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) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr> 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_TRANSPOSE_H 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_TRANSPOSE_H 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen { 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \class Transpose 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \ingroup Core_Module 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \brief Expression of the transpose of a matrix 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \param MatrixType the type of the object of which we are taking the transpose 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * This class represents an expression of the transpose of a matrix. 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * It is the return type of MatrixBase::transpose() and MatrixBase::adjoint() 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * and most of the time this is the only way it is used. 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \sa MatrixBase::transpose(), MatrixBase::adjoint() 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */ 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal { 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<Transpose<MatrixType> > : traits<MatrixType> 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Scalar Scalar; 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename nested<MatrixType>::type MatrixTypeNested; 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain; 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename traits<MatrixType>::StorageKind StorageKind; 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename traits<MatrixType>::XprKind XprKind; 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath RowsAtCompileTime = MatrixType::ColsAtCompileTime, 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ColsAtCompileTime = MatrixType::RowsAtCompileTime, 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MaxRowsAtCompileTime = MatrixType::MaxColsAtCompileTime, 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MaxColsAtCompileTime = MatrixType::MaxRowsAtCompileTime, 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0, 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Flags0 = MatrixTypeNestedPlain::Flags & ~(LvalueBit | NestByRefBit), 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Flags1 = Flags0 | FlagsLvalueBit, 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Flags = Flags1 ^ RowMajorBit, 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CoeffReadCost = MatrixTypeNestedPlain::CoeffReadCost, 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath InnerStrideAtCompileTime = inner_stride_at_compile_time<MatrixType>::ret, 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath }; 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType, typename StorageKind> class TransposeImpl; 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> class Transpose 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : public TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind> 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath public: 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base; 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose) 64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 657faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez inline Transpose(MatrixType& a_matrix) : m_matrix(a_matrix) {} 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose) 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Index rows() const { return m_matrix.cols(); } 70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Index cols() const { return m_matrix.rows(); } 71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath /** \returns the nested expression */ 73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const typename internal::remove_all<typename MatrixType::Nested>::type& 74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath nestedExpression() const { return m_matrix; } 75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath /** \returns the nested expression */ 77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typename internal::remove_all<typename MatrixType::Nested>::type& 78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath nestedExpression() { return m_matrix.const_cast_derived(); } 79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath protected: 81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typename MatrixType::Nested m_matrix; 82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal { 85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType, bool HasDirectAccess = has_direct_access<MatrixType>::ret> 87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct TransposeImpl_base 88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename dense_xpr_base<Transpose<MatrixType> >::type type; 90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> 93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct TransposeImpl_base<MatrixType, false> 94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename dense_xpr_base<Transpose<MatrixType> >::type type; 96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal 99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> class TransposeImpl<MatrixType,Dense> 101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : public internal::TransposeImpl_base<MatrixType>::type 102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath public: 104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename internal::TransposeImpl_base<MatrixType>::type Base; 106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>) 1077faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl) 108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Index innerStride() const { return derived().nestedExpression().innerStride(); } 110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline Index outerStride() const { return derived().nestedExpression().outerStride(); } 111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename internal::conditional< 113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath internal::is_lvalue<MatrixType>::value, 114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Scalar, 115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Scalar 116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath >::type ScalarWithConstIfNotLvalue; 117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); } 119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline const Scalar* data() const { return derived().nestedExpression().data(); } 120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 1217faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez inline ScalarWithConstIfNotLvalue& coeffRef(Index rowId, Index colId) 122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath EIGEN_STATIC_ASSERT_LVALUE(MatrixType) 1247faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez return derived().nestedExpression().const_cast_derived().coeffRef(colId, rowId); 125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline ScalarWithConstIfNotLvalue& coeffRef(Index index) 128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath EIGEN_STATIC_ASSERT_LVALUE(MatrixType) 130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return derived().nestedExpression().const_cast_derived().coeffRef(index); 131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 1337faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez inline const Scalar& coeffRef(Index rowId, Index colId) const 134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 1357faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez return derived().nestedExpression().coeffRef(colId, rowId); 136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline const Scalar& coeffRef(Index index) const 139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return derived().nestedExpression().coeffRef(index); 141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 1437faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez inline CoeffReturnType coeff(Index rowId, Index colId) const 144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 1457faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez return derived().nestedExpression().coeff(colId, rowId); 146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline CoeffReturnType coeff(Index index) const 149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return derived().nestedExpression().coeff(index); 151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath template<int LoadMode> 1547faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez inline const PacketScalar packet(Index rowId, Index colId) const 155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 1567faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez return derived().nestedExpression().template packet<LoadMode>(colId, rowId); 