Nifty4NIFS 1.0b4

The Gemini NIFS data reduction pipeline.

Nifty

Now in Beta status! Please let us know of any bugs you find on the issues page.

A Python Data Reduction Pipeline for the Gemini-North Near-Infrared Integral Field Spectrometer (NIFS).

Full documentation: ReadTheDocs.

This is a new data reduction Python pipeline that uses Astroconda and the Gemini IRAF Package to reduce NIFS data. It offers a complete data reduction process from sorting the data to producing a final flux calibrated and wavelength calibrated combined cube with the full S/N for a science target.

This pipeline is open source but is not supported by Gemini Observatory.

Any feedback and comments ([e-mail]) are welcome!

Copyright

For more details, please read the LICENSE.

How to Submit Bugs and Requests

Very important: do not submit a Gemini help desk ticket!

If you want to report a problem, use the Gemini Data Reduction Forum thread or create an issue in this repo.

Installation

Pre-Requisites

Make sure you have the latest version of Gemini Astroconda installed, have activated an Astroconda environment and have set up PYRAF. You can find instructions for installing Astroconda here. PYRAF can be set up by running the mkiraf command in your “~/iraf” directory.

Installing

>From PyPi.org:

pip install Nifty4NIFS

Installing in Editable Mode

If you want to edit the Nifty source code, it’s recommended to install Nifty in editable Mode. First obtain the Nifty source code. You can do this by downloading and unpacking the latest release or cloning this github repository.

Once you have the source code, change to the top level of the source code directory (you should see the setup.py file). Run:

pip install -e .

to 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.

Quick Start

To run Nifty, getting data reduction parameters from an interactive input session:

runNifty linearPipeline -i

To run Nifty in full-automatic mode with default input parameters, provide the -f flag and a full local path to the raw data or a Gemini Program ID string (Eg: GN-2013A-Q-62).

runNifty linearPipeline -f <data_location>