def test_scalars():
"""test some scalar fields"""
grid = CartesianGrid([[0.1, 0.3], [-2, 3]], [3, 4])
s1 = ScalarField(grid, np.full(grid.shape, 1))
s2 = ScalarField(grid, np.full(grid.shape, 2))
assert s1.average == pytest.approx(1)
assert s1.magnitude == pytest.approx(1)
s3 = s1 + s2
assert s3.grid == grid
np.testing.assert_allclose(s3.data, 3)
s1 += s2
np.testing.assert_allclose(s1.data, 3)
s2 = FieldBase.from_state(s1.attributes, data=s1.data)
assert s1 == s2
assert s1.grid is s2.grid
attrs = ScalarField.unserialize_attributes(s1.attributes_serialized)
s2 = FieldBase.from_state(attrs, data=s1.data)
assert s1 == s2
assert s1.grid is not s2.grid
# test options for plotting images
if module_available("matplotlib"):
s1.plot(transpose=True, colorbar=True)
s3 = ScalarField(grid, s1)
assert s1 is not s3
assert s1 == s3
assert s1.grid is s3.grid
# multiplication with numpy arrays
arr = np.random.randn(*grid.shape)
np.testing.assert_allclose((arr * s1).data, (s1 * arr).data)
def test_complex_plotting():
"""test plotting of complex fields"""
for dim in (1, 2):
f = ScalarField(UnitGrid([3] * dim), 1j)
f.plot()