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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2010-2011 Gael Guennebaud <gael.guennebaud@inria.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/>.
#include "common.h"
#include <Eigen/LU>
// computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
EIGEN_LAPACK_FUNC(getrf,(int *m, int *n, RealScalar *pa, int *lda, int *ipiv, int *info))
{
*info = 0;
if(*m<0) *info = -1;
else if(*n<0) *info = -2;
else if(*lda<std::max(1,*m)) *info = -4;
if(*info!=0)
{
int e = -*info;
return xerbla_(SCALAR_SUFFIX_UP"GETRF", &e, 6);
}
if(*m==0 || *n==0)
return 0;
Scalar* a = reinterpret_cast<Scalar*>(pa);
int nb_transpositions;
int ret = Eigen::internal::partial_lu_impl<Scalar,ColMajor,int>
::blocked_lu(*m, *n, a, *lda, ipiv, nb_transpositions);
for(int i=0; i<std::min(*m,*n); ++i)
ipiv[i]++;
if(ret>=0)
*info = ret+1;
return 0;
}
//GETRS solves a system of linear equations
// A * X = B or A' * X = B
// with a general N-by-N matrix A using the LU factorization computed by GETRF
EIGEN_LAPACK_FUNC(getrs,(char *trans, int *n, int *nrhs, RealScalar *pa, int *lda, int *ipiv, RealScalar *pb, int *ldb, int *info))
{
*info = 0;
if(OP(*trans)==INVALID) *info = -1;
else if(*n<0) *info = -2;
else if(*nrhs<0) *info = -3;
else if(*lda<std::max(1,*n)) *info = -5;
else if(*ldb<std::max(1,*n)) *info = -8;
if(*info!=0)
{
int e = -*info;
return xerbla_(SCALAR_SUFFIX_UP"GETRS", &e, 6);
}
Scalar* a = reinterpret_cast<Scalar*>(pa);
Scalar* b = reinterpret_cast<Scalar*>(pb);
MatrixType lu(a,*n,*n,*lda);
MatrixType B(b,*n,*nrhs,*ldb);
for(int i=0; i<*n; ++i)
ipiv[i]--;
if(OP(*trans)==NOTR)
{
B = PivotsType(ipiv,*n) * B;
lu.triangularView<UnitLower>().solveInPlace(B);
lu.triangularView<Upper>().solveInPlace(B);
}
else if(OP(*trans)==TR)
{
lu.triangularView<Upper>().transpose().solveInPlace(B);
lu.triangularView<UnitLower>().transpose().solveInPlace(B);
B = PivotsType(ipiv,*n).transpose() * B;
}
else if(OP(*trans)==ADJ)
{
lu.triangularView<Upper>().adjoint().solveInPlace(B);
lu.triangularView<UnitLower>().adjoint().solveInPlace(B);
B = PivotsType(ipiv,*n).transpose() * B;
}
for(int i=0; i<*n; ++i)
ipiv[i]++;
return 0;
}
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