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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::Linear::IstlSparseMatrixAdapter
*/
#ifndef EWOMS_ISTL_SPARSE_MATRIX_ADAPTER_HH
#define EWOMS_ISTL_SPARSE_MATRIX_ADAPTER_HH
#include <dune/istl/bcrsmatrix.hh>
#include <dune/common/fmatrix.hh>
#include <dune/common/version.hh>
namespace Opm {
namespace Linear {
/*!
* \ingroup Linear
* \brief A sparse matrix interface backend for BCRSMatrix from dune-istl.
*/
template <class MatrixBlockType, class AllocatorType=std::allocator<MatrixBlockType> >
class IstlSparseMatrixAdapter
{
public:
//! \brief Implementation of matrix
using IstlMatrix = Dune::BCRSMatrix<MatrixBlockType, AllocatorType>;
//! \brief block type forming the matrix entries
using MatrixBlock = typename IstlMatrix::block_type;
static_assert(std::is_same<MatrixBlock, MatrixBlockType>::value,
"IstlMatrix::block_type and MatrixBlockType must be identical");
//! \brief type of scalar
using Scalar = typename MatrixBlock::field_type;
/*!
* \brief Constructor creating an empty matrix.
*/
IstlSparseMatrixAdapter(const size_t rows, const size_t columns)
: rows_(rows)
, columns_(columns)
, istlMatrix_()
{}
/*!
* \brief Constructor taking simulator and creating an empty matrix .
*/
template <class Simulator>
IstlSparseMatrixAdapter(const Simulator& simulator)
: IstlSparseMatrixAdapter(simulator.model().numTotalDof(), simulator.model().numTotalDof())
{}
/*!
* \brief Allocate matrix structure give a sparsity pattern.
*/
template <class Set>
void reserve(const std::vector<Set>& sparsityPattern)
{
// allocate raw matrix
istlMatrix_.reset(new IstlMatrix(rows_, columns_, IstlMatrix::random));
// make sure sparsityPattern is consistent with number of rows
assert(rows_ == sparsityPattern.size());
// allocate space for the rows of the matrix
for (size_t dofIdx = 0; dofIdx < rows_; ++ dofIdx)
istlMatrix_->setrowsize(dofIdx, sparsityPattern[dofIdx].size());
istlMatrix_->endrowsizes();
// fill the rows with indices. each degree of freedom talks to
// all of its neighbors. (it also talks to itself since
// degrees of freedom are sometimes quite egocentric.)
for (size_t dofIdx = 0; dofIdx < rows_; ++ dofIdx) {
auto nIt = sparsityPattern[dofIdx].begin();
auto nEndIt = sparsityPattern[dofIdx].end();
for (; nIt != nEndIt; ++nIt)
istlMatrix_->addindex(dofIdx, *nIt);
}
istlMatrix_->endindices();
}
/*!
* \brief Return constant reference to matrix implementation.
*/
IstlMatrix& istlMatrix()
{ return *istlMatrix_; }
const IstlMatrix& istlMatrix() const
{ return *istlMatrix_; }
/*!
* \brief Return number of rows of the matrix.
*/
size_t rows() const
{ return rows_; }
/*!
* \brief Return number of columns of the matrix.
*/
size_t cols() const
{ return columns_; }
/*!
* \brief Set all matrix entries to zero.
*/
void clear()
{ (*istlMatrix_) = Scalar(0.0); }
/*!
* \brief Set given row to zero except for the main-diagonal entry (if it exists).
*
* If the sparsity pattern of the matrix features an explicit block on the main
* diagonal, the diagonal on that block is set to the second agument of the function.
*/
void clearRow(const size_t row, const Scalar diag = 1.0)
{
MatrixBlock diagBlock(Scalar(0));
for (int i = 0; i < diagBlock.rows; ++i)
diagBlock[i][i] = diag;
auto& matRow = (*istlMatrix_)[row];
auto colIt = matRow.begin();
const auto& colEndIt = matRow.end();
for (; colIt != colEndIt; ++colIt) {
if (colIt.index() == row)
*colIt = diagBlock;
else
*colIt = Scalar(0.0);
}
}
/*!
* \brief Fill given block with entries stored in the matrix.
*/
void block(const size_t rowIdx, const size_t colIdx, MatrixBlock& value) const
{ value = (*istlMatrix_)[rowIdx][colIdx]; }
/*!
* \brief Set matrix block to given block.
*/
void setBlock(const size_t rowIdx, const size_t colIdx, const MatrixBlock& value)
{ (*istlMatrix_)[rowIdx][colIdx] = value; }
/*!
* \brief Add block to matrix block.
*/
void addToBlock(const size_t rowIdx, const size_t colIdx, const MatrixBlock& value)
{ (*istlMatrix_)[rowIdx][colIdx] += value; }
/*!
* \brief Commit matrix from local caches into matrix native structure.
*
* For the ISTL adapter this is unnecessary because there is no caching mechanism.
*/
void commit()
{ }
/*!
* \brief Finish modifying the matrix, i.e., convert the data structure from one
* tailored for linearization to one aimed at the linear solver.
*
* This may compress the matrix if the build mode is implicit. For the ISTL adapter
* this is not required.
*/
void finalize()
{ }
protected:
size_t rows_;
size_t columns_;
std::unique_ptr<IstlMatrix> istlMatrix_;
};
}} // namespace Linear, Opm
#endif
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