diff options
author | 2014-02-18 18:51:24 -0800 | |
---|---|---|
committer | 2014-02-18 18:51:24 -0800 | |
commit | cbd7e98174127a52d4d76bec4394316548bb31e5 (patch) | |
tree | cc14b314fc0b32591eeb88845d259591b1b37129 /Eigen/src | |
parent | 7ed9441ea472031bb9357b5bec80151cae7ed2cb (diff) | |
parent | 37a1d736bfd6fdaa0e1a93aee585d1861ab4004a (diff) |
Merged the latest version of the code from eigen/eigen
Diffstat (limited to 'Eigen/src')
-rw-r--r-- | Eigen/src/Cholesky/LDLT.h | 52 | ||||
-rw-r--r-- | Eigen/src/Core/EigenBase.h | 30 | ||||
-rw-r--r-- | Eigen/src/Core/MatrixBase.h | 45 | ||||
-rw-r--r-- | Eigen/src/Core/StableNorm.h | 27 | ||||
-rw-r--r-- | Eigen/src/Core/util/Memory.h | 18 | ||||
-rw-r--r-- | Eigen/src/Geometry/Transform.h | 14 | ||||
-rw-r--r-- | Eigen/src/SparseCore/ConservativeSparseSparseProduct.h | 34 | ||||
-rw-r--r-- | Eigen/src/SparseCore/SparseBlock.h | 136 | ||||
-rw-r--r-- | Eigen/src/SparseCore/SparseDenseProduct.h | 4 | ||||
-rw-r--r-- | Eigen/src/SparseCore/SparseMatrix.h | 10 | ||||
-rw-r--r-- | Eigen/src/SparseCore/SparseMatrixBase.h | 4 | ||||
-rw-r--r-- | Eigen/src/SparseCore/SparseProduct.h | 5 | ||||
-rw-r--r-- | Eigen/src/SparseCore/SparseSparseProductWithPruning.h | 13 | ||||
-rw-r--r-- | Eigen/src/SparseLU/SparseLU_Memory.h | 4 |
14 files changed, 269 insertions, 127 deletions
diff --git a/Eigen/src/Cholesky/LDLT.h b/Eigen/src/Cholesky/LDLT.h index 4faedd257..f34d26465 100644 --- a/Eigen/src/Cholesky/LDLT.h +++ b/Eigen/src/Cholesky/LDLT.h @@ -16,7 +16,10 @@ namespace Eigen { namespace internal { -template<typename MatrixType, int UpLo> struct LDLT_Traits; + template<typename MatrixType, int UpLo> struct LDLT_Traits; + + // PositiveSemiDef means positive semi-definite and non-zero; same for NegativeSemiDef + enum SignMatrix { PositiveSemiDef, NegativeSemiDef, ZeroSign, Indefinite }; } /** \ingroup Cholesky_Module @@ -69,7 +72,12 @@ template<typename _MatrixType, int _UpLo> class LDLT * The default constructor is useful in cases in which the user intends to * perform decompositions via LDLT::compute(const MatrixType&). */ - LDLT() : m_matrix(), m_transpositions(), m_isInitialized(false) {} + LDLT() + : m_matrix(), + m_transpositions(), + m_sign(internal::ZeroSign), + m_isInitialized(false) + {} /** \brief Default Constructor with memory preallocation * @@ -81,6 +89,7 @@ template<typename _MatrixType, int _UpLo> class LDLT : m_matrix(size, size), m_transpositions(size), m_temporary(size), + m_sign(internal::ZeroSign), m_isInitialized(false) {} @@ -93,6 +102,7 @@ template<typename _MatrixType, int _UpLo> class LDLT : m_matrix(matrix.rows(), matrix.cols()), m_transpositions(matrix.rows()), m_temporary(matrix.rows()), + m_sign(internal::ZeroSign), m_isInitialized(false) { compute(matrix); @@ -139,7 +149,7 @@ template<typename _MatrixType, int _UpLo> class LDLT inline bool isPositive() const { eigen_assert(m_isInitialized && "LDLT is not initialized."); - return m_sign == 1; + return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign; } #ifdef EIGEN2_SUPPORT @@ -153,7 +163,7 @@ template<typename _MatrixType, int _UpLo> class LDLT inline bool isNegative(void) const { eigen_assert(m_isInitialized && "LDLT is not initialized."); - return m_sign == -1; + return m_sign == internal::NegativeSemiDef || m_sign == internal::ZeroSign; } /** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A. @@ -235,7 +245,7 @@ template<typename _MatrixType, int _UpLo> class LDLT MatrixType m_matrix; TranspositionType m_transpositions; TmpMatrixType m_temporary; - int m_sign; + internal::SignMatrix m_sign; bool m_isInitialized; }; @@ -246,7 +256,7 @@ template<int UpLo> struct ldlt_inplace; template<> struct ldlt_inplace<Lower> { template<typename MatrixType, typename TranspositionType, typename Workspace> - static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, int* sign=0) + static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign) { using std::abs; typedef typename MatrixType::Scalar Scalar; @@ -258,8 +268,9 @@ template<> struct ldlt_inplace<Lower> if (size <= 1) { transpositions.setIdentity(); - if(sign) - *sign = numext::real(mat.coeff(0,0))>0 ? 