umami
umami: A Python package for Earth surface dynamics objective function construction - Published in JOSS (2019)
Science Score: 95.0%
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 7 DOI reference(s) in README and JOSS metadata -
✓Academic publication links
Links to: joss.theoj.org -
✓Committers with academic emails
2 of 4 committers (50.0%) from academic institutions -
○Institutional organization owner
-
✓JOSS paper metadata
Published in Journal of Open Source Software
Scientific Fields
Repository
Calculate topographic metrics for assessing model-data fit
Basic Info
- Host: GitHub
- Owner: TerrainBento
- License: mit
- Language: Python
- Default Branch: master
- Homepage: https://umami.readthedocs.io
- Size: 4.22 MB
Statistics
- Stars: 1
- Watchers: 2
- Forks: 2
- Open Issues: 1
- Releases: 10
Metadata Files
README.md
What is it?
Umami is a package for calculating objective functions or objective function
components for Earth surface dynamics modeling. It was designed to work well
with
terrainbento and other models built with the
Landlab Toolkit. Examples can be
found in the notebooks directory (or on Binder
).
Umami offers two primary classes:
* a Residual,
which represents the difference between model and data, and
* a Metric,
which is a calculated value on either model or data.
The set of currently supported calculations are found in the umami.calculations submodule.
What does it do well?
Umami was designed to provide an input-file based interface for calculating
single-value landscape metrics for use in model analysis. This supports
reproducible analysis and systematic variation in metric construction. When
used with terrainbento one input file can describe the model run, and one
input file can describe the model assessment or model-data comparison. This
streamlines model analysis applications. Umami also provides multiple output
formats (YAML and Dakota), the latter of which is designed to interface with
Sandia National Laboratory's Dakota package.
To get a sense of how it is meant to be used, check out the notebooks on Binder and the API documentation.
Where to get it
To install the release version of umami (this is probably what you want) we support conda and pip package management.
Using conda
Open a terminal and execute the following:
$ conda config --add channels conda-forge
$ conda install umami
Using pip
Open a terminal and execute the following:
$ pip install umami
From source code
The source code is housed on GitHub. To install the umami from source code we recommend creating a conda environment.
$ git clone https://github.com/TerrainBento/umami.git
$ cd umami
$ conda env create -f environment-dev.yml
$ conda activate umami-dev
$ python setup.py install
If you are interested in developing umami, please check out the development practices page.
Read the documentation
Documentation is housed on ReadTheDocs.
License
Report issues and get help
Umami uses Github Issue as a single point of contact for users and developers. To ask a question, report a bug, make a feature request, or to get in touch for any reason, please make an Issue.
Contribute to umami
All contributions are welcome and appreciated. Feel free to:
- Make an issue to ask a question. Your question will help others in the future.
- Make an issue to report a
bug or a potential improvement. We will work to fix it. If you have an idea
about how to fix it, please feel free to propose it, or make a Pull Request.
- Fork the repository, make changes to the source code on a development branch, and submit a Pull Request to have your changes brought into the umami repository. No contribution to the code base or documentation is too small.
Contributors and maintainers to this project are are expected to abide the Contributor Code of Conduct.
Cite umami
Umami is described by a Journal of Open Source Software paper. If you use umami in your research, please cite it.
JOSS Publication
umami: A Python package for Earth surface dynamics objective function construction
Authors
University of Colorado at Boulder, Department of Geological Sciences, University of Colorado at Boulder, Cooperative Institute for Research in Environmental Sciences
University of Colorado at Boulder, Community Surface Dynamics Modeling System Integration Facility, University of Colorado at Boulder, Institute for Arctic and Alpine Research
University of Colorado at Boulder, Department of Geological Sciences, University of Colorado at Boulder, Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Community Surface Dynamics Modeling System Integration Facility
Editor
Marie E. Rognes
Tags
landscape evolution geomorphology hydrology surface processes calibration validation model analysis model-data comparison objective functionGitHub Events
Total
Last Year
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Katy Barnhart | k****t@g****m | 194 |
| mcflugen | m****n@g****m | 4 |
| Greg Tucker | g****r@c****u | 3 |
| Daniel S. Katz | d****z@i****g | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 7
- Total pull requests: 23
- Average time to close issues: 27 days
- Average time to close pull requests: about 20 hours
- Total issue authors: 1
- Total pull request authors: 4
- Average comments per issue: 3.86
- Average comments per pull request: 0.83
- Merged pull requests: 22
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- kbarnhart (7)
Pull Request Authors
- kbarnhart (20)
- gregtucker (1)
- mcflugen (1)
- danielskatz (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
-
Total downloads:
- pypi 250 last-month
-
Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 1
(may contain duplicates) - Total versions: 20
- Total maintainers: 1
pypi.org: umami
Umami calculates landscape metrics
- Homepage: https://github.com/TerrainBento/umami/
- Documentation: https://umami.readthedocs.io/
- License: MIT
-
Latest release: 2.0.0
published almost 6 years ago
Rankings
Maintainers (1)
conda-forge.org: umami
Umami is a package for calculating objective functions or objective function components for landscape evolution modeling. Umami offers two primary classes: a Residual which represents the difference between model and data, and Metric which is a calculated value on either model or data. A set of currently supported calculations are found in the umami.calculations submodule. Umami is built on top of the Landlab Toolkit and designed to work well with terrainbento.
- Homepage: https://umami.readthedocs.io
- License: MIT
-
Latest release: 2.0.0
published almost 6 years ago
Rankings
Dependencies
- sphinxcontrib_github_alt *
- scipy *