| CSIRO Astronomy and Space Science Parkes Users Guide |
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Raw data output from ATNF correlators is written in RPFITS format. More information on RPFITS can be found at http://www.atnf.csiro.au/computing/software/rpfits.html.
A guide to using the AIPS++ programs LIVEDATA and GRIDZILLA can be found here (look under ’Parkes Multibeam Reduction’). More detailed information on the specifics of these programs as related to the HIPASS and ZOA HI Surveys can be found in Barnes et al. (2001), MNRAS, 322 486. The GRIDZILLA GUI contains a HELP menu item and the different sections of the LIVEDATA GUI contains widgets, which when clicked on, present the user with a popup containing information relevant to that section.
With GRIDZILLA it is possible to perform batch processing via a script (called batch.g) which contains the following:
include 'gridzilla.g'
files := shell('ls *.sdfits')
gridder := gridzilla(remote=T, files=files, selection=ind(files),
autosize=T,pixel_width=4.0, pixel_height=4.0,tsys_weight=T,
beam_FWHM=14.4, beam_normal=25, p_FITSfilename=test)
gridder->go()
await gridder->finished
print 'finished processing'
exit
Note the gridder line is split here over two lines, but should be only on one line.
The script is run by typing glish -l batch.g .
The ATNF Spectral Analysis Package (ASAP) is a new software package to reduce single-dish, single-pointing spectral line observations. At this stage it is tuned towards data from ATNF instruments and reads RPFITS, SDFITS and is able to output SDFITS, ASCII and CLASS format for processing within GILDAS and SPECX. A Cookbook, Tutorials and further information on ASAP is located here.
In this example, observations at 22GHz are done in Position Switching Mode, where the source
and a referenced position (free of line emission) are observed in sequence. The script below
is saved into a file (called proc.py) and run from within ASAP by typing execfile('proc.py') or
python -i proc.py from the command-line. It reads in and processes all *RCW49*.rpf files in
the current directory.
import glob
from asap import *
fnames = glob.glob('*RCW49*.rpf')
vec = []
for f in fnames:
vec.append(scantable(f,average=False))
quotients = []
for scan in vec:
scan.set_unit('km/s')
scan.set_freqframe('LSRK')
scan.average_pol() #comment out this line to display both pols
quotients.append(scan.auto_quotient())
for q in quotients:
msk = q.create_mask([-100,100])
q.poly_baseline(msk,0)
av = average_time(quotients)
iav = av.average_pol()
plotter.set_legend(mode=-1) # No legend
plotter.set_range(-100,100,-5,30)
plotter.plot(iav)
Figure 6.1: 22GHz Stokes I spectrum of RCW49.
In Beam–Switching or MX mode, each beam of the 20CM or 6GHz Multibeam receivers is placed in
turn on the source of interest. When not on-source, the other beams are still aquiring data
and so are used as reference data. In this example (taken from the P502 Methanol Multibeam
Survey), the RPFITS file contains two IFS; the first (IF0) contains the Methanol maser line at 6668MHz
and the second (IF1) contains Excited OH at 6035MHz. The IF selected depends on the index used
in selection.set_ifs(). This example only shows data associated with IF0.
The script file is shown below.
scans = scantable("2009-03-20_1025_MMB-MX-G300.96.rpf",average=False)
scans.set_selection()
selection = selector()
selection.set_ifs(0)
scans.set_selection(selection)
scans.set_unit('km/s')
scans.set_freqframe('LSRK')
q = scans.mx_quotient()
msk = q.create_mask([-55,-30])
q.poly_baseline(msk,0)
av = q.average_beam()
iav = q.average_pol()
plotter.set_range(-55,-20,-0.5,2)
plotter.plot(iav)
Figure 6.2: Stokes I 6668MHz Methanol spectrum for 300.96+1.14 .
It is possible to process Parkes data using MIRIAD. Initially, data is processed using LIVEDATA and GRIDZILLA, where the latter produces a FITS file which can be loaded into MIRIAD using the FITS utility. As an example, here we load in a GRIDZILLA–created FITS file and use the MIRIAD utility MBSPECT to display the profile of a galaxy, various parameters, plus create both an ASCII file of the spectra and a colour postscript file. The basic script below allows one to copy and past the code into a file (making it executable) for displaying a large number of sources quickly; it assumes the BASENAME utility is available on your system.
#!/bin/sh
if [ $# -lt 1 ]; then
echo "Please supply a FITS file"
exit 0
fi
FILE=$1
BASE=`basename ${FILE} .fits` #change suffix if different!
OPT="options=measure"
MSK="mask=4950,5450"
if [ -d "${BASE}.mir" ]; then #remove existing image if present
rm -rf ${BASE}.mir
fi
fits in=${BASE}.fits op=xyin out=${BASE}.mir
puthd in=${BASE}.mir/restfreq value=1.42040572 #insert rest freq of line
mbspect in=${BASE}.mir xaxis=optical hann=2 order=-3 ${OPT}
${MSK} device=/xs log=${BASE}.spec
mbspect in=${BASE}.mir xaxis=optical hann=2 order=-3 ${OPT}
${MSK} device=${BASE}.ps/cps
Running this script produces the following output and image.
