def test_add_interpolated_1d():
""" test the `add_interpolated` method for 1d systems """
grid = PolarGrid(3, 5)
f = ScalarField(grid)
g = f.copy()
a = np.random.random()
for r in np.linspace(0, 3, 8).reshape(8, 1):
f.data = g.data = 0
f.add_interpolated(r, a)
assert f.integral == pytest.approx(a)
grid.make_add_interpolated_compiled()(g.data, r, a)
np.testing.assert_array_almost_equal(f.data, g.data)
def test_add_interpolated_scalar(example_grid):
""" test the `add_interpolated` 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.add_interpolated(p, a)
assert f.data[c] == pytest.approx(a / example_grid.cell_volumes[c])
f.add_interpolated(example_grid.get_random_point(cartesian=False), a)
assert f.integral == pytest.approx(2 * a)
f.data = 0 # reset
add_interpolated = example_grid.make_add_interpolated_compiled()
c = tuple(example_grid.point_to_cell(example_grid.get_random_point()))
p = example_grid.cell_to_point(c, cartesian=False)
add_interpolated(f.data, p, a)
assert f.data[c] == pytest.approx(a / example_grid.cell_volumes[c])
add_interpolated(f.data, example_grid.get_random_point(cartesian=False), a)
assert f.integral == pytest.approx(2 * a)