MODS Basic 2D CCD Reduction Programs
modsCCDRed is a collection of Python programs to perform basic 2D reduction (bias, trim, flat field, and bad column fixing) on raw MODS CCD data.
The modsCCDRed Python programs have been tested on Linux (CentOS 5 to 7) and Mac OS X (v10.7 Lion thru 10.13 HighSierra) operating systems.
Python 2.5 or later is required, and the programs have been used primarily with Python versions 2.7 for the past year. We have adopted the free Anaconda Python for development of these program as it has proven to be the most trouble free distribution across Linux and Mac platforms, and we are becoming more invested in astropy across the profession for utilities like this.
NOTE: These programs might run under Python 3 but I would not bet on it. This version was better about print and expect syntax and tries to keep things simple.
If you do not use anaconda python, you will need to load and install the numpy and astropy modules before you can use modsCCDRed.
Your computer should have at least 4 Gb of memory in order to be able to perform the image median stacking steps, but otherwise the programs work with single images, but more is better. Runtime performance will depend on memory and processor speed, and is somewhat I/O limited given the large (24 Mpixel) images involved. On an older 2-processor 2.8GHz Pentium 4 computer with 8Gb of RAM running CentOS 5.8, the time required to bias, flat-field, bad column fix and axis flip a single full-frame unbinned 8x3K MODS red-channel spectrum is about 13 seconds.
The database/ subdirectory includes a set of default bad pixel list (bpl) files for the MODS CCDs.
The last version of the manual is in modsCCDRed.pdf, but it predates the upload to github, so beware.
You have two options: Personal or Public installation
For a personal installation, you have two ways to install the files to use:
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Keep the modsCCDRed Python programs in place, and put the modsCCDRed directory in your default execution path.
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Copy the executable Python programs into your ~/bin/ or ~/programs/ directory where you put executables in your default execution path.
For a public installation, e.g., on a central disk to share one copy of the package among many users, we suggest logging in as root and unpacking the tarball in your usual place for public add-on programs, e.g., /usr/local/, and then installing the executables in, e.g., /usr/local/bin/.
To use the default bad pixel lists, users need to define this environment variable
setenv MODS_DBDIR /usr/local/LBT/modsCCDRed/database/
for a csh/tcsh shells with a public installation where the source code lives in /usr/local/LBT/. Other shells (e.g., bash) use a different syntax.
Users can always override the default bad pixel list used with one of these methods:
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Redefining the MODS_DBDIR environment variable to point to the directory with their personal copies of bpl files with the same names (e.g., mods1r.bpl).
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Undefining MODS_DBDIR, at which point the modsCCDRed programs default to the current working directory (./), and look for the standard names.
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Using the -l flag with no path to use a custom file in MODS_DBDIR (or ./ if undefined), e.g., "modsFixPixl -l mym1r.bpl"
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Using the -l flag to give the full path and name of a particular bad pixel list file to use, e.g., "modsFixPix -l /my/path/to/mym1r.bpl"
There is no requirement of using the MODS_DBDIR environment variable, but care should be taken to avoid having multiple, possibly conflicting versions of bad pixel lists spread through many directories.
This is the last Python 2.7 version. The next revision will be Python 3 compatible, committed after thorough testing.
If your research used modsCCDRed, we ask that you follow emerging software citation principles being adopted by the astronomical community to ensure the proper citation of software in scientific publications.
If you publish MODS data reduced with the modsCCDRed, we ask that you add this line to the acknowledgments section of your paper:
This paper made use of the modsCCDRed data reduction code developed in part with funds provided by NSF Grants
AST-9987045 and AST-1108693.
modsCCDRed was developed for the MODS1 and MODS2 instruments at the Large Binocular Telescope Observatory, which were built with major support provided by grants from the U.S. National Science Foundation's Division of Astronomical Sciences Advanced Technologies and Instrumentation (AST-9987045), the NSF/NOAO TSIP Program, and matching funds provided by the Ohio State University Office of Research and the Ohio Board of Regents. Additional support for modsCCDRed was provided by NSF Grant AST-1108693.
- 2019 Apr 19 - v2.0.5 - bug fixes
- Fixed problems found in Python 2 to Python 3 conversion that will cause problems with some Python 2.7 distros
- 2018 Oct 24 - v2.0.4 - bug fixes
- Fixed stupid errors in modsBias.py and modsFixPix.py
- 2017 May 21 - v2.0.3 - astropy patch
- A recent update to the astropy.io FITS module removed support for the .update() method for FITS headers, but a backwards-compatible syntax is available that works regardless of the astropy.io update. Too many cooks in astropy.io FITS of late ...
- 2016 Mar 09 - v2.0.1 - First Public Release
- Release of changes in modsPixFlat in general
- Adoption of astropy.io.fits for FITS handling with the announcement by STScI of end of support for PyFITS (with the wholesale move of PyFITS development to AstroPy, so we're just moving with it).
- Suppression of nuisance FITS warnings, mostly because the AstroPy FITS implementation went a more orthodox route regarding FITS compliance than PyFITS.
- Many small changes fixing bugs and responding to user requests.
- Fixes an issues with astropy v1.1.0 and later in that in reading integer FITS the fits.open() function now defaults to retaining integer format instead of the desired (old) default behavior of converting to floats.
modsCCDRed was written by Rick Pogge, The Ohio State University Department of Astronomy (pogge.1@osu.edu), including bias correction programs developed for OSMOS by Paul Martini (OSU Astronomy).