1:-1; + if (numext::real(mat.coeff(0,0)) > 0) sign = PositiveSemiDef; + else if (numext::real(mat.coeff(0,0)) < 0) sign = NegativeSemiDef; + else sign = ZeroSign; return true; } @@ -284,7 +295,6 @@ template<> struct ldlt_inplace<Lower> if(biggest_in_corner < cutoff) { for(Index i = k; i < size; i++) transpositions.coeffRef(i) = i; - if(sign) *sign = 0; break; } @@ -325,15 +335,15 @@ template<> struct ldlt_inplace<Lower> } if((rs>0) && (abs(mat.coeffRef(k,k)) > cutoff)) A21 /= mat.coeffRef(k,k); - - if(sign) - { - // LDLT is not guaranteed to work for indefinite matrices, but let's try to get the sign right - int newSign = numext::real(mat.diagonal().coeff(index_of_biggest_in_corner)) > 0; - if(k == 0) - *sign = newSign; - else if(*sign != newSign) - *sign = 0; + + RealScalar realAkk = numext::real(mat.coeffRef(k,k)); + if (sign == PositiveSemiDef) { + if (realAkk < 0) sign = Indefinite; + } else if (sign == NegativeSemiDef) { + if (realAkk > 0) sign = Indefinite; + } else if (sign == ZeroSign) { + if (realAkk > 0) sign = PositiveSemiDef; + else if (realAkk < 0) sign = NegativeSemiDef; } } @@ -399,7 +409,7 @@ template<> struct ldlt_inplace<Lower> template<> struct ldlt_inplace<Upper> { template<typename MatrixType, typename TranspositionType, typename Workspace> - static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, int* sign=0) + static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign) { Transpose<MatrixType> matt(mat); return ldlt_inplace<Lower>::unblocked(matt, transpositions, temp, sign); @@ -445,7 +455,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a) m_isInitialized = false; m_temporary.resize(size); - internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, &m_sign); + internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign); m_isInitialized = true; return *this; @@ -473,7 +483,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Deri for (Index i = 0; i < size; i++) m_transpositions.coeffRef(i) = i; m_temporary.resize(size); - m_sign = sigma>=0 ? 1 : -1; + m_sign = sigma>=0 ? internal::PositiveSemiDef : internal::NegativeSemiDef; m_isInitialized = true; } diff --git a/Eigen/src/Core/EigenBase.h b/Eigen/src/Core/EigenBase.h index a25e823ab..1a577c2dc 100644 --- a/Eigen/src/Core/EigenBase.h +++ b/Eigen/src/Core/EigenBase.h @@ -141,36 +141,6 @@ Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other) return derived(); } -/** replaces \c *this by \c *this * \a other. - * - * \returns a reference to \c *this - */ -template<typename Derived> -template<typename OtherDerived> -inline Derived& -MatrixBase<Derived>::operator*=(const EigenBase<OtherDerived> &other) -{ - other.derived().applyThisOnTheRight(derived()); - return derived(); -} - -/** replaces \c *this by \c *this * \a other. It is equivalent to MatrixBase::operator*=(). - */ -template<typename Derived> -template<typename OtherDerived> -inline void MatrixBase<Derived>::applyOnTheRight(const EigenBase<OtherDerived> &other) -{ - other.derived().applyThisOnTheRight(derived()); -} - -/** replaces \c *this by \c *this * \a other. */ -template<typename Derived> -template<typename OtherDerived> -inline void MatrixBase<Derived>::applyOnTheLeft(const