterator InnerIterator; - typedef typename Base::ReverseInnerIterator ReverseInnerIterator; - - - using Base::IsRowMajor; - typedef internal::CompressedStorage<Scalar,StorageIndex> Storage; - enum { - Options = _Options - }; - - typedef typename Base::IndexVector IndexVector; - typedef typename Base::ScalarVector ScalarVector; - protected: - typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix; - - Index m_outerSize; - Index m_innerSize; - StorageIndex* m_outerIndex; - StorageIndex* m_innerNonZeros; // optional, if null then the data is compressed - Storage m_data; - - public: - - /** \returns the number of rows of the matrix */ - inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; } - /** \returns the number of columns of the matrix */ - inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; } - - /** \returns the number of rows (resp. columns) of the matrix if the storage order column major (resp. row major) */ - inline Index innerSize() const { return m_innerSize; } - /** \returns the number of columns (resp. rows) of the matrix if the storage order column major (resp. row major) */ - inline Index outerSize() const { return m_outerSize; } - - /** \returns a const pointer to the array of values. - * This function is aimed at interoperability with other libraries. - * \sa innerIndexPtr(), outerIndexPtr() */ - inline const Scalar* valuePtr() const { return m_data.valuePtr(); } - /** \returns a non-const pointer to the array of values. - * This function is aimed at interoperability with other libraries. - * \sa innerIndexPtr(), outerIndexPtr() */ - inline Scalar* valuePtr() { return m_data.valuePtr(); } - - /** \returns a const pointer to the array of inner indices. - * This function is aimed at interoperability with other libraries. - * \sa valuePtr(), outerIndexPtr() */ - inline const StorageIndex* innerIndexPtr() const { return m_data.indexPtr(); } - /** \returns a non-const pointer to the array of inner indices. - * This function is aimed at interoperability with other libraries. - * \sa valuePtr(), outerIndexPtr() */ - inline StorageIndex* innerIndexPtr() { return m_data.indexPtr(); } - - /** \returns a const pointer to the array of the starting positions of the inner vectors. - * This function is aimed at interoperability with other libraries. - * \sa valuePtr(), innerIndexPtr() */ - inline const StorageIndex* outerIndexPtr() const { return m_outerIndex; } - /** \returns a non-const pointer to the array of the starting positions of the inner vectors. - * This function is aimed at interoperability with other libraries. - * \sa valuePtr(), innerIndexPtr() */ - inline StorageIndex* outerIndexPtr() { return m_outerIndex; } - - /** \returns a const pointer to the array of the number of non zeros of the inner vectors. - * This function is aimed at interoperability with other libraries. - * \warning it returns the null pointer 0 in compressed mode */ - inline const StorageIndex* innerNonZeroPtr() const { return m_innerNonZeros; } - /** \returns a non-const pointer to the array of the number of non zeros of the inner vectors. - * This function is aimed at interoperability with other libraries. - * \warning it returns the null pointer 0 in compressed mode */ - inline StorageIndex* innerNonZeroPtr() { return m_innerNonZeros; } - - /** \internal */ - inline Storage& data() { return m_data; } - /** \internal */ - inline const Storage& data() const { return m_data; } - - /** \returns the value of the matrix at position \a i, \a j - * This function returns Scalar(0) if the element is an explicit \em zero */ - inline Scalar coeff(Index row, Index col) const - { - eigen_assert(row>=0 && row<rows() && col>=0 && col<cols()); - - const Index outer = IsRowMajor ? row : col; - const Index inner = IsRowMajor ? col : row; - Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1]; - return m_data.atInRange(m_outerIndex[outer], end, StorageIndex(inner)); - } - - /** \returns a non-const reference to the value of the matrix at position \a i, \a j - * - * If the element does not exist then it is inserted via the insert(Index,Index) function - * which itself turns the matrix into a non compressed form if that was not the case. - * - * This is a O(log(nnz_j)) operation (binary search) plus the cost of insert(Index,Index) - * function if the element does not already exist. - */ - inline Scalar& coeffRef(Index row, Index col) - { - eigen_assert(row>=0 && row<rows() && col>=0 && col<cols()); - - const Index outer = IsRowMajor ? row : col; - const Index inner = IsRowMajor ? col : row; - - Index start = m_outerIndex[outer]; - Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1]; - eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix"); - if(end<=start) - return insert(row,col); - const Index p = m_data.searchLowerIndex(start,end-1,StorageIndex(inner)); - if((p<end) && (m_data.index(p)==inner)) - return m_data.value(p); - else - return insert(row,col); - } - - /** \returns a reference to a novel non zero coefficient with coordinates \a row x \a col. - * The non zero coefficient must \b not already exist. - * - * If the matrix \c *this is in compressed mode, then \c *this is turned into uncompressed - * mode while reserving room for 2 x this->innerSize() non zeros if reserve(Index) has not been called earlier. - * In this case, the insertion procedure is optimized for a \e sequential insertion mode where