def test__numbering__uses_mask_correctly(simple_mask_5x5, cross_mask):
convolver = aa.Convolver(
mask=simple_mask_5x5,
kernel=aa.Kernel2D.ones(shape_native=(1, 1), pixel_scales=1.0),
)
mask_index_array = convolver.mask_index_array
assert mask_index_array.shape == (5, 5)
# noinspection PyUnresolvedReferences
assert (mask_index_array == np.array([
[-1, -1, -1, -1, -1],
[-1, 0, 1, 2, -1],
[-1, 3, 4, 5, -1],
[-1, 6, 7, 8, -1],
[-1, -1, -1, -1, -1],
])).all()
convolver = aa.Convolver(mask=cross_mask,
kernel=aa.Kernel2D.ones(shape_native=(1, 1),
pixel_scales=1.0))
assert (convolver.mask_index_array == np.array([
[-1, -1, -1, -1, -1],
[-1, -1, 0, -1, -1],
[-1, 1, 2, 3, -1],
[-1, -1, 4, -1, -1],
[-1, -1, -1, -1, -1],
])).all()
def test__convolution__cross_mask_with_blurring_entries__returns_array():
cross_mask = aa.Mask2D.manual(
mask=[
[True, True, True, True, True],
[True, True, False, True, True],
[True, False, False, False, True],
[True, True, False, True, True],
[True, True, True, True, True],
],
pixel_scales=0.1,
sub_size=1,
)
kernel = aa.Kernel2D.manual_native(array=[[0, 0.2, 0], [0.2, 0.4, 0.2],
[0, 0.2, 0]],
pixel_scales=0.1)
convolver = aa.Convolver(mask=cross_mask, kernel=kernel)
image_array = aa.Array2D.manual_mask(array=[1, 0, 0, 0, 0],
mask=cross_mask)
blurring_mask = cross_mask.blurring_mask_from_kernel_shape(
kernel_shape_native=kernel.shape_native)
blurring_array = aa.Array2D.manual_mask(
array=[0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
mask=blurring_mask)
result = convolver.convolve_image(image=image_array,
blurring_image=blurring_array)
assert (np.round(result, 1) == np.array([0.6, 0.2, 0.2, 0.0, 0.0])).all()
def test__even_kernel_failure():
with pytest.raises(exc.ConvolverException):
aa.Convolver(
mask=np.full((3, 3), False),
kernel=aa.Kernel2D.ones(shape_native=(2, 2), pixel_scales=1.0),
)
def test__blurring_frame_indexes__blurring_region_3x3_kernel(cross_mask):
convolver = aa.Convolver(mask=cross_mask,
kernel=aa.Kernel2D.ones(shape_native=(3, 3),
pixel_scales=1.0))
assert (convolver.blurring_frame_1d_indexes[4] == np.array(
[0, 1, 2, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.blurring_frame_1d_indexes[5] == np.array(
[0, 2, 3, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.blurring_frame_1d_indexes[10] == np.array(
[1, 2, 4, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.blurring_frame_1d_indexes[11] == np.array(
[2, 3, 4, -1, -1, -1, -1, -1, -1])).all()
def test__frame_extraction__frame_and_kernel_frame_at_coords(simple_mask_5x5):
convolver = aa.Convolver(
mask=simple_mask_5x5,
kernel=aa.Kernel2D.manual_native(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]],
pixel_scales=1.0),
)
frame, kernel_frame = convolver.frame_at_coordinates_jit(
coordinates=(2, 2),
mask=simple_mask_5x5,
mask_index_array=convolver.mask_index_array,
kernel_2d=convolver.kernel.native,
)
assert (frame == np.array([i for i in range(9)])).all()
assert (kernel_frame == np.array(
[[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]])).all()
corner_frame = np.array([0, 1, 3, 4, -1, -1, -1, -1, -1])
frame, kernel_frame = convolver.frame_at_coordinates_jit(
coordinates=(1, 1),
mask=simple_mask_5x5,
mask_index_array=convolver.mask_index_array,
kernel_2d=convolver.kernel.native,
)
assert (frame == corner_frame).all()
frame, kernel_frame = convolver.frame_at_coordinates_jit(
coordinates=(1, 1),
mask=simple_mask_5x5,
mask_index_array=convolver.mask_index_array,
kernel_2d=convolver.kernel.native,
)
assert (kernel_frame == np.array([5.0, 6.0, 8.0, 9.0, -1, -1, -1, -1,
-1])).all()
assert 9 == len(convolver.image_frame_1d_indexes)
assert (convolver.image_frame_1d_indexes[4] == np.array(
[i for i in range(9)])).all()
def test__blurring_frame_kernels__blurring_region_3x3_kernel(cross_mask):
convolver = aa.Convolver(
mask=cross_mask,
kernel=aa.Kernel2D.manual_native(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]],
pixel_scales=1.0),
)
assert (convolver.blurring_frame_1d_kernels[4] == np.array(
[6.0, 8.0, 9.0, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.blurring_frame_1d_kernels[5] == np.array(
