uvaver% inp Task: uvaver vis = gc_rx1.lsb.tsys select = source(sgra*, sgrb*, nrao530) out = gc_rx1.lsb.tsys.cal
The data gc_rx1.lsb.tsys.cal is the calibrated data. With uvaver, one can average the data from each chunk to produce a `ch0' data set. The corresponding setup is given below:
uvaver% inp Task: uvaver vis = gc_rx1.lsb.tsys.cal line = channel, 24,2,13,16 out = gc_rx1.lsb.tsys.cal.ch0
To make a continuum data, the setup below is suggested:
uvaver% inp Task: uvaver vis = gc_rx1.lsb.tsys.cal.ch0 line = channel, 1,1,24 out = gc_rx1.lsb.tsys.cal.cont
If the source has sufficient S/N for selfcal, it would be better to stay with the chunk-based `ch-0' data set. Then, the option of MFS in the self-calibration and imaging process will minimize the residual errors before averaging.
One can break the multi-source file into single source files using uvsplit
uvsplit% inp Task: uvsplit vis = gc_rx1.lsb.tsys.cal options = nowindow
As we have shown, the unwrapped phase across the broad SMA band (2 GHz) shows a large drift for some antennas (particularly for the antennas with long baselines). Even for continuum imaging, the bandpass calibration will be crucial for removing the phase ripples to increase the dynamic range. The calibration feature for multiple frequency windows (or chunks) in Miriad tasks mfcal or smamfcal is highlighted for synthesizing a continuum image from a large number of spectral windows's data.