elements are assumed to be - * inserted by increasing outer-indices. - * - * If that's not the case, then it is strongly recommended to either use a triplet-list to assemble the matrix, or to first - * call reserve(const SizesType &) to reserve the appropriate number of non-zero elements per inner vector. - * - * Assuming memory has been appropriately reserved, this function performs a sorted insertion in O(1) - * if the elements of each inner vector are inserted in increasing inner index order, and in O(nnz_j) for a random insertion. - * - */ - Scalar& insert(Index row, Index col); - - public: - - /** Removes all non zeros but keep allocated memory - * - * This function does not free the currently allocated memory. To release as much as memory as possible, - * call \code mat.data().squeeze(); \endcode after resizing it. - * - * \sa resize(Index,Index), data() - */ - inline void setZero() - { - m_data.clear(); - memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(StorageIndex)); - if(m_innerNonZeros) - memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(StorageIndex)); - } - - /** Preallocates \a reserveSize non zeros. - * - * Precondition: the matrix must be in compressed mode. */ - inline void reserve(Index reserveSize) - { - eigen_assert(isCompressed() && "This function does not make sense in non compressed mode."); - m_data.reserve(reserveSize); - } - - #ifdef EIGEN_PARSED_BY_DOXYGEN - /** Preallocates \a reserveSize[\c j] non zeros for each column (resp. row) \c j. - * - * This function turns the matrix in non-compressed mode. - * - * The type \c SizesType must expose the following interface: - \code - typedef value_type; - const value_type& operator[](i) const; - \endcode - * for \c i in the [0,this->outerSize()[ range. - * Typical choices include std::vector<int>, Eigen::VectorXi, Eigen::VectorXi::Constant, etc. - */ - template<class SizesType> - inline void reserve(const SizesType& reserveSizes); - #else - template<class SizesType> - inline void reserve(const SizesType& reserveSizes, const typename SizesType::value_type& enableif = - #if (!EIGEN_COMP_MSVC) || (EIGEN_COMP_MSVC>=1500) // MSVC 2005 fails to compile with this typename - typename - #endif - SizesType::value_type()) - { - EIGEN_UNUSED_VARIABLE(enableif); - reserveInnerVectors(reserveSizes); - } - #endif // EIGEN_PARSED_BY_DOXYGEN - protected: - template<class SizesType> - inline void reserveInnerVectors(const SizesType& reserveSizes) - { - if(isCompressed()) - { - Index totalReserveSize = 0; - // turn the matrix into non-compressed mode - m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex))); - if (!m_innerNonZeros) internal::throw_std_bad_alloc(); - - // temporarily use m_innerSizes to hold the new starting points. - StorageIndex* newOuterIndex = m_innerNonZeros; - - StorageIndex count = 0; - for(Index j=0; j<m_outerSize; ++j) - { - newOuterIndex[j] = count; - count += reserveSizes[j] + (m_outerIndex[j+1]-m_outerIndex[j]); - totalReserveSize += reserveSizes[j]; - } - m_data.reserve(totalReserveSize); - StorageIndex previousOuterIndex = m_outerIndex[m_outerSize]; - for(Index j=m_outerSize-1; j>=0; --j) - { - StorageIndex innerNNZ = previousOuterIndex - m_outerIndex[j]; - for(Index i=innerNNZ-1; i>=0; --i) - { - m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i); - m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i); - } - previousOuterIndex = m_outerIndex[j]; - m_outerIndex[j] = newOuterIndex[j]; - m_innerNonZeros[j] = innerNNZ; - } - m_outerIndex[m_outerSize] = m_outerIndex[m_outerSize-1] + m_innerNonZeros[m_outerSize-1] + reserveSizes[m_outerSize-1]; - - m_data.resize(m_outerIndex[m_outerSize]); - } - else - { - StorageIndex* newOuterIndex = static_cast<StorageIndex*>(std::malloc((m_outerSize+1)*sizeof(StorageIndex))); - if (!newOuterIndex) internal::throw_std_bad_alloc(); - - StorageIndex count = 0; - for(Index j=0; j<m_outerSize; ++j) - { - newOuterIndex[j] = count; - StorageIndex alreadyReserved = (m_outerIndex[j+1]-m_outerIndex[j]) - m_innerNonZeros[j]; - StorageIndex toReserve = std::max<StorageIndex>(reserveSizes[j], alreadyReserved); - count += toReserve + m_innerNonZeros[j]; - } - newOuterIndex[m_outerSize] = count; - - m_data.resize(count); - for(Index j=m_outerSize-1; j>=0; --j) - { - Index offset = newOuterIndex[j] - m_outerIndex[j]; - if(offset>0) - { - StorageIndex innerNNZ = m_innerNonZeros[j]; - for(Index i=innerNNZ-1; i>=0; --i) - { - m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i); - m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i); - } - } - } - - std::swap(m_outerIndex, newOuterIndex); - std::free(newOuterIndex); - } - - } - public: - - //--- low level purely coherent filling --- - - /** \internal - * \returns a reference to the non zero coefficient at position \a row, \a col assuming that: - * - the nonzero does not already exist - * - the new coefficient is the last one according to the storage order - * - * Before filling a given inner vector you must call the statVec(Index) function. - * - * After an insertion session, you should call the finalize() function. - * - * \sa insert, insertBackByOuterInner, startVec */ - inline Scalar& insertBack(Index row, Index col) - { - return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row); - } - - /** \internal - * \sa insertBack, startVec */ - inline Scalar& insertBackByOuterInner(Index outer, Index