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 test_grid_plotting():
"""test plotting of grids"""
grids.UnitGrid([4]).plot()
grids.UnitGrid([4, 4]).plot()
with pytest.raises(NotImplementedError):
grids.UnitGrid([4, 4, 4]).plot()
grids.PolarSymGrid(4, 8).plot()
grids.PolarSymGrid((2, 4), 8).plot()
def test_pde_wrong_input():
"""test some wrong input"""
with pytest.raises(ValueError):
PDE({"t": 1})
with pytest.raises(ValueError):
PDE({"E": 1})
with pytest.raises(ValueError):
PDE({"E": 1, "t": 0})
grid = grids.UnitGrid([4])
eq = PDE({"u": 1})
assert eq.expressions == {"u": "1.0"}
with pytest.raises(ValueError):
eq.evolution_rate(FieldCollection.scalar_random_uniform(2, grid))
eq = PDE({"u": 1, "v": 2})
assert eq.expressions == {"u": "1.0", "v": "2.0"}
with pytest.raises(ValueError):
eq.evolution_rate(ScalarField.random_uniform(grid))
eq = PDE({"u": "a"})
with pytest.raises(RuntimeError):
eq.evolution_rate(ScalarField.random_uniform(grid))
eq = PDE({"x": "x"})
with pytest.raises(ValueError):
eq.evolution_rate(ScalarField(grid))
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 test_pde_critical_input():
"""test some wrong input and edge cases"""
# test whether reserved symbols can be used as variables
grid = grids.UnitGrid([4])
eq = PDE({"E": 1})
res = eq.solve(ScalarField(grid), t_range=2)
np.testing.assert_allclose(res.data, 2)
with pytest.raises(ValueError):
PDE({"t": 1})
eq = PDE({"u": 1})
assert eq.expressions == {"u": "1.0"}
with pytest.raises(ValueError):
eq.evolution_rate(FieldCollection.scalar_random_uniform(2, grid))
eq = PDE({"u": 1, "v": 2})
assert eq.expressions == {"u": "1.0", "v": "2.0"}
with pytest.raises(ValueError):
eq.evolution_rate(ScalarField.random_uniform(grid))
eq = PDE({"u": "a"})
with pytest.raises(RuntimeError):
eq.evolution_rate(ScalarField.random_uniform(grid))
eq = PDE({"x": "x"})
with pytest.raises(ValueError):
eq.evolution_rate(ScalarField(grid))
def test_pde_bcs_error(bc):
"""test PDE with wrong boundary conditions"""
eq = PDE({"u": "laplace(u)"}, bc=bc)
grid = grids.UnitGrid([8, 8])
field = ScalarField.random_normal(grid)
for backend in ["numpy", "numba"]:
with pytest.raises(BCDataError):
eq.solve(field, t_range=1, dt=0.01, backend=backend, tracker=None)
def test_pde_user_funcs():
"""test user supplied functions"""
# test a simple case
eq = PDE({"u": "get_x(gradient(u))"}, user_funcs={"get_x": lambda arr: arr[0]})
field = ScalarField.random_colored(grids.UnitGrid([32, 32]))
rhs = eq.evolution_rate(field)
np.testing.assert_allclose(rhs.data, field.gradient("natural").data[0])
f = eq._make_pde_rhs_numba(field)
np.testing.assert_allclose(f(field.data, 0), field.gradient("natural").data[0])
def test_pde_product_operators():
"""test inner and outer products"""
eq = PDE(
{"p": "gradient(dot(p, p) + inner(p, p)) + tensor_divergence(outer(p, p))"}
)
assert not eq.explicit_time_dependence
assert not eq.complex_valued
field = VectorField(grids.UnitGrid([4]), 1)
res = eq.solve(field, t_range=1, dt=0.1, backend="numpy", tracker=None)
np.testing.assert_allclose(res.data, field.data)
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_pde_time_dependent_bcs(backend):
"""test PDE with time-dependent BCs"""
field = ScalarField(grids.UnitGrid([3]))
eq = PDE({"c": "laplace(c)"}, bc={"value_expression": "Heaviside(t - 1.5)"})
storage = MemoryStorage()
eq.solve(field, t_range=10, dt=1e-2, backend=backend, tracker=storage.tracker(1))
np.testing.assert_allclose(storage[1].data, 0)
