ghost is a modular, analytic statistical model of the connection between galaxies and dark matter halos. It is built from chains of parametrised scaling relations, linking basic halo and galaxy properties, and their (parametrised) pdfs.
A Python implementation of the model is available as ghost on GitHub. It is available under an open source MIT license, and contributions (e.g. pull requests and bug reports) are welcome. Please cite the paper (see below) if you use or modify the code.
Processed MCMC chains (i.e. that have been thinned and had burn-in discarded) can be downloaded from here [962KB, MD5: 980b8f07fdf8e9d4e24f40b523e5a549, processed_chain_20161028.tar.gz]. The data used were the g and z-band optical luminosity functions from GAMA and the NVSS/6dFGS 1.4 GHz radio luminosity function from Mauch & Sadler, all at z=0. The emcee affine-invariant ensemble sampler was used to produce the samples.
The paper is available on arXiv, but you can also download it from here [pdf].