Self-calibration without the hassle!#
Tired of self-calibrating your data by hand? You’ve come to the right place! The auto_selfcal package can automatically self-calibrate your (ALMA and VLA, currently) data with almost no effort from you. But don’t take our word for it, just ask the ALMA Pipeline. To see how to make this work for you, see our quickstart guide:
Quickstart#
To use auto_selfcal with an existing monolithic CASA distribution:
git clone https://github.com/jjtobin/auto_selfcal.git
cd </path/to/pipeline/calibrated/*_targets.ms/files>
casa -c </path/to/auto_selfcal>/bin/auto_selfcal.py
Or to install into an existing Python environment (note that a Python version for which CASA is available is required) and run from a directory where pipeline-calibrated *_targets.ms files exist:
pip install auto-selfcal
cd </path/to/pipeline/calibrated/*_targets.ms/files>
auto_selfcal
Or check out the rest of our documentation:
Acknowledging auto_selfcal#
Love auto_selfcal and want to cite it in your paper? Please include the following citations:
@software{auto_selfcal,
author = {John J. Tobin and Patrick Sheehan and Rui Xue and Austen Fourkas},
title = {jjtobin/auto\_selfcal: v2.0.0},
month = dec,
year = 2025,
publisher = {Zenodo},
version = {v2.0.0},
doi = {10.5281/zenodo.17871742},
url = {https://doi.org/10.5281/zenodo.17871742},
}
Contributing and/or Bugs#
Want to contribute? Found a bug? Please feel free to open an issue or pull request on GitHub and the auto_selfcal team will follow up with you there.
Acknowledgements:#
Certain functions to convert from LSRK to channel, S/N estimates, and tclean wrapper have their origins from the ALMA DSHARP large program reduction scripts.
The functions to parse the cont.dat file and convert to channel ranges (used the routine from above) was adapted from a function written by Patrick Sheehan for the ALMA eDisk large program