https://github.com/tylerjereddy/py_sphere_voronoi

Python utility code for handling spherical Voronoi Diagrams
https://github.com/tylerjereddy/py_sphere_voronoi

Last synced: 3 months ago
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Python utility code for handling spherical Voronoi Diagrams

• Host: GitHub
• URL: https://github.com/tylerjereddy/py_sphere_voronoi
• Owner: tylerjereddy
• License: mit
• Created: 2014-10-01T15:18:02.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2016-07-21T10:02:50.000Z (over 8 years ago)
• Last Synced: 2023-02-26T00:26:47.383Z (almost 2 years ago)
• Language: Jupyter Notebook
• Size: 11 MB
• Stars: 26
• Watchers: 5
• Forks: 14
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
Voronoi diagrams on the surface of a Sphere

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**Update: Please use `scipy 0.18` (`scipy.spatial.SphericalVoronoi`) for performing spherical Voronoi diagram calculations in Python -- the most robust version of the code is there, while this repo mostly exists for historical reasons and may contain bugs that have been patched by the collaborative work implementing the algorithm into scipy.**

Note that the most robust version of this code is now in a scipy PR: https://github.com/scipy/scipy/pull/5232

Slides from PyData London 2015 presentation about this package: https://www.slideshare.net/slideshow/embed_code/key/1bKCEyHa789nBe

A Python module for obtaining Voronoi diagrams on the surfaces of spheres, including the calculation of Voronoi region surface areas. Applications may range from calculating area per lipid in spherical viruses to geographical parsing.

The documentation for the project is available here: http://py-sphere-voronoi.readthedocs.org/en/latest/voronoi_utility.html

This project is still in development and some of the algorithm weaknesses are highlighted in the above documentation.

Please cite: [![DOI](https://zenodo.org/badge/6247/tylerjereddy/py_sphere_Voronoi.svg)](http://dx.doi.org/10.5281/zenodo.13688)

For contributions:

  * ensure most/all unit tests pass (run: nosetests)

  * ensure all doctests pass (run: python voronoi_utility.py)

  * if you import new modules, you may need to mock them in the Sphinx conf.py documentation file so that the docs are properly compiled by readthedocs

  * attempt to match the [numpy documentation standard](https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt) as closely as possible