Metadata-Version: 2.1
Name: astrostarfish
Version: 0.3.0.dev0
Summary: Covariance tools for fitting stellar spectra
Home-page: https://github.com/iancze/Starfish
Author: Ian Czekala
Author-email: iczekala@berkeley.edu
Maintainer: Ian Czekala
Maintainer-email: iancze@gmail.com
License: BSD
Download-URL: https://github.com/iancze/Starfish/archive/master.zip
Description: # Starfish
        
        [![Build Status](https://travis-ci.org/iancze/Starfish.svg)](https://travis-ci.org/iancze/Starfish)
        [![Doc Status](https://img.shields.io/readthedocs/starfish/latest.svg)](https://starfish.readthedocs.io/en/latest/?badge=latest)
        [![Coverage Status](https://coveralls.io/repos/github/iancze/Starfish/badge.svg?branch=master)](https://coveralls.io/github/iancze/Starfish?branch=master)
        [![PyPi](https://img.shields.io/pypi/v/astrostarfish.svg)](https://pypi.org/project/astrostarfish/)
        [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2221006.svg)](https://doi.org/10.5281/zenodo.2221006)
        
        *Starfish* is a set of tools used for spectroscopic inference. We designed the package to robustly determine stellar parameters using high resolution spectral models.
        
        ## Beta Version 0.3
        
        ### Documentation
        
        [![Doc Status](https://img.shields.io/readthedocs/starfish/latest.svg?label=latest)](https://starfish.readthedocs.io/en/latest/?badge=latest)
        [![Doc Status](https://img.shields.io/readthedocs/starfish/latest.svg?label=develop)](https://starfish.readthedocs.io/en/develop/?badge=develop)
        
        ### Citations
        
        If you use this code or derivative components of this code in your research, please cite our [paper](https://ui.adsabs.harvard.edu/abs/2015ApJ...812..128C/abstract) as well as the [code](https://doi.org/10.5281/zenodo.2221006). 
        
        <details>
        <summary>BibTex citation</summary>
        
        ```
        @ARTICLE{2015ApJ...812..128C,
               author = {{Czekala}, Ian and {Andrews}, Sean M. and {Mandel}, Kaisey S. and
                 {Hogg}, David W. and {Green}, Gregory M.},
                title = "{Constructing a Flexible Likelihood Function for Spectroscopic Inference}",
              journal = {\apj},
             keywords = {methods: data analysis, methods: statistical, stars: fundamental parameters, stars: late-type, stars: statistics, techniques: spectroscopic, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
                 year = "2015",
                month = "Oct",
               volume = {812},
               number = {2},
                  eid = {128},
                pages = {128},
                  doi = {10.1088/0004-637X/812/2/128},
        archivePrefix = {arXiv},
               eprint = {1412.5177},
         primaryClass = {astro-ph.SR},
               adsurl = {https://ui.adsabs.harvard.edu/abs/2015ApJ...812..128C},
              adsnote = {Provided by the SAO/NASA Astrophysics Data System}
        }
        
        @misc{ian_czekala_2018_2221006,
          author       = {Ian Czekala and
                          gully and
                          Kevin Gullikson and
                          Sean Andrews and
                          Jason Neal and
                          Miles Lucas and
                          Kevin Hardegree-Ullman and
                          Meredith Rawls and
                          Edward Betts},
          title        = {{iancze/Starfish: ca. Czekala et al. 2015 release 
                           w/ Zenodo}},
          month        = dec,
          year         = 2018,
          doi          = {10.5281/zenodo.2221006},
          url          = {https://doi.org/10.5281/zenodo.2221006}
        }
        ```
        
        </details>
        
        **Warning!**
        
        There have been major updates since version `0.2`, please see the section of the documentation that regards these changes if you are used to the old version!
        
        ### Papers
        * [Czekala et al. 2015](https://ui.adsabs.harvard.edu/#abs/2015ApJ...812..128C/abstract)
        * [Gully-Santiago et al. 2017](https://ui.adsabs.harvard.edu/#abs/2017ApJ...836..200G/abstract)
        
        Copyright Ian Czekala and collaborators 2013 - 2019 (see [`CONTRIBUTORS.md`](CONTRIBUTORS.md))
        
        Please bear in mind that this package is under heavy development and features may evolve rapidly. If something doesn't work, please fill an [issue](https://github.com/iancze/Starfish/issues) on this repository. If you would like to contribute to this project (either with bugfixes, documentation, or new features) please feel free to fork the repository and submit a pull request!
        
        # Installation Instructions
        
        ## Prerequisites
        
        *Starfish* has several dependencies, however most of them should be satisfied by an up-to-date scientific python installation. We highly recommend using the [Anaconda Scientific Python Distribution](https://store.continuum.io/cshop/anaconda/) and updating to 
        Python 3.6 or greater. This code makes no attempt to work on the Python 2.x series, and I doubt it will if you try. This package is tested across Linux, Mac OS X, and Windows. 
        
        To make sure you are running the correct version of python, start a python interpreter via the system shell and you should see something similar
        
            $ python
            Python 3.6.1 |Anaconda custom (64-bit)| (default, May 11 2017, 13:25:24) [MSC v.1900 64 bit (AMD64)] on win32
            Type "help", "copyright", "credits" or "license" for more information.
            >>> 
        
        If your shell says Python 2.x, try using the `python3` command instead of `python`.
        
        ## Installation
        
        For the most current release of *Starfish*, use the releases from PyPI
        
            $ pip install astrostarfish
        
        If you want to be on the most up-to-date version (or a development version), install from source via
        
            $ pip install git+https://github.com/iancze/Starfish.git#egg=astrostarfish
        
        
        To test that you've properly installed *Starfish*, try doing the following inside of a Python interpreter session
        
        ```python
        >>> import Starfish
        >>> Starfish.__version__
        '0.3.0'
        ```
        
        If you see any errors, then something went wrong--please file an [issue](https://github.com/iancze/Starfish/issues).
        
        Now that you've successfully installed the code, please see the [documentation](https://starfish.readthedocs.io/en/latest/) on how to begin using *Starfish* to solve your spectroscopic inference problem.
        
        # Contributing
        If you are interested in contributing to *Starfish*, first off, thank you! We appreciate your time and effort into
        making our project better. To get set up in a development environment, it is highly recommended to develop in a
        virtual environment. We use `pipenv` to manage our environments, to get started clone the repository (and we recommend forking us first)
        
            $ git clone https://github.com/<your_fork>/Starfish.git starfish
            $ cd starfish
        
        and then create the virtual environment and install pacakges from the `Pipfile` with
        
            $ pipenv install -d
        
        and to enter the virtual environment, simply issue
        
            $ pipenv shell
        
        whenever you're in the `starfish` folder.
        
        Take a look through the [issues](https://github.com/iancze/Starfish/issues) if you are looking for a place to start improving *Starfish*!
        
        **Tests**
        
        We use `py.test` for testing; within the virtual environment
        
            $ pytest
        
        
        ## Contributors
        
        See [`CONTRIBUTORS.md`](CONTRIBUTORS.md) for a full list of contributors.
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Description-Content-Type: text/markdown
