def test_addition(self):
phase_1 = DummyPhaseImaging("one")
phase_2 = DummyPhaseImaging("two")
phase_3 = DummyPhaseImaging("three")
pipeline1 = al.PipelineDataset("", phase_1, phase_2)
pipeline2 = al.PipelineDataset("", phase_3)
assert (phase_1, phase_2, phase_3) == (pipeline1 + pipeline2).phases
def make_pipeline(
name,
phase_folders,
real_space_shape_2d=(100, 100),
real_space_pixel_scales=(0.1, 0.1),
optimizer_class=af.MultiNest,
):
class LensPlanex2GalPhase(al.PhaseInterferometer):
def customize_priors(self, results):
self.galaxies.lens_0.light.centre_0 = -1.0
self.galaxies.lens_0.light.centre_1 = -1.0
self.galaxies.lens_1.light.centre_0 = 1.0
self.galaxies.lens_1.light.centre_1 = 1.0
phase1 = LensPlanex2GalPhase(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens_0=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic),
lens_1=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic),
),
real_space_shape_2d=real_space_shape_2d,
real_space_pixel_scales=real_space_pixel_scales,
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 40
phase1.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1)
def make_pipeline(name, phase_folders, non_linear_class=af.MultiNest):
class MMPhase(al.PhaseImaging):
pass
phase1 = MMPhase(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(lens=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic)),
non_linear_class=non_linear_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 20
phase1.optimizer.sampling_efficiency = 0.8
class MMPhase2(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens = results.from_phase("phase_1").model.lens
phase2 = MMPhase2(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(lens=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic)),
non_linear_class=non_linear_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 20
phase2.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, phase_folders, non_linear_class=af.MultiNest):
phase1 = al.PhaseImaging(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=al.mp.EllipticalIsothermal),
source_0=al.GalaxyModel(redshift=1.0, sersic=al.lp.EllipticalSersic),
),
non_linear_class=non_linear_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 60
phase1.optimizer.sampling_efficiency = 0.7
phase2 = al.PhaseImaging(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(
lens=phase1.result.model.galaxies.lens,
source_0=phase1.result.model.galaxies.source_0,
source_1=al.GalaxyModel(redshift=1.0, sersic=al.lp.EllipticalSersic),
source_2=al.GalaxyModel(redshift=1.0, sersic=al.lp.EllipticalSersic),
),
non_linear_class=non_linear_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 60
phase2.optimizer.sampling_efficiency = 0.7
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, phase_folders, non_linear_class=af.MultiNest):
class LensPhase(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens.mass.centre_0 = af.GaussianPrior(mean=4.0, sigma=0.1)
self.galaxies.lens.mass.centre_1 = af.GaussianPrior(mean=4.0, sigma=0.1)
self.galaxies.source.light.centre_0 = af.GaussianPrior(mean=4.0, sigma=0.1)
self.galaxies.source.light.centre_1 = af.GaussianPrior(mean=4.0, sigma=0.1)
phase1 = LensPhase(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=al.mp.SphericalIsothermal),
source=al.GalaxyModel(redshift=1.0, light=al.lp.EllipticalSersic),
),
positions_threshold=0.5,
non_linear_class=non_linear_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 30
phase1.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1)
def make_pipeline(name, phase_folders, non_linear_class=af.MultiNest):
phase1 = al.PhaseImaging(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=al.mp.EllipticalIsothermal),
source=al.GalaxyModel(redshift=1.0, sersic=al.lp.EllipticalSersic),
),
sub_size=1,
non_linear_class=non_linear_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 20
