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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_CHOLMODSUPPORT_H
#define EIGEN_CHOLMODSUPPORT_H
template<typename Scalar, int Flags>
cholmod_sparse SparseMatrix<Scalar,Flags>::asCholmodMatrix()
{
cholmod_sparse res;
res.nzmax = nonZeros();
res.nrow = rows();;
res.ncol = cols();
res.p = _outerIndexPtr();
res.i = _innerIndexPtr();
res.x = _valuePtr();
res.xtype = CHOLMOD_REAL;
res.itype = CHOLMOD_INT;
res.sorted = 1;
res.packed = 1;
res.dtype = 0;
res.stype = -1;
if (ei_is_same_type<Scalar,float>::ret)
{
res.xtype = CHOLMOD_REAL;
res.dtype = 1;
}
else if (ei_is_same_type<Scalar,double>::ret)
{
res.xtype = CHOLMOD_REAL;
res.dtype = 0;
}
else if (ei_is_same_type<Scalar,std::complex<float> >::ret)
{
res.xtype = CHOLMOD_COMPLEX;
res.dtype = 1;
}
else if (ei_is_same_type<Scalar,std::complex<double> >::ret)
{
res.xtype = CHOLMOD_COMPLEX;
res.dtype = 0;
}
else
{
ei_assert(false && "Scalar type not supported by CHOLMOD");
}
if (Flags & SelfAdjoint)
{
if (Flags & Upper)
res.stype = 1;
else if (Flags & Lower)
res.stype = -1;
else
res.stype = 0;
}
else
res.stype = 0;
return res;
}
template<typename Scalar, int Flags>
SparseMatrix<Scalar,Flags> SparseMatrix<Scalar,Flags>::Map(cholmod_sparse& cm)
{
SparseMatrix res;
res.m_innerSize = cm.nrow;
res.m_outerSize = cm.ncol;
res.m_outerIndex = reinterpret_cast<int*>(cm.p);
SparseArray<Scalar> data = SparseArray<Scalar>::Map(
reinterpret_cast<int*>(cm.i),
reinterpret_cast<Scalar*>(cm.x),
res.m_outerIndex[cm.ncol]);
res.m_data.swap(data);
res.markAsRValue();
return res;
}
template<typename MatrixType>
class SparseLLT<MatrixType,Cholmod> : public SparseLLT<MatrixType>
{
protected:
typedef SparseLLT<MatrixType> Base;
using Base::Scalar;
using Base::RealScalar;
using Base::MatrixLIsDirty;
using Base::SupernodalFactorIsDirty;
using Base::m_flags;
using Base::m_matrix;
using Base::m_status;
public:
SparseLLT(int flags = 0)
: Base(flags), m_cholmodFactor(0)
{
cholmod_start(&m_cholmod);
}
SparseLLT(const MatrixType& matrix, int flags = 0)
: Base(flags), m_cholmodFactor(0)
{
cholmod_start(&m_cholmod);
compute(matrix);
}
~SparseLLT()
{
if (m_cholmodFactor)
cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
cholmod_finish(&m_cholmod);
}
inline const typename Base::CholMatrixType& matrixL(void) const;
template<typename Derived>
void solveInPlace(MatrixBase<Derived> &b) const;
void compute(const MatrixType& matrix);
protected:
mutable cholmod_common m_cholmod;
cholmod_factor* m_cholmodFactor;
};
template<typename MatrixType>
void SparseLLT<MatrixType,Cholmod>::compute(const MatrixType& a)
{
if (m_cholmodFactor)
{
cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
m_cholmodFactor = 0;
}
cholmod_sparse A = const_cast<MatrixType&>(a).asCholmodMatrix();
// TODO
if (m_flags&IncompleteFactorization)
{
m_cholmod.nmethods = 1;
m_cholmod.method [0].ordering = CHOLMOD_NATURAL;
m_cholmod.postorder = 0;
}
else
{
m_cholmod.nmethods = 1;
m_cholmod.method[0].ordering = CHOLMOD_NATURAL;
m_cholmod.postorder = 0;
}
m_cholmod.final_ll = 1;
m_cholmodFactor = cholmod_analyze(&A, &m_cholmod);
cholmod_factorize(&A, m_cholmodFactor, &m_cholmod);
m_status = (m_status & ~SupernodalFactorIsDirty) | MatrixLIsDirty;
}
template<typename MatrixType>
inline const typename SparseLLT<MatrixType>::CholMatrixType&
SparseLLT<MatrixType,Cholmod>::matrixL() const
{
if (m_status & MatrixLIsDirty)
{
ei_assert(!(m_status & SupernodalFactorIsDirty));
cholmod_sparse* cmRes = cholmod_factor_to_sparse(m_cholmodFactor, &m_cholmod);
const_cast<typename Base::CholMatrixType&>(m_matrix) = Base::CholMatrixType::Map(*cmRes);
free(cmRes);
m_status = (m_status & ~MatrixLIsDirty);
}
return m_matrix;
}
template<typename MatrixType>
template<typename Derived>
void SparseLLT<MatrixType,Cholmod>::solveInPlace(MatrixBase<Derived> &b) const
{
if (m_status & MatrixLIsDirty)
matrixL();
const int size = m_matrix.rows();
ei_assert(size==b.rows());
Base::solveInPlace(b);
}
#endif // EIGEN_CHOLMODSUPPORT_H
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