def test_constants_work(self):
name = "const_float"
test_name = "/const_float"
integration_util.reset_paths(test_name, output_path)
sersic = al.EllipticalSersic(
centre=(0.0, 0.0),
axis_ratio=0.8,
phi=90.0,
intensity=1.0,
effective_radius=1.3,
sersic_index=3.0,
)
lens_galaxy = galaxy.Galaxy(redshift=0.5, light_profile=sersic)
simulate_integration_image(test_name=test_name,
pixel_scale=0.5,
galaxies=[lens_galaxy])
path = "{}/".format(os.path.dirname(os.path.realpath(
__file__))) # Setup path so we can output the simulated image.
imaging_data = al.load_imaging_data_from_fits(
image_path=path + "/test_files/data/" + test_name + "/image.fits",
psf_path=path + "/test_files/data/" + test_name + "/psf.fits",
noise_map_path=path + "/test_files/data/" + test_name +
"/noise_map.fits",
pixel_scale=0.1,
)
class MMPhase(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens.sersic.axis_ratio = 0.2
self.galaxies.lens.sersic.phi = 90.0
self.galaxies.lens.sersic.intensity = 1.0
self.galaxies.lens.sersic.effective_radius = 1.3
self.galaxies.lens.sersic.sersic_index = 3.0
phase = MMPhase(
galaxies=dict(lens=al.GalaxyModel(
redshift=0.5, sersic=al.light_profiles.EllipticalSersic)),
optimizer_class=af.MultiNest,
phase_name="{}/phase1".format(name),
)
phase.optimizer.n_live_points = 20
phase.optimizer.sampling_efficiency = 0.8
phase.make_analysis(data=imaging_data)
sersic = phase.variable.galaxies[0].sersic
assert isinstance(sersic, af.PriorModel)
assert isinstance(sersic.axis_ratio, float)
assert isinstance(sersic.phi, float)
assert isinstance(sersic.intensity, float)
assert isinstance(sersic.effective_radius, float)
assert isinstance(sersic.sersic_index, float)
def galaxy_fit_phase():
pixel_scale = 0.1
image_shape = (150, 150)
integration_util.reset_paths(test_name=test_name, output_path=output_path)
grid = al.Grid.from_shape_pixel_scale_and_sub_size(shape=image_shape,
pixel_scale=pixel_scale,
sub_size=4)
galaxy = al.Galaxy(
redshift=0.5,
mass=al.mass_profiles.SphericalIsothermal(centre=(0.0, 0.0),
einstein_radius=1.0),
)
deflections = galaxy.deflections_from_grid(galaxies=[galaxy],
grid=grid,
return_in_2d=True,
bypass_decorator=False)
noise_map = al.ScaledSquarePixelArray(array=np.ones(deflections[:,
0].shape),
pixel_scale=pixel_scale)
data_y = al.GalaxyData(image=deflections[:, 0],
noise_map=noise_map,
pixel_scale=pixel_scale)
data_x = al.GalaxyData(image=deflections[:, 1],
noise_map=noise_map,
pixel_scale=pixel_scale)
phase1 = al.PhaseGalaxy(
phase_name=test_name + "/",
galaxies=dict(gal=al.GalaxyModel(
redshift=0.5, light=al.mass_profiles.SphericalIsothermal)),
use_deflections=True,
sub_size=4,
optimizer_class=af.MultiNest,
)
phase1.run(galaxy_data=[data_y, data_x])
def galaxy_fit_phase():
pixel_scale = 0.1
image_shape = (150, 150)
integration_util.reset_paths(test_name=test_name, output_path=output_path)
grid = al.Grid.from_shape_pixel_scale_and_sub_size(shape=image_shape,
pixel_scale=pixel_scale,
sub_size=4)
galaxy = al.Galaxy(
redshift=0.5,
light=al.light_profiles.SphericalExponential(centre=(0.0, 0.0),
intensity=1.0,
effective_radius=0.5),
)
image = galaxy.profile_image_from_grid(galaxies=[galaxy],
grid=grid,
return_in_2d=True,
bypass_decorator=False)
noise_map = al.ScaledSquarePixelArray(array=np.ones(image.shape),
pixel_scale=pixel_scale)
data = al.GalaxyData(image=image,
noise_map=noise_map,
pixel_scale=pixel_scale)
phase1 = al.PhaseGalaxy(
phase_name=test_name + "/",
galaxies=dict(gal=al.GalaxyModel(
redshift=0.5, light=al.light_profiles.SphericalExponential)),
use_image=True,
sub_size=4,
optimizer_class=af.MultiNest,
)
phase1.run(galaxy_data=[data])
def run(
module,
test_name=None,
optimizer_class=af.MultiNest,
config_folder="config",
positions=None,
):
test_name = test_name or module.test_name
test_path = "{}/../".format(os.path.dirname(os.path.realpath(__file__)))
output_path = test_path + "output/"
config_path = test_path + config_folder
af.conf.instance = af.conf.Config(config_path=config_path, output_path=output_path)
integration_util.reset_paths(test_name=test_name, output_path=output_path)
imaging_data = simulation_util.load_test_imaging_data(
data_type=module.data_type, data_resolution=module.data_resolution
)
module.make_pipeline(
name=test_name,
phase_folders=[module.test_type, test_name],
optimizer_class=optimizer_class,
).run(data=imaging_data, positions=positions)
def test_pairing_works(self):
test_name = "pair_floats"
integration_util.reset_paths(test_name, output_path)
sersic = al.EllipticalSersic(
centre=(0.0, 0.0),
axis_ratio=0.8,
phi=90.0,
intensity=1.0,
effective_radius=1.3,
sersic_index=3.0,
)
lens_galaxy = galaxy.Galaxy(redshift=0.5, light_profile=sersic)
simulate_integration_image(test_name=test_name,
pixel_scale=0.5,
galaxies=[lens_galaxy])
path = "{}/".format(os.path.dirname(os.path.realpath(
__file__))) # Setup path so we can output the simulated image.
imaging_data = al.load_imaging_data_from_fits(
image_path=path + "/test_files/data/" + test_name + "/image.fits",
psf_path=path + "/test_files/data/" + test_name + "/psf.fits",
noise_map_path=path + "/test_files/data/" + test_name +
"/noise_map.fits",
pixel_scale=0.1,
)
class MMPhase(al.PhaseImaging):
def customize_priors(self, results):
self.galaxies.lens.sersic.intensity = (
self.galaxies.lens.sersic.axis_ratio)
phase = MMPhase(
galaxies=dict(lens=al.GalaxyModel(
redshift=0.5, sersic=al.light_profiles.EllipticalSersic)),
optimizer_class=af.MultiNest,
phase_name="{}/phase1".format(test_name),
)
initial_total_priors = phase.variable.prior_count
phase.make_analysis(data=imaging_data)
assert phase.galaxies[0].sersic.intensity == al.Galaxies[
0].sersic.axis_ratio
assert initial_total_priors - 1 == phase.variable.prior_count
lines = list(
filter(
lambda line: "axis_ratio" in line or "intensity" in line,
str(phase.variable).split("\n"),
))
assert len(lines) == 2
assert (
"galaxies_lens_sersic_axis_ratio UniformPrior, lower_limit = 0.2, upper_limit = 1.0"
in lines)
assert (
"galaxies_lens_sersic_intensity UniformPrior, lower_limit = 0.2, upper_limit = 1.0"
in lines)
