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403 lines
14 KiB
403 lines
14 KiB
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_TRANSPOSE_H
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#define EIGEN_TRANSPOSE_H
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namespace Eigen {
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namespace internal {
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template<typename MatrixType>
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struct traits<Transpose<MatrixType> > : public traits<MatrixType>
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{
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typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
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typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain;
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enum {
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RowsAtCompileTime = MatrixType::ColsAtCompileTime,
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ColsAtCompileTime = MatrixType::RowsAtCompileTime,
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MaxRowsAtCompileTime = MatrixType::MaxColsAtCompileTime,
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MaxColsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
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FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
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Flags0 = traits<MatrixTypeNestedPlain>::Flags & ~(LvalueBit | NestByRefBit),
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Flags1 = Flags0 | FlagsLvalueBit,
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Flags = Flags1 ^ RowMajorBit,
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InnerStrideAtCompileTime = inner_stride_at_compile_time<MatrixType>::ret,
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OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret
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};
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};
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}
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template<typename MatrixType, typename StorageKind> class TransposeImpl;
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/** \class Transpose
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* \ingroup Core_Module
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*
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* \brief Expression of the transpose of a matrix
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*
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* \tparam MatrixType the type of the object of which we are taking the transpose
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*
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* This class represents an expression of the transpose of a matrix.
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* It is the return type of MatrixBase::transpose() and MatrixBase::adjoint()
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* and most of the time this is the only way it is used.
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*
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* \sa MatrixBase::transpose(), MatrixBase::adjoint()
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*/
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template<typename MatrixType> class Transpose
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: public TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>
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{
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public:
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typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;
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typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
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EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
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typedef typename internal::remove_all<MatrixType>::type NestedExpression;
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EIGEN_DEVICE_FUNC
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explicit inline Transpose(MatrixType& matrix) : m_matrix(matrix) {}
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EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)
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EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.cols(); }
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EIGEN_DEVICE_FUNC inline Index cols() const { return m_matrix.rows(); }
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/** \returns the nested expression */
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EIGEN_DEVICE_FUNC
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const typename internal::remove_all<MatrixTypeNested>::type&
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nestedExpression() const { return m_matrix; }
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/** \returns the nested expression */
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EIGEN_DEVICE_FUNC
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typename internal::remove_reference<MatrixTypeNested>::type&
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nestedExpression() { return m_matrix; }
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/** \internal */
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void resize(Index nrows, Index ncols) {
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m_matrix.resize(ncols,nrows);
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}
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protected:
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typename internal::ref_selector<MatrixType>::non_const_type m_matrix;
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};
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namespace internal {
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template<typename MatrixType, bool HasDirectAccess = has_direct_access<MatrixType>::ret>
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struct TransposeImpl_base
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{
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typedef typename dense_xpr_base<Transpose<MatrixType> >::type type;
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};
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template<typename MatrixType>
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struct TransposeImpl_base<MatrixType, false>
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{
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typedef typename dense_xpr_base<Transpose<MatrixType> >::type type;
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};
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} // end namespace internal
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// Generic API dispatcher
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template<typename XprType, typename StorageKind>
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class TransposeImpl
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: public internal::generic_xpr_base<Transpose<XprType> >::type
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{
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public:
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typedef typename internal::generic_xpr_base<Transpose<XprType> >::type Base;
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};
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template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
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: public internal::TransposeImpl_base<MatrixType>::type
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{
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public:
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typedef typename internal::TransposeImpl_base<MatrixType>::type Base;
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using Base::coeffRef;
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EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
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EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl)
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EIGEN_DEVICE_FUNC inline Index innerStride() const { return derived().nestedExpression().innerStride(); }
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EIGEN_DEVICE_FUNC inline Index outerStride() const { return derived().nestedExpression().outerStride(); }
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typedef typename internal::conditional<
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internal::is_lvalue<MatrixType>::value,
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Scalar,
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const Scalar
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>::type ScalarWithConstIfNotLvalue;
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EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
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EIGEN_DEVICE_FUNC inline const Scalar* data() const { return derived().nestedExpression().data(); }
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// FIXME: shall we keep the const version of coeffRef?
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EIGEN_DEVICE_FUNC
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inline const Scalar& coeffRef(Index rowId, Index colId) const
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{
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return derived().nestedExpression().coeffRef(colId, rowId);
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}
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EIGEN_DEVICE_FUNC
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inline const Scalar& coeffRef(Index index) const
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{
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return derived().nestedExpression().coeffRef(index);
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}
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};
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/** \returns an expression of the transpose of *this.
