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https://github.com/nikdon/pyentropy
Entropy for Python
https://github.com/nikdon/pyentropy
entropy multiscale numpy permutation python sample
Last synced: about 4 hours ago
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Entropy for Python
- Host: GitHub
- URL: https://github.com/nikdon/pyentropy
- Owner: nikdon
- License: apache-2.0
- Created: 2015-02-27T20:53:15.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2025-01-14T11:06:15.000Z (1 day ago)
- Last Synced: 2025-01-14T12:22:20.236Z (1 day ago)
- Topics: entropy, multiscale, numpy, permutation, python, sample
- Language: Python
- Homepage: https://donets.org/projects/pyentropy/
- Size: 556 KB
- Stars: 337
- Watchers: 15
- Forks: 88
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# pyEntropy (pyEntrp)
1. [Quick start](#quick-start)
2. [Usage](#usage)
3. [Contributors and participation](#contributors-and-participation)
pyEntropy is a lightweight library built on top of NumPy
that provides functions for computing various types of entropy for time series analysis.
The library currently supports the following types of entropy computation:
+ Shannon Entropy ```shannon_entropy```
+ Sample Entropy ```sample_entropy```
+ Multiscale Entropy ```multiscale_entropy```
+ Composite Multiscale Entropy ```composite_multiscale_entropy```
+ Permutation Entropy ```permutation_entropy```
+ Multiscale Permutation Entropy ```multiscale_permutation_entropy```
+ Weighted Permutation Entropy ```weighted_permutation_entropy```
## Quick start
Install [pyEntropy](https://github.com/nikdon/pyEntropy) using pip:
```
pip install pyentrp
```
Install [pyEntropy](https://github.com/nikdon/pyEntropy) using poetry:
```
poetry add pyentrp
```
## Usage
```python
from pyentrp import entropy as ent
import numpy as np
ts = [1, 4, 5, 1, 7, 3, 1, 2, 5, 8, 9, 7, 3, 7, 9, 5, 4, 3]
std_ts = np.std(ts)
sample_entropy = ent.sample_entropy(ts, 4, 0.2 * std_ts)
```
## Contributors and participation
[pyEntropy](https://github.com/nikdon/pyEntropy) is an open-source project, and contributions are highly encouraged.
If you would like to contribute, you can:
- [Fork the repository](https://github.com/nikdon/pyEntropy/fork) and submit pull requests with your improvements, bug
fixes, or new features.
- Report any issues or bugs you encounter on the [issue tracker](https://github.com/nikdon/pyEntropy/issues).
- Help improve the documentation by
submitting [documentation improvements or corrections](https://github.com/nikdon/pyEntropy/issues?q=is%3Aissue+is%3Aopen+label%3Adocumentation).
- Participate in discussions and share your ideas.
The following contributors have made significant contributions to pyEntropy:
* [Nikolay Donets](https://github.com/nikdon)
* [Jakob Dreyer](https://github.com/jakobdreyer)
* [Raphael Vallat](https://github.com/raphaelvallat)
* [Christopher Schölzel](https://github.com/CSchoel)
* [Sam Dotson](https://github.com/samgdotson)
Contributions are very welcome, documentation improvements/corrections, bug reports, even feature requests :)
If you find [pyEntropy](https://github.com/nikdon/pyEntropy) useful, please consider giving it a star.
Your support is greatly appreciated!