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Diffstat (limited to 'src/3rdparty/eigen/Eigen/src/Core/VectorwiseOp.h')
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diff --git a/src/3rdparty/eigen/Eigen/src/Core/VectorwiseOp.h b/src/3rdparty/eigen/Eigen/src/Core/VectorwiseOp.h new file mode 100644 index 000000000..870f4f1e4 --- /dev/null +++ b/src/3rdparty/eigen/Eigen/src/Core/VectorwiseOp.h @@ -0,0 +1,784 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2019 Gael Guennebaud <gael.guennebaud@inria.fr> +// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> +// +// 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_PARTIAL_REDUX_H +#define EIGEN_PARTIAL_REDUX_H + +namespace Eigen { + +/** \class PartialReduxExpr + * \ingroup Core_Module + * + * \brief Generic expression of a partially reduxed matrix + * + * \tparam MatrixType the type of the matrix we are applying the redux operation + * \tparam MemberOp type of the member functor + * \tparam Direction indicates the direction of the redux (#Vertical or #Horizontal) + * + * This class represents an expression of a partial redux operator of a matrix. + * It is the return type of some VectorwiseOp functions, + * and most of the time this is the only way it is used. + * + * \sa class VectorwiseOp + */ + +template< typename MatrixType, typename MemberOp, int Direction> +class PartialReduxExpr; + +namespace internal { +template<typename MatrixType, typename MemberOp, int Direction> +struct traits<PartialReduxExpr<MatrixType, MemberOp, Direction> > + : traits<MatrixType> +{ + typedef typename MemberOp::result_type Scalar; + typedef typename traits<MatrixType>::StorageKind StorageKind; + typedef typename traits<MatrixType>::XprKind XprKind; + typedef typename MatrixType::Scalar InputScalar; + enum { + RowsAtCompileTime = Direction==Vertical ? 1 : MatrixType::RowsAtCompileTime, + ColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::ColsAtCompileTime, + MaxRowsAtCompileTime = Direction==Vertical ? 1 : MatrixType::MaxRowsAtCompileTime, + MaxColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::MaxColsAtCompileTime, + Flags = RowsAtCompileTime == 1 ? RowMajorBit : 0, + TraversalSize = Direction==Vertical ? MatrixType::RowsAtCompileTime : MatrixType::ColsAtCompileTime + }; +}; +} + +template< typename MatrixType, typename MemberOp, int Direction> +class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::type, + internal::no_assignment_operator +{ + public: + + typedef typename internal::dense_xpr_base<PartialReduxExpr>::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(PartialReduxExpr) + + EIGEN_DEVICE_FUNC + explicit PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp()) + : m_matrix(mat), m_functor(func) {} + + EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR + Index rows() const EIGEN_NOEXCEPT { return (Direction==Vertical ? 1 : m_matrix.rows()); } + EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR + Index cols() const EIGEN_NOEXCEPT { return (Direction==Horizontal ? 1 : m_matrix.cols()); } + + EIGEN_DEVICE_FUNC + typename MatrixType::Nested nestedExpression() const { return m_matrix; } + + EIGEN_DEVICE_FUNC + const MemberOp& functor() const { return m_functor; } + + protected: + typename MatrixType::Nested m_matrix; + const MemberOp m_functor; +}; + +template<typename A,typename B> struct partial_redux_dummy_func; + +#define EIGEN_MAKE_PARTIAL_REDUX_FUNCTOR(MEMBER,COST,VECTORIZABLE,BINARYOP) \ + template <typename ResultType,typename Scalar> \ + struct member_##MEMBER { \ + EIGEN_EMPTY_STRUCT_CTOR(member_##MEMBER) \ + typedef ResultType result_type; \ + typedef BINARYOP<Scalar,Scalar> BinaryOp; \ + template<int Size> struct Cost { enum { value = COST }; }; \ + enum { Vectorizable = VECTORIZABLE }; \ + template<typename XprType> \ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE \ + ResultType operator()(const XprType& mat) const \ + { return mat.MEMBER(); } \ + BinaryOp