157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath template<int LoadMode> 1607faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez inline void writePacket(Index rowId, Index colId, const PacketScalar& x) 161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 1627faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(colId, rowId, x); 163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath template<int LoadMode> 166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline const PacketScalar packet(Index index) const 167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return derived().nestedExpression().template packet<LoadMode>(index); 169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath template<int LoadMode> 172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath inline void writePacket(Index index, const PacketScalar& x) 173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(index, x); 175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \returns an expression of the transpose of *this. 179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Example: \include MatrixBase_transpose.cpp 181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Output: \verbinclude MatrixBase_transpose.out 182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \warning If you want to replace a matrix by its own transpose, do \b NOT do this: 184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m = m.transpose(); // bug!!! caused by aliasing effect 186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Instead, use the transposeInPlace() method: 188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m.transposeInPlace(); 190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * which gives Eigen good opportunities for optimization, or alternatively you can also do: 192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m = m.transpose().eval(); 194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \sa transposeInPlace(), adjoint() */ 197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline Transpose<Derived> 199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathDenseBase<Derived>::transpose() 200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return derived(); 202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** This is the const version of transpose(). 205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Make sure you read the warning for transpose() ! 207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \sa transposeInPlace(), adjoint() */ 209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 2107faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandezinline typename DenseBase<Derived>::ConstTransposeReturnType 211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathDenseBase<Derived>::transpose() const 212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return ConstTransposeReturnType(derived()); 214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \returns an expression of the adjoint (i.e. conjugate transpose) of *this. 217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Example: \include MatrixBase_adjoint.cpp 219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Output: \verbinclude MatrixBase_adjoint.out 220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \warning If you want to replace a matrix by its own adjoint, do \b NOT do this: 222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m = m.adjoint(); // bug!!! caused by aliasing effect 224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Instead, use the adjointInPlace() method: 226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m.adjointInPlace(); 228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * which gives Eigen good opportunities for optimization, or alternatively you can also do: 230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m = m.adjoint().eval(); 232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \sa adjointInPlace(), transpose(), conjugate(), class Transpose, class internal::scalar_conjugate_op */ 235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline const typename MatrixBase<Derived>::AdjointReturnType 237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathMatrixBase<Derived>::adjoint() const 238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath return this->transpose(); // in the complex case, the .conjugate() is be implicit here 240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // due to implicit conversion to return type 241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/*************************************************************************** 244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath* "in place" transpose implementation 245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath***************************************************************************/ 246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal { 248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType, 250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic> 251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct inplace_transpose_selector; 252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> 254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct inplace_transpose_selector<MatrixType,true> { // square matrix 255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static void run(MatrixType& m) { 2567faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose()); 257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> 261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct inplace_transpose_selector<MatrixType,false> { // non square matrix 262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static void run(MatrixType& m) { 263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if (m.rows()==m.cols()) 2647faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose()); 265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath else 266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m = m.transpose().eval(); 267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal 271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** This is the "in place" version of transpose(): it replaces \c *this by its own transpose. 273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Thus, doing 274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m.transposeInPlace(); 276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * has the same effect on m as doing 278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m = m.transpose().eval(); 280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * and is faster and also safer because in the latter line of code, forgetting the eval() results 2827faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez * in a bug caused by \ref TopicAliasing "aliasing". 283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Notice however that this method is only useful if you want to replace a matrix by its own transpose. 285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * If you just need the transpose of a matrix, use transpose(). 286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 2877faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez * \note if the matrix is not square, then \c *this must be a resizable matrix. 2887faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez * This excludes (non-square) fixed-size matrices, block-expressions and maps. 289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \sa transpose(), adjoint(), adjointInPlace() */ 291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void DenseBase<Derived>::transposeInPlace() 293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 2947faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez eigen_assert((rows() == cols() || (RowsAtCompileTime == Dynamic && ColsAtCompileTime == Dynamic)) 2957faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez && "transposeInPlace() called on a non-square non-resizable matrix"); 296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath internal::inplace_transpose_selector<Derived>::run(derived()); 297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/*************************************************************************** 300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath* "in place" adjoint implementation 301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath***************************************************************************/ 302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** This is the "in place" version of adjoint(): it replaces \c *this by its own transpose. 304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Thus, doing 305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m.adjointInPlace(); 307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * has the same effect on m as doing 309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \code 310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * m = m.adjoint().eval(); 311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \endcode 312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * and is faster and also safer because in the latter line of code, forgetting the eval() results 313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * in a bug caused by aliasing. 