mirror of
https://github.com/OPM/opm-simulators.git
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233 lines
8.2 KiB
C++
233 lines
8.2 KiB
C++
/*
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Copyright 2013 SINTEF ICT, Applied Mathematics.
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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 "AutoDiffBlock.hpp"
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#include <opm/core/grid.h>
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#include <opm/core/grid/GridManager.hpp>
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#include <opm/core/props/IncompPropertiesBasic.hpp>
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#include <opm/core/utility/Units.hpp>
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#include <opm/core/utility/StopWatch.hpp>
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#include <opm/core/pressure/tpfa/trans_tpfa.h>
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#include <Eigen/UmfPackSupport>
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#include <iostream>
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/*
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Equations for incompressible two-phase flow.
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Using s and p as variables:
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PV (s_i - s0_i) / dt + sum_{j \in U(i)} f(s_j) v_{ij} + sum_{j in D(i) f(s_i) v_{ij} = qw_i
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where
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v_{ij} = totmob_ij T_ij (p_i - p_j)
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Pressure equation:
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sum_{j \in N(i)} totmob_ij T_ij (p_i - p_j) = q_i
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*/
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/// Contains vectors and sparse matrices that represent subsets or
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/// operations on (AD or regular) vectors of data.
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struct HelperOps
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{
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typedef AutoDiff::ForwardBlock<double>::M M;
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typedef AutoDiff::ForwardBlock<double>::V V;
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/// A list of internal faces.
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Eigen::Array<int, Eigen::Dynamic, 1> internal_faces;
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/// Extract for each face the difference of its adjacent cells'values.
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M ngrad;
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/// Extract for each face the average of its adjacent cells' values.
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M caver;
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/// Extract for each cell the sum of its adjacent faces' (signed) values.
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M div;
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/// Constructs all helper vectors and matrices.
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HelperOps(const UnstructuredGrid& grid)
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{
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const int nc = grid.number_of_cells;
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const int nf = grid.number_of_faces;
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// Define some neighbourhood-derived helper arrays.
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typedef Eigen::Array<int, Eigen::Dynamic, 1> OneColInt;
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typedef Eigen::Array<bool, Eigen::Dynamic, 1> OneColBool;
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typedef Eigen::Array<int, Eigen::Dynamic, 2, Eigen::RowMajor> TwoColInt;
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typedef Eigen::Array<bool, Eigen::Dynamic, 2, Eigen::RowMajor> TwoColBool;
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TwoColInt nb = Eigen::Map<TwoColInt>(grid.face_cells, nf, 2);
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// std::cout << "nb = \n" << nb << std::endl;
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TwoColBool nbib = nb >= 0;
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OneColBool ifaces = nbib.rowwise().all();
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const int num_internal = ifaces.cast<int>().sum();
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// std::cout << num_internal << " internal faces." << std::endl;
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TwoColInt nbi(num_internal, 2);
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internal_faces.resize(num_internal);
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int fi = 0;
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for (int f = 0; f < nf; ++f) {
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if (ifaces[f]) {
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internal_faces[fi] = f;
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nbi.row(fi) = nb.row(f);
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++fi;
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}
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}
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// std::cout << "nbi = \n" << nbi << std::endl;
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// Create matrices.
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ngrad.resize(num_internal, nc);
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caver.resize(num_internal, nc);
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typedef Eigen::Triplet<double> Tri;
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std::vector<Tri> ngrad_tri;
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std::vector<Tri> caver_tri;
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ngrad_tri.reserve(2*num_internal);
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caver_tri.reserve(2*num_internal);
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for (int i = 0; i < num_internal; ++i) {
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ngrad_tri.emplace_back(i, nbi(i,0), 1.0);
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ngrad_tri.emplace_back(i, nbi(i,1), -1.0);
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caver_tri.emplace_back(i, nbi(i,0), 0.5);
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caver_tri.emplace_back(i, nbi(i,1), 0.5);
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}
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ngrad.setFromTriplets(ngrad_tri.begin(), ngrad_tri.end());
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caver.setFromTriplets(caver_tri.begin(), caver_tri.end());
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div = ngrad.transpose();
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}
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};
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int main()
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{
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typedef AutoDiff::ForwardBlock<double> ADB;
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typedef ADB::V V;
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typedef ADB::M M;
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Opm::time::StopWatch clock;
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clock.start();
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Opm::GridManager gm(50, 50, 10);
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const UnstructuredGrid& grid = *gm.c_grid();
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using namespace Opm::unit;
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using namespace Opm::prefix;
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Opm::IncompPropertiesBasic props(2, Opm::SaturationPropsBasic::Quadratic,
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{ 1000.0, 800.0 },
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{ 1.0*centi*Poise, 5.0*centi*Poise },
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0.2, 100*milli*darcy,
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grid.dimensions, grid.number_of_cells);
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std::vector<double> htrans(grid.cell_facepos[grid.number_of_cells]);
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tpfa_htrans_compute((UnstructuredGrid*)&grid, props.permeability(), htrans.data());
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// std::vector<double> trans(grid.number_of_faces);
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V trans_all(grid.number_of_faces);
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tpfa_trans_compute((UnstructuredGrid*)&grid, htrans.data(), trans_all.data());
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const int nc = grid.number_of_cells;
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std::vector<int> allcells(nc);
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for (int i = 0; i < nc; ++i) {
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allcells[i] = i;
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}
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std::cerr << "Opm core " << clock.secsSinceLast() << std::endl;
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// Define neighbourhood-derived operator matrices.
