def iter_grids():
"""generate some test grids"""
yield grids.UnitGrid([2, 2], periodic=[True, False])
yield grids.CartesianGrid([[0, 1]], [2], periodic=[False])
yield grids.CylindricalSymGrid(2, (0, 2), (2, 2), periodic_z=True)
yield grids.SphericalSymGrid(2, 2)
yield grids.PolarSymGrid(2, 2)
def iter_grids():
"""generator providing some test grids"""
for periodic in [True, False]:
yield grids.UnitGrid([3], periodic=periodic)
yield grids.UnitGrid([3, 3, 3], periodic=periodic)
yield grids.CartesianGrid([[-1, 2], [0, 3]], [5, 7], periodic=periodic)
yield grids.CylindricalSymGrid(3, [-1, 2], [7, 8], periodic_z=periodic)
yield grids.PolarSymGrid(3, 4)
yield grids.SphericalSymGrid(3, 4)
def iter_grids():
"""helper function iterating over different grids"""
for periodic in [True, False]:
yield grids.UnitGrid([3, 4], periodic=periodic)
yield grids.CartesianGrid([[0, 1], [-2, 3]], [4, 5],
periodic=periodic)
yield grids.CylindricalSymGrid(3, [-1, 2], [5, 7],
periodic_z=periodic)
yield grids.SphericalSymGrid(4, 6)
yield grids.PolarSymGrid(4, 5)
def test_anti_periodic_bcs():
"""test a simulation with anti-periodic BCs"""
grid = grids.CartesianGrid([[-10, 10]], 32, periodic=True)
field = ScalarField.from_expression(grid, "0.01 * x**2")
field -= field.average
# test normal periodic BCs
eq1 = PDE({"c": "laplace(c) + c - c**3"}, bc="periodic")
res1 = eq1.solve(field, t_range=1e5, dt=1e-1)
assert np.allclose(np.abs(res1.data), 1)
assert res1.fluctuations == pytest.approx(0)
# test normal anti-periodic BCs
eq2 = PDE({"c": "laplace(c) + c - c**3"}, bc="anti-periodic")
res2 = eq2.solve(field, t_range=1e3, dt=1e-3)
assert np.all(np.abs(res2.data) <= 1)
assert res2.fluctuations > 0.1
def test_normalize_point(reflect):
""" test normalize_point method """
grid = grids.CartesianGrid([[1, 3]], [1], periodic=False)
norm_numba = grid.make_normalize_point_compiled(reflect=reflect)
def norm_numba_wrap(x):
y = np.array([x])
norm_numba(y)
return y
if reflect:
values = [(0, 2), (1, 1), (2, 2), (3, 3), (4, 2), (5, 1), (6, 2)]
else:
values = [(0, 0), (1, 1), (2, 2), (3, 3), (4, 4), (5, 5), (6, 6)]
for norm in [
norm_numba_wrap,
partial(grid.normalize_point, reflect=reflect)
]:
for x, y in values:
assert norm(x) == pytest.approx(y), (norm, x)
