def test_complex_vectors():
"""test some complex vector fields"""
grid = CartesianGrid([[0.1, 0.3], [-2, 3]], [3, 4])
shape = (2, 2) + grid.shape
numbers = np.random.random(shape) + np.random.random(shape) * 1j
v1 = VectorField(grid, numbers[0])
v2 = VectorField(grid, numbers[1])
assert v1.is_complex and v2.is_complex
for backend in ["numpy", "numba"]:
dot_op = v1.make_dot_operator(backend)
# test complex conjugate
expected = v1.to_scalar("norm_squared").data
np.testing.assert_allclose((v1 @ v1).data, expected)
np.testing.assert_allclose(dot_op(v1.data, v1.data), expected)
# test dot product
res = dot_op(v1.data, v2.data)
for s in (v1 @ v2, (v2 @ v1).conjugate(), v1.dot(v2)):
assert isinstance(s, ScalarField)
assert s.grid is grid
np.testing.assert_allclose(s.data, res)
# test without conjugate
dot_op = v1.make_dot_operator(backend, conjugate=False)
res = v1.dot(v2, conjugate=False)
np.testing.assert_allclose(dot_op(v1.data, v2.data), res.data)
def test_vectors():
""" test some vector fields """
grid = CartesianGrid([[0.1, 0.3], [-2, 3]], [3, 4])
v1 = VectorField(grid, np.full((2, ) + grid.shape, 1))
v2 = VectorField(grid, np.full((2, ) + grid.shape, 2))
np.testing.assert_allclose(v1.average, (1, 1))
assert np.allclose(v1.magnitude, np.sqrt(2))
v3 = v1 + v2
assert v3.grid == grid
np.testing.assert_allclose(v3.data, 3)
v1 += v2
np.testing.assert_allclose(v1.data, 3)
# test projections
v1 = VectorField(grid)
v1.data[0, :] = 3
v1.data[1, :] = 4
for method, value in [
("min", 3),
("max", 4),
("norm", 5),
("squared_sum", 25),
("norm_squared", 25),
("auto", 5),
]:
p1 = v1.to_scalar(method)
assert p1.data.shape == grid.shape
np.testing.assert_allclose(p1.data, value)
v2 = FieldBase.from_state(v1.attributes, data=v1.data)
assert v1 == v2
assert v1.grid is v2.grid
attrs = VectorField.unserialize_attributes(v1.attributes_serialized)
v2 = FieldBase.from_state(attrs, data=v1.data)
assert v1 == v2
assert v1.grid is not v2.grid
# test dot product
v2._grid = v1.grid # make sure grids are identical
v1.data = 1
v2.data = 2
dot_op = v1.make_dot_operator()
res = ScalarField(grid, dot_op(v1.data, v2.data))
for s in (v1 @ v2, v2 @ v1, v1.dot(v2), res):
assert isinstance(s, ScalarField)
assert s.grid is grid
np.testing.assert_allclose(s.data, np.full(grid.shape, 4))
# test options for plotting images
if module_available("matplotlib"):
v1.plot(method="streamplot", transpose=True)
