def test__positions_found_for_simple_mass_profiles(self):
grid = al.Grid.uniform(shape_2d=(100, 100), pixel_scales=0.05)
sis = al.mp.SphericalIsothermal(centre=(0.0, 0.0), einstein_radius=1.0)
solver = al.PositionsFinder(grid=grid, pixel_scale_precision=0.01)
positions = solver.solve(lensing_obj=sis,
source_plane_coordinate=(0.0, 0.11))
assert positions[0] == pytest.approx(np.array([0.003125, -0.89062]),
1.0e-4)
assert positions[1] == pytest.approx(np.array([-0.003125, -0.89062]),
1.0e-4)
grid = al.Grid.uniform(shape_2d=(100, 100),
pixel_scales=0.05,
sub_size=1)
g0 = al.Galaxy(
redshift=0.5,
mass=al.mp.EllipticalIsothermal(
centre=(0.001, 0.001),
einstein_radius=1.0,
elliptical_comps=(0.0, 0.111111),
),
)
g1 = al.Galaxy(redshift=1.0)
tracer = al.Tracer.from_galaxies(galaxies=[g0, g1])
solver = pos.PositionsFinder(grid=grid, pixel_scale_precision=0.01)
coordinates = solver.solve(lensing_obj=tracer,
source_plane_coordinate=(0.0, 0.0))
assert coordinates.in_grouped_list[0][0] == pytest.approx(
(1.028125, -0.003125), 1.0e-4)
assert coordinates.in_grouped_list[0][1] == pytest.approx(
(0.009375, -0.95312), 1.0e-4)
assert coordinates.in_grouped_list[0][2] == pytest.approx(
(0.009375, 0.95312), 1.0e-4)
assert coordinates.in_grouped_list[0][3] == pytest.approx(
(-1.028125, -0.003125), 1.0e-4)
path = "{}".format(os.path.dirname(os.path.realpath(__file__)))
pickle_path = f"{path}/pickles"
# %%
"""The initial grid for position solver which is upscaled iteratively by the solver."""
# %%
grid = al.Grid.uniform(
shape_2d=(200, 200),
pixel_scales=
0.05, # <- The pixel-scale describes the conversion from pixel units to arc-seconds.
)
"""Use a _PositionsSolver_ which uses grid upscaling."""
solver = al.PositionsFinder(grid=grid,
pixel_scale_precision=0.01,
upscale_factor=3)
iters = 50
for i in range(iters):
tracer = al.Tracer.load(file_path=pickle_path, filename=f"tracer_{str(i)}")
positions = solver.solve(
lensing_obj=tracer,
source_plane_coordinate=tracer.source_plane.galaxies[0].light.centre,
)
positions_true = al.GridCoordinates.load(file_path=pickle_path,
filename=f"positions_{str(i)}")
# %%
"""The initial grid for position solver which is upscaled iteratively by the solver."""
# %%
grid = al.Grid.uniform(
shape_2d=(2000, 2000),
pixel_scales=
0.005, # <- The pixel-scale describes the conversion from pixel units to arc-seconds.
)
"""Use a `PositionsSolver` which uses grid upscaling."""
