def test__identical_to_gaussian_light_profile(self):
grid = al.Grid.from_shape_pixel_scale_and_sub_size(shape=(3, 3),
pixel_scale=1.0,
sub_size=1)
gaussian = al.light_profiles.EllipticalGaussian(centre=(0.1, 0.1),
axis_ratio=0.9,
phi=45.0,
intensity=1.0,
sigma=1.0)
profile_gaussian = gaussian.profile_image_from_grid(
grid=grid, bypass_decorator=False)
profile_psf = al.PrimaryBeam(array=profile_gaussian,
pixel_scale=1.0,
renormalize=True)
imaging_psf = al.PrimaryBeam.from_gaussian(
shape=(3, 3),
pixel_scale=1.0,
centre=(0.1, 0.1),
axis_ratio=0.9,
phi=45.0,
sigma=1.0,
)
assert profile_psf == pytest.approx(imaging_psf, 1e-4)
def test__kernel_is_not_odd_x_odd__raises_error(self):
kernel = np.array([[0.0, 1.0], [1.0, 2.0]])
psf = al.PrimaryBeam(array=kernel, pixel_scale=1.0)
with pytest.raises(exc.ConvolutionException):
psf.convolve(np.ones((5, 5)))
def test__input_is_already_normalized__no_change(self):
primary_beam_data = np.ones((3, 3)) / 9.0
psf = al.PrimaryBeam(array=primary_beam_data,
pixel_scale=1.0,
renormalize=True)
assert psf == pytest.approx(primary_beam_data, 1e-3)
def test__same_as_above__renomalized_false_does_not_renormalize(self):
primary_beam_data = np.ones((3, 3))
psf = al.PrimaryBeam(array=primary_beam_data,
pixel_scale=1.0,
renormalize=False)
assert psf == pytest.approx(np.ones((3, 3)), 1e-3)
def test__input_is_above_normalization_so_is_normalized(self):
primary_beam_data = np.ones((3, 3))
psf = al.PrimaryBeam(array=primary_beam_data,
pixel_scale=1.0,
renormalize=True)
assert psf == pytest.approx(np.ones((3, 3)) / 9.0, 1e-3)
def test__init__input_primary_beam__all_attributes_correct_including_data_inheritance(
self):
psf = al.PrimaryBeam(array=np.ones((3, 3)),
pixel_scale=1.0,
renormalize=False)
assert psf.shape == (3, 3)
assert psf.pixel_scale == 1.0
assert (psf == np.ones((3, 3))).all()
assert psf.origin == (0.0, 0.0)
psf = al.PrimaryBeam(array=np.ones((4, 3)),
pixel_scale=1.0,
renormalize=False)
assert (psf == np.ones((4, 3))).all()
assert psf.pixel_scale == 1.0
assert psf.shape == (4, 3)
assert psf.origin == (0.0, 0.0)
def test__input_is_already_normalized__no_change(self):
primary_beam_data = np.ones((3, 3)) / 9.0
psf = al.PrimaryBeam(array=primary_beam_data,
pixel_scale=1.0,
renormalize=False)
primary_beam_new = psf.new_primary_beam_with_renormalized_array()
assert primary_beam_new == pytest.approx(primary_beam_data, 1e-3)
def test__input_is_above_normalization_so_is_normalized(self):
primary_beam_data = np.ones((3, 3))
psf = al.PrimaryBeam(array=primary_beam_data,
pixel_scale=1.0,
renormalize=False)
primary_beam_new = psf.new_primary_beam_with_renormalized_array()
assert primary_beam_new == pytest.approx(
np.ones((3, 3)) / 9.0, 1e-3)
def test__image_is_3x3_central_value_of_one__kernel_is_cross__blurred_image_becomes_cross(
self):
image = np.array([[0.0, 0.0, 0.0], [0.0, 1.0, 0.0],
[0.0, 0.0, 0.0]])
kernel = np.array([[0.0, 1.0, 0.0], [1.0, 2.0, 1.0],
[0.0, 1.0, 0.0]])
psf = al.PrimaryBeam(array=kernel, pixel_scale=1.0)
blurred_image = psf.convolve(image)
assert (blurred_image == kernel).all()
