def pipeline():
tools.reset_paths(test_name=test_name, output_path=output_path)
lens_light = lp.SphericalDevVaucouleurs(centre=(0.0, 0.0),
intensity=0.1,
effective_radius=0.5)
lens_mass = mp.EllipticalIsothermal(centre=(0.0, 0.0),
axis_ratio=0.8,
phi=80.0,
einstein_radius=1.6)
source_light = lp.EllipticalSersic(centre=(0.0, 0.0),
axis_ratio=0.6,
phi=90.0,
intensity=1.0,
effective_radius=0.5,
sersic_index=1.0)
lens_galaxy = galaxy.Galaxy(dev=lens_light, sie=lens_mass)
source_galaxy = galaxy.Galaxy(sersic=source_light)
tools.simulate_integration_image(test_name=test_name,
pixel_scale=0.1,
lens_galaxies=[lens_galaxy],
source_galaxies=[source_galaxy],
target_signal_to_noise=30.0)
ccd_data = ccd.load_ccd_data_from_fits(
image_path=path + '/data/' + test_name + '/image.fits',
psf_path=path + '/data/' + test_name + '/psf.fits',
noise_map_path=path + '/data/' + test_name + '/noise_map.fits',
pixel_scale=0.1)
pipeline = make_pipeline(test_name=test_name)
pipeline.run(data=ccd_data)
def phase():
pixel_scale = 0.1
image_shape = (150, 150)
tools.reset_paths(test_name=test_name, output_path=output_path)
grid_stack = grids.GridStack.from_shape_pixel_scale_and_sub_grid_size(shape=image_shape, pixel_scale=pixel_scale,
sub_grid_size=4)
galaxy = g.Galaxy(mass=mp.SphericalIsothermal(centre=(0.0, 0.0), einstein_radius=1.0))
deflections = galaxy_util.deflections_of_galaxies_from_grid(galaxies=[galaxy], grid=grid_stack.sub)
deflections_y = grid_stack.regular.scaled_array_from_array_1d(array_1d=deflections[:,0])
deflections_x = grid_stack.regular.scaled_array_from_array_1d(array_1d=deflections[:,1])
noise_map = scaled_array.ScaledSquarePixelArray(array=np.ones(deflections_y.shape), pixel_scale=pixel_scale)
data_y = gd.GalaxyData(image=deflections_y, noise_map=noise_map, pixel_scale=pixel_scale)
data_x = gd.GalaxyData(image=deflections_x, noise_map=noise_map, pixel_scale=pixel_scale)
phase = ph.GalaxyFitPhase(galaxies=dict(gal=gm.GalaxyModel(light=mp.SphericalIsothermal)), use_deflections=True,
sub_grid_size=4,
optimizer_class=nl.MultiNest, phase_name=test_name+'/')
phase.run(galaxy_data=[data_y, data_x])
def pipeline():
tools.reset_paths(test_name=test_name, output_path=output_path)
pipeline = make_pipeline(test_name=test_name)
pipeline.run(positions=[[[1.0, 1.0], [1.0, -1.0], [-1.0, 1.0], [-1.0, -1.0]]], pixel_scale=0.05)
def phase():
pixel_scale = 0.1
image_shape = (150, 150)
tools.reset_paths(test_name=test_name, output_path=output_path)
grid_stack = grids.GridStack.from_shape_pixel_scale_and_sub_grid_size(
shape=image_shape, pixel_scale=pixel_scale, sub_grid_size=4)
galaxy = g.Galaxy(mass=lp.SphericalExponential(
centre=(0.0, 0.0), intensity=1.0, effective_radius=0.5))
intensities = galaxy_util.intensities_of_galaxies_from_grid(
galaxies=[galaxy], grid=grid_stack.sub)
intensities = grid_stack.regular.scaled_array_from_array_1d(
array_1d=intensities)
noise_map = scaled_array.ScaledSquarePixelArray(array=np.ones(
intensities.shape),
pixel_scale=pixel_scale)
data = gd.GalaxyData(image=intensities,
noise_map=noise_map,
pixel_scale=pixel_scale)
phase = ph.GalaxyFitPhase(
galaxies=dict(gal=gm.GalaxyModel(light=lp.SphericalExponential)),
use_intensities=True,
sub_grid_size=4,
optimizer_class=nl.MultiNest,
