GMOS Long-slit Reductions: It's an ADVENTURE!

Some resources:

• The Cookbook.
• In IRAF/gemini/gmos do a "gmosexample longslit"
• But best: The turorials (which is what this is basically modeled on).

Installation

• Install the special-doesn't-work-with-normal-IRAF-gemini software:
  • Go to https://www.anaconda.com/download/#macos and download the installer for Python 3. Run the installer.
  • Open a terminal window and do a "bash -l".
  • which conda should return something
  • conda config --add channels conda-forge
  • conda config --add channels http://astroconda.gemini.edu/public
  • conda create -n geminiconda python=3.7.9 iraf-all pyraf-all ds9
  • cd
  • mkdir gemiraf
  • conda activate geminiconda
  • cd gemiraf
  • mkiraf
  • cl should invoke iraf; pyraf should invoke PyRAF, and python starts singing I'm a Lumberjack.
• To update:
  • conda activate geminiconda
  • conda install iraf.gemini=1.15 --no-update-deps
  • To use the CR rejection code:
  • Put this in the login.cl: task lacos_spec = /path/to/wherever/you/put/it/lacos_spec.cl and don't forget the keep.
• Subsequent times:
  • Starting up IRAF
    • Open an xgterm window
    • bash -l
    • conda activate geminiconda
    • which cl
    • cd wherever you created the login.cl and uparm
    • cl
    • gemini, gmos
  • When done, conda deactivate

Getting Sorted Out

• Download the data. Put all of the cals and science bais frames in a subdirectory called "Raw"
• Make an observing log. The difficulty is that some header words are in [0] and others are in [1]. This gets around this. Here's a handy script: makelogs.cl. It creates obsLog.txt and (unlike the manual) retains the keywords. I found it handy to then write down in a notebook what the pertinent frames were.
• Making lists--although you may not need to so skip this section for now.
  • The major issue is that because of all the MEF stuff it's hard to just make a list of file names. You could, of course, use ls *.fits > mylist and edit it using the log, but the following is a little easier:
    • Edit script biasSelect.cl. Creates bias.txt.
    • Edit script compSelect.cl Creates flat_F538.txt, arc_F538.txt, etc.
  • If you're dealing with a situation with only a few frames, you can easily deal with them as below and then do some editing.
    • files S*%.fits%% > arcs.txt
    • copy arcs.txt flats.txt
    • copy arcs.txt science.txt
  • You can also just do something like:
    • gemlist "S20150503S" "275-278,280 > bias.txt

  ---

  Everything all at once

• Why, yes, there is a script for doing everything Here's how it works:
  • set rawdir="Raw/"
  • Make master bias frame: gbias @bias22.txt Zero22 rawpath=rawdir$ fl_over+ fl_trim+ fl_inter-
  • If you have only a few frames, do things the easy way:
    • !echo S20210209S0047.fits > science
    • !echo S20210209S0048.fits > flat
    • !echoo S20210209S0049.fits > arc
  • Do the basic processing (overscan, trim, and bias subtraction). Note that some of the unnecessary flags (like fl_cut-) actually are needed because, well, bugs I guess.
    • #Flat
    • gsreduce @flat rawpath="rawdir$" fl_flat- fl_gmosaic- \
    • fl_cut- fl_gsappwave- bias="Zero22.fits"
    • #Science
    • gsreduce @science rawpath="rawdir$" fl_flat- fl_gmosaic- \
    • fl_cut- fl_gsappwave- bias="Zero22.fits"
    • #Arc. Mosaic it.
    • gsreduce @arc rawpath="rawdir$" fl_flat- fl_gmosaic+ fl_fixpix- \
    • fl_gsappwave- fl_over+ bias="Zero22.fits"
  • Do the wavelength solution on the mosaic'd arc:
    • gswavelength gs//@arc fl_inte+ fl_addf-
    • gstransform gs//@arc wavtran=gs//@arc
    • implot the resulting "t" frame and make sure everyting is nicely lined up.
  • Do the QE corrections for the flat and the science exposures. These aren't mosaic'd yet (makes sense!)
    • #QE the science exposure: gqe gs//@science ref=gs//@arc
    • #QE the flat: gqe gs//@flat ref=gs//@arc
  • Make the flat-field:
    • gmosaic qgs//@flat fl_fixpix+
    • gsflat mqgs//@flat FlatN.fits order=23 fl_over+
  • Reduce the science exposure, mosaic'ing it in the process: gsreduce qgs//@science flat="FlatN" fl_over- fl_bias- fl_trim-
  • Apply the wavelength calibration. Note the extra "gs" at the start that got added abover:gstransform gsqgs//@science wavtran=gs//@arc
  • Extract the spectrum and enjoy:
    • gsskysub tgsqgs//@science
    • gsextract stgsqgs//@science fl_inte+ clean+
    • imcopy e*.fits[sci] CD.fits
    • splot CD.fits

    So, that sounded good, right? And the above works, sort of, if you have a single science frame. But one of the unusual things about GMOS data is a 20 minute exposure is just DOMINATED by cosmic rays; you have to get rid of these before you can even find the aperture to do extract something faint.

    I'm also not that delighted with their sky subtraction algorithm.

    gemcombine works, if you didn't dither. But if you did, a good alternative seems to be gemcrspec. I used it on my data after I had transformed but not sky subtracted:

    • gemcrspec tgsqgs//@science c//@science
    • imcopy cS20210208S0005.fits[sci] t1 [etc]
    • There are some very saturated and/or bad pixels.
      • imreplace @NewList 5000 lower=5000
      • imreplace @NewList 0 upper=0
      • apall @NewList
      • scombine @NewList//.ms.fits
      • gemcombine tgsqgs//@science LMC0551a reject=ccdclip