binaryFunc() const { return BinaryOp(); } \ + } + +#define EIGEN_MEMBER_FUNCTOR(MEMBER,COST) \ + EIGEN_MAKE_PARTIAL_REDUX_FUNCTOR(MEMBER,COST,0,partial_redux_dummy_func) + +namespace internal { + +EIGEN_MEMBER_FUNCTOR(norm, (Size+5) * NumTraits<Scalar>::MulCost + (Size-1)*NumTraits<Scalar>::AddCost); +EIGEN_MEMBER_FUNCTOR(stableNorm, (Size+5) * NumTraits<Scalar>::MulCost + (Size-1)*NumTraits<Scalar>::AddCost); +EIGEN_MEMBER_FUNCTOR(blueNorm, (Size+5) * NumTraits<Scalar>::MulCost + (Size-1)*NumTraits<Scalar>::AddCost); +EIGEN_MEMBER_FUNCTOR(hypotNorm, (Size-1) * functor_traits<scalar_hypot_op<Scalar> >::Cost ); +EIGEN_MEMBER_FUNCTOR(all, (Size-1)*NumTraits<Scalar>::AddCost); +EIGEN_MEMBER_FUNCTOR(any, (Size-1)*NumTraits<Scalar>::AddCost); +EIGEN_MEMBER_FUNCTOR(count, (Size-1)*NumTraits<Scalar>::AddCost); + +EIGEN_MAKE_PARTIAL_REDUX_FUNCTOR(sum, (Size-1)*NumTraits<Scalar>::AddCost, 1, internal::scalar_sum_op); +EIGEN_MAKE_PARTIAL_REDUX_FUNCTOR(minCoeff, (Size-1)*NumTraits<Scalar>::AddCost, 1, internal::scalar_min_op); +EIGEN_MAKE_PARTIAL_REDUX_FUNCTOR(maxCoeff, (Size-1)*NumTraits<Scalar>::AddCost, 1, internal::scalar_max_op); +EIGEN_MAKE_PARTIAL_REDUX_FUNCTOR(prod, (Size-1)*NumTraits<Scalar>::MulCost, 1, internal::scalar_product_op); + +template <int p, typename ResultType,typename Scalar> +struct member_lpnorm { + typedef ResultType result_type; + enum { Vectorizable = 0 }; + template<int Size> struct Cost + { enum { value = (Size+5) * NumTraits<Scalar>::MulCost + (Size-1)*NumTraits<Scalar>::AddCost }; }; + EIGEN_DEVICE_FUNC member_lpnorm() {} + template<typename XprType> + EIGEN_DEVICE_FUNC inline ResultType operator()(const XprType& mat) const + { return mat.template lpNorm<p>(); } +}; + +template <typename BinaryOpT, typename Scalar> +struct member_redux { + typedef BinaryOpT BinaryOp; + typedef typename result_of< + BinaryOp(const Scalar&,const Scalar&) + >::type result_type; + + enum { Vectorizable = functor_traits<BinaryOp>::PacketAccess }; + template<int Size> struct Cost { enum { value = (Size-1) * functor_traits<BinaryOp>::Cost }; }; + EIGEN_DEVICE_FUNC explicit member_redux(const BinaryOp func) : m_functor(func) {} + template<typename Derived> + EIGEN_DEVICE_FUNC inline result_type operator()(const DenseBase<Derived>& mat) const + { return mat.redux(m_functor); } + const BinaryOp& binaryFunc() const { return m_functor; } + const BinaryOp m_functor; +}; +} + +/** \class VectorwiseOp + * \ingroup Core_Module + * + * \brief Pseudo expression providing broadcasting and partial reduction operations + * + * \tparam ExpressionType the type of the object on which to do partial reductions + * \tparam Direction indicates whether to operate on columns (#Vertical) or rows (#Horizontal) + * + * This class represents a pseudo expression with broadcasting and partial reduction features. + * It is the return type of DenseBase::colwise() and DenseBase::rowwise() + * and most of the time this is the only way it is explicitly used. + * + * To understand the logic of rowwise/colwise expression, let's consider a generic case `A.colwise().foo()` + * where `foo` is any method of `VectorwiseOp`. This expression is equivalent to applying `foo()` to each + * column of `A` and then re-assemble the outputs in a matrix expression: + * \code [A.col(0).foo(), A.col(1).foo(), ..., A.col(A.cols()-1).foo()] \endcode + * + * Example: \include MatrixBase_colwise.cpp + * Output: \verbinclude MatrixBase_colwise.out + * + * The begin() and end() methods are obviously exceptions to the previous rule as they + * return STL-compatible begin/end iterators to the rows or columns of the nested expression. + * Typical use cases include for-range-loop and calls to STL algorithms: + * + * Example: \include MatrixBase_colwise_iterator_cxx11.cpp + * Output: \verbinclude MatrixBase_colwise_iterator_cxx11.out + * + * For a partial reduction on an empty input, some rules apply. + * For the sake of clarity, let's consider