miles-credit

MILES Community Research Digital Intelligence Twin (CREDIT): research platform for AI numerical weather prediction models.

https://github.com/ncar/miles-credit

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
    Links to: arxiv.org, zenodo.org
  • Committers with academic emails
    14 of 25 committers (56.0%) from academic institutions
  • Institutional organization owner
    Organization ncar has institutional domain (ncar.ucar.edu)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.7%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

MILES Community Research Digital Intelligence Twin (CREDIT): research platform for AI numerical weather prediction models.

Basic Info
Statistics
  • Stars: 52
  • Watchers: 15
  • Forks: 17
  • Open Issues: 14
  • Releases: 2
Created over 2 years ago · Last pushed 10 months ago
Metadata Files
Readme License

README.md

NSF NCAR MILES Community Research Earth Digital Intelligence Twin (CREDIT)

DOI PyPI - Version arXiv

About

CREDIT is an open software platform to train and deploy AI atmospheric prediction models. CREDIT offers fast models that can be flexibly configured both in terms of input data and neural network architecture. The interface is designed to be user-friendly and enable fast spin-up and iteration. CREDIT is backed by the AI and atmospheric science expertise of the MILES group and the NSF National Center for Atmospheric Research, leading to design choices that balance advanced AI/ML with our physical knowledge of the atmosphere.

CREDIT has reached its first stable release with a full set of models, training, and deployment options. It continues to be under active development. Please contact the MILES group if you have any questions about CREDIT.

MILES CREDIT also provides more detailed documentation with installation instructions, how to get started training and deploying models, how to interpret the config files, and full API docs.

Citing CREDIT

If you are interested in using CREDIT as part of your research, please cite the following paper: Schreck, J., Sha, Y., Chapman, W., Kimpara, D., Berner, J., McGinnis, S., Kazadi, A., Sobhani, N., Kirk, B., Gagne, D.J. (2024, November 9). Community Research Earth Digital Intelligence Twin (CREDIT). arXiv [cs.AI]. http://arxiv.org/abs/2411.07814

Model Weights and Data

Model weights for the CREDIT 6-hour WXFormer and FuXi models and the 1-hour WXFormer are available on huggingface.

Processed ERA5 Zarr Data are available for download through Globus (requires free account) through the CREDIT ERA5 Zarr Files collection.

Scaling/transform values for normalizing the data are available through Globus here.

Support

This software is based upon work supported by the NSF National Center for Atmospheric Research, a major facility sponsored by the U.S. National Science Foundation under Cooperative Agreement No. 1852977 and managed by the University Corporation for Atmospheric Research. Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of NSF. Additional support for development was provided by The NSF AI Institute for Research on Trustworthy AI for Weather, Climate, and Coastal Oceanography (AI2ES) with grant number RISE-2019758.

Owner

  • Name: NSF National Center for Atmospheric Research
  • Login: NCAR
  • Kind: organization
  • Location: Boulder, CO

NSF NCAR is sponsored by the U.S. National Science Foundation and managed by the University Corporation for Atmospheric Research.

GitHub Events

Total
  • Create event: 37
  • Commit comment event: 146
  • Release event: 2
  • Delete event: 15
  • Member event: 2
  • Pull request event: 124
  • Fork event: 11
  • Issues event: 13
  • Watch event: 33
  • Issue comment event: 61
  • Push event: 470
  • Public event: 1
  • Pull request review comment event: 65
  • Pull request review event: 119
Last Year
  • Create event: 38
  • Commit comment event: 146
  • Release event: 2
  • Delete event: 15
  • Member event: 2
  • Pull request event: 124
  • Fork event: 11
  • Issues event: 13
  • Watch event: 33
  • Issue comment event: 61
  • Push event: 470
  • Public event: 1
  • Pull request review comment event: 65
  • Pull request review event: 119