phase1.optimizer.sampling_efficiency = 0.8
# We want to set up the source from the result, where:
# If it is parametric, it is a model (thus N = 12).
# If it is an inversion, it is an instance (Thus N = 5)
# When we use af.last, this fails, because the promise pixelizzation attribute is another promise.
source = source_with_previous_model_or_instance()
phase2 = al.PhaseImaging(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(lens=phase1.result.model.galaxies.lens, source=source),
sub_size=1,
non_linear_class=non_linear_class,
)
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, folders, search=af.DynestyStatic()):
phase1 = al.PhaseImaging(
phase_name="phase_1",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=al.mp.EllipticalIsothermal),
source_0=al.GalaxyModel(redshift=1.0,
light=al.lp.EllipticalSersic),
),
search=search,
)
phase2 = al.PhaseImaging(
phase_name="phase_2",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5,
mass=phase1.result.model.galaxies.lens.mass),
source_0=al.GalaxyModel(
redshift=1.0,
light=phase1.result.model.galaxies.source_0.light),
source_1=al.GalaxyModel(redshift=1.0,
light=al.lp.EllipticalSersic),
),
search=search,
)
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, folders, real_space_mask, search=af.DynestyStatic()):
mass = af.PriorModel(al.mp.EllipticalIsothermal)
mass.centre.centre_0 = 0.0
mass.centre.centre_1 = 0.0
mass.einstein_radius = 1.6
pixelization = af.PriorModel(al.pix.Rectangular)
pixelization.shape_0 = 20.0
pixelization.shape_1 = 20.0
phase1 = al.PhaseInterferometer(
phase_name="phase_1",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5,
bulge=al.lp.SphericalDevVaucouleurs,
mass=mass),
source=al.GalaxyModel(redshift=1.0,
pixelization=pixelization,
regularization=al.reg.Constant),
),
real_space_mask=real_space_mask,
search=search,
)
phase1.search.const_efficiency_mode = True
phase1.search.n_live_points = 60
phase1.search.facc = 0.8
return al.PipelineDataset(name, phase1)
def make_pipeline(name, phase_folders, optimizer_class=af.MultiNest):
sersic = af.PriorModel(al.lp.EllipticalSersic)
# This will lead to pretty weird results
sersic.add_assertion(sersic.axis_ratio > sersic.intensity)
phase1 = al.PhaseImaging(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(lens=al.GalaxyModel(redshift=0.5, sersic=sersic)),
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 40
phase1.optimizer.sampling_efficiency = 0.8
# TODO : And even with them not causing errors above, the promise doesnt work.
phase2 = al.PhaseImaging(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(lens=phase1.result.model.galaxies.lens),
optimizer_class=optimizer_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 40
phase2.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, phase_folders, optimizer_class=af.MultiNest):
phase1 = al.PhaseImaging(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic)),
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 40
phase1.optimizer.sampling_efficiency = 0.8
phase1 = phase1.extend_with_multiple_hyper_phases(hyper_galaxy=True)
phase2 = al.PhaseImaging(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(lens=al.GalaxyModel(
redshift=0.5,
light=phase1.result.model.galaxies.lens.light,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.lens.
hyper_galaxy,
)),
optimizer_class=optimizer_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 40
phase2.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(
name,
phase_folders,
real_space_shape_2d=(100, 100),
real_space_pixel_scales=(0.1, 0.1),
optimizer_class=af.MultiNest,
):
phase1 = al.PhaseInterferometer(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
light=al.lp.SphericalDevVaucouleurs,
mass=al.mp.EllipticalIsothermal,
),
source=al.GalaxyModel(redshift=1.0, light=al.lp.EllipticalSersic),
),
real_space_shape_2d=real_space_shape_2d,
real_space_pixel_scales=real_space_pixel_scales,
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 60
phase1.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1)
def make_pipeline(
name,
phase_folders,
real_space_shape_2d=(100, 100),
real_space_pixel_scales=(0.1, 0.1),
optimizer_class=af.MultiNest,
):
phase1 = al.PhaseInterferometer(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
light=al.lp.SphericalDevVaucouleurs,
mass=al.mp.EllipticalIsothermal,
),
source=al.GalaxyModel(redshift=1.0, light=al.lp.EllipticalSersic),
),
real_space_shape_2d=real_space_shape_2d,
real_space_pixel_scales=real_space_pixel_scales,
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 60
phase1.optimizer.sampling_efficiency = 0.8
phase1 = phase1.extend_with_multiple_hyper_phases(hyper_galaxy=True)
phase2 = al.PhaseInterferometer(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
light=phase1.result.model.galaxies.lens.light,
mass=phase1.result.model.galaxies.lens.mass,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.
lens.hyper_galaxy,
),
source=al.GalaxyModel(
redshift=1.0,
light=phase1.result.model.galaxies.source.light,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.
