https://github.com/ofgulban/compoda
Simplex space operations for compositional data implemented in Python.
https://github.com/ofgulban/compoda
barycentric-coordinates compositional-data compositional-data-analysis n-simplex simplex simplex-space simplices
Last synced: about 1 month ago
JSON representation
Simplex space operations for compositional data implemented in Python.
- Host: GitHub
- URL: https://github.com/ofgulban/compoda
- Owner: ofgulban
- License: bsd-3-clause
- Created: 2017-01-08T00:31:09.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2022-02-17T18:02:57.000Z (about 4 years ago)
- Last Synced: 2026-01-30T03:47:39.597Z (about 1 month ago)
- Topics: barycentric-coordinates, compositional-data, compositional-data-analysis, n-simplex, simplex, simplex-space, simplices
- Language: Python
- Homepage:
- Size: 442 KB
- Stars: 13
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
[](https://zenodo.org/badge/latestdoi/78312374) [](https://travis-ci.org/ofgulban/compoda) [](https://ci.appveyor.com/project/ofgulban/compoda)
[](https://codecov.io/gh/ofgulban/compoda)
# Compoda
Compositional data analysis tools implemented in python.
Currently, this library is primarily being developed for (but not limited to) magnetic resonance images with multiple contrasts. For further details, please see my paper **[here](https://www.ajs.or.at/index.php/ajs/article/view/743)** (or [here](https://arxiv.org/abs/1705.03457)).
## Dependencies
**[Python 3](https://www.python.org/)**
| Package | Tested version |
|---------------------------------------------------------|----------------|
| [NumPy](http://www.numpy.org/) | 1.15.4 |
| [Scipy](https://www.scipy.org/) | 1.2.0 |
#### Additionally required for example scripts:
| Package | Tested version |
|---------------------------------------------------------|----------------|
| [matplotlib](http://matplotlib.org/) | 3.0.2 |
| [NiBabel](http://nipy.org/nibabel/) | 2.2.1 |
## Installation
Run this command in your command line:
```bash
pip install compoda
```
or as an alternative
- Clone this repository and change directory to:
```bash
cd /path/to/compoda
```
- Install the requirements by running the following command:
```bash
pip install -r requirements.txt
```
- Install compoda:
```bash
python setup.py install
```
## Support
Please use [GitHub issues](https://github.com/ofgulban/compoda/issues) for questions, bug reports or feature requests.
## License
The project is licensed under [BSD-3-Clause](https://opensource.org/licenses/BSD-3-Clause).
## References
* [Compositional data analysis in a nutshell.](http://www.sediment.uni-goettingen.de/staff/tolosana/extra/CoDaNutshell.pdf)
* Aitchison, J. (1982). The Statistical Analysis of Compositional Data. Journal of the Royal Statistical Society, 44(2), 139–177.
* Aitchison, J. (2002). A Concise Guide to Compositional Data Analysis. CDA Workshop Girona, 24, 73–81.
* Pawlowsky-Glahn, V., Egozcue, J. J., & Tolosana-Delgado, R. (2015). Modelling and Analysis of Compositional Data. Chichester, UK: John Wiley & Sons, Ltd.