def test__results_of_phase_include_pixelization__available_as_property(
self, imaging_7x7, mask_7x7):
lens = al.Galaxy(redshift=0.5,
light=al.lp.EllipticalSersic(intensity=1.0))
source = al.Galaxy(
redshift=1.0,
pixelization=al.pix.VoronoiMagnification(shape=(2, 3)),
regularization=al.reg.Constant(),
)
tracer = al.Tracer.from_galaxies(galaxies=[lens, source])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
phase_imaging_7x7 = al.PhaseImaging(
settings=al.SettingsPhaseImaging(),
search=mock.MockSearch("test_phase", samples=samples),
)
result = phase_imaging_7x7.run(dataset=imaging_7x7,
mask=mask_7x7,
results=mock.MockResults())
assert isinstance(result.pixelization, al.pix.VoronoiMagnification)
assert result.pixelization.shape == (2, 3)
lens = al.Galaxy(redshift=0.5,
light=al.lp.EllipticalSersic(intensity=1.0))
source = al.Galaxy(
redshift=1.0,
pixelization=al.pix.VoronoiBrightnessImage(pixels=6),
regularization=al.reg.Constant(),
)
source.hyper_galaxy_image = np.ones(9)
tracer = al.Tracer.from_galaxies(galaxies=[lens, source])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
phase_imaging_7x7 = al.PhaseImaging(
settings=al.SettingsPhaseImaging(),
search=mock.MockSearch("test_phase", samples=samples),
)
result = phase_imaging_7x7.run(dataset=imaging_7x7,
mask=mask_7x7,
results=mock.MockResults())
assert isinstance(result.pixelization, al.pix.VoronoiBrightnessImage)
assert result.pixelization.pixels == 6
def test__max_log_likelihood_tracer_source_light_profile_centres_correct(
self, analysis_imaging_7x7):
lens = al.Galaxy(redshift=0.5, light=al.lp.SphSersic(intensity=1.0))
source = al.Galaxy(redshift=1.0,
light=al.lp.SphSersic(centre=(1.0, 2.0),
intensity=2.0))
tracer = al.Tracer.from_galaxies(galaxies=[lens, source])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
result = res.Result(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
assert result.source_plane_light_profile_centre.in_list == [(1.0, 2.0)]
source = al.Galaxy(
redshift=1.0,
light=al.lp.SphSersic(centre=(1.0, 2.0), intensity=2.0),
light1=al.lp.SphSersic(centre=(3.0, 4.0), intensity=2.0),
)
source_1 = al.Galaxy(redshift=1.0,
light=al.lp.SphSersic(centre=(5.0, 6.0),
intensity=2.0))
tracer = al.Tracer.from_galaxies(galaxies=[lens, source, source_1])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
result = res.Result(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
assert result.source_plane_light_profile_centre.in_list == [(1.0, 2.0)]
tracer = al.Tracer.from_galaxies(galaxies=[al.Galaxy(redshift=0.5)])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
result = res.Result(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
assert result.source_plane_light_profile_centre == None
def make_samples():
galaxy_0 = al.Galaxy(redshift=0.5, light=al.lp.EllSersic(centre=(0.0, 1.0)))
galaxy_1 = al.Galaxy(redshift=1.0, light=al.lp.EllSersic())
tracer = al.Tracer.from_galaxies(galaxies=[galaxy_0, galaxy_1])
return mock.MockSamples(max_log_likelihood_instance=tracer)
def test___image_dict(self, analysis_imaging_7x7):
galaxies = af.ModelInstance()
galaxies.lens = al.Galaxy(redshift=0.5)
galaxies.source = al.Galaxy(redshift=1.0)
instance = af.ModelInstance()
instance.galaxies = galaxies
result = ResultImaging(
samples=mock.MockSamples(max_log_likelihood_instance=instance),
model=af.ModelMapper(),
analysis=analysis_imaging_7x7,
search=None,
)
image_dict = result.image_galaxy_dict
assert isinstance(image_dict[("galaxies", "lens")], np.ndarray)
assert isinstance(image_dict[("galaxies", "source")], np.ndarray)
result.instance.galaxies.lens = al.Galaxy(redshift=0.5)
image_dict = result.image_galaxy_dict
assert (image_dict[("galaxies", "lens")].native == np.zeros(
(7, 7))).all()
assert isinstance(image_dict[("galaxies", "source")], np.ndarray)
def test__image_plane_multiple_image_positions_and_threshold(
self, analysis_imaging_7x7):
tracer = al.Tracer.from_galaxies(galaxies=[
al.Galaxy(
redshift=0.5,
mass=al.mp.EllIsothermal(
centre=(0.1, 0.0),
einstein_radius=1.0,
