ConTEST performs a nonparametric consistency test between observations and astrophysical models by combining statistical methods and distance measures into a test statistic that quantifies how closely a model matches the data. It evaluates this statistic through hypothesis testing with bootstrap resampling and can be applied in different scenarios depending on the nature of the model. The package provides four core functions: two regression tests that assess the consistency of a model with an observed dataset and its uncertainties, including a smoothed version. ConTEST also includes an outlier test that evaluates whether an observed sample is likely drawn from a given density model or simulated dataset, and a density test for comparing a density model or simulated dataset with an observed dataset.

AutoSourceID-Light (ASID-L) analyzes optical imaging data using computer vision techniques that can naturally deal with large amounts of data. The framework rapidly and reliably localizes sources in optical images.