Hi,
I reduced gmos (mos mode) data following the example included in the Gemini package and I have some questions about the results I get.
After gsextract one could expect to get 1-d spectra in the resulting image.
In other words, if you do imhead image.fits[SCI,1] you would expect to get something like:
image.fits[SCI,1][3108,1][real]
that is a 1-d spectrum for each science object.
However, I get:
image.fits[SCI,2][3108,1,3][real]: 1032
which means 3 1-d spectra!
Moreover, if I splot image.fits[SCI,1], the routine asks the image band to plot,
and I see different scales (on Y) depending the band I choose.
Can anybody tell me what are these 3 spectra?
thanks
charly
Joined: 14 Apr 2010 Posts: 58 Location: IATE - Observatorio Astronomico Cordoba - Argentina
Posted: Thu Aug 04, 2011 1:32 pm Post subject:
Hi Emma,
thanks for your answer once again.
Please see below parameters used for gsextract and the result of fxhead
for one of the gsextracted images.
Let me know if you need any other information.
regards
charly
inimages = "stgsS0069.fits" Input images
(outimages = " ") Output images
(outprefix = "e") Output prefix
(refimages = "") Reference images for tracing apertures
(apwidth = 2.) Extraction aperture in arcsec (diameter)
(fl_inter = yes) Run interactively?
(find = yes) Define apertures automatically?
(recenter = yes) Recenter apertures?
(trace = yes) Trace apertures?
(tfunction = "chebyshev") Trace fitting function
(torder = 3) Trace fitting function order
(tnsum = 20) Number of dispersion lines to sum for trace
(tstep = 20) Tracing step
(weights = "variance") Extraction weights (none|variance)\n
(clean = yes) Detect and replace bad pixels?
(lsigma = 3.) Lower rejection threshold for cleaning
(usigma = 3.) Upper rejection threshold for cleaning\n
(background = "none") Background subtraction method
(bfunction = "chebyshev") Background function
(border = 1) Order of background fit
(long_bsample = "-200:-100, 100:200") LONGSLIT: backgr sample regions, WRT aperture
(mos_bsample = 0.5) MOS: fraction of slit length to use (bkg+obj)
(bnaverage = -10) Number of samples to average over
(bniterate = 2) Number of rejection iterations
(blow_reject = 2.5) Background lower rejection sigma
(bhigh_reject = 2.5) Background upper rejection sigma
(bgrow = 0.) Background rejection growing radius (pix)\n
(fl_vardq = no) Propagate VAR/DQ planes? (if yes, must use variance weighting)
(sci_ext = "SCI") Name of science extension
(var_ext = "VAR") Name of variance extension
(dq_ext = "DQ") Name of data quality extension
(key_ron = "RDNOISE") Keyword for readout noise in e-
(key_gain = "GAIN") Keyword for gain in electrons/ADU
(ron = 3.5) Default readout noise rms in electrons
(gain = 2.2) Default gain in e-/ADU
(logfile = "") Logfile
(verbose = yes) Verbose?
(status = 0) Exit status (0=good)
(scanfile = "") Internal use
(mode = "ql")
Thank you for the information. The extra planes are actually created by apall because you set the "weights" parameter to "variance". If you look in the header of the science extensions you should see some keywords like:
These keywords tell you what each plane in each science extension means. So, the first plane in the first science extension [SCI,1] (i.e., 3108x1x1) contains your extracted spectrum that has been cleaned and weighted by the variance. The second plane in the first science extension (i.e., 3108x1x2) contains the raw extracted spectrum that hasn't been cleaned or weighted by the variance. The third plane in the first science extension (i.e., 3108x1x3) contains the sigma. You can view each of these spectra by using:
You can read more about apall and weighted extractions by looking at the following help files:
Code:
cl> help apall
cl> help apsum
cl> help apvariance
If you decide that you don't want to do a weighted extraction, you will need to set the "weights" parameter to "none" and the "clean" parameter to "no" (since if the "clean" parameter is set to "yes", the "weights" parameter is set to "variance" automatically). If you do this, your output will contain a one dimensional spectrum for each slit provided to the task as expected.
I hope that helps. Please let me know if you have any more questions.
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