elliptical_comps=(0.0, 0.0),
),
),
al.Galaxy(redshift=1.0, bulge=al.lp.SphSersic(centre=(0.0, 0.0))),
])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
result = res.Result(samples=samples,
model=None,
analysis=analysis_imaging_7x7,
search=None)
assert result.image_plane_multiple_image_positions.in_list[0][
0] == pytest.approx(1.0004, 1.0e-2)
assert result.image_plane_multiple_image_positions.in_list[1][
0] == pytest.approx(-1.0004, 1.0e-2)
assert result.positions_threshold_from() == pytest.approx(
0.000973519, 1.0e-4)
assert result.positions_threshold_from(factor=5.0) == pytest.approx(
5.0 * 0.000973519, 1.0e-4)
assert result.positions_threshold_from(
minimum_threshold=0.2) == pytest.approx(0.2, 1.0e-4)
def test___image_dict(self, masked_imaging_7x7):
galaxies = af.ModelInstance()
galaxies.lens = al.Galaxy(redshift=0.5)
galaxies.source = al.Galaxy(redshift=1.0)
instance = af.ModelInstance()
instance.galaxies = galaxies
analysis = al.PhaseImaging.Analysis(
masked_imaging=masked_imaging_7x7,
settings=al.SettingsPhaseImaging(),
results=mock.MockResults(),
cosmology=cosmo.Planck15,
)
result = al.PhaseImaging.Result(
samples=mock.MockSamples(max_log_likelihood_instance=instance),
previous_model=af.ModelMapper(),
analysis=analysis,
search=None,
)
image_dict = result.image_galaxy_dict
assert isinstance(image_dict[("galaxies", "lens")], np.ndarray)
assert isinstance(image_dict[("galaxies", "source")], np.ndarray)
result.instance.galaxies.lens = al.Galaxy(redshift=0.5)
image_dict = result.image_galaxy_dict
assert (image_dict[("galaxies", "lens")].native == np.zeros(
(7, 7))).all()
assert isinstance(image_dict[("galaxies", "source")], np.ndarray)
def test__max_log_likelihood_tracer_source_centres_correct(
self, imaging_7x7, mask_7x7
):
lens = al.Galaxy(redshift=0.5, light=al.lp.SphericalSersic(intensity=1.0))
source = al.Galaxy(
redshift=1.0,
light=al.lp.SphericalSersic(centre=(9.0, 8.0), 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()
)
assert result.source_plane_centre.in_list == [(0.0, 0.0)]
def test__results_include_pixelization__available_as_property(
self, analysis_imaging_7x7):
lens = al.Galaxy(redshift=0.5, light=al.lp.EllSersic(intensity=1.0))
source = al.Galaxy(
redshift=1.0,
pixelization=al.pix.VoronoiMagnification(shape=(2, 3)),
regularization=al.reg.Constant(),
)
tracer = al.Tracer.from_galaxies(galaxies=[lens, source])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
result = res.ResultDataset(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
assert isinstance(result.pixelization, al.pix.VoronoiMagnification)
assert result.pixelization.shape == (2, 3)
lens = al.Galaxy(redshift=0.5, light=al.lp.EllSersic(intensity=1.0))
source = al.Galaxy(
redshift=1.0,
pixelization=al.pix.VoronoiBrightnessImage(pixels=6),
regularization=al.reg.Constant(),
)
source.hyper_galaxy_image = np.ones(9)
tracer = al.Tracer.from_galaxies(galaxies=[lens, source])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
result = res.ResultDataset(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
assert isinstance(result.pixelization, al.pix.VoronoiBrightnessImage)
assert result.pixelization.pixels == 6
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_native=(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.Grid2D.from_mask(mask=mask)
solver = al.PositionsSolver(grid=grid, pixel_scale_precision=0.001)
multiple_images_manual = solver.solve(
lensing_obj=tracer,
source_plane_coordinate=result.source_plane_inversion_centre[0],
)
assert multiple_images.in_list[0] == multiple_images_manual.in_list[0]
def test__max_log_likelihood_tracer_source_inversion_centres_correct(
self, analysis_imaging_7x7):
lens = al.Galaxy(redshift=0.5, light=al.lp.SphSersic(intensity=1.0))
source = al.Galaxy(
redshift=1.0,
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)
result = ResultImaging(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
assert (result.source_plane_inversion_centre.in_list[0] ==
result.max_log_likelihood_fit.inversion.