[4.0, 7.0, 8.0, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.blurring_frame_1d_kernels[10] == np.array(
[2.0, 3.0, 6.0, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.blurring_frame_1d_kernels[11] == np.array(
[1.0, 2.0, 4.0, -1, -1, -1, -1, -1, -1])).all()
def test__frame_lengths__frames_are_from_examples_above__lengths_are_right(
simple_mask_2d_7x7):
convolver = aa.Convolver(
mask=simple_mask_2d_7x7,
kernel=aa.Kernel2D.ones(shape_native=(3, 5), pixel_scales=1.0),
)
# convolver_image.image_frame_indexes[0] == np.array([0, 1, 2, 3, 4, 5])
# convolver_image.image_frame_indexes[1] == np.array([0, 1, 2, 3, 4, 5])
# convolver_image.image_frame_indexes[2] == np.array([0, 1, 2, 3, 4, 5])
# convolver_image.image_frame_indexes[3] == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])
# (convolver_image.image_frame_indexes[4] == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])
# convolver_image.image_frame_indexes[5] == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])
# convolver_image.image_frame_indexes[6] == np.array([3, 4, 5, 6, 7, 8])
# convolver_image.image_frame_indexes[7] == np.array([3, 4, 5, 6, 7, 8])
# convolver_image.image_frame_indexes[8] == np.array([3, 4, 5, 6, 7, 8])
assert (convolver.image_frame_1d_lengths == np.array(
[6, 6, 6, 9, 9, 9, 6, 6, 6])).all()
def test__compare_to_full_2d_convolution():
# Setup a blurred data, using the PSF to perform the convolution in 2D, then masks it to make a 1d array.
import scipy.signal
mask = aa.Mask2D.circular(shape_native=(30, 30),
pixel_scales=(1.0, 1.0),
sub_size=1,
radius=4.0)
kernel = aa.Kernel2D.manual_native(array=np.arange(49).reshape(7, 7),
pixel_scales=1.0)
image = aa.Array2D.manual_native(array=np.arange(900).reshape(30, 30),
pixel_scales=1.0)
blurred_image_via_scipy = scipy.signal.convolve2d(image.native,
kernel.native,
mode="same")
blurred_image_via_scipy = aa.Array2D.manual_native(
array=blurred_image_via_scipy, pixel_scales=1.0)
blurred_masked_image_via_scipy = aa.Array2D.manual_mask(
array=blurred_image_via_scipy.native, mask=mask)
# Now reproduce this data using the frame convolver_image
masked_image = aa.Array2D.manual_mask(array=image.native, mask=mask)
blurring_mask = mask.blurring_mask_from_kernel_shape(
kernel_shape_native=kernel.shape_native)
convolver = aa.Convolver(mask=mask, kernel=kernel)
blurring_image = aa.Array2D.manual_mask(array=image.native,
mask=blurring_mask)
blurred_masked_im_1 = convolver.convolve_image(
image=masked_image, blurring_image=blurring_image)
assert blurred_masked_image_via_scipy == pytest.approx(
blurred_masked_im_1, 1e-4)
def test__convolve_mapping_matrix__asymetric_convolver__matrix_blurred_correctly(
):
mask = np.array([
[True, True, True, True, True, True],
[True, False, False, False, False, True],
[True, False, False, False, False, True],
[True, False, False, False, False, True],
[True, False, False, False, False, True],
[True, True, True, True, True, True],
])
asymmetric_kernel = aa.Kernel2D.manual_native(array=[[0, 0.0, 0],
[0.4, 0.2, 0.3],
[0, 0.1, 0]],
pixel_scales=1.0)
convolver = aa.Convolver(mask=mask, kernel=asymmetric_kernel)
mapping = np.array([
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[
0,
1,
0,
], # The 0.3 should be 'chopped' from this pixel as it is on the right-most edge
[0, 0, 0],
[1, 0, 0],
[0, 0, 1],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
])
blurred_mapping = convolver.convolve_mapping_matrix(mapping)
assert (blurred_mapping == np.array([
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0.4, 0],
[0, 0.2, 0],
[0.4, 0, 0],
[0.2, 0, 0.4],
[0.3, 0, 0.2],
[0, 0.1, 0.3],
[0, 0, 0],
[0.1, 0, 0],
[0, 0, 0.1],
[0, 0, 0],
])).all()
asymmetric_kernel = aa.Kernel2D.manual_native(array=[[0, 0.0, 0],
[0.4, 0.2, 0.3],
[0, 0.1, 0]],
pixel_scales=1.0)
convolver = aa.Convolver(mask=mask, kernel=asymmetric_kernel)
mapping = np.array([
[0, 1, 0],
[0, 1, 0],
[0, 1, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[
0,
1,
0,
], # The 0.3 should be 'chopped' from this pixel as it is on the right-most edge
[1, 0, 0],
[1, 0, 0],
[0, 0, 1],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
