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| #ifndef EIGEN_SPARSEMATRIX_H |
| #define EIGEN_SPARSEMATRIX_H |
|
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| namespace Eigen { |
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| 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 |
| }; |
| }; |
|
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| 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; |
|
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| 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 |
| }; |
| }; |
|
|
| } |
|
|
| 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>; |
| template<typename, typename, typename, typename, typename> |
| friend struct internal::Assignment; |
| 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; |
| Storage m_data; |
|
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| public: |
| |
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| inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; } |
| |
| inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; } |
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| inline Index innerSize() const { return m_innerSize; } |
| |
| inline Index outerSize() const { return m_outerSize; } |
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| inline const Scalar* valuePtr() const { return m_data.valuePtr(); } |
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| inline Scalar* valuePtr() { return m_data.valuePtr(); } |
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| inline const StorageIndex* innerIndexPtr() const { return m_data.indexPtr(); } |
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| inline StorageIndex* innerIndexPtr() { return m_data.indexPtr(); } |
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| inline const StorageIndex* outerIndexPtr() const { return m_outerIndex; } |
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| inline StorageIndex* outerIndexPtr() { return m_outerIndex; } |
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| inline const StorageIndex* innerNonZeroPtr() const { return m_innerNonZeros; } |
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| inline StorageIndex* innerNonZeroPtr() { return m_innerNonZeros; } |
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| inline Storage& data() { return m_data; } |
| |
| inline const Storage& data() const { return m_data; } |
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| |
| 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)); |
| } |
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| 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; |
|
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| 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); |
| } |
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| Scalar& insert(Index row, Index col); |
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| public: |
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| 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)); |
| } |
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| 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 |
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| 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) |
| typename |
| #endif |
| SizesType::value_type()) |
| { |
| EIGEN_UNUSED_VARIABLE(enableif); |
| reserveInnerVectors(reserveSizes); |
| } |
| #endif |
| protected: |
| template<class SizesType> |
| inline void reserveInnerVectors(const SizesType& reserveSizes) |
| { |
| if(isCompressed()) |
| { |
| Index totalReserveSize = 0; |
| |
| m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex))); |
| if (!m_innerNonZeros) internal::throw_std_bad_alloc(); |
| |
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| 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; |
| } |
| if(m_outerSize>0) |
| 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: |
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| inline Scalar& insertBack(Index row, Index col) |
| { |
| return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row); |
| } |
|
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| |
| |
| 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); |
| } |
|
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| |
| |
| 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); |
| } |
|
