// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2009 Gael Guennebaud // // 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 . #ifndef EIGEN_TAUCSSUPPORT_H #define EIGEN_TAUCSSUPPORT_H template taucs_ccs_matrix SparseMatrixBase::asTaucsMatrix() { taucs_ccs_matrix res; res.n = cols(); res.m = rows(); res.flags = 0; res.colptr = derived()._outerIndexPtr(); res.rowind = derived()._innerIndexPtr(); res.values.v = derived()._valuePtr(); if (ei_is_same_type::ret) res.flags |= TAUCS_INT; else if (ei_is_same_type::ret) res.flags |= TAUCS_SINGLE; else if (ei_is_same_type::ret) res.flags |= TAUCS_DOUBLE; else if (ei_is_same_type >::ret) res.flags |= TAUCS_SCOMPLEX; else if (ei_is_same_type >::ret) res.flags |= TAUCS_DCOMPLEX; else { ei_assert(false && "Scalar type not supported by TAUCS"); } if (Flags & Upper) res.flags |= TAUCS_UPPER; if (Flags & Lower) res.flags |= TAUCS_LOWER; if (Flags & SelfAdjoint) res.flags |= (NumTraits::IsComplex ? TAUCS_HERMITIAN : TAUCS_SYMMETRIC); else if ((Flags & Upper) || (Flags & Lower)) res.flags |= TAUCS_TRIANGULAR; return res; } template MappedSparseMatrix::MappedSparseMatrix(taucs_ccs_matrix& taucsMat) { m_innerSize = taucsMat.m; m_outerSize = taucsMat.n; m_outerIndex = taucsMat.colptr; m_innerIndices = taucsMat.rowind; m_values = reinterpret_cast(taucsMat.values.v); m_nnz = taucsMat.colptr[taucsMat.n]; } template class SparseLLT : public SparseLLT { protected: typedef SparseLLT Base; typedef typename Base::Scalar Scalar; typedef typename Base::RealScalar 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_taucsSupernodalFactor(0) { } SparseLLT(const MatrixType& matrix, int flags = 0) : Base(flags), m_taucsSupernodalFactor(0) { compute(matrix); } ~SparseLLT() { if (m_taucsSupernodalFactor) taucs_supernodal_factor_free(m_taucsSupernodalFactor); } inline const typename Base::CholMatrixType& matrixL(void) const; template void solveInPlace(MatrixBase &b) const; void compute(const MatrixType& matrix); protected: void* m_taucsSupernodalFactor; }; template void SparseLLT::compute(const MatrixType& a) { if (m_taucsSupernodalFactor) { taucs_supernodal_factor_free(m_taucsSupernodalFactor); m_taucsSupernodalFactor = 0; } if (m_flags & IncompleteFactorization) { taucs_ccs_matrix taucsMatA = const_cast(a).asTaucsMatrix(); taucs_ccs_matrix* taucsRes = taucs_ccs_factor_llt(&taucsMatA, Base::m_precision, 0); // the matrix returned by Taucs is not necessarily sorted, // so let's copy it in two steps DynamicSparseMatrix tmp = MappedSparseMatrix(*taucsRes); m_matrix = tmp; free(taucsRes); m_status = (m_status & ~(CompleteFactorization|MatrixLIsDirty)) | IncompleteFactorization | SupernodalFactorIsDirty; } else { taucs_ccs_matrix taucsMatA = const_cast(a).asTaucsMatrix(); if ( (m_flags & SupernodalLeftLooking) || ((!(m_flags & SupernodalMultifrontal)) && (m_flags & MemoryEfficient)) ) { m_taucsSupernodalFactor = taucs_ccs_factor_llt_ll(&taucsMatA); } else { // use the faster Multifrontal routine m_taucsSupernodalFactor = taucs_ccs_factor_llt_mf(&taucsMatA); } m_status = (m_status & ~IncompleteFactorization) | CompleteFactorization | MatrixLIsDirty; } } template inline const typename SparseLLT::CholMatrixType& SparseLLT::matrixL() const { if (m_status & MatrixLIsDirty) { ei_assert(!(m_status & SupernodalFactorIsDirty)); taucs_ccs_matrix* taucsL = taucs_supernodal_factor_to_ccs(m_taucsSupernodalFactor); // the matrix returned by Taucs is not necessarily sorted, // so let's copy it in two steps DynamicSparseMatrix tmp = MappedSparseMatrix(*taucsL); const_cast(m_matrix) = tmp; free(taucsL); m_status = (m_status & ~MatrixLIsDirty); } return m_matrix; } template template void SparseLLT::solveInPlace(MatrixBase &b) const { bool inputIsCompatibleWithTaucs = (Derived::Flags&RowMajorBit)==0; if (!inputIsCompatibleWithTaucs) { matrixL(); Base::solveInPlace(b); } else if (m_flags & IncompleteFactorization) { taucs_ccs_matrix taucsLLT = const_cast(m_matrix).asTaucsMatrix(); typename ei_plain_matrix_type::type x(b.rows()); for (int j=0; j::type x(b.rows()); for (int j=0; j