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rAKA akantu
sparse_matrix_aij.cc
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/**
* @file sparse_matrix_aij.cc
*
* @author Nicolas Richart <nicolas.richart@epfl.ch>
*
* @date Tue Aug 18 16:31:23 2015
*
* @brief Implementation of the AIJ sparse matrix
*
* @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_aij.hh"
#include "dof_manager_default.hh"
/* -------------------------------------------------------------------------- */
#include <fstream>
/* -------------------------------------------------------------------------- */
__BEGIN_AKANTU__
/* -------------------------------------------------------------------------- */
SparseMatrixAIJ
::
SparseMatrixAIJ
(
DOFManagerDefault
&
dof_manager
,
const
MatrixType
&
matrix_type
,
const
ID
&
id
)
:
SparseMatrix
(
dof_manager
,
matrix_type
,
id
),
dof_manager
(
dof_manager
),
irn
(
0
,
1
,
id
+
":irn"
),
jcn
(
0
,
1
,
id
+
":jcn"
),
a
(
0
,
1
,
id
+
":a"
),
profile_release
(
0
),
value_release
(
0
)
{}
/* -------------------------------------------------------------------------- */
SparseMatrixAIJ
::
SparseMatrixAIJ
(
const
SparseMatrixAIJ
&
matrix
,
const
ID
&
id
)
:
SparseMatrix
(
matrix
,
id
),
dof_manager
(
matrix
.
dof_manager
),
irn
(
matrix
.
irn
,
true
,
id
+
":irn"
),
jcn
(
matrix
.
jcn
,
true
,
id
+
":jcn"
),
a
(
matrix
.
a
,
true
,
id
+
":a"
),
profile_release
(
0
),
value_release
(
0
)
{}
/* -------------------------------------------------------------------------- */
SparseMatrixAIJ
::~
SparseMatrixAIJ
()
{}
// /* --------------------------------------------------------------------------
// */
// void SparseMatrixAIJ::buildProfile(const Mesh & mesh,
// const DOFSynchronizer & dof_synchronizer,
// UInt nb_degree_of_freedom) {
// AKANTU_DEBUG_IN();
// // if(irn_jcn_to_k) delete irn_jcn_to_k;
// // irn_jcn_to_k = new std::map<std::pair<UInt, UInt>, UInt>;
// clearProfile();
// this->dof_synchronizer = &const_cast<DOFSynchronizer &>(dof_synchronizer);
// coordinate_list_map::iterator irn_jcn_k_it;
// Int * eq_nb_val = dof_synchronizer.getGlobalDOFEquationNumbers().storage();
// Mesh::type_iterator it =
// mesh.firstType(mesh.getSpatialDimension(), _not_ghost,
// _ek_not_defined);
// Mesh::type_iterator end =
// mesh.lastType(mesh.getSpatialDimension(), _not_ghost, _ek_not_defined);
// for (; it != end; ++it) {
// UInt nb_element = mesh.getNbElement(*it);
// UInt nb_nodes_per_element = Mesh::getNbNodesPerElement(*it);
// UInt size_mat = nb_nodes_per_element * nb_degree_of_freedom;
// UInt * conn_val = mesh.getConnectivity(*it, _not_ghost).storage();
// Int * local_eq_nb_val =
// new Int[nb_degree_of_freedom * nb_nodes_per_element];
// for (UInt e = 0; e < nb_element; ++e) {
// Int * tmp_local_eq_nb_val = local_eq_nb_val;
// for (UInt i = 0; i < nb_nodes_per_element; ++i) {
// UInt n = conn_val[i];
// for (UInt d = 0; d < nb_degree_of_freedom; ++d) {
// *tmp_local_eq_nb_val++ = eq_nb_val[n * nb_degree_of_freedom + d];
// }
// // memcpy(tmp_local_eq_nb_val, eq_nb_val + n * nb_degree_of_freedom,
// // nb_degree_of_freedom * sizeof(Int));