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| 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]; |
| } |
|
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| inline void finalize() |
| { |
| if(isCompressed()) |
| { |
| StorageIndex size = internal::convert_index<StorageIndex>(m_data.size()); |
| Index i = m_outerSize; |
| |
| while (i>=0 && m_outerIndex[i]==0) |
| --i; |
| ++i; |
| while (i<=m_outerSize) |
| { |
| m_outerIndex[i] = size; |
| ++i; |
| } |
| } |
| } |
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| template<typename InputIterators> |
| void setFromTriplets(const InputIterators& begin, const InputIterators& end); |
|
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| template<typename InputIterators,typename DupFunctor> |
| void setFromTriplets(const InputIterators& begin, const InputIterators& end, DupFunctor dup_func); |
|
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| void sumupDuplicates() { collapseDuplicates(internal::scalar_sum_op<Scalar,Scalar>()); } |
|
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| template<typename DupFunctor> |
| void collapseDuplicates(DupFunctor dup_func = DupFunctor()); |
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| Scalar& insertByOuterInner(Index j, Index i) |
| { |
| return insert(IsRowMajor ? j : i, IsRowMajor ? i : j); |
| } |
|
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| 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(); |
| } |
|
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| |
| 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]; |
| } |
| } |
|
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| void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) |
| { |
| prune(default_prunning_func(reference,epsilon)); |
| } |
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| template<typename KeepFunc> |
| void prune(const KeepFunc& keep = KeepFunc()) |
| { |
| |
| makeCompressed(); |
|
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| 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); |
| } |
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| void conservativeResize(Index rows, Index cols) |
| { |
| |
| if (this->rows() == rows && this->cols() == cols) return; |
| |
| |
| if(rows==0 || cols==0) return resize(rows,cols); |
|
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| 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); |
|
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| |
| if (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) |
| { |
| |
| m_innerNonZeros = static_cast<StorageIndex*>(std::malloc((m_outerSize + outerChange) * sizeof(StorageIndex))); |
| if (!m_innerNonZeros) internal::throw_std_bad_alloc(); |
| for(Index i = 0; i < m_outerSize + (std::min)(outerChange, Index(0)); i++) |
| m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i]; |
| for(Index i = m_outerSize; i < m_outerSize + outerChange; i++) |
| m_innerNonZeros[i] = 0; |
| } |
| |
| |
| 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; |
|
|
| |
| 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 lastIdx = m_outerSize == 0 ? 0 : m_outerIndex[m_outerSize]; |
| for(Index i=m_outerSize; i<m_outerSize+outerChange+1; i++) |
| m_outerIndex[i] = lastIdx; |
| } |
| m_outerSize += outerChange; |
| } |
| |
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| 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)); |
| } |
|
|
| |
| |
| void resizeNonZeros(Index size) |
| { |
| m_data.resize(size); |
| } |
|
|
| |
| const ConstDiagonalReturnType diagonal() const { return ConstDiagonalReturnType(*this); } |
| |
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| |
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| DiagonalReturnType diagonal() { return DiagonalReturnType(*this); } |
|
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| |
| inline SparseMatrix() |
| : m_outerSize(-1), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) |
| { |
| check_template_parameters(); |
| resize(0, 0); |
| } |
|
|
| |
| inline SparseMatrix(Index rows, Index cols) |
| : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) |
| { |
| check_template_parameters(); |
| resize(rows, cols); |
| } |
|
|
| |
| 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()); |
| } |
| } |
| |
| |
| 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); |
| } |
|
|
| |
| inline SparseMatrix(const SparseMatrix& other) |
| : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) |
