sparse module:

- remove some useless stuff => let's focus on a single sparse matrix format
 - finalize the new RandomSetter
This commit is contained in:
Gael Guennebaud
2008-10-21 13:35:04 +00:00
parent 9e02e42ff6
commit cf0f82ecbe
12 changed files with 316 additions and 84 deletions

166
disabled/HashMatrix.h Normal file
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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
// 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_HASHMATRIX_H
#define EIGEN_HASHMATRIX_H
template<typename _Scalar, int _Flags>
struct ei_traits<HashMatrix<_Scalar, _Flags> >
{
typedef _Scalar Scalar;
enum {
RowsAtCompileTime = Dynamic,
ColsAtCompileTime = Dynamic,
MaxRowsAtCompileTime = Dynamic,
MaxColsAtCompileTime = Dynamic,
Flags = SparseBit | _Flags,
CoeffReadCost = NumTraits<Scalar>::ReadCost,
SupportedAccessPatterns = RandomAccessPattern
};
};
// TODO reimplement this class using custom linked lists
template<typename _Scalar, int _Flags>
class HashMatrix
: public SparseMatrixBase<HashMatrix<_Scalar, _Flags> >
{
public:
EIGEN_GENERIC_PUBLIC_INTERFACE(HashMatrix)
class InnerIterator;
protected:
typedef typename std::map<int, Scalar>::iterator MapIterator;
typedef typename std::map<int, Scalar>::const_iterator ConstMapIterator;
public:
inline int rows() const { return m_innerSize; }
inline int cols() const { return m_data.size(); }
inline const Scalar& coeff(int row, int col) const
{
const MapIterator it = m_data[col].find(row);
if (it!=m_data[col].end())
return Scalar(0);
return it->second;
}
inline Scalar& coeffRef(int row, int col)
{
return m_data[col][row];
}
public:
inline void startFill(int /*reserveSize = 1000 --- currently unused, don't generate a warning*/) {}
inline Scalar& fill(int row, int col) { return coeffRef(row, col); }
inline void endFill() {}
~HashMatrix()
{}
inline void shallowCopy(const HashMatrix& other)
{
EIGEN_DBG_SPARSE(std::cout << "HashMatrix:: shallowCopy\n");
// FIXME implement a true shallow copy !!
resize(other.rows(), other.cols());
for (int j=0; j<this->outerSize(); ++j)
m_data[j] = other.m_data[j];
}
void resize(int _rows, int _cols)
{
if (cols() != _cols)
{
m_data.resize(_cols);
}
m_innerSize = _rows;
}
inline HashMatrix(int rows, int cols)
: m_innerSize(0)
{
resize(rows, cols);
}
template<typename OtherDerived>
inline HashMatrix(const MatrixBase<OtherDerived>& other)
: m_innerSize(0)
{
*this = other.derived();
}
inline HashMatrix& operator=(const HashMatrix& other)
{
if (other.isRValue())
{
shallowCopy(other);
}
else
{
resize(other.rows(), other.cols());
for (int col=0; col<cols(); ++col)
m_data[col] = other.m_data[col];
}
return *this;
}
template<typename OtherDerived>
inline HashMatrix& operator=(const MatrixBase<OtherDerived>& other)
{
return SparseMatrixBase<HashMatrix>::operator=(other);
}
protected:
std::vector<std::map<int, Scalar> > m_data;
int m_innerSize;
};
template<typename Scalar, int _Flags>
class HashMatrix<Scalar,_Flags>::InnerIterator
{
public:
InnerIterator(const HashMatrix& mat, int col)
: m_matrix(mat), m_it(mat.m_data[col].begin()), m_end(mat.m_data[col].end())
{}
InnerIterator& operator++() { m_it++; return *this; }
Scalar value() { return m_it->second; }
int index() const { return m_it->first; }
operator bool() const { return m_it!=m_end; }
protected:
const HashMatrix& m_matrix;
typename HashMatrix::ConstMapIterator m_it;
typename HashMatrix::ConstMapIterator m_end;
};
