def test_observation_pixels(image_data):
obs = Observation(image=image_data['image'],
weight=image_data['weight'],
jacobian=image_data['jacobian'])
pixels = obs.pixels
my_pixels = make_pixels(image_data['image'], image_data['weight'],
image_data['jacobian'])
assert np.all(pixels == my_pixels)
def test_observation_pixels_update_jacobian(image_data):
obs = Observation(image=image_data['image'],
weight=image_data['weight'],
jacobian=image_data['jacobian'])
new_jac = DiagonalJacobian(x=8, y=13, scale=1.2)
my_pixels = make_pixels(image_data['image'], image_data['weight'], new_jac)
assert np.all(obs.pixels != my_pixels)
obs.jacobian = new_jac
assert np.all(obs.pixels == my_pixels)
def test_observation_pixels_update_weight(image_data):
rng = np.random.RandomState(seed=11)
obs = Observation(image=image_data['image'],
weight=image_data['weight'],
jacobian=image_data['jacobian'])
new_arr = np.exp(rng.normal(size=obs.image.shape))
my_pixels = make_pixels(image_data['image'], new_arr,
image_data['jacobian'])
assert np.all(obs.pixels != my_pixels)
obs.weight = new_arr
assert np.all(obs.pixels == my_pixels)
def test_pixels_smoke(x, y, wcs_g1, wcs_g2, ignore_zero_weight):
gs_wcs = galsim.ShearWCS(0.25, galsim.Shear(g1=wcs_g1,
g2=wcs_g2)).jacobian()
jac = Jacobian(y=y,
x=x,
dudx=gs_wcs.dudx,
dudy=gs_wcs.dudy,
dvdx=gs_wcs.dvdx,
dvdy=gs_wcs.dvdy)
dims = (13, 15)
rng = np.random.RandomState(seed=11)
image = rng.normal(size=dims)
weight = np.exp(rng.normal(size=dims))
weight[10, 9] = 0
weight[8, 7] = 0
pixels = make_pixels(image,
weight,
jac,
ignore_zero_weight=ignore_zero_weight)
assert np.allclose(pixels['area'], jac.area)
found_zero = 0
for i in range(len(pixels)):
y, x = jac.get_rowcol(pixels['v'][i], pixels['u'][i])
assert np.allclose(x, int(x + 0.5))
assert np.allclose(y, int(y + 0.5))
x = int(x + 0.5)
y = int(y + 0.5)
assert pixels['val'][i] == image[y, x]
assert np.allclose(pixels['ierr'][i], np.sqrt(weight[y, x]))
if x == 9 and y == 10:
found_zero += 1
if y == 8 and x == 7:
found_zero += 1
if ignore_zero_weight:
assert found_zero == 0
else:
assert found_zero == 2
def test_observation_pixels_noignore_zero(image_data):
weight = image_data['weight'].copy()
weight[:, 5] = 0.0
obs = Observation(
image=image_data['image'],
weight=weight,
jacobian=image_data['jacobian'],
ignore_zero_weight=False,
)
pixels = obs.pixels
my_pixels = make_pixels(
image_data['image'],
weight,
image_data['jacobian'],
ignore_zero_weight=False,
)
assert np.all(pixels == my_pixels)