phase_name=test_name + '/')
phase.run(galaxy_data=[data])
def pipeline():
lens_mass = mp.SphericalIsothermal(centre=(0.0, 0.0), einstein_radius=1.6)
lens_subhalo = mp.SphericalIsothermal(centre=(1.0, 1.0),
einstein_radius=0.0)
source_light = lp.SphericalSersic(centre=(0.0, 0.0),
intensity=1.0,
effective_radius=0.5,
sersic_index=1.0)
lens_galaxy = galaxy.Galaxy(mass=lens_mass, subhalo=lens_subhalo)
source_galaxy = galaxy.Galaxy(light=source_light)
tools.reset_paths(test_name=test_name, output_path=output_path)
tools.simulate_integration_image(test_name=test_name,
pixel_scale=0.1,
lens_galaxies=[lens_galaxy],
source_galaxies=[source_galaxy],
target_signal_to_noise=30.0)
ccd_data = ccd.load_ccd_data_from_fits(
image_path=path + '/data/' + test_name + '/image.fits',
psf_path=path + '/data/' + test_name + '/psf.fits',
noise_map_path=path + '/data/' + test_name + '/noise_map.fits',
pixel_scale=0.1)
pipeline = make_pipeline(test_name=test_name)
result = pipeline.run(data=ccd_data)
print(dir(result))
def test_constants_work(self):
name = "const_float"
test_name = '/const_float'
tools.reset_paths(test_name, output_path)
sersic = lp.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(light_profile=sersic)
tools.simulate_integration_image(test_name=test_name, pixel_scale=0.5, lens_galaxies=[lens_galaxy],
source_galaxies=[], target_signal_to_noise=10.0)
path = "{}/".format(
os.path.dirname(os.path.realpath(__file__))) # Setup path so we can output the simulated image.
ccd_data = ccd.load_ccd_data_from_fits(image_path=path + '/data/' + test_name + '/image.fits',
psf_path=path + '/data/' + test_name + '/psf.fits',
noise_map_path=path + '/data/' + test_name + '/noise_map.fits',
pixel_scale=0.1)
class MMPhase(ph.LensPlanePhase):
def pass_priors(self, previous_results):
self.lens_galaxies.lens.sersic.axis_ratio = 0.2
self.lens_galaxies.lens.sersic.phi = 90.0
self.lens_galaxies.lens.sersic.intensity = 1.0
self.lens_galaxies.lens.sersic.effective_radius = 1.3
self.lens_galaxies.lens.sersic.sersic_index = 3.0
phase = MMPhase(lens_galaxies=dict(lens=gm.GalaxyModel(sersic=lp.EllipticalSersic)),
optimizer_class=nl.MultiNest, phase_name="{}/phase1".format(name))
phase.optimizer.n_live_points = 20
phase.optimizer.sampling_efficiency = 0.8
phase.make_analysis(data=ccd_data)
sersic = phase.variable.lens_galaxies[0].sersic
assert isinstance(sersic, mm.PriorModel)
assert isinstance(sersic.axis_ratio, prior.Constant)
assert isinstance(sersic.phi, prior.Constant)
assert isinstance(sersic.intensity, prior.Constant)
assert isinstance(sersic.effective_radius, prior.Constant)
assert isinstance(sersic.sersic_index, prior.Constant)
def test_pipeline():
bulge_0 = lp.EllipticalSersic(centre=(-1.0, -1.0),
axis_ratio=0.9,
phi=90.0,
intensity=1.0,
effective_radius=1.0,
sersic_index=4.0)
disk_0 = lp.EllipticalSersic(centre=(-1.0, -1.0),
axis_ratio=0.6,
phi=90.0,
intensity=20.0,
effective_radius=2.5,
sersic_index=1.0)
bulge_1 = lp.EllipticalSersic(centre=(1.0, 1.0),
axis_ratio=0.9,
phi=90.0,
intensity=1.0,
effective_radius=1.0,
sersic_index=4.0)
disk_1 = lp.EllipticalSersic(centre=(1.0, 1.0),
axis_ratio=0.6,
phi=90.0,
intensity=20.0,
effective_radius=2.5,
sersic_index=1.0)
lens_galaxy_0 = galaxy.Galaxy(bulge=bulge_0, disk=disk_0)
