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add a SparseNestByValue expression and fix issue in sparse adjoint evaluation
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@ -84,6 +84,7 @@ namespace Eigen {
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#include "src/Sparse/SparseUtil.h"
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#include "src/Sparse/SparseMatrixBase.h"
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#include "src/Sparse/SparseNestByValue.h"
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#include "src/Sparse/CompressedStorage.h"
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#include "src/Sparse/AmbiVector.h"
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#include "src/Sparse/RandomSetter.h"
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@ -443,9 +443,8 @@ class SparseMatrix
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// two passes algorithm:
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// 1 - compute the number of coeffs per dest inner vector
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// 2 - do the actual copy/eval
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// Since each coeff of the rhs has to be evaluated twice, let's evauluate it if needed
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//typedef typename ei_nested<OtherDerived,2>::type OtherCopy;
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typedef typename ei_eval<OtherDerived>::type OtherCopy;
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// Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed
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typedef typename ei_nested<OtherDerived,2>::type OtherCopy;
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typedef typename ei_cleantype<OtherCopy>::type _OtherCopy;
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OtherCopy otherCopy(other.derived());
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@ -99,8 +99,10 @@ template<typename Derived> class SparseMatrixBase
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/** \internal the return type of MatrixBase::imag() */
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typedef SparseCwiseUnaryOp<ei_scalar_imag_op<Scalar>, Derived> ImagReturnType;
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/** \internal the return type of MatrixBase::adjoint() */
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typedef SparseTranspose</*NestByValue<*/typename ei_cleantype<ConjugateReturnType>::type> /*>*/
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AdjointReturnType;
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typedef typename ei_meta_if<NumTraits<Scalar>::IsComplex,
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SparseCwiseUnaryOp<ei_scalar_conjugate_op<Scalar>, SparseNestByValue<Eigen::SparseTranspose<Derived> > >,
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SparseTranspose<Derived>
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>::ret AdjointReturnType;
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#ifndef EIGEN_PARSED_BY_DOXYGEN
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/** This is the "real scalar" type; if the \a Scalar type is already real numbers
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@ -342,7 +344,7 @@ template<typename Derived> class SparseMatrixBase
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SparseTranspose<Derived> transpose() { return derived(); }
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const SparseTranspose<Derived> transpose() const { return derived(); }
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// void transposeInPlace();
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const AdjointReturnType adjoint() const { return conjugate()/*.nestByValue()*/; }
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const AdjointReturnType adjoint() const { return transpose().nestByValue(); }
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// sub-vector
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SparseInnerVectorSet<Derived,1> row(int i);
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@ -520,7 +522,7 @@ template<typename Derived> class SparseMatrixBase
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*/
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// inline int stride(void) const { return derived().stride(); }
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// inline const NestByValue<Derived> nestByValue() const;
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inline const SparseNestByValue<Derived> nestByValue() const;
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ConjugateReturnType conjugate() const;
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84
Eigen/src/Sparse/SparseNestByValue.h
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84
Eigen/src/Sparse/SparseNestByValue.h
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@ -0,0 +1,84 @@
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// 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) 2008-2009 Gael Guennebaud <g.gael@free.fr>
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// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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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_SPARSENESTBYVALUE_H
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#define EIGEN_SPARSENESTBYVALUE_H
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/** \class SparseNestByValue
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*
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* \brief Expression which must be nested by value
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*
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* \param ExpressionType the type of the object of which we are requiring nesting-by-value
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*
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* This class is the return type of MatrixBase::nestByValue()
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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 SparseMatrixBase::nestByValue(), class NestByValue
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*/
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template<typename ExpressionType>
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struct ei_traits<SparseNestByValue<ExpressionType> > : public ei_traits<ExpressionType>
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{};
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template<typename ExpressionType> class SparseNestByValue
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: public SparseMatrixBase<NestByValue<ExpressionType> >
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{
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public:
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class InnerIterator;
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EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseNestByValue)
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inline SparseNestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
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EIGEN_STRONG_INLINE int rows() const { return m_expression.rows(); }
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EIGEN_STRONG_INLINE int cols() const { return m_expression.cols(); }
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operator const ExpressionType&() const { return m_expression; }
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protected:
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const ExpressionType m_expression;
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};
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/** \returns an expression of the temporary version of *this.
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*/
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template<typename Derived>
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inline const SparseNestByValue<Derived>
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SparseMatrixBase<Derived>::nestByValue() const
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{
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return SparseNestByValue<Derived>(derived());
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}
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template<typename MatrixType>
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class SparseNestByValue<MatrixType>::InnerIterator : public MatrixType::InnerIterator
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{
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typedef typename MatrixType::InnerIterator Base;
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public:
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EIGEN_STRONG_INLINE InnerIterator(const SparseNestByValue& expr, int outer)
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: Base(expr.m_expression, outer)
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{}
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};
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#endif // EIGEN_SPARSENESTBYVALUE_H
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@ -106,6 +106,7 @@ template<typename _Scalar, int _Flags = 0> class DynamicSparseMatrix;
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template<typename _Scalar, int _Flags = 0> class SparseVector;
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template<typename _Scalar, int _Flags = 0> class MappedSparseMatrix;
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template<typename MatrixType> class SparseNestByValue;
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template<typename MatrixType> class SparseTranspose;
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template<typename MatrixType, int Size> class SparseInnerVectorSet;
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template<typename Derived> class SparseCwise;
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@ -28,6 +28,7 @@
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#include <iostream>
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#include <string>
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#include <vector>
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#include <typeinfo>
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#ifndef EIGEN_TEST_FUNC
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#error EIGEN_TEST_FUNC must be defined
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@ -299,6 +299,8 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
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initSparse<Scalar>(density, refMat2, m2);
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VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
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VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
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VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
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}
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// test prune
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