// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2010 Gael Guennebaud // Copyright (C) 2006-2008 Benoit Jacob // // 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 struct traits > : traits { typedef typename MemberOp::result_type Scalar; typedef typename traits::StorageKind StorageKind; typedef typename traits::XprKind XprKind; typedef typename MatrixType::Scalar InputScalar; typedef typename nested::type MatrixTypeNested; typedef typename remove_all::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 = RowsAtCompileTime == 1 ? RowMajorBit : 0, TraversalSize = Direction==Vertical ? MatrixType::RowsAtCompileTime : MatrixType::ColsAtCompileTime }; }; } template< typename MatrixType, typename MemberOp, int Direction> class PartialReduxExpr : internal::no_assignment_operator, public internal::dense_xpr_base< PartialReduxExpr >::type { public: typedef typename internal::dense_xpr_base::type Base; EIGEN_DENSE_PUBLIC_INTERFACE(PartialReduxExpr) typedef typename internal::traits::MatrixTypeNested MatrixTypeNested; typedef typename internal::traits::_MatrixTypeNested _MatrixTypeNested; PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp()) : m_matrix(mat), m_functor(func) {} Index rows() const { return (Direction==Vertical ? 1 : m_matrix.rows()); } Index cols() const { return (Direction==Horizontal ? 1 : m_matrix.cols()); } EIGEN_STRONG_INLINE const Scalar coeff(Index i, Index j) const { if (Direction==Vertical) return m_functor(m_matrix.col(j)); else return m_functor(m_matrix.row(i)); } const Scalar coeff(Index index) const { if (Direction==Vertical) return m_functor(m_matrix.col(index)); else return m_functor(m_matrix.row(index)); } protected: MatrixTypeNested m_matrix; const MemberOp m_functor; }; #define EIGEN_MEMBER_FUNCTOR(MEMBER,COST) \ template \ struct member_##MEMBER { \ EIGEN_EMPTY_STRUCT_CTOR(member_##MEMBER) \ typedef ResultType result_type; \ template struct Cost \ { enum { value = COST }; }; \ template \ EIGEN_STRONG_INLINE ResultType operator()(const XprType& mat) const \ { return mat.MEMBER(); } \ } namespace internal { 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) * 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); template struct member_redux { typedef typename result_of< BinaryOp(Scalar) >::type result_type; template struct Cost { enum { value = (Size-1) * functor_traits::Cost }; }; member_redux(const BinaryOp func) : m_functor(func) {} template inline result_type operator()(const DenseBase& mat) const { return mat.redux(m_functor); } const BinaryOp m_functor; }; } /** \class VectorwiseOp * \ingroup Core_Module * * \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 DenseBase::colwise() and DenseBase::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 DenseBase::colwise(), DenseBase::rowwise(), class PartialReduxExpr */ template class VectorwiseOp { public: typedef typename ExpressionType::Scalar Scalar; typedef typename ExpressionType::RealScalar RealScalar; typedef typename ExpressionType::Index Index; typedef typename internal::conditional::ret, ExpressionType, ExpressionType&>::type ExpressionTypeNested; typedef typename internal::remove_all::type ExpressionTypeNestedCleaned; template class Functor, typename Scalar=typename internal::traits::Scalar> struct ReturnType { typedef PartialReduxExpr, 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 internal::conditional::type SubVector; SubVector subVector(Index i) { return SubVector(m_matrix.derived(),i); } /** \internal * \returns the number of subvectors in the direction \c Direction */ Index 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 DenseBase& other) const { EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Vertical, OtherDerived::MaxColsAtCompileTime==1), YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED) EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Horizontal, OtherDerived::MaxRowsAtCompileTime==1), YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED) return typename ExtendedType::Type (other.derived(), Direction==Vertical ? 1 : m_matrix.rows(), Direction==Horizontal ? 1 : m_matrix.cols()); } template struct OppositeExtendedType { typedef Replicate Type; }; /** \internal * Replicates a vector in the opposite direction to match the size of \c *this */ template typename OppositeExtendedType::Type extendedToOpposite(const DenseBase& other) const { EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Horizontal, OtherDerived::MaxColsAtCompileTime==1), YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED) EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Vertical, OtherDerived::MaxRowsAtCompileTime==1), YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED) return typename OppositeExtendedType::Type (other.derived(), Direction==Horizontal ? 1 : m_matrix.rows(), Direction==Vertical ? 