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* * * License disclaimer changed to BSD license for MKL_support.h * * * Pardiso support fixed, test added. blas/lapack tests fixed: Scalar parameter was added in Cholesky, product_matrix_vector_triangular remaned to triangular_matrix_vector_product. * * * PARDISO test was added physically.
428 lines
13 KiB
C++
428 lines
13 KiB
C++
/*
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Copyright (c) 2011, Intel Corporation. All rights reserved.
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of Intel Corporation nor the names of its contributors may
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be used to endorse or promote products derived from this software without
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specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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********************************************************************************
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* Content : Eigen bindings to Intel(R) MKL PARDISO
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********************************************************************************
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*/
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#ifndef EIGEN_PARDISOSUPPORT_H
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#define EIGEN_PARDISOSUPPORT_H
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template<typename _MatrixType>
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class PardisoLU;
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template<typename _MatrixType>
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class PardisoLLT;
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template<typename _MatrixType>
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class PardisoLDLT;
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namespace internal
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{
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template<typename Index>
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struct pardiso_run_selector
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{
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static Index run(_MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a,
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Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x)
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{
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Index error = 0;
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::pardiso(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error);
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return error;
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}
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};
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template<>
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struct pardiso_run_selector<long long int>
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{
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typedef long long int Index;
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static Index run(_MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a,
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Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x)
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{
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Index error = 0;
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::pardiso_64(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error);
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return error;
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}
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};
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template<class Pardiso>
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struct pardiso_traits;
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template<typename _MatrixType>
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struct pardiso_traits< PardisoLU<_MatrixType> >
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{
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typedef _MatrixType MatrixType;
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typedef typename _MatrixType::Scalar Scalar;
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typedef typename _MatrixType::RealScalar RealScalar;
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typedef typename _MatrixType::Index Index;
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};
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template<typename _MatrixType>
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struct pardiso_traits< PardisoLLT<_MatrixType> >
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{
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typedef _MatrixType MatrixType;
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typedef typename _MatrixType::Scalar Scalar;
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typedef typename _MatrixType::RealScalar RealScalar;
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typedef typename _MatrixType::Index Index;
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};
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template<typename _MatrixType>
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struct pardiso_traits< PardisoLDLT<_MatrixType> >
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{
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typedef _MatrixType MatrixType;
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typedef typename _MatrixType::Scalar Scalar;
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typedef typename _MatrixType::RealScalar RealScalar;
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typedef typename _MatrixType::Index Index;
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};
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}
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template<class Derived>
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class PardisoImpl
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{
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public:
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typedef typename internal::pardiso_traits<Derived>::MatrixType MatrixType;
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typedef typename internal::pardiso_traits<Derived>::Scalar Scalar;
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typedef typename internal::pardiso_traits<Derived>::RealScalar RealScalar;
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typedef typename internal::pardiso_traits<Derived>::Index Index;
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typedef Matrix<Scalar,Dynamic,1> VectorType;
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typedef Matrix<Index, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
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typedef Matrix<Index, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
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enum {
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ScalarIsComplex = NumTraits<Scalar>::IsComplex
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};
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PardisoImpl(int flags) : m_flags(flags)
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{
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eigen_assert((sizeof(Index) >= sizeof(_INTEGER_t) && sizeof(Index) <= 8) && "Non-supported index type");
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memset(m_iparm, 0, sizeof(m_iparm));
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m_msglvl = 0; /* No output */
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m_initialized = false;
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}
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~PardisoImpl()
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{
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pardisoRelease();
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}
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inline Index cols() const { return m_matrix.cols(); }
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inline Index rows() const { return m_matrix.rows(); }
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/** \brief Reports whether previous computation was successful.
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*
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* \returns \c Success if computation was succesful,
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* \c NumericalIssue if the matrix.appears to be negative.
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*/
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ComputationInfo info() const
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{
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eigen_assert(m_initialized && "Decomposition is not initialized.");
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return m_info;
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}
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int orderingMethod() const
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{
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return m_flags&OrderingMask;
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}
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Derived& compute(const MatrixType& matrix);
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/** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
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*
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* \sa compute()
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*/
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template<typename Rhs>
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inline const internal::solve_retval<PardisoImpl, Rhs>
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solve(const MatrixBase<Rhs>& b, const int transposed = SvNoTrans) const
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{
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eigen_assert(m_initialized && "SimplicialCholesky is not initialized.");
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eigen_assert(rows()==b.rows()
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&& "PardisoImpl::solve(): invalid number of rows of the right hand side matrix b");
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return internal::solve_retval<PardisoImpl, Rhs>(*this, b.derived(), transposed);
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}
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Derived& derived()
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{
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return *static_cast<Derived*>(this);
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}
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const Derived& derived() const
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{
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return *static_cast<const Derived*>(this);
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}
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template<typename BDerived, typename XDerived>
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bool _solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>& x, const int transposed = SvNoTrans) const;
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protected:
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void pardisoRelease()
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{
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if(m_initialized) // Factorization ran at least once
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{
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internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, -1, m_matrix.rows(), NULL, NULL, NULL, m_perm.data(), 0,
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m_iparm, m_msglvl, NULL, NULL);
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memset(m_iparm, 0, sizeof(m_iparm));
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}
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}
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protected:
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// cached data to reduce reallocation, etc.
