autolens.SetupHyper#

class autolens.SetupHyper(hyper_galaxies_lens: bool = False, hyper_galaxies_source: bool = False, hyper_image_sky: Optional[type] = None, hyper_background_noise: Optional[type] = None, hyper_fixed_after_source: bool = False, search_inversion_cls: Optional[autofit.non_linear.abstract_search.NonLinearSearch] = None, search_noise_cls: Optional[autofit.non_linear.abstract_search.NonLinearSearch] = None, search_bc_cls: Optional[autofit.non_linear.abstract_search.NonLinearSearch] = None, search_inversion_dict: Optional[dict] = None, search_noise_dict: Optional[dict] = None, search_bc_dict: Optional[dict] = None)[source]#
__init__(hyper_galaxies_lens: bool = False, hyper_galaxies_source: bool = False, hyper_image_sky: Optional[type] = None, hyper_background_noise: Optional[type] = None, hyper_fixed_after_source: bool = False, search_inversion_cls: Optional[autofit.non_linear.abstract_search.NonLinearSearch] = None, search_noise_cls: Optional[autofit.non_linear.abstract_search.NonLinearSearch] = None, search_bc_cls: Optional[autofit.non_linear.abstract_search.NonLinearSearch] = None, search_inversion_dict: Optional[dict] = None, search_noise_dict: Optional[dict] = None, search_bc_dict: Optional[dict] = None)[source]#

The hyper setup of a pipeline, which controls how hyper-features in PyAutoLens template pipelines run, for example controlling whether hyper galaxies are used to scale the noise and the non-linear searches used in these searchs.

Users can write their own pipelines which do not use or require the SetupHyper class.

Parameters
  • hyper_galaxies – If a hyper-pipeline is being used, this determines if hyper-galaxy functionality is used to scale the noise-map of the dataset throughout the fitting.

  • hyper_image_sky – If a hyper-pipeline is being used, this determines if hyper-galaxy functionality is used include the image’s background sky component in the model.

  • hyper_background_noise – If a hyper-pipeline is being used, this determines if hyper-galaxy functionality is used include the noise-map’s background component in the model.

  • hyper_fixed_after_source – If True, the hyper parameters are fixed and not updated after a desnated pipeline in the analysis. For the SLaM pipelines this is after the SourcePipeline. This allow Bayesian model comparison to be performed objected between later searchs in a pipeline.

  • search_inversion_cls – The non-linear search used by every hyper model-fit search.

  • search_inversion_dict – The dictionary of search options for the hyper model-fit searches.

Methods

__init__([hyper_galaxies_lens, …])

The hyper setup of a pipeline, which controls how hyper-features in PyAutoLens template pipelines run, for example controlling whether hyper galaxies are used to scale the noise and the non-linear searches used in these searchs.

hyper_background_noise_from(result)

hyper_galaxy_lens_from(result[, …])

Returns the HyperGalaxy Model from a previous pipeline or search of the lens galaxy in a template PyAutoLens pipeline.

hyper_galaxy_source_from(result[, …])

Returns the HyperGalaxy Model from a previous pipeline or search of the source galaxy in a template PyAutosource pipeline.

hyper_galaxy_via_galaxy_model_from(…[, …])

hyper_image_sky_from(result[, as_model])

Attributes

hypers_all_except_image_sky_off

hypers_all_off