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diff --git a/Eigen/src/SparseCore/SparseMatrix.h b/Eigen/src/SparseCore/SparseMatrix.h new file mode 100644 index 000000000..efb774f03 --- /dev/null +++ b/Eigen/src/SparseCore/SparseMatrix.h @@ -0,0 +1,1116 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2010 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 RowMajor. The default is 0 which means column-major. + * \tparam _Index the type of the indices. It has to be a \b signed type (e.g., short, int, std::ptrdiff_t). Default is \c int. + * + * 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_SPARSEMATRIX_PLUGIN. + */ + +namespace internal { +template<typename _Scalar, int _Options, typename _Index> +struct traits<SparseMatrix<_Scalar, _Options, _Index> > +{ + typedef _Scalar Scalar; + typedef _Index Index; + typedef Sparse StorageKind; + typedef MatrixXpr XprKind; + enum { + RowsAtCompileTime = Dynamic, + ColsAtCompileTime = Dynamic, + MaxRowsAtCompileTime = Dynamic, + MaxColsAtCompileTime = Dynamic, + Flags = _Options | NestByRefBit | LvalueBit, + CoeffReadCost = NumTraits<Scalar>::ReadCost, + SupportedAccessPatterns = InnerRandomAccessPattern + }; +}; + +template<typename _Scalar, int _Options, typename _Index, int DiagIndex> +struct traits<Diagonal<const SparseMatrix<_Scalar, _Options, _Index>, DiagIndex> > +{ + typedef SparseMatrix<_Scalar, _Options, _Index> MatrixType; + typedef typename nested<MatrixType>::type MatrixTypeNested; + typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested; + + typedef _Scalar Scalar; + typedef Dense StorageKind; + typedef _Index Index; + typedef MatrixXpr XprKind; + + enum { + RowsAtCompileTime = Dynamic, + ColsAtCompileTime = 1, + MaxRowsAtCompileTime = Dynamic, + MaxColsAtCompileTime = 1, + Flags = 0, + CoeffReadCost = _MatrixTypeNested::CoeffReadCost*10 + }; +}; + +} // end namespace internal + +template<typename _Scalar, int _Options, typename _Index> +class SparseMatrix + : public SparseMatrixBase<SparseMatrix<_Scalar, _Options, _Index> > +{ + public: + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=) + + typedef MappedSparseMatrix<Scalar,Flags> Map; + using Base::IsRowMajor; + typedef internal::CompressedStorage<Scalar,Index> Storage; + enum { + Options = _Options + }; + + protected: + + typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix; + + Index m_outerSize; + Index m_innerSize; + Index* m_outerIndex; + Index* m_innerNonZeros; // optional, if null then the data is compressed + Storage m_data; + + Eigen::Map<Matrix<Index,Dynamic,1> > innerNonZeros() { return Eigen::Map<Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); } + const Eigen::Map<const Matrix<Index,Dynamic,1> > innerNonZeros() const { return Eigen::Map<const Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); } + + public: + + /** \returns whether \c *this is in compressed form. */ + inline bool isCompressed() const { return m_innerNonZeros==0; } + + /** \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.value(0); } + /** \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.value(0); } + + /** \returns a const pointer to the array of inner indices. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), outerIndexPtr() */ + inline const Index* innerIndexPtr() const { return &m_data.index(0); } + /** \returns a non-const pointer to the array of inner indices. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), outerIndexPtr() */ + inline Index* innerIndexPtr() { return &m_data.index(0); } + + /** \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 Index* 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 Index* 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 Index* 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 Index* 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 + { + 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, 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) + { + 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,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 non zeros per inner vector. It is strongly recommended to first + * call reserve(const SizesType &) to reserve a more appropriate number of elements per + * inner vector that better match your scenario. + * + * 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. + * + */ + EIGEN_DONT_INLINE Scalar& insert(Index row, Index col) + { + if(isCompressed()) + { + reserve(VectorXi::Constant(outerSize(), 