def __init__(
self,
name: str,
positions: aa.Grid2DIrregular,
noise_map: aa.ValuesIrregular,
tracer: Tracer,
point_solver: PointSolver,
point_profile: Optional[ag.ps.Point] = None,
):
"""
A lens position fitter, which takes a set of positions (e.g. from a plane in the tracer) and computes \
their maximum separation, such that points which tracer closer to one another have a higher log_likelihood.
Parameters
-----------
positions : Grid2DIrregular
The (y,x) arc-second coordinates of positions which the maximum distance and log_likelihood is computed using.
noise_value
The noise-value assumed when computing the log likelihood.
"""
self.name = name
if point_profile is None:
point_profile = tracer.extract_profile(profile_name=name)
self.point_profile = point_profile
self.point_solver = point_solver
if self.point_profile is None:
raise exc.PointExtractionException(
f"For the point-source named {name} there was no matching point source profile "
f"in the tracer (make sure your tracer's point source name is the same the dataset name."
)
self.source_plane_coordinate = self.point_profile.centre
if len(tracer.planes) > 2:
upper_plane_index = tracer.extract_plane_index_of_profile(
profile_name=name)
else:
upper_plane_index = None
model_positions = point_solver.solve(
lensing_obj=tracer,
source_plane_coordinate=self.source_plane_coordinate,
upper_plane_index=upper_plane_index,
)
model_positions = model_positions.grid_of_closest_from(
grid_pair=positions)
super().__init__(
data=positions,
noise_map=noise_map,
model_data=model_positions,
mask=None,
inversion=None,
)
def __init__(
self,
name: str,
fluxes: aa.ValuesIrregular,
noise_map: aa.ValuesIrregular,
positions: aa.Grid2DIrregular,
tracer: Tracer,
point_profile: Optional[ag.ps.Point] = None,
):
self.tracer = tracer
self.name = name
self.positions = positions
if point_profile is None:
point_profile = tracer.extract_profile(profile_name=name)
self.point_profile = point_profile
if self.point_profile is None:
raise exc.PointExtractionException(
f"For the point-source named {name} there was no matching point source profile "
f"in the tracer (make sure your tracer's point source name is the same the dataset name."
)
elif not hasattr(self.point_profile, "flux"):
raise exc.PointExtractionException(
f"For the point-source named {name} the extracted point source was the "
f"class {self.point_profile.__class__.__name__} and therefore does "
f"not contain a flux component.")
if len(tracer.planes) > 2:
upper_plane_index = tracer.extract_plane_index_of_profile(
profile_name=name)
deflections_func = partial(
tracer.deflections_between_planes_from,
plane_i=0,
plane_j=upper_plane_index,
)
else:
deflections_func = tracer.deflections_yx_2d_from
self.magnifications = abs(
self.tracer.magnification_2d_via_hessian_from(
grid=positions, deflections_func=deflections_func))
model_fluxes = aa.ValuesIrregular(values=[
magnification * self.point_profile.flux
for magnification in self.magnifications
])
super().__init__(
data=fluxes,
noise_map=noise_map,
model_data=model_fluxes,
mask=None,
inversion=None,
)
