NeuralHydrology

Python library to train neural networks with a strong focus on hydrological applications.
https://github.com/neuralhydrology/neuralhydrology

Category: Hydrosphere
Sub Category: Freshwater and Hydrology

Keywords from Contributors

hydrology

Last synced: about 6 hours ago
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Repository metadata

Python library to train neural networks with a strong focus on hydrological applications.

README.md

#

Python library to train neural networks with a strong focus on hydrological applications.

This package has been used extensively in research over the last years and was used in various academic publications.
The core idea of this package is modularity in all places to allow easy integration of new datasets, new model
architectures or any training-related aspects (e.g. loss functions, optimizer, regularization).
One of the core concepts of this code base are configuration files, which let anyone train neural networks without
touching the code itself. The NeuralHydrology package is built on top of the deep learning framework
PyTorch, since it has proven to be the most flexible and useful for research purposes.

We (the AI for Earth Science group at the Institute for Machine Learning, Johannes Kepler University, Linz, Austria) are using
this code in our day-to-day research and will continue to integrate our new research findings into this public repository.

Cite NeuralHydrology

In case you use NeuralHydrology in your research or work, it would be highly appreciated if you include a reference to our JOSS paper in any kind of publication.

@article{kratzert2022joss,
  title = {NeuralHydrology --- A Python library for Deep Learning research in hydrology},
  author = {Frederik Kratzert and Martin Gauch and Grey Nearing and Daniel Klotz},
  journal = {Journal of Open Source Software},
  publisher = {The Open Journal},
  year = {2022},
  volume = {7},
  number = {71},
  pages = {4050},
  doi = {10.21105/joss.04050},
  url = {https://doi.org/10.21105/joss.04050},
}

Contact

For questions or comments regarding the usage of this repository, please use the discussion section on Github. For bug reports and feature requests, please open an issue on GitHub.
In special cases, you can also reach out to us by email: neuralhydrology(at)googlegroups.com

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Kratzert"
  given-names: "Frederik"
- family-names: "Gauch"
  given-names: "Martin"
- family-names: "Nearing"
  given-names: "Grey"
- family-names: "Klotz"
  given-names: "Daniel"
title: "NeuralHydrology --- A Python library for Deep Learning research in hydrology"
doi: 10.21105/joss.04050
url: "https://doi.org/10.21105/joss.04050"
preferred-citation:
  type: article
  authors:
  - family-names: "Kratzert"
    given-names: "Frederik"
  - family-names: "Gauch"
    given-names: "Martin"
  - family-names: "Nearing"
    given-names: "Grey"
  - family-names: "Klotz"
    given-names: "Daniel"
  doi: "10.21105/joss.04050"
  journal: "Journal of Open Source Software"
  publisher: 
    name: "The Open Journal"
  start: 4050 # First page number
  end: 4050 # Last page number
  title: "NeuralHydrology --- A Python library for Deep Learning research in hydrology"
  number: 71
  volume: 7
  year: 2022

Owner metadata


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Committers metadata

Last synced: 9 days ago

Total Commits: 227
Total Committers: 15
Avg Commits per committer: 15.133
Development Distribution Score (DDS): 0.524

Commits in past year: 20
Committers in past year: 7
Avg Commits per committer in past year: 2.857
Development Distribution Score (DDS) in past year: 0.45

Name Email Commits
Frederik Kratzert k****t 108
Martin Gauch 1****m 84
Grey Nearing g****g@g****m 13
Daniel Klotz k****z@m****t 6
Scott Hamshaw s****w@u****u 3
Brandon Victor M****r@h****m 2
Thomas Berends t****s@h****m 2
Eduardo Acuna 6****a 2
BaptisteFrancois 3****s 1
Bevan Jenkins 2****j 1
Martijn Visser m****r@g****m 1
Sebastian Drost s****t@5****g 1
Tadd Bindas t****6@p****u 1
Vincent Cloarec v****c@g****m 1
XuHuanHydro 1****o 1

Committer domains:


Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 57
Total pull requests: 78
Average time to close issues: about 1 month
Average time to close pull requests: 8 days
Total issue authors: 41
Total pull request authors: 20
Average comments per issue: 3.46
Average comments per pull request: 0.65
Merged pull request: 66
Bot issues: 0
Bot pull requests: 0

Past year issues: 10
Past year pull requests: 15
Past year average time to close issues: 11 days
Past year average time to close pull requests: 11 days
Past year issue authors: 8
Past year pull request authors: 10
Past year average comments per issue: 1.3
Past year average comments per pull request: 1.0
Past year merged pull request: 8
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/neuralhydrology/neuralhydrology

Top Issue Authors

  • shamshaw (4)
  • chuckaustin (3)
  • tommylees112 (3)
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  • Meelisha (2)
  • jamesYu365 (2)
  • Kavindra95 (2)
  • vlahm (2)
  • SebaDro (2)
  • ammilten (1)
  • gauchm (1)
  • NHoose (1)
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  • javierfernandezfidalgo (1)

Top Pull Request Authors

  • kratzert (37)
  • gauchm (13)
  • grey-nearing (4)
  • shamshaw (3)
  • Multihuntr (3)
  • tberends (3)
  • evanr1232 (2)
  • XuHuanHydro (1)
  • Yingying016 (1)
  • KMarkert (1)
  • vcloarec (1)
  • visr (1)
  • kyleniemeyer (1)
  • BaptisteFrancois (1)
  • ShihengDuan (1)

Top Issue Labels

  • enhancement (2)
  • documentation (2)
  • good first issue (2)
  • bug (1)
  • help wanted (1)

Top Pull Request Labels

  • enhancement (2)
  • documentation (1)
  • bug (1)

Package metadata

pypi.org: neuralhydrology

Library for training deep learning models with environmental focus

  • Homepage: https://neuralhydrology.readthedocs.io
  • Documentation: https://neuralhydrology.readthedocs.io
  • Licenses: BSD License
  • Latest release: 1.12.0 (published about 2 months ago)
  • Last Synced: 2025-04-29T14:10:41.778Z (1 day ago)
  • Versions: 17
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 838 Last month
  • Rankings:
    • Stargazers count: 4.192%
    • Forks count: 4.339%
    • Dependent packages count: 7.306%
    • Average: 10.215%
    • Downloads: 13.161%
    • Dependent repos count: 22.077%
  • Maintainers (1)

Dependencies

environments/rtd_requirements.txt pypi
  • ipython *
  • nbsphinx >=0.8.0
  • nbsphinx-link >=1.3.0
  • numpy *
  • sphinx >=3.2.1
  • sphinx-rtd-theme >=0.5.0
  • tensorboard *
  • torch *
setup.py pypi
  • matplotlib *
  • numba *
  • numpy *
  • pandas *
  • ruamel.yaml *
  • scipy *
  • tensorboard *
  • torch *
  • tqdm *
  • xarray *
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Score: 15.474538314738371