])
blurred_mapping = convolver.convolve_mapping_matrix(mapping)
assert blurred_mapping == pytest.approx(
np.array([
[0, 0.6, 0],
[0, 0.9, 0],
[0, 0.5, 0],
[0, 0.3, 0],
[0, 0.1, 0],
[0, 0.1, 0],
[0, 0.5, 0],
[0, 0.2, 0],
[0.6, 0, 0],
[0.5, 0, 0.4],
[0.3, 0, 0.2],
[0, 0.1, 0.3],
[0.1, 0, 0],
[0.1, 0, 0],
[0, 0, 0.1],
[0, 0, 0],
]),
1e-4,
)
def test_image_frame_kernels__different_shape_masks(simple_mask_5x5,
simple_mask_2d_7x7):
convolver = aa.Convolver(
mask=simple_mask_5x5,
kernel=aa.Kernel2D.manual_native(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]],
pixel_scales=1.0),
)
assert 9 == len(convolver.image_frame_1d_indexes)
assert (convolver.image_frame_1d_kernels[4] == np.array(
[[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]])).all()
convolver = aa.Convolver(
mask=simple_mask_2d_7x7,
kernel=aa.Kernel2D.manual_native(
[
[1.0, 2.0, 3.0, 4.0, 5.0],
[6.0, 7.0, 8.0, 9.0, 10.0],
[11.0, 12.0, 13.0, 14.0, 15.0],
],
pixel_scales=1.0,
),
)
assert (convolver.image_frame_1d_kernels[0] == np.array(
[8.0, 9.0, 10.0, 13.0, 14.0, 15.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[1] == np.array(
[7.0, 8.0, 9.0, 12.0, 13.0, 14.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[2] == np.array(
[6.0, 7.0, 8.0, 11.0, 12.0, 13.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[3] == np.array([
3.0, 4.0, 5.0, 8.0, 9.0, 10.0, 13.0, 14.0, 15.0, -1, -1, -1, -1, -1, -1
])).all()
assert (convolver.image_frame_1d_kernels[4] == np.array([
2.0, 3.0, 4.0, 7.0, 8.0, 9.0, 12.0, 13.0, 14.0, -1, -1, -1, -1, -1, -1
])).all()
assert (convolver.image_frame_1d_kernels[5] == np.array([
1.0, 2.0, 3.0, 6.0, 7.0, 8.0, 11.0, 12.0, 13.0, -1, -1, -1, -1, -1, -1
])).all()
assert (convolver.image_frame_1d_kernels[6] == np.array(
[3.0, 4.0, 5.0, 8.0, 9.0, 10.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[7] == np.array(
[2.0, 3.0, 4.0, 7.0, 8.0, 9.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[8] == np.array(
[1.0, 2.0, 3.0, 6.0, 7.0, 8.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
convolver = aa.Convolver(
mask=simple_mask_2d_7x7,
kernel=aa.Kernel2D.manual_native(
[
[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0],
[10.0, 11.0, 12.0],
[13.0, 14.0, 15.0],
],
pixel_scales=1.0,
),
)
assert (convolver.image_frame_1d_kernels[0] == np.array(
[8.0, 9.0, 11.0, 12.0, 14.0, 15.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[1] == np.array([
7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, -1, -1, -1, -1, -1,
-1
])).all()
assert (convolver.image_frame_1d_kernels[2] == np.array(
[7.0, 8.0, 10.0, 11.0, 13.0, 14.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[3] == np.array(
[5.0, 6.0, 8.0, 9.0, 11.0, 12.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[4] == np.array([
4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, -1, -1, -1, -1, -1, -1
])).all()
assert (convolver.image_frame_1d_kernels[5] == np.array(
[4.0, 5.0, 7.0, 8.0, 10.0, 11.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[6] == np.array(
[2.0, 3.0, 5.0, 6.0, 8.0, 9.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[7] == np.array(
[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, -1, -1, -1, -1, -1,
-1])).all()
assert (convolver.image_frame_1d_kernels[8] == np.array(
[1.0, 2.0, 4.0, 5.0, 7.0, 8.0, -1, -1, -1, -1, -1, -1, -1, -1,
-1])).all()
def test__image_frame_indexes__for_different_masks(cross_mask,
simple_mask_2d_7x7):
convolver = aa.Convolver(
mask=cross_mask,
kernel=aa.Kernel2D.manual_native(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]],
pixel_scales=1.0),
)
assert 5 == len(convolver.image_frame_1d_indexes)
assert (convolver.image_frame_1d_indexes[0] == np.array(
[0, 1, 2, 3, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[1] == np.array(
[0, 1, 2, 4, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[2] == np.array(
[0, 1, 2, 3, 4, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[3] == np.array(
[0, 2, 3, 4, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[4] == np.array(
[1, 2, 3, 4, -1, -1, -1, -1, -1])).all()
convolver = aa.Convolver(
mask=simple_mask_2d_7x7,
