Fri, 08 May 2026 17:16:34 -0500
Do not directly depend on ndarray, but through numpy
/// Minimisation code for second-order polynomial models from Fenics. #include <array> #include <cmath> #include <basix/finite-element.h> #include <dolfinx/fem/Function.h> #include <dolfinx/mesh/cell_types.h> #include <nanobind/nanobind.h> #include <nanobind/stl/array.h> // needed for array conversions in nanobind bindings. #include "dolfinx_access/minmax_p2.h" #include "pointsource_pde/src/dolfinx_access.rs.h" using namespace dolfinx::fem; using namespace basix::element; using namespace dolfinx_access; namespace dolfinx_access { // Since Fenics documentation is poor, and it does not seem to provide an easy way to access // an internal P2 model (that would not involve vomotting your guts out 🤮 dealing with the // putrid horror that C++ has become (and its documentation written by lawyers and bureacrats, // which is even worse than that of Fenics), our idea here is to simply assume that f is a // second-order polynomial on each cell, and then evaluate it on that cell at 6 points, to // construct a new model based on our existing P2 model code that is also used for minimising // arbitrary sums. inline CoordValuePair minmax_Function_f64_p2(Function<double> const* f, bool max) { auto v = f->x(); // Mesh auto fp = f->function_space(); auto mesh = fp->mesh(); auto geom = mesh->geometry(); auto topo = mesh->topology(); // Check that we're working with P2 elements // // Fenics defaults to GLL warped midpoint placement; see // https://docs.fenicsproject.org/dolfinx/v0.7.0.post0/python/demos/demo_lagrange_variants.html // This is not a problem with our current implementation, which works with an // second-order // polynomials due to duplication of effort (see above, why), but if we would directly // take the cell quadrature matrix from Fenics, we should restrict el.lagrange_variant() = // lagrange_variant::equispaced. auto el = fp->element()->basix_element(); // printf("%d %d %d %d\n", el.degree(), el.cell_type(), el.lagrange_variant(), // el.family()); if (el.degree() != 2 || el.cell_type() != basix::cell::type::triangle || /*el.lagrange_variant() != lagrange_variant::equispaced ||*/ el.family() != family::P) { throw "Only equispaced Lagrange second-order polynomial elements are supported"; } if (cell_num_entities(dolfinx::mesh::CellType::triangle, 0) != 3) { throw "A triangle should have three vertices"; } // Check that we are dealing with a scalar function if (fp->element()->value_shape().size() != 0) { throw "Only scalar functions are supported, obviously."; } // Check that we're in two dimensions if (topo->dim() != 2 || geom.dim() != 2) { throw "Only two-dimensional meshes are supported"; } // Check that there are no other types of eleemnts auto entity_types = topo->entity_types(2); for (auto& t : entity_types) { if (t != dolfinx::mesh::CellType::triangle) { throw "Only triangular meshes are supported"; } } auto adj = topo->connectivity(2, 0); auto n_cells = adj->num_nodes(); // assert(n_cells == n_triangles); // printf("cell count? %d\n", n_cells); // for (auto i = 0; i < n_cells; i++) { // // assert(adj->num_links(i) == 3); // Should not need this // auto d = fp->dofmap()->cell_dofs(i); // printf("%zd\n", d.size()); // } // DOF coordinates (may be more than nodes, e.g., intermediate points) auto gx = geom.x(); // auto num_points = gx.size() / 3; // Map from cells to DOF indices auto geom_dofmap = geom.dofmap(); assert(geom_dofmap.extent(0) == (size_t)n_cells); assert(geom_dofmap.extent(1) == 3); auto fp_dofmap = fp->dofmap(); // auto dof_coords = fp->tabulate_dof_coordinates(); CoordValuePair res{{{0.0, 0.0}}, INFINITY}; // printf("%zd %zd\n", v->array().size(), gx.size()); for (auto i = 0; i < n_cells; i++) { // Cell corners auto j0 = geom_dofmap(i, 0); auto j1 = geom_dofmap(i, 1); auto j2 = geom_dofmap(i, 2); // Construct list of coordinates. Due to f->eval, we construct this is a single list // with all the Fenics weirdness of hard-coded 3D. std::array<double, 9> x = {gx[3 * j0], gx[3 * j0 + 1], 0, gx[3 * j1], gx[3 * j1 + 1], 0, gx[3 * j2], gx[3 * j2 + 1], 0}; // Find the solution on the simplex. auto newres = minmax_dolfinx_p2_cell(f, x, i, max); // printf("%f [%f, %f] [%f %f %f %f %f %f] <%f, %f> <%f, %f> <‸%f, %f>\n", newres.v, // newres.x[0], newres.x[1], values[0], values[1], values[2], values[3], // values[4], values[5], x[0], x[1], x[3], x[4], x[6], x[7]); if (newres.v < res.v) { res = newres; } // // Full DOF data // auto d = fp_dofmap->cell_dofs(i); // // TODO: array() gives just local part of vector // assert(d.size() == 6); // for (auto k = 0; k < d.size(); k++) { // auto j = d[k]; // // printf("%d %d\n", 3 * j + 1, nodes.size()); // assert(2 * j + 1 <= nodes.size()); // auto x = {nodes[3 * j], nodes[3 * j + 1]}; // } } // Negate result if maximising. if (max) { res.v = -res.v; } return res; } CoordValuePair min_Function_f64_p2(Function<double> const* f) { return minmax_Function_f64_p2(f, false); } CoordValuePair max_Function_f64_p2(Function<double> const* f) { return minmax_Function_f64_p2(f, true); } // Create a Python module as well NB_MODULE(_dolfinx_access, m) { m.def("min_Function_f64_p2", &min_Function_f64_p2); m.def("max_Function_f64_p2", &max_Function_f64_p2); m.def("minmax_Function_f64_p2", &minmax_Function_f64_p2); m.def("eval_Function_f64", &eval_Function_f64); m.def("cell_Function_f64", &cell_Function_f64); // m.def("cell_Mesh_f64", &cell_Mesh_f64); m.def("cell_FunctionSpace_f64", &cell_FunctionSpace_f64); nanobind::class_<CoordValuePair>(m, "CoordValuePair") .def_rw("x", &CoordValuePair::x) .def_rw("v", &CoordValuePair::v); } } // namespace dolfinx_access // Forward declaration for manual registration extern "C" PyObject* PyInit__dolfinx_access();