add a SparseNestByValue expression and fix issue in sparse adjoint evaluation

This commit is contained in:
Gael Guennebaud 2009-07-13 14:55:03 +02:00
parent ab17f92728
commit 1e7b1a8a85
7 changed files with 97 additions and 7 deletions

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@ -84,6 +84,7 @@ namespace Eigen {
#include "src/Sparse/SparseUtil.h"
#include "src/Sparse/SparseMatrixBase.h"
#include "src/Sparse/SparseNestByValue.h"
#include "src/Sparse/CompressedStorage.h"
#include "src/Sparse/AmbiVector.h"
#include "src/Sparse/RandomSetter.h"

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@ -443,9 +443,8 @@ class SparseMatrix
// two passes algorithm:
// 1 - compute the number of coeffs per dest inner vector
// 2 - do the actual copy/eval
// Since each coeff of the rhs has to be evaluated twice, let's evauluate it if needed
//typedef typename ei_nested<OtherDerived,2>::type OtherCopy;
typedef typename ei_eval<OtherDerived>::type OtherCopy;
// Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed
typedef typename ei_nested<OtherDerived,2>::type OtherCopy;
typedef typename ei_cleantype<OtherCopy>::type _OtherCopy;
OtherCopy otherCopy(other.derived());

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@ -99,8 +99,10 @@ template<typename Derived> class SparseMatrixBase
/** \internal the return type of MatrixBase::imag() */
typedef SparseCwiseUnaryOp<ei_scalar_imag_op<Scalar>, Derived> ImagReturnType;
/** \internal the return type of MatrixBase::adjoint() */
typedef SparseTranspose</*NestByValue<*/typename ei_cleantype<ConjugateReturnType>::type> /*>*/
AdjointReturnType;
typedef typename ei_meta_if<NumTraits<Scalar>::IsComplex,
SparseCwiseUnaryOp<ei_scalar_conjugate_op<Scalar>, SparseNestByValue<Eigen::SparseTranspose<Derived> > >,
SparseTranspose<Derived>
>::ret AdjointReturnType;
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** This is the "real scalar" type; if the \a Scalar type is already real numbers
@ -342,7 +344,7 @@ template<typename Derived> class SparseMatrixBase
SparseTranspose<Derived> transpose() { return derived(); }
const SparseTranspose<Derived> transpose() const { return derived(); }
// void transposeInPlace();
const AdjointReturnType adjoint() const { return conjugate()/*.nestByValue()*/; }
const AdjointReturnType adjoint() const { return transpose().nestByValue(); }
// sub-vector
SparseInnerVectorSet<Derived,1> row(int i);
@ -520,7 +522,7 @@ template<typename Derived> class SparseMatrixBase
*/
// inline int stride(void) const { return derived().stride(); }
// inline const NestByValue<Derived> nestByValue() const;
inline const SparseNestByValue<Derived> nestByValue() const;
ConjugateReturnType conjugate() const;

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@ -0,0 +1,84 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_SPARSENESTBYVALUE_H
#define EIGEN_SPARSENESTBYVALUE_H
/** \class SparseNestByValue
*
* \brief Expression which must be nested by value
*
* \param ExpressionType the type of the object of which we are requiring nesting-by-value
*
* This class is the return type of MatrixBase::nestByValue()
* and most of the time this is the only way it is used.
*
* \sa SparseMatrixBase::nestByValue(), class NestByValue
*/
template<typename ExpressionType>
struct ei_traits<SparseNestByValue<ExpressionType> > : public ei_traits<ExpressionType>
{};
template<typename ExpressionType> class SparseNestByValue
: public SparseMatrixBase<NestByValue<ExpressionType> >
{
public:
class InnerIterator;
EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseNestByValue)
inline SparseNestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
EIGEN_STRONG_INLINE int rows() const { return m_expression.rows(); }
EIGEN_STRONG_INLINE int cols() const { return m_expression.cols(); }
operator const ExpressionType&() const { return m_expression; }
protected:
const ExpressionType m_expression;
};
/** \returns an expression of the temporary version of *this.
*/
template<typename Derived>
inline const SparseNestByValue<Derived>
SparseMatrixBase<Derived>::nestByValue() const
{
return SparseNestByValue<Derived>(derived());
}
template<typename MatrixType>
class SparseNestByValue<MatrixType>::InnerIterator : public MatrixType::InnerIterator
{
typedef typename MatrixType::InnerIterator Base;
public:
EIGEN_STRONG_INLINE InnerIterator(const SparseNestByValue& expr, int outer)
: Base(expr.m_expression, outer)
{}
};
#endif // EIGEN_SPARSENESTBYVALUE_H

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@ -106,6 +106,7 @@ template<typename _Scalar, int _Flags = 0> class DynamicSparseMatrix;
template<typename _Scalar, int _Flags = 0> class SparseVector;
template<typename _Scalar, int _Flags = 0> class MappedSparseMatrix;
template<typename MatrixType> class SparseNestByValue;
template<typename MatrixType> class SparseTranspose;
template<typename MatrixType, int Size> class SparseInnerVectorSet;
template<typename Derived> class SparseCwise;

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@ -28,6 +28,7 @@
#include <iostream>
#include <string>
#include <vector>
#include <typeinfo>
#ifndef EIGEN_TEST_FUNC
#error EIGEN_TEST_FUNC must be defined

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@ -299,6 +299,8 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
initSparse<Scalar>(density, refMat2, m2);
VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
VERIFY_IS_APPROX(SparseMatrixType(m2.adjoint()), refMat2.adjoint());
}
// test prune