opm-simulators/opm/simulators/linalg/fixpointcriterion.hh
2019-10-30 08:49:28 +01:00

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// -*- mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
// vi: set et ts=4 sw=4 sts=4:
/*
This file is part of the Open Porous Media project (OPM).
OPM is free software: 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.
OPM 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 General Public License for more details.
You should have received a copy of the GNU General Public License
along with OPM. If not, see <http://www.gnu.org/licenses/>.
Consult the COPYING file in the top-level source directory of this
module for the precise wording of the license and the list of
copyright holders.
*/
/*!
* \file
* \copydoc Opm::FixPointCriterion
*/
#ifndef EWOMS_ISTL_FIXPOINT_CRITERION_HH
#define EWOMS_ISTL_FIXPOINT_CRITERION_HH
#include "convergencecriterion.hh"
#include <opm/material/common/Unused.hpp>
namespace Opm {
namespace Linear {
/*! \addtogroup Linear
* \{
*/
/*!
* \brief Provides a convergence criterion for the linear solvers
* which looks at the weighted maximum of the difference
* between two iterations.
*
* For the FixPointCriterion, the error of the solution is defined
* as
* \f[ e^k = \max_i\{ \left| w_i \delta^k_i \right| \}\;, \f]
*
* where \f$\delta = x^k - x^{k + 1} \f$ is the difference between
* two consequtive iterative solution vectors \f$x^k\f$ and \f$x^{k + 1}\f$
* and \f$w_i\f$ is the weight of the \f$i\f$-th degree of freedom.
*
* This criterion requires that the block type of the
* vector is a Dune::FieldVector
*/
template <class Vector, class CollectiveCommunication>
class FixPointCriterion : public ConvergenceCriterion<Vector>
{
typedef typename Vector::field_type Scalar;
typedef typename Vector::block_type BlockType;
public:
FixPointCriterion(const CollectiveCommunication& comm) : comm_(comm)
{}
FixPointCriterion(const CollectiveCommunication& comm,
const Vector& weightVec, Scalar reduction)
: comm_(comm), weightVec_(weightVec), tolerance_(reduction)
{}
/*!
* \brief Sets the relative weight of a primary variable
*
* For the FixPointCriterion, the error of the solution is defined
* as
* \f[ e^k = \max_i\{ \left| w_i \delta^k_i \right| \}\;, \f]
*
* where \f$\delta = x^k - x^{k + 1} \f$ is the difference between
* two consequtive iterative solution vectors \f$x^k\f$ and \f$x^{k + 1}\f$
* and \f$w_i\f$ is the weight of the \f$i\f$-th degree of freedom.
*
* This method is specific to the FixPointCriterion.
*
* \param weightVec A Dune::BlockVector<Dune::FieldVector<Scalar, n> >
* with the relative weights of the degrees of freedom
*/
void setWeight(const Vector& weightVec)
{ weightVec_ = weightVec; }
/*!
* \brief Return the relative weight of a primary variable
*
* For the FixPointCriterion, the error of the solution is defined
* as
* \f[ e^k = \max_i\{ \left| w_i \delta^k_i \right| \}\;, \f]
*
* where \f$\delta = x^k - x^{k + 1} \f$ is the difference between
* two consequtive iterative solution vectors \f$x^k\f$ and \f$x^{k + 1}\f$
* and \f$w_i\f$ is the weight of the \f$i\f$-th degree of freedom.
*
* This method is specific to the FixPointCriterion.
*
* \param outerIdx The index of the outer vector (i.e. Dune::BlockVector)
* \param innerIdx The index of the inner vector (i.e. Dune::FieldVector)
*/
Scalar weight(int outerIdx, int innerIdx) const
{ return (weightVec_.size() == 0) ? 1.0 : weightVec_[outerIdx][innerIdx]; }
/*!
* \brief Set the maximum allowed weighted maximum difference between two
* iterations
*/
/*!
* \brief Set the maximum allowed maximum difference between two
* iterationsfor the solution considered to be converged.
*/
void setTolerance(Scalar tol)
{ tolerance_ = tol; }
/*!
* \brief Return the maximum allowed weighted difference between two
* iterations for the solution considered to be converged.
*/
Scalar tolerance() const
{ return tolerance_; }
/*!
* \copydoc ConvergenceCriterion::setInitial(const Vector&, const Vector&)
*/
void setInitial(const Vector& curSol, const Vector& curResid OPM_UNUSED)
{
lastSol_ = curSol;
delta_ = 1000 * tolerance_;
}
/*!
* \copydoc ConvergenceCriterion::update(const Vector&, const Vector&, const Vector&)
*/
void update(const Vector& curSol,
const Vector& changeIndicator OPM_UNUSED,
const Vector& curResid OPM_UNUSED)
{
assert(curSol.size() == lastSol_.size());
delta_ = 0.0;
for (size_t i = 0; i < curSol.size(); ++i) {
for (size_t j = 0; j < BlockType::dimension; ++j) {
delta_ =
std::max(delta_, weight(i, j)*std::abs(curSol[i][j] - lastSol_[i][j]));
}
}
delta_ = comm_.max(delta_);
lastSol_ = curSol;
}
/*!
* \copydoc ConvergenceCriterion::converged()
*/
bool converged() const
{ return accuracy() < tolerance(); }
/*!
* \copydoc ConvergenceCriterion::accuracy()
*/
Scalar accuracy() const
{ return delta_; }
private:
const CollectiveCommunication& comm_;
Vector lastSol_; // solution of the last iteration
Vector weightVec_; // solution of the last iteration
Scalar delta_; // the maximum of the absolute weighted difference of the
// last two iterations
Scalar tolerance_; // the maximum allowed delta for the solution to be
// considered converged
};
//! \} end documentation
}} // end namespace Linear, Opm
#endif