2)); + } + return insertUncompressed(row,col); + } + + public: + + class InnerIterator; + class ReverseInnerIterator; + + /** Removes all non zeros but keep allocated memory */ + inline void setZero() + { + m_data.clear(); + memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index)); + if(m_innerNonZeros) + memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(Index)); + } + + /** \returns the number of non zero coefficients */ + inline Index nonZeros() const + { + if(m_innerNonZeros) + return innerNonZeros().sum(); + return static_cast<Index>(m_data.size()); + } + + /** 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 */ + 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 = typename SizesType::value_type()) + { + EIGEN_UNUSED_VARIABLE(enableif); + reserveInnerVectors(reserveSizes); + } + template<class SizesType> + inline void reserve(const SizesType& reserveSizes, const typename SizesType::Scalar& enableif = + #if (!defined(_MSC_VER)) || (_MSC_VER>=1500) // MSVC 2005 fails to compile with this typename + typename + #endif + SizesType::Scalar()) + { + EIGEN_UNUSED_VARIABLE(enableif); + reserveInnerVectors(reserveSizes); + } + #endif // EIGEN_PARSED_BY_DOXYGEN + protected: + template<class SizesType> + inline void reserveInnerVectors(const SizesType& reserveSizes) + { + + if(isCompressed()) + { + std::size_t totalReserveSize = 0; + // turn the matrix into non-compressed mode + m_innerNonZeros = new Index[m_outerSize]; + + // temporarily use m_innerSizes to hold the new starting points. + Index* newOuterIndex = m_innerNonZeros; + + Index 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); + std::ptrdiff_t previousOuterIndex = m_outerIndex[m_outerSize]; + for(std::ptrdiff_t j=m_outerSize-1; j>=0; --j) + { + ptrdiff_t innerNNZ = previousOuterIndex - m_outerIndex[j]; + for(std::ptrdiff_t 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 + { + Index* newOuterIndex = new Index[m_outerSize+1]; + Index count = 0; + for(Index j=0; j<m_outerSize; ++j) + { + newOuterIndex[j] = count; + Index alreadyReserved = (m_outerIndex[j+1]-m_outerIndex[j]) - m_innerNonZeros[j]; + Index toReserve = std::max<std::ptrdiff_t>(reserveSizes[j], alreadyReserved); + count += toReserve + m_innerNonZeros[j]; + } + newOuterIndex[m_outerSize] = count; + + m_data.resize(count); + for(ptrdiff_t j=m_outerSize-1; j>=0; --j) + { + std::ptrdiff_t offset = newOuterIndex[j] - m_outerIndex[j]; + if(offset>0) + { + std::ptrdiff_t innerNNZ = m_innerNonZeros[j]; + for(std::ptrdiff_t 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); + delete[] 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(size_t(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(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(0, inner); + return m_data.value(p); + } + + /** \internal + * \sa insertBack, insertBackByOuterInner */ + inline void startVec(Index outer) + { + eigen_assert(m_outerIndex[outer]==int(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()) + { + Index size = static_cast<Index>(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); + + void sumupDuplicates(); + + //--- + + /** \internal + * same as insert(Index,Index) except that the indices are given relative to the storage order */ + EIGEN_DONT_INLINE 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; + + 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]; + std::ptrdiff_t 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; + } + delete[] m_innerNonZeros; + m_innerNonZeros = 0; + m_data.resize(m_outerIndex[m_outerSize]); + m_data.squeeze(); + } + + /** Suppresses all nonzeros which are \b much \b smaller \b than \a reference under the tolerence \a epsilon */ + void prune(Scalar reference, 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 + // TODO also implement a unit test + makeCompressed(); + + Index 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 and initializes it to zero. + * \sa resizeNonZeros(Index), 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) + { + delete[] m_outerIndex; + m_outerIndex = new Index [outerSize+1]; + m_outerSize = outerSize; + } + if(m_innerNonZeros) + { + delete[] m_innerNonZeros; + m_innerNonZeros = 0; + } + memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index)); + } + + /** \internal + * Resize the nonzero vector to \a size */ + void resizeNonZeros(Index size) + { + // TODO remove this