// // tmp_local_eq_nb_val += nb_degree_of_freedom;
// }
// for (UInt i = 0; i < size_mat; ++i) {
// UInt c_irn = local_eq_nb_val[i];
// if (c_irn < this->size) {
// UInt j_start = (sparse_matrix_type == _symmetric) ? i : 0;
// for (UInt j = j_start; j < size_mat; ++j) {
// UInt c_jcn = local_eq_nb_val[j];
// if (c_jcn < this->size) {
// KeyCOO irn_jcn = key(c_irn, c_jcn);
// irn_jcn_k_it = irn_jcn_k.find(irn_jcn);
// if (irn_jcn_k_it == irn_jcn_k.end()) {
// irn_jcn_k[irn_jcn] = nb_non_zero;
// irn.push_back(c_irn + 1);
// jcn.push_back(c_jcn + 1);
// nb_non_zero++;
// }
// }
// }
// }
// }
// conn_val += nb_nodes_per_element;
// }
// delete[] local_eq_nb_val;
// }
// /// for pbc @todo correct it for parallel
// if (StaticCommunicator::getStaticCommunicator().getNbProc() == 1) {
// for (UInt i = 0; i < size; ++i) {
// KeyCOO irn_jcn = key(i, i);
// irn_jcn_k_it = irn_jcn_k.find(irn_jcn);
// if (irn_jcn_k_it == irn_jcn_k.end()) {
// irn_jcn_k[irn_jcn] = nb_non_zero;
// irn.push_back(i + 1);
// jcn.push_back(i + 1);
// nb_non_zero++;
// }
// }
// }
// a.resize(nb_non_zero);
// AKANTU_DEBUG_OUT();
// }
/* -------------------------------------------------------------------------- */
void
SparseMatrixAIJ
::
applyBoundary
(
Real
block_val
)
{
AKANTU_DEBUG_IN
();
const
Array
<
bool
>
&
blocked_dofs
=
this
->
dof_manager
.
getGlobalBlockedDOFs
();
Array
<
Int
>::
const_scalar_iterator
irn_val
=
irn
.
begin
();
Array
<
Int
>::
const_scalar_iterator
jcn_val
=
jcn
.
begin
();
Array
<
Real
>::
scalar_iterator
a_val
=
a
.
begin
();
for
(
UInt
i
=
0
;
i
<
nb_non_zero
;
++
i
)
{
UInt
ni
=
this
->
dof_manager
.
globalToLocalEquationNumber
(
*
irn_val
-
1
);
UInt
nj
=
this
->
dof_manager
.
globalToLocalEquationNumber
(
*
jcn_val
-
1
);
if
(
blocked_dofs
(
ni
)
||
blocked_dofs
(
nj
))
{
if
(
*
irn_val
!=
*
jcn_val
)
{
*
a_val
=
0
;
}
else
{
if
(
this
->
dof_manager
.
isLocalOrMasterDOF
(
ni
))
{
*
a_val
=
block_val
;
}
else
{
*
a_val
=
0
;
}
}
}
++
irn_val
;
++
jcn_val
;
++
a_val
;
}
this
->
value_release
++
;
AKANTU_DEBUG_OUT
();
}
/* -------------------------------------------------------------------------- */
void
SparseMatrixAIJ
::
saveProfile
(
const
std
::
string
&
filename
)
const
{
AKANTU_DEBUG_IN
();
std
::
ofstream
outfile
;
outfile
.
open
(
filename
.
c_str
());
outfile
<<
"%%MatrixMarket matrix coordinate pattern"
;
if
(
this
->
matrix_type
==
_symmetric
)
outfile
<<
" symmetric"
;
else
outfile
<<
" general"
;
outfile
<<
std
::
endl
;
UInt
m
=
this
->
size
;
outfile
<<
m
<<
" "
<<
m
<<
" "
<<
this
->
nb_non_zero
<<
std
::
endl
;
for
(
UInt
i
=
0
;
i
<
this
->
nb_non_zero
;
++
i
)
{
outfile
<<
this
->
irn
.
storage
()[
i
]
<<
" "
<<
this
->
jcn
.
storage
()[
i
]
<<
" 1"
<<
std
::
endl
;
}
outfile
.
close
();
AKANTU_DEBUG_OUT
();
}
/* -------------------------------------------------------------------------- */
void
SparseMatrixAIJ
::
saveMatrix
(
const
std
::
string
&
filename
)
const
{
AKANTU_DEBUG_IN
();
std
::
ofstream
outfile
;
outfile
.
precision
(
std
::
numeric_limits
<
Real
>::
digits10
);
outfile
.
open
(
filename
.