lens_galaxy_1 = galaxy.Galaxy(bulge=bulge_1, disk=disk_1)
tools.reset_paths(test_name=test_name, output_path=output_path)
tools.simulate_integration_image(
test_name=test_name,
pixel_scale=0.1,
lens_galaxies=[lens_galaxy_0, lens_galaxy_1],
source_galaxies=[],
target_signal_to_noise=30.0)
ccd_data = ccd.load_ccd_data_from_fits(
image_path=path + '/data/' + test_name + '/image.fits',
psf_path=path + '/data/' + test_name + '/psf.fits',
noise_map_path=path + '/data/' + test_name + '/noise_map.fits',
pixel_scale=0.1)
pipeline = make_pipeline(test_name=test_name)
pipeline.run(data=ccd_data)
def test_pairing_works(self):
test_name = 'pair_floats'
tools.reset_paths(test_name, output_path)
sersic = lp.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(light_profile=sersic)
tools.simulate_integration_image(test_name=test_name, pixel_scale=0.5, lens_galaxies=[lens_galaxy],
source_galaxies=[], target_signal_to_noise=10.0)
path = "{}/".format(
os.path.dirname(os.path.realpath(__file__))) # Setup path so we can output the simulated image.
ccd_data = ccd.load_ccd_data_from_fits(image_path=path + '/data/' + test_name + '/image.fits',
psf_path=path + '/data/' + test_name + '/psf.fits',
noise_map_path=path + '/data/' + test_name + '/noise_map.fits',
pixel_scale=0.1)
class MMPhase(ph.LensPlanePhase):
def pass_priors(self, previous_results):
self.lens_galaxies.lens.sersic.intensity = self.lens_galaxies.lens.sersic.axis_ratio
phase = MMPhase(lens_galaxies=dict(lens=gm.GalaxyModel(sersic=lp.EllipticalSersic)),
optimizer_class=nl.MultiNest, phase_name="{}/phase1".format(test_name))
initial_total_priors = phase.variable.prior_count
phase.make_analysis(data=ccd_data)
assert phase.lens_galaxies[0].sersic.intensity == phase.lens_galaxies[0].sersic.axis_ratio
assert initial_total_priors - 1 == phase.variable.prior_count
assert len(phase.variable.flat_prior_model_tuples) == 1
lines = list(
filter(lambda line: "axis_ratio" in line or "intensity" in line, phase.variable.info.split("\n")))
assert len(lines) == 2
assert "lens_axis_ratio UniformPrior, lower_limit = 0.2, " \
"upper_limit = 1.0" in lines
assert "lens_intensity UniformPrior, lower_limit = 0.2, " \
"upper_limit = 1.0" in lines
def pipeline():
lens_mass = mp.EllipticalIsothermal(centre=(0.01, 0.01),
axis_ratio=0.8,
phi=80.0,
einstein_radius=1.6)
source_bulge_0 = lp.EllipticalSersic(centre=(0.01, 0.01),
axis_ratio=0.9,
phi=90.0,
intensity=1.0,
effective_radius=1.0,
sersic_index=4.0)
source_bulge_1 = lp.EllipticalSersic(centre=(0.1, 0.1),
axis_ratio=0.9,
phi=90.0,
intensity=1.0,
effective_radius=1.0,
sersic_index=4.0)
lens_galaxy = galaxy.Galaxy(sie=lens_mass)
source_galaxy = galaxy.Galaxy(bulge_0=source_bulge_0,
bulge_1=source_bulge_1)
tools.reset_paths(test_name=test_name, output_path=output_path)
tools.simulate_integration_image(test_name=test_name,
pixel_scale=0.1,
lens_galaxies=[lens_galaxy],
source_galaxies=[source_galaxy],
target_signal_to_noise=30.0)
ccd_data = ccd.load_ccd_data_from_fits(
image_path=path + '/data/' + test_name + '/image.fits',
psf_path=path + '/data/' + test_name + '/psf.fits',
noise_map_path=path + '/data/' + test_name + '/noise_map.fits',
pixel_scale=0.1)
pipeline = make_pipeline(test_name=test_name)
pipeline.run(data=ccd_data)