a vertical reduction: + * - If the number of columns is zero, then a 1x0 row-major vector expression is returned. + * - Otherwise, if the number of rows is zero, then + * - a row vector of zeros is returned for sum-like reductions (sum, squaredNorm, norm, etc.) + * - a row vector of ones is returned for a product reduction (e.g., <code>MatrixXd(n,0).colwise().prod()</code>) + * - an assert is triggered for all other reductions (minCoeff,maxCoeff,redux(bin_op)) + * + * \sa DenseBase::colwise(), DenseBase::rowwise(), class PartialReduxExpr + */ +template<typename ExpressionType, int Direction> class VectorwiseOp +{ + public: + + typedef typename ExpressionType::Scalar Scalar; + typedef typename ExpressionType::RealScalar RealScalar; + typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3 + typedef typename internal::ref_selector<ExpressionType>::non_const_type ExpressionTypeNested; + typedef typename internal::remove_all<ExpressionTypeNested>::type ExpressionTypeNestedCleaned; + + template<template<typename OutScalar,typename InputScalar> class Functor, + typename ReturnScalar=Scalar> struct ReturnType + { + typedef PartialReduxExpr<ExpressionType, + Functor<ReturnScalar,Scalar>, + Direction + > Type; + }; + + template<typename BinaryOp> struct ReduxReturnType + { + typedef PartialReduxExpr<ExpressionType, + internal::member_redux<BinaryOp,Scalar>, + Direction + > Type; + }; + + enum { + isVertical = (Direction==Vertical) ? 1 : 0, + isHorizontal = (Direction==Horizontal) ? 1 : 0 + }; + + protected: + + template<typename OtherDerived> struct ExtendedType { + typedef Replicate<OtherDerived, + isVertical ? 1 : ExpressionType::RowsAtCompileTime, + isHorizontal ? 1 : ExpressionType::ColsAtCompileTime> Type; + }; + + /** \internal + * Replicates a vector to match the size of \c *this */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + typename ExtendedType<OtherDerived>::Type + extendedTo(const DenseBase<OtherDerived>& other) const + { + EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isVertical, OtherDerived::MaxColsAtCompileTime==1), + YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED) + EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isHorizontal, OtherDerived::MaxRowsAtCompileTime==1), + YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED) + return typename ExtendedType<OtherDerived>::Type + (other.derived(), + isVertical ? 1 : m_matrix.rows(), + isHorizontal ? 1 : m_matrix.cols()); + } + + template<typename OtherDerived> struct OppositeExtendedType { + typedef Replicate<OtherDerived, + isHorizontal ? 1 : ExpressionType::RowsAtCompileTime, + isVertical ? 1 : ExpressionType::ColsAtCompileTime> Type; + }; + + /** \internal + * Replicates a vector in the opposite direction to match the size of \c *this */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + typename OppositeExtendedType<OtherDerived>::Type + extendedToOpposite(const DenseBase<OtherDerived>& other) const + { + EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isHorizontal, OtherDerived::MaxColsAtCompileTime==1), + YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED) + EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isVertical, OtherDerived::MaxRowsAtCompileTime==1), + YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED) + return typename OppositeExtendedType<OtherDerived>::Type + (other.derived(), + isHorizontal ? 1 : m_matrix.rows(), + isVertical ? 