source.hyper_galaxy,
),
),
real_space_shape_2d=real_space_shape_2d,
real_space_pixel_scales=real_space_pixel_scales,
optimizer_class=optimizer_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 40
phase2.optimizer.sampling_efficiency = 0.8
phase2 = phase2.extend_with_multiple_hyper_phases(hyper_galaxy=True)
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, phase_folders, optimizer_class=af.MultiNest):
class SourcePix(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens.mass.centre.centre_0 = 0.0
self.galaxies.lens.mass.centre.centre_1 = 0.0
self.galaxies.lens.mass.einstein_radius = 1.6
self.galaxies.source.pixelization.shape_0 = 20.0
self.galaxies.source.pixelization.shape_1 = 20.0
phase1 = SourcePix(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
light=al.lp.SphericalDevVaucouleurs,
mass=al.mp.EllipticalIsothermal,
),
source=al.GalaxyModel(
redshift=1.0,
pixelization=al.pix.VoronoiMagnification,
regularization=al.reg.Constant,
),
),
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 60
phase1.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1)
def make_pipeline(name, phase_folders, optimizer_class=af.MultiNest):
class MMPhase(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens_0.light.axis_ratio = 0.2
self.galaxies.lens_0.light.phi = 90.0
self.galaxies.lens_0.light.centre_0 = 1.0
self.galaxies.lens_0.light.centre_1 = 2.0
self.galaxies.lens_1.light.axis_ratio = 0.2
self.galaxies.lens_1.light.phi = 90.0
self.galaxies.lens_1.light.centre_0 = 1.0
self.galaxies.lens_1.light.centre_1 = 2.0
phase1 = MMPhase(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens_0=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic),
lens_1=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic),
),
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 20
phase1.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1)
def make_pipeline(
name,
phase_folders,
real_space_shape_2d=(100, 100),
real_space_pixel_scales=(0.1, 0.1),
non_linear_class=af.MultiNest,
):
class LensPlaneGalaxyX2Phase(al.PhaseInterferometer):
def customize_priors(self, results):
self.galaxies.lens_0.light.centre_0 = -1.0
self.galaxies.lens_0.light.centre_1 = -1.0
self.galaxies.lens_1.light.centre_0 = 1.0
self.galaxies.lens_1.light.centre_1 = 1.0
phase1 = LensPlaneGalaxyX2Phase(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens_0=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic),
lens_1=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic),
),
real_space_shape_2d=real_space_shape_2d,
real_space_pixel_scales=real_space_pixel_scales,
non_linear_class=non_linear_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 40
phase1.optimizer.sampling_efficiency = 0.8
phase1 = phase1.extend_with_multiple_hyper_phases(hyper_galaxy=True)
phase2 = al.PhaseInterferometer(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(
lens_0=al.GalaxyModel(
redshift=0.5,
light=phase1.result.model.galaxies.lens_0.light,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.lens_0.hyper_galaxy,
),
lens_1=al.GalaxyModel(
redshift=0.5,
light=phase1.result.model.galaxies.lens_1.light,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.lens_1.hyper_galaxy,
),
),
real_space_shape_2d=real_space_shape_2d,
real_space_pixel_scales=real_space_pixel_scales,
non_linear_class=non_linear_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 40
phase2.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, phase_folders, optimizer_class=af.MultiNest):
class QuickPhase(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens.light.centre_0 = af.UniformPrior(
lower_limit=-0.01, upper_limit=0.01)
self.galaxies.lens.light.centre_1 = af.UniformPrior(
lower_limit=-0.01, upper_limit=0.01)
self.galaxies.lens.light.axis_ratio = af.UniformPrior(
lower_limit=0.79, upper_limit=0.81)
