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https://github.com/OPM/opm-simulators.git
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111 lines
3.2 KiB
C++
111 lines
3.2 KiB
C++
/*===========================================================================
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//
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// File: find_zero.cpp
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//
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// Created: 2013-04-29 11:58:29+0200
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//
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// Authors: Knut-Andreas Lie <Knut-Andreas.Lie@sintef.no>
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// Halvor M. Nilsen <HalvorMoll.Nilsen@sintef.no>
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// Atgeirr F. Rasmussen <atgeirr@sintef.no>
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// Xavier Raynaud <Xavier.Raynaud@sintef.no>
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// Bård Skaflestad <Bard.Skaflestad@sintef.no>
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//
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//==========================================================================*/
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/*
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Copyright 2013 SINTEF ICT, Applied Mathematics.
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Copyright 2013 Statoil ASA.
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This file is part of the Open Porous Media Project (OPM).
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OPM is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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OPM is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with OPM. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include <config.h>
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#include <opm/autodiff/AutoDiff.hpp>
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#include <iostream>
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#include <cmath>
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struct Func
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{
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template <typename T>
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T operator()(T x) const
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{
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#if 1
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T r = std::sqrt(std::cos(x * x) + x) - 1.2;
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return r;
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#else
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return x;
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// const int n = 6;
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// double xv[6] = { 0.0, 0.2, 0.4, 0.6, 0.8, 1.0 };
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// double yv[6] = { -0.5, -0.3, -0.1, 0.1, 0.3, 0.5 };
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// int interv = -1;
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// for (int i = 0; i < n; ++i) {
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// if (x < xv[i]) {
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// interv = i - 1;
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// break;
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// }
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// }
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// T t = (x - xv[interv])/(xv[interv+1] - xv[interv]);
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// return (1.0 - t)*yv[interv] + t*yv[interv+1];
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#endif
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}
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};
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// template <class ErrorPolicy = ThrowOnError>
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class Newton
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{
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public:
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/// Implements a scalar Newton solve.
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template <class Functor>
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inline static double solve(const Functor& f,
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const double initial_guess,
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const int max_iter,
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const double tolerance,
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int& iterations_used)
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{
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double x = initial_guess;
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iterations_used = 0;
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typedef Opm::AutoDiff<double> AD;
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while (std::abs(f(x)) > tolerance && ++iterations_used < max_iter) {
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AD xfad = AD::variable(x);
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AD rfad = f(xfad);
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x = x - rfad.val()/rfad.der();
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}
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return x;
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}
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};
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int main()
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try
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{
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int iter = 0;
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const double atol = 1.0e-13;
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const double soln = Newton::solve(Func(), 0.1, 30, atol, iter);
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std::cout.precision(16);
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std::cout << "Solution is: " << soln
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<< " using " << iter << " iterations." << '\n';
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std::cout << " f(x) = " << Func()(soln) << '\n';
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}
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catch (const std::exception &e) {
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std::cerr << "Program threw an exception: " << e.what() << "\n";
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throw;
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}
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