1 : m_matrix.cols()); + } + + public: + EIGEN_DEVICE_FUNC + explicit inline VectorwiseOp(ExpressionType& matrix) : m_matrix(matrix) {} + + /** \internal */ + EIGEN_DEVICE_FUNC + inline const ExpressionType& _expression() const { return m_matrix; } + + #ifdef EIGEN_PARSED_BY_DOXYGEN + /** STL-like <a href="https://en.cppreference.com/w/cpp/named_req/RandomAccessIterator">RandomAccessIterator</a> + * iterator type over the columns or rows as returned by the begin() and end() methods. + */ + random_access_iterator_type iterator; + /** This is the const version of iterator (aka read-only) */ + random_access_iterator_type const_iterator; + #else + typedef internal::subvector_stl_iterator<ExpressionType, DirectionType(Direction)> iterator; + typedef internal::subvector_stl_iterator<const ExpressionType, DirectionType(Direction)> const_iterator; + typedef internal::subvector_stl_reverse_iterator<ExpressionType, DirectionType(Direction)> reverse_iterator; + typedef internal::subvector_stl_reverse_iterator<const ExpressionType, DirectionType(Direction)> const_reverse_iterator; + #endif + + /** returns an iterator to the first row (rowwise) or column (colwise) of the nested expression. + * \sa end(), cbegin() + */ + iterator begin() { return iterator (m_matrix, 0); } + /** const version of begin() */ + const_iterator begin() const { return const_iterator(m_matrix, 0); } + /** const version of begin() */ + const_iterator cbegin() const { return const_iterator(m_matrix, 0); } + + /** returns a reverse iterator to the last row (rowwise) or column (colwise) of the nested expression. + * \sa rend(), crbegin() + */ + reverse_iterator rbegin() { return reverse_iterator (m_matrix, m_matrix.template subVectors<DirectionType(Direction)>()-1); } + /** const version of rbegin() */ + const_reverse_iterator rbegin() const { return const_reverse_iterator (m_matrix, m_matrix.template subVectors<DirectionType(Direction)>()-1); } + /** const version of rbegin() */ + const_reverse_iterator crbegin() const { return const_reverse_iterator (m_matrix, m_matrix.template subVectors<DirectionType(Direction)>()-1); } + + /** returns an iterator to the row (resp. column) following the last row (resp. column) of the nested expression + * \sa begin(), cend() + */ + iterator end() { return iterator (m_matrix, m_matrix.template subVectors<DirectionType(Direction)>()); } + /** const version of end() */ + const_iterator end() const { return const_iterator(m_matrix, m_matrix.template subVectors<DirectionType(Direction)>()); } + /** const version of end() */ + const_iterator cend() const { return const_iterator(m_matrix, m_matrix.template subVectors<DirectionType(Direction)>()); } + + /** returns a reverse iterator to the row (resp. column) before the first row (resp. column) of the nested expression + * \sa begin(), cend() + */ + reverse_iterator rend() { return reverse_iterator (m_matrix, -1); } + /** const version of rend() */ + const_reverse_iterator rend() const { return const_reverse_iterator (m_matrix, -1); } + /** const version of rend() */ + const_reverse_iterator crend() const { return const_reverse_iterator (m_matrix, -1); } + + /** \returns a row or column vector expression of \c *this reduxed by \a func + * + * The template parameter \a BinaryOp is the type of the functor + * of the custom redux operator. Note that func must be an associative operator. + * + * \warning the size along the reduction direction must be strictly positive, + * otherwise an assertion is triggered. + * + * \sa class VectorwiseOp, DenseBase::colwise(), DenseBase::rowwise() + */ + template<typename BinaryOp> + EIGEN_DEVICE_FUNC + const typename ReduxReturnType<BinaryOp>::Type + redux(const BinaryOp& func = BinaryOp()) const + { + eigen_assert(redux_length()>0 && "you are using an empty matrix"); + return typename ReduxReturnType<BinaryOp>::Type(_expression(), internal::member_redux<BinaryOp,Scalar>(func)); + } + + typedef typename ReturnType<internal::member_minCoeff>::Type MinCoeffReturnType; + typedef typename ReturnType<internal::member_maxCoeff>::Type MaxCoeffReturnType; + typedef PartialReduxExpr<const CwiseUnaryOp<internal::scalar_abs2_op<Scalar>, const ExpressionTypeNestedCleaned>,internal::member_sum<RealScalar,RealScalar>,Direction> SquaredNormReturnType; + typedef CwiseUnaryOp<internal::scalar_sqrt_op<RealScalar>, const SquaredNormReturnType> NormReturnType; + typedef typename ReturnType<internal::member_blueNorm,RealScalar>::Type