General direction-independent and direction-dependent self-calibration:
- refinement self-calibration for individual 'extracted' datasets
- full field of view self-calibration and extraction of regions of interest
If you use facetselfcal or extraction for scientific work, please cite van Weeren et al. (2021, A&A, 651, 115) paper:
https://ui.adsabs.harvard.edu/abs/2021A%26A...651A.115V/abstract
Requirements:
- Container with all standard LOFAR software: https://tikk3r.github.io/flocs/
Installation:
git clone https://github.com/rvweeren/lofar_facet_selfcal.git
pip install git+https://github.com/rvweeren/lofar_facet_selfcal.git
(with pip install, you install facetselfcal, h5_merger, ds9facetgenerator, sub_sources_outside_region
as command line functionalities)
Usage examples:
-
HBA Dutch baselines for extracted LoTSS data from the ddf-pipeline:
python /<path>/lofar_facet_selfcal/facetselfcal.py -b yourDS9extractbox.reg --auto -i yourimagename yourextracted.ms -
Standard auto settings:
python /<path>/lofar_facet_selfcal/facetselfcal.py --imsize=1600 --auto -i yourimagename yourextracted.ms -
With a config file (see an example in data/example_config.txt)):
python /<path>/lofar_facet_selfcal/facetselfcal.py --config=yourconfig.txt yourextracted.ms
HBA international baselines
- delaycalibrator
- target source
LBA Dutch baselines
- < 30 MHz
- < 30 MHz
MeerKAT
- UHF, L-band, and S-band
- direction-independent and direction-dependent self-calibration
