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removed sparse dynamic matrix

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jenswehner 2021-08-24 10:33:00 +02:00
parent e5c8f283ae
commit d85de1ef56
4 changed files with 0 additions and 538 deletions
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2
unsupported/Eigen/SparseExtra
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@ -38,8 +38,6 @@
*/
#include "src/SparseExtra/DynamicSparseMatrix.h"
#include "src/SparseExtra/BlockOfDynamicSparseMatrix.h"
#include "src/SparseExtra/RandomSetter.h"
#include "src/SparseExtra/MarketIO.h"

122
unsupported/Eigen/src/SparseExtra/BlockOfDynamicSparseMatrix.h
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@ -1,122 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_SPARSE_BLOCKFORDYNAMICMATRIX_H
#define EIGEN_SPARSE_BLOCKFORDYNAMICMATRIX_H
namespace Eigen {
#if 0
// NOTE Have to be reimplemented as a specialization of BlockImpl< DynamicSparseMatrix<Scalar_, Options_, Index_>, ... >
// See SparseBlock.h for an example
/***************************************************************************
* specialisation for DynamicSparseMatrix
***************************************************************************/
template<typename Scalar_, int Options_, typename Index_, int Size>
class SparseInnerVectorSet<DynamicSparseMatrix<Scalar_, Options_, Index_>, Size>
: public SparseMatrixBase<SparseInnerVectorSet<DynamicSparseMatrix<Scalar_, Options_, Index_>, Size> >
{
typedef DynamicSparseMatrix<Scalar_, Options_, Index_> MatrixType;
public:
enum { IsRowMajor = internal::traits<SparseInnerVectorSet>::IsRowMajor };
EIGEN_SPARSE_PUBLIC_INTERFACE(SparseInnerVectorSet)
class InnerIterator: public MatrixType::InnerIterator
{
public:
inline InnerIterator(const SparseInnerVectorSet& xpr, Index outer)
: MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
{}
inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
protected:
Index m_outer;
};
inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize)
: m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
{
eigen_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
}
inline SparseInnerVectorSet(const MatrixType& matrix, Index outer)
: m_matrix(matrix), m_outerStart(outer), m_outerSize(Size)
{
eigen_assert(Size!=Dynamic);
eigen_assert( (outer>=0) && (outer<matrix.outerSize()) );
}
template<typename OtherDerived>
inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
{
if (IsRowMajor != ((OtherDerived::Flags&RowMajorBit)==RowMajorBit))
{
// need to transpose => perform a block evaluation followed by a big swap
DynamicSparseMatrix<Scalar,IsRowMajor?RowMajorBit:0> aux(other);
*this = aux.markAsRValue();
}
else
{
// evaluate/copy vector per vector
for (Index j=0; j<m_outerSize.value(); ++j)
{
SparseVector<Scalar,IsRowMajor ? RowMajorBit : 0> aux(other.innerVector(j));
m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data());
}
}
return *this;
}
inline SparseInnerVectorSet& operator=(const SparseInnerVectorSet& other)
{
return operator=<SparseInnerVectorSet>(other);
}
Index nonZeros() const
{
Index count = 0;
for (Index j=0; j<m_outerSize.value(); ++j)
count += m_matrix._data()[m_outerStart+j].size();
return count;
}
const Scalar& lastCoeff() const
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(SparseInnerVectorSet);
eigen_assert(m_matrix.data()[m_outerStart].size()>0);
return m_matrix.data()[m_outerStart].vale(m_matrix.data()[m_outerStart].size()-1);
}
// template<typename Sparse>
// inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
// {
// return *this;
// }
EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
protected:
const typename MatrixType::Nested m_matrix;
Index m_outerStart;
const internal::variable_if_dynamic<Index, Size> m_outerSize;
};
#endif
} // end namespace Eigen
#endif // EIGEN_SPARSE_BLOCKFORDYNAMICMATRIX_H

404
unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h
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@ -1,404 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_DYNAMIC_SPARSEMATRIX_H
#define EIGEN_DYNAMIC_SPARSEMATRIX_H
namespace Eigen {
/** \deprecated use a SparseMatrix in an uncompressed mode
*
* \class DynamicSparseMatrix
*
* \brief A sparse matrix class designed for matrix assembly purpose
*
* \param Scalar_ the scalar type, i.e. the type of the coefficients
*
* Unlike SparseMatrix, this class provides a much higher degree of flexibility. In particular, it allows
* random read/write accesses in log(rho*outer_size) where \c rho is the probability that a coefficient is
* nonzero and outer_size is the number of columns if the matrix is column-major and the number of rows
* otherwise.
