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105 lines
3.3 KiB
C++
105 lines
3.3 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2010-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "common.h"
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#include <Eigen/LU>
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// computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
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EIGEN_LAPACK_FUNC(getrf,(int *m, int *n, RealScalar *pa, int *lda, int *ipiv, int *info))
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{
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*info = 0;
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if(*m<0) *info = -1;
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else if(*n<0) *info = -2;
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else if(*lda<std::max(1,*m)) *info = -4;
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if(*info!=0)
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{
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int e = -*info;
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return xerbla_(SCALAR_SUFFIX_UP"GETRF", &e, 6);
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}
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if(*m==0 || *n==0)
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return 0;
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Scalar* a = reinterpret_cast<Scalar*>(pa);
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int nb_transpositions;
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int ret = Eigen::internal::partial_lu_impl<Scalar,ColMajor,int>
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::blocked_lu(*m, *n, a, *lda, ipiv, nb_transpositions);
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for(int i=0; i<std::min(*m,*n); ++i)
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ipiv[i]++;
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if(ret>=0)
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*info = ret+1;
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return 0;
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}
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//GETRS solves a system of linear equations
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// A * X = B or A' * X = B
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// with a general N-by-N matrix A using the LU factorization computed by GETRF
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EIGEN_LAPACK_FUNC(getrs,(char *trans, int *n, int *nrhs, RealScalar *pa, int *lda, int *ipiv, RealScalar *pb, int *ldb, int *info))
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{
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*info = 0;
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if(OP(*trans)==INVALID) *info = -1;
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else if(*n<0) *info = -2;
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else if(*nrhs<0) *info = -3;
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else if(*lda<std::max(1,*n)) *info = -5;
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else if(*ldb<std::max(1,*n)) *info = -8;
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if(*info!=0)
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{
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int e = -*info;
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return xerbla_(SCALAR_SUFFIX_UP"GETRS", &e, 6);
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}
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Scalar* a = reinterpret_cast<Scalar*>(pa);
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Scalar* b = reinterpret_cast<Scalar*>(pb);
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MatrixType lu(a,*n,*n,*lda);
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MatrixType B(b,*n,*nrhs,*ldb);
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for(int i=0; i<*n; ++i)
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ipiv[i]--;
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if(OP(*trans)==NOTR)
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{
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B = PivotsType(ipiv,*n) * B;
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lu.triangularView<UnitLower>().solveInPlace(B);
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lu.triangularView<Upper>().solveInPlace(B);
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}
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else if(OP(*trans)==TR)
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{
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lu.triangularView<Upper>().transpose().solveInPlace(B);
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lu.triangularView<UnitLower>().transpose().solveInPlace(B);
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B = PivotsType(ipiv,*n).transpose() * B;
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}
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else if(OP(*trans)==ADJ)
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{
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lu.triangularView<Upper>().adjoint().solveInPlace(B);
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lu.triangularView<UnitLower>().adjoint().solveInPlace(B);
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B = PivotsType(ipiv,*n).transpose() * B;
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}
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for(int i=0; i<*n; ++i)
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ipiv[i]++;
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return 0;
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}
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