kernel=aa.Kernel2D.ones(shape_native=(3, 5), pixel_scales=1.0),
)
assert (convolver.image_frame_1d_indexes[0] == np.array(
[0, 1, 2, 3, 4, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[1] == np.array(
[0, 1, 2, 3, 4, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[2] == np.array(
[0, 1, 2, 3, 4, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[3] == np.array(
[0, 1, 2, 3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[4] == np.array(
[0, 1, 2, 3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[5] == np.array(
[0, 1, 2, 3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[6] == np.array(
[3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[7] == np.array(
[3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[8] == np.array(
[3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
convolver = aa.Convolver(
mask=simple_mask_2d_7x7,
kernel=aa.Kernel2D.ones(shape_native=(5, 3), pixel_scales=1.0),
)
assert (convolver.image_frame_1d_indexes[0] == np.array(
[0, 1, 3, 4, 6, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[1] == np.array(
[0, 1, 2, 3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[2] == np.array(
[1, 2, 4, 5, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[3] == np.array(
[0, 1, 3, 4, 6, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[4] == np.array(
[0, 1, 2, 3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[5] == np.array(
[1, 2, 4, 5, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[6] == np.array(
[0, 1, 3, 4, 6, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[7] == np.array(
[0, 1, 2, 3, 4, 5, 6, 7, 8, -1, -1, -1, -1, -1, -1])).all()
assert (convolver.image_frame_1d_indexes[8] == np.array(
[1, 2, 4, 5, 7, 8, -1, -1, -1, -1, -1, -1, -1, -1, -1])).all()
convolver = aa.Convolver(
mask=simple_mask_2d_7x7,
kernel=aa.Kernel2D.ones(shape_native=(5, 5), pixel_scales=1.0),
)
assert (convolver.image_frame_1d_indexes[0] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
assert (convolver.image_frame_1d_indexes[1] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
assert (convolver.image_frame_1d_indexes[2] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
assert (convolver.image_frame_1d_indexes[3] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
assert (convolver.image_frame_1d_indexes[4] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
assert (convolver.image_frame_1d_indexes[5] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
assert (convolver.image_frame_1d_indexes[6] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
assert (convolver.image_frame_1d_indexes[7] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
assert (convolver.image_frame_1d_indexes[8] == np.array([
0,
1,
2,
3,
4,
5,
6,
7,
8,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
])).all()
def test__frame_extraction__more_complicated_frames(simple_mask_2d_7x7):
convolver = aa.Convolver(
mask=simple_mask_2d_7x7,
kernel=aa.Kernel2D.manual_native(
[
[1.0, 2.0, 3.0, 4.0, 5.0],
[6.0, 7.0, 8.0, 9.0, 10.0],
[11.0, 12.0, 13.0, 14.0, 15.0],
[16.0, 17.0, 18.0, 19.0, 20.0],
[21.0, 22.0, 23.0, 24.0, 25.0],
],
pixel_scales=1.0,
),
)
frame, kernel_frame = convolver.frame_at_coordinates_jit(
coordinates=(2, 2),
mask=simple_mask_2d_7x7,
mask_index_array=convolver.mask_index_array,
kernel_2d=convolver.kernel.native,
)
assert (kernel_frame == np.array([
13.0,
14.0,
15.0,
18.0,
19.0,
20.0,
23.0,
24.0,
25.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
])).all()
frame, kernel_frame = convolver.frame_at_coordinates_jit(
coordinates=(3, 2),
mask=simple_mask_2d_7x7,
mask_index_array=convolver.mask_index_array,
kernel_2d=convolver.kernel.native,
)
assert (kernel_frame == np.array([
8.0,
9.0,
10.0,
13.0,
14.0,
15.0,
18.0,
19.0,
20.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1,
])).all()
frame, kernel_frame = convolver.frame_at_coordinates_jit(
coordinates=(3, 3),
mask=simple_mask_2d_7x7,
mask_index_array=convolver.mask_index_array,
kernel_2d=convolver.kernel.native,
)
assert (kernel_frame == np.array([
7.0,
8.0,
9.0,
12.0,
13.0,
14.0,
17.0,
18.0,
19.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1,
])).all()
