Metadata-Version: 2.1
Name: afqinsight
Version: 0.1.dev24560066971
Summary: AFQ-Insight: Statistical Learning for Tractometry
Home-page: https://richford.github.io/afqinsight
Author: Adam Richie-Halford
Author-email: richiehalford@gmail.com
Maintainer: Adam Richie-Halford
Maintainer-email: richiehalford@gmail.com
License: BSD License
Download-URL: https://github.com/richford/afqinsight
Platform: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
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# Python based statistical learning of AFQ data

See <https://yeatmanlab.github.io/AFQ-Browser/> for documentation of the AFQ data format

This is a work in progress.

## Contributing

We love contributions! AFQ-Insight is open source, built on open source,
and we'd love to have you hang out in our community.

We have developed some [guidelines](CONTRIBUTING.md) for contributing to
AFQ-Insight.

**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.

## Credits

The imposter syndrome 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 based on its use in the README file for the [MetPy
project](https://github.com/Unidata/MetPy).


