Metadata-Version: 2.3
Name: GeoCS
Version: 1.0.3
Summary: Coherent sets for Geophysical trajectories.
Project-URL: Documentation, https://geocs.readthedocs.io/
Project-URL: Repository, https://github.com/hschoeller/GeoCS
Author-email: Henry Schoeller <h.schoeller@posteo.de>
Maintainer-email: Henry Schoeller <h.schoeller@posteo.de>
License: MIT License
        
        Copyright (c) [2024] [Henry Schoeller]
        
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License-File: LICENSE.txt
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Oceanography
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.8
Requires-Dist: alphashape
Requires-Dist: cartopy
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: seaborn
Provides-Extra: docs
Requires-Dist: furo; extra == 'docs'
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Description-Content-Type: text/markdown

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[![DOI](https://zenodo.org/badge/777665015.svg)](https://doi.org/10.5281/zenodo.14899385)

# GeoCS

A package to calculate coherent sets from geospatial trajectory data.

## Installation

```bash
pip install GeoCS
```

## Quick Start

The package follows object orientation and is centered around classes handling trajectories (Traj), point-wise distances (Dist), point-cloud boundaries (Bound), and diffusion maps (DiffMap). Each class can be calculated, saved, loaded and plotted.

```
from GeoCS import Traj, Dist, Bound, DiffMap
from datetime import datetime

T = Traj(path_to_your_trajectories, datetime(Y, M, D, H))
T.load()

r = 1e5  # cut-off radius
k = 15  # scaling parameter

D = Dist(path_to_distances, r=r, k=k, traj_data=T)
D.save()

B = Bound(path_to_boundaries, k=k, convex=True, traj_data=T)
B.save()

eps = 1e5  # diffusion bandwidth
DM = DiffMap(path_to_diffusion_maps, eps=eps, bound_data=B, dist_data=D)

DM.save()

DM.plot()
```

## Documentation

Full documentation is available on readthedocs: [https://geocs.readthedocs.io/](https://geocs.readthedocs.io/).

Project repository is at github: [https://github.com/hschoeller/GeoCS](https://github.com/hschoeller/GeoCS)

## Citation

If you use this package in your research, please cite it as:

**Schoeller, Henry (2025). GeoCS (Version 1.0.3). Zenodo.**  
[https://doi.org/10.5281/zenodo.14899385](https://doi.org/10.5281/zenodo.14899385)

## License:

Licensed under the [MIT License](https://github.com/hschoeller/GeoCS/blob/main/LICENSE).

## Credits:

Development has been financed by the DFG funded [CRC 1114](https://www.mi.fu-berlin.de/en/sfb1114/index.html).

Largely based on theory laid out in Banisch & Koltai, 2017. Application and extension in the context of atmospheric flow will be detailed in future publication (Schoeller et. al, 2025). Preprint is available as:

Schoeller, H., Chemnitz, R., Koltai, P., Engel, M., and Pfahl, S.: Assessing Lagrangian Coherence in Atmospheric Blocking, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-2173, 2024. 

Banisch, Ralf and P ́eter Koltai (Mar. 2017). “Understanding the Geometry of Transport: Diffusion Maps for Lagrangian Trajectory Data Unravel Coherent Sets”. In: Chaos 27.3, p. 035804. issn: 1054-1500, 1089-7682. doi: 10.1063/1.4971788.