*
* Internally, the data are stored as a std::vector of compressed vector. The performances of random writes might
* decrease as the number of nonzeros per inner-vector increase. In practice, we observed very good performance
* till about 100 nonzeros/vector, and the performance remains relatively good till 500 nonzeros/vectors.
*
* \see SparseMatrix
*/
namespace internal {
template<typename Scalar_, int Options_, typename StorageIndex_>
struct traits<DynamicSparseMatrix<Scalar_, Options_, StorageIndex_> >
{
typedef Scalar_ Scalar;
typedef StorageIndex_ StorageIndex;
typedef Sparse StorageKind;
typedef MatrixXpr XprKind;
enum {
RowsAtCompileTime = Dynamic,
ColsAtCompileTime = Dynamic,
MaxRowsAtCompileTime = Dynamic,
MaxColsAtCompileTime = Dynamic,
Flags = Options_ | NestByRefBit | LvalueBit,
CoeffReadCost = NumTraits<Scalar>::ReadCost,
SupportedAccessPatterns = OuterRandomAccessPattern
};
};
}
template<typename Scalar_, int Options_, typename StorageIndex_>
class DynamicSparseMatrix
: public SparseMatrixBase<DynamicSparseMatrix<Scalar_, Options_, StorageIndex_> >
{
typedef SparseMatrixBase<DynamicSparseMatrix> Base;
using Base::convert_index;
public:
EIGEN_SPARSE_PUBLIC_INTERFACE(DynamicSparseMatrix)
// FIXME: why are these operator already alvailable ???
// EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, +=)
// EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, -=)
typedef MappedSparseMatrix<Scalar,Flags> Map;
using Base::IsRowMajor;
using Base::operator=;
enum {
Options = Options_
};
protected:
typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0), StorageIndex> TransposedSparseMatrix;
Index m_innerSize;
std::vector<internal::CompressedStorage<Scalar,StorageIndex> > m_data;
public:
inline Index rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
inline Index cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
inline Index innerSize() const { return m_innerSize; }
inline Index outerSize() const { return convert_index(m_data.size()); }
inline Index innerNonZeros(Index j) const { return m_data[j].size(); }
std::vector<internal::CompressedStorage<Scalar,StorageIndex> >& _data() { return m_data; }
const std::vector<internal::CompressedStorage<Scalar,StorageIndex> >& _data() const { return m_data; }
/** \returns the coefficient value at given position \a row, \a col
* This operation involes a log(rho*outer_size) binary search.
*/
inline Scalar coeff(Index row, Index col) const
{
const Index outer = IsRowMajor ? row : col;
const Index inner = IsRowMajor ? col : row;
return m_data[outer].at(inner);
}
/** \returns a reference to the coefficient value at given position \a row, \a col
* This operation involes a log(rho*outer_size) binary search. If the coefficient does not
* exist yet, then a sorted insertion into a sequential buffer is performed.
*/
inline Scalar& coeffRef(Index row, Index col)
{
const Index outer = IsRowMajor ? row : col;
const Index inner = IsRowMajor ? col : row;
return m_data[outer].atWithInsertion(inner);
}
class InnerIterator;
class ReverseInnerIterator;
void setZero()
{
for (Index j=0; j<outerSize(); ++j)
m_data[j].clear();
}
/** \returns the number of non zero coefficients */
Index nonZeros() const
{
Index res = 0;
for (Index j=0; j<outerSize(); ++j)
res += m_data[j].size();
return res;
}
void reserve(Index reserveSize = 1000)
{
if (outerSize()>0)
{
Index reserveSizePerVector = (std::max)(reserveSize/outerSize(),Index(4));
for (Index j=0; j<outerSize(); ++j)
{
m_data[j].reserve(reserveSizePerVector);
}
}
}
/** Does nothing: provided for compatibility with SparseMatrix */
inline void startVec(Index /*outer*/) {}
/** \returns a reference to the non zero coefficient at position \a row, \a col assuming that:
* - the nonzero does not already exist
* - the new coefficient is the last one of the given inner vector.
