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rAKA/src/solver/sparse_matrix_aij.hh
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/**
* @file sparse_matrix_aij.hh
*
* @author Nicolas Richart <nicolas.richart@epfl.ch>
*
* @date creation: Mon Dec 13 2010
* @date last modification: Wed Sep 16 2020
*
* @brief AIJ implementation of the SparseMatrix (this the format used by
* Mumps)
*
*
* @section LICENSE
*
* Copyright (©) 2010-2021 EPFL (Ecole Polytechnique Fédérale de Lausanne)
* Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
*
* Akantu is free software: you can redistribute it and/or modify it under the
* terms of the GNU Lesser General Public License as published by the Free
* Software Foundation, either version 3 of the License, or (at your option) any
* later version.
*
* Akantu 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 Lesser General Public License for more
* details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with Akantu. If not, see <http://www.gnu.org/licenses/>.
*
*/
/* -------------------------------------------------------------------------- */
#include "aka_array.hh"
#include "aka_common.hh"
#include "sparse_matrix.hh"
/* -------------------------------------------------------------------------- */
#include <unordered_map>
/* -------------------------------------------------------------------------- */
#ifndef AKANTU_SPARSE_MATRIX_AIJ_HH_
#define AKANTU_SPARSE_MATRIX_AIJ_HH_
namespace akantu {
class DOFManagerDefault;
class TermsToAssemble;
} // namespace akantu
namespace akantu {
class SparseMatrixAIJ : public SparseMatrix {
/* ------------------------------------------------------------------------ */
/* Constructors/Destructors */
/* ------------------------------------------------------------------------ */
public:
SparseMatrixAIJ(DOFManagerDefault & dof_manager,
const MatrixType & matrix_type,
const ID & id = "sparse_matrix_aij");
SparseMatrixAIJ(const SparseMatrixAIJ & matrix,
const ID & id = "sparse_matrix_aij");
~SparseMatrixAIJ() override;
/* ------------------------------------------------------------------------ */
/* Methods */
/* ------------------------------------------------------------------------ */
public:
/// remove the existing profile
inline void clearProfile() override;
/// add a non-zero element
inline UInt add(UInt i, UInt j) override;
/// set the matrix to 0
void set(Real val) override;
/// assemble a local matrix in the sparse one
inline void add(UInt i, UInt j, Real value) override;
/// add a block of values
inline void addValues(const Vector<Int> & is, const Vector<Int> & js,
const Matrix<Real> & values, MatrixType values_type);
/// set the size of the matrix
void resize(UInt size) { this->size_ = size; }
/// modify the matrix to "remove" the blocked dof
void applyBoundary(Real block_val = 1.) override;
/// save the profil in a file using the MatrixMarket file format
void saveProfile(const std::string & filename) const override;
/// save the matrix in a file using the MatrixMarket file format
void saveMatrix(const std::string & filename) const override;
/// copy assuming the profile are the same
virtual void copyContent(const SparseMatrix & matrix);
/// multiply the matrix by a scalar
void mul(Real alpha) override;
/// Equivalent of *gemv in blas
void matVecMul(const SolverVector & x, SolverVector & y, Real alpha = 1.,
Real beta = 0.) const override;
void matVecMul(const Array<Real> & x, Array<Real> & y, Real alpha = 1.,
Real beta = 0.) const;
/// copy the profile of another matrix
void copyProfile(const SparseMatrix & other) override;
/* ------------------------------------------------------------------------ */
/// accessor to A_{ij} - if (i, j) not present it returns 0
inline Real operator()(UInt i, UInt j) const override;
/// accessor to A_{ij} - if (i, j) not present it fails, (i, j) should be
/// first added to the profile
inline Real & operator()(UInt i, UInt j) override;
/// accessor to get the minimum value of A_{ij}
inline Real min() override;
protected:
void addMeTo(SparseMatrix & B, Real alpha) const override;
inline void addSymmetricValuesToSymmetric(const Vector<Int> & is,
const Vector<Int> & js,
const Matrix<Real> & values);
inline void addUnsymmetricValuesToSymmetric(const Vector<Int> & is,
const Vector<Int> & js,
const Matrix<Real> & values);
inline void addValuesToUnsymmetric(const Vector<Int> & is,
const Vector<Int> & js,
const Matrix<Real> & values);
private:
/// This is just to inline the addToMatrix function
template <class MatrixType>
void addMeToTemplated(MatrixType & B, Real alpha) const;
/* ------------------------------------------------------------------------ */
/* Accessors */
/* ------------------------------------------------------------------------ */
public:
AKANTU_GET_MACRO(IRN, irn, const Array<Int> &);
AKANTU_GET_MACRO(JCN, jcn, const Array<Int> &);
AKANTU_GET_MACRO(A, a, const Array<Real> &);
/// The release changes at each call of a function that changes the profile,
/// it in increasing but could overflow so it should be checked as
/// (my_release != release) and not as (my_release < release)
AKANTU_GET_MACRO(ProfileRelease, profile_release, UInt);
AKANTU_GET_MACRO(ValueRelease, value_release, UInt);
UInt getRelease() const override { return value_release; }
protected:
using KeyCOO = std::pair<UInt, UInt>;
using coordinate_list_map = std::unordered_map<KeyCOO, UInt>;
/// get the pair corresponding to (i, j)
inline KeyCOO key(UInt i, UInt j) const {
if (this->matrix_type == _symmetric && (i > j)) {
return std::make_pair(j, i);
}
return std::make_pair(i, j);
}
/* ------------------------------------------------------------------------ */
/* Class Members */
/* ------------------------------------------------------------------------ */
private:
DOFManagerDefault & dof_manager;
/// row indexes
Array<Int> irn;
/// column indexes
Array<Int> jcn;
/// values : A[k] = Matrix[irn[k]][jcn[k]]
Array<Real> a;
/// Profile release
UInt profile_release{1};
/// Value release
UInt value_release{1};
/// map for (i, j) -> k correspondence
coordinate_list_map irn_jcn_k;
};
} // namespace akantu
/* -------------------------------------------------------------------------- */
/* inline functions */
/* -------------------------------------------------------------------------- */
#include "sparse_matrix_aij_inline_impl.hh"
#endif /* AKANTU_SPARSE_MATRIX_AIJ_HH_ */
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