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"Intended Audience :: Education",
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"License :: OSI Approved :: MIT License",
"Operating System :: MacOS",
"Programming Language :: Python :: 2.7",
"Topic :: Scientific/Engineering :: Astronomy",
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"description": "Nifty\n=====\n\n.. image:: https://zenodo.org/badge/93109208.svg\n :alt: DOI of the latest release. See releases.\n :target: https://zenodo.org/record/852696#.WaWmr5PyhMA\n.. image:: https://readthedocs.org/projects/newer-nifty/badge/?version=latest\n :alt: Nifty's documentation, hosted on ReadtheDocs.\n :target: http://newer-nifty.readthedocs.io/en/latest/\n.. image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat\n :alt: Nifty uses Astropy! Here is a link to the project webpage:\n :target: http://www.astropy.org/\n\n*Now in Beta status! Please let us know of any bugs you find on the issues page.*\n\nA Python Data Reduction Pipeline for the Gemini-North Near-Infrared Integral\nField Spectrometer (NIFS).\n\nFull documentation: `ReadTheDocs `_.\n\nThis is a new data reduction Python pipeline that uses Astroconda and the Gemini\nIRAF Package to reduce NIFS data. It offers a complete data reduction process from\nsorting the data to producing a final flux calibrated and wavelength calibrated\ncombined cube with the full S/N for a science target.\n\nThis pipeline is open source but is not supported by Gemini Observatory.\n\nAny feedback and comments (mbusserolle@gemini.edu) are welcome!\n\nCopyright\n---------\n\nFor more details, please read the LICENSE.\n\n\nHow to Submit Bugs and Requests\n-------------------------------\n\nVery important: **do not submit a Gemini help desk ticket!**\n\nIf you want to report a problem, use the `Gemini Data Reduction Forum thread `_\nor create an issue in this repo.\n\nInstallation\n============\n\nPre-Requisites\n--------------\nMake sure you have the latest version of Gemini Astroconda installed, have activated an Astroconda environment and have set up PYRAF.\nYou can find instructions for installing Astroconda `here `_. PYRAF can be set up by running the mkiraf command\nin your \"~/iraf\" directory.\n\nInstalling\n----------\n>From PyPi.org:\n\n.. code-block:: text\n\n pip install Nifty4NIFS\n\nInstalling in Editable Mode\n---------------------------\nIf you want to edit the Nifty source code, it's recommended to install Nifty in editable Mode. First obtain the Nifty source code. You\ncan do this by downloading and unpacking the latest release or cloning this github repository.\n\nOnce you have the source code, change to the top level of the source code directory (you should see the setup.py file). Run:\n\n.. code-block:: text\n\n pip install -e .\n\nto install Nifty in editable mode. Now you can edit your copy of the Nifty source code and run it without having to reinstall every time.\n\nQuick Start\n===========\n\nTo run Nifty, getting data reduction parameters from an interactive input session:\n\n.. code-block:: text\n\n runNifty nifsPipeline -i\n\nTo run Nifty in full-automatic mode with default input parameters, provide the -f flag\nand a full local path to the raw data or a Gemini Program ID string (Eg: GN-2013A-Q-62).\n\n.. code-block:: text\n\n runNifty nifsPipeline -f \n\n\n",
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