# 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 fit – A fractional value indicating how well this model fit and the model masked_imaging itself Fit