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*
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* Example: \include MatrixBase_transpose.cpp
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* Output: \verbinclude MatrixBase_transpose.out
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*
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* \warning If you want to replace a matrix by its own transpose, do \b NOT do this:
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* \code
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* m = m.transpose(); // bug!!! caused by aliasing effect
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* \endcode
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* Instead, use the transposeInPlace() method:
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* \code
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* m.transposeInPlace();
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* \endcode
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* which gives Eigen good opportunities for optimization, or alternatively you can also do:
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* \code
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* m = m.transpose().eval();
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* \endcode
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*
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* \sa transposeInPlace(), adjoint() */
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template<typename Derived>
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inline Transpose<Derived>
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DenseBase<Derived>::transpose()
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{
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return TransposeReturnType(derived());
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}
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/** This is the const version of transpose().
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*
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* Make sure you read the warning for transpose() !
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*
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* \sa transposeInPlace(), adjoint() */
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template<typename Derived>
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inline typename DenseBase<Derived>::ConstTransposeReturnType
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DenseBase<Derived>::transpose() const
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{
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return ConstTransposeReturnType(derived());
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}
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/** \returns an expression of the adjoint (i.e. conjugate transpose) of *this.
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*
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* Example: \include MatrixBase_adjoint.cpp
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* Output: \verbinclude MatrixBase_adjoint.out
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*
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* \warning If you want to replace a matrix by its own adjoint, do \b NOT do this:
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* \code
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* m = m.adjoint(); // bug!!! caused by aliasing effect
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* \endcode
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* Instead, use the adjointInPlace() method:
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* \code
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* m.adjointInPlace();
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* \endcode
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* which gives Eigen good opportunities for optimization, or alternatively you can also do:
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* \code
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* m = m.adjoint().eval();
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* \endcode
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*
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* \sa adjointInPlace(), transpose(), conjugate(), class Transpose, class internal::scalar_conjugate_op */
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template<typename Derived>
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inline const typename MatrixBase<Derived>::AdjointReturnType
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MatrixBase<Derived>::adjoint() const
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{
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return AdjointReturnType(this->transpose());
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}
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/***************************************************************************
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* "in place" transpose implementation
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***************************************************************************/
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namespace internal {
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template<typename MatrixType,
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bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime!=Dynamic,
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bool MatchPacketSize =
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(int(MatrixType::RowsAtCompileTime) == int(internal::packet_traits<typename MatrixType::Scalar>::size))
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&& (internal::evaluator<MatrixType>::Flags&PacketAccessBit) >
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struct inplace_transpose_selector;
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template<typename MatrixType>
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struct inplace_transpose_selector<MatrixType,true,false> { // square matrix
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static void run(MatrixType& m) {
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m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
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}
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};
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// TODO: vectorized path is currently limited to LargestPacketSize x LargestPacketSize cases only.
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template<typename MatrixType>
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struct inplace_transpose_selector<MatrixType,true,true> { // PacketSize x PacketSize
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static void run(MatrixType& m) {
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typedef typename MatrixType::Scalar Scalar;
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typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet;
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const Index PacketSize = internal::packet_traits<Scalar>::size;
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const Index Alignment = internal::evaluator<MatrixType>::Alignment;
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PacketBlock<Packet> A;
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for (Index i=0; i<PacketSize; ++i)
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A.packet[i] = m.template packetByOuterInner<Alignment>(i,0);
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internal::ptranspose(A);
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for (Index i=0; i<PacketSize; ++i)
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m.template writePacket<Alignment>(m.rowIndexByOuterInner(i,0), m.colIndexByOuterInner(i,0), A.packet[i]);
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}
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};
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template<typename MatrixType,bool MatchPacketSize>
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struct inplace_transpose_selector<MatrixType,false,MatchPacketSize> { // non square matrix
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static void run(MatrixType& m) {
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if (m.rows()==m.cols())
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m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
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else
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m = m.transpose().eval();
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}
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};
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} // end namespace internal
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/** This is the "in place" version of transpose(): it replaces \c *this by its own transpose.
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* Thus, doing
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* \code
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* m.transposeInPlace();
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* \endcode
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* has the same effect on m as doing
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* \code
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* m = m.transpose().eval();
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* \endcode
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* and is faster and also safer because in the latter line of code, forgetting the eval() results
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* in a bug caused by \ref TopicAliasing "aliasing".
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*
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* Notice however that this method is only useful if you want to replace a matrix by its own transpose.
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* If you just need the transpose of a matrix, use transpose().
