Some Additional Tools

We briefly describe some other useful tools.

• Mosaic Coverage - MOSLST: In doing a mosaic observation, you will want to good Fourier sampling (coverage) as well as even sampling of the different pointing centres. Task moslst produces a simple plot of LST vs point number for mosaiced visibility files. In doing this, it required that you follow the field naming convention mentioned earlier (see Section 21.3).
• Listing Mosaic Tables - IMLIST: Task invert stores information concerning its linear mosaic operation in the item mostable (stored in both the map and beam datasets). The table can be printed by imlist, using options=mosaic.
• Mosaic Point-Spread Function - MOSPSF: It is occasionally instructive to look at the point-spread function at a particular position in a mosaic experiment. Task mospsf can compute this. Apart from the input beam data-set, the user must specify a position and frequency of interest (the point-spread function is also frequency dependent).
• Mosaic Sensitivity and Gain Images - MOSSEN: Just as the point-spread function varies, so does the expected noise level in an output mosaiced image. Additionally, as mentioned above, invert does not attempt to completely correct for the primary beam attenuation where there is too little data (i.e. some primary beam attenuation is in the output image). The task mossen can produce images of the expected rms noise and the remaining primary beam attenuation given a mosaiced image.
• MOSTESS: mostess implements a mosaicing algorithm identical to the AIPS VTESS program. It is more cumbersome to use, and produces results which are no better than mosmem. Its use is not recommended.
• PMOSMEM: pmosmem can be used to do a joint deconvolution of a polarimetric mosaic. The ``joint'' in this case applies to both jointly processing the multiple Stokes parameters as well as processing the different pointings. With polarised emission being potentially positive and negative valued, the entropy measure for this is different from a simple total intensity deconvolution. See Sault et al. (1999) (A&A 139, 387) for more background on joint polarimetric deconvolution.