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// Copyright (C) 2017-2023 Chris Richardson and Garth N. Wells
//
// This file is part of DOLFINx (https://www.fenicsproject.org)
//
// SPDX-License-Identifier: LGPL-3.0-or-later
#if defined(HAS_PETSC) && defined(HAS_PETSC4PY)
#include "array.h"
#include "caster_mpi.h"
#include "caster_petsc.h"
#include "pycoeff.h"
#include <dolfinx/common/IndexMap.h>
#include <dolfinx/fem/DirichletBC.h>
#include <dolfinx/fem/DofMap.h>
#include <dolfinx/fem/FiniteElement.h>
#include <dolfinx/fem/Form.h>
#include <dolfinx/fem/FunctionSpace.h>
#include <dolfinx/fem/assembler.h>
#include <dolfinx/fem/discreteoperators.h>
#include <dolfinx/fem/petsc.h>
#include <dolfinx/fem/sparsitybuild.h>
#include <dolfinx/fem/utils.h>
#include <dolfinx/la/SparsityPattern.h>
#include <dolfinx/la/petsc.h>
#include <dolfinx/mesh/Mesh.h>
#include <dolfinx/nls/NewtonSolver.h>
#include <nanobind/nanobind.h>
#include <nanobind/ndarray.h>
#include <nanobind/stl/complex.h>
#include <nanobind/stl/function.h>
#include <nanobind/stl/map.h>
#include <nanobind/stl/pair.h>
#include <nanobind/stl/shared_ptr.h>
#include <nanobind/stl/string.h>
#include <nanobind/stl/tuple.h>
#include <nanobind/stl/vector.h>
#include <petsc4py/petsc4py.h>
#include <petscis.h>
namespace
{
// Declare assembler function that have multiple scalar types
template <typename T, typename U>
void declare_petsc_discrete_operators(nb::module_& m)
{
m.def(
"discrete_gradient",
[](const dolfinx::fem::FunctionSpace<U>& V0,
const dolfinx::fem::FunctionSpace<U>& V1)
{
assert(V0.mesh());
auto mesh = V0.mesh();
assert(V1.mesh());
assert(mesh == V1.mesh());
MPI_Comm comm = mesh->comm();
auto dofmap0 = V0.dofmap();
assert(dofmap0);
auto dofmap1 = V1.dofmap();
assert(dofmap1);
// Create and build sparsity pattern
assert(dofmap0->index_map);
assert(dofmap1->index_map);
dolfinx::la::SparsityPattern sp(
comm, {dofmap1->index_map, dofmap0->index_map},
{dofmap1->index_map_bs(), dofmap0->index_map_bs()});
int tdim = mesh->topology()->dim();
auto map = mesh->topology()->index_map(tdim);
assert(map);
std::vector<std::int32_t> c(map->size_local(), 0);
std::iota(c.begin(), c.end(), 0);
dolfinx::fem::sparsitybuild::cells(sp, {c, c}, {*dofmap1, *dofmap0});
sp.finalize();
// Build operator
Mat A = dolfinx::la::petsc::create_matrix(comm, sp);
MatSetOption(A, MAT_IGNORE_ZERO_ENTRIES, PETSC_TRUE);
dolfinx::fem::discrete_gradient<T, U>(
*V0.mesh()->topology_mutable(), {*V0.element(), *V0.dofmap()},
{*V1.element(), *V1.dofmap()},
dolfinx::la::petsc::Matrix::set_fn(A, INSERT_VALUES));
return A;
},
nb::rv_policy::take_ownership, nb::arg("V0"), nb::arg("V1"));
m.def(
"interpolation_matrix",
[](const dolfinx::fem::FunctionSpace<U>& V0,
const dolfinx::fem::FunctionSpace<U>& V1)
{
assert(V0.mesh());
auto mesh = V0.mesh();
assert(V1.mesh());
assert(mesh == V1.mesh());
MPI_Comm comm = mesh->comm();
auto dofmap0 = V0.dofmap();
assert(dofmap0);
auto dofmap1 = V1.dofmap();
assert(dofmap1);
// Create and build sparsity pattern
assert(dofmap0->index_map);
assert(dofmap1->index_map);
dolfinx::la::SparsityPattern sp(
comm, {dofmap1->index_map, dofmap0->index_map},
{dofmap1->index_map_bs(), dofmap0->index_map_bs()});
int tdim = mesh->topology()->dim();
auto map = mesh->topology()->index_map(tdim);
assert(map);
std::vector<std::int32_t> c(map->size_local(), 0);
std::iota(c.begin(), c.end(), 0);