| { |
| check_template_parameters(); |
| *this = other.derived(); |
| } |
|
|
| |
| 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); |
| } |
| |
| |
| 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(); |
| } |
|
|
| |
| |
| inline void swap(SparseMatrix& other) |
| { |
| |
| 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 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; |
| } |
|
|
| template<typename OtherDerived> |
| inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other) |
| { return Base::operator=(other.derived()); } |
|
|
| template<typename Lhs, typename Rhs> |
| inline SparseMatrix& operator=(const Product<Lhs,Rhs,AliasFreeProduct>& other); |
|
|
| template<typename OtherDerived> |
| EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other); |
|
|
| #ifndef EIGEN_NO_IO |
| 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; |
| } |
| #endif |
|
|
| |
| inline ~SparseMatrix() |
| { |
| std::free(m_outerIndex); |
| std::free(m_innerNonZeros); |
| } |
|
|
| |
| 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; |
| } |
| } |
|
|
| |
| |
| EIGEN_DONT_INLINE Scalar& insertCompressed(Index row, Index col); |
|
|
| |
| |
| 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; } |
| }; |
|
|
| |
| |
| EIGEN_DONT_INLINE Scalar& insertUncompressed(Index row, Index col); |
|
|
| public: |
| |
| |
| 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) = Scalar(0)); |
| } |
| protected: |
| struct IndexPosPair { |
| IndexPosPair(Index a_i, Index a_p) : i(a_i), p(a_p) {} |
| Index i; |
| Index p; |
| }; |
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| template<typename DiagXpr, typename Func> |
| void assignDiagonal(const DiagXpr diagXpr, const Func& assignFunc) |
| { |
| Index n = diagXpr.size(); |
|
|
| const bool overwrite = internal::is_same<Func, internal::assign_op<Scalar,Scalar> >::value; |
| if(overwrite) |
| { |
| if((this->rows()!=n) || (this->cols()!=n)) |
| this->resize(n, n); |
| } |
|
|
| if(m_data.size()==0 || overwrite) |
| { |
| typedef Array<StorageIndex,Dynamic,1> ArrayXI; |
| this->makeCompressed(); |
| this->resizeNonZeros(n); |
| Eigen::Map<ArrayXI>(this->innerIndexPtr(), n).setLinSpaced(0,StorageIndex(n)-1); |
| Eigen::Map<ArrayXI>(this->outerIndexPtr(), n+1).setLinSpaced(0,StorageIndex(n)); |
| Eigen::Map<Array<Scalar,Dynamic,1> > values = this->coeffs(); |
| values.setZero(); |
| internal::call_assignment_no_alias(values, diagXpr, assignFunc); |
| } |
| else |
| { |
| bool isComp = isCompressed(); |
| internal::evaluator<DiagXpr> diaEval(diagXpr); |
| std::vector<IndexPosPair> newEntries; |
|
|
| |
| for(Index i = 0; i<n; ++i) |
| { |
| internal::LowerBoundIndex lb = this->lower_bound(i,i); |
| Index p = lb.value; |
| if(lb.found) |
| { |
| |
| assignFunc.assignCoeff(m_data.value(p), diaEval.coeff(i)); |
| } |
| else if((!isComp) && m_innerNonZeros[i] < (m_outerIndex[i+1]-m_outerIndex[i])) |
| { |
| |
| m_data.moveChunk(p, p+1, m_outerIndex[i]+m_innerNonZeros[i]-p); |
| m_innerNonZeros[i]++; |
| m_data.value(p) = Scalar(0); |
| m_data.index(p) = StorageIndex(i); |
| assignFunc.assignCoeff(m_data.value(p), diaEval.coeff(i)); |
| } |
| else |
| { |
| |
| newEntries.push_back(IndexPosPair(i,p)); |
| } |
| } |
| |
| Index n_entries = Index(newEntries.size()); |
| if(n_entries>0) |
| { |
| Storage newData(m_data.size()+n_entries); |
| Index prev_p = 0; |
| Index prev_i = 0; |
| for(Index k=0; k<n_entries;++k) |
| { |
| Index i = newEntries[k].i; |
| Index p = newEntries[k].p; |
| internal::smart_copy(m_data.valuePtr()+prev_p, m_data.valuePtr()+p, newData.valuePtr()+prev_p+k); |
| internal::smart_copy(m_data.indexPtr()+prev_p, m_data.indexPtr()+p, newData.indexPtr()+prev_p+k); |
| for(Index j=prev_i;j<i;++j) |
| m_outerIndex[j+1] += k; |
| if(!isComp) |
| m_innerNonZeros[i]++; |
| prev_p = p; |
| prev_i = i; |
| newData.value(p+k) = Scalar(0); |
| newData.index(p+k) = StorageIndex(i); |
| assignFunc.assignCoeff(newData.value(p+k), diaEval.coeff(i)); |
| } |
| { |
| internal::smart_copy(m_data.valuePtr()+prev_p, m_data.valuePtr()+m_data.size(), newData.valuePtr()+prev_p+n_entries); |
| internal::smart_copy(m_data.indexPtr()+prev_p, m_data.indexPtr()+m_data.size(), newData.indexPtr()+prev_p+n_entries); |
| for(Index j=prev_i+1;j<=m_outerSize;++j) |
| m_outerIndex[j] += n_entries; |
| } |
| m_data.swap(newData); |
| } |
| } |
| } |
|
|
