dorado
dorado: A Python package for simulating passive particle transport in shallow-water flows - Published in JOSS (2020)
Science Score: 95.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README and JOSS metadata -
✓Academic publication links
Links to: joss.theoj.org -
✓Committers with academic emails
5 of 6 committers (83.3%) from academic institutions -
○Institutional organization owner
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✓JOSS paper metadata
Published in Journal of Open Source Software
Keywords
Scientific Fields
Repository
For shallow-water Lagrangian particle routing.
Basic Info
- Host: GitHub
- Owner: passaH2O
- License: mit
- Language: Python
- Default Branch: master
- Homepage: https://passah2o.github.io/dorado
- Size: 87.5 MB
Statistics
- Stars: 59
- Watchers: 2
- Forks: 11
- Open Issues: 6
- Releases: 18
Topics
Metadata Files
README.md
dorado - Lagrangian particle routing
dorado is a Python package for simulating passive Lagrangian particle transport over flow-fields from any 2D shallow-water hydrodynamic model using a weighted random walk methodology.
For user guides and detailed examples, refer to the documentation.
Example Uses:
Particles on an Unsteady ANUGA Flow Field of the Wax Lake Delta
Particles on a DeltaRCM Simulated Delta
Installation:
dorado supports Python 3.11+. For the full distribution including examples, clone this repository using git clone and run python setup.py install from the cloned directory. To test this "full" installation, you must first install pytest via pip install pytest. Then from the cloned directory the command pytest can be run to ensure that your installed distribution passes all of the unit tests.
For a lightweight distribution including just the core functionality, use pip to install via PyPI:
pip install pydorado
Installation using conda via conda-forge is also supported:
conda install -c conda-forge pydorado
For additional installation options and instructions, refer to the documentation.
Contributing
We welcome contributions to the dorado project. Please open an issue or a pull request if there is functionality you would like to see or propose. Refer to our contributing guide for more information.
Citing
If you use this package and wish to cite it, please use the Journal of Open Source Software article.
Funding Acknowledgments
This work was supported in part by NSF EAR-1719670, the NSF GRFP under grant DGE-1610403 and the NASA Earth Venture Suborbital (EVS) award 17-EVS3-17_1-0009 in support of the DELTA-X project.
Owner
- Name: PassaH2O Group
- Login: passaH2O
- Kind: organization
- Website: https://sites.google.com/site/passalacquagroup/home
- Repositories: 10
- Profile: https://github.com/passaH2O
JOSS Publication
dorado: A Python package for simulating passive particle transport in shallow-water flows
Authors
Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin
Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin
Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin
Editor
Katy Barnhart
Tags
Lagrangian transport random walk hydrodynamicsGitHub Events
Total
- Create event: 10
- Release event: 6
- Issues event: 8
- Watch event: 5
- Delete event: 3
- Issue comment event: 11
- Push event: 17
- Pull request review event: 6
- Pull request review comment event: 15
- Pull request event: 12
- Fork event: 1
Last Year
- Create event: 10
- Release event: 6
- Issues event: 8
- Watch event: 5
- Delete event: 3
- Issue comment event: 11
- Push event: 17
- Pull request review event: 6
- Pull request review comment event: 15
- Pull request event: 12
- Fork event: 1
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| JayH | j****n@u****u | 225 |
| wrightky | k****t@u****u | 50 |
| Wright | k****5@a****u | 39 |
| Katherine Barnhart | k****t@u****v | 3 |
| Paola Passalacqua | p****a@a****u | 1 |
| Caitlin (Katie) Turner | 7****r | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 21
- Total pull requests: 42
- Average time to close issues: 3 months
- Average time to close pull requests: about 1 month
- Total issue authors: 5
- Total pull request authors: 4
- Average comments per issue: 1.0
- Average comments per pull request: 1.88
- Merged pull requests: 39
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 5
- Pull requests: 12
- Average time to close issues: 19 days
- Average time to close pull requests: 5 days
- Issue authors: 2
- Pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 2.5
- Merged pull requests: 10
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- elbeejay (13)
- kbarnhart (3)
- gassmoeller (2)
- caitlinturner (2)
- wrightky (1)
Pull Request Authors
- elbeejay (30)
- wrightky (7)
- caitlinturner (4)
- kbarnhart (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 3
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Total downloads:
- pypi 196 last-month
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Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 1
(may contain duplicates) - Total versions: 51
- Total maintainers: 2
proxy.golang.org: github.com/passaH2O/dorado
- Documentation: https://pkg.go.dev/github.com/passaH2O/dorado#section-documentation
- License: mit
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Latest release: v2.6.0+incompatible
published 6 months ago
Rankings
proxy.golang.org: github.com/passah2o/dorado
- Documentation: https://pkg.go.dev/github.com/passah2o/dorado#section-documentation
- License: mit
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Latest release: v2.6.0+incompatible
published 6 months ago
Rankings
pypi.org: pydorado
dorado - Lagrangian particle routing routine via weighted random walks
- Homepage: https://github.com/passaH2O/dorado
- Documentation: https://pydorado.readthedocs.io/
- License: MIT License Copyright (c) 2020 Passalacqua Group Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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Latest release: 2.6.0
published 6 months ago
Rankings
Maintainers (2)
Dependencies
- future *
- matplotlib *
- numpy *
- scipy *
- tqdm *
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