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* Add short documentation for Array class * Put all classes explicitly in Core module (where applicable) * Section on Modules in Quick Reference Guide * Put Page 7 after Page 6 in Contents :)
172 lines
6.7 KiB
C++
172 lines
6.7 KiB
C++
// 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) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_SELFCWISEBINARYOP_H
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#define EIGEN_SELFCWISEBINARYOP_H
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/** \class SelfCwiseBinaryOp
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* \ingroup Core_Module
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*
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* \internal
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*
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* \brief Internal helper class for optimizing operators like +=, -=
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*
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* This is a pseudo expression class re-implementing the copyCoeff/copyPacket
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* method to directly performs a +=/-= operations in an optimal way. In particular,
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* this allows to make sure that the input/output data are loaded only once using
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* aligned packet loads.
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*
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* \sa class SwapWrapper for a similar trick.
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*/
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template<typename BinaryOp, typename MatrixType>
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struct ei_traits<SelfCwiseBinaryOp<BinaryOp,MatrixType> > : ei_traits<MatrixType>
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{
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};
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template<typename BinaryOp, typename MatrixType> class SelfCwiseBinaryOp
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: public ei_dense_xpr_base< SelfCwiseBinaryOp<BinaryOp, MatrixType> >::type
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{
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public:
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typedef typename ei_dense_xpr_base<SelfCwiseBinaryOp>::type Base;
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EIGEN_DENSE_PUBLIC_INTERFACE(SelfCwiseBinaryOp)
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typedef typename ei_packet_traits<Scalar>::type Packet;
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using Base::operator=;
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inline SelfCwiseBinaryOp(MatrixType& xpr, const BinaryOp& func = BinaryOp()) : m_matrix(xpr), m_functor(func) {}
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inline Index rows() const { return m_matrix.rows(); }
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inline Index cols() const { return m_matrix.cols(); }
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inline Index outerStride() const { return m_matrix.outerStride(); }
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inline Index innerStride() const { return m_matrix.innerStride(); }
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inline const Scalar* data() const { return m_matrix.data(); }
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// note that this function is needed by assign to correctly align loads/stores
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// TODO make Assign use .data()
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inline Scalar& coeffRef(Index row, Index col)
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{
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return m_matrix.const_cast_derived().coeffRef(row, col);
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}
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// note that this function is needed by assign to correctly align loads/stores
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// TODO make Assign use .data()
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inline Scalar& coeffRef(Index index)
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{
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return m_matrix.const_cast_derived().coeffRef(index);
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}
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template<typename OtherDerived>
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void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
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{
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OtherDerived& _other = other.const_cast_derived();
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ei_internal_assert(row >= 0 && row < rows()
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&& col >= 0 && col < cols());
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Scalar& tmp = m_matrix.coeffRef(row,col);
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tmp = m_functor(tmp, _other.coeff(row,col));
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}
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template<typename OtherDerived>
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void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
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{
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OtherDerived& _other = other.const_cast_derived();
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ei_internal_assert(index >= 0 && index < m_matrix.size());
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Scalar& tmp = m_matrix.coeffRef(index);
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tmp = m_functor(tmp, _other.coeff(index));
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}
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template<typename OtherDerived, int StoreMode, int LoadMode>
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void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
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{
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OtherDerived& _other = other.const_cast_derived();
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ei_internal_assert(row >= 0 && row < rows()
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&& col >= 0 && col < cols());
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m_matrix.template writePacket<StoreMode>(row, col,
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m_functor.packetOp(m_matrix.template packet<StoreMode>(row, col),_other.template packet<LoadMode>(row, col)) );
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}
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template<typename OtherDerived, int StoreMode, int LoadMode>
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void copyPacket(Index index, const DenseBase<OtherDerived>& other)
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{
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OtherDerived& _other = other.const_cast_derived();
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ei_internal_assert(index >= 0 && index < m_matrix.size());
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m_matrix.template writePacket<StoreMode>(index,
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m_functor.packetOp(m_matrix.template packet<StoreMode>(index),_other.template packet<LoadMode>(index)) );
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}
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// reimplement lazyAssign to handle complex *= real
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// see CwiseBinaryOp ctor for details
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template<typename RhsDerived>
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EIGEN_STRONG_INLINE SelfCwiseBinaryOp& lazyAssign(const DenseBase<RhsDerived>& rhs)
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{
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EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(MatrixType,RhsDerived)
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EIGEN_STATIC_ASSERT((ei_functor_allows_mixing_real_and_complex<BinaryOp>::ret
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? int(ei_is_same_type<typename MatrixType::RealScalar, typename RhsDerived::RealScalar>::ret)
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: int(ei_is_same_type<typename MatrixType::Scalar, typename RhsDerived::Scalar>::ret)),
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YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
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#ifdef EIGEN_DEBUG_ASSIGN
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ei_assign_traits<SelfCwiseBinaryOp, RhsDerived>::debug();
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#endif
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ei_assert(rows() == rhs.rows() && cols() == rhs.cols());
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ei_assign_impl<SelfCwiseBinaryOp, RhsDerived>::run(*this,rhs.derived());
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#ifndef EIGEN_NO_DEBUG
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this->checkTransposeAliasing(rhs.derived());
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#endif
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return *this;
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}
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protected:
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MatrixType& m_matrix;
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const BinaryOp& m_functor;
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private:
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SelfCwiseBinaryOp& operator=(const SelfCwiseBinaryOp&);
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};
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template<typename Derived>
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inline Derived& DenseBase<Derived>::operator*=(const Scalar& other)
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{
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SelfCwiseBinaryOp<ei_scalar_product_op<Scalar>, Derived> tmp(derived());
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typedef typename Derived::PlainObject PlainObject;
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tmp = PlainObject::Constant(rows(),cols(),other);
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return derived();
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}
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template<typename Derived>
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inline Derived& DenseBase<Derived>::operator/=(const Scalar& other)
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{
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SelfCwiseBinaryOp<typename ei_meta_if<NumTraits<Scalar>::IsInteger,
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ei_scalar_quotient_op<Scalar>,
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ei_scalar_product_op<Scalar> >::ret, Derived> tmp(derived());
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typedef typename Derived::PlainObject PlainObject;
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tmp = PlainObject::Constant(rows(),cols(), NumTraits<Scalar>::IsInteger ? other : Scalar(1)/other);
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return derived();
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}
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#endif // EIGEN_SELFCWISEBINARYOP_H
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