self.galaxies.lens.light.phi = af.UniformPrior(lower_limit=-1.0,
upper_limit=1.0)
self.galaxies.lens.light.intensity = af.UniformPrior(
lower_limit=0.99, upper_limit=1.01)
self.galaxies.lens.light.effective_radius = af.UniformPrior(
lower_limit=1.25, upper_limit=1.35)
self.galaxies.lens.light.sersic_index = af.UniformPrior(
lower_limit=3.95, upper_limit=4.05)
phase1 = QuickPhase(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic)),
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 40
phase1.optimizer.sampling_efficiency = 0.8
class GridPhase(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens.light.centre_0 = 0.0
self.galaxies.lens.light.centre_1 = 0.0
self.galaxies.lens.light.axis_ratio = results.from_phase(
"phase_1").instance.lens.light.axis_ratio
self.galaxies.lens.light.phi = results.from_phase(
"phase_1").instance.lens.light.phi
self.galaxies.lens.light.intensity = results.from_phase(
"phase_1").instance.lens.light.intensity
self.galaxies.lens.light.effective_radius = af.UniformPrior(
lower_limit=0.0, upper_limit=4.0)
self.galaxies.lens.light.sersic_index = af.UniformPrior(
lower_limit=1.0, upper_limit=8.0)
phase2 = GridPhase(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, light=al.lp.EllipticalSersic)),
optimizer_class=af.GridSearch,
)
phase2.optimizer.const_efficiency_mode = True
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, phase_folders, non_linear_class=af.MultiNest):
phase1 = al.PhaseImaging(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
light=al.lp.SphericalDevVaucouleurs,
mass=al.mp.EllipticalIsothermal,
),
source=al.GalaxyModel(redshift=1.0, light=al.lp.EllipticalSersic),
),
non_linear_class=non_linear_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 60
phase1.optimizer.sampling_efficiency = 0.8
phase1 = phase1.extend_with_multiple_hyper_phases(
hyper_galaxy=True,
include_background_sky=True,
include_background_noise=True)
phase2 = al.PhaseImaging(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
light=phase1.result.model.galaxies.lens.light,
mass=phase1.result.model.galaxies.lens.mass,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.
lens.hyper_galaxy,
),
source=al.GalaxyModel(
redshift=1.0,
light=phase1.result.model.galaxies.source.light,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.
source.hyper_galaxy,
),
),
hyper_image_sky=phase1.result.hyper_combined.instance.hyper_image_sky,
hyper_background_noise=phase1.result.hyper_combined.instance.
hyper_background_noise,
non_linear_class=non_linear_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 40
phase2.optimizer.sampling_efficiency = 0.8
phase2 = phase2.extend_with_multiple_hyper_phases(
hyper_galaxy=True,
include_background_sky=True,
include_background_noise=True)
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, folders, real_space_mask, search=af.DynestyStatic()):
mass = af.PriorModel(al.mp.EllipticalIsothermal)
mass.centre.centre_0 = 2.0
mass.centre.centre_1 = 2.0
mass.einstein_radius = 1.6
pixelization = af.PriorModel(al.pix.VoronoiMagnification)
pixelization.shape_0 = 20.0
pixelization.shape_1 = 20.0
phase1 = al.PhaseInterferometer(
phase_name="phase_1",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=mass),
source=al.GalaxyModel(redshift=1.0,
pixelization=pixelization,
regularization=al.reg.Constant),
),
real_space_mask=real_space_mask,
search=search,
)
phase1.search.const_efficiency_mode = True
phase1.search.n_live_points = 60
phase1.search.facc = 0.8
phase1 = phase1.extend_with_inversion_phase()
phase2 = al.PhaseInterferometer(
phase_name="phase_2",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5,
mass=phase1.result.model.galaxies.lens.mass),
source=al.GalaxyModel(
redshift=1.0,
pixelization=phase1.results.settings_inversion.instance.
galaxies.source.pixelization,
regularization=phase1.results.settings_inversion.instance.
