PetroFit is a package for calculating Petrosian properties, such as radii and concentration indices, as well as fitting
galaxy light profiles. In particular, PetroFit includes tools for performing accurate photometry, segmentations,
Petrosian profiling, and Sérsic fitting. Please see the petrofit documentation
for installation instructions and a guide to the petrofit module.
You can install PetroFit using pip install petrofit. Please see
the petrofit documentation for detailed installation instructions.
This project is Copyright (c) The PetroFit Team 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.
We love contributions! petrofit 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 petrofit based on its use in the README file for the MetPy project.