EigenBase<OtherDerived> &other) -{ - other.derived().applyThisOnTheLeft(derived()); -} - } // end namespace Eigen #endif // EIGEN_EIGENBASE_H diff --git a/Eigen/src/Core/MatrixBase.h b/Eigen/src/Core/MatrixBase.h index 61798317e..49b69f873 100644 --- a/Eigen/src/Core/MatrixBase.h +++ b/Eigen/src/Core/MatrixBase.h @@ -564,6 +564,51 @@ template<typename Derived> class MatrixBase {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} }; + +/*************************************************************************** +* Implementation of matrix base methods +***************************************************************************/ + +/** replaces \c *this by \c *this * \a other. + * + * \returns a reference to \c *this + * + * Example: \include MatrixBase_applyOnTheRight.cpp + * Output: \verbinclude MatrixBase_applyOnTheRight.out + */ +template<typename Derived> +template<typename OtherDerived> +inline Derived& +MatrixBase<Derived>::operator*=(const EigenBase<OtherDerived> &other) +{ + other.derived().applyThisOnTheRight(derived()); + return derived(); +} + +/** replaces \c *this by \c *this * \a other. It is equivalent to MatrixBase::operator*=(). + * + * Example: \include MatrixBase_applyOnTheRight.cpp + * Output: \verbinclude MatrixBase_applyOnTheRight.out + */ +template<typename Derived> +template<typename OtherDerived> +inline void MatrixBase<Derived>::applyOnTheRight(const EigenBase<OtherDerived> &other) +{ + other.derived().applyThisOnTheRight(derived()); +} + +/** replaces \c *this by \a other * \c *this. + * + * Example: \include MatrixBase_applyOnTheLeft.cpp + * Output: \verbinclude MatrixBase_applyOnTheLeft.out + */ +template<typename Derived> +template<typename OtherDerived> +inline void MatrixBase<Derived>::applyOnTheLeft(const EigenBase<OtherDerived> &other) +{ + other.derived().applyThisOnTheLeft(derived()); +} + } // end namespace Eigen #endif // EIGEN_MATRIXBASE_H diff --git a/Eigen/src/Core/StableNorm.h b/Eigen/src/Core/StableNorm.h index c219e2f53..525620bad 100644 --- a/Eigen/src/Core/StableNorm.h +++ b/Eigen/src/Core/StableNorm.h @@ -17,16 +17,29 @@ namespace internal { template<typename ExpressionType, typename Scalar> inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& scale, Scalar& invScale) { - Scalar max = bl.cwiseAbs().maxCoeff(); - if (max>scale) + using std::max; + Scalar maxCoeff = bl.cwiseAbs().maxCoeff(); + + if (maxCoeff>scale) { - ssq = ssq * numext::abs2(scale/max); - scale = max; - invScale = Scalar(1)/scale; + ssq = ssq * numext::abs2(scale/maxCoeff); + Scalar tmp = Scalar(1)/maxCoeff; + if(tmp > NumTraits<Scalar>::highest()) + { + invScale = NumTraits<Scalar>::highest(); + scale = Scalar(1)/invScale; + } + else + { + scale = maxCoeff; + invScale = tmp; + } } - // TODO if the max is much much smaller than the current scale, + + // TODO if the maxCoeff is much much smaller than the current scale, // then we can neglect this sub vector - ssq += (bl*invScale).squaredNorm(); + if(scale>Scalar(0)) // if scale==0, then bl is 0 + ssq += (bl*invScale).squaredNorm(); } template<typename Derived> diff --git a/Eigen/src/Core/util/Memory.h b/Eigen/src/Core/util/Memory.h index 2f2398bbf..88cf1c30d 100644 --- a/Eigen/src/Core/util/Memory.h +++ b/Eigen/src/Core/util/Memory.h @@ -608,7 +608,7 @@ template<typename T> class aligned_stack_memory_handler */ #ifdef EIGEN_ALLOCA // The native alloca() that comes with llvm aligns buffer on 16 bytes even when AVX is enabled. - #if defined(__arm__) || EIGEN_ALIGN_BYTES > 16 +#if defined(__arm__) || defined(_WIN32) || EIGEN_ALIGN_BYTES > 16 #define EIGEN_ALIGNED_ALLOCA(SIZE) reinterpret_cast<void*>((reinterpret_cast<size_t>(EIGEN_ALLOCA(SIZE+EIGEN_ALIGN_BYTES)) & ~(size_t(EIGEN_ALIGN_BYTES-1))) + EIGEN_ALIGN_BYTES) #else #define EIGEN_ALIGNED_ALLOCA EIGEN_ALLOCA @@ -761,11 +761,27 @@ public: ::new( p ) T( value ); } +#if (__cplusplus >= 201103L) + template <typename U, typename... Args> + void construct( U* u, Args&&... args) + { + ::new( static_cast<void*>(u) ) U( std::forward<Args>( args )... ); + } +#endif + void destroy( pointer p ) { p->~T(); } +#if (__cplusplus >= 201103L) + template <typename U> + void destroy( U* u ) + { + u->~U(); + } +#endif + void deallocate( pointer p, size_type /*num*/ ) { internal::aligned_free( p ); diff --git a/Eigen/src/Geometry/Transform.h b/Eigen/src/Geometry/Transform.h index 419f90148..0a5012cfe 100644 --- a/Eigen/src/Geometry/Transform.h +++ b/Eigen/src/Geometry/Transform.h @@ -530,9 +530,9 @@ public: inline Transform& operator=(const UniformScaling<Scalar>& t); inline Transform& operator*=(const UniformScaling<Scalar>& s) { return scale(s.factor()); } - inline Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Isometry)> operator*(const UniformScaling<Scalar>& s) const + inline Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Mode)> operator*(const UniformScaling<Scalar>& s) const { - Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Isometry),Options> res = *this; + Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Mode),Options> res = *this; res.scale(s.factor()); return res; } @@ -699,9 +699,13 @@ template<typename Scalar, int Dim, int Mode,int Options> Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const QMatrix& other) { EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE) - m_matrix << other.m11(), other.m21(), other.dx(), - other.m12(), other.m22(), other.dy(), - 0, 0, 1; + if (Mode == int(AffineCompact)) + m_matrix << other.m11(), other.m21(), other.dx(), + other.m12(), other.m22(), other.dy(); + else + m_matrix << other.m11(), other.m21(), other.dx(), + other.m12(), other.m22(), other.dy(), + 0, 0, 1; return *this; } diff --git a/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h b/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h index 4b13f08d4..5c320e2d2 100644 --- a/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h +++ b/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h @@ -66,9 +66,9 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r } // unordered insertion - for(int k=0; k<nnz; ++k) + for(Index k=0; k<nnz; ++k) { - int i = indices[k]; + Index i = indices[k]; res.insertBackByOuterInnerUnordered(j,i) = values[i]; mask[i] = false; } @@ -76,8 +76,8 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r #if 0 // alternative ordered insertion code: - int t200 = rows/(log2(200)*1.39); - int t = (rows*100)/139; + Index t200 = rows/(log2(200)*1.39); + Index t = (rows*100)/139; // FIXME reserve nnz non zeros // FIXME implement fast sort algorithms for very small nnz @@ -90,9 +90,9 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r if(true) { if(nnz>1) std::sort(indices.data(),indices.data()+nnz); - for(int k=0; k<nnz; ++k) + for(Index k=0; k<nnz; ++k) { - int i = indices[k]; + Index i = indices[k]; res.insertBackByOuterInner(j,i) = values[i]; mask[i] = false; } @@ -100,7 +100,7 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r else { // dense path - for(int i=0; i<rows; ++i) + for(Index i=0; i<rows; ++i) { if(mask[i]) { @@ -134,8 +134,8 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,C static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix; - typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix; ColMajorMatrix resCol(lhs.rows(),rhs.cols()); internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol); // sort the non zeros: @@ -149,7 +149,7 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,C { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix; RowMajorMatrix rhsRow = rhs; RowMajorMatrix resRow(lhs.rows(), rhs.cols()); internal::conservative_sparse_sparse_product_impl<RowMajorMatrix,Lhs,RowMajorMatrix>(rhsRow, lhs, resRow); @@ -162,7 +162,7 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,R { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix; RowMajorMatrix lhsRow = lhs; RowMajorMatrix resRow(lhs.rows(), rhs.cols()); internal::conservative_sparse_sparse_product_impl<Rhs,RowMajorMatrix,RowMajorMatrix>(rhs, lhsRow, resRow); @@ -175,7 +175,7 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,R { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix; RowMajorMatrix resRow(lhs.rows(), rhs.cols()); internal::conservative_sparse_sparse_product_impl<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow); res = resRow; @@ -190,7 +190,7 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,C static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix; ColMajorMatrix resCol(lhs.rows(), rhs.cols()); internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol); res = resCol; @@ -202,7 +202,7 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,C { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix; ColMajorMatrix lhsCol = lhs; ColMajorMatrix resCol(lhs.rows(), rhs.cols()); internal::conservative_sparse_sparse_product_impl<ColMajorMatrix,Rhs,ColMajorMatrix>(lhsCol, rhs, resCol); @@ -215,7 +215,7 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,R { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix; ColMajorMatrix rhsCol = rhs; ColMajorMatrix resCol(lhs.rows(), rhs.cols()); internal::conservative_sparse_sparse_product_impl<Lhs,ColMajorMatrix,ColMajorMatrix>(lhs, rhsCol, resCol); @@ -228,8 +228,8 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,R { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix; - typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix; RowMajorMatrix resRow(lhs.rows(),rhs.cols()); internal::conservative_sparse_sparse_product_impl<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow); // sort the non zeros: diff --git a/Eigen/src/SparseCore/SparseBlock.h b/Eigen/src/SparseCore/SparseBlock.h index d0436aa7c..6f615e250 100644 --- a/Eigen/src/SparseCore/SparseBlock.h +++ b/Eigen/src/SparseCore/SparseBlock.h @@ -335,6 +335,14 @@ const Block<const Derived,Dynamic,Dynamic,true> SparseMatrixBase<Derived>::inner }
+namespace internal {
+
+template< typename XprType, int BlockRows, int BlockCols, bool InnerPanel,
+ bool OuterVector = (BlockCols==1 && XprType::IsRowMajor) || (BlockRows==1 && !XprType::IsRowMajor)>
+class GenericSparseBlockInnerIteratorImpl;
+
+}
+
/** Generic implementation of sparse Block expression.
* Real-only.
*/
@@ -342,11 +350,12 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class BlockImpl<XprType,BlockRows,BlockCols,InnerPanel,Sparse>
: public SparseMatrixBase<Block<XprType,BlockRows,BlockCols,InnerPanel> >, internal::no_assignment_operator
{
- typedef typename internal::remove_all<typename XprType::Nested>::type _MatrixTypeNested;
typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
public:
enum { IsRowMajor = internal::traits<BlockType>::IsRowMajor };
EIGEN_SPARSE_PUBLIC_INTERFACE(BlockType)
+
+ typedef typename internal::remove_all<typename XprType::Nested>::type _MatrixTypeNested;
/** Column or Row constructor
*/
@@ -354,8 +363,8 @@ public: : m_matrix(xpr),
m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0),
m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0),
- m_blockRows(xpr.rows()),
- m_blockCols(xpr.cols())