#endif // EIGEN_HASHMATRIX_H

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
// 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_LINKEDVECTORMATRIX_H
#define EIGEN_LINKEDVECTORMATRIX_H
template<typename _Scalar, int _Flags>
struct ei_traits<LinkedVectorMatrix<_Scalar,_Flags> >
{
typedef _Scalar Scalar;
enum {
RowsAtCompileTime = Dynamic,
ColsAtCompileTime = Dynamic,
MaxRowsAtCompileTime = Dynamic,
MaxColsAtCompileTime = Dynamic,
Flags = SparseBit | _Flags,
CoeffReadCost = NumTraits<Scalar>::ReadCost,
SupportedAccessPatterns = InnerCoherentAccessPattern
};
};
template<typename Element, int ChunkSize = 8>
struct LinkedVectorChunk
{
LinkedVectorChunk() : next(0), prev(0), size(0) {}
Element data[ChunkSize];
LinkedVectorChunk* next;
LinkedVectorChunk* prev;
int size;
bool isFull() const { return size==ChunkSize; }
};
template<typename _Scalar, int _Flags>
class LinkedVectorMatrix
: public SparseMatrixBase<LinkedVectorMatrix<_Scalar,_Flags> >
{
public:
EIGEN_GENERIC_PUBLIC_INTERFACE(LinkedVectorMatrix)
class InnerIterator;
protected:
enum {
RowMajor = Flags&RowMajorBit ? 1 : 0
};
struct ValueIndex
{
ValueIndex() : value(0), index(0) {}
ValueIndex(Scalar v, int i) : value(v), index(i) {}
Scalar value;
int index;
};
typedef LinkedVectorChunk<ValueIndex,8> VectorChunk;
inline int find(VectorChunk** _el, int id)
{
VectorChunk* el = *_el;
while (el && el->data[el->size-1].index<id)
el = el->next;
*_el = el;
if (el)
{
// binary search
int maxI = el->size-1;
int minI = 0;
int i = el->size/2;
const ValueIndex* data = el->data;
while (data[i].index!=id)
{
if (data[i].index<id)
{
minI = i+1;
i = (maxI + minI)+2;
}
else
{
maxI = i-1;
i = (maxI + minI)+2;
}
if (minI>=maxI)
return -1;
}
if (data[i].index==id)
return i;
}
return -1;
}
public:
inline int rows() const { return RowMajor ? m_data.size() : m_innerSize; }
inline int cols() const { return RowMajor ? m_innerSize : m_data.size(); }
inline const Scalar& coeff(int row, int col) const
{
const int outer = RowMajor ? row : col;
const int inner = RowMajor ? col : row;
VectorChunk* el = m_data[outer];
int id = find(&el, inner);
if (id<0)
return Scalar(0);
return el->data[id].value;
}
inline Scalar& coeffRef(int row, int col)
{
const int outer = RowMajor ? row : col;
const int inner = RowMajor ? col : row;
VectorChunk* el = m_data[outer];
int id = find(&el, inner);
ei_assert(id>=0);
// if (id<0)
// return Scalar(0);
return el->data[id].value;
}
public:
inline void startFill(int reserveSize = 1000)
{
clear();
for (unsigned int i=0; i<m_data.size(); ++i)
m_ends[i] = m_data[i] = 0;
}
inline Scalar& fill(int row, int col)
{
const int outer = RowMajor ? row : col;
const int inner = RowMajor ? col : row;
// std::cout << " ll fill " << outer << "," << inner << "\n";
if (m_ends[outer]==0)
{
m_data[outer] = m_ends[outer] = new VectorChunk();
}
else
{
ei_assert(m_ends[outer]->data[m_ends[outer]->size-1].index < inner);
if (m_ends[outer]->isFull())
{
VectorChunk* el = new VectorChunk();
m_ends[outer]->next = el;
el->prev = m_ends[outer];
m_ends[outer] = el;
}
}
m_ends[outer]->data[m_ends[outer]->size].index = inner;
return m_ends[outer]->data[m_ends[outer]->size++].value;
}
inline void endFill() { }
void printDbg()
{
for (int j=0; j<m_data.size(); ++j)
{
VectorChunk* el = m_data[j];
while (el)
{
for (int i=0; i<el->size; ++i)
std::cout << j << "," << el->data[i].index << " = " << el->data[i].value << "\n";
el = el->next;
}
}
