Homec4science
Diffusion akantu (features/doc_energies) Browse

rAKA/src/solver/sparse_matrix_aij_inline_impl.hh
20e355af2b02features/doc_energies

Last Change
Raw File

sparse_matrix_aij_inline_impl.hh
View Options

/**
* Copyright (©) 2015-2023 EPFL (Ecole Polytechnique Fédérale de Lausanne)
* Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
*
* This file is part of Akantu
*
* 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"
/* -------------------------------------------------------------------------- */
#ifndef AKANTU_SPARSE_MATRIX_AIJ_INLINE_IMPL_HH_
#define AKANTU_SPARSE_MATRIX_AIJ_INLINE_IMPL_HH_
namespace akantu {
inline Idx SparseMatrixAIJ::add(Idx i, Idx j) {
KeyCOO jcn_irn = this->key(i, j);
auto it = this->irn_jcn_k.find(jcn_irn);
if (!(it == this->irn_jcn_k.end())) {
return it->second;
}
if (i + 1 > this->size_) {
this->size_ = i + 1;
}
if (j + 1 > this->size_) {
this->size_ = j + 1;
}
this->irn.push_back(i + 1);
this->jcn.push_back(j + 1);
this->a.push_back(0.);
this->irn_jcn_k[jcn_irn] = this->nb_non_zero;
(this->nb_non_zero)++;
this->profile_release++;
this->value_release++;
return (this->nb_non_zero - 1);
}
/* -------------------------------------------------------------------------- */
inline void SparseMatrixAIJ::clearProfile() {
SparseMatrix::clearProfile();
this->irn_jcn_k.clear();
this->irn.clear();
this->jcn.clear();
this->a.clear();
this->size_ = 0;
this->nb_non_zero = 0;
this->profile_release++;
this->value_release++;
}
/* -------------------------------------------------------------------------- */
inline void SparseMatrixAIJ::add(Idx i, Idx j, Real value) {
Idx idx = this->add(i, j);
this->a(idx) += value;
this->value_release++;
}
/* -------------------------------------------------------------------------- */
inline Real SparseMatrixAIJ::operator()(Idx i, Idx j) const {
KeyCOO jcn_irn = this->key(i, j);
auto irn_jcn_k_it = this->irn_jcn_k.find(jcn_irn);
if (irn_jcn_k_it == this->irn_jcn_k.end()) {
return 0.;
}
return this->a(irn_jcn_k_it->second);
}
/* -------------------------------------------------------------------------- */
inline Real & SparseMatrixAIJ::operator()(Idx i, Idx j) {
KeyCOO jcn_irn = this->key(i, j);
auto irn_jcn_k_it = this->irn_jcn_k.find(jcn_irn);
AKANTU_DEBUG_ASSERT(irn_jcn_k_it != this->irn_jcn_k.end(),
"Couple (i,j) = (" << i << "," << j
<< ") does not exist in the profile");
// it may change the profile so it is considered as a change
this->value_release++;
return this->a(irn_jcn_k_it->second);
}
/* -------------------------------------------------------------------------- */
inline void
SparseMatrixAIJ::addSymmetricValuesToSymmetric(const Vector<Idx> & is,
const Vector<Idx> & js,
const Matrix<Real> & values) {
for (decltype(values.rows()) i = 0; i < values.rows(); ++i) {
auto c_irn = is(i);
if (c_irn < size_) {
for (decltype(values.cols()) j = i; j < values.cols(); ++j) {
auto c_jcn = js(j);
if (c_jcn < size_) {
operator()(c_irn, c_jcn) += values(i, j);
}
}
}
}
}
/* -------------------------------------------------------------------------- */
inline void
SparseMatrixAIJ::addUnsymmetricValuesToSymmetric(const Vector<Idx> & is,
const Vector<Idx> & js,
const Matrix<Real> & values) {
for (decltype(values.rows()) i = 0; i < values.rows(); ++i) {
auto c_irn = is(i);
if (c_irn < size_) {
for (decltype(values.cols()) j = 0; j < values.cols(); ++j) {
auto c_jcn = js(j);
if (c_jcn < size_) {
if (c_jcn >= c_irn) {
operator()(c_irn, c_jcn) += values(i, j);
}
}
}
}
}
}
/* -------------------------------------------------------------------------- */
inline void
SparseMatrixAIJ::addValuesToUnsymmetric(const Vector<Idx> & is,
const Vector<Idx> & js,
const Matrix<Real> & values) {
for (decltype(values.rows()) i = 0; i < values.rows(); ++i) {
auto c_irn = is(i);
if (c_irn < size_) {
for (decltype(values.cols()) j = 0; j < values.cols(); ++j) {
auto c_jcn = js(j);
if (c_jcn < size_) {
operator()(c_irn, c_jcn) += values(i, j);
}
}
}
}
}
/* -------------------------------------------------------------------------- */
inline void SparseMatrixAIJ::addValues(const Vector<Idx> & is,
const Vector<Idx> & js,
const Matrix<Real> & values,
MatrixType values_type) {
if (getMatrixType() == _symmetric) {
if (values_type == _symmetric) {
this->addSymmetricValuesToSymmetric(is, js, values);
} else {
this->addUnsymmetricValuesToSymmetric(is, js, values);
}
} else {
this->addValuesToUnsymmetric(is, js, values);
}
}
/* -------------------------------------------------------------------------- */
inline Real SparseMatrixAIJ::min() {
return *std::min_element(this->a.cbegin(), this->a.cend());
}
} // namespace akantu
#endif /* AKANTU_SPARSE_MATRIX_AIJ_INLINE_IMPL_HH_ */
c4science · Help