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-rw-r--r--Eigen/src/Sparse/CholmodSupport.h246
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diff --git a/Eigen/src/Sparse/CholmodSupport.h b/Eigen/src/Sparse/CholmodSupport.h
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-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2009 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, typename CholmodType>
-void ei_cholmod_configure_matrix(CholmodType& mat)
-{
- if (ei_is_same_type<Scalar,float>::ret)
- {
- mat.xtype = CHOLMOD_REAL;
- mat.dtype = CHOLMOD_SINGLE;
- }
- else if (ei_is_same_type<Scalar,double>::ret)
- {
- mat.xtype = CHOLMOD_REAL;
- mat.dtype = CHOLMOD_DOUBLE;
- }
- else if (ei_is_same_type<Scalar,std::complex<float> >::ret)
- {
- mat.xtype = CHOLMOD_COMPLEX;
- mat.dtype = CHOLMOD_SINGLE;
- }
- else if (ei_is_same_type<Scalar,std::complex<double> >::ret)
- {
- mat.xtype = CHOLMOD_COMPLEX;
- mat.dtype = CHOLMOD_DOUBLE;
- }
- else
- {
- ei_assert(false && "Scalar type not supported by CHOLMOD");
- }
-}
-
-template<typename Derived>
-cholmod_sparse SparseMatrixBase<Derived>::asCholmodMatrix()
-{
- typedef typename Derived::Scalar Scalar;
- cholmod_sparse res;
- res.nzmax = nonZeros();
- res.nrow = rows();;
- res.ncol = cols();
- res.p = derived()._outerIndexPtr();
- res.i = derived()._innerIndexPtr();
- res.x = derived()._valuePtr();
- res.xtype = CHOLMOD_REAL;
- res.itype = CHOLMOD_INT;
- res.sorted = 1;
- res.packed = 1;
- res.dtype = 0;
- res.stype = -1;
-
- ei_cholmod_configure_matrix<Scalar>(res);
-
-
- if (Derived::Flags & SelfAdjoint)
- {
- if (Derived::Flags & Upper)
- res.stype = 1;
- else if (Derived::Flags & Lower)
- res.stype = -1;
- else
- res.stype = 0;
- }
- else
- res.stype = -1; // by default we consider the lower part
-
- return res;
-}
-
-template<typename Derived>
-cholmod_dense ei_cholmod_map_eigen_to_dense(MatrixBase<Derived>& mat)
-{
- EIGEN_STATIC_ASSERT((ei_traits<Derived>::Flags&RowMajorBit)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
- typedef typename Derived::Scalar Scalar;
-
- cholmod_dense res;
- res.nrow = mat.rows();
- res.ncol = mat.cols();
- res.nzmax = res.nrow * res.ncol;
- res.d = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride();
- res.x = mat.derived().data();
- res.z = 0;
-
- ei_cholmod_configure_matrix<Scalar>(res);
-
- return res;
-}
-
-template<typename Scalar, int Flags, typename _Index>
-MappedSparseMatrix<Scalar,Flags,_Index>::MappedSparseMatrix(cholmod_sparse& cm)
-{
- m_innerSize = cm.nrow;
- m_outerSize = cm.ncol;
- m_outerIndex = reinterpret_cast<Index*>(cm.p);
- m_innerIndices = reinterpret_cast<Index*>(cm.i);
- m_values = reinterpret_cast<Scalar*>(cm.x);
- m_nnz = m_outerIndex[cm.ncol];
-}
-
-template<typename MatrixType>
-class SparseLLT<MatrixType,Cholmod> : public SparseLLT<MatrixType>
-{
- protected:
- typedef SparseLLT<MatrixType> Base;
- typedef typename Base::Scalar Scalar;
- typedef typename Base::RealScalar RealScalar;
- typedef typename Base::CholMatrixType CholMatrixType;
- typedef typename MatrixType::Index Index;
- 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 CholMatrixType& matrixL() const;
-
- template<typename Derived>
- bool 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();
-// m_cholmod.supernodal = CHOLMOD_AUTO;
- // 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,Cholmod>::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) = MappedSparseMatrix<Scalar>(*cmRes);
- free(cmRes);
-
- m_status = (m_status & ~MatrixLIsDirty);
- }
- return m_matrix;
-}
-
-template<typename MatrixType>
-template<typename Derived>
-bool SparseLLT<MatrixType,Cholmod>::solveInPlace(MatrixBase<Derived> &b) const
-{
- const Index size = m_cholmodFactor->n;
- ei_assert(size==b.rows());
-
- // this uses Eigen's triangular sparse solver
-// if (m_status & MatrixLIsDirty)
-// matrixL();
-// Base::solveInPlace(b);
- // as long as our own triangular sparse solver is not fully optimal,
- // let's use CHOLMOD's one:
- cholmod_dense cdb = ei_cholmod_map_eigen_to_dense(b);
- //cholmod_dense* x = cholmod_solve(CHOLMOD_LDLt, m_cholmodFactor, &cdb, &m_cholmod);
- cholmod_dense* x = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &cdb, &m_cholmod);
- if(!x)
- {
- //std::cerr << "Eigen: cholmod_solve failed\n";
- return false;
- }
- b = Matrix<typename Base::Scalar,Dynamic,1>::Map(reinterpret_cast<typename Base::Scalar*>(x->x),b.rows());
- cholmod_free_dense(&x, &m_cholmod);
- return true;
-}
-
-#endif // EIGEN_CHOLMODSUPPORT_H
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