def test__pixel_scales_work_for_voronoi_mapper(self, grid_7x7, image_7x7):
pixelization_grid = np.array(
[[0.1, 0.1], [1.1, 0.1], [2.1, 0.1], [0.1, 1.1], [1.1, 1.1], [2.1, 1.1]]
)
nearest_pixelization_1d_index_for_mask_1d_index = np.array(
[0, 0, 1, 0, 0, 1, 2, 2, 3]
)
pixelization_grid = aa.grid_voronoi(
grid_1d=pixelization_grid,
nearest_pixelization_1d_index_for_mask_1d_index=nearest_pixelization_1d_index_for_mask_1d_index,
)
mapper = aa.mapper(
grid=grid_7x7,
pixelization_grid=pixelization_grid,
hyper_image=image_7x7,
)
pixel_signals = mapper.pixel_signals_from_signal_scale(signal_scale=2.0)
pixel_signals_util = aa.util.mapper.adaptive_pixel_signals_from_images(
pixels=6,
signal_scale=2.0,
pixelization_1d_index_for_sub_mask_1d_index=mapper.pixelization_1d_index_for_sub_mask_1d_index,
mask_1d_index_for_sub_mask_1d_index=grid_7x7.regions._mask_1d_index_for_sub_mask_1d_index,
hyper_image=image_7x7,
)
assert (pixel_signals == pixel_signals_util).all()
def test__4x3_grid__non_symmetric_centre_shift(self):
# _ _ _
# |_|_|_|
# |_|_|_|
# |_|_|_|
# |_|_|_|
grid = np.array(
[[3.0, -0.5], [3.0, 0.51], [2.49, -0.5], [1.4, 1.0], [1.0, 2.5]]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(4, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 1, 3, 10, 11])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[1],
[],
[2],
[],
[],
[],
[],
[],
[],
[3],
[4],
]
def test__3x3_pixelization__solution_vector_ascending(self):
grid = np.array(
[
[2.0, -1.0],
[2.0, 0.0],
[2.0, 1.0],
[0.0, -1.0],
[0.0, 0.0],
[0.0, 1.0],
[-2.0, -1.0],
[-2.0, 0.0],
[-2.0, 1.0],
]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
recon_pix = mapper.reconstructed_pixelization_from_solution_vector(
solution_vector=np.array([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0])
)
assert (
recon_pix.in_2d
== np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]])
).all()
assert recon_pix.pixel_scales == pytest.approx((4.0 / 3.0, 2.0 / 3.0), 1e-2)
assert recon_pix.origin == (0.0, 0.0)
def test__3x4_grid__change_arcsecond_dimensions__not_symmetric(self):
# _ _ _ _
# |_|_|_|_|
# |_|_|_|_|
# |_|_|_|_|
grid = np.array(
[[1.0, -1.5], [1.0, -0.49], [0.32, -1.5], [-0.34, 0.49], [-1.0, 1.5]]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 4), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 1, 4, 10, 11])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[1],
[],
[],
[2],
[],
[],
[],
[],
[],
[3],
[4],
]
def test__3x3_grid__change_arcsecond_dimensions__not_symmetric(self):
# _ _ _
# |_|_|_| Boundaries for pixels x = 0 and y = 0 -1.5 to -0.5
# |_|_|_| Boundaries for pixels x = 1 and y = 1 -0.5 to 0.5
# |_|_|_| Boundaries for pixels x = 2 and y = 2 0.5 to 1.5
grid = np.array(
[[1.0, -1.5], [1.0, -0.49], [0.32, -1.5], [0.32, 0.51], [-1.0, 1.5]]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 1, 3, 5, 8])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[1],
[],
[2],
[],
[3],
[],
[],
[4],
]
def test__3x3_grid__change_arcsecond_dimensions_size__grid_adapts_accordingly(
self
):
# _ _ _
# |_|_|_| Boundaries for pixels x = 0 and y = 0 -1.5 to -0.5
# |_|_|_| Boundaries for pixels x = 1 and y = 1 -0.5 to 0.5
# |_|_|_| Boundaries for pixels x = 2 and y = 2 0.5 to 1.5
grid = np.array(
[[1.5, -1.5], [1.0, 0.0], [1.0, 0.6], [-1.4, 0.0], [-1.5, 1.5]]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 1, 2, 7, 8])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[1],
[2],
[],
[],
[],
[],
[3],
[4],
]
def test__sub_to_pix_of_mapper_matches_nearest_neighbor_calculation(
self, grid_7x7
):
pixelization_grid = np.array(
[[0.1, 0.1], [1.1, 0.1], [2.1, 0.1], [0.1, 1.1], [1.1, 1.1], [2.1, 1.1]]
