Installing and using smerf

Smear fitting has been implemented as smerf, a patch to difmap. difmap, by Martin Shepherd, is a fairly general program for deconvolution (optionally automated), modeling, and selfcalibration of radio data. Don't make the mistake of thinking it's only for VLBI! smerf is built on top of difmap, and tries to include a superset of difmap's functionality, but necessarily there is sometimes a lag between difmap and smerf releases.

Installing smerf

1. Get a copy of difmap, preferably 2.4i, from either
   • Caltech, or
   • here.
2. Uncompress and untar it into a directory (let's call it $SR) with at least 10 MB of free space.
3. The above step creates $SR/uvf_difmap.

         % cd $SR/uvf_difmap
         

4. Download the patch and its signature into $SR/uvf_difmap.
5. Optional: Verify the patch's signature.

6.       % gunzip difmap2.4i_to_smerf1.3.patch.gz
         

7.       % patch -p1 < difmap2.4i_to_smerf1.3.patch
         

8. From now on the compilation uses the same instructions as difmap, under "INSTALLATION INSTRUCTIONS" in $SR/uvf_difmap/README. Remember to specify your pgplot directory in $SR/uvf_difmap/configure. The resulting executable will be $SR/uvf_difmap/smerf. Note that smerf still uses $DIFMAP_LOGIN for convenience (mine, anyway).

Using smerf

smerf (and difmap) come with online help (help difmap and help models), but you will probably also want to read Greg Taylor's Difmap cookbook (in PostScript) and Getting the Most out of smerf (PDF).

A note on the amount of smearing:

(Also given on the info page.)

With the default settings and properly calibrated data smearing should convolve each feature with a beam corresponding to the probability distribution of its extent on the sky, i.e. it smears to one standard deviation in position, major and minor axes, and position angle. I think this matches what people intuitively expect when they look at an image, but you may want to use two or more standard deviations, to

• account for systematic errors,
• be conservative, or
• just to see what it looks like.

There are two ways to adjust the smearing "knob": change the third parameter of smearall (read the manual and/or help smearall), or wtscale (ditto). The latter way is not recommended, but often happens by accident. I strongly recommend reading AIPS Memo 108, Weights For VLA Data before smearing or preferably at the FILLM stage. And of course you should read help wtscale in difmap/smerf, but you've all done that already, right? Right. If wtscale is too low or high, smearall will yield respectively more or less smearing than you requested. "vplot 4" in difmap/smerf is useful for checking whether wtscale is way off (it is often left unset or set to the wrong value by the telescope), since it shows whether the error bars are too large or small. A more precise check is to compare the rms predicted by wtscale to the rms seen in an empty patch of sky, optionally in Stokes V. You may even prefer to empirically set wtscale using the observed "empty" rms.

Referencing smear fitting

Hopefully in the fullness of time smear fitting will become common knowledge, but in the meantime please consider citing it in your papers:

• R.I. Reid, MNRAS, 367, 4, pp. 1766-1780, 2006 (= astro-ph/0601442) (2.8 MB), and/or
• R.I. Reid, Ph.D. thesis, Univ. of Toronto, 2003 (14 MB)

Report bugs or check for updates

Niceties for use with difmap and/or smerf

• digestsmearall, a crude awk script to summarize smearall's output.
• A colorizer for modelfit's output
• polflux: start your model in I and get a headstart in Q, U, and/or V.
• Emacs gets its own page.
• Something to put in your ~/.teclarc:

  bind up history-search-backward

  Binds the up arrow go back through your command history, skipping duplicates.

Last modified: Mon Jun 4 23:20:06 EDT 2007
Rob Reid,