def test_interpolation_mutable():
"""test interpolation on mutable fields"""
grid = UnitGrid([2], periodic=True)
field = ScalarField(grid)
for backend in ["numba", "scipy"]:
field.data = 1
np.testing.assert_allclose(field.interpolate([0.5], backend=backend), 1)
field.data = 2
np.testing.assert_allclose(field.interpolate([0.5], backend=backend), 2)
# test overwriting field values
data = np.full_like(field.data, 3)
intp = field.make_interpolator(backend="numba")
np.testing.assert_allclose(intp(np.array([0.5]), data), 3)
def test_poisson_solver_1d():
""" test the poisson solver on 1d grids """
# solve Laplace's equation
grid = UnitGrid([4])
field = ScalarField(grid)
res = field.solve_poisson([{"value": -1}, {"value": 3}])
np.testing.assert_allclose(res.data, grid.axes_coords[0] - 1)
res = field.solve_poisson([{"value": -1}, {"derivative": 1}])
np.testing.assert_allclose(res.data, grid.axes_coords[0] - 1)
# test Poisson equation with 2nd Order BC
res = field.solve_poisson([{"value": -1}, "extrapolate"])
# solve Poisson's equation
grid = CartesianGrid([[0, 1]], 4)
field = ScalarField(grid, data=1)
res = field.copy()
field.solve_poisson([{"value": 1}, {"derivative": 1}], out=res)
xs = grid.axes_coords[0]
np.testing.assert_allclose(res.data, 1 + 0.5 * xs**2, rtol=1e-2)
# test inconsistent problem
field.data = 1
with pytest.raises(RuntimeError, match="Neumann"):
field.solve_poisson({"derivative": 0})
def test_insert_scalar(example_grid):
"""test the `insert` method"""
f = ScalarField(example_grid)
a = np.random.random()
c = tuple(example_grid.point_to_cell(example_grid.get_random_point()))
p = example_grid.cell_to_point(c, cartesian=False)
f.insert(p, a)
assert f.data[c] == pytest.approx(a / example_grid.cell_volumes[c])
f.insert(example_grid.get_random_point(cartesian=False), a)
assert f.integral == pytest.approx(2 * a)
f.data = 0 # reset
insert = example_grid.make_inserter_compiled()
c = tuple(example_grid.point_to_cell(example_grid.get_random_point()))
p = example_grid.cell_to_point(c, cartesian=False)
insert(f.data, p, a)
assert f.data[c] == pytest.approx(a / example_grid.cell_volumes[c])
insert(f.data, example_grid.get_random_point(cartesian=False), a)
assert f.integral == pytest.approx(2 * a)
def test_insert_scalar(grid):
"""test the `insert` method"""
f = ScalarField(grid)
a = np.random.random()
c = tuple(grid.get_random_point(coords="cell"))
p = grid.transform(c, "cell", "grid")
f.insert(p, a)
assert f.data[c] == pytest.approx(a / grid.cell_volumes[c])
f.insert(grid.get_random_point(coords="grid"), a)
assert f.integral == pytest.approx(2 * a)
f.data = 0 # reset
insert = grid.make_inserter_compiled()
c = tuple(grid.get_random_point(coords="cell"))
p = grid.transform(c, "cell", "grid")
insert(f.data, p, a)
assert f.data[c] == pytest.approx(a / grid.cell_volumes[c])
insert(f.data, grid.get_random_point(coords="grid"), a)
assert f.integral == pytest.approx(2 * a)