The coaddition service builds coadded images from the public release of the Palomar-Quest survey. This is a synoptic (repeating) survey, so that any given point on the sky may have been imaged multiple times, with each pass labelled by the date of the observation.
Images are projected onto one of the map projections ("pages") of the hyperatlas standard, which has standard page centers, projection type, and scale. More information about hyperatlas is available here. This service is using by default the TM-5-TAN-20 atlas, meaning a collection of 1734 pages, so any point is within 4 degrees of a plate center, and a scale of one arc-second per pixel.
It should be noted that this service works only within the public data release area, 120 < RA < 240, and 11 < Dec < 20.
The arguments that are sent to the service include:
-ra: the right ascension of the center of the requested coadd, in degrees. As noted above, this value should be between 120 and 240.
-dec: the declination of the center of the requested coadd image, in degrees. As noted above this value should be between 11 and 20.
-rawidth and -decwidth may be used to specify the size in degrees of the resulting coadded image. You can specify either naxis1/naxis2 OR rawidth/decwidth.
As an alternate to the explicit sky coordinates (ra, dec, rawidth, decwidth), the user may specify page, tilex, tilex, which refer to hyperatlas pages and tiles on those pages. The page number runs from 1 to 1734, and each of tile-x amd tile-y runs from -2 to +2.
-dates: a Python regular expression defining which observation dates to include. Dates are expressed as a string YYYYMMDD, for example 20060518. The regular expression ".*" matches all dates, and is the default. The regex "2003*" would catch all observations from 2003.
-bandpass: The PQ survey uses two sets of filters, both Johnson (JR, JI, JB) and Gunn (gr, gi, z1, z2).
Below is a Python program that can be used to drive the cutout service. First we find the file that contains the list of positions, then build the argument list that contains the desired surveys.
import time
import sys
import nesssi_client as nesssi
# Create a connection
# This uses a proxy certificate , or a key/cert pair from $HOME/.globus if a
# proxy can't be found
nesssiServer=nesssi.client('https://envoy.cacr.caltech.edu:8443/clarens/',debug=0)
# Initialize the service
sessionID = nesssiServer.hyperatlas.init()
print "Session id is ", sessionID
# Arguments for service, the coaddition to do
args = "-bandpass JR -ra 150 -dec 15 -rawidth 0.5 -decwidth 0.5"
# Run service
nesssiServer.hyperatlas.run(sessionID, args)
# Monitor every minute for 5 minutes
for i in range(1,5):
msg = nesssiServer.hyperatlas.monitor(sessionID)
print msg
print "sleeping ............"
time.sleep(60)
Part of the response from the monitor service is a URL, and under that is diagnostic information and, eventually, the output FITS file, with the name "out.fits".