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ComputationInfo m_info;
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bool m_symmetric, m_initialized, m_succeeded;
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int m_flags;
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Index m_type, m_msglvl;
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mutable void *m_pt[64];
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mutable Index m_iparm[64];
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mutable SparseMatrix<Scalar, RowMajor> m_matrix;
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mutable IntColVectorType m_perm;
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};
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template<class Derived>
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Derived& PardisoImpl<Derived>::compute(const MatrixType& a)
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{
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Index n = a.rows(), i;
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eigen_assert(a.rows() == a.cols());
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pardisoRelease();
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memset(m_pt, 0, sizeof(m_pt));
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m_initialized = true;
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m_symmetric = abs(m_type) < 10;
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switch (orderingMethod())
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{
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case MinimumDegree_AT_PLUS_A : m_iparm[1] = 0; break;
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case NaturalOrdering : m_iparm[5] = 1; break;
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case Metis : m_iparm[1] = 3; break;
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default:
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//std::cerr << "Eigen: ordering method \"" << Base::orderingMethod() << "\" not supported by the PARDISO backend\n";
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m_iparm[1] = 0;
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};
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m_iparm[0] = 1; /* No solver default */
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/* Numbers of processors, value of OMP_NUM_THREADS */
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m_iparm[2] = 1;
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m_iparm[3] = 0; /* No iterative-direct algorithm */
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m_iparm[4] = 0; /* No user fill-in reducing permutation */
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m_iparm[5] = 0; /* Write solution into x */
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m_iparm[6] = 0; /* Not in use */
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m_iparm[7] = 2; /* Max numbers of iterative refinement steps */
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m_iparm[8] = 0; /* Not in use */
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m_iparm[9] = 13; /* Perturb the pivot elements with 1E-13 */
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m_iparm[10] = m_symmetric ? 0 : 1; /* Use nonsymmetric permutation and scaling MPS */
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m_iparm[11] = 0; /* Not in use */
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m_iparm[12] = m_symmetric ? 0 : 1; /* Maximum weighted matching algorithm is switched-off (default for symmetric). Try m_iparm[12] = 1 in case of inappropriate accuracy */
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m_iparm[13] = 0; /* Output: Number of perturbed pivots */
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m_iparm[14] = 0; /* Not in use */
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m_iparm[15] = 0; /* Not in use */
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m_iparm[16] = 0; /* Not in use */
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m_iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */
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m_iparm[18] = -1; /* Output: Mflops for LU factorization */
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m_iparm[19] = 0; /* Output: Numbers of CG Iterations */
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m_iparm[20] = 0; /* 1x1 pivoting */
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m_iparm[26] = 0; /* No matrix checker */
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m_iparm[27] = (sizeof(RealScalar) == 4) ? 1 : 0;
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m_iparm[34] = 0; /* Fortran indexing */
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m_iparm[59] = 1; /* Automatic switch between In-Core and Out-of-Core modes */
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m_perm.resize(n);
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if(orderingMethod() == NaturalOrdering)
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{
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for(Index i = 0; i < n; i++)
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m_perm[i] = i;
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}
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m_matrix = a;
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/* Convert to Fortran-style indexing */
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for(i = 0; i <= m_matrix.rows(); ++i)
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++m_matrix._outerIndexPtr()[i];
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for(i = 0; i < m_matrix.nonZeros(); ++i)
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++m_matrix._innerIndexPtr()[i];
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Index error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 12, n,
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m_matrix._valuePtr(), m_matrix._outerIndexPtr(), m_matrix._innerIndexPtr(),
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m_perm.data(), 0, m_iparm, m_msglvl, NULL, NULL);
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switch(error)
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{
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case 0:
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m_succeeded = true;
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m_info = Success;
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return derived();
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case -4:
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case -7:
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m_info = NumericalIssue;
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break;
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default:
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m_info = InvalidInput;
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}
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m_succeeded = false;
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return derived();
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}
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template<class Base>
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template<typename BDerived,typename XDerived>
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bool PardisoImpl<Base>::_solve(const MatrixBase<BDerived> &b,
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MatrixBase<XDerived>& x, const int transposed) const
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{
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if(m_iparm[0] == 0) // Factorization was not computed
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return false;
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Index n = m_matrix.rows();
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Index nrhs = b.cols();
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eigen_assert(n==b.rows());
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eigen_assert(((MatrixBase<BDerived>::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major right hand sides are not supported");
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eigen_assert(((MatrixBase<XDerived>::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major matrices of unknowns are not supported");
