This repository provides the code used to calculate the Bayesian probability of stars in some photometric catalog being a match to a subset of Gaia sources. Additionally, an example use of the code is provided in the form of a Jupyter Notebook. This code was written to carry out the analysis outlined in Medan, Lepine and Hartman (2021), not as a stand alone Python package. Because of this, if you would like to adapt or use this code, it is strongly encouraged that you read that paper to understand the assumptions made in this method. Additionally, using this code requires pre-querying an external catalog (as outlined in Medan, Lepine and Hartman (2021)) and formatting the data as stated in the example Jupyter Notebook.

If you use any of this code to match data used in a subsequent study, please cite Medan, Lepine and Hartman (2021).

To install this code onto your machine simply run:

pip install git+https://github.com/imedan/bayes_match.git

In the branch "chunked_match", there is an updated version of the code that will query the external catalog for you and completes some of the tasks in parallel to speed up the initial match. This code is written, but not thoroughly tested. If your match is very large though, it may be worthwhile to try this version of the code.