autolens.AnalysisPoint

class autolens.AnalysisPoint(point_dict: autolens.point.point_dataset.PointDict, solver: autolens.point.point_solver.PointSolver, imaging=None, cosmology=FlatLambdaCDM(name="Planck15", H0=67.7 km / (Mpc s), Om0=0.307, Tcmb0=2.725 K, Neff=3.05, m_nu=[0. 0. 0.06] eV, Ob0=0.0486), settings_lens=<autolens.lens.model.settings.SettingsLens object>)

__init__(point_dict: autolens.point.point_dataset.PointDict, solver: autolens.point.point_solver.PointSolver, imaging=None, cosmology=FlatLambdaCDM(name="Planck15", H0=67.7 km / (Mpc s), Om0=0.307, Tcmb0=2.725 K, Neff=3.05, m_nu=[0. 0. 0.06] eV, Ob0=0.0486), settings_lens=<autolens.lens.model.settings.SettingsLens object>)

The analysis performed for model-fitting a point-source dataset, for example fitting the point-sources of a multiply imaged lensed quasar or supernovae of many source galaxies of a galaxy cluster.

The analysis brings together the data, model and non-linear search in the classes log_likelihood_function, which is called by every iteration of the non-linear search to compute a likelihood value which samples parameter space.

Parameters:

• point_dict – A dictionary containing the full point source dictionary that is used for model-fitting.
• solver – The object which is used to determine the image-plane of source-plane positions of a model (via a Tracer).
• imaging – The imaging of the point-source dataset, which is not used for model-fitting but can be used for visualization.
• cosmology – The cosmology of the ray-tracing calculation.
• settings_lens – Settings which control how the model-fit is performed.

Methods

__init__(point_dict, solver[, imaging, …])	The analysis performed for model-fitting a point-source dataset, for example fitting the point-sources of a multiply imaged lensed quasar or supernovae of many source galaxies of a galaxy cluster.
fit_positions_for(instance)
log_likelihood_function(instance)	Determine the fit of the strong lens system of lens galaxies and source galaxies to the point source data.
make_result(samples, model, search)
modify_after_fit(paths, model, result)	Overwrite this method to modify the attributes of the Analysis class before the non-linear search begins.
modify_before_fit(paths, model)	Overwrite this method to modify the attributes of the Analysis class before the non-linear search begins.
profile_log_likelihood_function(paths, instance)	Overwrite this function for profiling of the log likelihood function to be performed every update of a non-linear search.
save_attributes_for_aggregator(paths)
save_results_for_aggregator(paths, model, …)
tracer_for_instance(instance, …)
visualize(paths, instance, during_analysis)

log_likelihood_function(instance)

Determine the fit of the strong lens system of lens galaxies and source galaxies to the point source data.

Parameters:instance – A model instance with attributes Returns:fit – A fractional value indicating how well this model fit and the model masked_imaging itself Return type:Fit