def make_galaxy_data(image, mask):
noise_map = sca.ScaledSquarePixelArray(array=2.0 * np.ones((4, 4)),
pixel_scale=3.0)
galaxy_data = gd.GalaxyData(image=image,
noise_map=noise_map,
pixel_scale=3.0)
return gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
use_intensities=True)
def test__multiple_use_methods__raises_exception(self, image, mask):
galaxy_data = gd.GalaxyData(image=image,
noise_map=2.0 * np.ones((4, 4)),
pixel_scale=3.0)
with pytest.raises(exc.GalaxyException):
gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_intensities=True,
use_surface_density=True)
with pytest.raises(exc.GalaxyException):
gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_intensities=True,
use_potential=True)
with pytest.raises(exc.GalaxyException):
gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_intensities=True,
use_deflections_y=True)
with pytest.raises(exc.GalaxyException):
gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_intensities=True,
use_surface_density=True,
use_potential=True)
with pytest.raises(exc.GalaxyException):
gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_intensities=True,
use_surface_density=True,
use_potential=True,
use_deflections_x=True)
def test__no_use_method__raises_exception(self, image, mask):
galaxy_data = gd.GalaxyData(image=image,
noise_map=2.0 * np.ones((4, 4)),
pixel_scale=3.0)
with pytest.raises(exc.GalaxyException):
gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2)
def test__galaxy_data_deflections_x(self, image, mask):
galaxy_data = gd.GalaxyData(image=image,
noise_map=2.0 * np.ones((4, 4)),
pixel_scale=3.0)
galaxy_fit_data = gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_deflections_x=True)
assert galaxy_fit_data.pixel_scale == 3.0
assert (galaxy_fit_data.image == np.ones((4, 4))).all()
assert (galaxy_fit_data.noise_map == 2.0 * np.ones((4, 4))).all()
assert (galaxy_fit_data.mask == np.array([[True, True, True, True],
[True, False, False, True],
[True, False, False, True],
[True, True, True,
True]])).all()
assert (galaxy_fit_data.image_1d == np.ones(4)).all()
assert (galaxy_fit_data.noise_map_1d == 2.0 * np.ones(4)).all()
assert (galaxy_fit_data.mask_1d == np.array(
[False, False, False, False])).all()
galaxy = MockGalaxy(value=1, shape=4)
deflections_x = galaxy_fit_data.profile_quantity_from_galaxy_and_sub_grid(
galaxies=[galaxy], sub_grid=galaxy_fit_data.grid_stack.sub)
assert (deflections_x == np.array([1.0, 1.0, 1.0, 1.0])).all()
galaxy = g.Galaxy(mass=mp.SphericalIsothermal(einstein_radius=1.0))
deflections_gal = galaxy.deflections_from_grid(
grid=galaxy_fit_data.grid_stack.sub)
deflections_gal = np.asarray([
galaxy_fit_data.grid_stack.sub.sub_data_to_regular_data(
deflections_gal[:, 0]),
galaxy_fit_data.grid_stack.sub.sub_data_to_regular_data(
deflections_gal[:, 1])
]).T
deflections_gd = galaxy_fit_data.profile_quantity_from_galaxy_and_sub_grid(
galaxies=[galaxy], sub_grid=galaxy_fit_data.grid_stack.sub)
assert (deflections_gal[:, 1] == deflections_gd).all()
def test__galaxy_data_intensities(self, image, mask):
galaxy_data = gd.GalaxyData(image=image,
noise_map=2.0 * np.ones((4, 4)),
pixel_scale=3.0)
galaxy_fit_data = gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_intensities=True)
assert galaxy_fit_data.pixel_scale == 3.0
assert (galaxy_fit_data.image == np.ones((4, 4))).all()
assert (galaxy_fit_data.noise_map == 2.0 * np.ones((4, 4))).all()
assert (galaxy_fit_data.mask == np.array([[True, True, True, True],
