From efomalon@cv3.cv.nrao.edu Fri Aug 10 11:20:27 2001 Date: Fri, 10 Aug 2001 10:38:44 -0400 From: Ed Fomalont To: Frazer Owen Cc: aips2-naug@zia.aoc.NRAO.EDU Subject: AIPS - AIPS++ Imaging test Hello all, Here is a note that I just submitted to the aips++ group. On the whole it demonstrates that the aips++ cleaning algorithms work well. But, they are about a factor of three times slower than those in aips for this limited testing range. A COMPARISON OF AIPS++ and AIPS IMAGING SOFTWARE: August 10, 2001 Ed Fomalont This memo gives the results of a simple comparison between the imaging and cleaning methods which are available in aips and aips++. A simple data set is used and the comparison concentrates on two aspects: the execution time (a little on disk space) and the type of cleaning method for which aips++ has several options. The tests were made on a relatively empty linux machine with 786M of memory. The execution times are given in seconds. They are about 1.3 times longer than the cpu times unless otherwise noted. SUMMARY OF COMPARISON: 1. At the level of a dynamic range of about 50, all aips++ and aips convolution methods produce clean images which are in good agreement. The field emission is relatively simple, so that these experiments are not a test of the ultimate accuracy of the various algorithms. 2. The typical execution times for aips++ deconvolutions range from 3 to 7 times slower than the comparable aips deconvolutions. It is unclear how this will scale with larger data sets. 3. The number of deconvolution options in aips++ are somewhat confusing and overlapping and need a bit more explanation. --------------------------------------------------------------------------- THE DATA SET The data set contains 2 hours of data (over a span of 8 hours) at 5 GHz from the VLA with two IF's and 10-sec data sampling. It contains 180,000 data points and is a typical relatively small wide-band continuum data set from the VLA. It is 1/32th of the complete data set spread over eight days at four mozaic pointings. The data were calibrated and edited in aips, and then tranferred to aips++ using fits data sets. All weights were set to 1.0 before transferral. Some problem with weight transfer is being looked into. READING DATA FROM DISK: System real time size of all files aips++ 55 19.9 mb aips 32 10.8 mb (compressed) 20.5 mb (uncompressed) The timing difference is not very significant. The file sizes reflects the general tendency that a u-v data base in aips++ is about twice the size of a comparable compressed data base in aips, but about the same size as an aips uncompressed u-v data set. MAKING DIRTY IMAGES AND BEAMS: The image size was 2048x2048 with 1" cell size. This covers the primary beam for the VLA 5 GHz, C-configuration data. Natural weighting was used to make the comparison as similar as possible. The comparison of execution between aips++ and aips are: System real time(s) Tasks aips++ 42 making 3 cols (only once) 66 make beam 66 make map 132 Total time (excluding 3 col formation) aips 22 Total time for map and beam The execution in aips++ is a factor of six longer than in aips, even without the overhead of making the three columns on initial use of imager. CLEANING: The radio emission is relatively simple and confined to the inner quarter of the radio field. The dynamic range in the image is 50, so that all deconvolution processes should work reasonably well. The field will be cleaned with 2000 iterations with no boxes. Two deconvolution procedures are available in aips: Hobgom clean using the dirty image and beam (APCLN), which does not go back to the u-v data. Clark clean done in IMAGR has a combination of image subtraction and u-v subtraction during the cleaning process. The aips++ counterparts, I think, are as follows: Task Parameter Execution time (sec) aips task APCLN 72 aips++ algorithm hogbom 356 aips++ algorithm deconvolver >1000 (something wrong with the iterator) aips task IMAGR 205 aips++algorithm wfclark 750 aips++algorithm clark+restore 380 COMMENTS on AIPS++ Deconvolution methods: 1. The Hogbom cleans take much too long. Part of the problem is that the algorithm for choosing when to stop finding peaks on the image and subtracting the beam patterns needs some improvement. 2. What's the difference between the clark and wfclark algorithms if only one field is cleaned? I am guessing but I think the `clark' algorithm does the u-v subtraction by making a simple fft of the clean components and in this way may be little different from the hogbom clean. I believe that `wfclark' algorithm does the subtraction of the clean components more accurately. This is why the whole image is cleaned with wfclark and only the inner quarter area with clark, before the restore step. IMAGR does clean all of the image except at the very boundries. In any case, more discussion of these deconvolving algorithms are needed and recommendations of their use. 3. The aips++ deconvolvers work satisfactorily. If they can be sped-up by a factor of about three in execution speed, they would have about the same efficiency as the comparable processors in aips - at least for these moderately small data sets.