inner) - { - eigen_assert(Index(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)"); - eigen_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)<inner) && "Invalid ordered insertion (invalid inner index)"); - Index p = m_outerIndex[outer+1]; - ++m_outerIndex[outer+1]; - m_data.append(Scalar(0), inner); - return m_data.value(p); - } - - /** \internal - * \warning use it only if you know what you are doing */ - inline Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner) - { - Index p = m_outerIndex[outer+1]; - ++m_outerIndex[outer+1]; - m_data.append(Scalar(0), inner); - return m_data.value(p); - } - - /** \internal - * \sa insertBack, insertBackByOuterInner */ - inline void startVec(Index outer) - { - eigen_assert(m_outerIndex[outer]==Index(m_data.size()) && "You must call startVec for each inner vector sequentially"); - eigen_assert(m_outerIndex[outer+1]==0 && "You must call startVec for each inner vector sequentially"); - m_outerIndex[outer+1] = m_outerIndex[outer]; - } - - /** \internal - * Must be called after inserting a set of non zero entries using the low level compressed API. - */ - inline void finalize() - { - if(isCompressed()) - { - StorageIndex size = internal::convert_index<StorageIndex>(m_data.size()); - Index i = m_outerSize; - // find the last filled column - while (i>=0 && m_outerIndex[i]==0) - --i; - ++i; - while (i<=m_outerSize) - { - m_outerIndex[i] = size; - ++i; - } - } - } - - //--- - - template<typename InputIterators> - void setFromTriplets(const InputIterators& begin, const InputIterators& end); - - template<typename InputIterators,typename DupFunctor> - void setFromTriplets(const InputIterators& begin, const InputIterators& end, DupFunctor dup_func); - - void sumupDuplicates() { collapseDuplicates(internal::scalar_sum_op<Scalar,Scalar>()); } - - template<typename DupFunctor> - void collapseDuplicates(DupFunctor dup_func = DupFunctor()); - - //--- - - /** \internal - * same as insert(Index,Index) except that the indices are given relative to the storage order */ - Scalar& insertByOuterInner(Index j, Index i) - { - return insert(IsRowMajor ? j : i, IsRowMajor ? i : j); - } - - /** Turns the matrix into the \em compressed format. - */ - void makeCompressed() - { - if(isCompressed()) - return; - - eigen_internal_assert(m_outerIndex!=0 && m_outerSize>0); - - Index oldStart = m_outerIndex[1]; - m_outerIndex[1] = m_innerNonZeros[0]; - for(Index j=1; j<m_outerSize; ++j) - { - Index nextOldStart = m_outerIndex[j+1]; - Index offset = oldStart - m_outerIndex[j]; - if(offset>0) - { - for(Index k=0; k<m_innerNonZeros[j]; ++k) - { - m_data.index(m_outerIndex[j]+k) = m_data.index(oldStart+k); - m_data.value(m_outerIndex[j]+k) = m_data.value(oldStart+k); - } - } - m_outerIndex[j+1] = m_outerIndex[j] + m_innerNonZeros[j]; - oldStart = nextOldStart; - } - std::free(m_innerNonZeros); - m_innerNonZeros = 0; - m_data.resize(m_outerIndex[m_outerSize]); - m_data.squeeze(); - } - - /** Turns the matrix into the uncompressed mode */ - void uncompress() - { - if(m_innerNonZeros != 0) - return; - m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex))); - for (Index i = 0; i < m_outerSize; i++) - { - m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i]; - } - } - - /** Suppresses all nonzeros which are \b much \b smaller \b than \a reference under the tolerence \a epsilon */ - void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) - { - prune(default_prunning_func(reference,epsilon)); - } - - /** Turns the matrix into compressed format, and suppresses all nonzeros which do not satisfy the predicate \a keep. - * The functor type \a KeepFunc must implement the following function: - * \code - * bool operator() (const Index& row, const Index& col, const Scalar& value) const; - * \endcode - * \sa prune(Scalar,RealScalar) - */ - template<typename KeepFunc> - void prune(const KeepFunc& keep = KeepFunc()) - { - // TODO optimize the uncompressed mode to avoid moving and allocating the data twice - makeCompressed(); - - StorageIndex k = 0; - for(Index j=0; j<m_outerSize; ++j) - { - Index previousStart = m_outerIndex[j]; - m_outerIndex[j] = k; - Index end = m_outerIndex[j+1]; - for(Index i=previousStart; i<end; ++i) - { - if(keep(IsRowMajor?j:m_data.index(i), IsRowMajor?m_data.index(i):j, m_data.value(i))) - { - m_data.value(k) = m_data.value(i); - m_data.index(k) = m_data.index(i); - ++k; - } - } - } - m_outerIndex[m_outerSize] = k; - m_data.resize(k,0); - } - - /** Resizes the matrix to a \a rows x \a cols matrix leaving old values untouched. - * - * If the sizes of the matrix are decreased, then the matrix is turned to \b uncompressed-mode - * and the storage of the out of bounds coefficients is kept and reserved. - * Call makeCompressed() to pack the entries and squeeze extra memory. - * - * \sa reserve(), setZero(), makeCompressed() - */ - void conservativeResize(Index rows, Index cols) - { - // No change - if (this->rows() == rows && this->cols() == cols) return; - - // If one dimension is null, then there is nothing to be preserved - if(rows==0 || cols==0) return resize(rows,cols); - - Index innerChange = IsRowMajor ? cols - this->cols() : rows - this->rows(); - Index outerChange = IsRowMajor ? rows - this->rows() : cols - this->cols(); - StorageIndex newInnerSize = convert_index(IsRowMajor ? cols : rows); - - // Deals with inner non zeros - if (m_innerNonZeros) - { - // Resize m_innerNonZeros - StorageIndex *newInnerNonZeros = static_cast<StorageIndex*>(std::realloc(m_innerNonZeros, (m_outerSize + outerChange) * sizeof(StorageIndex))); - if (!newInnerNonZeros) internal::throw_std_bad_alloc(); - m_innerNonZeros = newInnerNonZeros; - - for(Index i=m_outerSize; i<m_outerSize+outerChange; i++) - m_innerNonZeros[i] = 0; - } - else if (innerChange < 0) - { - // Inner size decreased: allocate a new m_innerNonZeros - m_innerNonZeros = static_cast<StorageIndex*>(std::malloc((m_outerSize+outerChange+1) * sizeof(StorageIndex))); - if (!m_innerNonZeros) internal::throw_std_bad_alloc(); - for(Index i = 0; i < m_outerSize; i++) - m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i]; - } - - // Change the m_innerNonZeros in case of a decrease of inner size - if (m_innerNonZeros && innerChange < 0) - { - for(Index i = 0; i < m_outerSize + (std::min)(outerChange, Index(0)); i++) - { - StorageIndex &n = m_innerNonZeros[i]; - StorageIndex start = m_outerIndex[i]; - while (n > 0 && m_data.index(start+n-1) >= newInnerSize) --n; - } - } - - m_innerSize = newInnerSize; - - // Re-allocate outer index structure if necessary - if (outerChange == 0) - return; - - StorageIndex *newOuterIndex = static_cast<StorageIndex*>(std::realloc(m_outerIndex, (m_outerSize + outerChange + 1) * sizeof(StorageIndex))); - if (!newOuterIndex) internal::throw_std_bad_alloc(); - m_outerIndex = newOuterIndex; - if (outerChange > 0) - { - StorageIndex last = m_outerSize == 0 ? 0 : m_outerIndex[m_outerSize]; - for(Index i=m_outerSize; i<m_outerSize+outerChange+1; i++) - m_outerIndex[i] = last; - } - m_outerSize += outerChange; - } - - /** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero. - * - * This function does not free the currently allocated memory. To release as much as memory as possible, - * call \code mat.data().squeeze(); \endcode after resizing it. - * - * \sa reserve(), setZero() - */ - void resize(Index rows, Index cols) - { - const Index outerSize = IsRowMajor ? rows : cols; - m_innerSize = IsRowMajor ? cols : rows; - m_data.clear(); - if (m_outerSize != outerSize || m_outerSize==0) - { - std::free(m_outerIndex); - m_outerIndex = static_cast<StorageIndex*>(std::malloc((outerSize + 1) * sizeof(StorageIndex))); - if (!m_outerIndex) internal::throw_std_bad_alloc(); - - m_outerSize = outerSize; - } - if(m_innerNonZeros) - { - std::free(m_innerNonZeros); - m_innerNonZeros = 0; - } - memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(StorageIndex)); - } - - /** \internal - * Resize the nonzero vector to \a size */ - void resizeNonZeros(Index size) - { - m_data.resize(size); - } - - /** \returns a const expression of the diagonal coefficients. */ - const ConstDiagonalReturnType diagonal() const { return ConstDiagonalReturnType(*this); } - - /** \returns a read-write expression of the diagonal coefficients. - * \warning If the diagonal entries are written, then all diagonal - * entries \b must already exist, otherwise an assertion will be raised. - */ - DiagonalReturnType diagonal() { return DiagonalReturnType(*this); } - - /** Default constructor yielding an empty \c 0 \c x \c 0 matrix */ - inline SparseMatrix() - : m_outerSize(-1), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) - { - check_template_parameters(); - resize(0, 0); - } - - /** Constructs a \a rows \c x \a cols empty matrix */ - inline SparseMatrix(Index rows, Index cols) - : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) - { - check_template_parameters(); - resize(rows, cols); - } - - /** Constructs a sparse matrix from the sparse expression \a other */ - template<typename OtherDerived> - inline SparseMatrix(const SparseMatrixBase<OtherDerived>& other) - : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) - { - EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value), - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - check_template_parameters(); - const bool needToTranspose = (Flags & RowMajorBit) != (internal::evaluator<OtherDerived>::Flags & RowMajorBit); - if (needToTranspose) - *this = other.derived(); - else - { - #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN - EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN - #endif - internal::call_assignment_no_alias(*this, other.derived()); - } - } - - /** Constructs a sparse matrix from the sparse selfadjoint view \a other */ - template<typename OtherDerived, unsigned int UpLo> - inline SparseMatrix(const SparseSelfAdjointView<OtherDerived, UpLo>& other) - : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) - { - check_template_parameters(); - Base::operator=(other); - } - - /** Copy constructor (it performs a deep copy) */ - inline SparseMatrix(const SparseMatrix& other) - : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) - { - check_template_parameters(); - *this = other.derived(); - } - - /** \brief Copy constructor with in-place evaluation */ - template<typename OtherDerived> - SparseMatrix(const ReturnByValue<OtherDerived>& other) - : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) - { - check_template_parameters(); - initAssignment(other); - other.evalTo(*this); - } - - /** \brief Copy constructor with in-place evaluation */ - template<typename OtherDerived> - explicit SparseMatrix(const DiagonalBase<OtherDerived>& other) - : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) - { - check_template_parameters(); - *this = other.derived(); - } - - /** Swaps the content of two sparse matrices of the same type. - * This is a fast operation that simply swaps the underlying pointers and parameters. */ - inline void swap(SparseMatrix& other) - { - //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n"); - std::swap(m_outerIndex, other.m_outerIndex); - std::swap(m_innerSize, other.m_innerSize); - std::swap(m_outerSize, other.m_outerSize); - std::swap(m_innerNonZeros, other.m_innerNonZeros); - m_data.swap(other.m_data); - } - - /** Sets *this to the identity matrix. - * This function also turns the matrix into compressed mode, and drop any reserved memory. */ - inline void setIdentity() - { - eigen_assert(rows() == cols() && "ONLY FOR SQUARED MATRICES"); - this->m_data.resize(rows()); - Eigen::Map<IndexVector>(this->m_data.indexPtr(), rows()).setLinSpaced(0, StorageIndex(rows()-1)); - Eigen::Map<ScalarVector>(this->m_data.valuePtr(), rows()).setOnes(); - Eigen::Map<IndexVector>(this->m_outerIndex, rows()+1).setLinSpaced(0, StorageIndex(rows())); - std::free(m_innerNonZeros); - m_innerNonZeros = 0; - } - inline SparseMatrix& operator=(const SparseMatrix& other) - { - if (other.isRValue()) - { - swap(other.const_cast_derived()); - } - else if(this!=&other) - { - #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN - EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN - #endif - initAssignment(other); - if(other.isCompressed()) - { - internal::smart_copy(other.m_outerIndex, other.m_outerIndex + m_outerSize + 1, m_outerIndex); - m_data = other.m_data; - } - else - { - Base::operator=(other); - } - } - return *this; - } - -#ifndef EIGEN_PARSED_BY_DOXYGEN - template<typename OtherDerived> - inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other) - { return Base::operator=(other.derived()); } -#endif // EIGEN_PARSED_BY_DOXYGEN - - template<typename OtherDerived> - EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other); - - friend std::ostream & operator << (std::ostream & s, const SparseMatrix& m) - { - EIGEN_DBG_SPARSE( - s << "Nonzero entries:\n"; - if(m.isCompressed()) - { - for (Index i=0; i<m.nonZeros(); ++i) - s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") "; - } - else - { - for (Index i=0; i<m.outerSize(); ++i) - { - Index p = m.m_outerIndex[i]; - Index pe = m.m_outerIndex[i]+m.m_innerNonZeros[i]; - Index k=p; - for (; k<pe; ++k) { - s << "(" << m.m_data.value(k) << "," << m.m_data.index(k) << ") "; - } - for (; k<m.m_outerIndex[i+1]; ++k) { - s << "(_,_) "; - } - } - } - s << std::endl; - s << std::endl; - s << "Outer pointers:\n"; - for (Index i=0; i<m.outerSize(); ++i) { - s << m.m_outerIndex[i] << " "; - } - s << " $" << std::endl; - if(!m.isCompressed()) - { - s << "Inner non zeros:\n"; - for (Index i=0; i<m.outerSize(); ++i) { - s << m.m_innerNonZeros[i] << " "; - } - s << " $" << std::endl; - } - s << std::endl; - ); - s << static_cast<const SparseMatrixBase<SparseMatrix>&>(m); - return s; - } - - /** Destructor */ - inline ~SparseMatrix() - { - std::free(m_outerIndex); - std::free(m_innerNonZeros); - } - - /** Overloaded for performance */ - Scalar sum() const; - -# ifdef EIGEN_SPARSEMATRIX_PLUGIN -# include EIGEN_SPARSEMATRIX_PLUGIN -# endif - -protected: - - template<typename Other> - void initAssignment(const Other& other) - { - resize(other.rows(), other.cols()); - if(m_innerNonZeros) - { - std::free(m_innerNonZeros); - m_innerNonZeros = 0; - } - } - - /** \internal - * \sa insert(Index,Index) */ - EIGEN_DONT_INLINE Scalar& insertCompressed(Index row, Index col); - - /** \internal - * A vector object that is equal to 0 everywhere but v at the position i */ - class SingletonVector - { - StorageIndex m_index; - StorageIndex m_value; - public: - typedef StorageIndex value_type; - SingletonVector(Index i, Index v) - : m_index(convert_index(i)), m_value(convert_index(v)) - {} - - StorageIndex operator[](Index i) const { return i==m_index ? m_value : 0; } - }; - - /** \internal - * \sa insert(Index,Index) */ - EIGEN_DONT_INLINE Scalar& insertUncompressed(Index row, Index col); - -public: - /** \internal - * \sa insert(Index,Index) */ - EIGEN_STRONG_INLINE Scalar& insertBackUncompressed(Index row, Index col) - { - const Index outer = IsRowMajor ? row : col; - const Index inner = IsRowMajor ? col : row; - - eigen_assert(!isCompressed()); - eigen_assert(m_innerNonZeros[outer]<=(m_outerIndex[outer+1] - m_outerIndex[outer])); - - Index p = m_outerIndex[outer] + m_innerNonZeros[outer]++; - m_data.index(p) = convert_index(inner); - return (m_data.value(p) = 0); - } - -private: - static void check_template_parameters() - { - 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); - } - - struct default_prunning_func { - default_prunning_func(const Scalar& ref, const RealScalar& eps) : reference(ref), epsilon(eps) {} - inline bool operator() (const Index&, const Index&, const Scalar& value) const - { - return !internal::isMuchSmallerThan(value, reference, epsilon); - } - Scalar reference; - RealScalar epsilon; - }; -}; - -namespace internal { - -template<typename InputIterator, typename SparseMatrixType, typename DupFunctor> -void set_from_triplets(const InputIterator& begin, const InputIterator& end, SparseMatrixType& mat, DupFunctor dup_func) -{ - enum { IsRowMajor = SparseMatrixType::IsRowMajor }; - typedef typename SparseMatrixType::Scalar Scalar; - typedef typename SparseMatrixType::StorageIndex StorageIndex; - SparseMatrix<Scalar,IsRowMajor?ColMajor:RowMajor,StorageIndex> trMat(mat.rows(),mat.cols()); - - if(begin!