def test__primary_beam_is_odd_and_even_after_binning_up__resized_to_odd_and_odd_with_shape_plus_one(
self):
array_2d = np.ones((6, 4))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.5, renormalize=True)
assert psf.pixel_scale == pytest.approx(2.0, 1.0e-4)
assert psf == (1.0 / 9.0) * np.ones((3, 3))
array_2d = np.ones((9, 12))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.33333333333, renormalize=True)
assert psf.pixel_scale == pytest.approx(3.0, 1.0e-4)
assert psf == (1.0 / 15.0) * np.ones((3, 5))
array_2d = np.ones((4, 6))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.5, renormalize=True)
assert psf.pixel_scale == pytest.approx(2.0, 1.0e-4)
assert psf == (1.0 / 9.0) * np.ones((3, 3))
array_2d = np.ones((12, 9))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.33333333333, renormalize=True)
assert psf.pixel_scale == pytest.approx(3.0, 1.0e-4)
assert psf == (1.0 / 15.0) * np.ones((5, 3))
def test__primary_beam_is_even_x_even_after_binning_up__resized_to_odd_x_odd_with_shape_plus_one(
self):
array_2d = np.ones((2, 2))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=2.0, renormalize=True)
assert psf.pixel_scale == 0.4
assert psf == (1.0 / 25.0) * np.ones((5, 5))
array_2d = np.ones((40, 40))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.1, renormalize=True)
assert psf.pixel_scale == 8.0
assert psf == (1.0 / 25.0) * np.ones((5, 5))
array_2d = np.ones((2, 4))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=2.0, renormalize=True)
assert psf.pixel_scale == pytest.approx(0.4444444, 1.0e-4)
assert psf == (1.0 / 45.0) * np.ones((5, 9))
array_2d = np.ones((4, 2))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=2.0, renormalize=True)
assert psf.pixel_scale == pytest.approx(0.4444444, 1.0e-4)
assert psf == (1.0 / 45.0) * np.ones((9, 5))
def test__primary_beam_is_even_x_even__rescaled_to_odd_x_odd__no_use_of_dimension_trimming(
self):
array_2d = np.ones((6, 6))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.5, renormalize=True)
assert psf.pixel_scale == 2.0
assert psf == (1.0 / 9.0) * np.ones((3, 3))
array_2d = np.ones((9, 9))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.333333333333333, renormalize=True)
assert psf.pixel_scale == 3.0
assert psf == (1.0 / 9.0) * np.ones((3, 3))
array_2d = np.ones((18, 6))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.5, renormalize=True)
assert psf.pixel_scale == 2.0
assert psf == (1.0 / 27.0) * np.ones((9, 3))
array_2d = np.ones((6, 18))
psf = al.PrimaryBeam(array=array_2d,
pixel_scale=1.0,
renormalize=False)
psf = psf.new_primary_beam_with_rescaled_odd_dimensioned_array(
rescale_factor=0.5, renormalize=True)
assert psf.pixel_scale == 2.0
assert psf == (1.0 / 27.0) * np.ones((3, 9))
def test__new_data_with_resized_primary_beam(self):
uv_plane_data = al.UVPlaneData(
shape=(2, 2),
visibilities=np.array([[1, 1]]),
pixel_scale=1.0,
primary_beam=al.PrimaryBeam(np.zeros((5, 5)), pixel_scale=1.0),
noise_map=1,
exposure_time_map=1,
uv_wavelengths=1,
)
uv_plane_data = uv_plane_data.new_uv_plane_data_with_resized_primary_beam(
new_shape=(1, 1))
assert uv_plane_data.pixel_scale == 1.0