*
* \sa insert, insertBackByOuterInner */
inline Scalar& insertBack(Index row, Index col)
{
return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row);
}
/** \sa insertBack */
inline Scalar& insertBackByOuterInner(Index outer, Index inner)
{
eigen_assert(outer<Index(m_data.size()) && inner<m_innerSize && "out of range");
eigen_assert(((m_data[outer].size()==0) || (m_data[outer].index(m_data[outer].size()-1)<inner))
&& "wrong sorted insertion");
m_data[outer].append(0, inner);
return m_data[outer].value(m_data[outer].size()-1);
}
inline Scalar& insert(Index row, Index col)
{
const Index outer = IsRowMajor ? row : col;
const Index inner = IsRowMajor ? col : row;
Index startId = 0;
Index id = static_cast<Index>(m_data[outer].size()) - 1;
m_data[outer].resize(id+2,1);
while ( (id >= startId) && (m_data[outer].index(id) > inner) )
{
m_data[outer].index(id+1) = m_data[outer].index(id);
m_data[outer].value(id+1) = m_data[outer].value(id);
--id;
}
m_data[outer].index(id+1) = inner;
m_data[outer].value(id+1) = 0;
return m_data[outer].value(id+1);
}
/** Does nothing: provided for compatibility with SparseMatrix */
inline void finalize() {}
/** Suppress all nonzeros which are smaller than \a reference under the tolerance \a epsilon */
void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
{
for (Index j=0; j<outerSize(); ++j)
m_data[j].prune(reference,epsilon);
}
/** Resize the matrix without preserving the data (the matrix is set to zero)
*/
void resize(Index rows, Index cols)
{
const Index outerSize = IsRowMajor ? rows : cols;
m_innerSize = convert_index(IsRowMajor ? cols : rows);
setZero();
if (Index(m_data.size()) != outerSize)
{
m_data.resize(outerSize);
}
}
void resizeAndKeepData(Index rows, Index cols)
{
const Index outerSize = IsRowMajor ? rows : cols;
const Index innerSize = IsRowMajor ? cols : rows;
if (m_innerSize>innerSize)
{
// remove all coefficients with innerCoord>=innerSize
// TODO
//std::cerr << "not implemented yet\n";
exit(2);
}
if (m_data.size() != outerSize)
{
m_data.resize(outerSize);
}
}
/** The class DynamicSparseMatrix is deprecated */
EIGEN_DEPRECATED inline DynamicSparseMatrix()
: m_innerSize(0), m_data(0)
{
#ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
#endif
eigen_assert(innerSize()==0 && outerSize()==0);
}
/** The class DynamicSparseMatrix is deprecated */
EIGEN_DEPRECATED inline DynamicSparseMatrix(Index rows, Index cols)
: m_innerSize(0)
{
#ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
#endif
resize(rows, cols);
}
/** The class DynamicSparseMatrix is deprecated */
template<typename OtherDerived>
EIGEN_DEPRECATED explicit inline DynamicSparseMatrix(const SparseMatrixBase<OtherDerived>& other)
: m_innerSize(0)
{
#ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
#endif
Base::operator=(other.derived());
}
inline DynamicSparseMatrix(const DynamicSparseMatrix& other)
: Base(), m_innerSize(0)
{
#ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
#endif
*this = other.derived();
}
inline void swap(DynamicSparseMatrix& other)
{
//EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n");
std::swap(m_innerSize, other.m_innerSize);
//std::swap(m_outerSize, other.m_outerSize);
m_data.swap(other.m_data);
}
inline DynamicSparseMatrix& operator=(const DynamicSparseMatrix& other)
{
if (other.isRValue())
{
swap(other.const_cast_derived());
}
else
{
resize(other.rows(), other.cols());
m_data = other.m_data;
}
return *this;
}
/** Destructor */
inline ~DynamicSparseMatrix() {}
public:
/** \deprecated
* Set the matrix to zero and reserve the memory for \a reserveSize nonzero coefficients. */
EIGEN_DEPRECATED void startFill(Index reserveSize = 1000)
{
setZero();
reserve(reserveSize);
}
/** \deprecated use insert()
* inserts a nonzero coefficient at given coordinates \a row, \a col and returns its reference assuming that:
* 1 - the coefficient does not exist yet
* 2 - this the coefficient with greater inner coordinate for the given outer coordinate.
* In other words, assuming \c *this is column-major, then there must not exists any nonzero coefficient of coordinates
* \c i \c x \a col such that \c i >= \a row. Otherwise the matrix is invalid.
*
* \see fillrand(), coeffRef()
*/
EIGEN_DEPRECATED Scalar& fill(Index row, Index col)
{
const Index outer = IsRowMajor ? row : col;
const Index inner = IsRowMajor ? col : row;
return insertBack(outer,inner);
}
/** \deprecated use insert()
* Like fill() but with random inner coordinates.
