// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> // Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr> // // 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_TRANSPOSE_H #define EIGEN_TRANSPOSE_H namespace Eigen { namespace internal { template<typename MatrixType> struct traits<Transpose<MatrixType> > : public traits<MatrixType> { typedef typename ref_selector<MatrixType>::type MatrixTypeNested; typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain; enum { RowsAtCompileTime = MatrixType::ColsAtCompileTime, ColsAtCompileTime = MatrixType::RowsAtCompileTime, MaxRowsAtCompileTime = MatrixType::MaxColsAtCompileTime, MaxColsAtCompileTime = MatrixType::MaxRowsAtCompileTime, FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0, Flags0 = traits<MatrixTypeNestedPlain>::Flags & ~(LvalueBit | NestByRefBit), Flags1 = Flags0 | FlagsLvalueBit, Flags = Flags1 ^ RowMajorBit, InnerStrideAtCompileTime = inner_stride_at_compile_time<MatrixType>::ret, OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret }; }; } template<typename MatrixType, typename StorageKind> class TransposeImpl; /** \class Transpose * \ingroup Core_Module * * \brief Expression of the transpose of a matrix * * \tparam MatrixType the type of the object of which we are taking the transpose * * This class represents an expression of the transpose of a matrix. * It is the return type of MatrixBase::transpose() and MatrixBase::adjoint() * and most of the time this is the only way it is used. * * \sa MatrixBase::transpose(), MatrixBase::adjoint() */ template<typename MatrixType> class Transpose : public TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind> { public: typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested; typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base; EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose) typedef typename internal::remove_all<MatrixType>::type NestedExpression; EIGEN_DEVICE_FUNC explicit inline Transpose(MatrixType& matrix) : m_matrix(matrix) {} EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose) EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.cols(); } EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.rows(); } /** \returns the nested expression */ EIGEN_DEVICE_FUNC const typename internal::remove_all<MatrixTypeNested>::type& nestedExpression() const { return m_matrix; } /** \returns the nested expression */ EIGEN_DEVICE_FUNC typename internal::remove_reference<MatrixTypeNested>::type& nestedExpression() { return m_matrix; } /** \internal */ void resize(Index nrows, Index ncols) { m_matrix.resize(ncols,nrows); } protected: typename internal::ref_selector<MatrixType>::non_const_type m_matrix; }; namespace internal { template<typename MatrixType, bool HasDirectAccess = has_direct_access<MatrixType>::ret> struct TransposeImpl_base { typedef typename dense_xpr_base<Transpose<MatrixType> >::type type; }; template<typename MatrixType> struct TransposeImpl_base<MatrixType, false> { typedef typename dense_xpr_base<Transpose<MatrixType> >::type type; }; } // end namespace internal // Generic API dispatcher template<typename XprType, typename StorageKind> class TransposeImpl : public internal::generic_xpr_base<Transpose<XprType> >::type { public: typedef typename internal::generic_xpr_base<Transpose<XprType> >::type Base; }; template<typename MatrixType> class TransposeImpl<MatrixType,Dense> : public internal::TransposeImpl_base<MatrixType>::type { public: typedef typename internal::TransposeImpl_base<MatrixType>::type Base; using Base::coeffRef; EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>) EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl) EIGEN_DEVICE_FUNC inline Index innerStride() const { return derived().nestedExpression().innerStride(); } EIGEN_DEVICE_FUNC inline Index outerStride() const { return derived().nestedExpression().outerStride(); } typedef typename internal::conditional< internal::is_lvalue<MatrixType>::value, Scalar, const Scalar >::type ScalarWithConstIfNotLvalue; EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); } EIGEN_DEVICE_FUNC inline const Scalar* data() const { return derived().nestedExpression().data(); } // FIXME: shall we keep the const version of coeffRef? EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const { return