BlueNormReturnType; + typedef typename ReturnType<internal::member_stableNorm,RealScalar>::Type StableNormReturnType; + typedef typename ReturnType<internal::member_hypotNorm,RealScalar>::Type HypotNormReturnType; + typedef typename ReturnType<internal::member_sum>::Type SumReturnType; + typedef EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(SumReturnType,Scalar,quotient) MeanReturnType; + typedef typename ReturnType<internal::member_all>::Type AllReturnType; + typedef typename ReturnType<internal::member_any>::Type AnyReturnType; + typedef PartialReduxExpr<ExpressionType, internal::member_count<Index,Scalar>, Direction> CountReturnType; + typedef typename ReturnType<internal::member_prod>::Type ProdReturnType; + typedef Reverse<const ExpressionType, Direction> ConstReverseReturnType; + typedef Reverse<ExpressionType, Direction> ReverseReturnType; + + template<int p> struct LpNormReturnType { + typedef PartialReduxExpr<ExpressionType, internal::member_lpnorm<p,RealScalar,Scalar>,Direction> Type; + }; + + /** \returns a row (or column) vector expression of the smallest coefficient + * of each column (or row) of the referenced expression. + * + * \warning the size along the reduction direction must be strictly positive, + * otherwise an assertion is triggered. + * + * \warning the result is undefined if \c *this contains NaN. + * + * Example: \include PartialRedux_minCoeff.cpp + * Output: \verbinclude PartialRedux_minCoeff.out + * + * \sa DenseBase::minCoeff() */ + EIGEN_DEVICE_FUNC + const MinCoeffReturnType minCoeff() const + { + eigen_assert(redux_length()>0 && "you are using an empty matrix"); + return MinCoeffReturnType(_expression()); + } + + /** \returns a row (or column) vector expression of the largest coefficient + * of each column (or row) of the referenced expression. + * + * \warning the size along the reduction direction must be strictly positive, + * otherwise an assertion is triggered. + * + * \warning the result is undefined if \c *this contains NaN. + * + * Example: \include PartialRedux_maxCoeff.cpp + * Output: \verbinclude PartialRedux_maxCoeff.out + * + * \sa DenseBase::maxCoeff() */ + EIGEN_DEVICE_FUNC + const MaxCoeffReturnType maxCoeff() const + { + eigen_assert(redux_length()>0 && "you are using an empty matrix"); + return MaxCoeffReturnType(_expression()); + } + + /** \returns a row (or column) vector expression of the squared norm + * of each column (or row) of the referenced expression. + * This is a vector with real entries, even if the original matrix has complex entries. + * + * Example: \include PartialRedux_squaredNorm.cpp + * Output: \verbinclude PartialRedux_squaredNorm.out + * + * \sa DenseBase::squaredNorm() */ + EIGEN_DEVICE_FUNC + const SquaredNormReturnType squaredNorm() const + { return SquaredNormReturnType(m_matrix.cwiseAbs2()); } + + /** \returns a row (or column) vector expression of the norm + * of each column (or row) of the referenced expression. + * This is a vector with real entries, even if the original matrix has complex entries. + * + * Example: \include PartialRedux_norm.cpp + * Output: \verbinclude PartialRedux_norm.out + * + * \sa DenseBase::norm() */ + EIGEN_DEVICE_FUNC + const NormReturnType norm() const + { return NormReturnType(squaredNorm()); } + + /** \returns a row (or column) vector expression of the norm + * of each column (or row) of the referenced expression. + * This is a vector with real entries, even if the original matrix has complex entries. + * + * Example: \include PartialRedux_norm.cpp + * Output: \verbinclude PartialRedux_norm.out + * + * \sa DenseBase::norm() */ + template<int p> + EIGEN_DEVICE_FUNC + const typename LpNormReturnType<p>::Type lpNorm() const + { return typename LpNormReturnType<p>::Type(_expression()); } + + + /** \returns a row (or column) vector expression of the norm + * of each column (or row) of the referenced expression, using + * Blue's algorithm. + * This is a vector with real