Both selfcal
and gpscal
produce antenna gain tables in the same
format as the
calibration tasks previously described. Consequently, after running
these tasks, the gains they derive are applied to the data `on-the-fly'.
However, the new gain tables derived by the self-calibration
tasks will overwrite any old gain tables. Provided the self-calibration
produces an improvement, this is fine. However, if the self-calibration process
degrades the quality of the image (possibly because you gave it bad inputs
or a poor model,
or because you were attempting to calibrate a weak source), then you may have
lost your good set of gains. An additional shortcoming is that the
self-calibration tasks do not apply bandpass corrections - they
assume bandpass corrections have been previously applied. Finally,
if the primary gains have appreciable XY phase (for any antenna
for selfcal, but for the reference antenna only for gpscal),
or significant amplitude gain mismatches (for selfcal
only)
then these corrections should be applied to the data before self-calibration.
Consequently, it is usually wise, before starting to perform self-calibration
iterations, to form a calibrated dataset (apply bandpass
corrections and primary antenna gains). Additionally if you are going to
use selfcal, as discussed below, you should convert to Stokes
parameters. The task used to apply calibration and convert to Stokes
parameters is uvaver.
Thus when using selfcal, use inputs to uvaver
such as;
UVAVER |
vis=vela.uv |
Raw visibility dataset, with primary |
|
calibration tables. |
out=vela.uv.cal |
Output with primary calibration applied. |
stokes=i,q,u,v |
Perform Stokes conversion. |
If using gpscal, do not perform Stokes conversion.
UVAVER |
vis=vela.uv |
Raw visibility dataset, with primary |
|
calibration tables. |
out=vela.uv.cal |
Output with primary calibration applied. |
stokes |
Unset for no Stokes conversion. |
Once you have started self-calibrating, however, you probably
do not need to form a calibrated dataset after each iteration. Provided you
keep your best model of the image, if you do overwrite good gains with bad ones,
then they are simple enough to regenerate using self-calibration and the best
model.
Miriad manager
2016-06-21