[True, False, False, True],
[True, False, False, True],
[True, True, True,
True]])).all()
assert (galaxy_fit_data.image_1d == np.ones(4)).all()
assert (galaxy_fit_data.noise_map_1d == 2.0 * np.ones(4)).all()
assert (galaxy_fit_data.mask_1d == np.array(
[False, False, False, False])).all()
galaxy = MockGalaxy(value=1, shape=4)
intensities = galaxy_fit_data.profile_quantity_from_galaxy_and_sub_grid(
galaxies=[galaxy], sub_grid=galaxy_fit_data.grid_stack.sub)
assert (intensities == np.array([1.0, 1.0, 1.0, 1.0])).all()
galaxy = g.Galaxy(light=lp.SphericalSersic(intensity=1.0))
intensities_gal = galaxy.intensities_from_grid(
grid=galaxy_fit_data.grid_stack.sub)
intensities_gal = galaxy_fit_data.grid_stack.sub.sub_data_to_regular_data(
sub_array=intensities_gal)
intensities_gd = galaxy_fit_data.profile_quantity_from_galaxy_and_sub_grid(
galaxies=[galaxy], sub_grid=galaxy_fit_data.grid_stack.sub)
assert (intensities_gal == intensities_gd).all()
def make_analysis(self, galaxy_data, results=None, mask=None):
"""
Create an lens object. Also calls the prior passing and lens_data modifying
functions to allow child classes to change the behaviour of the phase.
Parameters
----------
galaxy_data
mask: Mask
The default masks passed in by the pipeline
results: autofit.tools.pipeline.ResultsCollection
The result from the previous phase
Returns
-------
lens: Analysis
An lens object that the non-linear optimizer calls to determine the fit of a
set of values
"""
mask = setup_phase_mask(
data=galaxy_data[0],
mask=mask,
mask_function=self.mask_function,
inner_mask_radii=None,
)
if self.use_image or self.use_convergence or self.use_potential:
galaxy_data = gd.GalaxyFitData(
galaxy_data=galaxy_data[0],
mask=mask,
pixel_scale_interpolation_grid=self.
pixel_scale_interpolation_grid,
use_image=self.use_image,
use_convergence=self.use_convergence,
use_potential=self.use_potential,
use_deflections_y=self.use_deflections,
use_deflections_x=self.use_deflections,
)
return AnalysisSingle(
galaxy_data=galaxy_data,
cosmology=self.cosmology,
image_path=self.optimizer.image_path,
results=results,
)
elif self.use_deflections:
galaxy_data_y = gd.GalaxyFitData(
galaxy_data=galaxy_data[0],
mask=mask,
pixel_scale_interpolation_grid=self.
pixel_scale_interpolation_grid,
use_image=self.use_image,
use_convergence=self.use_convergence,
use_potential=self.use_potential,
use_deflections_y=self.use_deflections,
use_deflections_x=False,
)
galaxy_data_x = gd.GalaxyFitData(
galaxy_data=galaxy_data[1],
mask=mask,
pixel_scale_interpolation_grid=self.
pixel_scale_interpolation_grid,
use_image=self.use_image,
use_convergence=self.use_convergence,
use_potential=self.use_potential,
use_deflections_y=False,
use_deflections_x=self.use_deflections,
)
return AnalysisDeflections(
galaxy_data_y=galaxy_data_y,
galaxy_data_x=galaxy_data_x,
cosmology=self.cosmology,
image_path=self.optimizer.image_path,
results=results,
)
def make_galaxy_data_deflections_x(galaxy_data, mask):
return gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_deflections_x=True)
def make_galaxy_data_potential(galaxy_data, mask):
return gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_potential=True)
def make_galaxy_data_surface_density(galaxy_data, mask):
return gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_surface_density=True)
def make_galaxy_data_intensities(galaxy_data, mask):
return gd.GalaxyFitData(galaxy_data=galaxy_data,
mask=mask,
sub_grid_size=2,
use_intensities=True)