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rAKA/python/py_solver.cc
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py_solver.cc
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/**
* @file py_solver.cc
*
* @author Nicolas Richart <nicolas.richart@epfl.ch>
*
* @date creation: Tue Sep 29 2020
* @date last modification: Sat Mar 06 2021
*
* @brief pybind11 interface to Solver and SparseMatrix
*
*
* @section LICENSE
*
* Copyright (©) 2018-2021 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 "py_solver.hh"
#include "py_aka_array.hh"
/* -------------------------------------------------------------------------- */
#include <model.hh>
#include <non_linear_solver.hh>
#include <sparse_matrix_aij.hh>
#include <terms_to_assemble.hh>
/* -------------------------------------------------------------------------- */
#include <pybind11/operators.h>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
/* -------------------------------------------------------------------------- */
namespace py = pybind11;
/* -------------------------------------------------------------------------- */
namespace akantu {
/* -------------------------------------------------------------------------- */
void register_solvers(py::module & mod) {
py::class_<SparseMatrix>(mod, "SparseMatrix")
.def("getMatrixType", &SparseMatrix::getMatrixType)
.def("size", &SparseMatrix::size)
.def("zero", &SparseMatrix::zero)
.def("saveProfile", &SparseMatrix::saveProfile)
.def("saveMatrix", &SparseMatrix::saveMatrix)
.def(
"add", [](SparseMatrix & self, UInt i, UInt j) { self.add(i, j); },
"Add entry in the profile")
.def(
"add",
[](SparseMatrix & self, UInt i, UInt j, Real value) {
self.add(i, j, value);
},
"Add the value to the matrix")
.def(
"add",
[](SparseMatrix & self, SparseMatrix & A, Real alpha) {
self.add(A, alpha);
},
"Add a matrix to the matrix", py::arg("A"), py::arg("alpha") = 1.)
.def("__call__",
[](const SparseMatrix & self, UInt i, UInt j) { return self(i, j); })
.def("getRelease", &SparseMatrix::getRelease);
py::class_<SparseMatrixAIJ, SparseMatrix>(mod, "SparseMatrixAIJ")
.def("getIRN", &SparseMatrixAIJ::getIRN)
.def("getJCN", &SparseMatrixAIJ::getJCN)
.def("getA", &SparseMatrixAIJ::getA);
py::class_<SolverVector>(mod, "SolverVector")
.def("getValues",
[](SolverVector& self) -> decltype(auto) {
return static_cast<const Array<Real>& >(self);
},
py::return_value_policy::reference_internal,
"Transform this into a vector, Is not copied.")
.def("isDistributed", [](const SolverVector& self) { return self.isDistributed(); })
;
py::class_<TermsToAssemble::TermToAssemble>(mod, "TermToAssemble")
.def(py::init<Int, Int>())
.def(py::self += Real())
.def_property_readonly("i", &TermsToAssemble::TermToAssemble::i)
.def_property_readonly("j", &TermsToAssemble::TermToAssemble::j);
py::class_<TermsToAssemble>(mod, "TermsToAssemble")
.def(py::init<const ID &, const ID &>())
.def("getDOFIdM", &TermsToAssemble::getDOFIdM)
.def("getDOFIdN", &TermsToAssemble::getDOFIdN)
.def(
"__call__",
[](TermsToAssemble & self, UInt i, UInt j, Real val) {
auto & term = self(i, j);
term = val;
return term;
},
py::arg("i"), py::arg("j"), py::arg("val") = 0.,
py::return_value_policy::reference);
}
} // namespace akantu
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