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*
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* \note if the matrix is not square, then \c *this must be a resizable matrix.
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* This excludes (non-square) fixed-size matrices, block-expressions and maps.
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*
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* \sa transpose(), adjoint(), adjointInPlace() */
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template<typename Derived>
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inline void DenseBase<Derived>::transposeInPlace()
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{
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eigen_assert((rows() == cols() || (RowsAtCompileTime == Dynamic && ColsAtCompileTime == Dynamic))
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&& "transposeInPlace() called on a non-square non-resizable matrix");
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internal::inplace_transpose_selector<Derived>::run(derived());
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}
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/***************************************************************************
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* "in place" adjoint implementation
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***************************************************************************/
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/** This is the "in place" version of adjoint(): it replaces \c *this by its own transpose.
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* Thus, doing
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* \code
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* m.adjointInPlace();
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* \endcode
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* has the same effect on m as doing
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* \code
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* m = m.adjoint().eval();
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* \endcode
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* and is faster and also safer because in the latter line of code, forgetting the eval() results
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* in a bug caused by aliasing.
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*
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* Notice however that this method is only useful if you want to replace a matrix by its own adjoint.
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* If you just need the adjoint of a matrix, use adjoint().
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*
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* \note if the matrix is not square, then \c *this must be a resizable matrix.
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* This excludes (non-square) fixed-size matrices, block-expressions and maps.
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*
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* \sa transpose(), adjoint(), transposeInPlace() */
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template<typename Derived>
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inline void MatrixBase<Derived>::adjointInPlace()
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{
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derived() = adjoint().eval();
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}
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#ifndef EIGEN_NO_DEBUG
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// The following is to detect aliasing problems in most common cases.
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namespace internal {
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template<bool DestIsTransposed, typename OtherDerived>
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struct check_transpose_aliasing_compile_time_selector
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{
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enum { ret = bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed };
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};
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template<bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB>
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struct check_transpose_aliasing_compile_time_selector<DestIsTransposed,CwiseBinaryOp<BinOp,DerivedA,DerivedB> >
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{
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enum { ret = bool(blas_traits<DerivedA>::IsTransposed) != DestIsTransposed
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|| bool(blas_traits<DerivedB>::IsTransposed) != DestIsTransposed
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};
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};
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template<typename Scalar, bool DestIsTransposed, typename OtherDerived>
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struct check_transpose_aliasing_run_time_selector
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{
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static bool run(const Scalar* dest, const OtherDerived& src)
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{
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return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src));
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}
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};
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template<typename Scalar, bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB>
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struct check_transpose_aliasing_run_time_selector<Scalar,DestIsTransposed,CwiseBinaryOp<BinOp,DerivedA,DerivedB> >
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{
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static bool run(const Scalar* dest, const CwiseBinaryOp<BinOp,DerivedA,DerivedB>& src)
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{
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return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.lhs())))
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|| ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.rhs())));
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}
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};
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// the following selector, checkTransposeAliasing_impl, based on MightHaveTransposeAliasing,
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// is because when the condition controlling the assert is known at compile time, ICC emits a warning.
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// This is actually a good warning: in expressions that don't have any transposing, the condition is
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// known at compile time to be false, and using that, we can avoid generating the code of the assert again
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// and again for all these expressions that don't need it.
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template<typename Derived, typename OtherDerived,
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bool MightHaveTransposeAliasing
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= check_transpose_aliasing_compile_time_selector
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<blas_traits<Derived>::IsTransposed,OtherDerived>::ret
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>
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struct checkTransposeAliasing_impl
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{
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static void run(const Derived& dst, const OtherDerived& other)
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{
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eigen_assert((!check_transpose_aliasing_run_time_selector
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<typename Derived::Scalar,blas_traits<Derived>::IsTransposed,OtherDerived>
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::run(extract_data(dst), other))
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&& "aliasing detected during transposition, use transposeInPlace() "
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"or evaluate the rhs into a temporary using .eval()");
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}
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};
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template<typename Derived, typename OtherDerived>
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struct checkTransposeAliasing_impl<Derived, OtherDerived, false>
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{
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static void run(const Derived&, const OtherDerived&)
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{
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}
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};
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template<typename Dst, typename Src>
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void check_for_aliasing(const Dst &dst, const Src &src)
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{
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internal::checkTransposeAliasing_impl<Dst, Src>::run(dst, src);
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}
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} // end namespace internal
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#endif // EIGEN_NO_DEBUG
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} // end namespace Eigen
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#endif // EIGEN_TRANSPOSE_H
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