yt is an open-source, permissively-licensed python package for analyzing and visualizing volumetric data.

yt supports structured, variable-resolution meshes, unstructured meshes, and discrete or sampled data such as particles. Focused on driving physically-meaningful inquiry, yt has been applied in domains such as astrophysics, seismology, nuclear engineering, molecular dynamics, and oceanography. Composed of a friendly community of users and developers, we want to make it easy to use and develop - we'd love it if you got involved!

We've written a method paper you may be interested in; if you use yt in the preparation of a publication, please consider citing it.

If you're using conda with conda-forge, you can install the most recent stable version by running:

conda install -c conda-forge yt

or by doing:

pip install yt

If you want the latest nightly build, you can manually install from our repository:

conda install -c http://use.yt/with_conda yt

To get set up with a development version, you can clone this repository and install like this:

git clone https://github.com/yt-project/yt yt-git
cd yt-git
python setup.py develop

To set up yt in a virtualenv (and there are many good reasons to do so!) you can follow this prescription:

# Assuming you have cd'd into yt-git
# It is conventional to create virtualenvs at ~/.virtualenv/
$ mkdir -p ~/.virtualenv
# Assuming your version of Python 3 is 3.4 or higher,
# create a virtualenv named yt
$ python3 -m venv ~/.virtualenv/yt
# Activate it
$ source ~/.virtualenv/yt/bin/activate
# Make sure you run the latest version of pip
$ pip install --upgrade pip
$ pip install -e .
# Output installed packages
$ pip freeze

yt is designed to provide meaningful analysis of data. We have some Quickstart example notebooks in the repository:

• Introduction
• Data Inspection
• Simple Visualization
• Data Objects and Time Series
• Derived Fields and Profiles
• Volume Rendering

If you'd like to try these online, you can visit our yt Hub and run a notebook next to some of our example data.

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

We have developed some guidelines for contributing to yt.

We have some community and documentation resources available.

• Our latest documentation is always at http://yt-project.org/docs/dev/ and it includes recipes, tutorials, and API documentation
• The discussion mailing list should be your first stop for general questions
• The development mailing list is better suited for more development issues
• You can also join us on Slack at yt-project.slack.com (request an invite)