)
sub_to_pix_nearest_neighbour = grid_to_pixel_pixels_via_nearest_neighbour(
grid_7x7, pixelization_grid
)
nearest_pixelization_1d_index_for_mask_1d_index = np.array(
[0, 0, 1, 0, 0, 1, 2, 2, 3]
)
pixelization_grid = aa.grid_voronoi(
grid_1d=pixelization_grid,
nearest_pixelization_1d_index_for_mask_1d_index=nearest_pixelization_1d_index_for_mask_1d_index,
)
mapper = aa.mapper(grid=grid_7x7, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== sub_to_pix_nearest_neighbour
).all()
def test__compare_to_imaging_util(self):
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(4, 3), grid=np.ones((2, 2))
)
mapper = aa.mapper(grid=None, pixelization_grid=pixelization_grid)
solution = np.array(
[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 1.0, 2.0, 3.0]
)
recon_pix = mapper.reconstructed_pixelization_from_solution_vector(
solution_vector=solution
)
recon_pix_util = aa.util.array.sub_array_2d_from_sub_array_1d(
sub_array_1d=solution,
mask=np.full(fill_value=False, shape=(4, 3)),
sub_size=1,
)
assert (recon_pix.in_2d == recon_pix_util).all()
assert recon_pix.shape_2d == (4, 3)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 4), grid=np.ones((2, 2))
)
mapper = aa.mapper(grid=None, pixelization_grid=pixelization_grid)
solution = np.array(
[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 1.0, 2.0, 3.0]
)
recon_pix = mapper.reconstructed_pixelization_from_solution_vector(
solution_vector=solution
)
recon_pix_util = aa.util.array.sub_array_2d_from_sub_array_1d(
sub_array_1d=solution,
mask=np.full(fill_value=False, shape=(3, 4)),
sub_size=1,
)
assert (recon_pix.in_2d == recon_pix_util).all()
assert recon_pix.shape_2d == (3, 4)
def test__4x3_grid_of_pixel_grid__1_coordinate_in_each_pixel(self):
# _ _ _
# |_|_|_|
# |_|_|_|
# |_|_|_|
# |_|_|_|
# Boundaries for column pixel 0 -1.0 to -(1/3)
# Boundaries for column pixel 1 -(1/3) to (1/3)
# Boundaries for column pixel 2 (1/3) to 1.0
# Bounadries for row pixel 0 -1.0 to -0.5
# Bounadries for row pixel 1 -0.5 to 0.0
# Bounadries for row pixel 2 0.0 to 0.5
# Bounadries for row pixel 3 0.5 to 1.0
grid = np.array(
[
[1.0, -1.0],
[1.0, 0.0],
[1.0, 1.0],
[0.5, -1.0],
[-0.5, 1.0],
[-1.0, 1.0],
]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(4, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 1, 2, 3, 8, 11])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[1],
[2],
[3],
[],
[],
[],
[],
[4],
[],
[],
[5],
]
def test__3x3_grid_of_pixel_grid__1_coordinate_per_square_pixel__near_edges_of_pixels(
self
):
# _ _ _
# |_|_|_| Boundaries for pixels x = 0 and y = 0 -1.0 to -(1/3)
# |_|_|_| Boundaries for pixels x = 1 and y = 1 - (1/3) to (1/3)
# |_|_|_| Boundaries for pixels x = 2 and y = 2 - (1/3)" to 1.0"
grid = np.array(
[
[1.0, -1.0],
[1.0, 0.0],
[1.0, 1.0],
[-0.32, -1.0],
[-0.32, 0.32],
[0.0, 1.0],
[-0.34, -0.34],
[-0.34, 0.325],
[-1.0, 1.0],
]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[1],
[2],
[3],
[4],
[5],
[6],
[7],
[8],
]
def test__3x3_grid_of_pixel_grid___shift_coordinates_to_new_centre__centre_adjusts_based_on_grid(
self
):
# _ _ _
# |_|_|_| Boundaries for pixels x = 0 and y = 0 -1.0 to -(1/3)
# |_|_|_| Boundaries for pixels x = 1 and y = 1 - (1/3) to (1/3)
# |_|_|_| Boundaries for pixels x = 2 and y = 2 - (1/3)" to 1.0"
grid = np.array(
[
[2.0, 0.0],
[2.0, 1.0],
[2.0, 2.0],
[1.0, 0.0],
[1.0, 1.0],
[1.0, 2.0],
[0.0, 0.0],
[0.0, 1.0],
[0.0, 2.0],
]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[1],
[2],
[3],
[4],
[5],
[6],
[7],
[8],
]
def test__different_image_and_sub_grids(self):
# _ _ _
# -1.0 to -(1/3) |_|_|_|
# -(1/3) to (1/3) |_|_|_|
# (1/3) to 1.0 |_|_|_|
grid = np.array(
