roughness
Predict illumination of planetary surfaces accounting for roughness.
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 6 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (16.2%) to scientific vocabulary
Repository
Predict illumination of planetary surfaces accounting for roughness.
Basic Info
- Host: GitHub
- Owner: NAU-PIXEL
- License: mit
- Language: Python
- Default Branch: main
- Size: 35 MB
Statistics
- Stars: 5
- Watchers: 3
- Forks: 1
- Open Issues: 3
- Releases: 4
Metadata Files
README.md
Roughness
A python package for predicting the thermal emission from anisothermal rough planetary surfaces.
Documentation
See full documentation at nau-pixel.github.io/roughness
See usage examples at nau-pixel.github.io/roughness/examples
Installation
To clone and run the package, you'll need Git and Poetry installed on your computer.
```bash
Clone this repository
$ git clone git@github.com:NAU-PIXEL/roughness.git
Enter the repository
$ cd roughness
Install dependencies into a venv with poetry
$ poetry install
Run setup script (may take awhile)
$ poetry run python setup_roughness.py
Now you can open a Jupyter server...
$ poetry run python jupyter notebook
or activate the venv directly from the terminal...
$ poetry shell $ python
or activate the venv from your favorite IDE
The venv is located at ~/roughness/.venv/bin/python
```
Contribute
This package is a work in progress. We appreciate any and all contributions in the form of bug reports & feature requests on our issues page, or as pull requests (see contributing guide for more details).
References and citation
This package is adapted from code by the late Dr. J. L. Bandfield. You can read more about the first iterations of this code in Bandfield et al. (2015) and Bandfield et al. (2018).
Please cite this software using the DOI of the latest version provided on Zenodo.
License
Copyright (c) 2023, Christian J. Tai Udovicic
Owner
- Name: NAU-PIXEL
- Login: NAU-PIXEL
- Kind: organization
- Repositories: 2
- Profile: https://github.com/NAU-PIXEL
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Tai Udovicic"
given-names: "Christian J."
orcid: "https://orcid.org/0000-0001-9972-1534"
- family-names: "Haberle"
given-names: "Christopher W."
- family-names: "Edwards"
given-names: "Christopher S."
- family-names: "Bandfield"
given-names: "Joshua L."
contact:
- affiliation: "Northern Arizona University (NAU)"
email: "cjtu@nau.edu"
family-names: "Tai Udovicic"
given-names: "Christian J."
title: "Roughness"
abstract: "Illumination of rough planetary surfaces."
doi: 10.5281/zenodo.5498089
license: MIT
repository-code: "https://github.com/NAU-PIXEL/roughness"
type: "software"
url: https://nau-pixel.github.io/roughness/
GitHub Events
Total
- Watch event: 1
- Push event: 2
Last Year
- Watch event: 1
- Push event: 2
Dependencies
- 133 dependencies
- black 20.8b1 develop
- jupyter ^1.0 develop
- jupytext ^1.11.2 develop
- matplotlib ^3.4.1 develop
- mkdocs-material ^6.1.5 develop
- pre-commit ^2.13.0 develop
- pylint ^2.6.0 develop
- pytest ^6.0 develop
- pytest-cov ^2.10.1 develop
- netCDF4 ^1.5.7
- numpy ^1.19.5
- python ^3.8,<3.10
- rasterio ^1.2.8
- rioxarray ^0.11.1
- scipy ^1.7.1
- xarray ^2022.3.0
- actions/cache v2 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- snok/install-poetry v1.1.4 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/setup-python v1 composite
- actions/checkout v2 composite
- actions/setup-python v1 composite