* Compared to the generic coeffRef(), the unique limitation is that we assume
* the coefficient does not exist yet.
*/
EIGEN_DEPRECATED Scalar& fillrand(Index row, Index col)
{
return insert(row,col);
}
/** \deprecated use finalize()
* Does nothing. Provided for compatibility with SparseMatrix. */
EIGEN_DEPRECATED void endFill() {}
# ifdef EIGEN_DYNAMICSPARSEMATRIX_PLUGIN
# include EIGEN_DYNAMICSPARSEMATRIX_PLUGIN
# endif
};
template<typename Scalar, int Options_, typename StorageIndex_>
class DynamicSparseMatrix<Scalar,Options_,StorageIndex_>::InnerIterator : public SparseVector<Scalar,Options_,StorageIndex_>::InnerIterator
{
typedef typename SparseVector<Scalar,Options_,StorageIndex_>::InnerIterator Base;
public:
InnerIterator(const DynamicSparseMatrix& mat, Index outer)
: Base(mat.m_data[outer]), m_outer(outer)
{}
inline Index row() const { return IsRowMajor ? m_outer : Base::index(); }
inline Index col() const { return IsRowMajor ? Base::index() : m_outer; }
inline Index outer() const { return m_outer; }
protected:
const Index m_outer;
};
template<typename Scalar, int Options_, typename StorageIndex_>
class DynamicSparseMatrix<Scalar,Options_,StorageIndex_>::ReverseInnerIterator : public SparseVector<Scalar,Options_,StorageIndex_>::ReverseInnerIterator
{
typedef typename SparseVector<Scalar,Options_,StorageIndex_>::ReverseInnerIterator Base;
public:
ReverseInnerIterator(const DynamicSparseMatrix& mat, Index outer)
: Base(mat.m_data[outer]), m_outer(outer)
{}
inline Index row() const { return IsRowMajor ? m_outer : Base::index(); }
inline Index col() const { return IsRowMajor ? Base::index() : m_outer; }
inline Index outer() const { return m_outer; }
protected:
const Index m_outer;
};
namespace internal {
template<typename Scalar_, int Options_, typename StorageIndex_>
struct evaluator<DynamicSparseMatrix<Scalar_,Options_,StorageIndex_> >
: evaluator_base<DynamicSparseMatrix<Scalar_,Options_,StorageIndex_> >
{
typedef Scalar_ Scalar;
typedef DynamicSparseMatrix<Scalar_,Options_,StorageIndex_> SparseMatrixType;
typedef typename SparseMatrixType::InnerIterator InnerIterator;
typedef typename SparseMatrixType::ReverseInnerIterator ReverseInnerIterator;
enum {
CoeffReadCost = NumTraits<Scalar_>::ReadCost,
Flags = SparseMatrixType::Flags
};
evaluator() : m_matrix(0) {}
evaluator(const SparseMatrixType &mat) : m_matrix(&mat) {}
operator SparseMatrixType&() { return m_matrix->const_cast_derived(); }
operator const SparseMatrixType&() const { return *m_matrix; }
Scalar coeff(Index row, Index col) const { return m_matrix->coeff(row,col); }
Index nonZerosEstimate() const { return m_matrix->nonZeros(); }
const SparseMatrixType *m_matrix;
};
}
} // end namespace Eigen
#endif // EIGEN_DYNAMIC_SPARSEMATRIX_H

10
unsupported/test/sparse_extra.cpp
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@ -27,9 +27,6 @@ static long g_dense_op_sparse_count = 0;
#define EIGEN_SPARSE_PRODUCT_IGNORE_TEMPORARY_COUNT
#include "sparse_product.cpp"
#if 0 // sparse_basic(DynamicSparseMatrix) does not compile at all -> disabled
#include "sparse_basic.cpp"
#endif
#if EIGEN_HAS_CXX11
@ -195,13 +192,6 @@ EIGEN_DECLARE_TEST(sparse_extra)
CALL_SUBTEST_2( sparse_extra(SparseMatrix<std::complex<double> >(s, s)) );
CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(s, s)) );
CALL_SUBTEST_3( sparse_extra(DynamicSparseMatrix<double>(s, s)) );
// CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double>(s, s)) ));
// CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double,ColMajor,long int>(s, s)) ));
CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, ColMajor> >()) );
CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, RowMajor> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<float,ColMajor,int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<double,ColMajor,int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<std::complex<float>,ColMajor,int> >()) );