TrAjectory BAsed RFI Subtraction and CALibration (tabascal) of radio interferometry data. A source to visibility model for RFI sources including certain near-field effects. Visibility data is jointly calibrated and cleaned from specific RFI contamination by modelling the RFI signal in the visibilities.
tabascal
is written in JAX
and Dask and can therefore use GPUs and/or CPUs and be distributed across clusters of these compute units.
git clone https://github.com/chrisfinlay/tabascal.git
conda env create -n tab_env -f tabascal/env.yaml
pip install -e tabascal/
To enable GPU compute you need the GPU version of jaxlib
installed. The easiest way is using conda, otherwise, refer to the JAX installation documentation.
conda install jaxlib=*=*cuda* jax cuda-nvcc -c conda-forge -c nvidia
python tabascal/examples/target_observation.py
python tabascal/examples/target_observation.py --help
https://tabascal.readthedocs.io/en/latest/
@ARTICLE{Finlay2023,
author = {{Finlay}, Chris and {Bassett}, Bruce A. and {Kunz}, Martin and {Oozeer}, Nadeem},
title = "{Trajectory-based RFI subtraction and calibration for radio interferometry}",
journal = {\mnras},
year = 2023,
month = sep,
volume = {524},
number = {3},
pages = {3231-3251},
doi = {10.1093/mnras/stad1979},
archivePrefix = {arXiv},
eprint = {2301.04188},
}