dolfinx::fem::sparsitybuild::cells(sp, {c, c}, {*dofmap1, *dofmap0});
sp.finalize();
// Build operator
Mat A = dolfinx::la::petsc::create_matrix(comm, sp);
MatSetOption(A, MAT_IGNORE_ZERO_ENTRIES, PETSC_TRUE);
dolfinx::fem::interpolation_matrix<T, U>(
V0, V1, dolfinx::la::petsc::Matrix::set_block_fn(A, INSERT_VALUES));
return A;
},
nb::rv_policy::take_ownership, nb::arg("V0"), nb::arg("V1"));
}
void petsc_la_module(nb::module_& m)
{
import_petsc4py();
m.def(
"create_matrix",
[](dolfinx_wrappers::MPICommWrapper comm,
const dolfinx::la::SparsityPattern& p, const std::string& type)
{
Mat A = dolfinx::la::petsc::create_matrix(comm.get(), p, type);
PyObject* obj = PyPetscMat_New(A);
PetscObjectDereference((PetscObject)A);
return nb::borrow(obj);
},
nb::arg("comm"), nb::arg("p"), nb::arg("type") = std::string(),
"Create a PETSc Mat from sparsity pattern.");
m.def(
"create_index_sets",
[](const std::vector<std::pair<const common::IndexMap*, int>>& maps)
{
std::vector<
std::pair<std::reference_wrapper<const common::IndexMap>, int>>
_maps;
for (auto m : maps)
_maps.push_back({*m.first, m.second});
std::vector<IS> index_sets
= dolfinx::la::petsc::create_index_sets(_maps);
std::vector<nb::object> py_index_sets;
for (auto is : index_sets)
{
PyObject* obj = PyPetscIS_New(is);
PetscObjectDereference((PetscObject)is);
py_index_sets.push_back(nb::steal(obj));
}
return py_index_sets;
},
nb::arg("maps"));
m.def(
"scatter_local_vectors",
[](Vec x,
const std::vector<
nb::ndarray<const PetscScalar, nb::ndim<1>, nb::c_contig>>& x_b,
const std::vector<std::pair<
std::shared_ptr<const dolfinx::common::IndexMap>, int>>& maps)
{
std::vector<std::span<const PetscScalar>> _x_b;
std::vector<std::pair<
std::reference_wrapper<const dolfinx::common::IndexMap>, int>>
_maps;
for (auto& array : x_b)
_x_b.emplace_back(array.data(), array.size());
for (auto q : maps)
_maps.push_back({*q.first, q.second});
dolfinx::la::petsc::scatter_local_vectors(x, _x_b, _maps);
},
nb::arg("x"), nb::arg("x_b"), nb::arg("maps"),
"Scatter the (ordered) list of sub vectors into a block "
"vector.");
m.def(
"get_local_vectors",
[](const Vec x,
const std::vector<std::pair<
std::shared_ptr<const dolfinx::common::IndexMap>, int>>& maps)
{
std::vector<std::pair<
std::reference_wrapper<const dolfinx::common::IndexMap>, int>>
_maps;
for (auto m : maps)
_maps.push_back({*m.first, m.second});
std::vector<std::vector<PetscScalar>> vecs
= dolfinx::la::petsc::get_local_vectors(x, _maps);
std::vector<nb::ndarray<PetscScalar, nb::numpy>> ret;
for (std::vector<PetscScalar>& v : vecs)
ret.push_back(dolfinx_wrappers::as_nbarray(std::move(v)));
return ret;
},
nb::arg("x"), nb::arg("maps"),
"Gather an (ordered) list of sub vectors from a block vector.");
}
void petsc_fem_module(nb::module_& m)
{
// Create PETSc vectors and matrices
m.def(
"create_vector_block",
[](const std::vector<
std::pair<std::shared_ptr<const common::IndexMap>, int>>& maps)
{
std::vector<
std::pair<std::reference_wrapper<const common::IndexMap>, int>>
_maps;
for (auto q : maps)
_maps.push_back({*q.first, q.second});
return dolfinx::fem::petsc::create_vector_block(_maps);
},
nb::rv_policy::take_ownership, nb::arg("maps"),
"Create a monolithic vector for multiple (stacked) linear forms.");
m.def(
"create_vector_nest",
[](const std::vector<
std::pair<std::shared_ptr<const common::IndexMap>, int>>& maps)
{
std::vector<
