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
JSON representation
Repository metadata
Python library to train neural networks with a strong focus on hydrological applications.
- Host: GitHub
- URL: https://github.com/neuralhydrology/neuralhydrology
- Owner: neuralhydrology
- License: bsd-3-clause
- Created: 2020-09-30T07:16:56.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2025-04-22T14:02:05.000Z (8 days ago)
- Last Synced: 2025-04-29T14:11:24.329Z (1 day ago)
- Language: Python
- Homepage: https://neuralhydrology.readthedocs.io/
- Size: 11.3 MB
- Stars: 412
- Watchers: 25
- Forks: 214
- Open Issues: 5
- Releases: 27
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.rst
- License: LICENSE
- Citation: CITATION.cff
- Codeowners: CODEOWNERS
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.
- Documentation: neuralhydrology.readthedocs.io
- Research Blog: neuralhydrology.github.io
- Bug reports/Feature requests https://github.com/neuralhydrology/neuralhydrology/issues
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
- Name: Neural Hydrology
- Login: neuralhydrology
- Email:
- Kind: organization
- Description: AI 4 Earth Sciences research group, Institute of Machine Learning, JKU Linz
- Website: https://neuralhydrology.github.io/
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/59032226?v=4
- Repositories: 2
- Last ynced at: 2023-08-07T04:21:04.993Z
- Profile URL: https://github.com/neuralhydrology
GitHub Events
Total
- Create event: 2
- Release event: 1
- Issues event: 11
- Watch event: 54
- Delete event: 1
- Issue comment event: 21
- Push event: 8
- Pull request review event: 26
- Pull request review comment event: 18
- Pull request event: 17
- Fork event: 31
Last Year
- Create event: 2
- Release event: 1
- Issues event: 11
- Watch event: 54
- Delete event: 1
- Issue comment event: 21
- Push event: 8
- Pull request review event: 26
- Pull request review comment event: 18
- Pull request event: 17
- Fork event: 31
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 | 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:
- psu.edu: 1
- 52north.org: 1
- uvm.edu: 1
- ml.jku.at: 1
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
Top Issue Authors
- shamshaw (4)
- chuckaustin (3)
- tommylees112 (3)
- Flash-Of-Thunder (3)
- pedrozamboni (3)
- Meelisha (2)
- jamesYu365 (2)
- Kavindra95 (2)
- vlahm (2)
- SebaDro (2)
- ammilten (1)
- gauchm (1)
- NHoose (1)
- rhedouin (1)
- 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
- Total packages: 1
-
Total downloads:
- pypi: 838 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 17
- Total maintainers: 1
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
- ipython *
- nbsphinx >=0.8.0
- nbsphinx-link >=1.3.0
- numpy *
- sphinx >=3.2.1
- sphinx-rtd-theme >=0.5.0
- tensorboard *
- torch *
- matplotlib *
- numba *
- numpy *
- pandas *
- ruamel.yaml *
- scipy *
- tensorboard *
- torch *
- tqdm *
- xarray *
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout master composite
- actions/setup-python v2 composite
- pypa/gh-action-pypi-publish master composite
- actions/cache v2 composite
- actions/checkout v2 composite
- s-weigand/setup-conda v1 composite
Score: 15.474538314738371