brightest_reconstruction_pixel_centre_list[0].in_list[0])
lens = al.Galaxy(redshift=0.5, light=al.lp.SphSersic(intensity=1.0))
source = al.Galaxy(redshift=1.0)
tracer = al.Tracer.from_galaxies(galaxies=[lens, source])
samples = mock.MockSamples(max_log_likelihood_instance=tracer)
result = ResultImaging(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
assert result.source_plane_inversion_centre == None
def make_samples(model):
galaxy_0 = al.Galaxy(redshift=0.5,
light=al.lp.EllSersic(centre=(0.0, 1.0)))
galaxy_1 = al.Galaxy(redshift=1.0, light=al.lp.EllSersic())
tracer = al.Tracer.from_galaxies(galaxies=[galaxy_0, galaxy_1])
parameters = [model.prior_count * [1.0], model.prior_count * [10.0]]
sample_list = Sample.from_lists(
model=model,
parameter_lists=parameters,
log_likelihood_list=[1.0, 2.0],
log_prior_list=[0.0, 0.0],
weight_list=[0.0, 1.0],
)
return mock.MockSamples(model=model,
sample_list=sample_list,
max_log_likelihood_instance=tracer)
def test__max_log_likelihood_tracer__multiple_image_positions_of_source_plane_centres_and_separations(
self, analysis_imaging_7x7):
lens = al.Galaxy(
redshift=0.5,
mass=al.mp.EllIsothermal(
centre=(0.001, 0.001),
einstein_radius=1.0,
elliptical_comps=(0.0, 0.111111),
),
)
source = al.Galaxy(
redshift=1.0,
light=al.lp.SphSersic(centre=(0.0, 0.0), intensity=2.0),
light1=al.lp.SphSersic(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)
result = ResultImaging(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
multiple_images = result.image_plane_multiple_image_positions
assert multiple_images.in_list[0][0] == pytest.approx(
1.20556641, 1.0e-4)
assert multiple_images.in_list[0][1] == pytest.approx(
-1.10205078, 1.0e-4)
assert multiple_images.in_list[1][0] == pytest.approx(
-0.19287109, 1.0e-4)
assert multiple_images.in_list[1][1] == pytest.approx(
0.27978516, 1.0e-4)
def test__max_log_likelihood_tracer_source_centres_correct(
self, analysis_imaging_7x7):
lens = al.Galaxy(redshift=0.5, light=al.lp.SphSersic(intensity=1.0))
source = al.Galaxy(
redshift=1.0,
light=al.lp.SphSersic(centre=(9.0, 8.0), 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)
result = ResultImaging(samples=samples,
analysis=analysis_imaging_7x7,
model=None,
search=None)
assert result.source_plane_centre.in_list[0] == pytest.approx(
(-0.916666, -0.916666), 1.0e-4)
def test__make_result__result_imaging_is_returned(self,
masked_imaging_7x7):
model = af.Collection(galaxies=af.Collection(galaxy_0=al.Galaxy(
redshift=0.5)))
instance = model.instance_from_prior_medians()
samples = mock.MockSamples(max_log_likelihood_instance=instance)
search = mock.MockSearch(name="test_search", samples=samples)
analysis = al.AnalysisImaging(dataset=masked_imaging_7x7)
def modify_after_fit(paths: af.DirectoryPaths,
model: af.AbstractPriorModel, result: af.Result):
pass
analysis.modify_after_fit = modify_after_fit
result = search.fit(model=model, analysis=analysis)
assert isinstance(result, ResultImaging)
def test__max_log_likelihood_tracer_source_light_profile_centres_correct(
self, imaging_7x7, mask_7x7):
lens = al.Galaxy(redshift=0.5,
light=al.lp.SphericalSersic(intensity=1.0))
source = al.Galaxy(redshift=1.0,
light=al.lp.SphericalSersic(centre=(1.0, 2.0),
intensity=2.0))
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())
assert result.source_plane_light_profile_centres.in_grouped_list == [[
(1.0, 2.0)
]]
source = al.Galaxy(
redshift=1.0,
light=al.lp.SphericalSersic(centre=(1.0, 2.0), intensity=2.0),
light1=al.lp.SphericalSersic(centre=(3.0, 4.0), intensity=2.0),
)
source_1 = al.Galaxy(redshift=1.0,
light=al.lp.SphericalSersic(centre=(5.0, 6.0),
intensity=2.0))
tracer = al.Tracer.from_galaxies(galaxies=[lens, source, source_1])
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())
assert result.source_plane_light_profile_centres.in_grouped_list == [
[(1.0, 2.0), (3.0, 4.0)],
[(5.0, 6.0)],
]
tracer = al.Tracer.from_galaxies(galaxies=[al.Galaxy(redshift=0.5)])
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())
assert result.source_plane_light_profile_centres == []
