The RHT (Rolling Hough Transform) measures linear intensity as a function of orientation in images. This machine vision algorithm works on any image-space (2D) data, and quantifies the presence of linear structure as a function of orientation. The RHT can be used to identify linear features in images, to quantify the orientation of structure in images, and to map image intensity from 2D x-y space to 3D x-y-orientation space. An option in the code allows the user to quantify intensity as a function of direction (modulo 2pi) rather than orientation (modulo pi). The RHT was first used to discover that filamentary structures in neutral hydrogen emission are aligned with the ambient magnetic field.

DPMhalo (Descriptive Parametric Model) generates profiles of gaseous halos (pressure, electron density, and metallicity) as functions of radius, halo mass, and redshift. The code assumes spherically symmetric, volume-filling warm/hot gas, and enables mock observations of the circumgalactic medium (CGM), group halos, and clusters across a number of wavebands including X-ray, sub-millimeter/millimeter, radio, and ultraviolet (UV).