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https://github.com/OPM/opm-simulators.git
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186 lines
6.0 KiB
C++
186 lines
6.0 KiB
C++
// -*- mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
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// vi: set et ts=4 sw=4 sts=4:
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/*
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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 2 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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Consult the COPYING file in the top-level source directory of this
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module for the precise wording of the license and the list of
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copyright holders.
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*/
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/*!
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* \file
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* \copydoc Opm::FixPointCriterion
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*/
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#ifndef EWOMS_ISTL_FIXPOINT_CRITERION_HH
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#define EWOMS_ISTL_FIXPOINT_CRITERION_HH
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#include "convergencecriterion.hh"
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#include <opm/material/common/Unused.hpp>
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namespace Opm {
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namespace Linear {
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/*! \addtogroup Linear
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* \{
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*/
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/*!
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* \brief Provides a convergence criterion for the linear solvers
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* which looks at the weighted maximum of the difference
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* between two iterations.
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*
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* For the FixPointCriterion, the error of the solution is defined
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* as
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* \f[ e^k = \max_i\{ \left| w_i \delta^k_i \right| \}\;, \f]
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*
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* where \f$\delta = x^k - x^{k + 1} \f$ is the difference between
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* two consequtive iterative solution vectors \f$x^k\f$ and \f$x^{k + 1}\f$
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* and \f$w_i\f$ is the weight of the \f$i\f$-th degree of freedom.
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*
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* This criterion requires that the block type of the
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* vector is a Dune::FieldVector
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*/
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template <class Vector, class CollectiveCommunication>
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class FixPointCriterion : public ConvergenceCriterion<Vector>
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{
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typedef typename Vector::field_type Scalar;
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typedef typename Vector::block_type BlockType;
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public:
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FixPointCriterion(const CollectiveCommunication& comm) : comm_(comm)
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{}
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FixPointCriterion(const CollectiveCommunication& comm,
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const Vector& weightVec, Scalar reduction)
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: comm_(comm), weightVec_(weightVec), tolerance_(reduction)
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{}
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/*!
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* \brief Sets the relative weight of a primary variable
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*
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* For the FixPointCriterion, the error of the solution is defined
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* as
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* \f[ e^k = \max_i\{ \left| w_i \delta^k_i \right| \}\;, \f]
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*
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* where \f$\delta = x^k - x^{k + 1} \f$ is the difference between
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* two consequtive iterative solution vectors \f$x^k\f$ and \f$x^{k + 1}\f$
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* and \f$w_i\f$ is the weight of the \f$i\f$-th degree of freedom.
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*
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* This method is specific to the FixPointCriterion.
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*
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* \param weightVec A Dune::BlockVector<Dune::FieldVector<Scalar, n> >
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* with the relative weights of the degrees of freedom
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*/
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void setWeight(const Vector& weightVec)
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{ weightVec_ = weightVec; }
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/*!
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* \brief Return the relative weight of a primary variable
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*
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* For the FixPointCriterion, the error of the solution is defined
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* as
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* \f[ e^k = \max_i\{ \left| w_i \delta^k_i \right| \}\;, \f]
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*
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* where \f$\delta = x^k - x^{k + 1} \f$ is the difference between
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* two consequtive iterative solution vectors \f$x^k\f$ and \f$x^{k + 1}\f$
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* and \f$w_i\f$ is the weight of the \f$i\f$-th degree of freedom.
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*
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* This method is specific to the FixPointCriterion.
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*
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* \param outerIdx The index of the outer vector (i.e. Dune::BlockVector)
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* \param innerIdx The index of the inner vector (i.e. Dune::FieldVector)
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*/
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Scalar weight(int outerIdx, int innerIdx) const
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{ return (weightVec_.size() == 0) ? 1.0 : weightVec_[outerIdx][innerIdx]; }
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/*!
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* \brief Set the maximum allowed weighted maximum difference between two
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* iterations
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*/
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/*!
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* \brief Set the maximum allowed maximum difference between two
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* iterationsfor the solution considered to be converged.
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*/
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void setTolerance(Scalar tol)
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{ tolerance_ = tol; }
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/*!
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* \brief Return the maximum allowed weighted difference between two
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* iterations for the solution considered to be converged.
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*/
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Scalar tolerance() const
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{ return tolerance_; }
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/*!
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* \copydoc ConvergenceCriterion::setInitial(const Vector&, const Vector&)
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*/
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void setInitial(const Vector& curSol, const Vector& curResid OPM_UNUSED)
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{
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lastSol_ = curSol;
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delta_ = 1000 * tolerance_;
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}
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/*!
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* \copydoc ConvergenceCriterion::update(const Vector&, const Vector&, const Vector&)
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*/
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void update(const Vector& curSol,
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const Vector& changeIndicator OPM_UNUSED,
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const Vector& curResid OPM_UNUSED)
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{
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assert(curSol.size() == lastSol_.size());
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delta_ = 0.0;
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for (size_t i = 0; i < curSol.size(); ++i) {
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for (size_t j = 0; j < BlockType::dimension; ++j) {
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delta_ =
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std::max(delta_, weight(i, j)*std::abs(curSol[i][j] - lastSol_[i][j]));
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}
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}
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delta_ = comm_.max(delta_);
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lastSol_ = curSol;
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}
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/*!
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* \copydoc ConvergenceCriterion::converged()
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*/
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bool converged() const
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{ return accuracy() < tolerance(); }
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/*!
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* \copydoc ConvergenceCriterion::accuracy()
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*/
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Scalar accuracy() const
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{ return delta_; }
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private:
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const CollectiveCommunication& comm_;
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Vector lastSol_; // solution of the last iteration
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Vector weightVec_; // solution of the last iteration
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Scalar delta_; // the maximum of the absolute weighted difference of the
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// last two iterations
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Scalar tolerance_; // the maximum allowed delta for the solution to be
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// considered converged
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};
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//! \} end documentation
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}} // end namespace Linear, Opm
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#endif
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