#FR Clipped rms: 0.0066 Jy
#FN ( 654 out of 1024 channels)
# SPECTRAL FITTING
#MC xaxis: optical
#MX Maximum: 0.050 Jy at 5065.440 km/s
#MN Minimum: -0.028 Jy at 6141.707 km/s
#NP Number of spectral points: 1024
#SN1 Peak S/N ratio = 7.57
#CL Clipping inside range ( 0.000, 0.000) Jy
Moment: 0 1 2
#MM 9.660 5215.471 101.712
#SN2 Mean S/N ratio = 0.83
Robust moments: 0 1 2
#MR 9.744 5197.634 104.134
units: Jy km/s km/s km/s
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Figure 6.3: Spectrum of a galaxy using the MBSPECT utility of MIRIAD
For information on keywords used in the above script, please refer to the MIRIAD user guide.
Although MIRIAD has utilities to perform gaussian-fits to spectra, you can import the ASCII file created from MBSPECT (using log=file) into ASAP. For example, place the following code into the asapuserfuncs.py file (located in your $HOME/.asap directory).
def readxy(filename=None):
f = file(filename,'r')
x = []
y = []
lines = f.readlines()
f.close()
for l in lines:
vals = l.split()
x.append(float(vals[0]))
y.append(float(vals[1]))
return x,y
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Now when you run ASAP, you read in the ASCII file (with comments removed and only two columns) and fit a two–component gaussian and output a Postscript file of the plot as follows.
x,y = readxy('fred')
f = fitter()
f.set_data(x,y)
f.set_function(gauss=2)
f.fit()
f.get_parameters()
f.plot(components=[-1,0,1])
f._p.set_axes('xlabel','velocity km/s (LSR-K)')
f._p.set_axes('ylabel','Y-label')
f._p.set_axes('title','Title')
f._p.save('fred.eps')
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ASAP has the functionality to identify spectral lines within a data cube using LINEFINDER. Similarly, the DUCHAMP utility can also search for spectral-line sources, produce source lists, spectra and moment maps. Users are encouraged to view the online documentation for these.
A list of supported and non-supported data-reduction software can be found at the ATNF website.
The site has DLT IV, SuperDLT and DLT-S4 drives. Magnetic tapes are available at cost price.
Since some projects obtain very large datasets, it will be more convenient to take your files away on a portable hard drive than on multiple DVDs. To get your files onto your portable drive, you may use any of the PCs in the observers area by following the steps:
df |grep media to check whether it has mounted.
cp /nfs/PKCCC3_4/*P345* .
to copy all project P345 data.
Do not transfer files directly from correlator machines! Please use the following NFS mount points as provided on all Linux machines in the control room:
Correlator Machine NFS mount Multibeam pkccc1 /nfs/PKCCC1_1 DFB3(P) pkccc3 /nfs/PKCCC3_1 and /nfs/PKCCC3_2 DFB3(S) pkccc3 /nfs/PKCCC3_4 DFB4(P) pkccc4 /nfs/PKCCC4_1 DFB4(S) pkccc4 /nfs/PKCCC4_2 |
Table 6.1
An (S) above denotes spectral-line (non-pulsar) data and a (P) denotes pulsar-only data.
You can also copy your data to your laptop in a similar fashion to that described in Portable Storage. When your laptop is plugged in to a pink cable, you may access LAGAVULIN, so you can copy your data with the command:
scp username@lagavulin:/nfs/PKCCC3_4/*P345* .
which would copy all project P345 data, and where username is your ATNF username.
Usually observers copy their spectral-line data from the correlators to their own laptops or mass-storage devices (see above). Normally local operations staff will operate the archiver to create a hardcopy for the Observatory archives, but it is possible for observers to take away a hardcopy of their data if required.
The harware associated with the archiving system comprises a Rimage 2000i desktop publisher system with dual CD/DVD writers and a Rimage 400i inkjet printer connected to a Dell Optiplex 760 running Windows XP (MIMOSA-PA). The archiver station is located on the second-level control room opposite the CPSR2 racks.
When using PKARC, you are requested to supply one copy of each data DVD you produce for the Observatory archives. To enable the archiver, you will need to make sure the following applications are running (see image below):
These are usually up and running, but if not, simply double-click on their icons on the desktop to start up.
Figure 6.4: GUIs on the archiver station required for DVD-R production.
To begin archiving data, follow the procedure below.
If a directory was created for you in /DATA on the Linux/Unix system, please backup and delete this data BEFORE you leave. Otherwise, it will be deleted at any time after you leave to make room for other observers.
At the end of your run, we request you fill in an Observers Report to help us make the Observatory a better place to work and play. The form is found here. The completed form is distributed with your name visible to a selected list of Observatory staff whom are listed via a link on the above form.
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