The Cannon is a data-driven approach to stellar label determination.

Installation

Build status Coverage status License

The code can be installed using the following terminal commands:

pip install https://github.com/andycasey/AnniesLasso/archive/master.zip

(This will be on the PyPI repository when stable)

Basic Usage

[Some example code that grabs the Ness et al. 2015 data in the right format.]

Now let's build a model and train it up:

License & Attribution

This code is released under a modified MIT license. If you use this code for scientific research then you must cite the following papers:

The BibTeX and bibstem entries for these papers are given below for your convenience. 

@ARTICLE{2015ApJ...808...16N,
   author = {{Ness}, M. and {Hogg}, D.~W. and {Rix}, H.-W. and {Ho}, A.~Y.~Q. and 
  {Zasowski}, G.},
    title = "{The Cannon: A Data-driven Approach to Stellar Label Determination}",
  journal = {\apj},
archivePrefix = "arXiv",
   eprint = {1501.07604},
 primaryClass = "astro-ph.SR",
 keywords = {methods: data analysis, methods: statistical, stars: abundances, stars: fundamental parameters, surveys, techniques: spectroscopic},
     year = 2015,
    month = jul,
   volume = 808,
      eid = {16},
    pages = {16},
      doi = {10.1088/0004-637X/808/1/16},
   adsurl = {http://adsabs.harvard.edu/abs/2015ApJ...808...16N},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

% Bibstem:
%\bibitem[Ness et al.(2015)]{2015ApJ...808...16N} Ness, M., Hogg, D.~W., 
%Rix, H.-W., Ho, A.~Y.~Q., \& Zasowski, G.\ 2015, \apj, 808, 16

If you are interested in reviewing or citing other papers using The Cannon, please view the publications page.