@pytest.mark.parametrize(
"problem, max_k",
[
(Square(), 6),
(Disk(), 4),
(Cube(), 4),
# Disable Ball() to avoid broken gmsh on gh-actions TODO enable
# (Ball(), 3)
],
)
def test(problem, max_k):
H, error_norm_1, error_norm_inf, order_1, order_inf = solve(problem, max_k)
expected_order = 2
tol = 5.0e-2
assert order_1[-1] > expected_order - tol
assert order_inf[-1] > expected_order - tol
if __name__ == "__main__":
# problem = Square()
problem = Disk()
# problem = Cube()
# problem = Ball()
max_k = 6
H, error_norm_1, error_norm_inf, order_1, order_inf = solve(problem,
max_k,
verbose=True)
helpers.show_error_data(H, error_norm_1, error_norm_inf)
def jacobian_solver(u0, rhs):
from scipy.sparse import linalg
jac = jacobian.get_linear_operator(u0)
return linalg.spsolve(jac, rhs)
u0 = numpy.zeros(len(mesh.node_coords))
u = pyfvm.newton(f.eval, jacobian_solver, u0, verbose=False)
return u
return helpers.perform_convergence_tests(
solver, problem.exact_sol, problem.get_mesh, range(max_k), verbose=verbose
)
@pytest.mark.parametrize(
"problem, max_k", [(Square(), 6), (Circle(), 4), (Cube(), 4), (Ball(), 3)]
)
def test(problem, max_k):
H, error_norm_1, error_norm_inf, order_1, order_inf = solve(problem, max_k)
expected_order = 2
tol = 5.0e-2
assert order_1[-1] > expected_order - tol
assert order_inf[-1] > expected_order - tol
return
if __name__ == "__main__":
H, error_norm_1, error_norm_inf, order_1, order_inf = solve(verbose=True)
helpers.show_error_data(H, error_norm_1, error_norm_inf)