| 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) |
| { |
| |
| 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())++; |
| } |
|
|
| |
| trMat.reserve(wi); |
| for(InputIterator it(begin); it!=end; ++it) |
| trMat.insertBackUncompressed(it->row(),it->col()) = it->value(); |
|
|
| |
| trMat.collapseDuplicates(dup_func); |
| } |
|
|
| |
| mat = trMat; |
| } |
|
|
| } |
|
|
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| 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>()); |
| } |
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| 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); |
| } |
|
|
| |
| template<typename Scalar, int _Options, typename _StorageIndex> |
| template<typename DupFunctor> |
| void SparseMatrix<Scalar,_Options,_StorageIndex>::collapseDuplicates(DupFunctor dup_func) |
| { |
| eigen_assert(!isCompressed()); |
| |
| IndexVector wi(innerSize()); |
| wi.fill(-1); |
| StorageIndex count = 0; |
| |
| 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) |
| { |
| |
| 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; |
|
|
| |
| 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 |
| |
| |
| |
| |
| 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(); |
|
|
| |
| |
| for (Index j=0; j<otherCopy.outerSize(); ++j) |
| for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it) |
| ++dest.m_outerIndex[it.index()]; |
|
|
| |
| 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; |
| |
| dest.m_data.resize(count); |
| |
| 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()); |
| } |
| |
| 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) |
| { |
| |
| if(m_data.allocatedSize()==0) |
| m_data.reserve(2*m_innerSize); |
| |
| |
| 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)); |
| |
| |
| |
| StorageIndex end = convert_index(m_data.allocatedSize()); |
| for(Index j=1; j<=m_outerSize; ++j) |
| m_outerIndex[j] = end; |
| } |
| else |
| { |
| |
| 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]; |
| } |
| } |
| |
| |
| Index data_end = m_data.allocatedSize(); |
| |
| |
| |
| if(m_outerIndex[outer]==data_end) |
| { |
| eigen_internal_assert(m_innerNonZeros[outer]==0); |
| |
| |
| |
| StorageIndex p = convert_index(m_data.size()); |
| Index j = outer; |
| while(j>=0 && m_innerNonZeros[j]==0) |
| m_outerIndex[j--] = p; |
| |
| |
| ++m_innerNonZeros[outer]; |
| m_data.append(Scalar(0), inner); |
| |
| |
| if(data_end != m_data.allocatedSize()) |
| { |
| |
| |
| |
| 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); |
| } |
| |
| |
| |
| 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); |
| |
| |
| ++m_innerNonZeros[outer]; |
| m_data.resize(m_data.size()+1); |
| |
| |
| if(data_end != m_data.allocatedSize()) |
| { |
| |
| |
| |
| 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; |
| } |
| |
| |
| 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) = Scalar(0)); |
| } |
| |
| if(m_data.size() != m_data.allocatedSize()) |
| { |
| |
| 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) |
| { |
| |
| 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) = Scalar(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) |
| { |
| |
| while (previousOuter>=0 && m_outerIndex[previousOuter]==0) |
| { |
| m_outerIndex[previousOuter] = convert_index(m_data.size()); |
| --previousOuter; |
| } |
| m_outerIndex[outer+1] = m_outerIndex[outer]; |
| } |
|
|
| |
| |
| |
| 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]; |
| |
| std::size_t p = m_outerIndex[outer+1]; |
| ++m_outerIndex[outer+1]; |
|
|
| double reallocRatio = 1; |
| if (m_data.allocatedSize()<=m_data.size()) |
| { |
| |
| if (m_data.size()==0) |
| { |
| m_data.reserve(32); |
| } |
| else |
| { |
| |
| |
| |
| double nnzEstimate = double(m_outerIndex[outer])*double(m_outerSize)/double(outer+1); |
| reallocRatio = (nnzEstimate-double(m_data.size()))/double(m_data.size()); |
| |
| |
| |
| reallocRatio = (std::min)((std::max)(reallocRatio,1.5),8.); |
| } |
| } |
| m_data.resize(m_data.size()+1,reallocRatio); |
|
|
| if (!isLastVec) |
| { |
| if (previousOuter==-1) |
| { |
| |
| |
| 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 |
| { |
| |
| |
| Index j = outer+2; |
| while (j<=m_outerSize && m_outerIndex[j]!=0) |
| m_outerIndex[j++]++; |
| --j; |
| |
| 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) = Scalar(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) {} |
| }; |
|
|
| } |
|
|
| } |
|
|
| #endif |
|
|