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eigen_assert(((nrhs == 1) || b.outerStride() == b.rows()));
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x.derived().resizeLike(b);
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switch (transposed) {
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case SvNoTrans : m_iparm[11] = 0 ; break;
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case SvTranspose : m_iparm[11] = 2 ; break;
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case SvAdjoint : m_iparm[11] = 1 ; break;
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default:
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//std::cerr << "Eigen: transposition option \"" << transposed << "\" not supported by the PARDISO backend\n";
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m_iparm[11] = 0;
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}
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Index error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 33, n,
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m_matrix._valuePtr(), m_matrix._outerIndexPtr(), m_matrix._innerIndexPtr(),
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m_perm.data(), nrhs, m_iparm, m_msglvl, const_cast<Scalar*>(&b(0, 0)), &x(0, 0));
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return error==0;
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}
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template<typename MatrixType>
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class PardisoLU : public PardisoImpl< PardisoLU<MatrixType> >
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{
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protected:
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typedef PardisoImpl< PardisoLU<MatrixType> > Base;
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typedef typename Base::Scalar Scalar;
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typedef typename Base::RealScalar RealScalar;
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using Base::m_type;
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public:
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using Base::compute;
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using Base::solve;
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PardisoLU(int flags = Metis)
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: Base(flags)
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{
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m_type = Base::ScalarIsComplex ? 13 : 11;
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}
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PardisoLU(const MatrixType& matrix, int flags = Metis)
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: Base(flags)
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{
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m_type = Base::ScalarIsComplex ? 13 : 11;
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compute(matrix);
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}
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};
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template<typename MatrixType>
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class PardisoLLT : public PardisoImpl< PardisoLLT<MatrixType> >
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{
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protected:
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typedef PardisoImpl< PardisoLLT<MatrixType> > Base;
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typedef typename Base::Scalar Scalar;
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typedef typename Base::RealScalar RealScalar;
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using Base::m_type;
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public:
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using Base::compute;
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using Base::solve;
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PardisoLLT(int flags = Metis)
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: Base(flags)
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{
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m_type = Base::ScalarIsComplex ? 4 : 2;
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}
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PardisoLLT(const MatrixType& matrix, int flags = Metis)
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: Base(flags)
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{
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m_type = Base::ScalarIsComplex ? 4 : 2;
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compute(matrix);
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}
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};
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template<typename MatrixType>
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class PardisoLDLT : public PardisoImpl< PardisoLDLT<MatrixType> >
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{
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protected:
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typedef PardisoImpl< PardisoLDLT<MatrixType> > Base;
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typedef typename Base::Scalar Scalar;
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typedef typename Base::RealScalar RealScalar;
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using Base::m_type;
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public:
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using Base::compute;
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using Base::solve;
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PardisoLDLT(int flags = Metis)
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: Base(flags)
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{
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m_type = Base::ScalarIsComplex ? -4 : -2;
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}
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PardisoLDLT(const MatrixType& matrix, int flags = Metis, bool hermitian = true)
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: Base(flags)
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{
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compute(matrix, hermitian);
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}
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void compute(const MatrixType& matrix, bool hermitian = true)
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{
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m_type = Base::ScalarIsComplex ? (hermitian ? -4 : 6) : -2;
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Base::compute(matrix);
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}
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};
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namespace internal {
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template<typename _Derived, typename Rhs>
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struct solve_retval<PardisoImpl<_Derived>, Rhs>
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: solve_retval_base<PardisoImpl<_Derived>, Rhs>
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{
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typedef PardisoImpl<_Derived> Dec;
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EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
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solve_retval(const PardisoImpl<_Derived>& dec, const Rhs& rhs, const int transposed)
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: Base(dec, rhs), m_transposed(transposed) {}
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template<typename Dest> void evalTo(Dest& dst) const
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{
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dec()._solve(rhs(),dst,m_transposed);
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}
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int m_transposed;
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};
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}
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#endif // EIGEN_PARDISOSUPPORT_H
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