// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2009 Gael Guennebaud // Copyright (C) 2006-2008 Benoit Jacob // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public // License as published by the Free Software Foundation; either // version 3 of the License, or (at your option) any later version. // // Alternatively, you can redistribute it and/or // modify it under the terms of the GNU General Public License as // published by the Free Software Foundation; either version 2 of // the License, or (at your option) any later version. // // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the // GNU General Public License for more details. // // You should have received a copy of the GNU Lesser General Public // License and a copy of the GNU General Public License along with // Eigen. If not, see . #ifndef EIGEN_PARTIAL_REDUX_H #define EIGEN_PARTIAL_REDUX_H /** \array_module \ingroup Array_Module * * \class PartialReduxExpr * * \brief Generic expression of a partially reduxed matrix * * \param MatrixType the type of the matrix we are applying the redux operation * \param MemberOp type of the member functor * \param 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; template struct ei_traits > { typedef typename MemberOp::result_type Scalar; typedef typename MatrixType::Scalar InputScalar; typedef typename ei_nested::type MatrixTypeNested; typedef typename ei_cleantype::type _MatrixTypeNested; 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 = (unsigned int)_MatrixTypeNested::Flags & HereditaryBits, TraversalSize = Direction==Vertical ? RowsAtCompileTime : ColsAtCompileTime }; #if EIGEN_GNUC_AT_LEAST(3,4) typedef typename MemberOp::template Cost CostOpType; #else typedef typename MemberOp::template Cost CostOpType; #endif enum { CoeffReadCost = TraversalSize * ei_traits<_MatrixTypeNested>::CoeffReadCost + int(CostOpType::value) }; }; template< typename MatrixType, typename MemberOp, int Direction> class PartialReduxExpr : ei_no_assignment_operator, public MatrixBase > { public: EIGEN_GENERIC_PUBLIC_INTERFACE(PartialReduxExpr) typedef typename ei_traits::MatrixTypeNested MatrixTypeNested; typedef typename ei_traits::_MatrixTypeNested _MatrixTypeNested; PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp()) : m_matrix(mat), m_functor(func) {} int rows() const { return (Direction==Vertical ? 1 : m_matrix.rows()); } int cols() const { return (Direction==Horizontal ? 1 : m_matrix.cols()); } const Scalar coeff(int i, int j) const { if (Direction==Vertical) return m_functor(m_matrix.col(j)); else return m_functor(m_matrix.row(i)); } const Scalar coeff(int index) const { if (Direction==Vertical) return m_functor(m_matrix.col(index)); else return m_functor(m_matrix.row(index)); } protected: const MatrixTypeNested m_matrix; const MemberOp m_functor; }; #define EIGEN_MEMBER_FUNCTOR(MEMBER,COST) \ template \ struct ei_member_##MEMBER { \ EIGEN_EMPTY_STRUCT_CTOR(ei_member_##MEMBER) \ typedef ResultType result_type; \ template struct Cost \ { enum { value = COST }; }; \ template \ inline ResultType operator()(const MatrixBase& mat) const \ { return mat.MEMBER(); } \ } EIGEN_MEMBER_FUNCTOR(squaredNorm, Size * NumTraits::MulCost + (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(norm, (Size+5) * NumTraits::MulCost + (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(stableNorm, (Size+5) * NumTraits::MulCost + (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(blueNorm, (Size+5) * NumTraits::MulCost + (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(hypotNorm, (Size-1) * ei_functor_traits >::Cost ); EIGEN_MEMBER_FUNCTOR(sum, (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(mean, (Size-1)*NumTraits::AddCost + NumTraits::MulCost); EIGEN_MEMBER_FUNCTOR(minCoeff, (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(maxCoeff, (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(all, (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(any, (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(count, (Size-1)*NumTraits::AddCost); EIGEN_MEMBER_FUNCTOR(prod, (Size-1)*NumTraits::MulCost); /** \internal */ template struct ei_member_redux { typedef typename ei_result_of< BinaryOp(Scalar) >::type result_type; template struct Cost { enum { value = (Size-1) * ei_functor_traits::Cost }; }; ei_member_redux(const BinaryOp func) : m_functor(func) {} template inline result_type operator()(const MatrixBase& mat) const { return mat.redux(m_functor); } const BinaryOp m_functor; }; /** \array_module \ingroup Array_Module * * \class VectorwiseOp * * \brief Pseudo expression providing partial reduction operations * * \param ExpressionType