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HelperOps ops(grid);
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const int num_internal = ops.internal_faces.size();
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V transi(num_internal);
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for (int fi = 0; fi < num_internal; ++fi) {
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transi[fi] = trans_all[ops.internal_faces[fi]];
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}
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std::cerr << "Topology matrices " << clock.secsSinceLast() << std::endl;
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typedef AutoDiff::ForwardBlock<double> ADB;
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typedef ADB::V V;
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// q
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V q(nc);
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q.setZero();
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q[0] = 1.0;
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q[nc-1] = -1.0;
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// s - this is explicit now
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typedef Eigen::Array<double, Eigen::Dynamic, 2, Eigen::RowMajor> TwoCol;
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TwoCol s(nc, 2);
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s.leftCols<1>().setZero();
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s.rightCols<1>().setOnes();
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// totmob - explicit as well
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TwoCol kr(nc, 2);
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props.relperm(nc, s.data(), allcells.data(), kr.data(), 0);
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V krw = kr.leftCols<1>();
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V kro = kr.rightCols<1>();
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const double* mu = props.viscosity();
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V totmob = krw/mu[0] + kro/mu[1];
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V totmobf = (ops.caver*totmob.matrix()).array();
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// Mobility-weighted transmissibilities per internal face.
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// Still explicit, and no upwinding!
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V mobtransf = totmobf*transi;
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std::cerr << "Property arrays " << clock.secsSinceLast() << std::endl;
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// Initial pressure.
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V p0(nc,1);
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p0.fill(200*Opm::unit::barsa);
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// First actual AD usage: defining pressure variable.
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std::vector<int> block_pattern = { nc };
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// Could actually write { nc } instead of block_pattern below,
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// but we prefer a named variable since we will repeat it.
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ADB p = ADB::variable(0, p0, block_pattern);
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ADB ngradp = ops.ngrad*p;
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// We want flux = totmob*trans*(p_i - p_j) for the ij-face.
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// We only need to multiply mobtransf and pdiff_face,
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// but currently multiplication with constants is not in,
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// so we define an AD constant to multiply with.
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ADB mobtransf_ad = ADB::constant(mobtransf, block_pattern);
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ADB flux = mobtransf_ad*ngradp;
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ADB residual = ops.div*flux - ADB::constant(q, block_pattern);
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std::cerr << "Construct AD residual " << clock.secsSinceLast() << std::endl;
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// std::cout << div << pdiff_face;
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// std::cout << div*pdiff_face;
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// std::cout << q << std::endl;
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// std::cout << residual << std::endl;
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// It's the residual we want to be zero. We know it's linear in p,
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// so we just need a single linear solve. Since we have formulated
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// ourselves with a residual and jacobian we do this with a single
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// Newton step (hopefully easy to extend later):
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// p = p0 - J(p0) \ R(p0)
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// Where R(p0) and J(p0) are contained in residual.value() and
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// residual.derived()[0].
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Eigen::UmfPackLU<M> solver;
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M matr = residual.derivative()[0];
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matr.coeffRef(0,0) *= 2.0;
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matr.makeCompressed();
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solver.compute(residual.derivative()[0]);
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// if (solver.info() != Eigen::Succeeded) {
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// std::cerr << "Decomposition error!\n";
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// return 1;
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// }
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Eigen::VectorXd x = solver.solve(residual.value().matrix());
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// if (solver.info() != Eigen::Succeeded) {
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// std::cerr << "Solve failure!\n";
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// return 1;
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// }
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V p_new = p0 - x.array();
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std::cerr << "Solve " << clock.secsSinceLast() << std::endl;
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std::cout << p_new << std::endl;
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}
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