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saga-code

Code for the SAGA survey.

How this code is organized

The basic structure is based on .py files and directories, named after either observatories or tasks. For example, the hosts.py file defines data structures and functions for the SAGA hosts, including downloading SDSS catalogs of their environs. The targeting.py file contains the code for selecting targets from those catalogs. The magellan.py, mmthecto.py, and wiyn.py files all contain code to assist in generating configurations/masks for the respective instruments.

These codes are each designed to place their outputs in appropriate directories. For example, wiyn.py always places configuration files for HYDRA in the wiyn_targets directory, and similar for magellan.py and the imacs_targets directory. hosts.py and targeting.py use the catalogs directory, which will automatically be created if not present when an SDSS catalog download is requested.

How to use the code

For detailed instructions on the various pieces, see the *.py file comments and docstrings. In general, though, they are intended to be used with ipython notebooks, so that we can keep a record of how targets are selected, objects are analyzed, etc.

The prerequesites are:

  • Python (2.7+), numpy, scipy, and matplotlib - these can usually be installed with a package manager if you have one, but if you're not sure, google (or asking someone like Erik) will generally get you the necessary installation functions.
  • Astropy - the front page of the web site has [detailed install instructions.
  • IPython - you'll need a version that supports html [notebooks to follow the instructions below. I think that means v0.13 or [later, but your best bet is just the latest (v2.0).

If you have already downloaded the NSA catalog, you might want to symlink it to the saga directory (with the default name: nsa_v0_1_2.fits). The code will automatically download it, but it's a pretty big file, so you probably don't want more than one.

Once you've got everything, you can cd into the ipython_notebooks directory, and start ipython as ipython notebook --matplotlib=inline. You can then either run pre-existing notebooks, or create new ones if you're preparing for a new observing run or doing some new analysis task.

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