function + m_data.resize(size); + } + + /** \returns a const expression of the diagonal coefficients */ + const Diagonal<const SparseMatrix> diagonal() const { return *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) + { + check_template_parameters(); + *this = other.derived(); + } + + /** 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(); + } + + /** 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); + } + + inline SparseMatrix& operator=(const SparseMatrix& other) + { + if (other.isRValue()) + { + swap(other.const_cast_derived()); + } + else + { + initAssignment(other); + if(other.isCompressed()) + { + memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(Index)); + m_data = other.m_data; + } + else + { + Base::operator=(other); + } + } + return *this; + } + + #ifndef EIGEN_PARSED_BY_DOXYGEN + template<typename Lhs, typename Rhs> + inline SparseMatrix& operator=(const SparseSparseProduct<Lhs,Rhs>& product) + { return Base::operator=(product); } + + template<typename OtherDerived> + inline SparseMatrix& operator=(const ReturnByValue<OtherDerived>& other) + { return Base::operator=(other.derived()); } + + template<typename OtherDerived> + inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other) + { return Base::operator=(other.derived()); } + #endif + + template<typename OtherDerived> + EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other) + { + initAssignment(other.derived()); + const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + if (needToTranspose) + { + // 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<OtherDerived,2>::type OtherCopy; + typedef typename internal::remove_all<OtherCopy>::type _OtherCopy; + OtherCopy otherCopy(other.derived()); + + Eigen::Map<Matrix<Index, Dynamic, 1> > (m_outerIndex,outerSize()).setZero(); + // pass 1 + // FIXME the above copy could be merged with that pass + for (Index j=0; j<otherCopy.outerSize(); ++j) + for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it) + ++m_outerIndex[it.index()]; + + // prefix sum + Index count = 0; + VectorXi positions(outerSize()); + for (Index j=0; j<outerSize(); ++j) + { + Index tmp = m_outerIndex[j]; + m_outerIndex[j] = count; + positions[j] = count; + count += tmp; + } + m_outerIndex[outerSize()] = count; + // alloc + m_data.resize(count); + // pass 2 + for (Index j=0; j<otherCopy.outerSize(); ++j) + { + for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it) + { + Index pos = positions[it.index()]++; + m_data.index(pos) = j; + m_data.value(pos) = it.value(); + } + } + return *this; + } + else + { + // there is no special optimization + return Base::operator=(other.derived()); + } + } + + 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) + { + int p = m.m_outerIndex[i]; + int 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() + { + delete[] m_outerIndex; + delete[] m_innerNonZeros; + } + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** Overloaded for performance */ + Scalar sum() const; +#endif + +# 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) + { + delete[] m_innerNonZeros; + m_innerNonZeros = 0; + } + } + + /** \internal + * \sa insert(Index,Index) */ + EIGEN_DONT_INLINE Scalar& 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] = static_cast<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)) + && (size_t(m_outerIndex[outer+1]) == m_data.size()); + + size_t startId = m_outerIndex[outer]; + // FIXME let's make sure sizeof(long int) == sizeof(size_t) + size_t p = m_outerIndex[outer+1]; + ++m_outerIndex[outer+1]; + + float 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 float to avoid integers overflows + float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1); + reallocRatio = (nnzEstimate-float(m_data.size()))/float(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,1.5f),8.f); + } + } + 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); + } + + /** \internal + * A vector object that is equal to 0 everywhere but v at the position i */ + class SingletonVector + { + Index m_index; + Index m_value; + public: + typedef Index value_type; + SingletonVector(Index i, Index v) + : m_index(i), m_value(v) + {} + + Index 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) + { + eigen_assert(!isCompressed()); + + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + std::ptrdiff_t room = m_outerIndex[outer+1] - m_outerIndex[outer]; + std::ptrdiff_t innerNNZ = m_innerNonZeros[outer]; + if(innerNNZ>=room) + { + // this inner vector is full, we need to reallocate the whole buffer :( + reserve(SingletonVector(outer,std::max<std::ptrdiff_t>(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; + } + + m_innerNonZeros[outer]++; + + m_data.index(p) = inner; + return (m_data.value(p) = 0); + } + +public: + /** \internal + * \sa insert(Index,Index) */ + 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_innerNonZeros[outer]++; + m_data.index(p) = inner; + return (m_data.value(p) = 0); + } + +private: + static void check_template_parameters() + { + EIGEN_STATIC_ASSERT(NumTraits<Index>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE); + } + + struct default_prunning_func { + default_prunning_func(Scalar ref, 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; + }; +}; + +template<typename Scalar, int _Options, typename _Index> +class SparseMatrix<Scalar,_Options,_Index>::InnerIterator +{ + public: + InnerIterator(const SparseMatrix& mat, Index outer) + : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_id(mat.m_outerIndex[outer]) + { + if(mat.isCompressed()) + m_end = mat.m_outerIndex[outer+1]; + else + m_end = m_id + mat.m_innerNonZeros[outer]; + } + + inline InnerIterator& operator++() { m_id++; return *this; } + + inline const Scalar& value() const { return m_values[m_id]; } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id]); } + + inline Index index() const { return m_indices[m_id]; } + inline Index outer() const { return m_outer; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id < m_end); } + + protected: + const Scalar* m_values; + const Index* m_indices; + const Index m_outer; + Index m_id; + Index m_end; +}; + +template<typename Scalar, int _Options, typename _Index> +class SparseMatrix<Scalar,_Options,_Index>::ReverseInnerIterator +{ + public: + ReverseInnerIterator(const SparseMatrix& mat, Index outer) + : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_start(mat.m_outerIndex[outer]) + { + if(mat.isCompressed()) + m_id = mat.m_outerIndex[outer+1]; + else + m_id = m_start + mat.m_innerNonZeros[outer]; + } + + inline ReverseInnerIterator& operator--() { --m_id; return *this; } + + inline const Scalar& value() const { return m_values[m_id-1]; } + inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id-1]); } + + inline Index index() const { return m_indices[m_id-1]; } + inline Index outer() const { return m_outer; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id > m_start); } + + protected: + const Scalar* m_values; + const Index* m_indices; + const Index m_outer; + Index m_id; + const Index m_start; +}; + +namespace internal { + +template<typename InputIterator, typename SparseMatrixType> +void set_from_triplets(const InputIterator& begin, const InputIterator& end, SparseMatrixType& mat, int Options = 0) +{ + EIGEN_UNUSED_VARIABLE(Options); + enum { IsRowMajor = SparseMatrixType::IsRowMajor }; + typedef typename SparseMatrixType::Scalar Scalar; + typedef typename SparseMatrixType::Index Index; + SparseMatrix<Scalar,IsRowMajor?ColMajor:RowMajor> trMat(mat.rows(),mat.cols()); + + // pass 1: count the nnz per inner-vector + VectorXi wi(trMat.outerSize()); + wi.setZero(); + for(InputIterator it(begin); it!=end; ++it) + 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.sumupDuplicates(); + + // 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 - \b. + * + * 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 _Index> +template<typename InputIterators> +void SparseMatrix<Scalar,_Options,_Index>::setFromTriplets(const InputIterators& begin, const InputIterators& end) +{ + internal::set_from_triplets(begin, end, *this); +} + +/** \internal */ +template<typename Scalar, int _Options, typename _Index> +void SparseMatrix<Scalar,_Options,_Index>::sumupDuplicates() +{ + eigen_assert(!isCompressed()); + // TODO, in practice we should be able to use m_innerNonZeros for that task + VectorXi wi(innerSize()); + wi.fill(-1); + Index count = 0; + // for each inner-vector, wi[inner_index] will hold the position of first element into the index/value buffers + for(int j=0; j<outerSize(); ++j) + { + Index 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)) += 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 + delete[] m_innerNonZeros; + m_innerNonZeros = 0; + m_data.resize(m_outerIndex[m_outerSize]); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSEMATRIX_H |