Metadata-Version: 2.3
Name: GeoCS
Version: 1.0.2
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]
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
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'
Requires-Dist: myst-parser>=0.13; extra == 'docs'
Requires-Dist: sphinx-autodoc-typehints; extra == 'docs'
Requires-Dist: sphinx-copybutton; extra == 'docs'
Requires-Dist: sphinx>=4.0; extra == 'docs'
Description-Content-Type: text/markdown

<!-- SPHINX-START -->

[![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 1.0.2). 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).

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.