=end) - { - // pass 1: count the nnz per inner-vector - typename SparseMatrixType::IndexVector wi(trMat.outerSize()); - wi.setZero(); - for(InputIterator it(begin); it!=end; ++it) - { - eigen_assert(it->row()>=0 && it->row()<mat.rows() && it->col()>=0 && it->col()<mat.cols()); - wi(IsRowMajor ? it->col() : it->row())++; - } - - // pass 2: insert all the elements into trMat - trMat.reserve(wi); - for(InputIterator it(begin); it!=end; ++it) - trMat.insertBackUncompressed(it->row(),it->col()) = it->value(); - - // pass 3: - trMat.collapseDuplicates(dup_func); - } - - // pass 4: transposed copy -> implicit sorting - mat = trMat; -} - -} - - -/** Fill the matrix \c *this with the list of \em triplets defined by the iterator range \a begin - \a end. - * - * A \em triplet is a tuple (i,j,value) defining a non-zero element. - * The input list of triplets does not have to be sorted, and can contains duplicated elements. - * In any case, the result is a \b sorted and \b compressed sparse matrix where the duplicates have been summed up. - * This is a \em O(n) operation, with \em n the number of triplet elements. - * The initial contents of \c *this is destroyed. - * The matrix \c *this must be properly resized beforehand using the SparseMatrix(Index,Index) constructor, - * or the resize(Index,Index) method. The sizes are not extracted from the triplet list. - * - * The \a InputIterators value_type must provide the following interface: - * \code - * Scalar value() const; // the value - * Scalar row() const; // the row index i - * Scalar col() const; // the column index j - * \endcode - * See for instance the Eigen::Triplet template class. - * - * Here is a typical usage example: - * \code - typedef Triplet<double> T; - std::vector<T> tripletList; - triplets.reserve(estimation_of_entries); - for(...) - { - // ... - tripletList.push_back(T(i,j,v_ij)); - } - SparseMatrixType m(rows,cols); - m.setFromTriplets(tripletList.begin(), tripletList.end()); - // m is ready to go! - * \endcode - * - * \warning The list of triplets is read multiple times (at least twice). Therefore, it is not recommended to define - * an abstract iterator over a complex data-structure that would be expensive to evaluate. The triplets should rather - * be explicitely stored into a std::vector for instance. - */ -template<typename Scalar, int _Options, typename _StorageIndex> -template<typename InputIterators> -void SparseMatrix<Scalar,_Options,_StorageIndex>::setFromTriplets(const InputIterators& begin, const InputIterators& end) -{ - internal::set_from_triplets<InputIterators, SparseMatrix<Scalar,_Options,_StorageIndex> >(begin, end, *this, internal::scalar_sum_op<Scalar,Scalar>()); -} - -/** The same as setFromTriplets but when duplicates are met the functor \a dup_func is applied: - * \code - * value = dup_func(OldValue, NewValue) - * \endcode - * Here is a C++11 example keeping the latest entry only: - * \code - * mat.setFromTriplets(triplets.begin(), triplets.end(), [] (const Scalar&,const Scalar &b) { return b; }); - * \endcode - */ -template<typename Scalar, int _Options, typename _StorageIndex> -template<typename InputIterators,typename DupFunctor> -void SparseMatrix<Scalar,_Options,_StorageIndex>::setFromTriplets(const InputIterators& begin, const InputIterators& end, DupFunctor dup_func) -{ - internal::set_from_triplets<InputIterators, SparseMatrix<Scalar,_Options,_StorageIndex>, DupFunctor>(begin, end, *this, dup_func); -} - -/** \internal */ -template<typename Scalar, int _Options, typename _StorageIndex> -template<typename DupFunctor> -void SparseMatrix<Scalar,_Options,_StorageIndex>::collapseDuplicates(DupFunctor dup_func) -{ - eigen_assert(!isCompressed()); - // TODO, in practice we should be able to use m_innerNonZeros for that task - IndexVector wi(innerSize()); - wi.fill(-1); - StorageIndex count = 0; - // for each inner-vector, wi[inner_index] will hold the position of first element into the index/value buffers - for(Index j=0; j<outerSize(); ++j) - { - StorageIndex start = count; - Index oldEnd = m_outerIndex[j]+m_innerNonZeros[j]; - for(Index k=m_outerIndex[j]; k<oldEnd; ++k) - { - Index i = m_data.index(k); - if(wi(i)>=start) - { - // we already meet this entry => accumulate it - m_data.value(wi(i)) = dup_func(m_data.value(wi(i)), m_data.value(k)); - } - else - { - m_data.value(count) = m_data.value(k); - m_data.index(count) = m_data.index(k); - wi(i) = count; - ++count; - } - } - m_outerIndex[j] = start; - } - m_outerIndex[m_outerSize] = count; - - // turn the matrix into compressed form - std::free(m_innerNonZeros); - m_innerNonZeros = 0; - m_data.resize(m_outerIndex[m_outerSize]); -} - -template<typename Scalar, int _Options, typename _StorageIndex> -template<typename OtherDerived> -EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_StorageIndex>& SparseMatrix<Scalar,_Options,_StorageIndex>::operator=(const SparseMatrixBase<OtherDerived>& other) -{ - EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value), - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - - #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN - EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN - #endif - - const bool needToTranspose = (Flags & RowMajorBit) != (internal::evaluator<OtherDerived>::Flags & RowMajorBit); - if (needToTranspose) - { - #ifdef EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN - EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN - #endif - // two passes algorithm: - // 1 - compute the number of coeffs per dest inner vector - // 2 - do the actual copy/eval - // Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed - typedef typename internal::nested_eval<OtherDerived,2,typename internal::plain_matrix_type<OtherDerived>::type >::type OtherCopy; - typedef typename internal::remove_all<OtherCopy>::type _OtherCopy; - typedef internal::evaluator<_OtherCopy> OtherCopyEval; - OtherCopy otherCopy(other.derived()); - OtherCopyEval otherCopyEval(otherCopy); - - SparseMatrix dest(other.rows(),other.cols()); - Eigen::Map<IndexVector> (dest.m_outerIndex,dest.outerSize()).setZero(); - - // pass 1 - // FIXME the above copy could be merged with that pass - for (Index j=0; j<otherCopy.outerSize(); ++j) - for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it) - ++dest.m_outerIndex[it.index()]; - - // prefix sum - StorageIndex count = 0; - IndexVector positions(dest.outerSize()); - for (Index j=0; j<dest.outerSize(); ++j) - { - StorageIndex tmp = dest.m_outerIndex[j]; - dest.m_outerIndex[j] = count; - positions[j] = count; - count += tmp; - } - dest.m_outerIndex[dest.outerSize()] = count; - // alloc - dest.m_data.resize(count); - // pass 2 - for (StorageIndex j=0; j<otherCopy.outerSize(); ++j) - { - for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it) - { - Index pos = positions[it.index()]++; - dest.m_data.index(pos) = j; - dest.m_data.value(pos) = it.value(); - } - } - this->swap(dest); - return *this; - } - else - { - if(other.isRValue()) - { - initAssignment(other.derived()); - } - // there is no special optimization - return Base::operator=(other.derived()); - } -} - -template<typename _Scalar, int _Options, typename _StorageIndex> -typename SparseMatrix<_Scalar,_Options,_StorageIndex>::Scalar& SparseMatrix<_Scalar,_Options,_StorageIndex>::insert(Index row, Index col) -{ - eigen_assert(row>=0 && row<rows() && col>=0 && col<cols()); - - const Index outer = IsRowMajor ? row : col; - const Index inner = IsRowMajor ? col : row; - - if(isCompressed()) - { - if(nonZeros()==0) - { - // reserve space if not already done - if(m_data.allocatedSize()==0) - m_data.reserve(2*m_innerSize); - - // turn the matrix into non-compressed mode - m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex))); - if(!m_innerNonZeros) internal::throw_std_bad_alloc(); - - memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(StorageIndex)); - - // pack all inner-vectors to the end of the pre-allocated space - // and allocate the entire free-space to the first inner-vector - StorageIndex end = convert_index(m_data.allocatedSize()); - for(Index j=1; j<=m_outerSize; ++j) - m_outerIndex[j] = end; - } - else - { - // turn the matrix into non-compressed mode - m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex))); - if(!m_innerNonZeros) internal::throw_std_bad_alloc(); - for(Index j=0; j<m_outerSize; ++j) - m_innerNonZeros[j] = m_outerIndex[j+1]-m_outerIndex[j]; - } - } - - // check whether we can do a fast "push back" insertion - Index data_end = m_data.allocatedSize(); - - // First case: we are filling a new inner vector which is packed at the end. - // We assume that all remaining inner-vectors are also empty and packed to the end. - if(m_outerIndex[outer]==data_end) - { - eigen_internal_assert(m_innerNonZeros[outer]==0); - - // pack previous empty inner-vectors to end of the used-space - // and allocate the entire free-space to the current inner-vector. - StorageIndex p = convert_index(m_data.size()); - Index j = outer; - while(j>=0 && m_innerNonZeros[j]==0) - m_outerIndex[j--] = p; - - // push back the new element - ++m_innerNonZeros[outer]; - m_data.append(Scalar(0), inner); - - // check for reallocation - if(data_end != m_data.allocatedSize()) - { - // m_data has been reallocated - // -> move remaining inner-vectors back to the end of the free-space - // so that the entire free-space is allocated to the current inner-vector. - eigen_internal_assert(data_end < m_data.allocatedSize()); - StorageIndex new_end = convert_index(m_data.allocatedSize()); - for(Index k=outer+1; k<=m_outerSize; ++k) - if(m_outerIndex[k]==data_end) - m_outerIndex[k] = new_end; - } - return m_data.value(p); - } - - // Second case: the next inner-vector is packed to the end - // and the current inner-vector end match the used-space. - if(m_outerIndex[outer+1]==data_end && m_outerIndex[outer]+m_innerNonZeros[outer]==m_data.size()) - { - eigen_internal_assert(outer+1==m_outerSize || m_innerNonZeros[outer+1]==0); - - // add space for the new element - ++m_innerNonZeros[outer]; - m_data.resize(m_data.size()+1); - - // check for reallocation - if(data_end != m_data.allocatedSize()) - { - // m_data has been reallocated - // -> move remaining inner-vectors back to the end of the free-space - // so that the entire free-space is allocated to the current inner-vector. - eigen_internal_assert(data_end < m_data.allocatedSize()); - StorageIndex new_end = convert_index(m_data.allocatedSize()); - for(Index k=outer+1; k<=m_outerSize; ++k) - if(m_outerIndex[k]==data_end) - m_outerIndex[k] = new_end; - } - - // and insert it at the right position (sorted insertion) - Index startId = m_outerIndex[outer]; - Index p = m_outerIndex[outer]+m_innerNonZeros[outer]-1; - while ( (p > startId) && (m_data.index(p-1) > inner) ) - { - m_data.index(p) = m_data.index(p-1); - m_data.value(p) = m_data.value(p-1); - --p; - } - - m_data.index(p) = convert_index(inner); - return (m_data.value(p) = 0); - } - - if(m_data.size() != m_data.allocatedSize()) - { - // make sure the matrix is compatible to random un-compressed insertion: - m_data.resize(m_data.allocatedSize()); - this->reserveInnerVectors(Array<StorageIndex,Dynamic,1>::Constant(m_outerSize, 2)); - } - - return insertUncompressed(row,col); -} - -template<typename _Scalar, int _Options, typename _StorageIndex> -EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_StorageIndex>::Scalar& SparseMatrix<_Scalar,_Options,_StorageIndex>::insertUncompressed(Index row, Index col) -{ - eigen_assert(!isCompressed()); - - const Index outer = IsRowMajor ? row : col; - const StorageIndex inner = convert_index(IsRowMajor ? col : row); - - Index room = m_outerIndex[outer+1] - m_outerIndex[outer]; - StorageIndex innerNNZ = m_innerNonZeros[outer]; - if(innerNNZ>=room) - { - // this inner vector is full, we need to reallocate the whole buffer :( - reserve(SingletonVector(outer,std::max<StorageIndex>(2,innerNNZ))); - } - - Index startId = m_outerIndex[outer]; - Index p = startId + m_innerNonZeros[outer]; - while ( (p > startId) && (m_data.index(p-1) > inner) ) - { - m_data.index(p) = m_data.index(p-1); - m_data.value(p) = m_data.value(p-1); - --p; - } - eigen_assert((p<=startId || m_data.index(p-1)!=inner) && "you cannot insert an element that already exists, you must call coeffRef to this end"); - - m_innerNonZeros[outer]++; - - m_data.index(p) = inner; - return (m_data.value(p) = 0); -} - -template<typename _Scalar, int _Options, typename _StorageIndex> -EIGEN_DONT_INLINE typename SparseMatrix<_Scalar,_Options,_StorageIndex>::Scalar& SparseMatrix<_Scalar,_Options,_StorageIndex>::insertCompressed(Index row, Index col) -{ - eigen_assert(isCompressed()); - - const Index outer = IsRowMajor ? row : col; - const Index inner = IsRowMajor ? col : row; - - Index previousOuter = outer; - if (m_outerIndex[outer+1]==0) - { - // we start a new inner vector - while (previousOuter>=0 && m_outerIndex[previousOuter]==0) - { - m_outerIndex[previousOuter] = convert_index(m_data.size()); - --previousOuter; - } - m_outerIndex[outer+1] = m_outerIndex[outer]; - } - - // here we have to handle the tricky case where the outerIndex array - // starts with: [ 0 0 0 0 0 1 ...] and we are inserted in, e.g., - // the 2nd inner vector... - bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0)) - && (std::size_t(m_outerIndex[outer+1]) == m_data.size()); - - std::size_t startId = m_outerIndex[outer]; - // FIXME let's make sure sizeof(long int) == sizeof(std::size_t) - std::size_t p = m_outerIndex[outer+1]; - ++m_outerIndex[outer+1]; - - double reallocRatio = 1; - if (m_data.allocatedSize()<=m_data.size()) - { - // if there is no preallocated memory, let's reserve a minimum of 32 elements - if (m_data.size()==0) - { - m_data.reserve(32); - } - else - { - // we need to reallocate the data, to reduce multiple reallocations - // we use a smart resize algorithm based on the current filling ratio - // in addition, we use double to avoid integers overflows - double nnzEstimate = double(m_outerIndex[outer])*double(m_outerSize)/double(outer+1); - reallocRatio = (nnzEstimate-double(m_data.size()))/double(m_data.size()); - // furthermore we bound the realloc ratio to: - // 1) reduce multiple minor realloc when the matrix is almost filled - // 2) avoid to allocate too much memory when the matrix is almost empty - reallocRatio = (std::min)((std::max)(reallocRatio,1.5),8.); - } - } - m_data.resize(m_data.size()+1,reallocRatio); - - if (!isLastVec) - { - if (previousOuter==-1) - { - // oops wrong guess. - // let's correct the outer offsets - for (Index k=0; k<=(outer+1); ++k) - m_outerIndex[k] = 0; - Index k=outer+1; - while(m_outerIndex[k]==0) - m_outerIndex[k++] = 1; - while (k<=m_outerSize && m_outerIndex[k]!=0) - m_outerIndex[k++]++; - p = 0; - --k; - k = m_outerIndex[k]-1; - while (k>0) - { - m_data.index(k) = m_data.index(k-1); - m_data.value(k) = m_data.value(k-1); - k--; - } - } - else - { - // we are not inserting into the last inner vec - // update outer indices: - Index j = outer+2; - while (j<=m_outerSize && m_outerIndex[j]!=0) - m_outerIndex[j++]++; - --j; - // shift data of last vecs: - Index k = m_outerIndex[j]-1; - while (k>=Index(p)) - { - m_data.index(k) = m_data.index(k-1); - m_data.value(k) = m_data.value(k-1); - k--; - } - } - } - - while ( (p > startId) && (m_data.index(p-1) > inner) ) - { - m_data.index(p) = m_data.index(p-1); - m_data.value(p) = m_data.value(p-1); - --p; - } - - m_data.index(p) = inner; - return (m_data.value(p) = 0); -} - -namespace internal { - -template<typename _Scalar, int _Options, typename _StorageIndex> -struct evaluator<SparseMatrix<_Scalar,_Options,_StorageIndex> > - : evaluator<SparseCompressedBase<SparseMatrix<_Scalar,_Options,_StorageIndex> > > -{ - typedef evaluator<SparseCompressedBase<SparseMatrix<_Scalar,_Options,_StorageIndex> > > Base; - typedef SparseMatrix<_Scalar,_Options,_StorageIndex> SparseMatrixType; - evaluator() : Base() {} - explicit evaluator(const SparseMatrixType &mat) : Base(mat) {} -}; - -} - -} // end namespace Eigen - -#endif // EIGEN_SPARSEMATRIX_H |