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Unstable Releases

  • v1.13_comm : Commissioning release for GMOS-S Hamamatsu CCDs.

    Release Date: July 22, 2014
    Expires on: TBD

    FOR USE ONLY ON GMOS-S HAMAMATSU CCDs DATA. (Until expiry date.)

    Quick installation instructions:
    • % mkdir gemini_v113_comm
    • % cd gemini_v113_comm
    • % tar xvzf gemini_v113_comm_iraf.tar.gz
    • % cd ~/iraf
    • % vi
    • Add these lines and save:
         reset gemini=/your/path/to/gemini_v113_comm/
         task gemini.pkg=gemini$
    • % cd ~/iraf
    • % cl
    • ecl> gemini
      Check that the correct version is being loaded: v1.13_comm, July 22, 2014

    Run the Python script on the data you downloaded before doing anything with the data. You will need Python and pyfits or astropy. If you are using Ureka, you are good to go.
    • % --files="*.fits" --destination=/path/to/fixed_outputs/

    This "commissioning" release of the Gemini IRAF data reduction package is being made available to assist in the reduction of the Hamamatsu data.

    WARNING: This package is NOT fully vetted, and it is still, like the instrument, being commissioned. Unless you know exactly what you are doing and your program objectives allow it, do NOT use this package to draw scientific- quality measurements.

    WARNING: DO NOT USE for anything but GMOS-S Hamamatsu CCD data. If you wish to reduce other types of Gemini data, please use the stable release, v1.12. It can be downloaded as a tar file from our website, or if you are using Ureka (>v1.0), that is the version already packaged in it.

    Please read the release note (gemini_v113_comm.txt) included in the package's tar file.

    Here is a summary of the known remaining issues.

    Step 1 is to run the script "" on the datasets. Some critical header keywords are assigned wrong values. If you do not run this script, the Gemini IRAF package will not work properly.

    You will need Python and either the "pyfits" or "astropy" module installed. If you are using Ureka, you already have everything you need.

    To run the script:
    % --files="*.fits" --destination=/path/to/fixed_outputs/

    Gains and full well:
    The values used in the package are not the final values but they should be very close to the them.

    Read noise:
    The values used in the package for read noise are from lab measurements, before the CCDs went on sky.

    Bad Pixel Masks (BPMs):
    The BPMs are NOT available at this time for the GMOS-S Hamamatsu data.

    Quantum Efficiency (QE):
    The coefficients to correct for variations in QE with wavelength and across the chips have NOT been calculated yet. QE correction is effectively NOT AVAILABLE at this time.

    The default values for the overscan fitting and correction are NOT ADEQUATE. You will have to fit the overscan section in INTERACTIVE mode (fl_inter, inter, or ovs_flinter, parameter depending on the task), or inspect the overscan section ahead of time to find the appropriate fit parameters. See the release note (gemini_v113_comm.txt) for a list of the parameters related to overscan fitting.

    We are working on finding the best defaults to avoid having you do all this work, but that investigation is not completed yet.

    Example scripts:
    The examples in the Gemini IRAF package should work fine with the new data. The reduction steps are the same as with the old data. BUT DO REMEMBER to run the "" script BEFORE you run any IRAF script. (The examples are located in gmos$doc/ and can be accessed with the "gmosexamples" task.)

    Getting Help:
    To get help with this commissioning package, please file a HelpDesk ticket under the "Gemini IRAF" category and request that the ticket be elevated to Tier 2 (Gemini staff) right away. This will ensure that the request gets to our developers. The Tier 1 NGOs are not currently in a position to help you with this commissioning data reduction package.

    On behalf of the Data Processing Software Group, good luck! and please do let us know how the package behaves. Remember, this is still under development and we are providing the software early to help with your with quick-look assessment of your data. A beta and/or stable release will be issued in a few weeks.