entries, even if the original matrix has complex entries. + * + * \sa DenseBase::blueNorm() */ + EIGEN_DEVICE_FUNC + const BlueNormReturnType blueNorm() const + { return BlueNormReturnType(_expression()); } + + + /** \returns a row (or column) vector expression of the norm + * of each column (or row) of the referenced expression, avoiding + * underflow and overflow. + * This is a vector with real entries, even if the original matrix has complex entries. + * + * \sa DenseBase::stableNorm() */ + EIGEN_DEVICE_FUNC + const StableNormReturnType stableNorm() const + { return StableNormReturnType(_expression()); } + + + /** \returns a row (or column) vector expression of the norm + * of each column (or row) of the referenced expression, avoiding + * underflow and overflow using a concatenation of hypot() calls. + * This is a vector with real entries, even if the original matrix has complex entries. + * + * \sa DenseBase::hypotNorm() */ + EIGEN_DEVICE_FUNC + const HypotNormReturnType hypotNorm() const + { return HypotNormReturnType(_expression()); } + + /** \returns a row (or column) vector expression of the sum + * of each column (or row) of the referenced expression. + * + * Example: \include PartialRedux_sum.cpp + * Output: \verbinclude PartialRedux_sum.out + * + * \sa DenseBase::sum() */ + EIGEN_DEVICE_FUNC + const SumReturnType sum() const + { return SumReturnType(_expression()); } + + /** \returns a row (or column) vector expression of the mean + * of each column (or row) of the referenced expression. + * + * \sa DenseBase::mean() */ + EIGEN_DEVICE_FUNC + const MeanReturnType mean() const + { return sum() / Scalar(Direction==Vertical?m_matrix.rows():m_matrix.cols()); } + + /** \returns a row (or column) vector expression representing + * whether \b all coefficients of each respective column (or row) are \c true. + * This expression can be assigned to a vector with entries of type \c bool. + * + * \sa DenseBase::all() */ + EIGEN_DEVICE_FUNC + const AllReturnType all() const + { return AllReturnType(_expression()); } + + /** \returns a row (or column) vector expression representing + * whether \b at \b least one coefficient of each respective column (or row) is \c true. + * This expression can be assigned to a vector with entries of type \c bool. + * + * \sa DenseBase::any() */ + EIGEN_DEVICE_FUNC + const AnyReturnType any() const + { return AnyReturnType(_expression()); } + + /** \returns a row (or column) vector expression representing + * the number of \c true coefficients of each respective column (or row). + * This expression can be assigned to a vector whose entries have the same type as is used to + * index entries of the original matrix; for dense matrices, this is \c std::ptrdiff_t . + * + * Example: \include PartialRedux_count.cpp + * Output: \verbinclude PartialRedux_count.out + * + * \sa DenseBase::count() */ + EIGEN_DEVICE_FUNC + const CountReturnType count() const + { return CountReturnType(_expression()); } + + /** \returns a row (or column) vector expression of the product + * of each column (or row) of the referenced expression. + * + * Example: \include PartialRedux_prod.cpp + * Output: \verbinclude PartialRedux_prod.out + * + * \sa DenseBase::prod() */ + EIGEN_DEVICE_FUNC + const ProdReturnType prod() const + { return ProdReturnType(_expression()); } + + + /** \returns a matrix expression + * where each column (or row) are reversed. + * + * Example: \include Vectorwise_reverse.cpp + * Output: \verbinclude Vectorwise_reverse.out + * + * \sa DenseBase::reverse() */ + EIGEN_DEVICE_FUNC + const ConstReverseReturnType reverse() const + { return ConstReverseReturnType( _expression() ); } + + /** \returns a writable matrix expression + * where each column (or row) are reversed. + * + * \sa reverse() const */ + EIGEN_DEVICE_FUNC + ReverseReturnType reverse() + { return ReverseReturnType( _expression() ); } + + typedef