1 : m_matrix.cols()); } public: inline VectorwiseOp(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, DenseBase::colwise(), DenseBase::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. * * \warning the result is undefined if \c *this contains NaN. * * Example: \include PartialRedux_minCoeff.cpp * Output: \verbinclude PartialRedux_minCoeff.out * * \sa DenseBase::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. * * \warning the result is undefined if \c *this contains NaN. * * Example: \include PartialRedux_maxCoeff.cpp * Output: \verbinclude PartialRedux_maxCoeff.out * * \sa DenseBase::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. * 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() */ 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. * 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() */ 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. * This is a vector with real entries, even if the original matrix has complex entries. * * \sa DenseBase::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. * This is a vector with real entries, even if the original matrix has complex entries. * * \sa DenseBase::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. * This is a vector with real entries, even if the original matrix has complex entries. * * \sa DenseBase::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 DenseBase::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 DenseBase::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. * This expression can be assigned to a vector with entries of type \c bool. * * \sa DenseBase::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. * This expression can be assigned to a vector with entries of type \c bool. * * \sa DenseBase::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). * 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() */ 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 DenseBase::prod() */ const typename ReturnType::Type prod() const { return _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() */ const Reverse reverse() const { return Reverse( _expression() ); } typedef Replicate ReplicateReturnType; 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 template const Replicate replicate(Index 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 DenseBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) //eigen_assert((m_matrix.isNull()) == (other.isNull())); FIXME return const_cast(m_matrix = extendedTo(other.derived())); } /** Adds the vector \a other to each subvector of \c *this */ template ExpressionType& operator+=(const DenseBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) return const_cast(m_matrix += extendedTo(other.derived())); } /** Substracts the vector \a other to each subvector of \c *this */ template ExpressionType& operator-=(const DenseBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) return const_cast(m_matrix -= extendedTo(other.derived())); } /** Multiples each subvector of \c *this by the vector \a other */ template ExpressionType& operator*=(const DenseBase& 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 const_cast(m_matrix); } /** Divides each subvector of \c *this by the vector \a other */ template ExpressionType& operator/=(const DenseBase& 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 const_cast(m_matrix); } /** Returns the expression of the sum of the vector \a other to each subvector of \c *this */ template EIGEN_STRONG_INLINE CwiseBinaryOp, const ExpressionTypeNestedCleaned, const typename ExtendedType::Type> operator+(const DenseBase& 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 CwiseBinaryOp, const ExpressionTypeNestedCleaned, const typename ExtendedType::Type> operator-(const DenseBase& 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 EIGEN_STRONG_INLINE CwiseBinaryOp, const ExpressionTypeNestedCleaned, const typename ExtendedType::Type> operator*(const DenseBase& 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 CwiseBinaryOp, const ExpressionTypeNestedCleaned, const typename ExtendedType::Type> operator/(const DenseBase& 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 of row of the referenced matrix are normalized. * The referenced matrix is \b not modified. * \sa MatrixBase::normalized(), normalize() */ CwiseBinaryOp, const ExpressionTypeNestedCleaned, const typename OppositeExtendedType::Type>::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() */ void normalize() { m_matrix = this->normalized(); } /////////// Geometry module /////////// Homogeneous homogeneous() const; typedef typename ExpressionType::PlainObject CrossReturnType; template const CrossReturnType cross(const MatrixBase& other) const; enum { HNormalized_Size = Direction==Vertical ? internal::traits::RowsAtCompileTime : internal::traits::ColsAtCompileTime, HNormalized_SizeMinusOne = HNormalized_Size==Dynamic ? Dynamic : HNormalized_Size-1 }; typedef Block::RowsAtCompileTime), Direction==Horizontal ? int(HNormalized_SizeMinusOne) : int(internal::traits::ColsAtCompileTime)> HNormalized_Block; typedef Block::RowsAtCompileTime), Direction==Horizontal ? 1 : int(internal::traits::ColsAtCompileTime)> HNormalized_Factors; typedef CwiseBinaryOp::Scalar>, const HNormalized_Block, const Replicate > HNormalizedReturnType; const HNormalizedReturnType hnormalized() const; protected: ExpressionTypeNested m_matrix; }; /** \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, \ref TutorialReductionsVisitorsBroadcasting */ template inline const typename DenseBase::ConstColwiseReturnType DenseBase::colwise() const { return derived(); } /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations * * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting */ template inline typename DenseBase::ColwiseReturnType DenseBase::colwise() { return derived(); } /** \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, \ref TutorialReductionsVisitorsBroadcasting */ template inline const typename DenseBase::ConstRowwiseReturnType DenseBase::rowwise() const { return derived(); } /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations * * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting */ template inline typename DenseBase::RowwiseReturnType DenseBase::rowwise() { return derived(); } } // end namespace Eigen #endif // EIGEN_PARTIAL_REDUX_H