Montblanc, written in Python, is a GPU implementation of the Radio interferometer measurement equation (RIME) in support of the Bayesian inference for radio observations (BIRO) technique. The parameter space that BIRO explores results in tens of thousands of computationally expensive RIME evaluations before reduction to a single X² value. The RIME is calculated over four dimensions, time, baseline, channel and source and the values in this 4D space can be independently calculated; therefore, the RIME is particularly amenable to a parallel implementation accelerated by Graphics Programming Units (GPUs). Montblanc is implemented for NVIDIA's CUDA architecture and outperforms MeqTrees (ascl:1209.010) and OSKAR.

CARACal (Containerized Automated Radio Astronomy Calibration, formerly MeerKATHI) reduces radio-interferometric data. Developed originally as an end-to-end continuum- and line imaging pipeline for MeerKAT, it can also be used with other radio telescopes. CARACal reduces large data sets and produces high-dynamic-range continuum images and spectroscopic data cubes. The pipeline is platform-independent and delivers imaging quality metrics to efficiently assess the data quality.

katdal interacts with the chunk stores and HDF5 files produced by the MeerKAT radio telescope and its predecessors (KAT-7 and Fringe Finder), which are collectively known as MeerKAT Visibility Format (MVF) data sets. The library uses memory carefully, allowing data sets to be inspected and partially loaded into memory. Data sets may be concatenated and split via a flexible selection mechanism. In addition, katdal provides a script to convert these data sets to CASA MeasurementSets.

QuartiCal is the successor to CubiCal (ascl:1805.031). It implements a suite of fast radio interferometric calibration routines exploiting complex optimization. Unlike CubiCal, QuartiCal allows for any available Jones terms to be combined. It can also be deployed on a cluster.