derived().nestedExpression().coeffRef(colId, rowId); } EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return derived().nestedExpression().coeffRef(index); } }; /** \returns an expression of the transpose of *this. * * Example: \include MatrixBase_transpose.cpp * Output: \verbinclude MatrixBase_transpose.out * * \warning If you want to replace a matrix by its own transpose, do \b NOT do this: * \code * m = m.transpose(); // bug!!! caused by aliasing effect * \endcode * Instead, use the transposeInPlace() method: * \code * m.transposeInPlace(); * \endcode * which gives Eigen good opportunities for optimization, or alternatively you can also do: * \code * m = m.transpose().eval(); * \endcode * * \sa transposeInPlace(), adjoint() */ template<typename Derived> inline Transpose<Derived> DenseBase<Derived>::transpose() { return TransposeReturnType(derived()); } /** This is the const version of transpose(). * * Make sure you read the warning for transpose() ! * * \sa transposeInPlace(), adjoint() */ template<typename Derived> inline typename DenseBase<Derived>::ConstTransposeReturnType DenseBase<Derived>::transpose() const { return ConstTransposeReturnType(derived()); } /** \returns an expression of the adjoint (i.e. conjugate transpose) of *this. * * Example: \include MatrixBase_adjoint.cpp * Output: \verbinclude MatrixBase_adjoint.out * * \warning If you want to replace a matrix by its own adjoint, do \b NOT do this: * \code * m = m.adjoint(); // bug!!! caused by aliasing effect * \endcode * Instead, use the adjointInPlace() method: * \code * m.adjointInPlace(); * \endcode * which gives Eigen good opportunities for optimization, or alternatively you can also do: * \code * m = m.adjoint().eval(); * \endcode * * \sa adjointInPlace(), transpose(), conjugate(), class Transpose, class internal::scalar_conjugate_op */ template<typename Derived> inline const typename MatrixBase<Derived>::AdjointReturnType MatrixBase<Derived>::adjoint() const { return AdjointReturnType(this->transpose()); } /*************************************************************************** * "in place" transpose implementation ***************************************************************************/ namespace internal { template<typename MatrixType, bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic, bool MatchPacketSize = (int(MatrixType::RowsAtCompileTime) == int(internal::packet_traits<typename MatrixType::Scalar>::size)) && (internal::evaluator<MatrixType>::Flags&PacketAccessBit) > struct inplace_transpose_selector; template<typename MatrixType> struct inplace_transpose_selector<MatrixType,true,false> { // square matrix static void run(MatrixType& m) { m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose()); } }; // TODO: vectorized path is currently limited to LargestPacketSize x LargestPacketSize cases only. template<typename MatrixType> struct inplace_transpose_selector<MatrixType,true,true> { // PacketSize x PacketSize static void run(MatrixType& m) { typedef typename MatrixType::Scalar Scalar; typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet; const Index PacketSize = internal::packet_traits<Scalar>::size; const Index Alignment = internal::evaluator<MatrixType>::Alignment; PacketBlock<Packet> A; for (Index i=0; i<PacketSize; ++i) A.packet[i] = m.template packetByOuterInner<Alignment>(i,0); internal::ptranspose(A); for (Index i=0; i<PacketSize; ++i) m.template writePacket<Alignment>(m.rowIndexByOuterInner(i,0), m.colIndexByOuterInner(i,0), A.packet[i]); } }; template<typename MatrixType,bool MatchPacketSize> struct inplace_transpose_selector<MatrixType,false,MatchPacketSize> { // non square matrix static void run(MatrixType& m) { if (m.rows()==m.cols()) m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose()); else m = m.transpose().eval(); } }; } // end namespace internal /** This is the "in place" version of transpose(): it replaces \c *this by its own transpose. * Thus, doing * \code * m.transposeInPlace(); * \endcode * has the same effect on m as doing * \code * m = m.transpose().eval(); * \endcode * and is faster and also safer because in the latter line of code, forgetting the eval() results * in a bug caused by \ref TopicAliasing "aliasing". * * Notice however that this method is only useful if you want to replace a matrix by its own transpose. * If you just need the transpose of a matrix, use transpose(). * * \note