galaxies.source.regularization,
),
),
real_space_mask=real_space_mask,
search=search,
)
phase2.search.const_efficiency_mode = True
phase2.search.n_live_points = 60
phase2.search.facc = 0.8
phase2 = phase2.extend_with_inversion_phase()
return al.PipelineDataset(name, phase1, phase2)
def test_run_pipeline(self):
phase_1 = DummyPhaseImaging("one")
phase_2 = DummyPhaseImaging("two")
pipeline = al.PipelineDataset("", phase_1, phase_2)
pipeline.run(dataset=MockImagingData(), mask=MockMask())
assert len(phase_2.results) == 2
def test_pass_mask(self):
mask = MockMask()
phase_1 = DummyPhaseImaging("one")
phase_2 = DummyPhaseImaging("two")
pipeline = al.PipelineDataset("", phase_1, phase_2)
pipeline.run(dataset=MockImagingData(), mask=mask)
assert phase_1.mask is mask
assert phase_2.mask is mask
def make_pipeline(name, folders, search=af.DynestyStatic()):
phase1 = al.PhaseImaging(
phase_name="phase_1",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=al.mp.EllipticalIsothermal),
source=al.GalaxyModel(redshift=1.0, light=al.lp.EllipticalSersic),
),
search=af.DynestyStatic(n_live_points=40, evidence_tolerance=10.0),
)
pixeliation = af.PriorModel(al.pix.VoronoiBrightnessImage)
pixeliation.pixels = 100
phase1 = phase1.extend_with_multiple_hyper_phases(setup=al.SetupPipeline(),
include_inversion=False)
phase2 = al.PhaseImaging(
phase_name="phase_2",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5, mass=phase1.result.instance.galaxies.lens.mass),
source=al.GalaxyModel(
redshift=1.0,
pixelization=pixeliation,
regularization=al.reg.AdaptiveBrightness,
),
),
search=af.DynestyStatic(n_live_points=40, evidence_tolerance=10.0),
)
phase2 = phase2.extend_with_multiple_hyper_phases(setup=al.SetupPipeline(),
include_inversion=True)
phase3 = al.PhaseImaging(
phase_name="phase_3",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5,
mass=phase1.result.model.galaxies.lens.mass),
source=al.GalaxyModel(
redshift=1.0,
pixelization=phase2.result.instance.galaxies.source.
pixelization,
regularization=phase2.result.instance.galaxies.source.
regularization,
),
),
search=af.DynestyStatic(n_live_points=40, evidence_tolerance=10.0),
)
return al.PipelineDataset(name, phase1, phase2, phase3)
def make_pipeline(name, phase_folders, non_linear_class=af.MultiNest):
class SourcePix(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens.mass.centre.centre_0 = 0.0
self.galaxies.lens.mass.centre.centre_1 = 0.0
self.galaxies.lens.mass.einstein_radius = 1.6
phase1 = SourcePix(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=al.mp.EllipticalIsothermal),
source=al.GalaxyModel(
redshift=1.0,
pixelization=al.pix.Rectangular,
regularization=al.reg.Constant,
),
),
non_linear_class=non_linear_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 60
phase1.optimizer.sampling_efficiency = 0.8
phase1.extend_with_multiple_hyper_phases(hyper_galaxy=True)
phase2 = al.PhaseImaging(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
mass=phase1.result.model.galaxies.lens.mass,
hyper_galaxy=al.HyperGalaxy,
),
source=al.GalaxyModel(
redshift=1.0,
pixelization=phase1.result.model.galaxies.source.pixelization,
regularization=phase1.result.model.galaxies.source.
regularization,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.
source.hyper_galaxy,
),
),
non_linear_class=non_linear_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 40
phase2.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, phase_folders, non_linear_class=af.MultiNest):
phase1 = al.PhaseImaging(
phase_name="phase_1__lens_bulge_disk",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
light=al.lp.SphericalDevVaucouleurs,
mass=al.mp.EllipticalIsothermal,
),
source=al.GalaxyModel(redshift=1.0, light=al.lp.EllipticalSersic),
),
non_linear_class=af.MultiNest,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 40
phase1.optimizer.sampling_efficiency = 0.3
lens = al.setup.lens_with_light_only_from_result(result=af.last,
fix_lens_light=True)
# Setup the power-law mass profile and initialize its priors from the SIE.
mass = af.PriorModel(al.mp.EllipticalPowerLaw)
mass.centre = af.last.model.galaxies.lens.mass.centre
mass.axis_ratio = af.last.model.galaxies.lens.mass.axis_ratio
mass.phi = af.last.model.galaxies.lens.mass.phi
mass.einstein_radius = af.last.model_absolute(
a=0.3).galaxies.lens.mass.einstein_radius
lens.mass = mass
lens.hyper_galaxy = (
af.last.hyper_combined.instance.optional.galaxies.lens.hyper_galaxy)
phase2 = al.PhaseImaging(
phase_name="phase_2__lens_power_law__source",
phase_folders=phase_folders,
galaxies=dict(lens=lens,
source=phase1.result.instance.galaxies.source),
hyper_image_sky=af.last.hyper_combined.instance.optional.
hyper_image_sky,
hyper_background_noise=af.last.hyper_combined.instance.optional.
