SkyPy: A package for modelling the Universe

This package contains methods for modelling the Universe, galaxies and the Milky Way. Also included are methods for generating observed data.

• Galaxy morphology, luminosity and redshift distributions
• Halo and subhalo mass distributions
• Gravitational Wave binary merger rates
• Power Spectra using CAMB and Halofit
• Pipelines to generate populations of astronomical objects

The full list of features can be found in the SkyPy Documentation.

If you use SkyPy for work or research presented in a publication please follow our Citation Guidelines.

Getting Started

SkyPy is distributed through PyPI and conda-forge. To install SkyPy and its dependencies using pip:

$ pip install skypy

To install using conda:

$ conda install -c conda-forge skypy

You can test your SkyPy intallation using pytest:

$ pytest --pyargs skypy

The SkyPy library can then be imported from python:

>>> import skypy
>>> help(skypy)

SkyPy also has a driver script that can run simulation pipelines from the command line. The skypyproject/examples repository contains sample configuration files that you can clone and run:

git clone --depth 1 -b v$(skypy --version) https://github.com/skypyproject/examples.git
skypy examples/mccl_galaxies.yml --format fits

Contributing

We love contributions! SkyPy is open source, built on open source, and we'd love to have you hang out in our community. For information on how to contribute see our Contributor Guidelines. All communication relating to The SkyPy Project must meet the standards set out in the Code of Conduct.

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 SkyPy based on its use in the README file for the MetPy project.