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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_SPARSEMATRIX_H
#define EIGEN_SPARSEMATRIX_H
/** \class SparseMatrix
*
* \brief Sparse matrix
*
* \param _Scalar the scalar type, i.e. the type of the coefficients
*
* See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
*
*/
template<typename _Scalar, int _Flags>
struct ei_traits<SparseMatrix<_Scalar, _Flags> >
{
typedef _Scalar Scalar;
enum {
RowsAtCompileTime = Dynamic,
ColsAtCompileTime = Dynamic,
MaxRowsAtCompileTime = Dynamic,
MaxColsAtCompileTime = Dynamic,
Flags = SparseBit | _Flags,
CoeffReadCost = NumTraits<Scalar>::ReadCost,
SupportedAccessPatterns = FullyCoherentAccessPattern
};
};
template<typename _Scalar, int _Flags>
class SparseMatrix : public SparseMatrixBase<SparseMatrix<_Scalar, _Flags> >
{
public:
EIGEN_GENERIC_PUBLIC_INTERFACE(SparseMatrix)
protected:
public:
typedef SparseMatrixBase<SparseMatrix> SparseBase;
enum {
RowMajor = SparseBase::RowMajor
};
int m_outerSize;
int m_innerSize;
int* m_outerIndex;
SparseArray<Scalar> m_data;
public:
inline int rows() const { return RowMajor ? m_outerSize : m_innerSize; }
inline int cols() const { return RowMajor ? m_innerSize : m_outerSize; }
inline int innerSize() const { return m_innerSize; }
inline int outerSize() const { return m_outerSize; }
inline int innerNonZeros(int j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
inline Scalar coeff(int row, int col) const
{
const int outer = RowMajor ? row : col;
const int inner = RowMajor ? col : row;
int start = m_outerIndex[outer];
int end = m_outerIndex[outer+1];
if (start==end)
return Scalar(0);
else if (end>0 && inner==m_data.index(end-1))
return m_data.value(end-1);
// ^^ optimization: let's first check if it is the last coefficient
// (very common in high level algorithms)
const int* r = std::lower_bound(&m_data.index(start),&m_data.index(end),inner);
const int id = r-&m_data.index(0);
return ((*r==inner) && (id<end)) ? m_data.value(id) : Scalar(0);
}
inline Scalar& coeffRef(int row, int col)
{
const int outer = RowMajor ? row : col;
const int inner = RowMajor ? col : row;
int start = m_outerIndex[outer];
int end = m_outerIndex[outer+1];
ei_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
ei_assert(end>start && "coeffRef cannot be called on a zero coefficient");
int* r = std::lower_bound(&m_data.index(start),&m_data.index(end),inner);
const int id = r-&m_data.index(0);
ei_assert((*r==inner) && (id<end) && "coeffRef cannot be called on a zero coefficient");
return m_data.value(id);
}
public:
class InnerIterator;
/** \returns the number of non zero coefficients */
inline int nonZeros() const { return m_data.size(); }
inline void startFill(int reserveSize = 1000)
{
m_data.clear();
m_data.reserve(reserveSize);
for (int i=0; i<=m_outerSize; ++i)
m_outerIndex[i] = 0;
}
inline Scalar& fill(int row, int col)
{
const int outer = RowMajor ? row : col;
const int inner = RowMajor ? col : row;
if (m_outerIndex[outer+1]==0)
{
int i=col;
while (i>=0 && m_outerIndex[i]==0)
{
m_outerIndex[i] = m_data.size();
--i;
}
m_outerIndex[outer+1] = m_outerIndex[outer];
}
assert(m_outerIndex[outer+1] == m_data.size());
int id = m_outerIndex[outer+1];
m_outerIndex[outer+1]++;
m_data.append(0, inner);
return m_data.value(id);
}
inline void endFill()
{
int size = m_data.size();
int i = m_outerSize;
// find the last filled column
while (i>=0 && m_outerIndex[i]==0)
--i;
i++;
while (i<=m_outerSize)
{
m_outerIndex[i] = size;
++i;
}
}
void resize(int rows, int cols)
{
const int outerSize = RowMajor ? rows : cols;
m_innerSize = RowMajor ? cols : rows;
m_data.clear();
if (m_outerSize != outerSize)
{
delete[] m_outerIndex;
m_outerIndex = new int [outerSize+1];
m_outerSize = outerSize;
}
}
inline SparseMatrix(int rows, int cols)
: m_outerSize(0), m_innerSize(0), m_outerIndex(0)
{
resize(rows, cols);
}
template<typename OtherDerived>
inline SparseMatrix(const MatrixBase<OtherDerived>& other)
: m_outerSize(0), m_innerSize(0), m_outerIndex(0)
{
*this = other.derived();
}
inline void swap(SparseMatrix& other)
{
EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n");
std::swap(m_outerIndex, other.m_outerIndex);
std::swap(m_innerSize, other.m_innerSize);
std::swap(m_outerSize, other.m_outerSize);
m_data.swap(other.m_data);
}
inline SparseMatrix& operator=(const SparseMatrix& other)
{
if (other.isRValue())
{
swap(other.const_cast_derived());
}
else
{
resize(other.rows(), other.cols());
for (int j=0; j<=m_outerSize; ++j)
m_outerIndex[j] = other.m_outerIndex[j];
m_data = other.m_data;
return *this;
}
}
template<typename OtherDerived>
inline SparseMatrix& operator=(const MatrixBase<OtherDerived>& other)
{
return SparseMatrixBase<SparseMatrix>::operator=(other.derived());
}
friend std::ostream & operator << (std::ostream & s, const SparseMatrix& m)
{
EIGEN_DBG_SPARSE(
s << "Nonzero entries:\n";
for (uint i=0; i<m.nonZeros(); ++i)
{
s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
}
s << std::endl;
s << std::endl;
s << "Column pointers:\n";
for (uint i=0; i<m.cols(); ++i)
{
s << m.m_outerIndex[i] << " ";
}
s << std::endl;
s << std::endl;
);
s << static_cast<const SparseMatrixBase<SparseMatrix>&>(m);
return s;
}
/** Destructor */
inline ~SparseMatrix()
{
delete[] m_outerIndex;
}
};
template<typename Scalar, int _Flags>
class SparseMatrix<Scalar,_Flags>::InnerIterator
{
public:
InnerIterator(const SparseMatrix& mat, int outer)
: m_matrix(mat), m_id(mat.m_outerIndex[outer]), m_start(m_id), m_end(mat.m_outerIndex[outer+1])
{}
InnerIterator& operator++() { m_id++; return *this; }
Scalar value() { return m_matrix.m_data.value(m_id); }
int index() const { return m_matrix.m_data.index(m_id); }
operator bool() const { return (m_id < m_end) && (m_id>=m_start); }
protected:
const SparseMatrix& m_matrix;
int m_id;
const int m_start;
const int m_end;
};
#endif // EIGEN_SPARSEMATRIX_H
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