GNU Astronomy Utilities

Next: , Previous: , Up: General program usage tutorial   [Contents][Index]

2.2.19 Finding reddest clumps and visual inspection

As a final step, let’s go back to the original clumps-based color measurement we generated in Working with catalogs (estimating colors). We’ll find the objects with the strongest color and make a cutout to inspect them visually and finally, we’ll see how they are located on the image. With the command below, we’ll select the reddest objects (those with a color larger than 1.5):

$ asttable cat/mags-with-color.fits --range=F105W-F160W,1.5,inf

You can see how many they are by piping it to wc -l:

$ asttable cat/mags-with-color.fits --range=F105W-F160W,1.5,inf | wc -l

Let’s crop the F160W image around each of these objects, but we first need a unique identifier for them. We’ll define this identifier using the object and clump labels (with an underscore between them) and feed the output of the command above to AWK to generate a catalog. Note that since we are making a plain text table, we’ll define the necessary (for the string-type first column) metadata manually (see Gnuastro text table format).

$ echo "# Column 1: ID [name, str10] Object ID" > reddest.txt
$ asttable cat/mags-with-color.fits --range=F105W-F160W,1.5,inf \
           | awk '{printf("%d_%-10d %f %f\n", $1, $2, $3, $4)}' \
           >> reddest.txt

We can now feed reddest.txt into Gnuastro’s Crop program to see what these objects look like. To keep things clean, we’ll make a directory called crop-red and ask Crop to save the crops in this directory. We’ll also add a -f160w.fits suffix to the crops (to remind us which filter they came from). The width of the crops will be 15 arc-seconds (or 15/3600 degrees, which is the units of the WCS).

$ mkdir crop-red
$ astcrop flat-ir/xdf-f160w.fits --mode=wcs --namecol=ID \
          --catalog=reddest.txt --width=15/3600,15/3600  \
          --suffix=-f160w.fits --output=crop-red

You can see all the cropped FITS files in the crop-red directory. Like the MakeProfiles command in Aperture photometry, you might notice that the crops aren’t made in order. This is because each crop is independent of the rest, therefore crops are done in parallel, and parallel operations are asynchronous. In the command above, you can change f160w to f105w to make the crops in both filters.

To view the crops more easily (not having to open ds9 for each image), you can convert the FITS crops into the JPEG format with a shell loop like below.

$ cd crop-red
$ for f in *.fits; do                                                  \
    astconvertt $f --fluxlow=-0.001 --fluxhigh=0.005 --invert -ojpg;   \
$ cd ..
$ ls crop-red/

You can now use your general graphic user interface image viewer to flip through the images more easily, or import them into your papers/reports.

The for loop above to convert the images will do the job in series: each file is converted only after the previous one is complete. If you have GNU Parallel, you can greatly speed up this conversion. GNU Parallel will run the separate commands simultaneously on different CPU threads in parallel. For more information on efficiently using your threads, see Multi-threaded operations. Here is a replacement for the shell for loop above using GNU Parallel.

$ cd crop-red
$ parallel astconvertt --fluxlow=-0.001 --fluxhigh=0.005 --invert   \
           -ojpg ::: *.fits
$ cd ..

Did you notice how much faster this one was? When possible, its always very helpful to do your analysis in parallel. But the problem is that many operations are not as simple as this. For such cases, you can use Make which will greatly help designing workflows. But that is beyond the topic here.

As the final action, let’s see how these objects are positioned over the dataset. DS9 has the “Region”s concept for this purpose. You just have to convert your catalog into a “region file” to feed into DS9. To do that, you can use AWK again as shown below.

$ awk 'BEGIN{print "# Region file format: DS9 version 4.1";      \
             print "global color=green width=2";                 \
             print "fk5";}                                       \
       !/^#/{printf "circle(%s,%s,1\") # text={%s}\n",$2,$3,$1;}'\
      reddest.txt > reddest.reg

This region file can be loaded into DS9 with its -regions option to display over any image (that has world coordinate system). In the example below, we’ll open Segment’s output and load the regions over all the extensions (to see the image and the respective clump):

$ ds9 -mecube seg/xdf-f160w.fits -zscale -zoom to fit    \
      -regions load all reddest.reg

Next: Writing scripts to automate the steps, Previous: Matching catalogs, Up: General program usage tutorial   [Contents][Index]