Welcome!

This is the documentation of hsr4hci, a Python package (and a set of scripts) that provides methods for applying a post-processing scheme based on Half-Sibling Regression (HSR) to High-Contrast Imaging (HCI) data. It contains all the code for the following research paper (see also Citation):

Gebhard, T. D., Bonse, M. J., Quanz, S. P., & Schölkopf, B. (2022). Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework. Astronomy & Astrophysics, 666, A9. Also available on arXiv:2204.03439.

In this documentation, we explain the structure of the code base and provide some guides to help you get started if you want to reproduce our results or use our code for your own experiments.

We have tried our best to follow best practices for software development and document all important steps. However, at the end of the day, it is still research code. Therefore, if you do get stuck with anything, please feel free to reach out to us!

This applies, of course, also if you find any bugs or problems (either in the code or the docs)! 🐛