if the matrix is not square, then \c *this must be a resizable matrix. * This excludes (non-square) fixed-size matrices, block-expressions and maps. * * \sa transpose(), adjoint(), adjointInPlace() */ template<typename Derived> inline void DenseBase<Derived>::transposeInPlace() { eigen_assert((rows() == cols() || (RowsAtCompileTime == Dynamic && ColsAtCompileTime == Dynamic)) && "transposeInPlace() called on a non-square non-resizable matrix"); internal::inplace_transpose_selector<Derived>::run(derived()); } /*************************************************************************** * "in place" adjoint implementation ***************************************************************************/ /** This is the "in place" version of adjoint(): it replaces \c *this by its own transpose. * Thus, doing * \code * m.adjointInPlace(); * \endcode * has the same effect on m as doing * \code * m = m.adjoint().eval(); * \endcode * and is faster and also safer because in the latter line of code, forgetting the eval() results * in a bug caused by aliasing. * * Notice however that this method is only useful if you want to replace a matrix by its own adjoint. * If you just need the adjoint of a matrix, use adjoint(). * * \note if the matrix is not square, then \c *this must be a resizable matrix. * This excludes (non-square) fixed-size matrices, block-expressions and maps. * * \sa transpose(), adjoint(), transposeInPlace() */ template<typename Derived> inline void MatrixBase<Derived>::adjointInPlace() { derived() = adjoint().eval(); } #ifndef EIGEN_NO_DEBUG // The following is to detect aliasing problems in most common cases. namespace internal { template<bool DestIsTransposed, typename OtherDerived> struct check_transpose_aliasing_compile_time_selector { enum { ret = bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed }; }; template<bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB> struct check_transpose_aliasing_compile_time_selector<DestIsTransposed,CwiseBinaryOp<BinOp,DerivedA,DerivedB> > { enum { ret = bool(blas_traits<DerivedA>::IsTransposed) != DestIsTransposed || bool(blas_traits<DerivedB>::IsTransposed) != DestIsTransposed }; }; template<typename Scalar, bool DestIsTransposed, typename OtherDerived> struct check_transpose_aliasing_run_time_selector { static bool run(const Scalar* dest, const OtherDerived& src) { return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src)); } }; template<typename Scalar, bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB> struct check_transpose_aliasing_run_time_selector<Scalar,DestIsTransposed,CwiseBinaryOp<BinOp,DerivedA,DerivedB> > { static bool run(const Scalar* dest, const CwiseBinaryOp<BinOp,DerivedA,DerivedB>& src) { return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.lhs()))) || ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.rhs()))); } }; // the following selector, checkTransposeAliasing_impl, based on MightHaveTransposeAliasing, // is because when the condition controlling the assert is known at compile time, ICC emits a warning. // This is actually a good warning: in expressions that don't have any transposing, the condition is // known at compile time to be false, and using that, we can avoid generating the code of the assert again // and again for all these expressions that don't need it. template<typename Derived, typename OtherDerived, bool MightHaveTransposeAliasing = check_transpose_aliasing_compile_time_selector <blas_traits<Derived>::IsTransposed,OtherDerived>::ret > struct checkTransposeAliasing_impl { static void run(const Derived& dst, const OtherDerived& other) { eigen_assert((!check_transpose_aliasing_run_time_selector <typename Derived::Scalar,blas_traits<Derived>::IsTransposed,OtherDerived> ::run(extract_data(dst), other)) && "aliasing detected during transposition, use transposeInPlace() " "or evaluate the rhs into a temporary using .eval()"); } }; template<typename Derived, typename OtherDerived> struct checkTransposeAliasing_impl<Derived, OtherDerived, false> { static void run(const Derived&, const OtherDerived&) { } }; template<typename Dst, typename Src> void check_for_aliasing(const Dst &dst, const Src &src) { internal::checkTransposeAliasing_impl<Dst, Src>::run(dst, src); } } // end namespace internal #endif // EIGEN_NO_DEBUG } // end namespace Eigen #endif // EIGEN_TRANSPOSE_H