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Digitized Observatory Resources for Automated Data Operations

Project description

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DORADO

Digitized Observatory Resources for Automated Data Operations (DORADO) is a python based expansion of astropy (and affiliated packages) that aims to be a simple and common framework for data reduction tailored for life at the Allan I. Carswell Observatory at York university, Toronto, Ontario, Canada

☣⚠ Note: DORADO is in beta ⚠☣

DORADO is in beta and as such is highly experimental and still a work in progress. While still in active development DORADO may still be used and experimented with; but a stable channel will not be created until DORADO enters a beta phase in the future.

Use of DORADO while in beta will not result in any risk to your computer or hardware, but may affect stability of software that are written with DORADO or the quality of data that is produced using DORADO.

During the beta, documentation and code commenting may be subpar as many things will being changing regularly with new code being written and rewritten and in-line testing appearing temporarily.

Dependencies

Dorado aims to be as lightweight as possible and utilize as little dependencies as it can.

Currently DORADO relies on:

  1. numpy

  2. matplotlib

  3. astropy

  4. CCDPROC >> CCDprocX

  5. scipy

  6. photutils

  7. astroquery

  8. astroalign

  9. tqdm

  10. lightkurve

License

This project is Copyright (c) Mucephie and licensed under the terms of the BSD 3-Clause license. This package is based upon the Astropy package template which is licensed under the BSD 3-clause license. See the licenses folder for more information.

Contributing

We love contributions! dorado 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 for a PyCon talk, and was adapted by dorado based on its use in the README file for the MetPy project.

Contact

If you have any questions or would like to contribute to DORADO, please contact @mucephie at <mucephie@my.yorku.ca>. If you are interested in the Allan I. Carswell observatory at York university, you can find more information at our website.

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