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 1,262
  • Total Committers: 25
  • Avg Commits per committer: 50.48
  • Development Distribution Score (DDS): 0.622
Past Year
  • Commits: 681
  • Committers: 23
  • Avg Commits per committer: 29.609
  • Development Distribution Score (DDS): 0.649
Top Committers
Name Email Commits
Yingkai Sha y****a@g****m 477
John Schreck j****k@g****m 249
David John Gagne d****e@g****m 206
dkimpara d****a@u****u 51
willychap w****n@u****u 51
dkimpara d****a@g****m 50
Seth McGinnis m****s@u****u 44
Arnold Kazadi a****o@g****m 23
charlie-becker c****r@u****u 17
Katelyn FitzGerald 7****d@u****m 15
Negin Sobhani n****3@g****m 14
willychap w****n@u****u 13
ggantos g****s@u****u 8
Stanley Akor s****r@c****u 6
Stanley Akor s****r@c****u 6
jsschreck s****k@u****u 6
David John Gagne 8****e@u****m 4
Stanley Akor s****r@c****u 4
sgpearse p****e@u****u 4
Jay Rothenberger 3****r@u****m 3
Nihanth Wagmi Cherukuru n****u@u****u 3
gabrielle 2****s@u****m 3
Stanley Akor s****r@u****u 2
sgpearse s****e@g****m 2
Stanley Akor s****r@c****u 1

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 23
  • Total pull requests: 179
  • Average time to close issues: 5 months
  • Average time to close pull requests: 8 days
  • Total issue authors: 10
  • Total pull request authors: 14
  • Average comments per issue: 1.09
  • Average comments per pull request: 0.55
  • Merged pull requests: 142
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 12
  • Pull requests: 103
  • Average time to close issues: 3 months
  • Average time to close pull requests: 12 days
  • Issue authors: 7
  • Pull request authors: 13
  • Average comments per issue: 0.58
  • Average comments per pull request: 0.44
  • Merged pull requests: 71
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • dkimpara (8)
  • yingkaisha (4)
  • NihanthCW (2)
  • kafitzgerald (2)
  • sethmcg (2)
  • charlie-becker (1)
  • tmerlis (1)
  • WillyChap (1)
  • djgagne (1)
  • jsschreck (1)
Pull Request Authors
  • jsschreck (57)
  • yingkaisha (32)
  • djgagne (19)
  • dkimpara (18)
  • WillyChap (13)
  • kanz76 (11)
  • kafitzgerald (7)
  • sethmcg (5)
  • stanleyakor1 (4)
  • charlie-becker (4)
  • NihanthCW (3)
  • ggantos (2)
  • negin513 (2)
  • sgpearse (2)
Top Labels
Issue Labels
Pull Request Labels
bug (1) enhancement (1)

Packages

  • Total packages: 2
  • Total downloads: unknown
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 4
proxy.golang.org: github.com/NCAR/miles-credit
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 9 months ago
proxy.golang.org: github.com/ncar/miles-credit
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 9 months ago

Dependencies

.github/workflows/python-package-conda.yml actions
  • actions/checkout v4 composite
  • mamba-org/setup-micromamba v1 composite
.github/workflows/python-publish.yml actions
  • actions/checkout v4 composite
  • actions/download-artifact v4 composite
  • actions/setup-python v5 composite
  • actions/upload-artifact v4 composite
  • pypa/gh-action-pypi-publish release/v1 composite
pyproject.toml pypi
  • bridgescaler *
  • cartopy *
  • dask *
  • dask-jobqueue *
  • distributed *
  • echo-opt *
  • einops *
  • fsspec *
  • gcsfs *
  • haversine *
  • matplotlib *
  • myst_parser *
  • netcdf4 *
  • numpy *
  • pandas *
  • pre-commit *
  • pvlib *
  • pyarrow *
  • pysteps *
  • pytest *
  • pyyaml *
  • ruff *
  • scikit-learn *
  • segmentation-models-pytorch *
  • sphinx *
  • sphinx-autoapi *
  • sphinx-book-theme *
  • torch *
  • torch-harmonics *
  • torch_geometric *
  • torchvision *
  • xarray *
  • zarr *
requirements.txt pypi
  • bridgescaler *
  • cartopy *
  • dask *
  • dask-jobqueue *
  • distributed *
  • echo-opt *
  • einops *
  • fsspec *
  • gcsfs *
  • haversine *
  • jupyter *
  • matplotlib *
  • netcdf4 *
  • numpy *
  • pandas *
  • pre-commit *
  • pvlib *
  • pyarrow *
  • pytest *
  • pyyaml *
  • ruff *
  • scikit-learn *
  • segmentation-models-pytorch *
  • torch *
  • torch-harmonics *
  • torch_geometric *
  • torchvision *
  • xarray *
  • zarr *
setup.py pypi