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rAKA/src/solver/sparse_matrix.hh
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sparse_matrix.hh
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/**
* @file sparse_matrix.hh
*
* @author Nicolas Richart <nicolas.richart@epfl.ch>
*
* @date creation: Mon Dec 13 2010
* @date last modification: Mon Sep 15 2014
*
* @brief sparse matrix storage class (distributed assembled matrix)
* This is a COO format (Coordinate List)
*
* @section LICENSE
*
* Copyright (©) 2010-2012, 2014 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/>.
*
*/
/* -------------------------------------------------------------------------- */
#ifndef __AKANTU_SPARSE_MATRIX_HH__
#define __AKANTU_SPARSE_MATRIX_HH__
/* -------------------------------------------------------------------------- */
#include "aka_common.hh"
#include "mesh.hh"
/* -------------------------------------------------------------------------- */
#ifndef __INTEL_COMPILER
namespace std {
namespace tr1 {
template<typename a, typename b>
struct hash< std::pair<a, b> > {
private:
const hash<a> ah;
const hash<b> bh;
public:
hash() : ah(), bh() {}
size_t operator()(const std::pair<a, b> &p) const {
size_t seed = ah(p.first);
return bh(p.second) + 0x9e3779b9 + (seed<<6) + (seed>>2);
}
};
}
} // namespaces
#endif
__BEGIN_AKANTU__
class DOFSynchronizer;
class SparseMatrix : private Memory {
/* ------------------------------------------------------------------------ */
/* Constructors/Destructors */
/* ------------------------------------------------------------------------ */
public:
SparseMatrix(UInt size,
const SparseMatrixType & sparse_matrix_type,
const ID & id = "sparse_matrix",
const MemoryID & memory_id = 0);
SparseMatrix(const SparseMatrix & matrix,
const ID & id = "sparse_matrix",
const MemoryID & memory_id = 0);
virtual ~SparseMatrix();
typedef std::pair<UInt, UInt> KeyCOO;
typedef unordered_map<KeyCOO, UInt>::type coordinate_list_map;
/* ------------------------------------------------------------------------ */
/* 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
inline 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; }
virtual void buildProfile(const Mesh & mesh, const DOFSynchronizer & dof_synchronizer, UInt nb_degree_of_freedom);
/// modify the matrix to "remove" the blocked dof
virtual void applyBoundary(const Array<bool> & boundary, Real block_val = 1.);
// /// modify the matrix to "remove" the blocked dof
// void applyBoundaryNormal(Array<bool> & boundary_normal, Array<Real> & EulerAngles, Array<Real> & rhs, const Array<Real> & matrix, Array<Real> & rhs_rotated);
/// 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);
/// copy profile
// void copyProfile(const SparseMatrix & matrix);
/// add matrix assuming the profile are the same
virtual void add(const SparseMatrix & matrix, Real alpha);
/// diagonal lumping
virtual void lump(Array<Real> & lumped);
/// function to print the contain of the class
//virtual void printself(std::ostream & stream, int indent = 0) const;
protected:
inline KeyCOO key(UInt i, UInt j) const {
if(sparse_matrix_type == _symmetric && (i > j))
return std::make_pair(j, i);
return std::make_pair(i, j);
}
/* ------------------------------------------------------------------------ */
/* Accessors */
/* ------------------------------------------------------------------------ */
public:
/// return the values at potition i, j
inline Real operator()(UInt i, UInt j) const;
inline Real & operator()(UInt i, UInt j);
AKANTU_GET_MACRO(IRN, irn, const Array<Int> &);
AKANTU_GET_MACRO(JCN, jcn, const Array<Int> &);
AKANTU_GET_MACRO(A, a, const Array<Real> &);
AKANTU_GET_MACRO(NbNonZero, nb_non_zero, UInt);
AKANTU_GET_MACRO(Size, size, UInt);
AKANTU_GET_MACRO(SparseMatrixType, sparse_matrix_type, const SparseMatrixType &);
AKANTU_GET_MACRO(Offset, offset, UInt);
const DOFSynchronizer & getDOFSynchronizer() const {
AKANTU_DEBUG_ASSERT(dof_synchronizer != NULL,
"DOFSynchronizer not initialized in the SparseMatrix!");
return *dof_synchronizer;
}
private:
AKANTU_GET_MACRO(DOFSynchronizerPointer, dof_synchronizer, DOFSynchronizer *);
friend Array<Real> & operator*=(Array<Real> & vect, const SparseMatrix & mat);
/* ------------------------------------------------------------------------ */
/* Class Members */
/* ------------------------------------------------------------------------ */
protected:
/// id of the SparseMatrix
ID id;
/// sparce matrix type
SparseMatrixType sparse_matrix_type;
/// Mesh corresponding to the profile
// const Mesh * mesh;
/// Size of the matrix
UInt size;
/// number of processors
UInt nb_proc;
/// number of non zero element
UInt nb_non_zero;
/// row indexes
Array<Int> irn;
/// column indexes
Array<Int> jcn;
/// values : A[k] = Matrix[irn[k]][jcn[k]]
Array<Real> a;
/// saved row indexes
Array<Int> * irn_save;
/// saved column indexes
Array<Int> * jcn_save;
/// saved size
UInt size_save;
/// information to know where to assemble an element in a global sparse matrix
// ElementTypeMapArray<UInt> element_to_sparse_profile;
/* map for (i,j) -> k correspondence \warning std::map are slow
* \todo improve with hash_map (non standard in stl) or unordered_map (boost or C++0x)
*/
coordinate_list_map irn_jcn_k;
DOFSynchronizer * dof_synchronizer;
// std::map<std::pair<UInt, UInt>, UInt> * irn_jcn_to_k;
/// offset to inidcate whether row and column indices start at 0 (C/C++) or 1 (Fortran)
UInt offset;
};
/* -------------------------------------------------------------------------- */
/* inline functions */
/* -------------------------------------------------------------------------- */
#if defined (AKANTU_INCLUDE_INLINE_IMPL)
# include "sparse_matrix_inline_impl.cc"
#endif
// /// standard output stream operator
// inline std::ostream & operator <<(std::ostream & stream, const SparseMatrix & _this)
// {
// _this.printself(stream);
// return stream;
// }
Array<Real> & operator*=(Array<Real> & vect, const SparseMatrix & mat);
__END_AKANTU__
#endif /* __AKANTU_SPARSE_MATRIX_HH__ */
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