Replicate<ExpressionType,(isVertical?Dynamic:1),(isHorizontal?Dynamic:1)> ReplicateReturnType; + EIGEN_DEVICE_FUNC + const ReplicateReturnType replicate(Index factor) const; + + /** + * \return an expression of the replication of each column (or row) of \c *this + * + * Example: \include DirectionWise_replicate.cpp + * Output: \verbinclude DirectionWise_replicate.out + * + * \sa VectorwiseOp::replicate(Index), DenseBase::replicate(), class Replicate + */ + // NOTE implemented here because of sunstudio's compilation errors + // isVertical*Factor+isHorizontal instead of (isVertical?Factor:1) to handle CUDA bug with ternary operator + template<int Factor> const Replicate<ExpressionType,isVertical*Factor+isHorizontal,isHorizontal*Factor+isVertical> + EIGEN_DEVICE_FUNC + replicate(Index factor = Factor) const + { + return Replicate<ExpressionType,(isVertical?Factor:1),(isHorizontal?Factor:1)> + (_expression(),isVertical?factor:1,isHorizontal?factor:1); + } + +/////////// Artithmetic operators /////////// + + /** Copies the vector \a other to each subvector of \c *this */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + ExpressionType& operator=(const DenseBase<OtherDerived>& other) + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + //eigen_assert((m_matrix.isNull()) == (other.isNull())); FIXME + return m_matrix = extendedTo(other.derived()); + } + + /** Adds the vector \a other to each subvector of \c *this */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + ExpressionType& operator+=(const DenseBase<OtherDerived>& other) + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return m_matrix += extendedTo(other.derived()); + } + + /** Substracts the vector \a other to each subvector of \c *this */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + ExpressionType& operator-=(const DenseBase<OtherDerived>& other) + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return m_matrix -= extendedTo(other.derived()); + } + + /** Multiples each subvector of \c *this by the vector \a other */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + ExpressionType& operator*=(const DenseBase<OtherDerived>& other) + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + m_matrix *= extendedTo(other.derived()); + return m_matrix; + } + + /** Divides each subvector of \c *this by the vector \a other */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + ExpressionType& operator/=(const DenseBase<OtherDerived>& other) + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + m_matrix /= extendedTo(other.derived()); + return m_matrix; + } + + /** Returns the expression of the sum of the vector \a other to each subvector of \c *this */ + template<typename OtherDerived> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC + CwiseBinaryOp<internal::scalar_sum_op<Scalar,typename OtherDerived::Scalar>, + const ExpressionTypeNestedCleaned, + const typename ExtendedType<OtherDerived>::Type> + operator+(const DenseBase<OtherDerived>& other) const + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return m_matrix + extendedTo(other.derived()); + } + + /** Returns the expression of the difference between each subvector of \c *this and the vector \a other */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + CwiseBinaryOp<internal::scalar_difference_op<Scalar,typename OtherDerived::Scalar>, + const ExpressionTypeNestedCleaned, + const typename ExtendedType<OtherDerived>::Type> + operator-(const DenseBase<OtherDerived>& other) const + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return m_matrix - extendedTo(other.derived()); + } + + /** Returns the expression where each subvector is the product of the vector \a other + * by the corresponding subvector of \c *this */ + template<typename OtherDerived> EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC + CwiseBinaryOp<internal::scalar_product_op<Scalar>, + const ExpressionTypeNestedCleaned, + const typename ExtendedType<OtherDerived>::Type> + EIGEN_DEVICE_FUNC + operator*(const