1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Ricard Marxer <email@ricardmarxer.com> 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr> 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_REVERSE_H 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_REVERSE_H 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen { 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \class Reverse 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \ingroup Core_Module 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \brief Expression of the reverse of a vector or matrix 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \param MatrixType the type of the object of which we are taking the reverse 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * This class represents an expression of the reverse of a vector. 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * It is the return type of MatrixBase::reverse() and VectorwiseOp::reverse() 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * and most of the time this is the only way it is used. 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \sa MatrixBase::reverse(), VectorwiseOp::reverse() 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */ 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal { 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType, int Direction> 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<Reverse<MatrixType, Direction> > 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : traits<MatrixType> 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Scalar Scalar; 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename traits<MatrixType>::StorageKind StorageKind; 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename traits<MatrixType>::XprKind XprKind; 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename nested<MatrixType>::type MatrixTypeNested; 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested; 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath RowsAtCompileTime = MatrixType::RowsAtCompileTime, 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ColsAtCompileTime = MatrixType::ColsAtCompileTime, 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // let's enable LinearAccess only with vectorization because of the product overhead 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath LinearAccess = ( (Direction==BothDirections) && (int(_MatrixTypeNested::Flags)&PacketAccessBit) ) 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ? LinearAccessBit : 0, 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Flags = int(_MatrixTypeNested::Flags) & (HereditaryBits | LvalueBit | PacketAccessBit | LinearAccess), 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CoeffReadCost = _MatrixTypeNested::CoeffReadCost 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath }; 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename PacketScalar, bool ReversePacket> struct reverse_packet_cond 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static inline PacketScalar run(const PacketScalar& x) { return preverse(x); } 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename PacketScalar> struct reverse_packet_cond<PacketScalar,false> 64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static inline PacketScalar run(const PacketScalar& x) { return x; } 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType, int Direction> class Reverse 71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : public internal::dense_xpr_base< Reverse<MatrixType, Direction> >::type 72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath public: 74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename internal::dense_xpr_base<Reverse>::type Base; 76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath EIGEN_DENSE_PUBLIC_INTERFACE(Reverse) 77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath using Base::IsRowMajor; 78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // next line is necessary because otherwise const version of operator() 80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // is hidden by non-const version defined in this file 81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath using Base::operator(); 82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath protected: 84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { 85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath PacketSize = internal::packet_traits<Scalar>::size, 86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath IsColMajor = !IsRowMajor, 87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReverseRow = (Direction == Vertical) || (Direction == BothDirections), 88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReverseCol = (Direction == Horizontal) || (Direction == BothDirections), 89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1, 90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1, 91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReversePacket = (Direction == BothDirections) 92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath || ((Direction == Vertical) && IsColMajor) 93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath || ((Direction == Horizontal) && IsRowMajor) 94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath }; 95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef internal::reverse_packet_cond<PacketScalar,ReversePacket> reverse_packet; 96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath public: 97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Reverse(const MatrixType& matrix) : m_matrix(matrix) { } 99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Reverse) 101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Index rows() const { return m_matrix.rows(); } 103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Index cols() const { return m_matrix.cols(); } 104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Index innerStride() const 106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return -m_matrix.innerStride(); 108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Scalar& operator()(Index row, Index col) 111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); 113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return coeffRef(row, col); 114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Scalar& coeffRef(Index row, Index col) 117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return m_matrix.const_cast_derived().coeffRef(ReverseRow ? m_matrix.rows() - row - 1 : row, 119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReverseCol ? m_matrix.cols() - col - 1 : col); 120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline CoeffReturnType coeff(Index row, Index col) const 123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return m_matrix.coeff(ReverseRow ? m_matrix.rows() - row - 1 : row, 125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReverseCol ? m_matrix.cols() - col - 1 : col); 126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline CoeffReturnType coeff(Index index) const 129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return m_matrix.coeff(m_matrix.size() - index - 1); 131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Scalar& coeffRef(Index index) 134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return m_matrix.const_cast_derived().coeffRef(m_matrix.size() - index - 1); 136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Scalar& operator()(Index index) 139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath eigen_assert(index >= 0 && index < m_matrix.size()); 141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return coeffRef(index); 142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath template<int LoadMode> 145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline const PacketScalar packet(Index row, Index col) const 146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return reverse_packet::run(m_matrix.template packet<LoadMode>( 148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReverseRow ? m_matrix.rows() - row - OffsetRow : row, 149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReverseCol ? m_matrix.cols() - col - OffsetCol : col)); 150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath template<int LoadMode> 153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline void writePacket(Index row, Index col, const PacketScalar& x) 154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m_matrix.const_cast_derived().template writePacket<LoadMode>( 156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReverseRow ? m_matrix.rows() - row - OffsetRow : row, 157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ReverseCol ? m_matrix.cols() - col - OffsetCol : col, 158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath reverse_packet::run(x)); 159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath template<int LoadMode> 162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline const PacketScalar packet(Index index) const 163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return internal::preverse(m_matrix.template packet<LoadMode>( m_matrix.size() - index - PacketSize )); 165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath template<int LoadMode> 168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline void writePacket(Index index, const PacketScalar& x) 169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m_matrix.const_cast_derived().template writePacket<LoadMode>(m_matrix.size() - index - PacketSize, internal::preverse(x)); 171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const typename internal::remove_all<typename MatrixType::Nested>::type& 174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath nestedExpression() const 175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return m_matrix; 177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath protected: 180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typename MatrixType::Nested m_matrix; 181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \returns an expression of the reverse of *this. 184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Example: \include MatrixBase_reverse.cpp 186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Output: \verbinclude MatrixBase_reverse.out 187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */ 189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline typename DenseBase<Derived>::ReverseReturnType 191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathDenseBase<Derived>::reverse() 192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return derived(); 194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** This is the const version of reverse(). */ 197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline const typename DenseBase<Derived>::ConstReverseReturnType 199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathDenseBase<Derived>::reverse() const 200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return derived(); 202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** This is the "in place" version of reverse: it reverses \c *this. 205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * In most cases it is probably better to simply use the reversed expression 207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * of a matrix. However, when reversing the matrix data itself is really needed, 208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * then this "in-place" version is probably the right choice because it provides 209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * the following additional features: 210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * - less error prone: doing the same operation with .reverse() requires special care: 211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code m = m.reverse().eval(); \endcode 212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * - this API allows to avoid creating a temporary (the current implementation creates a temporary, but that could be avoided using swap) 213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * - it allows future optimizations (cache friendliness, etc.) 214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \sa reverse() */ 216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void DenseBase<Derived>::reverseInPlace() 218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath derived() = derived().reverse().eval(); 220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen 223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_REVERSE_H 225