np.testing.assert_allclose(storage[-1].data, 1, rtol=1e-3)
def test_pde_vector():
"""test PDE with a single vector field"""
eq = PDE({"u": "vector_laplace(u) + exp(-t)"})
assert eq.explicit_time_dependence
assert not eq.complex_valued
grid = grids.UnitGrid([8, 8])
field = VectorField.random_normal(grid)
res_a = eq.solve(field, t_range=1, dt=0.01, backend="numpy", tracker=None)
res_b = eq.solve(field, t_range=1, dt=0.01, backend="numba", tracker=None)
res_a.assert_field_compatible(res_b)
np.testing.assert_allclose(res_a.data, res_b.data)
def test_pde_2scalar():
"""test PDE with two scalar fields"""
eq = PDE({"u": "laplace(u) - u", "v": "- u * v"})
assert not eq.explicit_time_dependence
assert not eq.complex_valued
grid = grids.UnitGrid([8])
field = FieldCollection.scalar_random_uniform(2, grid)
res_a = eq.solve(field, t_range=1, dt=0.01, backend="numpy", tracker=None)
res_b = eq.solve(field, t_range=1, dt=0.01, backend="numba", tracker=None)
res_a.assert_field_compatible(res_b)
np.testing.assert_allclose(res_a.data, res_b.data)
def test_pde_bcs(bc):
"""test PDE with boundary conditions"""
eq = PDE({"u": "laplace(u)"}, bc=bc)
assert not eq.explicit_time_dependence
assert not eq.complex_valued
grid = grids.UnitGrid([8])
field = ScalarField.random_normal(grid)
res_a = eq.solve(field, t_range=1, dt=0.01, backend="numpy", tracker=None)
res_b = eq.solve(field, t_range=1, dt=0.01, backend="numba", tracker=None)
res_a.assert_field_compatible(res_b)
np.testing.assert_allclose(res_a.data, res_b.data)
def test_pde_complex():
"""test complex valued PDE"""
eq = PDE({"p": "I * laplace(p)"})
assert not eq.explicit_time_dependence
assert eq.complex_valued
field = ScalarField.random_uniform(grids.UnitGrid([4]))
assert not field.is_complex
res1 = eq.solve(field, t_range=1, dt=0.1, backend="numpy", tracker=None)
assert res1.is_complex
res2 = eq.solve(field, t_range=1, dt=0.1, backend="numpy", tracker=None)
assert res2.is_complex
np.testing.assert_allclose(res1.data, res2.data)
def test_pde_spatial_args():
""" test ScalarFieldExpression without extra dependence """
eq = PDE({"a": "x"})
field = ScalarField(grids.UnitGrid([2]))
rhs = eq.evolution_rate(field)
assert rhs == field.copy(data=[0.5, 1.5])
rhs = eq.make_pde_rhs(field, backend="numba")
np.testing.assert_allclose(rhs(field.data, 0.0), np.array([0.5, 1.5]))
eq = PDE({"a": "x + y"})
with pytest.raises(RuntimeError):
eq.evolution_rate(field)
def test_pde_integral(backend):
"""test PDE with integral"""
grid = grids.UnitGrid([16])
field = ScalarField.random_uniform(grid)
eq = PDE({"c": "-integral(c)"})
# test rhs
rhs = eq.make_pde_rhs(field, backend=backend)
np.testing.assert_allclose(rhs(field.data, 0), -field.integral)
# test evolution
for method in ["scipy", "explicit"]:
res = eq.solve(field, t_range=1000, method=method, tracker=None)
assert res.integral == pytest.approx(0, abs=1e-2)
np.testing.assert_allclose(res.data, field.data - field.magnitude, atol=1e-3)
def test_pde_vector_scalar():
"""test PDE with a vector and a scalar field"""
eq = PDE({"u": "vector_laplace(u) - u + gradient(v)", "v": "- divergence(u)"})
assert not eq.explicit_time_dependence
assert not eq.complex_valued
grid = grids.UnitGrid([8, 8])
field = FieldCollection(
[VectorField.random_uniform(grid), ScalarField.random_uniform(grid)]
)
res_a = eq.solve(field, t_range=1, dt=0.01, backend="numpy", tracker=None)
res_b = eq.solve(field, t_range=1, dt=0.01, backend="numba", tracker=None)