DenseBase<OtherDerived>& other) const + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return m_matrix * extendedTo(other.derived()); + } + + /** Returns the expression where each subvector is the quotient of the corresponding + * subvector of \c *this by the vector \a other */ + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + CwiseBinaryOp<internal::scalar_quotient_op<Scalar>, + const ExpressionTypeNestedCleaned, + const typename ExtendedType<OtherDerived>::Type> + operator/(const DenseBase<OtherDerived>& other) const + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return m_matrix / extendedTo(other.derived()); + } + + /** \returns an expression where each column (or row) of the referenced matrix are normalized. + * The referenced matrix is \b not modified. + * \sa MatrixBase::normalized(), normalize() + */ + EIGEN_DEVICE_FUNC + CwiseBinaryOp<internal::scalar_quotient_op<Scalar>, + const ExpressionTypeNestedCleaned, + const typename OppositeExtendedType<NormReturnType>::Type> + normalized() const { return m_matrix.cwiseQuotient(extendedToOpposite(this->norm())); } + + + /** Normalize in-place each row or columns of the referenced matrix. + * \sa MatrixBase::normalize(), normalized() + */ + EIGEN_DEVICE_FUNC void normalize() { + m_matrix = this->normalized(); + } + + EIGEN_DEVICE_FUNC inline void reverseInPlace(); + +/////////// Geometry module /////////// + + typedef Homogeneous<ExpressionType,Direction> HomogeneousReturnType; + EIGEN_DEVICE_FUNC + HomogeneousReturnType homogeneous() const; + + typedef typename ExpressionType::PlainObject CrossReturnType; + template<typename OtherDerived> + EIGEN_DEVICE_FUNC + const CrossReturnType cross(const MatrixBase<OtherDerived>& other) const; + + enum { + HNormalized_Size = Direction==Vertical ? internal::traits<ExpressionType>::RowsAtCompileTime + : internal::traits<ExpressionType>::ColsAtCompileTime, + HNormalized_SizeMinusOne = HNormalized_Size==Dynamic ? Dynamic : HNormalized_Size-1 + }; + typedef Block<const ExpressionType, + Direction==Vertical ? int(HNormalized_SizeMinusOne) + : int(internal::traits<ExpressionType>::RowsAtCompileTime), + Direction==Horizontal ? int(HNormalized_SizeMinusOne) + : int(internal::traits<ExpressionType>::ColsAtCompileTime)> + HNormalized_Block; + typedef Block<const ExpressionType, + Direction==Vertical ? 1 : int(internal::traits<ExpressionType>::RowsAtCompileTime), + Direction==Horizontal ? 1 : int(internal::traits<ExpressionType>::ColsAtCompileTime)> + HNormalized_Factors; + typedef CwiseBinaryOp<internal::scalar_quotient_op<typename internal::traits<ExpressionType>::Scalar>, + const HNormalized_Block, + const Replicate<HNormalized_Factors, + Direction==Vertical ? HNormalized_SizeMinusOne : 1, + Direction==Horizontal ? HNormalized_SizeMinusOne : 1> > + HNormalizedReturnType; + + EIGEN_DEVICE_FUNC + const HNormalizedReturnType hnormalized() const; + +# ifdef EIGEN_VECTORWISEOP_PLUGIN +# include EIGEN_VECTORWISEOP_PLUGIN +# endif + + protected: + Index redux_length() const + { + return Direction==Vertical ? m_matrix.rows() : m_matrix.cols(); + } + ExpressionTypeNested m_matrix; +}; + +//const colwise moved to DenseBase.h due to CUDA compiler bug + + +/** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations + * + * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting + */ +template<typename Derived> +EIGEN_DEVICE_FUNC inline typename DenseBase<Derived>::ColwiseReturnType +DenseBase<Derived>::colwise() +{ + return ColwiseReturnType(derived()); +} + +//const rowwise moved to DenseBase.h due to CUDA compiler bug + + +/** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations + * + * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting + */ +template<typename Derived> +EIGEN_DEVICE_FUNC inline typename DenseBase<Derived>::RowwiseReturnType +DenseBase<Derived>::rowwise() +{ + return RowwiseReturnType(derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_PARTIAL_REDUX_H |