hyper_background_noise,
non_linear_class=af.MultiNest,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 75
phase2.optimizer.sampling_efficiency = 0.2
return al.PipelineDataset(name, phase1, phase2)
def test_files(self, mock_files):
pipeline = al.PipelineDataset(
"pipeline_name", DummyPhaseImaging(phase_name="phase_name"))
pipeline.run(dataset=MockImagingData(), mask=MockMask())
assert (
mock_files[2].text ==
"phase=phase_name\nphase_tag=\npipeline=pipeline_name\npipeline_tag=\ndataset_name=data_name"
)
assert "phase_name///optimizer.pickle" in mock_files[3].filename
def test_pass_positions(self):
positions = [[(1.0, 1.0), (2.0, 2.0)]]
phase_1 = DummyPhaseImaging("one")
phase_2 = DummyPhaseImaging("two")
pipeline = al.PipelineDataset("", phase_1, phase_2)
pipeline.run(dataset=MockImagingData(),
mask=MockMask(),
positions=positions)
assert phase_1.positions == positions
assert phase_2.positions == positions
def make_pipeline(name, folders, search=af.DynestyStatic()):
mass = af.PriorModel(al.mp.EllipticalIsothermal)
mass.centre.centre_0 = 0.0
mass.centre.centre_1 = 0.0
mass.einstein_radius = 1.6
phase1 = al.PhaseImaging(
phase_name="phase_1",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=mass),
source=al.GalaxyModel(
redshift=1.0,
pixelization=al.pix.Rectangular,
regularization=al.reg.Constant,
),
),
search=search,
)
phase1.search.const_efficiency_mode = True
phase1.search.n_live_points = 60
phase1.search.facc = 0.8
phase1.extend_with_multiple_hyper_phases(hyper_galaxies_search=True)
phase2 = al.PhaseImaging(
phase_name="phase_2",
folders=folders,
galaxies=dict(
lens=al.GalaxyModel(
redshift=0.5,
mass=phase1.result.model.galaxies.lens.mass,
hyper_galaxy=al.HyperGalaxy,
),
source=al.GalaxyModel(
redshift=1.0,
pixelization=phase1.result.model.galaxies.source.pixelization,
regularization=phase1.result.model.galaxies.source.regularization,
hyper_galaxy=phase1.result.hyper_combined.instance.galaxies.source.hyper_galaxy,
),
),
search=search,
)
phase2.search.const_efficiency_mode = True
phase2.search.n_live_points = 40
phase2.search.facc = 0.8
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(name, phase_folders, optimizer_class=af.MultiNest):
class SourcePix(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens.mass.centre.centre_0 = 2.0
self.galaxies.lens.mass.centre.centre_1 = 2.0
self.galaxies.lens.mass.einstein_radius = 1.2
phase1 = SourcePix(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5, mass=al.mp.EllipticalIsothermal),
source=al.GalaxyModel(
redshift=1.0,
pixelization=al.pix.VoronoiMagnification,
regularization=al.reg.Constant,
),
),
optimizer_class=optimizer_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 60
phase1.optimizer.sampling_efficiency = 0.8
phase1 = phase1.extend_with_inversion_phase()
phase2 = al.PhaseImaging(
phase_name="phase_2",
phase_folders=phase_folders,
galaxies=dict(
lens=al.GalaxyModel(redshift=0.5,
mass=phase1.result.model.galaxies.lens.mass),
source=al.GalaxyModel(
redshift=1.0,
pixelization=phase1.result.inversion.instance.galaxies.source.
pixelization,
regularization=phase1.result.inversion.instance.galaxies.
source.regularization,
),
),
optimizer_class=optimizer_class,
)
phase2.optimizer.const_efficiency_mode = True
phase2.optimizer.n_live_points = 60
phase2.optimizer.sampling_efficiency = 0.8
phase2 = phase2.extend_with_inversion_phase()
return al.PipelineDataset(name, phase1, phase2)
def make_pipeline(slam, settings):
"""SETUP PIPELINE & PHASE NAMES, TAGS AND PATHS"""
pipeline_name = "pipeline_mass[total]"
"""
This pipeline is tagged according to whether:
1) Hyper-fitting settings (galaxies, sky, background noise) are used.
2) The lens galaxy mass model includes an `ExternalShear`.
3) The lens`s light model is fixed or variable.