314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * Notice however that this method is only useful if you want to replace a matrix by its own adjoint. 316c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * If you just need the adjoint of a matrix, use adjoint(). 317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 318c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \note if the matrix is not square, then \c *this must be a resizable matrix. 3197faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez * This excludes (non-square) fixed-size matrices, block-expressions and maps. 320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * 321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * \sa transpose(), adjoint(), transposeInPlace() */ 322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline void MatrixBase<Derived>::adjointInPlace() 324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath derived() = adjoint().eval(); 326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_NO_DEBUG 329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// The following is to detect aliasing problems in most common cases. 331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal { 333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename BinOp,typename NestedXpr,typename Rhs> 335c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct blas_traits<SelfCwiseBinaryOp<BinOp,NestedXpr,Rhs> > 336c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : blas_traits<NestedXpr> 337c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 338c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef SelfCwiseBinaryOp<BinOp,NestedXpr,Rhs> XprType; 339c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static inline const XprType extract(const XprType& x) { return x; } 340c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 341c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 342c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<bool DestIsTransposed, typename OtherDerived> 343c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct check_transpose_aliasing_compile_time_selector 344c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 345c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { ret = bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed }; 346c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 347c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 348c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB> 349c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct check_transpose_aliasing_compile_time_selector<DestIsTransposed,CwiseBinaryOp<BinOp,DerivedA,DerivedB> > 350c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 351c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { ret = bool(blas_traits<DerivedA>::IsTransposed) != DestIsTransposed 352c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath || bool(blas_traits<DerivedB>::IsTransposed) != DestIsTransposed 353c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath }; 354c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 355c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 356c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar, bool DestIsTransposed, typename OtherDerived> 357c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct check_transpose_aliasing_run_time_selector 358c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 359c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static bool run(const Scalar* dest, const OtherDerived& src) 360c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 3617faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src)); 362c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 363c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 364c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 365c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar, bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB> 366c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct check_transpose_aliasing_run_time_selector<Scalar,DestIsTransposed,CwiseBinaryOp<BinOp,DerivedA,DerivedB> > 367c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 368c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static bool run(const Scalar* dest, const CwiseBinaryOp<BinOp,DerivedA,DerivedB>& src) 369c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 3707faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.lhs()))) 3717faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez || ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.rhs()))); 372c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 373c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 374c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 375c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// the following selector, checkTransposeAliasing_impl, based on MightHaveTransposeAliasing, 376c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// is because when the condition controlling the assert is known at compile time, ICC emits a warning. 377c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This is actually a good warning: in expressions that don't have any transposing, the condition is 378c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// known at compile time to be false, and using that, we can avoid generating the code of the assert again 379c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// and again for all these expressions that don't need it. 380c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 381c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived, typename OtherDerived, 382c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath bool MightHaveTransposeAliasing 383c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath = check_transpose_aliasing_compile_time_selector 384c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath <blas_traits<Derived>::IsTransposed,OtherDerived>::ret 385c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath > 386c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct checkTransposeAliasing_impl 387c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 388c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static void run(const Derived& dst, const OtherDerived& other) 389c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 390c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath eigen_assert((!check_transpose_aliasing_run_time_selector 391c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath <typename Derived::Scalar,blas_traits<Derived>::IsTransposed,OtherDerived> 392c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ::run(extract_data(dst), other)) 3937faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez && "aliasing detected during transposition, use transposeInPlace() " 394c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath "or evaluate the rhs into a temporary using .eval()"); 395c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 396c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 397c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 398c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 399c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived, typename OtherDerived> 400c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct checkTransposeAliasing_impl<Derived, OtherDerived, false> 401c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 402c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static void run(const Derived&, const OtherDerived&) 403c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 404c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 405c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 406c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 407c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal 408c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 409c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Derived> 410c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename OtherDerived> 411c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid DenseBase<Derived>::checkTransposeAliasing(const OtherDerived& other) const 412c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 413c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath internal::checkTransposeAliasing_impl<Derived, OtherDerived>::run(derived(), other); 414c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 415c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif 416c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 417c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen 418c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 419c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_TRANSPOSE_H 420