Have you ever done a self-calibration run to find out the self cal is actually making your images worse, not better? Have you ever guessed at what SOLINT to use while self calibrating? I know I have!
People always say you should evaluate the signal-to-noise of your data before self-calibrating, but I never understood what this meant until today! There is a simple equation to find out if you can self-cal and if the SOLINT you are considering might be too short....
First image your data and clean it pretty good. Afterwards you can look in the image header and not the total cleaned flux. This is your 'Signal'.
Second of all, you want to calculate the noise in your data, per baseline per SOLINT. First, measure the rms noise in your image, in Jy/beam (sig_image). Next, calculate the number of baselines in your data (N_base where N_base = ((N_ant * N_ant-1) / 2) and N_ant is the number of operational antennae). Finally, figure out how much time-on-source went into making your image, in minutes (TOS). The noise of your data per baseline for a given SOLINT (in minutes) is then:
Noise = sig_image * sqrt(N_base) * sqrt(TOS/SOLINT)
Now, compare the 'Signal' with the 'Noise'. For 'P' self cal, you want the Signal to be at least 5 times greater than the Noise. If it's not, then increase your SOLINT. For A&P self cal, you probably want a signal-to-noise of 10-20, at least.
Note: If you are doing multi-facet imaging (at lower frequencies), you want to use the total flux in your data-- that is the sum from all facets, The image headers tell you this as 'CCTOTAL'.
Wednesday, July 9, 2008
How to Know When You Can Self-Cal and What Solint To Use
Self Calibration and DBCON
Let's say you have two data sets that you want to DBCON together. Should you self calibrate them individually? or after DBCONing?
The tip I got is you should self-cal each data set individually as best you can, then DBCON. However, after DBCONing, there might be some small gain offsets between the two data sets. Do a final A&P self cal on the DBCONed data set with a really long SOLINT, so that you basically have one SN solution per data set. This will ensure the original data sets are as consistent with one another as possible.
Two More Ways to Identify Bad Data
Crystal also said a good way to identify RFI is to look at Stokes V, either in TVFLG or UVPLT or whatever. RFI is usually polarized and will pop out as unusually high baselines/channels/times.
Stokes V will usually mimic your amplitude structure (as a function of baseline length). So, for example, if your source has high amplitudes at short baselines, Stokes V should also be a bit higher on these short baselines (so don't get confused and flag them).
And another way to find that bad data-- Data weights. Plot your data in UVPLT with BPARM = 0 13. The weights for all the data should cluster-- if there are any points that are anomalously low or high, flag them! Crystal says she likes to use WIPER. Obviously, be more concerned about data with really high weights that really low weights-- because this data will affect your overall data set more, as it is up-weighted!
Don't Clip Your Data!
I'm at the GBT, and just had a nice long chat with Crystal Brogan (who was very helpful when she reeally didn't need to be). I'm gonna list a few tips she suggests.
Here's one: DON'T CLIP!! She said that if you clip your data based on amplitude (or phase), what you're really doing is masking the lower-level bad data. A baseline is probably all bad if it has quite a few high points, and you don't want to just flag the really high stuff, you want to flag it all. If you clip the high stuff, it will be very hard to ever identify that whole baseline as bad. You'll essentially be 'losing' bad data. I know CLIPing is sometimes tempting, especially at the GMRT, but I can see that it's an especially bad idea in this case.
Monday, June 30, 2008
Need Larger Fonts on Plots
I'm trying to get the labels for my plots in AIPS to be much larger than the default. LWPLA has an option to specify the font size, dparm(8), but after playing with it, it seems like 24pt is the maximum font size. I would really like to use something bigger than this. I can modify the labels manually in Illustrator, but that requires repositioning all the labels, which is way too time intensive. Any other ideas?
UPDATE: Solution using ASPMM parameter in LWPLA detailed in comments.
Saturday, June 28, 2008
Bins in UVPLT
You know what is a great easy way to visualize your data that I often forget about? Bin your data in UVPLT! For example, if you are making a UV distance vs. Amplitude plot, then you can actually see the amplitude structure instead of just seeing tons of points ranging all the way down to an amplitude of zero.
All you have to do is set BPARM(8) = 50 or the number of bins you want.
I think it also plots up faster this way then plotting lots of individual points!
Of course, if what you care about is a handful of really pathelogical points, than this is not the right strategy. But if you are, say, trying to identify a bad baseline or something, this works great!
Tuesday, June 17, 2008
Calibrating Data without a Flux Calibrator
Sometimes when I get data from the archive, it appears that the observers have not observed a flux calibrator. There is a phase calibrator. Is it possible to use this data? Is the data really only good for imaging and getting the morphology of an object, but you can not trust it for absolute fluxes? I feel like I should be able to do something clever to get fluxes...
If you have a question about AIPS that CANNOT be answered by reading the