res_a.assert_field_compatible(res_b)
np.testing.assert_allclose(res_a.data, res_b.data)
def test_pde_noise(backend):
"""test noise operator on PDE class"""
grid = grids.UnitGrid([64, 64])
state = FieldCollection([ScalarField(grid), ScalarField(grid)])
eq = PDE({"a": 0, "b": 0}, noise=0.5)
res = eq.solve(state, t_range=1, backend=backend, dt=1, tracker=None)
assert res.data.std() == pytest.approx(0.5, rel=0.1)
eq = PDE({"a": 0, "b": 0}, noise=[0.01, 2.0])
res = eq.solve(state, t_range=1, backend=backend, dt=1)
assert res.data[0].std() == pytest.approx(0.01, rel=0.1)
assert res.data[1].std() == pytest.approx(2.0, rel=0.1)
with pytest.raises(ValueError):
eq = PDE({"a": 0}, noise=[0.01, 2.0])
eq.solve(ScalarField(grid), t_range=1, backend=backend, dt=1, tracker=None)
def test_pde_spatial_args(backend):
"""test PDE with spatial dependence"""
field = ScalarField(grids.UnitGrid([2]))
eq = PDE({"a": "x"})
rhs = eq.make_pde_rhs(field, backend=backend)
np.testing.assert_allclose(rhs(field.data, 0.0), np.array([0.5, 1.5]))
# test combination of spatial dependence and differential oeprators
eq = PDE({"a": "dot(gradient(x), gradient(a))"})
rhs = eq.make_pde_rhs(field, backend=backend)
np.testing.assert_allclose(rhs(field.data, 0.0), np.array([0.0, 0.0]))
# test invalid spatial dependence
eq = PDE({"a": "x + y"})
with pytest.raises(RuntimeError):
rhs = eq.make_pde_rhs(field, backend=backend)
rhs(field.data, 0.0)
def test_custom_operators():
""" test using a custom operator """
grid = grids.UnitGrid([32])
field = ScalarField.random_normal(grid)
eq = PDE({"u": "undefined(u)"})
with pytest.raises(NameError):
eq.evolution_rate(field)
def make_op(state):
return lambda state: state
grids.UnitGrid.register_operator("undefined", make_op)
eq._cache = {} # reset cache
res = eq.evolution_rate(field)
np.testing.assert_allclose(field.data, res.data)
del grids.UnitGrid._operators["undefined"] # reset original state
def test_pde_consts():
"""test using the consts argument in PDE"""
field = ScalarField(grids.UnitGrid([3]), 1)
eq = PDE({"a": "b"}, consts={"b": 2})
np.testing.assert_allclose(eq.evolution_rate(field).data, 2)
eq = PDE({"a": "b**2"}, consts={"b": field})
np.testing.assert_allclose(eq.evolution_rate(field).data, field.data)
eq = PDE({"a": "laplace(b)"}, consts={"b": field})
np.testing.assert_allclose(eq.evolution_rate(field).data, 0)
eq = PDE({"a": "laplace(b)"}, consts={"b": 3})
with pytest.raises(Exception):
eq.evolution_rate(field)
eq = PDE({"a": "laplace(b)"}, consts={"b": field.data})
with pytest.raises(Exception):
eq.evolution_rate(field)
def test_iter_mirror_points():
"""test iterating mirror points in grids"""
grid_cart = grids.UnitGrid([2, 2], periodic=[True, False])
grid_cyl = grids.CylindricalSymGrid(2, (0, 2), (2, 2), periodic_z=False)
grid_sph = grids.SphericalSymGrid(2, 2)
assert grid_cart._cache_hash() != grid_cyl._cache_hash(
) != grid_sph._cache_hash()
for with_, only_periodic in itertools.product([False, True], repeat=2):
num_expect = 2 if only_periodic else 8
num_expect += 1 if with_ else 0
ps = grid_cart.iter_mirror_points([1, 1], with_, only_periodic)
assert len(list(ps)) == num_expect
num_expect = 0 if only_periodic else 2
num_expect += 1 if with_ else 0
ps = grid_cyl.iter_mirror_points([0, 0, 1], with_, only_periodic)
assert len(list(ps)) == num_expect
num_expect = 1 if with_ else 0
ps = grid_sph.iter_mirror_points([0, 0, 0], with_, only_periodic)
assert len(list(ps)) == num_expect