std::pair<std::reference_wrapper<const common::IndexMap>, int>>
_maps;
for (auto m : maps)
_maps.push_back({*m.first, m.second});
return dolfinx::fem::petsc::create_vector_nest(_maps);
},
nb::rv_policy::take_ownership, nb::arg("maps"),
"Create nested vector for multiple (stacked) linear forms.");
m.def("create_matrix", dolfinx::fem::petsc::create_matrix<PetscReal>,
nb::rv_policy::take_ownership, nb::arg("a"),
nb::arg("type") = std::string(),
"Create a PETSc Mat for bilinear form.");
m.def("create_matrix_block",
&dolfinx::fem::petsc::create_matrix_block<PetscReal>,
nb::rv_policy::take_ownership, nb::arg("a"),
nb::arg("type") = std::string(),
"Create monolithic sparse matrix for stacked bilinear forms.");
m.def("create_matrix_nest",
&dolfinx::fem::petsc::create_matrix_nest<PetscReal>,
nb::rv_policy::take_ownership, nb::arg("a"),
nb::arg("types") = std::vector<std::vector<std::string>>(),
"Create nested sparse matrix for bilinear forms.");
// PETSc Matrices
m.def(
"assemble_matrix",
[](Mat A, const dolfinx::fem::Form<PetscScalar, PetscReal>& a,
nb::ndarray<const PetscScalar, nb::ndim<1>, nb::c_contig> constants,
const std::map<std::pair<dolfinx::fem::IntegralType, int>,
nb::ndarray<const PetscScalar, nb::ndim<2>,
nb::c_contig>>& coefficients,
const std::vector<std::shared_ptr<
const dolfinx::fem::DirichletBC<PetscScalar, PetscReal>>>& bcs,
bool unrolled)
{
if (unrolled)
{
auto set_fn = dolfinx::la::petsc::Matrix::set_block_expand_fn(
A, a.function_spaces()[0]->dofmap()->bs(),
a.function_spaces()[1]->dofmap()->bs(), ADD_VALUES);
dolfinx::fem::assemble_matrix(
set_fn, a, std::span(constants.data(), constants.size()),
py_to_cpp_coeffs(coefficients), bcs);
}
else
{
dolfinx::fem::assemble_matrix(
dolfinx::la::petsc::Matrix::set_block_fn(A, ADD_VALUES), a,
std::span(constants.data(), constants.size()),
py_to_cpp_coeffs(coefficients), bcs);
}
},
nb::arg("A"), nb::arg("a"), nb::arg("constants"), nb::arg("coeffs"),
nb::arg("bcs"), nb::arg("unrolled") = false,
"Assemble bilinear form into an existing PETSc matrix");
m.def(
"assemble_matrix",
[](Mat A, const dolfinx::fem::Form<PetscScalar, PetscReal>& a,
nb::ndarray<const PetscScalar, nb::ndim<1>, nb::c_contig> constants,
const std::map<std::pair<dolfinx::fem::IntegralType, int>,
nb::ndarray<const PetscScalar, nb::ndim<2>,
nb::c_contig>>& coefficients,
nb::ndarray<const std::int8_t, nb::ndim<1>, nb::c_contig> rows0,
nb::ndarray<const std::int8_t, nb::ndim<1>, nb::c_contig> rows1,
bool unrolled)
{
std::function<int(std::span<const std::int32_t>,
std::span<const std::int32_t>,
std::span<const PetscScalar>)>
set_fn;
if (unrolled)
{
set_fn = dolfinx::la::petsc::Matrix::set_block_expand_fn(
A, a.function_spaces()[0]->dofmap()->bs(),
a.function_spaces()[1]->dofmap()->bs(), ADD_VALUES);
}
else
set_fn = dolfinx::la::petsc::Matrix::set_block_fn(A, ADD_VALUES);
dolfinx::fem::assemble_matrix(
set_fn, a, std::span(constants.data(), constants.size()),
py_to_cpp_coeffs(coefficients),
std::span(rows0.data(), rows0.size()),
std::span(rows1.data(), rows1.size()));
},
nb::arg("A"), nb::arg("a"), nb::arg("constants"), nb::arg("coeffs"),
nb::arg("rows0"), nb::arg("rows1"), nb::arg("unrolled") = false);
m.def(
"insert_diagonal",
[](Mat A, const dolfinx::fem::FunctionSpace<PetscReal>& V,
const std::vector<std::shared_ptr<
const dolfinx::fem::DirichletBC<PetscScalar, PetscReal>>>& bcs,