c_str
());
outfile
<<
"%%MatrixMarket matrix coordinate real"
;
if
(
this
->
matrix_type
==
_symmetric
)
outfile
<<
" symmetric"
;
else
outfile
<<
" general"
;
outfile
<<
std
::
endl
;
outfile
<<
this
->
size
<<
" "
<<
this
->
size
<<
" "
<<
this
->
nb_non_zero
<<
std
::
endl
;
for
(
UInt
i
=
0
;
i
<
this
->
nb_non_zero
;
++
i
)
{
outfile
<<
this
->
irn
(
i
)
<<
" "
<<
this
->
jcn
(
i
)
<<
" "
<<
this
->
a
(
i
)
<<
std
::
endl
;
}
outfile
.
close
();
AKANTU_DEBUG_OUT
();
}
/* -------------------------------------------------------------------------- */
void
SparseMatrixAIJ
::
matVecMul
(
const
Array
<
Real
>
&
x
,
Array
<
Real
>
&
y
,
Real
alpha
,
Real
beta
)
const
{
AKANTU_DEBUG_IN
();
y
*=
beta
;
Array
<
Int
>::
const_scalar_iterator
i_it
=
this
->
irn
.
storage
();
Array
<
Int
>::
const_scalar_iterator
j_it
=
this
->
jcn
.
storage
();
Array
<
Real
>::
const_scalar_iterator
a_it
=
this
->
a
.
storage
();
Array
<
Real
>::
const_scalar_iterator
x_it
=
x
.
storage
();
Array
<
Real
>::
scalar_iterator
y_it
=
y
.
storage
();
for
(
UInt
k
=
0
;
k
<
this
->
nb_non_zero
;
++
k
,
++
i_it
,
++
j_it
,
++
a_it
)
{
const
Int
&
i
=
*
i_it
;
const
Int
&
j
=
*
j_it
;
const
Real
&
A
=
*
a_it
;
y_it
[
i
]
+=
alpha
*
A
*
x_it
[
j
];
if
((
this
->
matrix_type
==
_symmetric
)
&&
(
i
!=
j
))
y_it
[
j
]
+=
alpha
*
A
*
x_it
[
i
];
}
// if (dof_synchronizer)
// dof_synchronizer->reduceSynchronize<AddOperation>(vect);
AKANTU_DEBUG_OUT
();
}
/* -------------------------------------------------------------------------- */
void
SparseMatrixAIJ
::
copyContent
(
const
SparseMatrix
&
matrix
)
{
AKANTU_DEBUG_IN
();
const
SparseMatrixAIJ
&
mat
=
dynamic_cast
<
const
SparseMatrixAIJ
&>
(
matrix
);
AKANTU_DEBUG_ASSERT
(
nb_non_zero
==
mat
.
getNbNonZero
(),
"The to matrix don't have the same profiles"
);
memcpy
(
a
.
storage
(),
mat
.
getA
().
storage
(),
nb_non_zero
*
sizeof
(
Real
));
this
->
value_release
++
;
AKANTU_DEBUG_OUT
();
}
/* -------------------------------------------------------------------------- */
void
SparseMatrixAIJ
::
add
(
const
SparseMatrix
&
B
,
Real
alpha
)
{
Array
<
Real
>::
scalar_iterator
a_it
=
this
->
a
.
begin
();
try
{
const
SparseMatrixAIJ
&
B_aij
=
dynamic_cast
<
const
SparseMatrixAIJ
&>
(
B
);
Array
<
Real
>::
const_scalar_iterator
b_it
=
B_aij
.
a
.
begin
();
for
(
UInt
n
=
0
;
n
<
this
->
nb_non_zero
;
++
n
,
++
a_it
,
++
b_it
)
{
*
a_it
+=
alpha
*
*
b_it
;
}
}
catch
(...)
{
Array
<
Int
>::
const_scalar_iterator
i_it
=
this
->
irn
.
begin
();
Array
<
Int
>::
const_scalar_iterator
j_it
=
this
->
jcn
.
begin
();
for
(
UInt
n
=
0
;
n
<
this
->
nb_non_zero
;
++
n
,
++
a_it
,
++
i_it
,
++
j_it
)
{
const
Int
&
i
=
*
i_it
;
const
Int
&
j
=
*
j_it
;
Real
&
A_ij
=
*
a_it
;
A_ij
+=
alpha
*
B
(
i
-
1
,
j
-
1
);
}
}
this
->
value_release
++
;
}
/* -------------------------------------------------------------------------- */
void
SparseMatrixAIJ
::
clear
()
{
a
.
set
(
0.
);
this
->
value_release
++
;
}
__END_AKANTU__
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