assert (uv_plane_data.primary_beam == np.zeros((1, 1))).all()
assert uv_plane_data.origin == (0.0, 0.0)
def test__image_is_4x4_has_two_central_values__kernel_is_asymmetric__blurred_image_follows_convolution(
self):
image = np.array([
[0.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0],
[0.0, 0.0, 0.0, 0.0],
])
kernel = np.array([[1.0, 1.0, 1.0], [2.0, 2.0, 1.0],
[1.0, 3.0, 3.0]])
psf = al.PrimaryBeam(array=kernel, pixel_scale=1.0)
blurred_image = psf.convolve(image)
assert (blurred_image == np.array([
[1.0, 1.0, 1.0, 0.0],
[2.0, 3.0, 2.0, 1.0],
[1.0, 5.0, 5.0, 1.0],
[0.0, 1.0, 3.0, 3.0],
])).all()
def test__image_is_4x4_values_are_on_corner__kernel_is_asymmetric__blurring_does_not_account_for_edge_effects(
self):
image = np.array([
[1.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 1.0],
])
kernel = np.array([[1.0, 1.0, 1.0], [2.0, 2.0, 1.0],
[1.0, 3.0, 3.0]])
psf = al.PrimaryBeam(array=kernel, pixel_scale=1.0)
blurred_image = psf.convolve(image)
assert (blurred_image == np.array([
[2.0, 1.0, 0.0, 0.0],
[3.0, 3.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 2.0, 2.0],
])).all()
def test__new_data_with_modified_visibilities(self):
uv_plane_data = al.UVPlaneData(
shape=(2, 2),
visibilities=np.array([[1, 1]]),
pixel_scale=1.0,
primary_beam=al.PrimaryBeam(np.zeros((5, 5)), pixel_scale=1.0),
noise_map=1,
exposure_time_map=2,
uv_wavelengths=3,
)
uv_plane_data = uv_plane_data.new_uv_plane_data_with_modified_visibilities(
modified_visibilities=np.array([[2, 2]]))
assert (uv_plane_data.visibilities == np.array([[2, 2]])).all()
assert uv_plane_data.shape == (2, 2)
assert uv_plane_data.pixel_scale == 1.0
assert (uv_plane_data.primary_beam == np.zeros((1, 1))).all()
assert uv_plane_data.noise_map == 1
assert uv_plane_data.exposure_time_map == 2
assert uv_plane_data.uv_wavelengths == 3
assert uv_plane_data.origin == (0.0, 0.0)
def test__different_uv_plane_data_without_mock_objects__customize_constructor_inputs(
self):
primary_beam = al.PrimaryBeam(np.ones((7, 7)), 1)
uv_plane_data = al.UVPlaneData(
shape=(2, 2),
visibilities=np.ones((19, 2)),
pixel_scale=3.0,
primary_beam=primary_beam,
noise_map=2.0 * np.ones((19, )),
uv_wavelengths=3.0 * np.ones((19, 2)),
)
mask = al.Mask.unmasked_from_shape_pixel_scale_and_sub_size(
shape=(19, 19), pixel_scale=1.0, invert=True, sub_size=8)
mask[9, 9] = False
lens_uv_plane_data_7 = al.LensUVPlaneData(
uv_plane_data=uv_plane_data,
mask=mask,
trimmed_primary_beam_shape=(7, 7),
positions=[np.array([[1.0, 1.0]])],
positions_threshold=1.0,
)
assert (lens_uv_plane_data_7.visibilities() == np.ones((19, 2))).all()
assert (lens_uv_plane_data_7.noise_map() == 2.0 * np.ones(
(19, ))).all()
assert (lens_uv_plane_data_7.uv_plane_data.uv_wavelengths == 3.0 *
np.ones((19, 2))).all()
assert (lens_uv_plane_data_7.primary_beam == np.ones((7, 7))).all()
assert lens_uv_plane_data_7.sub_size == 8
assert (lens_uv_plane_data_7.positions[0] == np.array([[1.0,
1.0]])).all()
assert lens_uv_plane_data_7.positions_threshold == 1.0
assert lens_uv_plane_data_7.trimmed_primary_beam_shape == (7, 7)