"""
path_prefix = f"{slam.path_prefix}/{pipeline_name}/{slam.source_tag}/{slam.light_parametric_tag}/{slam.mass_tag}"
"""SLaM: Set whether shear is included in the mass model using the `ExternalShear` model of the Source pipeline."""
shear = slam.pipeline_mass.shear_from_previous_pipeline(index=-1)
"""
Phase 1: Fit the lens `Galaxy`'s light and mass and one source galaxy, where we:
1) Use the source galaxy of the `source` pipeline.
2) Use the lens galaxy light of the `light` pipeline.
3) Set priors on the lens galaxy `MassProfile`'s using the `EllipticalIsothermal` and `ExternalShear` of
previous pipelines.
"""
mass = slam.pipeline_mass.setup_mass.mass_prior_model_with_updated_priors(
index=-1, unfix_mass_centre=True)
"""SLaM: Use the source and lens light models from the previous *Source* and *Light* pipelines."""
lens = slam.lens_from_light_parametric_pipeline_for_mass_total_pipeline(
mass=mass, shear=shear)
source = slam.source_from_previous_pipeline_model_if_parametric()
phase1 = al.PhaseImaging(
search=af.DynestyStatic(
name="phase[1]_light[parametric]_mass[total]_source",
n_live_points=100),
galaxies=dict(lens=lens, source=source),
hyper_image_sky=af.last.hyper_combined.instance.optional.
hyper_image_sky,
hyper_background_noise=af.last.hyper_combined.instance.optional.
hyper_background_noise,
settings=settings,
)
if not slam.setup_hyper.hyper_fixed_after_source:
phase1 = phase1.extend_with_multiple_hyper_phases(
setup_hyper=slam.setup_hyper, include_inversion=True)
return al.PipelineDataset(pipeline_name, path_prefix, phase1)
def make_pipeline(name, phase_folders, non_linear_class=af.MultiNest):
phase1 = al.PhaseImaging(
phase_name="phase_1",
phase_folders=phase_folders,
galaxies=dict(lens=al.GalaxyModel(redshift=0.5, sersic=al.lp.EllipticalSersic)),
non_linear_class=non_linear_class,
)
phase1.optimizer.const_efficiency_mode = True
phase1.optimizer.n_live_points = 40
phase1.optimizer.sampling_efficiency = 0.8
return al.PipelineDataset(name, phase1)
def make_pipeline(name, folders, search=af.DynestyStatic()):
lens = al.GalaxyModel(redshift=0.5, mass=al.mp.EllipticalIsothermal)
lens.mass.centre_0 = af.UniformPrior(lower_limit=-0.01, upper_limit=0.01)
lens.mass.centre_1 = af.UniformPrior(lower_limit=-0.01, upper_limit=0.01)
lens.mass.einstein_radius = af.UniformPrior(lower_limit=1.55,
upper_limit=1.65)
source = al.GalaxyModel(redshift=1.0, light=al.lp.EllipticalSersic)
source.light.centre_0 = af.UniformPrior(lower_limit=-0.01,
upper_limit=0.01)
source.light.centre_1 = af.UniformPrior(lower_limit=-0.01,
upper_limit=0.01)
source.light.intensity = af.UniformPrior(lower_limit=0.35,
upper_limit=0.45)
source.light.effective_radius = af.UniformPrior(lower_limit=0.45,
upper_limit=0.55)
source.light.sersic_index = af.UniformPrior(lower_limit=0.9,
upper_limit=1.1)
class GridPhase(
af.as_grid_search(phase_class=al.PhaseImaging, parallel=True)):
@property
def grid_priors(self):
return [
self.model.galaxies.subhalo.mass.centre_0,
self.model.galaxies.subhalo.mass.centre_1,
]
subhalo = al.GalaxyModel(redshift=0.5,
mass=al.mp.SphericalTruncatedNFWMCRLudlow)
subhalo.mass.mass_at_200 = af.LogUniformPrior(lower_limit=1.0e6,
upper_limit=1.0e11)
subhalo.mass.centre_0 = af.UniformPrior(lower_limit=-2.5, upper_limit=2.5)
subhalo.mass.centre_1 = af.UniformPrior(lower_limit=-2.5, upper_limit=2.5)
phase1 = GridPhase(
phase_name="phase_1",
folders=folders,
galaxies=dict(lens=lens, subhalo=subhalo, source=source),
search=search,
settings=al.SettingsPhaseImaging(),
number_of_steps=2,
)
return al.PipelineDataset(name, phase1)
