// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2006-2008 Benoit Jacob // Copyright (C) 2009-2010 Gael Guennebaud // // 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 { /** \class Transpose * \ingroup Core_Module * * \brief Expression of the transpose of a matrix * * \param 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() */ namespace internal { template struct traits > : traits { typedef typename MatrixType::Scalar Scalar; typedef typename nested::type MatrixTypeNested; typedef typename remove_reference::type MatrixTypeNestedPlain; typedef typename traits::StorageKind StorageKind; typedef typename traits::XprKind XprKind; enum { RowsAtCompileTime = MatrixType::ColsAtCompileTime, ColsAtCompileTime = MatrixType::RowsAtCompileTime, MaxRowsAtCompileTime = MatrixType::MaxColsAtCompileTime, MaxColsAtCompileTime = MatrixType::MaxRowsAtCompileTime, FlagsLvalueBit = is_lvalue::value ? LvalueBit : 0, Flags0 = MatrixTypeNestedPlain::Flags & ~(LvalueBit | NestByRefBit), Flags1 = Flags0 | FlagsLvalueBit, Flags = Flags1 ^ RowMajorBit, CoeffReadCost = MatrixTypeNestedPlain::CoeffReadCost, InnerStrideAtCompileTime = inner_stride_at_compile_time::ret, OuterStrideAtCompileTime = outer_stride_at_compile_time::ret }; }; } template class TransposeImpl; template class Transpose : public TransposeImpl::StorageKind> { public: typedef typename TransposeImpl::StorageKind>::Base Base; EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose) inline Transpose(MatrixType& a_matrix) : m_matrix(a_matrix) {} EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose) inline Index rows() const { return m_matrix.cols(); } inline Index cols() const { return m_matrix.rows(); } /** \returns the nested expression */ const typename internal::remove_all::type& nestedExpression() const { return m_matrix; } /** \returns the nested expression */ typename internal::remove_all::type& nestedExpression() { return m_matrix.const_cast_derived(); } protected: typename MatrixType::Nested m_matrix; }; namespace internal { template::ret> struct TransposeImpl_base { typedef typename dense_xpr_base >::type type; }; template struct TransposeImpl_base { typedef typename dense_xpr_base >::type type; }; } // end namespace internal template class TransposeImpl : public internal::TransposeImpl_base::type { public: typedef typename internal::TransposeImpl_base::type Base; EIGEN_DENSE_PUBLIC_INTERFACE(Transpose) EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl) inline Index innerStride() const { return derived().nestedExpression().innerStride(); } inline Index outerStride() const { return derived().nestedExpression().outerStride(); } typedef typename internal::conditional< internal::is_lvalue::value, Scalar, const Scalar >::type ScalarWithConstIfNotLvalue; inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); } inline const Scalar* data() const { return derived().nestedExpression().data(); } inline ScalarWithConstIfNotLvalue& coeffRef(Index rowId, Index colId) { EIGEN_STATIC_ASSERT_LVALUE(MatrixType) return derived().nestedExpression().const_cast_derived().coeffRef(colId, rowId); } inline ScalarWithConstIfNotLvalue& coeffRef(Index index) { EIGEN_STATIC_ASSERT_LVALUE(MatrixType) return derived().nestedExpression().const_cast_derived().coeffRef(index); } inline const Scalar& coeffRef(Index rowId, Index colId) const { return derived().nestedExpression().coeffRef(colId, rowId); } inline const Scalar& coeffRef(Index index) const { return derived().nestedExpression().coeffRef(index); } inline CoeffReturnType coeff(Index rowId, Index colId) const { return derived().nestedExpression().coeff(colId, rowId); } inline CoeffReturnType coeff(Index index) const { return derived().nestedExpression().coeff(index); } template inline const PacketScalar packet(Index rowId, Index colId) const { return derived().nestedExpression().template packet(colId, rowId); } template inline void writePacket(Index rowId, Index colId, const PacketScalar& x) { derived().nestedExpression().const_cast_derived().template writePacket(colId, rowId, x); } template inline const PacketScalar packet(Index index) const { return derived().nestedExpression().template packet(index); } template inline void writePacket(Index index, const PacketScalar& x) { derived().nestedExpression().const_cast_derived().template writePacket(index, x); } }; /** \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 inline Transpose DenseBase::transpose() { return derived(); } /** This is the const version of transpose(). * * Make sure you read the warning for transpose() ! * * \sa transposeInPlace(), adjoint() */ template inline typename DenseBase::ConstTransposeReturnType DenseBase::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 inline const typename MatrixBase::AdjointReturnType MatrixBase::adjoint() const { return this->transpose(); // in the complex case, the .conjugate() is be implicit here // due to implicit conversion to return type } /*************************************************************************** * "in place" transpose implementation ***************************************************************************/ namespace internal { template struct inplace_transpose_selector; template struct inplace_transpose_selector { // square matrix static void run(MatrixType& m) { m.matrix().template triangularView().swap(m.matrix().transpose()); } }; template struct inplace_transpose_selector { // non square matrix static void run(MatrixType& m) { if (m.rows()==m.cols()) m.matrix().template triangularView().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 inline void DenseBase::transposeInPlace() { eigen_assert((rows() == cols() || (RowsAtCompileTime == Dynamic && ColsAtCompileTime == Dynamic)) && "transposeInPlace() called on a non-square non-resizable matrix"); internal::inplace_transpose_selector::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 inline void MatrixBase::adjointInPlace() { derived() = adjoint().eval(); } #ifndef EIGEN_NO_DEBUG // The following is to detect aliasing problems in most common cases. namespace internal { template struct blas_traits > : blas_traits { typedef SelfCwiseBinaryOp XprType; static inline const XprType extract(const XprType& x) { return x; } }; template struct check_transpose_aliasing_compile_time_selector { enum { ret = bool(blas_traits::IsTransposed) != DestIsTransposed }; }; template struct check_transpose_aliasing_compile_time_selector > { enum { ret = bool(blas_traits::IsTransposed) != DestIsTransposed || bool(blas_traits::IsTransposed) != DestIsTransposed }; }; template struct check_transpose_aliasing_run_time_selector { static bool run(const Scalar* dest, const OtherDerived& src) { return (bool(blas_traits::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src)); } }; template struct check_transpose_aliasing_run_time_selector > { static bool run(const Scalar* dest, const CwiseBinaryOp& src) { return ((blas_traits::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.lhs()))) || ((blas_traits::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::IsTransposed,OtherDerived>::ret > struct checkTransposeAliasing_impl { static void run(const Derived& dst, const OtherDerived& other) { eigen_assert((!check_transpose_aliasing_run_time_selector ::IsTransposed,OtherDerived> ::run(extract_data(dst), other)) && "aliasing detected during transposition, use transposeInPlace() " "or evaluate the rhs into a temporary using .eval()"); } }; template struct checkTransposeAliasing_impl { static void run(const Derived&, const OtherDerived&) { } }; } // end namespace internal template template void DenseBase::checkTransposeAliasing(const OtherDerived& other) const { internal::checkTransposeAliasing_impl::run(derived(), other); } #endif } // end namespace Eigen #endif // EIGEN_TRANSPOSE_H