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sparse_matrix_aij.hh
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/**
* @file sparse_matrix_aij.hh
*
* @author Nicolas Richart <nicolas.richart@epfl.ch>
*
* @date Mon Aug 17 21:22:57 2015
*
* @brief AIJ implementation of the SparseMatrix (this the format used by Mumps)
*
* @section LICENSE
*
* Copyright (©) 2010-2011 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 "sparse_matrix.hh"
/* -------------------------------------------------------------------------- */
#ifndef __AKANTU_SPARSE_MATRIX_AIJ_HH__
#define __AKANTU_SPARSE_MATRIX_AIJ_HH__
/* -------------------------------------------------------------------------- */
#if defined(AKANTU_UNORDERED_MAP_IS_CXX11)
__BEGIN_AKANTU_UNORDERED_MAP__
#if AKANTU_INTEGER_SIZE == 4
#define AKANTU_HASH_COMBINE_MAGIC_NUMBER 0x9e3779b9
#elif AKANTU_INTEGER_SIZE == 8
#define AKANTU_HASH_COMBINE_MAGIC_NUMBER 0x9e3779b97f4a7c13LL
#endif
/**
* Hashing function for pairs based on hash_combine from boost The magic number
* is coming from the golden number @f[\phi = \frac{1 + \sqrt5}{2}@f]
* @f[\frac{2^32}{\phi} = 0x9e3779b9@f]
* http://stackoverflow.com/questions/4948780/magic-number-in-boosthash-combine
* http://burtleburtle.net/bob/hash/doobs.html
*/
template <typename a, typename b> struct hash<std::pair<a, b> > {
public:
hash() : ah(), bh() {}
size_t operator()(const std::pair<a, b> & p) const {
size_t seed = ah(p.first);
return bh(p.second) + AKANTU_HASH_COMBINE_MAGIC_NUMBER + (seed << 6) +
(seed >> 2);
}
private:
const hash<a> ah;
const hash<b> bh;
};
__END_AKANTU_UNORDERED_MAP__
#endif
__BEGIN_AKANTU__
class SparseMatrixAIJ : public SparseMatrix {
/* ------------------------------------------------------------------------ */
/* Constructors/Destructors */
/* ------------------------------------------------------------------------ */
public:
SparseMatrixAIJ(DOFManager & dof_manager, const MatrixType & matrix_type,
const ID & id = "sparse_matrix_aij",
const MemoryID & memory_id = 0);
SparseMatrixAIJ(const SparseMatrix & matrix, const ID & id = "sparse_matrix_aij",
const MemoryID & memory_id = 0);
virtual ~SparseMatrixAIJ();
/* ------------------------------------------------------------------------ */
/* Methods */
/* ------------------------------------------------------------------------ */
public:
/// remove the existing profile
inline void clearProfile();
/// add a non-zero element
virtual UInt addToProfile(UInt i, UInt j);
/// set the matrix to 0
virtual void clear();
/// assemble a local matrix in the sparse one
inline void addToMatrix(UInt i, UInt j, Real value);
/// set the size of the matrix
void resize(UInt size) { this->size = size; }
/// modify the matrix to "remove" the blocked dof
virtual void applyBoundary(const Array<bool> & boundary, Real block_val = 1.);
/// save the profil in a file using the MatrixMarket file format
virtual void saveProfile(const std::string & filename) const;
/// save the matrix in a file using the MatrixMarket file format
virtual void saveMatrix(const std::string & filename) const;
/// copy assuming the profile are the same
virtual void copyContent(const SparseMatrix & matrix);
/// add matrix assuming the profile are the same
virtual void add(const SparseMatrix & matrix, Real alpha);
/// Equivalent of *gemv in blas
virtual void matVecMul(const Array<Real> & x, Array<Real> & y,
Real alpha = 1., Real beta = 0.);
/* ------------------------------------------------------------------------ */
/// accessor to A_{ij} - if (i, j) not present it returns 0
inline Real operator()(UInt i, UInt j) const;
/// 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);
/* ------------------------------------------------------------------------ */
/* 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> &);
protected:
typedef std::pair<UInt, UInt> KeyCOO;
typedef unordered_map<KeyCOO, UInt>::type coordinate_list_map;
/// 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:
/// row indexes
Array<Int> irn;
/// column indexes
Array<Int> jcn;
/// values : A[k] = Matrix[irn[k]][jcn[k]]
Array<Real> a;
/*
* map for (i, j) -> k correspondence
*/
coordinate_list_map irn_jcn_k;
};
__END_AKANTU__
/* -------------------------------------------------------------------------- */
/* inline functions */
/* -------------------------------------------------------------------------- */
#include "sparse_matrix_aij_inline_impl.cc"
#endif /* __AKANTU_SPARSE_MATRIX_AIJ_HH__ */

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