solver = al.PositionsFinder(
grid=grid,
use_upscaling=True,
pixel_scale_precision=0.0000001,
upscale_factor=2,
distance_from_source_centre=0.1,
)
iters = 50
for i in range(40, 41):
tracer = al.Tracer.load(file_path=pickle_path, filename=f"tracer_{str(i)}")
positions = solver.solve(
lensing_obj=tracer,
source_plane_coordinate=tracer.source_plane.galaxies[0].light.centre,
)
def test__max_log_likelihood_tracer__multiple_image_positions_of_source_plane_centres_and_separations(
self, imaging_7x7, mask_7x7):
lens = al.Galaxy(
redshift=0.5,
mass=al.mp.EllipticalIsothermal(
centre=(0.001, 0.001),
einstein_radius=1.0,
elliptical_comps=(0.0, 0.111111),
),
)
source = al.Galaxy(
redshift=1.0,
light=al.lp.SphericalSersic(centre=(0.0, 0.0), intensity=2.0),
light1=al.lp.SphericalSersic(centre=(0.0, 0.1), intensity=2.0),
pixelization=al.pix.Rectangular((3, 3)),
regularization=al.reg.Constant(coefficient=1.0),
)
tracer = al.Tracer.from_galaxies(galaxies=[lens, source])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
phase_dataset_7x7 = al.PhaseImaging(
search=mock.MockSearch("test_phase_2", samples=samples))
result = phase_dataset_7x7.run(dataset=imaging_7x7,
mask=mask_7x7,
results=mock.MockResults())
mask = al.Mask2D.unmasked(shape_2d=(100, 100),
pixel_scales=0.05,
sub_size=1)
result.analysis.masked_dataset.mask = mask
multiple_images = (
result.image_plane_multiple_image_positions_of_source_plane_centres
)
grid = al.Grid.from_mask(mask=mask)
solver = al.PositionsFinder(grid=grid, pixel_scale_precision=0.001)
multiple_images_manual_0 = solver.solve(lensing_obj=tracer,
source_plane_coordinate=(0.0,
0.0))
multiple_images_manual_1 = solver.solve(lensing_obj=tracer,
source_plane_coordinate=(0.0,
0.1))
multiple_images_manual_2 = solver.solve(
lensing_obj=tracer,
source_plane_coordinate=result.source_plane_inversion_centres[0],
)
assert (multiple_images.in_grouped_list[0] ==
multiple_images_manual_0.in_grouped_list[0])
assert (multiple_images.in_grouped_list[1] ==
multiple_images_manual_1.in_grouped_list[0])
assert (multiple_images.in_grouped_list[2] ==
multiple_images_manual_2.in_grouped_list[0])
# %%
mass_profile_model = af.PriorModel(al.mp.EllipticalIsothermal)
mass_profile_model.centre.centre_0 = 0.0
mass_profile_model.centre.centre_1 = 0.0
mass_profile_model.elliptical_comps.ellipitical_comps_0 = af.UniformPrior(
lower_limit=-1.0, upper_limit=1.0)
mass_profile_model.elliptical_comps.ellipitical_comps_1 = af.UniformPrior(
lower_limit=-1.0, upper_limit=1.0)
mass_profile_model.centre.einstein_radius = af.UniformPrior(lower_limit=0.3,
upper_limit=2.0)
iters = 50
"""Use a _PositionsSolver_ which does not use grid upscaling."""
solver = al.PositionsFinder(grid=grid, use_upscaling=True, upscale_factor=2)
for i in range(iters):
"""Make a random _MassProfile_ instance from the priors defined above."""
mass_profile = mass_profile_model.random_instance()
"""
Only the _LightProfile_ centre is used by the position solver, but a light profile is used to visalize the
lensed source.
"""
exponential_light_profile = al.lp.EllipticalExponential(
centre=(0.0, 0.0),
elliptical_comps=(0.2, 0.0),
intensity=0.05,
effective_radius=0.2,
light_profile_model = af.PriorModel(al.lp.EllipticalExponential)
light_profile_model.centre.centre_0 = af.UniformPrior(lower_limit=-1.0,
upper_limit=1.0)
light_profile_model.centre.centre_1 = af.UniformPrior(lower_limit=-1.0,
upper_limit=1.0)
light_profile_model.elliptical_comps.elliptical_comps_0 = 0.2
light_profile_model.elliptical_comps.elliptical_comps_1 = 0.0
light_profile_model.intensity = 0.05
light_profile_model.effective_radius = 0.2
iters = 50
"""Use a `PositionsSolver` which does not use grid upscaling."""
solver = al.PositionsFinder(grid=grid,
use_upscaling=True,
pixel_scale_precision=0.0001,
upscale_factor=2)
for i in range(iters):
"""Make a random `MassProfile` instance from the priors defined above."""
mass_profile = mass_profile_model.random_instance()
"""
Only the `LightProfile` centre is used by the position solver, but a light profile is used to visalize the
lensed source.
"""
light_profile = light_profile_model.random_instance()
"""Setup the lens, source and _Tracer_."""
lens_galaxy = al.Galaxy(redshift=0.5, mass=mass_profile)