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296 lines
9.2 KiB
C++
296 lines
9.2 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) 2009 Thomas Capricelli <orzel@freehackers.org>
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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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#ifndef EIGEN_NONLINEAR_MATHFUNCTIONS_H
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#define EIGEN_NONLINEAR_MATHFUNCTIONS_H
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#include <cminpack.h>
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template<typename Functor, typename Scalar>
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int ei_hybrd1(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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Scalar tol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>())
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)
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{
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int lwa = (x.size()*(3*x.size()+13))/2;
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
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fvec.resize(x.size());
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return hybrd1(Functor::f, 0, x.size(), x.data(), fvec.data(), tol, wa.data(), lwa);
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}
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template<typename Functor, typename Scalar>
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int ei_hybrd(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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int &nfev,
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Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &fjac,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &R,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &qtf,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &diag,
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int mode=1,
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int nb_of_subdiagonals = -1,
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int nb_of_superdiagonals = -1,
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int maxfev = 2000,
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Scalar factor = Scalar(100.),
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Scalar xtol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>()),
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Scalar epsfcn = Scalar(0.),
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int nprint=0
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)
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{
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int n = x.size();
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int lr = (n*(n+1))/2;
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa1(n), wa2(n), wa3(n), wa4(n);
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if (nb_of_subdiagonals<0) nb_of_subdiagonals = n-1;
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if (nb_of_superdiagonals<0) nb_of_superdiagonals = n-1;
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fvec.resize(n);
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qtf.resize(n);
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R.resize(lr);
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int ldfjac = n;
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fjac.resize(ldfjac, n);
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return hybrd(
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Functor::f, 0,
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n, x.data(), fvec.data(),
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xtol, maxfev,
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nb_of_subdiagonals, nb_of_superdiagonals,
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epsfcn,
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diag.data(), mode,
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factor,
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nprint,
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&nfev,
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fjac.data(), ldfjac,
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R.data(), lr,
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qtf.data(),
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wa1.data(), wa2.data(), wa3.data(), wa4.data()
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);
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}
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template<typename Functor, typename Scalar>
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int ei_hybrj1(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &fjac,
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Scalar tol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>())
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)
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{
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int n = x.size();
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int lwa = (n*(3*n+13))/2;
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
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int ldfjac = n;
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fvec.resize(n);
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fjac.resize(ldfjac, n);
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return hybrj1(Functor::f, 0, n, x.data(), fvec.data(), fjac.data(), ldfjac, tol, wa.data(), lwa);
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}
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template<typename Functor, typename Scalar>
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int ei_hybrj(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &fjac,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &R,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &qtf,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &diag,
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int mode=1,
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int maxfev = 1000,
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Scalar factor = Scalar(100.),
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Scalar xtol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>()),
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int nprint=0
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)
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{
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int n = x.size();
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int lr = (n*(n+1))/2;
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa1(n), wa2(n), wa3(n), wa4(n);
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fvec.resize(n);
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qtf.resize(n);
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R.resize(lr);
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int ldfjac = n;
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fjac.resize(ldfjac, n);
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return hybrj (
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Functor::f, 0,
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n, x.data(), fvec.data(),
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fjac.data(), ldfjac,
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xtol, maxfev,
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diag.data(), mode,
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factor,
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nprint,
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&nfev,
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&njev,
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R.data(), lr,
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qtf.data(),
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wa1.data(), wa2.data(), wa3.data(), wa4.data()
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);
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}
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template<typename Functor, typename Scalar>
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int ei_lmder1(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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VectorXi &ipvt,
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Scalar tol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>())
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)
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{
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int lwa = 5*x.size()+fvec.size();
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int ldfjac = fvec.size();
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
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Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > fjac(ldfjac, x.size());
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ipvt.resize(x.size());
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return lmder1 (
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Functor::f, 0,
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fvec.size(), x.size(), x.data(), fvec.data(),
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fjac.data() , ldfjac,
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tol,
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ipvt.data(),
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wa.data(), lwa
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);
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}
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template<typename Functor, typename Scalar>
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int ei_lmder(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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int &nfev,
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int &njev,
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Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &fjac,
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VectorXi &ipvt,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &wa1,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &diag,
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int mode=1,
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double factor = 100.,
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int maxfev = 400,
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Scalar ftol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>()),
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Scalar xtol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>()),
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Scalar gtol = Scalar(0.),
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int nprint=0
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)
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{
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 >
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qtf(x.size()),
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wa2(x.size()), wa3(x.size()),
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wa4(fvec.size());
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int ldfjac = fvec.size();
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ipvt.resize(x.size());
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wa1.resize(x.size());
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fjac.resize(ldfjac, x.size());
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diag.resize(x.size());
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return lmder (
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Functor::f, 0,
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fvec.size(), x.size(), x.data(), fvec.data(),
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fjac.data() , ldfjac,
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ftol, xtol, gtol,
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maxfev,
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diag.data(), mode,
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factor,
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nprint,
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&nfev, &njev,
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ipvt.data(),
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qtf.data(),
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wa1.data(), wa2.data(), wa3.data(), wa4.data()
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);
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}
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template<typename Functor, typename Scalar>
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int ei_lmdif(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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int &nfev,
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Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &fjac,
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VectorXi &ipvt,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &wa1,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &diag,
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int mode=1,
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double factor = 100.,
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int maxfev = 400,
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Scalar ftol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>()),
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Scalar xtol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>()),
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Scalar gtol = Scalar(0.),
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Scalar epsfcn = Scalar(0.),
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int nprint=0
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)
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{
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 >
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qtf(x.size()),
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wa2(x.size()), wa3(x.size()),
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wa4(fvec.size());
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int ldfjac = fvec.size();
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ipvt.resize(x.size());
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wa1.resize(x.size());
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fjac.resize(ldfjac, x.size());
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diag.resize(x.size());
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return lmdif (
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Functor::f, 0,
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fvec.size(), x.size(), x.data(), fvec.data(),
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ftol, xtol, gtol,
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maxfev,
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epsfcn,
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diag.data(), mode,
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factor,
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nprint,
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&nfev,
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fjac.data() , ldfjac,
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ipvt.data(),
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qtf.data(),
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wa1.data(), wa2.data(), wa3.data(), wa4.data()
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);
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}
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template<typename Functor, typename Scalar>
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int ei_lmdif1(
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &x,
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &fvec,
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VectorXi &iwa,
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Scalar tol = Eigen::ei_sqrt(Eigen::machine_epsilon<Scalar>())
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)
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{
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int n = x.size();
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int ldfjac = fvec.size();
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int lwa = ldfjac*n+5*n+ldfjac;
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Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > wa(lwa);
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Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > fjac(ldfjac, n);
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iwa.resize(n);
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wa.resize(lwa);
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return lmdif1 (
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Functor::f, 0,
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fvec.size(), n, x.data(), fvec.data(),
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tol,
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iwa.data(),
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wa.data(), lwa
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);
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}
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#endif // EIGEN_NONLINEAR_MATHFUNCTIONS_H
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