Example of clfind output ======================== Here is an example of the log file that results from running clfind (the same test file is available in the tar package). ---------------------------------------------------------------- CLFIND: Mon May 31 17:32:11 2004 ---------------------------------------------------------------- Filename = ../example/rosette Lowest contour level = 0.50 Contour increment = 0.50 ---------------------------------------------------------------- Contour level 8.50: 1 pixels 1 regions 1 new clumps Contour level 8.00: 0 pixels 1 regions 0 new clumps Contour level 7.50: 1 pixels 1 regions 0 new clumps Contour level 7.00: 1 pixels 1 regions 0 new clumps Contour level 6.50: 0 pixels 1 regions 0 new clumps Contour level 6.00: 4 pixels 3 regions 2 new clumps Contour level 5.50: 11 pixels 5 regions 2 new clumps Contour level 5.00: 26 pixels 11 regions 6 new clumps Contour level 4.50: 37 pixels 17 regions 3 new clumps Contour level 4.00: 64 pixels 17 regions 4 new clumps Contour level 3.50: 106 pixels 23 regions 1 new clumps Contour level 3.00: 140 pixels 29 regions 6 new clumps Contour level 2.50: 235 pixels 45 regions 8 new clumps Contour level 2.00: 370 pixels 60 regions 12 new clumps Contour level 1.50: 600 pixels 86 regions 23 new clumps Contour level 1.00: 1188 pixels 90 regions 28 new clumps Contour level 0.50: 3586 pixels 386 regions 350 new clumps 105 clumps found (341 rejected) ================================================================ Writing output file: ../example/rosette.fits.clf 0.8 minutes elapsed The meaning of this output is to show how deep the program is into the processing. It proceeds from the highest contour levels to the lowest, and at each level first counts the number of pixels, then determines how many disconnected regions there are. These regions are either new clumps or a lower intensity extension to a previously defined clump (note that at the lowest level, no new clumps are allowed to be defined, only previously defined clumps can be extended in this range). The number of new clumps that are found at each level is displayed. In itself, these numbers are a measure of the degree of complexity in the data cube and may be used in an analysis similar to that described in Adams & Wiseman (1994, ApJ, 435, 693). Once the output file containing the clump assignments is written, you can go ahead and plot clumps, calculate statistics, etc. using the other IDL programs in the package, or using your own tailor-made programs.