Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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✓Committers with academic emails
63 of 200 committers (31.5%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (16.0%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
Main yt repository
Basic Info
- Host: GitHub
- Owner: yt-project
- License: other
- Language: Python
- Default Branch: main
- Homepage: http://yt-project.org
- Size: 392 MB
Statistics
- Stars: 515
- Watchers: 19
- Forks: 293
- Open Issues: 454
- Releases: 16
Topics
Metadata Files
README.md
The yt Project
yt is an open-source, permissively-licensed Python library 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.
Code of Conduct
yt abides by a code of conduct partially modified from the PSF code of conduct, and is found in our contributing guide.
Installation
You can install the most recent stable version of yt either with conda from conda-forge:
shell
conda install -c conda-forge yt
or with pip:
shell
python -m pip install yt
More information on the various ways to install yt, and in particular to install from source, can be found on the project's website.
Getting Started
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.
Contributing
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.
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.
(This disclaimer was originally written by Adrienne Lowe for a PyCon talk, and was adapted by yt based on its use in the README file for the MetPy project)
Resources
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)
Is your code compatible with yt ? Great ! Please consider giving us a shoutout as a shiny badge in your README
- markdown
markdown [![yt-project](https://img.shields.io/static/v1?label="works%20with"&message="yt"&color="blueviolet")](https://yt-project.org) - rst ```reStructuredText |yt-project|
.. |yt-project| image:: https://img.shields.io/static/v1?label="works%20with"&message="yt"&color="blueviolet" :target: https://yt-project.org ```
Powered by NumFOCUS
yt is a fiscally sponsored project of NumFOCUS. If you're interested in supporting the active maintenance and development of this project, consider donating to the project.
Owner
- Name: The yt project
- Login: yt-project
- Kind: organization
- Email: yt-users@python.org
- Website: http://yt-project.org/
- Repositories: 43
- Profile: https://github.com/yt-project
A toolkit for analysis and visualization of volumetric data
Citation (CITATION)
To cite yt in publications, please use:
Turk, M. J., Smith, B. D., Oishi, J. S., et al. 2011, ApJS, 192, 9
In the body of the text, please add a footnote to the yt webpage:
http://yt-project.org/
For LaTex and BibTex users:
\bibitem[Turk et al.(2011)]{2011ApJS..192....9T} Turk, M.~J., Smith, B.~D.,
Oishi, J.~S., et al.\ 2011, The Astrophysical Journal Supplement Series, 192, 9
@ARTICLE{2011ApJS..192....9T,
author = {{Turk}, M.~J. and {Smith}, B.~D. and {Oishi}, J.~S. and {Skory}, S. and
{Skillman}, S.~W. and {Abel}, T. and {Norman}, M.~L.},
title = "{yt: A Multi-code Analysis Toolkit for Astrophysical Simulation Data}",
journal = {The Astrophysical Journal Supplement Series},
archivePrefix = "arXiv",
eprint = {1011.3514},
primaryClass = "astro-ph.IM",
keywords = {cosmology: theory, methods: data analysis, methods: numerical},
year = 2011,
month = jan,
volume = 192,
eid = {9},
pages = {9},
doi = {10.1088/0067-0049/192/1/9},
adsurl = {http://adsabs.harvard.edu/abs/2011ApJS..192....9T},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
Using yt can also utilize other functionality. If you utilize ORIGAMI, we ask
that you please cite the ORIGAMI paper:
@ARTICLE{2012ApJ...754..126F,
author = {{Falck}, B.~L. and {Neyrinck}, M.~C. and {Szalay}, A.~S.},
title = "{ORIGAMI: Delineating Halos Using Phase-space Folds}",
journal = {\apj},
archivePrefix = "arXiv",
eprint = {1201.2353},
primaryClass = "astro-ph.CO",
keywords = {dark matter, galaxies: halos, large-scale structure of universe, methods: numerical},
year = 2012,
month = aug,
volume = 754,
eid = {126},
pages = {126},
doi = {10.1088/0004-637X/754/2/126},
adsurl = {http://adsabs.harvard.edu/abs/2012ApJ...754..126F},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
The main homepage for ORIGAMI can be found here:
http://icg.port.ac.uk/~falckb/origami.html
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Matthew Turk | m****k@g****m | 6,975 |
| Nathan Goldbaum | n****u@i****u | 3,326 |
| John ZuHone | j****e@g****m | 2,513 |
| Clément Robert | c****2@p****m | 2,095 |
| Britton Smith | b****h@g****m | 1,949 |
| Corentin Cadiou | c****u@i****r | 1,333 |
| Andrew Myers | a****2@g****m | 1,233 |
| Cameron Hummels | c****s@g****m | 1,064 |
| Kacper Kowalik | x****k@g****m | 975 |
| Sam Skillman | s****n@g****m | 623 |
| Stephen Skory | s@s****s | 575 |
| Chris Moody | j****n@g****m | 358 |
| Chris Havlin | c****n@g****m | 327 |
| Ashley Kelly | a****y@d****k | 273 |
| J.S. Oishi | j****i@g****m | 233 |
| pre-commit-ci[bot] | 6****] | 213 |
| Bili Dong | q****p@g****m | 195 |
| Douglas Rudd | d****d@u****u | 180 |
| Michael Zingale | m****e@s****u | 171 |
| Suoqing Ji | j****g@g****m | 159 |
| Meagan Lang | l****o@g****m | 152 |
| Madicken Munk | m****k@g****m | 144 |
| John Wise | j****e@p****u | 139 |
| Alex Lindsay | a****y@i****v | 137 |
| Hilary Egan | h****n@c****u | 116 |
| Abhishek Singh | a****g@u****u | 116 |
| Jill Naiman | j****n@i****u | 105 |
| Allyson Julian | a****r@g****m | 101 |
| Miguel de Val-Borro | m****l@g****m | 100 |
| Jared Coughlin | j****2@n****u | 79 |
| and 170 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 257
- Total pull requests: 961
- Average time to close issues: 4 months
- Average time to close pull requests: 26 days
- Total issue authors: 71
- Total pull request authors: 50
- Average comments per issue: 2.95
- Average comments per pull request: 3.1
- Merged pull requests: 716
- Bot issues: 7
- Bot pull requests: 134
Past Year
- Issues: 72
- Pull requests: 339
- Average time to close issues: 16 days
- Average time to close pull requests: 9 days
- Issue authors: 30
- Pull request authors: 29
- Average comments per issue: 1.26
- Average comments per pull request: 1.85
- Merged pull requests: 211
- Bot issues: 4
- Bot pull requests: 79
Top Authors
Issue Authors
- neutrinoceros (76)
- chrishavlin (30)
- matthewturk (23)
- cphyc (14)
- nastasha-w (8)
- github-actions[bot] (7)
- olebole (7)
- Xarthisius (4)
- zingale (3)
- yut23 (3)
- arkordt (3)
- V-Nathir (3)
- AsierLambarri (3)
- chummels (3)
- BenWibking (3)
Pull Request Authors
- neutrinoceros (308)
- meeseeksmachine (149)
- chrishavlin (112)
- dependabot[bot] (91)
- cphyc (48)
- pre-commit-ci[bot] (43)
- matthewturk (32)
- yut23 (29)
- jzuhone (26)
- zingale (15)
- mabruzzo (12)
- nastasha-w (10)
- Lenoble-lab (7)
- chummels (7)
- henrynjones (6)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
-
Total downloads:
- pypi 27,047 last-month
-
Total dependent packages: 18
(may contain duplicates) -
Total dependent repositories: 82
(may contain duplicates) - Total versions: 64
- Total maintainers: 6
pypi.org: yt
An analysis and visualization toolkit for volumetric data
- Homepage: https://yt-project.org/
- Documentation: https://yt-project.org/doc/
- License: BSD 3-Clause
-
Latest release: 4.4.1
published 6 months ago
Rankings
Maintainers (6)
anaconda.org: yt
yt is a community-developed analysis and visualization toolkit for volumetric data. yt has been applied mostly to astrophysical simulation data, but it can be applied to many different types of data including seismology, radio telescope data, weather simulations, and nuclear
- Homepage: https://yt-project.org/
- License: BSD-3-Clause
-
Latest release: 4.4.0
published 10 months ago
Rankings
Dependencies
- actions/checkout v3 composite
- actions/setup-python v4 composite
- imjohnbo/issue-bot v3 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- actions/upload-artifact v3 composite
- s-weigand/setup-conda v1 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- actions/checkout v3 composite
- actions/download-artifact v3 composite
- actions/setup-python v4 composite
- actions/upload-artifact v3 composite
- pypa/cibuildwheel v2.15.0 composite
- pypa/gh-action-pypi-publish v1.8.10 composite
- cmyt >=1.1.2
- ewah-bool-utils >=1.0.2
- ipywidgets >=8.0.0
- matplotlib >=3.5
- more-itertools >=8.4
- numpy >=1.19.3
- packaging >=20.9
- pillow >=8.0.0
- tomli >=1.2.3;python_version < '3.11'
- tomli-w >=0.4.0
- tqdm >=3.4.0
- typing-extensions >=4.4.0;python_version < '3.12'
- unyt >=2.9.2,<3.0