def test_observation_set(image_data):
obs = Observation(image=image_data['image'],
weight=image_data['weight'],
bmask=image_data['bmask'],
ormask=image_data['ormask'],
noise=image_data['noise'],
jacobian=image_data['jacobian'],
gmix=image_data['gmix'],
psf=image_data['psf'],
meta=image_data['meta'])
rng = np.random.RandomState(seed=11)
new_arr = rng.normal(size=image_data['image'].shape)
assert np.all(obs.image != new_arr)
obs.image = new_arr
assert np.all(obs.image == new_arr)
new_arr = np.exp(rng.normal(size=image_data['image'].shape))
assert np.all(obs.weight != new_arr)
obs.weight = new_arr
assert np.all(obs.weight == new_arr)
new_arr = (np.exp(rng.normal(size=image_data['image'].shape)) *
100).astype(np.int32)
assert np.all(obs.bmask != new_arr)
obs.bmask = new_arr
assert np.all(obs.bmask == new_arr)
new_arr = (np.exp(rng.normal(size=image_data['image'].shape)) *
100).astype(np.int32)
assert np.all(obs.ormask != new_arr)
obs.ormask = new_arr
assert np.all(obs.ormask == new_arr)
new_arr = rng.normal(size=image_data['image'].shape)
assert np.all(obs.noise != new_arr)
obs.noise = new_arr
assert np.all(obs.noise == new_arr)
new_jac = DiagonalJacobian(x=8, y=13, scale=1.2)
assert new_jac.get_galsim_wcs() != obs.jacobian.get_galsim_wcs()
obs.jacobian = new_jac
assert new_jac.get_galsim_wcs() == obs.jacobian.get_galsim_wcs()
new_meta = {'new': 5}
assert obs.meta != new_meta
obs.meta = new_meta
assert obs.meta == new_meta
new_meta = {'blue': 10}
new_meta.update(obs.meta)
assert obs.meta != new_meta
obs.update_meta_data({'blue': 10})
assert obs.meta == new_meta
new_gmix = GMix(pars=rng.uniform(size=6))
assert np.all(obs.gmix.get_full_pars() != new_gmix.get_full_pars())
obs.gmix = new_gmix
assert np.all(obs.gmix.get_full_pars() == new_gmix.get_full_pars())
new_psf = Observation(image=rng.normal(size=obs.psf.image.shape),
meta={'ispsf': True})
assert np.all(obs.psf.image != new_psf.image)
obs.psf = new_psf
assert np.all(obs.psf.image == new_psf.image)
