def test_unit_spherical_with_differentials(rep):
c = TCoo1(rep)
# register and do the transformation and check against expected
trans = t.AffineTransform(transfunc.just_matrix, TCoo1, TCoo2)
trans.register(frame_transform_graph)
c2 = c.transform_to(TCoo2())
assert 's' in rep.differentials
assert isinstance(c2.data.differentials['s'],
rep.differentials['s'].__class__)
if isinstance(rep.differentials['s'], r.RadialDifferential):
assert c2.data.differentials['s'] is rep.differentials['s']
trans.unregister(frame_transform_graph)
# should fail if we have to do offsets
trans = t.AffineTransform(transfunc.both, TCoo1, TCoo2)
trans.register(frame_transform_graph)
with pytest.raises(TypeError):
c.transform_to(TCoo2())
trans.unregister(frame_transform_graph)
def test_affine_transform_fail(transfunc):
diff = r.CartesianDifferential(8, 9, 10, unit=u.pc/u.Myr)
rep = r.CartesianRepresentation(5, 6, 7, unit=u.pc, differentials=diff)
c = TCoo1(rep)
# register and do the transformation and check against expected
trans = t.AffineTransform(transfunc, TCoo1, TCoo2)
trans.register(frame_transform_graph)
with pytest.raises(ValueError):
c.transform_to(TCoo2())
trans.unregister(frame_transform_graph)
def test_too_many_differentials():
dif1 = r.CartesianDifferential(*np.arange(3, 6)*u.pc/u.Myr)
dif2 = r.CartesianDifferential(*np.arange(3, 6)*u.pc/u.Myr**2)
rep = r.CartesianRepresentation(np.arange(3)*u.pc,
differentials={'s': dif1, 's2': dif2})
with pytest.raises(ValueError):
c = TCoo1(rep)
# register and do the transformation and check against expected
trans = t.AffineTransform(transfunc.both, TCoo1, TCoo2)
trans.register(frame_transform_graph)
# Check that if frame somehow gets through to transformation, multiple
# differentials are caught
c = TCoo1(rep.without_differentials())
c._data = c._data.with_differentials({'s': dif1, 's2': dif2})
with pytest.raises(ValueError):
c.transform_to(TCoo2())
trans.unregister(frame_transform_graph)
def test_affine_transform_succeed(transfunc, rep):
c = TCoo1(rep)
# compute expected output
M, offset = transfunc(c, TCoo2)
_rep = rep.to_cartesian()
diffs = {k: diff.represent_as(r.CartesianDifferential, rep)
for k, diff in rep.differentials.items()}
expected_rep = _rep.with_differentials(diffs)
if M is not None:
expected_rep = expected_rep.transform(M)
expected_pos = expected_rep.without_differentials()
if offset is not None:
expected_pos = expected_pos + offset.without_differentials()
expected_vel = None
if c.data.differentials:
expected_vel = expected_rep.differentials['s']
if offset and offset.differentials:
expected_vel = (expected_vel + offset.differentials['s'])
# register and do the transformation and check against expected
trans = t.AffineTransform(transfunc, TCoo1, TCoo2)
trans.register(frame_transform_graph)
c2 = c.transform_to(TCoo2())
assert quantity_allclose(c2.data.to_cartesian().xyz,
expected_pos.to_cartesian().xyz)
if expected_vel is not None:
diff = c2.data.differentials['s'].to_cartesian(base=c2.data)
assert quantity_allclose(diff.xyz, expected_vel.d_xyz)
trans.unregister(frame_transform_graph)
