def test__solver_for_tracer_method__multiple_source_planes_or_galaxies(self):
grid = al.Grid.uniform(shape_2d=(50, 50), pixel_scales=0.05, sub_size=4)
g0 = al.Galaxy(
redshift=0.5,
mass=al.mp.EllipticalIsothermal(
centre=(0.0, 0.0), einstein_radius=1.0, elliptical_comps=(0.0, 0.055555)
),
)
g1 = al.Galaxy(
redshift=1.0,
light_0=al.lp.EllipticalLightProfile(centre=(0.0, 0.0)),
light_1=al.lp.EllipticalLightProfile(centre=(0.1, 0.1)),
)
tracer = al.Tracer.from_galaxies(galaxies=[g0, g1])
solver = pos.PositionsSolver(grid=grid, pixel_scale_precision=0.01)
position_manual_0 = solver.solve(
lensing_obj=tracer, source_plane_coordinate=(0.0, 0.0)
)
position_manual_1 = solver.solve(
lensing_obj=tracer, source_plane_coordinate=(0.1, 0.1)
)
positions = solver.solve_from_tracer(tracer=tracer)
assert position_manual_0.in_grouped_list[0] == positions.in_grouped_list[0]
assert position_manual_1.in_grouped_list[0] == positions.in_grouped_list[1]
g2 = al.Galaxy(
redshift=1.0, light=al.lp.EllipticalLightProfile(centre=(0.0, 0.0))
)
g3 = al.Galaxy(
redshift=1.0, light=al.lp.EllipticalLightProfile(centre=(0.1, 0.1))
)
tracer = al.Tracer.from_galaxies(galaxies=[g0, g2, g3])
solver = pos.PositionsSolver(grid=grid, pixel_scale_precision=0.01)
positions = solver.solve_from_tracer(tracer=tracer)
assert position_manual_0.in_grouped_list[0] == positions.in_grouped_list[0]
assert position_manual_1.in_grouped_list[0] == positions.in_grouped_list[1]
def test__same_as_above_using_solver_for_tracer_method(self):
grid = al.Grid.uniform(shape_2d=(100, 100), pixel_scales=0.05, sub_size=1)
g0 = al.Galaxy(
redshift=0.5,
mass=al.mp.EllipticalIsothermal(
centre=(0.001, 0.001),
einstein_radius=1.0,
elliptical_comps=(0.0, 0.111111),
),
)
g1 = al.Galaxy(
redshift=1.0, light=al.lp.EllipticalLightProfile(centre=(0.0, 0.0))
)
tracer = al.Tracer.from_galaxies(galaxies=[g0, g1])
solver = pos.PositionsSolver(grid=grid, pixel_scale_precision=0.01)
coordinates = solver.solve_from_tracer(tracer=tracer)
assert coordinates.in_grouped_list[0][0] == pytest.approx(
(1.028125, -0.003125), 1.0e-4
)
assert coordinates.in_grouped_list[0][1] == pytest.approx(
(0.009375, -0.95312), 1.0e-4
)
assert coordinates.in_grouped_list[0][2] == pytest.approx(
(0.009375, 0.95312), 1.0e-4
)
assert coordinates.in_grouped_list[0][3] == pytest.approx(
(-1.028125, -0.003125), 1.0e-4
)
def test__positions_found_for_multi_plane_tracer(self):
grid = al.Grid2D.uniform(shape_native=(100, 100),
pixel_scales=0.05,
sub_size=1)
g0 = al.Galaxy(
redshift=0.5,
mass=al.mp.EllIsothermal(
centre=(0.001, 0.001),
einstein_radius=1.0,
elliptical_comps=(0.0, 0.111111),
),
)
g1 = al.Galaxy(redshift=1.0)
g2 = al.Galaxy(redshift=2.0)
tracer = al.Tracer.from_galaxies(galaxies=[g0, g1, g2])
solver = pos.PositionsSolver(grid=grid, pixel_scale_precision=0.01)
coordinates_to_plane_2 = solver.solve(lensing_obj=tracer,
source_plane_coordinate=(0.0,
0.0))
coordinates_to_plane_1 = solver.solve(lensing_obj=tracer,
source_plane_coordinate=(0.0,
0.0),
upper_plane_index=1)
assert coordinates_to_plane_1[0][0] != coordinates_to_plane_2[0][0]
scaling_factor = al.util.cosmology.scaling_factor_between_redshifts_from(
redshift_0=0.5,
redshift_1=1.0,
redshift_final=2.0,
cosmology=tracer.cosmology,
)