the type of the object on which to do partial reductions * \param Direction indicates the direction of the redux (Vertical or Horizontal) * * This class represents a pseudo expression with partial reduction features. * It is the return type of MatrixBase::colwise() and MatrixBase::rowwise() * and most of the time this is the only way it is used. * * Example: \include MatrixBase_colwise.cpp * Output: \verbinclude MatrixBase_colwise.out * * \sa MatrixBase::colwise(), MatrixBase::rowwise(), class PartialReduxExpr */ template class VectorwiseOp { public: typedef typename ei_traits::Scalar Scalar; typedef typename ei_meta_if::ret, ExpressionType, const ExpressionType&>::ret ExpressionTypeNested; template class Functor> struct ReturnType { typedef PartialReduxExpr::Scalar>, Direction > Type; }; template struct ReduxReturnType { typedef PartialReduxExpr::Scalar>, Direction > Type; }; enum { IsVertical = (Direction==Vertical) ? 1 : 0, IsHorizontal = (Direction==Horizontal) ? 1 : 0 }; protected: /** \internal * \returns the i-th subvector according to the \c Direction */ typedef typename ei_meta_if::ret SubVector; SubVector subVector(int i) { return SubVector(m_matrix.derived(),i); } /** \internal * \returns the number of subvectors in the direction \c Direction */ int subVectors() const { return Direction==Vertical?m_matrix.cols():m_matrix.rows(); } template struct ExtendedType { typedef Replicate Type; }; /** \internal * Replicates a vector to match the size of \c *this */ template typename ExtendedType::Type extendedTo(const MatrixBase& other) const { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived); return typename ExtendedType::Type (other.derived(), Direction==Vertical ? 1 : m_matrix.rows(), Direction==Horizontal ? 1 : m_matrix.cols()); } public: inline VectorwiseOp(const ExpressionType& matrix) : m_matrix(matrix) {} /** \internal */ inline const ExpressionType& _expression() const { return m_matrix; } /** \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. * * \sa class VectorwiseOp, MatrixBase::colwise(), MatrixBase::rowwise() */ template const typename ReduxReturnType::Type redux(const BinaryOp& func = BinaryOp()) const { return typename ReduxReturnType::Type(_expression(), func); } /** \returns a row (or column) vector expression of the smallest coefficient * of each column (or row) of the referenced expression. * * Example: \include PartialRedux_minCoeff.cpp * Output: \verbinclude PartialRedux_minCoeff.out * * \sa MatrixBase::minCoeff() */ const typename ReturnType::Type minCoeff() const { return _expression(); } /** \returns a row (or column) vector expression of the largest coefficient * of each column (or row) of the referenced expression. * * Example: \include PartialRedux_maxCoeff.cpp * Output: \verbinclude PartialRedux_maxCoeff.out * * \sa MatrixBase::maxCoeff() */ const typename ReturnType::Type maxCoeff() const { return _expression(); } /** \returns a row (or column) vector expression of the squared norm * of each column (or row) of the referenced expression. * * Example: \include PartialRedux_squaredNorm.cpp * Output: \verbinclude PartialRedux_squaredNorm.out * * \sa MatrixBase::squaredNorm() */ const typename ReturnType::Type squaredNorm() const { return _expression(); } /** \returns a row (or column) vector expression of the norm * of each column (or row) of the referenced expression. * * Example: \include PartialRedux_norm.cpp * Output: \verbinclude PartialRedux_norm.out * * \sa MatrixBase::norm() */ const typename ReturnType::Type norm() const { return _expression(); } /** \returns a row (or column) vector expression of the norm * of each column (or row) of the referenced expression, using * blue's algorithm. * * \sa MatrixBase::blueNorm() */ const typename ReturnType::Type blueNorm() const { return _expression(); } /** \returns a row (or column) vector expression of the norm * of each column (or row) of the referenced expression, avoiding * underflow and overflow. * * \sa MatrixBase::stableNorm() */ const typename ReturnType::Type stableNorm() const { return _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. * * \sa MatrixBase::hypotNorm() */ const typename ReturnType::Type hypotNorm() const { return _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 MatrixBase::sum() */ const typename ReturnType::Type sum() const { return _expression(); } /** \returns a row (or column) vector expression of the mean * of each column (or row) of the referenced expression. * * \sa MatrixBase::mean() */ const typename ReturnType::Type mean() const { return _expression(); } /** \returns a row (or column) vector expression