+ m_blockRows(BlockRows==1 ? 1 : xpr.rows()),
+ m_blockCols(BlockCols==1 ? 1 : xpr.cols())
{}
/** Dynamic-size constructor
@@ -394,29 +403,8 @@ public: inline const _MatrixTypeNested& nestedExpression() const { return m_matrix; }
- class InnerIterator : public _MatrixTypeNested::InnerIterator
- {
- typedef typename _MatrixTypeNested::InnerIterator Base;
- const BlockType& m_block;
- Index m_end;
- public:
-
- EIGEN_STRONG_INLINE InnerIterator(const BlockType& block, Index outer)
- : Base(block.derived().nestedExpression(), outer + (IsRowMajor ? block.m_startRow.value() : block.m_startCol.value())),
- m_block(block),
- m_end(IsRowMajor ? block.m_startCol.value()+block.m_blockCols.value() : block.m_startRow.value()+block.m_blockRows.value())
- {
- while( (Base::operator bool()) && (Base::index() < (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value())) )
- Base::operator++();
- }
-
- inline Index index() const { return Base::index() - (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value()); }
- inline Index outer() const { return Base::outer() - (IsRowMajor ? m_block.m_startRow.value() : m_block.m_startCol.value()); }
- inline Index row() const { return Base::row() - m_block.m_startRow.value(); }
- inline Index col() const { return Base::col() - m_block.m_startCol.value(); }
-
- inline operator bool() const { return Base::operator bool() && Base::index() < m_end; }
- };
+ typedef internal::GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel> InnerIterator;
+
class ReverseInnerIterator : public _MatrixTypeNested::ReverseInnerIterator
{
typedef typename _MatrixTypeNested::ReverseInnerIterator Base;
@@ -441,7 +429,7 @@ public: inline operator bool() const { return Base::operator bool() && Base::index() >= m_begin; }
};
protected:
- friend class InnerIterator;
+ friend class internal::GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel>;
friend class ReverseInnerIterator;
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
@@ -454,6 +442,100 @@ public: };
+namespace internal {
+ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
+ class GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel,false> : public Block<XprType, BlockRows, BlockCols, InnerPanel>::_MatrixTypeNested::InnerIterator
+ {
+ typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
+ enum {
+ IsRowMajor = BlockType::IsRowMajor
+ };
+ typedef typename BlockType::_MatrixTypeNested _MatrixTypeNested;
+ typedef typename BlockType::Index Index;
+ typedef typename _MatrixTypeNested::InnerIterator Base;
+ const BlockType& m_block;
+ Index m_end;
+ public:
+
+ EIGEN_STRONG_INLINE GenericSparseBlockInnerIteratorImpl(const BlockType& block, Index outer)
+ : Base(block.derived().nestedExpression(), outer + (IsRowMajor ? block.m_startRow.value() : block.m_startCol.value())),
+ m_block(block),
+ m_end(IsRowMajor ? block.m_startCol.value()+block.m_blockCols.value() : block.m_startRow.value()+block.m_blockRows.value())
+ {
+ while( (Base::operator bool()) && (Base::index() < (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value())) )
+ Base::operator++();
+ }
+
+ inline Index index() const { return Base::index() - (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value()); }
+ inline Index outer() const { return Base::outer() - (IsRowMajor ? m_block.m_startRow.value() : m_block.m_startCol.value()); }
+ inline Index row() const { return Base::row() - m_block.m_startRow.value(); }
+ inline Index col() const { return Base::col() - m_block.m_startCol.value(); }
+
+ inline operator bool() const { return Base::operator bool() && Base::index() < m_end; }
+ };
+
+ // Row vector of a column-major sparse matrix or column of a row-major one.
+ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
+ class GenericSparseBlockInnerIteratorImpl<XprType,BlockRows,BlockCols,InnerPanel,true>
+ {
+ typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
+ enum {
+ IsRowMajor = BlockType::IsRowMajor
+ };
+ typedef typename BlockType::_MatrixTypeNested _MatrixTypeNested;
+ typedef typename BlockType::Index Index;
+ typedef typename BlockType::Scalar Scalar;
+ const BlockType& m_block;
+ Index m_outerPos;
+ Index m_innerIndex;
+ Scalar m_value;
+ Index m_end;
+ public:
+
+ EIGEN_STRONG_INLINE GenericSparseBlockInnerIteratorImpl(const BlockType& block, Index outer = 0)
+ :
+ m_block(block),
+ m_outerPos( (IsRowMajor ? block.m_startCol.value() : block.m_startRow.value()) - 1), // -1 so that operator++ finds the first non-zero entry
+ m_innerIndex(IsRowMajor ? block.m_startRow.value() : block.m_startCol.value()),
+ m_end(IsRowMajor ? block.m_startCol.value()+block.m_blockCols.value() : block.m_startRow.value()+block.m_blockRows.value())
+ {
+ EIGEN_UNUSED_VARIABLE(outer);
+ eigen_assert(outer==0);
+
+ ++(*this);
+ }
+
+ inline Index index() const { return m_outerPos - (IsRowMajor ? m_block.m_startCol.value() : m_block.m_startRow.value()); }
+ inline Index outer() const { return 0; }
+ inline Index row() const { return IsRowMajor ? 0 : index(); }
+ inline Index col() const { return IsRowMajor ? index() : 0; }
+
+ inline Scalar value() const { return m_value; }
+
+ inline GenericSparseBlockInnerIteratorImpl& operator++()
+ {
+ // search next non-zero entry
+ while(m_outerPos<m_end)
+ {
+ m_outerPos++;
+ typename XprType::InnerIterator it(m_block.m_matrix, m_outerPos);
+ // search for the key m_innerIndex in the current outer-vector
+ while(it && it.index() < m_innerIndex) ++it;
+ if(it && it.index()==m_innerIndex)
+ {
+ m_value = it.value();
+ break;
+ }
+ }
+ return *this;
+ }
+
+ inline operator bool() const { return m_outerPos < m_end; }
+ };
+
+} // end namespace internal
+
+
} // end namespace Eigen
#endif // EIGEN_SPARSE_BLOCK_H
diff --git a/Eigen/src/SparseCore/SparseDenseProduct.h b/Eigen/src/SparseCore/SparseDenseProduct.h index 6132a4880..610833f3b 100644 --- a/Eigen/src/SparseCore/SparseDenseProduct.h +++ b/Eigen/src/SparseCore/SparseDenseProduct.h @@ -125,7 +125,7 @@ class SparseDenseOuterProduct<Lhs,Rhs,Transpose>::InnerIterator : public _LhsNes inline Scalar value() const { return Base::value() * m_factor; } protected: - int m_outer; + Index m_outer; Scalar m_factor; }; @@ -156,7 +156,7 @@ struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, t { for(Index c=0; c<rhs.cols(); ++c) { - int n = lhs.outerSize(); + Index n = lhs.outerSize(); for(Index j=0; j<n; ++j) { typename Res::Scalar tmp(0); diff --git a/Eigen/src/SparseCore/SparseMatrix.h b/Eigen/src/SparseCore/SparseMatrix.h index f2e234eee..0e7e760fb 100644 --- a/Eigen/src/SparseCore/SparseMatrix.h +++ b/Eigen/src/SparseCore/SparseMatrix.h @@ -402,7 +402,7 @@ class SparseMatrix * \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]==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]; } @@ -480,7 +480,7 @@ class SparseMatrix if(m_innerNonZeros != 0) return; m_innerNonZeros = static_cast<Index*>(std::malloc(m_outerSize * sizeof(Index))); - for (int i = 0; i < m_outerSize; i++) + for (Index i = 0; i < m_outerSize; i++) { m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i]; } @@ -752,8 +752,8 @@ class SparseMatrix 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 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) << ") "; @@ -1022,7 +1022,7 @@ void SparseMatrix<Scalar,_Options,_Index>::sumupDuplicates() 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) + for(Index j=0; j<outerSize(); ++j) { Index start = count; Index oldEnd = m_outerIndex[j]+m_innerNonZeros[j]; diff --git a/Eigen/src/SparseCore/SparseMatrixBase.h b/Eigen/src/SparseCore/SparseMatrixBase.h index 706f699b8..bbcf7fb1c 100644 --- a/Eigen/src/SparseCore/SparseMatrixBase.h +++ b/Eigen/src/SparseCore/SparseMatrixBase.h @@ -302,8 +302,8 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived> } else { - SparseMatrix<Scalar, RowMajorBit> trans = m; - s << static_cast<const SparseMatrixBase<SparseMatrix<Scalar, RowMajorBit> >&>(trans); + SparseMatrix<Scalar, RowMajorBit, Index> trans = m; + s << static_cast<const SparseMatrixBase<SparseMatrix<Scalar, RowMajorBit, Index> >&>(trans); } } return s; diff --git a/Eigen/src/SparseCore/SparseProduct.h b/Eigen/src/SparseCore/SparseProduct.h index 70b6480ef..cf7663070 100644 --- a/Eigen/src/SparseCore/SparseProduct.h +++ b/Eigen/src/SparseCore/SparseProduct.h @@ -16,6 +16,7 @@ template<typename Lhs, typename Rhs> struct SparseSparseProductReturnType { typedef typename internal::traits<Lhs>::Scalar Scalar; + typedef typename internal::traits<Lhs>::Index Index; enum { LhsRowMajor = internal::traits<Lhs>::Flags & RowMajorBit, RhsRowMajor = internal::traits<Rhs>::Flags & RowMajorBit, @@ -24,11 +25,11 @@ struct SparseSparseProductReturnType }; typedef typename internal::conditional<TransposeLhs, - SparseMatrix<Scalar,0>, + SparseMatrix<Scalar,0,Index>, typename internal::nested<Lhs,Rhs::RowsAtCompileTime>::type>::type LhsNested; typedef typename internal::conditional<TransposeRhs, - SparseMatrix<Scalar,0>, + SparseMatrix<Scalar,0,Index>, typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type>::type RhsNested; typedef SparseSparseProduct<LhsNested, RhsNested> Type; diff --git a/Eigen/src/SparseCore/SparseSparseProductWithPruning.h b/Eigen/src/SparseCore/SparseSparseProductWithPruning.h index 70857c7b6..fcc18f5c9 100644 --- a/Eigen/src/SparseCore/SparseSparseProductWithPruning.h +++ b/Eigen/src/SparseCore/SparseSparseProductWithPruning.h @@ -27,7 +27,7 @@ static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& r // make sure to call innerSize/outerSize since we fake the storage order. Index rows = lhs.innerSize(); Index cols = rhs.outerSize(); - //int size = lhs.outerSize(); + //Index size = lhs.outerSize(); eigen_assert(lhs.outerSize() == rhs.innerSize()); // allocate a temporary buffer @@ -100,7 +100,7 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,C static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) { // we need a col-major matrix to hold the result - typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> SparseTemporaryType; SparseTemporaryType _res(res.rows(), res.cols()); internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,SparseTemporaryType>(lhs, rhs, _res, tolerance); res = _res; @@ -126,10 +126,11 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,R typedef typename ResultType::RealScalar RealScalar; static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix; - ColMajorMatrix colLhs(lhs); - ColMajorMatrix colRhs(rhs); - internal::sparse_sparse_product_with_pruning_impl<ColMajorMatrix,ColMajorMatrix,ResultType>(colLhs, colRhs, res, tolerance); + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::Index> ColMajorMatrixLhs; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::Index> ColMajorMatrixRhs; + ColMajorMatrixLhs colLhs(lhs); + ColMajorMatrixRhs colRhs(rhs); + internal::sparse_sparse_product_with_pruning_impl<ColMajorMatrixLhs,ColMajorMatrixRhs,ResultType>(colLhs, colRhs, res, tolerance); // let's transpose the product to get a column x column product // typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType; diff --git a/Eigen/src/SparseLU/SparseLU_Memory.h b/Eigen/src/SparseLU/SparseLU_Memory.h index d068d62df..1ffa7d54e 100644 --- a/Eigen/src/SparseLU/SparseLU_Memory.h +++ b/Eigen/src/SparseLU/SparseLU_Memory.h @@ -70,7 +70,7 @@ Index SparseLUImpl<Scalar,Index>::expand(VectorType& vec, Index& length, Index if(num_expansions == 0 || keep_prev) new_len = length ; // First time allocate requested else - new_len = Index(alpha * length); + new_len = (std::max)(length+1,Index(alpha * length)); VectorType old_vec; // Temporary vector to hold the previous values if (nbElts > 0 ) @@ -107,7 +107,7 @@ Index SparseLUImpl<Scalar,Index>::expand(VectorType& vec, Index& length, Index do { alpha = (alpha + 1)/2; - new_len = Index(alpha * length); + new_len = (std::max)(length+1,Index(alpha * length)); #ifdef EIGEN_EXCEPTIONS try #endif |