Function test_matrix

cpp/test/matrix.cpp:129–172

}

void test_matrix()
{
  auto map0 = std::make_shared<common::IndexMap>(MPI_COMM_WORLD, 8);
  la::SparsityPattern p(MPI_COMM_WORLD, {map0, map0}, {1, 1});
  p.insert(0, 0);
  p.insert(4, 5);
  p.insert(5, 4);
  p.finalize();

  using T = float;
  la::MatrixCSR<T> A(p);
  A.add(std::vector<decltype(A)::value_type>{1}, std::vector{0},
        std::vector{0});
  A.add(std::vector<decltype(A)::value_type>{2.3}, std::vector{4},
        std::vector{5});

  const std::vector Adense0 = A.to_dense();

  // Note: we cut off the ghost rows by intent here! But therefore we are not
  // able to work with the dimensions of Adense0 to compute indices, these
  // contain the ghost rows, which also vary between processes.
  md::mdspan<const T, md::extents<std::size_t, 8, md::dynamic_extent>> Adense(
      Adense0.data(), 8, A.index_map(1)->size_global());

  std::vector<T> Aref_data(8 * A.index_map(1)->size_global(), 0);
  md::mdspan<T, md::extents<std::size_t, 8, md::dynamic_extent>> Aref(
      Aref_data.data(), 8, A.index_map(1)->size_global());

  auto to_global_col = [&](auto col)
  {
    std::array<std::int64_t, 1> tmp;
    A.index_map(1)->local_to_global(std::vector<std::int32_t>{col}, tmp);
    return tmp[0];
  };
  Aref(0, to_global_col(0)) = 1;
  Aref(4, to_global_col(5)) = 2.3;

  for (std::size_t i = 0; i < Adense.extent(0); ++i)
    for (std::size_t j = 0; j < Adense.extent(1); ++j)
      CHECK(Adense(i, j) == Aref(i, j));

  Aref(4, to_global_col(4)) = 2.3;
  CHECK(Adense(4, to_global_col(4)) != Aref(4, to_global_col(4)));
}

} // namespace