Authors:
- David Rafferty
- Bas van der Tol
These scripts, along with the TECFIT and TECSCREEN operations in LoSoTo, allow for semi-automated derivation and application of ionospheric TEC screens for LOFAR data. The following scripts are available:
- ion_peel.py: Performs peeling to derive direction-dependent phase solutions
- ion_apply.py: Applies the TEC screens derived by the TECSCREEN operation in LoSoTo
- ion_image.py: Images, with and (optionally) without the TEC screen
The ion_peel.py script takes as input a set of measurement sets at various frequencies and (possibly) multiple fields and performs directional calibration that can be used to correct for time- and position-dependent ionospheric effects. All solutions are copied to a single H5parm file that can be used with LoSoTo to fit for TEC values and to derive phase screens that may be used to make ionospheric corrections with the AWimager.
Command-line arguments define the position and radius over which to search for potential calibrators, the minimum apparent flux for a calibrator, the maximum size of a calibrator, etc. From these inputs, the script can determine the optimal set of calibrators to solve for in each band and in each field. At a given frequency, only the field in which the calibrator is brightest is used.
All the measurement sets are assumed to be a single directory (defined by the 'indir' option). All results are saved in an output directory (defined by the 'outdir' option).
For more information on the options, run:
ion_peeling.py --help
The ion_apply.py script takes as input a H5parm file with a TEC screen fit generated by the TECSCREEN operation in LoSoTo. By default, the screen is exported to all measurement sets in the specified input directory (default is '.').
For more information on the options, run:
ion_apply.py --help
The ion_image.py script automates the imaging of a dataset, including the application of a TEC screen. By default, all measurement sets in the specified input directory are concatenated and imaging together.
For more information on the options, run:
ion_image.py --help