Metadata-Version: 2.4
Name: fronttracker
Version: 1.0.0
Summary: Library for detection and monitoring of ocean fronts
Home-page: https://github.com/romeroqe/fronttracker
Author: Emmanuel Romero
Author-email: romeroqe@gmail.com
License: CC-BY-4.0
Classifier: Programming Language :: Python :: 3
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: geopy
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: scikit-image
Requires-Dist: shapely
Requires-Dist: alphashape
Requires-Dist: matplotlib
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# FrontTracker 
<a href="https://github.com/romeroqe/fronttracker"><img src="https://shields.io/github/v/release/romeroqe/fronttracker" alt="Release"></a>
<a href="https://pypi.org/project/fronttracker/"><img src="https://img.shields.io/pypi/v/fronttracker" alt="PyPI Version"></a>
<a href="http://creativecommons.org/licenses/by/4.0/"><img src="https://shields.io/github/license/romeroqe/fronttracker" alt="License"></a>
<a href="https://zenodo.org/badge/latestdoi/1062783898"><img src="https://zenodo.org/badge/1062783898.svg" alt="DOI"></a>

FrontTracker is a Python library for the segmentation, and analysis of oceanic fronts from satellite and reanalysis datasets. It integrates clustering, skeletonization, statistical and geometric analysis to provide robust descriptors of frontal structures, including position, intensity, orientation, eccentricity, and temporal evolution.

This methodology is suitable for both global and regional studies, enabling the monitoring of frontal dynamics, lifecycle events (formation, enhancement, splitting, merging, attenuation, and decay), and links with biogeochemical processes.

## Features
- Segmentation and skeletonization of frontal lines.  
- Extraction of geometric descriptors (length, width, eccentricity).  
- Statistical metrics from pixel distribution (kurtosis, skewness).  
- Tracking of fronts through time based on spatial overlap.  
- Compatible with satellite, model, and reanalysis data.  


## Installation
To use this methodology install it with:
```bash
pip install fronttracker
```

## Documentation

Full documentation and Jupyter demos are available in the [FrontTracker documentation page](https://romeroqe.github.io/fronttracker/).


## How to cite

> [!IMPORTANT]
> _A scientific publication related to FrontTracker is being reviewed by a journal, for now, you can use the Zenodo reference:_
> 
> Emmanuel Romero. (2025). romeroqe/fronttracker: FrontTracker (v1.0). Zenodo. https://doi.org/10.5281/zenodo.17187343

## License
  
<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.
