def test__intensity_from_grid__change_geometry(self):
exponential_0 = lp.EllipticalExponential(axis_ratio=0.5,
phi=0.0,
intensity=3.0,
effective_radius=2.0)
exponential_1 = lp.EllipticalExponential(axis_ratio=0.5,
phi=90.0,
intensity=3.0,
effective_radius=2.0)
assert exponential_0.intensities_from_grid(grid=np.array([[0.0, 1.0]])) == \
exponential_1.intensities_from_grid(grid=np.array([[1.0, 0.0]]))
def test__intensity_at_radius__correct_value(self):
exponential = lp.EllipticalExponential(axis_ratio=1.0,
phi=0.0,
intensity=1.0,
effective_radius=0.6)
assert exponential.intensities_from_grid_radii(
grid_radii=1.0) == pytest.approx(0.3266, 1e-3)
exponential = lp.EllipticalExponential(axis_ratio=1.0,
phi=0.0,
intensity=3.0,
effective_radius=2.0)
assert exponential.intensities_from_grid_radii(
grid_radii=1.5) == pytest.approx(4.5640, 1e-3)
def pipeline():
bulge = lp.EllipticalSersic(centre=(0.0, 0.0),
axis_ratio=0.8,
phi=0.0,
intensity=1.0,
effective_radius=1.3,
sersic_index=3.0)
disk = lp.EllipticalExponential(centre=(0.0, 0.0),
axis_ratio=0.7,
phi=0.0,
intensity=2.0,
effective_radius=2.0)
lens_galaxy = galaxy.Galaxy(bulge=bulge, disk=disk)
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=[],
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__spherical_and_elliptical_match(self):
elliptical = lp.EllipticalExponential(axis_ratio=1.0,
phi=0.0,
intensity=3.0,
effective_radius=2.0)
spherical = lp.SphericalExponential(intensity=3.0,
effective_radius=2.0)
assert (elliptical.intensities_from_grid(grid) ==
spherical.intensities_from_grid(grid)).all()
def test__intensity_from_grid__correct_values(self):
exponential = lp.EllipticalExponential(axis_ratio=0.5,
phi=0.0,
intensity=3.0,
effective_radius=2.0)
assert exponential.intensities_from_grid(
grid=np.array([[1.0, 0.0]])) == pytest.approx(4.9047, 1e-3)
exponential = lp.EllipticalExponential(axis_ratio=0.5,
phi=90.0,
intensity=2.0,
effective_radius=3.0)
assert exponential.intensities_from_grid(
grid=np.array([[0.0, 1.0]])) == pytest.approx(4.8566, 1e-3)
exponential = lp.EllipticalExponential(axis_ratio=0.5,
phi=90.0,
intensity=4.0,
effective_radius=3.0)
assert exponential.intensities_from_grid(
grid=np.array([[0.0, 1.0]])) == pytest.approx(2.0 * 4.8566, 1e-3)
def test__constructor(self):
exponential = lp.EllipticalExponential(axis_ratio=0.5,
phi=0.0,
intensity=1.0,
effective_radius=0.6)
assert exponential.centre == (0.0, 0.0)
assert exponential.axis_ratio == 0.5
assert exponential.phi == 0.0
assert exponential.intensity == 1.0
assert exponential.effective_radius == 0.6
assert exponential.sersic_index == 1.0
assert exponential.sersic_constant == pytest.approx(1.678378, 1e-3)
assert exponential.elliptical_effective_radius == 0.6 / math.sqrt(0.5)
def test__grid_calculations__same_as_exponential(self):
sersic_lp = lp.EllipticalExponential(axis_ratio=0.7,
phi=1.0,
intensity=1.0,
effective_radius=0.6)
sersic_mp = mp.EllipticalExponential(axis_ratio=0.7,
phi=1.0,
intensity=1.0,
effective_radius=0.6,
mass_to_light_ratio=2.0)
sersic_lmp = lmp.EllipticalExponential(axis_ratio=0.7,
phi=1.0,
intensity=1.0,
effective_radius=0.6,
mass_to_light_ratio=2.0)
assert (sersic_lp.intensities_from_grid(grid) ==
sersic_lmp.intensities_from_grid(grid)).all()
assert (sersic_mp.surface_density_from_grid(grid) ==
sersic_lmp.surface_density_from_grid(grid)).all()
# assert (sersic_mp.potential_from_grid(grid) == sersic_lmp.potential_from_grid(grid)).all()
assert (sersic_mp.deflections_from_grid(grid) ==
sersic_lmp.deflections_from_grid(grid)).all()
print(lens_satellite)
# Lets have a quick look at the appearance of our lens galaxy and its satellite
galaxy_plotters.plot_intensities(galaxy=lens_galaxy, grid=image_plane_grid_stack.regular, title='Lens Galaxy')
galaxy_plotters.plot_intensities(galaxy=lens_satellite, grid=image_plane_grid_stack.regular, title='Lens Satellite')
# And their deflection angles - note that the satellite doesn't contribute as much to the deflections
galaxy_plotters.plot_deflections_y(galaxy=lens_galaxy, grid=image_plane_grid_stack.regular, title='Lens Galaxy Deflections (y)')
galaxy_plotters.plot_deflections_y(galaxy=lens_satellite, grid=image_plane_grid_stack.regular, title='Lens Satellite Deflections (y)')
galaxy_plotters.plot_deflections_x(galaxy=lens_galaxy, grid=image_plane_grid_stack.regular, title='Lens Galalxy Deflections (x)')
galaxy_plotters.plot_deflections_x(galaxy=lens_satellite, grid=image_plane_grid_stack.regular, title='Lens Satellite Deflections (x)')
# Now, lets make two source galaxies at redshift 1.0. Lets not use the terms 'light' and 'mass' to setup the light and
# mass profiles. Instead, lets use more descriptive names of what we think each component represents ( e.g. a 'bulge' and 'disk').