for (int j=0; j<m_data.size(); ++j)
{
InnerIterator it(*this,j);
while (it)
{
std::cout << j << "," << it.index() << " = " << it.value() << "\n";
++it;
}
}
}
~LinkedVectorMatrix()
{
clear();
}
void clear()
{
for (unsigned int i=0; i<m_data.size(); ++i)
{
VectorChunk* el = m_data[i];
while (el)
{
VectorChunk* tmp = el;
el = el->next;
delete tmp;
}
}
}
void resize(int rows, int cols)
{
const int outers = RowMajor ? rows : cols;
const int inners = RowMajor ? cols : rows;
if (this->outerSize() != outers)
{
clear();
m_data.resize(outers);
m_ends.resize(outers);
for (unsigned int i=0; i<m_data.size(); ++i)
m_ends[i] = m_data[i] = 0;
}
m_innerSize = inners;
}
inline LinkedVectorMatrix(int rows, int cols)
: m_innerSize(0)
{
resize(rows, cols);
}
template<typename OtherDerived>
inline LinkedVectorMatrix(const MatrixBase<OtherDerived>& other)
: m_innerSize(0)
{
*this = other.derived();
}
inline void swap(LinkedVectorMatrix& other)
{
EIGEN_DBG_SPARSE(std::cout << "LinkedVectorMatrix:: swap\n");
resize(other.rows(), other.cols());
m_data.swap(other.m_data);
m_ends.swap(other.m_ends);
}
inline LinkedVectorMatrix& operator=(const LinkedVectorMatrix& other)
{
if (other.isRValue())
{
swap(other.const_cast_derived());
}
else
{
// TODO implement a specialized deep copy here
return operator=<LinkedVectorMatrix>(other);
}
return *this;
}
template<typename OtherDerived>
inline LinkedVectorMatrix& operator=(const MatrixBase<OtherDerived>& other)
{
return SparseMatrixBase<LinkedVectorMatrix>::operator=(other.derived());
}
protected:
// outer vector of inner linked vector chunks
std::vector<VectorChunk*> m_data;
// stores a reference to the last vector chunk for efficient filling
std::vector<VectorChunk*> m_ends;
int m_innerSize;
};
template<typename Scalar, int _Flags>
class LinkedVectorMatrix<Scalar,_Flags>::InnerIterator
{
public:
InnerIterator(const LinkedVectorMatrix& mat, int col)
: m_matrix(mat), m_el(mat.m_data[col]), m_it(0)
{}
InnerIterator& operator++()
{
m_it++;
if (m_it>=m_el->size)
{
m_el = m_el->next;
m_it = 0;
}
return *this;
}
Scalar value() { return m_el->data[m_it].value; }
int index() const { return m_el->data[m_it].index; }
operator bool() const { return m_el && (m_el->next || m_it<m_el->size); }
protected:
const LinkedVectorMatrix& m_matrix;
VectorChunk* m_el;
int m_it;
};
#endif // EIGEN_LINKEDVECTORMATRIX_H

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//
// 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_SPARSESETTER_H
#define EIGEN_SPARSESETTER_H
template<typename MatrixType, int AccessPattern,
int IsSupported = ei_support_access_pattern<MatrixType,AccessPattern>::ret>
struct ei_sparse_setter_selector;
/** \class SparseSetter
*
* Goal: provides a unified API to fill/update a dense or sparse matrix.
*
* Usage:
* \code
* {
* SparseSetter<MatrixType, RandomAccessPattern> w(m);
* for (...) w->coeffRef(rand(),rand()) = rand();
* }
* \endcode
*
* In the above example we want to fill a matrix m (could be a SparseMatrix or whatever other matrix type)
* in a random fashion (whence the RandomAccessPattern). Internally, if \a MatrixType supports random writes
* then \c w behaves as a pointer to m, and m is filled directly. Otherwise, a temporary matrix supporting
* random writes is created and \c w behaves as a pointer to this temporary object. When the object \c w
* is deleted (at the end of the block), then the temporary object is assigned to the matrix m.
