BaSC is short for Bayesian Source Characterisation. It is an MCMC process that performs source detection and characterisation on dirty maps, taking into account the properties of the beam in a more rigorous way that CLEAN does.
It is based on a method developed by Steve Gull, and uses the BayeSys MCMC driver.
BaSC requires a c compiler, Python 3, and the numpy, astropy and sklearn libraries. On Linux, type make to compile the extension, or if using Mac, type 'make mac'. Currently Windows is not supported - you will have to run it in an Ubuntu terminal on a Windows machine.
To try out BaSC, run the example script example.py in the BaSC folder. This should locate a single source in the centre of the map, and return the models from the burned in chain to chain.txt
To run BaSC on your own data, use
basc.py <dirty map file> <dirty psf file> <primary beam flux file>
In general, import basc into your Python program and use it as shown in example.py
For more information, please email Peter Hague at peterhague AT protonmail.com