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#include <medusa/Medusa.hpp>
#include <Eigen/SparseCore>
#include <Eigen/IterativeLinearSolvers>
#include <cmath>
/// Custom RBF example. Solves Poisson equation.
/// http://e6.ijs.si/medusa/wiki/index.php/Customization
using namespace mm; // NOLINT
/// f(r) = r^3 + r^5.
class MyRBF {
public:
typedef double scalar_t;
double operator()(double r2) const {
double r = std::sqrt(r2);
return ipow<3>(r) + ipow<5>(r);
}
template <int dim>
double operator()(double r2, Lap<dim>) const {
double r = std::sqrt(r2);
return 3*(dim+1)*r + 5*(dim+3)*ipow<3>(r);
}
};
int main() {
// Create the domain and discretize it
BallShape<Vec2d> b(0.0, 1.0);
double dx = 0.05;
DomainDiscretization <Vec2d> domain = b.discretizeBoundaryWithStep(dx);
// fill the domain
GeneralFill <Vec2d> fill;
fill.seed(999);
domain.fill(fill, dx);
int N = domain.size();
FindClosest find_support(12);
domain.findSupport(find_support);
RBFFD<MyRBF, Vec2d, ScaleToClosest> appr({}, Monomials<Vec2d>(2));
auto storage = domain.computeShapes<sh::lap>(appr);
Eigen::SparseMatrix<double, Eigen::RowMajor> M(N, N);
Eigen::VectorXd rhs(N); rhs.setZero();
Range<int> reserve = storage.supportSizes();
auto op = storage.implicitOperators(M, rhs);
M.reserve(storage.supportSizes());
for (int i : domain.interior()) {
double x = domain.pos(i, 0);
double y = domain.pos(i, 1);
op.lap(i) = -2*PI*PI*std::sin(x)*std::sin(y);
}
for (int i : domain.boundary()) {
double x = domain.pos(i, 0);
double y = domain.pos(i, 1);
op.value(i) = std::sin(x) * std::sin(y);
}
Eigen::BiCGSTAB<decltype(M), Eigen::IncompleteLUT<double>> solver;
solver.compute(M);
ScalarFieldd u = solver.solve(rhs);
// Write the solution into file
std::ofstream out_file("custom_rbf_data.m");
out_file << "positions = " << domain.positions() << ";" << std::endl;
out_file << "solution = " << u << ";" << std::endl;
out_file.close();
return 0;
}