representing * whether \b all coefficients of each respective column (or row) are \c true. * * \sa MatrixBase::all() */ const typename ReturnType::Type all() const { return _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. * * \sa MatrixBase::any() */ const typename ReturnType::Type any() const { return _expression(); } /** \returns a row (or column) vector expression representing * the number of \c true coefficients of each respective column (or row). * * Example: \include PartialRedux_count.cpp * Output: \verbinclude PartialRedux_count.out * * \sa MatrixBase::count() */ const PartialReduxExpr, Direction> count() const { return _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 MatrixBase::prod() */ const typename ReturnType::Type prod() const { return _expression(); } /** \returns a matrix expression * where each column (or row) are reversed. * * Example: \include PartialRedux_reverse.cpp * Output: \verbinclude PartialRedux_reverse.out * * \sa MatrixBase::reverse() */ const Reverse reverse() const { return Reverse( _expression() ); } const Replicate replicate(int factor) const; /** \nonstableyet * \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(int), MatrixBase::replicate(), class Replicate */ // NOTE implemented here because of sunstudio's compilation errors template const Replicate replicate(int factor = Factor) const { return Replicate (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1); } /////////// Artithmetic operators /////////// /** Copies the vector \a other to each subvector of \c *this */ template ExpressionType& operator=(const MatrixBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) //ei_assert((m_matrix.isNull()) == (other.isNull())); FIXME for(int j=0; j(m_matrix); } /** Adds the vector \a other to each subvector of \c *this */ template ExpressionType& operator+=(const MatrixBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) for(int j=0; j(m_matrix); } /** Substracts the vector \a other to each subvector of \c *this */ template ExpressionType& operator-=(const MatrixBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) for(int j=0; j(m_matrix); } /** Returns the expression of the sum of the vector \a other to each subvector of \c *this */ template CwiseBinaryOp, ExpressionType, typename ExtendedType::Type> operator+(const MatrixBase& other) const { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived); return m_matrix + extendedTo(other); } /** Returns the expression of the difference between each subvector of \c *this and the vector \a other */ template CwiseBinaryOp, ExpressionType, typename ExtendedType::Type> operator-(const MatrixBase& other) const { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived); return m_matrix - extendedTo(other); } /////////// Geometry module /////////// const Homogeneous homogeneous() const; typedef typename ExpressionType::PlainMatrixType CrossReturnType; template const CrossReturnType cross(const MatrixBase& other) const; enum { HNormalized_Size = Direction==Vertical ? ei_traits::RowsAtCompileTime : ei_traits::ColsAtCompileTime, HNormalized_SizeMinusOne = HNormalized_Size==Dynamic ? Dynamic : HNormalized_Size-1 }; typedef Block::RowsAtCompileTime), Direction==Horizontal ? int(HNormalized_SizeMinusOne) : int(ei_traits::ColsAtCompileTime)> HNormalized_Block; typedef Block::RowsAtCompileTime), Direction==Horizontal ? 1 : int(ei_traits::ColsAtCompileTime)> HNormalized_Factors; typedef CwiseBinaryOp::Scalar>, HNormalized_Block, Replicate > HNormalizedReturnType; const HNormalizedReturnType hnormalized() const; protected: ExpressionTypeNested m_matrix; }; /** \array_module * * \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations * * Example: \include MatrixBase_colwise.cpp * Output: \verbinclude MatrixBase_colwise.out * * \sa rowwise(), class VectorwiseOp */ template inline const VectorwiseOp MatrixBase::colwise() const { return derived(); } /** \array_module * * \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations * * \sa rowwise(), class VectorwiseOp */ template inline VectorwiseOp MatrixBase::colwise() { return derived(); } /** \array_module * * \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations * * Example: \include MatrixBase_rowwise.cpp * Output: \verbinclude MatrixBase_rowwise.out * * \sa colwise(), class VectorwiseOp */ template inline const VectorwiseOp MatrixBase::rowwise() const { return derived(); } /** \array_module * * \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations * * \sa colwise(), class VectorwiseOp */ template inline VectorwiseOp MatrixBase::rowwise() { return derived(); } #endif // EIGEN_PARTIAL_REDUX_H