vla_selfcal

Self-calibration pipeline to process VLA data, using CASA tools and WSClean.

Operations

• Begins imaging in WSClean using high DR parameters (multi-term, multi-scale, deep clean)
• Uses model to calibrate on chosen solution intervals and modes
• (optional) Performs statistical flagging on RESIDUAL_DATA column
• (optional) Smoothes short-timescale solutions for less noise

Install the prerequisite software:

-Singularity -Singularity container from https://tikk3r.github.io/flocs/ -CASA -Python (version 3 and above)

Running instructions

1. Initiate a CASA environment module load casa
   

2. Ensure that PYTHONPATH points to the CASA installation python export PYTHONPATH="/soft/casa-latest/bin/python3"
   

3. Edit vla_selfcal.py so that singularity and CASA paths point to your installations. Place paths to MS and output directories
   

4. Run python3 vla_selfcal.py <ms> <output_dir> <config.txt>
   

Example outputs

Basic example of running the pipeline on JVLA Ku-band C-array data on the bright radio source 3C 123, using 5 cycles with just phase calibration.