def test__1x1_image__light_profile_fits_data_perfectly__lh_is_noise(self):
image = al.ScaledSquarePixelArray(array=np.ones((3, 3)),
pixel_scale=1.0)
noise_map = al.ScaledSquarePixelArray(array=np.ones((3, 3)),
pixel_scale=1.0)
galaxy_data = al.GalaxyData(image=image,
noise_map=noise_map,
pixel_scale=3.0)
mask = al.Mask(
array=np.array([[True, True, True], [True, False, True],
[True, True, True]]),
pixel_scale=1.0,
sub_size=1,
)
g0 = MockGalaxy(value=1.0)
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_image=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.model_galaxies == [g0]
assert fit.likelihood == -0.5 * np.log(2 * np.pi * 1.0)
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_convergence=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.model_galaxies == [g0]
assert fit.likelihood == -0.5 * np.log(2 * np.pi * 1.0)
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_potential=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.model_galaxies == [g0]
assert fit.likelihood == -0.5 * np.log(2 * np.pi * 1.0)
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_deflections_y=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.model_galaxies == [g0]
assert fit.likelihood == -0.5 * np.log(2 * np.pi * 1.0)
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_deflections_x=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.model_galaxies == [g0]
assert fit.likelihood == -0.5 * np.log(2 * np.pi * 1.0)
def test__deflections_y(self, gal_data_7x7, sub_mask_7x7):
galaxy_fit_data = al.GalaxyFitData(galaxy_data=gal_data_7x7,
mask=sub_mask_7x7,
use_deflections_y=True)
galaxy = al.Galaxy(
redshift=0.5,
mass=al.mass_profiles.SphericalIsothermal(centre=(1.0, 2.0),
einstein_radius=1.0),
)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data,
model_galaxies=[galaxy])
assert fit.model_galaxies == [galaxy]
model_data_2d = galaxy.deflections_from_grid(
grid=galaxy_fit_data.grid,
return_in_2d=True,
return_binned=True,
bypass_decorator=False,
)[:, :, 0]
residual_map_2d = af.fit_util.residual_map_from_data_mask_and_model_data(
data=galaxy_fit_data.image(return_in_2d=True),
mask=galaxy_fit_data.mask,
model_data=model_data_2d,
)
assert residual_map_2d == pytest.approx(
fit.residual_map(return_in_2d=True), 1e-4)
chi_squared_map_2d = af.fit_util.chi_squared_map_from_residual_map_noise_map_and_mask(
residual_map=residual_map_2d,
mask=galaxy_fit_data.mask,
noise_map=galaxy_fit_data.noise_map(return_in_2d=True),
)
assert chi_squared_map_2d == pytest.approx(
fit.chi_squared_map(return_in_2d=True), 1e-4)
chi_squared = af.fit_util.chi_squared_from_chi_squared_map_and_mask(
chi_squared_map=chi_squared_map_2d, mask=sub_mask_7x7)
noise_normalization = af.fit_util.noise_normalization_from_noise_map_and_mask(
mask=galaxy_fit_data.mask,
noise_map=galaxy_fit_data.noise_map(return_in_2d=True),
)
likelihood = af.fit_util.likelihood_from_chi_squared_and_noise_normalization(
chi_squared=chi_squared, noise_normalization=noise_normalization)
assert likelihood == pytest.approx(fit.likelihood, 1e-4)
def test__1x2_image__noise_not_1__alls_correct(self):
image = al.ScaledSquarePixelArray(array=5.0 * np.ones((3, 4)),
pixel_scale=1.0)
image[1, 2] = 4.0
noise_map = al.ScaledSquarePixelArray(array=2.0 * np.ones((3, 4)),
pixel_scale=1.0)
galaxy_data = al.GalaxyData(image=image,
noise_map=noise_map,
pixel_scale=3.0)
mask = al.Mask(
array=np.array([
[True, True, True, True],
[True, False, False, True],
[True, True, True, True],
]),
pixel_scale=1.0,
sub_size=1,
)
g0 = MockGalaxy(value=1.0, shape=2)
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_image=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.model_galaxies == [g0]
assert fit.chi_squared == (25.0 / 4.0)
assert fit.reduced_chi_squared == (25.0 / 4.0) / 2.0
assert fit.likelihood == -0.5 * (
(25.0 / 4.0) + 2.0 * np.log(2 * np.pi * 2.0**2))
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_convergence=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.model_galaxies == [g0]
assert fit.chi_squared == (25.0 / 4.0)
assert fit.reduced_chi_squared == (25.0 / 4.0) / 2.0
assert fit.likelihood == -0.5 * (
(25.0 / 4.0) + 2.0 * np.log(2 * np.pi * 2.0**2))
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_potential=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.model_galaxies == [g0]
assert fit.chi_squared == (25.0 / 4.0)
assert fit.reduced_chi_squared == (25.0 / 4.0) / 2.0
assert fit.likelihood == -0.5 * (
(25.0 / 4.0) + 2.0 * np.log(2 * np.pi * 2.0**2))
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_deflections_y=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.chi_squared == (25.0 / 4.0)
assert fit.reduced_chi_squared == (25.0 / 4.0) / 2.0
assert fit.likelihood == -0.5 * (
(25.0 / 4.0) + 2.0 * np.log(2 * np.pi * 2.0**2))
galaxy_fit_data = al.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_deflections_x=True)
fit = al.GalaxyFit(galaxy_data=galaxy_fit_data, model_galaxies=[g0])
assert fit.chi_squared == (25.0 / 4.0)
assert fit.reduced_chi_squared == (25.0 / 4.0) / 2.0
assert fit.likelihood == -0.5 * (
(25.0 / 4.0) + 2.0 * np.log(2 * np.pi * 2.0**2))
def make_gal_fit_7x7_deflections_x(gal_fit_data_7x7_deflections_x, gal_x1_mp):
return al.GalaxyFit(galaxy_data=gal_fit_data_7x7_deflections_x,
model_galaxies=[gal_x1_mp])
def make_gal_fit_7x7_potential(gal_fit_data_7x7_potential, gal_x1_mp):
return al.GalaxyFit(galaxy_data=gal_fit_data_7x7_potential,
model_galaxies=[gal_x1_mp])
def make_gal_fit_7x7_convergence(gal_fit_data_7x7_convergence, gal_x1_mp):
return al.GalaxyFit(galaxy_data=gal_fit_data_7x7_convergence,
model_galaxies=[gal_x1_mp])
def make_gal_fit_7x7_image(gal_fit_data_7x7_image, gal_x1_lp):
return al.GalaxyFit(galaxy_data=gal_fit_data_7x7_image,
model_galaxies=[gal_x1_lp])