PetscScalar diagonal)
{
dolfinx::fem::set_diagonal(
dolfinx::la::petsc::Matrix::set_fn(A, INSERT_VALUES), V, bcs,
diagonal);
},
nb::arg("A"), nb::arg("V"), nb::arg("bcs"), nb::arg("diagonal"));
declare_petsc_discrete_operators<PetscScalar, PetscReal>(m);
}
void petsc_nls_module(nb::module_& m)
{
// dolfinx::NewtonSolver
nb::class_<dolfinx::nls::petsc::NewtonSolver>(m, "NewtonSolver")
.def(
"__init__",
[](dolfinx::nls::petsc::NewtonSolver* ns,
const dolfinx_wrappers::MPICommWrapper comm)
{ new (ns) dolfinx::nls::petsc::NewtonSolver(comm.get()); },
nb::arg("comm"))
.def_prop_ro("krylov_solver",
[](const dolfinx::nls::petsc::NewtonSolver& self)
{
KSP ksp = self.get_krylov_solver().ksp();
PyObject* obj = PyPetscKSP_New(ksp);
return nb::steal(obj);
})
.def("setF", &dolfinx::nls::petsc::NewtonSolver::setF, nb::arg("F"),
nb::arg("b"))
.def("setJ", &dolfinx::nls::petsc::NewtonSolver::setJ, nb::arg("J"),
nb::arg("Jmat"))
.def("setP", &dolfinx::nls::petsc::NewtonSolver::setP, nb::arg("P"),
nb::arg("Pmat"))
.def(
"set_update",
[](dolfinx::nls::petsc::NewtonSolver& self,
std::function<void(const dolfinx::nls::petsc::NewtonSolver* solver,
const Vec, Vec)>
update) // See
// https://github.com/wjakob/nanobind/discussions/361
// on why we pass NewtonSolver* rather than
// NewtonSolver&
{
self.set_update(
[update](const dolfinx::nls::petsc::NewtonSolver& solver,
const Vec dx, Vec x) { update(&solver, dx, x); });
},
nb::arg("update"))
.def(
"set_convergence_check",
[](dolfinx::nls::petsc::NewtonSolver& self,
std::function<std::pair<double, bool>(
const dolfinx::nls::petsc::NewtonSolver* solver, const Vec)>
convergence_check) // See
// https://github.com/wjakob/nanobind/discussions/361
// on why we pass NewtonSolver* rather than
// NewtonSolver&
{
self.set_convergence_check(
[convergence_check](
const dolfinx::nls::petsc::NewtonSolver& solver,
const Vec r) { return convergence_check(&solver, r); });
},
nb::arg("convergence_check"))
.def("set_form", &dolfinx::nls::petsc::NewtonSolver::set_form,
nb::arg("form"))
.def("solve", &dolfinx::nls::petsc::NewtonSolver::solve, nb::arg("x"))
.def_rw("atol", &dolfinx::nls::petsc::NewtonSolver::atol,
"Absolute tolerance")
.def_rw("rtol", &dolfinx::nls::petsc::NewtonSolver::rtol,
"Relative tolerance")
.def_rw("error_on_nonconvergence",
&dolfinx::nls::petsc::NewtonSolver::error_on_nonconvergence)
.def_rw("report", &dolfinx::nls::petsc::NewtonSolver::report)
.def_rw("relaxation_parameter",
&dolfinx::nls::petsc::NewtonSolver::relaxation_parameter,
"Relaxation parameter")
.def_rw("max_it", &dolfinx::nls::petsc::NewtonSolver::max_it,
"Maximum number of iterations")
.def_rw("convergence_criterion",
&dolfinx::nls::petsc::NewtonSolver::convergence_criterion,
"Convergence criterion, either 'residual' (default) or "
"'incremental'");
}
} // namespace
namespace dolfinx_wrappers
{
void petsc(nb::module_& m_fem, nb::module_& m_la, nb::module_& m_nls)
{
nb::module_ petsc_fem_mod
= m_fem.def_submodule("petsc", "PETSc-specific finite element module");
petsc_fem_module(petsc_fem_mod);
nb::module_ petsc_la_mod
= m_la.def_submodule("petsc", "PETSc-specific linear algebra module");
petsc_la_module(petsc_la_mod);
nb::module_ petsc_nls_mod
= m_nls.def_submodule("petsc", "PETSc-specific nonlinear solvers");
petsc_nls_module(petsc_nls_mod);
}
} // namespace dolfinx_wrappers
#endif
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