Function test_basic_assembly

python/test/unit/fem/test_assembler.py:123–164

(mode, dtype)

@pytest.mark.parametrize("mode", [GhostMode.none, GhostMode.shared_facet])
@dtype_parametrize
def test_basic_assembly(mode, dtype):
    mesh = create_unit_square(MPI.COMM_WORLD, 12, 12, ghost_mode=mode, dtype=dtype(0).real.dtype)
    V = functionspace(mesh, ("Lagrange", 1))
    u, v = ufl.TrialFunction(V), ufl.TestFunction(V)

    f = Function(V, dtype=dtype)
    f.x.array[:] = 10.0
    a = inner(f * u, v) * dx + inner(u, v) * ds
    L = inner(f, v) * dx + inner(2.0, v) * ds
    a, L = form(a, dtype=dtype), form(L, dtype=dtype)

    # Initial assembly
    A = assemble_matrix(a)
    A.scatter_reverse()
    assert isinstance(A, la.MatrixCSR)
    b = assemble_vector(L)
    b.scatter_reverse(la.InsertMode.add)
    assert isinstance(b, la.Vector)

    # Second assembly
    normA = A.squared_norm()
    A.set_value(0)
    A = assemble_matrix(A, a)
    A.scatter_reverse()
    assert isinstance(A, la.MatrixCSR)
    assert normA == pytest.approx(A.squared_norm())
    normb = la.norm(b)
    b.array[:] = 0
    assemble_vector(b.array, L)
    b.scatter_reverse(la.InsertMode.add)
    assert normb == pytest.approx(la.norm(b))

    # Vector re-assembly - no zeroing (but need to zero ghost entries)
    b.array[b.index_map.size_local * b.block_size :] = 0
    assemble_vector(b.array, L)
    b.scatter_reverse(la.InsertMode.add)
    assert 2 * normb == pytest.approx(la.norm(b))

    # Matrix re-assembly (no zeroing)
    assemble_matrix(A, a)
    A.scatter_reverse()
    assert 4 * normA == pytest.approx(A.squared_norm())


def nest_matrix_norm(A):