assert coordinates_to_plane_1[0][0] == pytest.approx(
coordinates_to_plane_2[0][0] * scaling_factor, 1.0e-1)
coordinates_to_plane_2_with_index = solver.solve(
lensing_obj=tracer,
source_plane_coordinate=(0.0, 0.0),
upper_plane_index=2)
assert coordinates_to_plane_2[0][
0] == coordinates_to_plane_2_with_index[0][0]
def test__positions_found_for_simple_mass_profiles(self):
grid = al.Grid2D.uniform(shape_native=(100, 100), pixel_scales=0.05)
sis = al.mp.SphIsothermal(centre=(0.0, 0.0), einstein_radius=1.0)
solver = al.PositionsSolver(grid=grid, pixel_scale_precision=0.01)
positions = solver.solve(lensing_obj=sis,
source_plane_coordinate=(0.0, 0.11))
assert positions[0] == pytest.approx(np.array([0.003125, -0.890625]),
1.0e-4)
assert positions[3] == pytest.approx(np.array([-0.003125, 1.109375]),
1.0e-4)
grid = al.Grid2D.uniform(shape_native=(100, 100),
pixel_scales=0.05,
sub_size=1)
g0 = al.Galaxy(
redshift=0.5,
mass=al.mp.EllIsothermal(
centre=(0.001, 0.001),
einstein_radius=1.0,
elliptical_comps=(0.0, 0.111111),
),
)
g1 = al.Galaxy(redshift=1.0)
tracer = al.Tracer.from_galaxies(galaxies=[g0, g1])
solver = pos.PositionsSolver(grid=grid, pixel_scale_precision=0.01)
coordinates = solver.solve(lensing_obj=tracer,
source_plane_coordinate=(0.0, 0.0))
assert coordinates.in_list[0] == pytest.approx((1.028125, -0.003125),
1.0e-4)
assert coordinates.in_list[1] == pytest.approx((0.009375, -0.95312),
1.0e-4)
assert coordinates.in_list[2] == pytest.approx((0.009375, 0.95312),
1.0e-4)
assert coordinates.in_list[3] == pytest.approx((-1.028125, -0.003125),
1.0e-4)
def image_plane_multiple_image_positions(
self, ) -> grid_2d_irregular.Grid2DIrregular:
"""
Backwards ray-trace the source-plane centres (see above) to the image-plane via the mass model, to determine
the multiple image position of the source(s) in the image-plane.
These image-plane positions are used by the next search in a pipeline if automatic position updating is turned
on."""
# TODO : In the future, the multiple image positions functioon wil use an in-built adaptive grid.
grid = self.analysis.dataset.mask.unmasked_grid_sub_1
solver = pos.PositionsSolver(grid=grid, pixel_scale_precision=0.001)
multiple_images = solver.solve(
lensing_obj=self.max_log_likelihood_tracer,
source_plane_coordinate=self.source_plane_centre.in_list[0],
)
return grid_2d_irregular.Grid2DIrregular(grid=multiple_images)
def image_plane_multiple_image_positions_of_source_plane_centres(
self, ) -> grids.GridIrregularGrouped:
"""Backwards ray-trace the source-plane centres (see above) to the image-plane via the mass model, to determine
the multiple image position of the source(s) in the image-plane..
These image-plane positions are used by the next phase in a pipeline if automatic position updating is turned
on."""
# TODO : In the future, the multiple image positions functioon wil use an in-built adaptive grid.
grid = self.analysis.masked_dataset.mask.geometry.unmasked_grid_sub_1
solver = pos.PositionsSolver(grid=grid, pixel_scale_precision=0.001)
try:
multiple_images = [
solver.solve(
lensing_obj=self.max_log_likelihood_tracer,
source_plane_coordinate=centre,
) for centre in self.source_plane_centres.in_grouped_list[0]
]
return grids.GridIrregularGrouped(grid=multiple_images)
except IndexError:
return None