source_galaxy_0 = g.Galaxy(bulge=lp.SphericalDevVaucouleurs(centre=(0.1, 0.2), intensity=0.3, effective_radius=0.3),
disk=lp.EllipticalExponential(centre=(0.1, 0.2), axis_ratio=0.8, phi=45.0, intensity=3.0,
effective_radius=2.0),
redshift=1.0)
source_galaxy_1 = g.Galaxy(disk=lp.EllipticalExponential(centre=(-0.3, -0.5), axis_ratio=0.6, phi=80.0, intensity=8.0,
effective_radius=1.0),
redshift=1.0)
print(source_galaxy_0)
print(source_galaxy_1)
# Lets look at our source galaxies (before lensing)
galaxy_plotters.plot_intensities(galaxy=source_galaxy_0, grid=image_plane_grid_stack.regular, title='Source Galaxy 0')
galaxy_plotters.plot_intensities(galaxy=source_galaxy_1, grid=image_plane_grid_stack.regular, title='Source Galaxy 1')
# Now lets pass these our 4 galaxies to the ray_tracing module, which means the following will occur:
# 1) Using every mass-profile in each lens galaxy, the deflection angles are computed.
def make_galaxy():
return g.Galaxy(redshift=3,
sersic=light_profiles.EllipticalSersic(),
exponential=light_profiles.EllipticalExponential(),
spherical=mass_profiles.SphericalIsothermal())
print("EllipticalGaussian time = {}".format(diff))
### SphericalGaussian ###
mass_profile = lp.SphericalGaussian(centre=(0.0, 0.0), sigma=1.0)
start = time.time()
mass_profile.intensities_from_grid(grid=lens_data.grid_stack.sub)
diff = time.time() - start
print("SphericalGaussian time = {}".format(diff))
### EllipticalExponential ###
profile = lp.EllipticalExponential(centre=(0.0, 0.0),
axis_ratio=0.8,
phi=45.0,
intensity=1.0,
effective_radius=1.0)
start = time.time()
profile.intensities_from_grid(grid=lens_data.grid_stack.sub)
diff = time.time() - start
print("EllipticalExponential time = {}".format(diff))
### SphericalExponential ###
profile = lp.SphericalExponential(centre=(0.0, 0.0),
intensity=1.0,
effective_radius=1.0)
start = time.time()
def test__simulate_lensed_source_and_fit__include_psf_blurring__chi_squared_is_0__noise_normalization_correct(
):
psf = ccd.PSF.simulate_as_gaussian(shape=(3, 3),
pixel_scale=0.2,
sigma=0.75)
grid_stack = grids.GridStack.grid_stack_for_simulation(shape=(11, 11),
pixel_scale=0.2,
psf_shape=psf.shape,
sub_grid_size=1)
lens_galaxy = g.Galaxy(light=lp.EllipticalSersic(centre=(0.1, 0.1),
intensity=0.1),
mass=mp.EllipticalIsothermal(centre=(0.1, 0.1),
einstein_radius=1.8))
source_galaxy = g.Galaxy(
light=lp.EllipticalExponential(centre=(0.1, 0.1), intensity=0.5))
tracer = ray_tracing.TracerImageSourcePlanes(
lens_galaxies=[lens_galaxy],
source_galaxies=[source_galaxy],
image_plane_grid_stack=grid_stack)
ccd_simulated = ccd.CCDData.simulate(
array=tracer.image_plane_image_for_simulation,
pixel_scale=0.2,
exposure_time=300.0,
psf=psf,
background_sky_level=None,
add_noise=False)
ccd_simulated.noise_map = np.ones(ccd_simulated.image.shape)
path = "{}/data/simulate_and_fit".format(
os.path.dirname(os.path.realpath(
__file__))) # Setup path so we can output the simulated image.
try:
shutil.rmtree(path)
except FileNotFoundError:
pass
if os.path.exists(path) == False:
os.makedirs(path)
array_util.numpy_array_to_fits(array=ccd_simulated.image,
file_path=path + '/image.fits')
array_util.numpy_array_to_fits(array=ccd_simulated.noise_map,
file_path=path + '/noise_map.fits')
array_util.numpy_array_to_fits(array=psf, file_path=path + '/psf.fits')
ccd_data = ccd.load_ccd_data_from_fits(image_path=path + '/image.fits',
noise_map_path=path +
'/noise_map.fits',
psf_path=path + '/psf.fits',
pixel_scale=0.2)
mask = msk.Mask.circular(shape=ccd_data.image.shape,
pixel_scale=0.2,
radius_arcsec=0.8)
lens_data = ld.LensData(ccd_data=ccd_data, mask=mask, sub_grid_size=1)
tracer = ray_tracing.TracerImageSourcePlanes(
lens_galaxies=[lens_galaxy],
source_galaxies=[source_galaxy],
image_plane_grid_stack=lens_data.grid_stack)
fitter = lens_fit.LensProfileFit(lens_data=lens_data, tracer=tracer)
assert fitter.chi_squared == pytest.approx(0.0, 1e-4)