[
[1.0, -1.0],
[1.0, 0.0],
[1.0, 1.0],
[0.0, -1.0],
[0.0, 0.0],
[0.0, 1.0],
[-1.0, -1.0],
[-1.0, 0.0],
[-1.0, 1.0],
]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[1],
[2],
[3],
[4],
[5],
[6],
[7],
[8],
]
def test__3x3_grid_of_pixel_grid__add_multiple_grid_to_1_pixel_pixel(self):
# _ _ _
# -1.0 to -(1/3) |_|_|_|
# -(1/3) to (1/3) |_|_|_|
# (1/3) to 1.0 |_|_|_|
grid = np.array(
[
[1.0, -1.0],
[0.0, 0.0],
[1.0, 1.0],
[0.0, 0.0],
[0.0, 0.0],
[0.0, 0.0],
[-1.0, -1.0],
[0.0, 0.0],
[-1.0, 1.0],
]
)
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 3), grid=grid
)
mapper = aa.mapper(grid=grid, pixelization_grid=pixelization_grid)
assert (
mapper.pixelization_1d_index_for_sub_mask_1d_index
== np.array([0, 4, 2, 4, 4, 4, 6, 4, 8])
).all()
assert mapper.all_sub_mask_1d_indexes_for_pixelization_1d_index == [
[0],
[],
[2],
[],
[1, 3, 4, 5, 7],
[],
[6],
[],
[8],
]
def test__image_from_source__different_types_of_lists_input(self, sub_grid_7x7):
rectangular_pixelization_grid = aa.grid_rectangular.overlay_grid(
grid=sub_grid_7x7, shape_2d=(3, 3)
)
rectangular_mapper = aa.mapper(
grid=sub_grid_7x7, pixelization_grid=rectangular_pixelization_grid
)
image_pixel_indexes = rectangular_mapper.image_pixel_indexes_from_source_pixel_indexes(
source_pixel_indexes=[0, 1]
)
assert image_pixel_indexes == [0, 1, 2, 3, 4, 5, 6, 7]
image_pixel_indexes = rectangular_mapper.image_pixel_indexes_from_source_pixel_indexes(
source_pixel_indexes=[[0], [4]]
)
assert image_pixel_indexes == [[0, 1, 2, 3], [16, 17, 18, 19]]
def test__pixel_signals__compare_to_mapper_util(self, grid_7x7, image_7x7):
pixelization_grid = aa.grid_rectangular.overlay_grid(
shape_2d=(3, 3), grid=grid_7x7
)
mapper = aa.mapper(
grid=grid_7x7,
pixelization_grid=pixelization_grid,
hyper_image=image_7x7,
)
pixel_signals = mapper.pixel_signals_from_signal_scale(signal_scale=2.0)
pixel_signals_util = aa.util.mapper.adaptive_pixel_signals_from_images(
pixels=9,
signal_scale=2.0,
pixelization_1d_index_for_sub_mask_1d_index=mapper.pixelization_1d_index_for_sub_mask_1d_index,
mask_1d_index_for_sub_mask_1d_index=grid_7x7.regions._mask_1d_index_for_sub_mask_1d_index,
hyper_image=image_7x7,
)
assert (pixel_signals == pixel_signals_util).all()
[-0.6, -0.5],
[-0.4, -1.1],
[-1.2, 0.8],
[-1.5, 0.9],
],
shape_2d=(3, 3),
pixel_scales=1.0,
)
voronoi_grid = aa.grid_voronoi(
grid_1d=grid_9,
nearest_pixelization_1d_index_for_mask_1d_index=np.zeros(
shape=grid_7x7.shape_1d, dtype="int"
),
)
voronoi_mapper = aa.mapper(grid=grid_7x7, pixelization_grid=voronoi_grid)
regularization = aa.reg.Constant(coefficient=1.0)
inversion = aa.inversion(
masked_dataset=masked_imaging, mapper=voronoi_mapper, regularization=regularization
)
aplt.inversion.subplot_inversion(
inversion=inversion,
image_positions=[(0.05, 0.05)],
lines=[(0.0, 0.0), (0.1, 0.1)],
image_pixel_indexes=[0],
source_pixel_indexes=[5],
)
import autoarray as aa import autoarray.plot as aplt grid_7x7 = aa.grid.uniform(shape_2d=(7, 7), pixel_scales=0.3) grid_3x3 = aa.grid.uniform(shape_2d=(3, 3), pixel_scales=1.0) rectangular_grid = aa.grid_rectangular.overlay_grid(grid=grid_3x3, shape_2d=(3, 3)) rectangular_mapper = aa.mapper(grid=grid_7x7, pixelization_grid=rectangular_grid) aplt.mapper_obj(mapper=rectangular_mapper, include_pixelization_grid=True)
def make_voronoi_mapper_9_3x3(grid_7x7, voronoi_pixelization_grid_9):
return aa.mapper(grid=grid_7x7,
pixelization_grid=voronoi_pixelization_grid_9)
def make_rectangular_mapper_7x7_3x3(grid_7x7,
rectangular_pixelization_grid_3x3):
return aa.mapper(grid=grid_7x7,
pixelization_grid=rectangular_pixelization_grid_3x3)
