Metadata-Version: 2.1
Name: stark-package
Version: 0.4.0
Summary: Spectral exTraction And Reduction Kit
Home-page: https://github.com/Jayshil/stark
Author: Jayshil A. Patel, Alexis Brandeker, Gayathri Viswanath, Maria Cavallius, Markus Janson
Author-email: jayshil.patel@astro.su.se
License: Apache Software License 2.0
Requires-Python: >=3.7
License-File: licenses/LICENSE.rst
Requires-Dist: numpy
Requires-Dist: astropy
Requires-Dist: scipy
Provides-Extra: all
Provides-Extra: test
Requires-Dist: pytest; extra == "test"
Requires-Dist: pytest-doctestplus; extra == "test"
Requires-Dist: pytest-cov; extra == "test"
Provides-Extra: docs
Requires-Dist: sphinx; extra == "docs"
Requires-Dist: sphinx-automodapi; extra == "docs"

Spectral exTraction And Reduction Kit
-------------------------------------

Spectral exTraction And Reduction Kit, or :code:`stark`, is written with the aim to provide a general purpose tool for optimal extraction of spectrum from the raw (or, reduced) data with special attention towards JWST data.
The concept of the code was originally developed by Alexis Brandeker and initial versions are implemented by Marcus Karlsson and Erwan Taillanter.
Later, the code was adapted to process UVES data by Gayathri Viswanath and Maria Cavallius with valuable help from Markus Janson.
The current version of the original code is developed with keeping in mind analysis of JWST (NIRCam) data.

License
-------

This project is Copyright (c) Jayshil A. Patel, Alexis Brandeker, Gayathri Viswanath, Maria Cavallius and Markus Janson and licensed under
the terms of the Apache Software License 2.0 license. This package is based upon
the `Openastronomy packaging guide <https://github.com/OpenAstronomy/packaging-guide>`_
which is licensed under the BSD 3-clause licence. See the licenses folder for
more information.


Contributing
------------

We love contributions! :code:`stark` is open source,
built on open source, and we'd love to have you hang out in our community.

..
    **Imposter syndrome disclaimer**: We want your help. No, really.


    There may be a little voice inside your head that is telling you that you're not
    ready to be an open source contributor; that your skills aren't nearly good
    enough to contribute. What could you possibly offer a project like this one?

    We assure you - the little voice in your head is wrong. If you can write code at
    all, you can contribute code to open source. Contributing to open source
    projects is a fantastic way to advance one's coding skills. Writing perfect code
    isn't the measure of a good developer (that would disqualify all of us!); it's
    trying to create something, making mistakes, and learning from those
    mistakes. That's how we all improve, and we are happy to help others learn.

    Being an open source contributor doesn't just mean writing code, either. You can
    help out by writing documentation, tests, or even giving feedback about the
    project (and yes - that includes giving feedback about the contribution
    process). Some of these contributions may be the most valuable to the project as
    a whole, because you're coming to the project with fresh eyes, so you can see
    the errors and assumptions that seasoned contributors have glossed over.

    Note: This disclaimer was originally written by
    `Adrienne Lowe <https://github.com/adriennefriend>`_ for a
    `PyCon talk <https://www.youtube.com/watch?v=6Uj746j9Heo>`_, and was adapted by
    stark based on its use in the README file for the
    `MetPy project <https://github.com/Unidata/MetPy>`_.