*
* So far we can distinghished 4 types of access pattern:
* - FullyCoherentAccessPattern (if col major, i+j*rows must increase)
* - InnerCoherentAccessPattern (if col major, i must increase for each column j)
* - OuterCoherentAccessPattern (if col major, the column j is set in a random order, but j must increase)
* - RandomAccessPattern
*
* See the wiki for more details.
*
* The template class ei_support_access_pattern is used to determine the type of the temporary object (which
* can be a reference to \a MatrixType if \a MatrixType support \a AccessPattern)
*
* Currently only the RandomAccessPattern seems to work as expected.
*
* \todo define the API for each kind of access pattern
* \todo allows both update and set modes (set start a new matrix)
* \todo implement the OuterCoherentAccessPattern
*
*/
template<typename MatrixType,
int AccessPattern,
typename WrapperType = typename ei_sparse_setter_selector<MatrixType,AccessPattern>::type>
class SparseSetter
{
typedef typename ei_unref<WrapperType>::type _WrapperType;
public:
inline SparseSetter(MatrixType& matrix) : m_wrapper(matrix), mp_matrix(&matrix) {}
~SparseSetter()
{ *mp_matrix = m_wrapper; }
inline _WrapperType* operator->() { return &m_wrapper; }
inline _WrapperType& operator*() { return m_wrapper; }
protected:
WrapperType m_wrapper;
MatrixType* mp_matrix;
};
template<typename MatrixType, int AccessPattern>
struct ei_sparse_setter_selector<MatrixType, AccessPattern, AccessPatternSupported>
{
typedef MatrixType& type;
};
// forward each derived of SparseMatrixBase to the generic SparseMatrixBase specializations
template<typename Scalar, int Flags, int AccessPattern>
struct ei_sparse_setter_selector<SparseMatrix<Scalar,Flags>, AccessPattern, AccessPatternNotSupported>
: public ei_sparse_setter_selector<SparseMatrixBase<SparseMatrix<Scalar,Flags> >,AccessPattern, AccessPatternNotSupported>
{};
template<typename Scalar, int Flags, int AccessPattern>
struct ei_sparse_setter_selector<LinkedVectorMatrix<Scalar,Flags>, AccessPattern, AccessPatternNotSupported>
: public ei_sparse_setter_selector<LinkedVectorMatrix<SparseMatrix<Scalar,Flags> >,AccessPattern, AccessPatternNotSupported>
{};
template<typename Scalar, int Flags, int AccessPattern>
struct ei_sparse_setter_selector<HashMatrix<Scalar,Flags>, AccessPattern, AccessPatternNotSupported>
: public ei_sparse_setter_selector<HashMatrix<SparseMatrix<Scalar,Flags> >,AccessPattern, AccessPatternNotSupported>
{};
// generic SparseMatrixBase specializations
template<typename Derived>
struct ei_sparse_setter_selector<SparseMatrixBase<Derived>, RandomAccessPattern, AccessPatternNotSupported>
{
typedef HashMatrix<typename Derived::Scalar, Derived::Flags> type;
};
template<typename Derived>
struct ei_sparse_setter_selector<SparseMatrixBase<Derived>, OuterCoherentAccessPattern, AccessPatternNotSupported>
{
typedef HashMatrix<typename Derived::Scalar, Derived::Flags> type;
};
template<typename Derived>
struct ei_sparse_setter_selector<SparseMatrixBase<Derived>, InnerCoherentAccessPattern, AccessPatternNotSupported>
{
typedef LinkedVectorMatrix<typename Derived::Scalar, Derived::Flags> type;
};
template<typename Derived>
struct ei_sparse_setter_selector<SparseMatrixBase<Derived>, FullyCoherentAccessPattern, AccessPatternNotSupported>
{
typedef SparseMatrix<typename Derived::Scalar, Derived::Flags> type;
};
#endif // EIGEN_SPARSESETTER_H