Multiple output files

If one wants to write out multiple fits files at a time which have same inname and inclass just different inseq no. how does one do that?

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limited line length in runfiles

in runfiles you can't have lines longer than ~70 characters (i'm not sure what the actual limit is). i've only had a problem with this once when i was defining a large array of filenames for the multiple pointings in a mosaic. the only way to get the whole array defined was to fill in the last three entries manually. i've posted the code i used below.

     string*8 obj_name(15)
     obj_name = 'GH40-1','GH40-2','GH40-3','GH40-4','GH40-5','GH40-6'
     obj_name(7) = 'GH40-7'
     obj_name(8) = 'GH40-8'
     obj_name(9) = 'GH40-9'

Note added by Amanda on 10/05/07: It's actually easier to use the tilde. See this post.

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SMOTH and and regridding

Can anyone suggest an AIPS task that can help me with the following? I'm looking at emission lines in a diffuse source. I needed to try and increase my S/N levels, but could not smooth the line because it has some complicated structure (multiple velocity components, etc) that I want to fit. So, I smoothed spatially using SMOTH.

Since my beam is now almost twice the size that it used to be (6'' instead of 4'') I think the pixel size of the original image may be oversampling the beam. Can I regrid the smoothed image to have 1'' pixels instead of 0.5'' pixels? How?

Thanks,
Katie

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Gaussian Fitting

Here is a request from an anonymous reader; any advice, anyone?

Can you please help me with the following? I have an image with 5 substructures in it. The peaks inthe image decrease in size from left to right, the leftmost two are the brightest. All of them are close to each other. With AIPS jmfit I can fit not more than 4 gaussians. I played around a bit and noticed that dividing the whole image into two parts and fitting 2 gaussians and 3 gaussians respectively in the two parts does not work properly and gives a bad fit. So I came up with this idea. I can first fit four gaussians to first four peaks, and then from the whole image subtract the brightest two. To the residual image now I fit 3 gaussians. I checked whether this technique gives me a good fit to a slice of data (Wrote my own fortran programs for that). It seems to work but my problem is how to do it in aips.

So my problem is the following. I want to fit 4 gaussians to a selected range of data. Then subtract only the brightest two gaussian from the whole image. Then fit other three gaussians to another restricted part of the data. Could anyone please help me on this?

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self-calibration subtleties : 2 questions

• i have a dataset which shows significantly different structure depending on the weighting (robust value) used when i image it. should i self-cal using maps with a natural weighting that show the diffuse emission or maps with a more uniform weighting which emphasize the point sources? i'm inclined to use a robust value around 0 because i feel like the point sources are more reliable self-cal targets (and contribute more flux) even though what i really care about is the diffuse stuff and the maps i make for the analysis will use a robust > 0.



• do i always need to self-cal using clean components from the entire primary beam even if the source i care about is only in the inner 15%? since it does seem true that "the best self-cal model is the one that contains the most flux" i think i am obligated to image the entire primary beam during self-calibration.

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Reference Frequencies (Center v. Edge?)

I've come to the conclusion that for 1-channel continuum data coming from the VLA, the frequency that you see in the header and in your LISTR 'scans' ouput is the center of your bandwidth (not the beginning).

I come to this conclusion mostly because the L-band observing guide on the VLA web page says that "The two recommended center frequencies are 1365 and 1435 MHz." I used the defaults when I made my observe files, and now my LISTR output lists these two frequencies.

EDIT: June 21 2007
And these words from Eric Greisen

In FITS coordinates, the stated coordinate is at the center of each
voxel.  It may be moved by having a non-integer reference pixel.  In
normal VLA data we do not do that, so these frequencies are nominally
at the center of your band.  I say nominally, because if the bandshape
is not symmetric about the center, then the effective frequency will
diverge from the one stated.  True astrometry should never be done
with wide, asymmetric bandshapes (and the VLA at 50 MHz is
asymmetric).

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Where did R go?

Ok, this is kind of a strange thing. I'm working with Pband data. I've gone through initial flagging, and then I run CALIB. But for some reason it's not finding my R data... so I get 1/2 good solutions and 1/2 failed solutions (because it finds the L just fine). But I look at the data (and when I flagged it too) and it's *there*. Has anyone encountered this? What's going on and how to I fix it? I'm using pretty standard inputs...

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