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_structure_factor_random():
"""test the structure factor function for random input"""
g1 = CartesianGrid([[0, 10]] * 2, 64, periodic=True)
f1 = ScalarField.random_colored(g1, -2)
# test invariance with re-meshing
g2 = CartesianGrid([[0, 10]] * 2, [128, 64], periodic=True)
f2 = f1.interpolate_to_grid(g2)
ks = np.linspace(0.2, 3)
k1, s1 = image_analysis.get_structure_factor(f1, wave_numbers=ks)
k2, s2 = image_analysis.get_structure_factor(f2, wave_numbers=ks)
np.testing.assert_equal(ks, k1)
np.testing.assert_equal(ks, k2)
np.testing.assert_allclose(s1, s2, atol=0.05)
# test invariance with respect to scaling
k2, s2 = image_analysis.get_structure_factor(100 * f1, wave_numbers=ks)
np.testing.assert_equal(ks, k2)
np.testing.assert_allclose(s1, s2, atol=0.05)