Hello,
I am trying to import a calibrated ATCA dataset reduced with miriad to CASA MS format but I'm having some issues. I have tried two approaches:
1- using casa 4.3.1 task importmiriad:
CASA> inp importmiriad
CASA> mirfile='j1550-564.4800'
CASA> vis='test.MS'
where j1550-564.4800 is my calibrated miriad dataset. This is the warning message that I get:
importmiriad: Version 4 - Miriad to MS filler (08-May-2014)
Warning: gains table present, but cannot apply them
(and same for bandpass and leakage corrections)
2-first I convert the vis file to a fits file using miriad task fits:
fits in=j1550-564.4800 op=uvout out=test.fits
Applying bandpass corrections to j1550-564.4800
Applying gain corrections to j1550-564.4800
Applying polarization leakage corrections to j1550-564.4800
Polarisations copied: XX,YY,XY,YX.
169584 visibilities copied to 42396 output records.
Writing FITS antenna table
and then I convert the fits file to a MS format with the CASA task importuvfits:
CASA <2>: inp importuvfits
--------> inp(importuvfits)
# importuvfits :: Convert a UVFITS file to a CASA visibility data set
fitsfile = '' # Name of input UV FITS file
vis = '' # Name of output visibility file (MS)
antnamescheme = 'old' # VLA/EVLA/CARMA only; 'new' or 'old'; 'VA04' or '04' for VLA ant 4
CASA <3>: fitsfile='test.fits'
CASA <4>: vis='test.MS'
CASA <5>: go
--------> go()
Executing: importuvfits()
Here, in theory, the fits task should apply the calibration correction, however in the final MS dataset the calibrated data are missing, looking at the table columns:
['UVW', 'FLAG', 'FLAG_CATEGORY', 'WEIGHT', 'SIGMA', 'ANTENNA1', 'ANTENNA2', 'ARRAY_ID', 'DATA_DESC_ID', 'EXPOSURE', 'FEED1', 'FEED2', 'FIELD_ID', 'FLAG_ROW', 'INTERVAL', 'OBSERVATION_ID', 'PROCESSOR_ID', 'SCAN_NUMBER', 'STATE_ID', 'TIME', 'TIME_CENTROID', 'DATA', 'WEIGHT_SPECTRUM']
it seems that the DATA_CORRECTED column has not been created.
I have tried with a different calibrated dataset but the issue is still there.
Do you have any suggestions?
Thank you in advance for your help,
best,
Giulia
