Python implementation of a K-D Tree as a pseudo-balanced Tree
Project description
kdtrees
Python implementation of a K-D Tree as a pseudo-balanced Tree
Overview
K-Dimensional Tree is a space-partitioning data structure, efficiently organizing points in k-dimensional space.
This K-D Tree implementation allows for construction, modification and searching of a K-D Tree. It also maintains the tree in a pseudo-balanced manner through a secondary invariant where every node is the median ± dimensionality of subsidiary nodes along a specific axis.
More details regarding this implementation can be found here
Installation
Dependencies
kdtrees requires:
- numpy
kdtrees is tested and supported on Python 3.4+ up to Python 3.7. Usage on other versions of Python is not guaranteed to work as intended.
User Installation
kdtrees can be easily installed using pip
pip install kdtrees
Changelog
See the changelog for a history of notable changes to kdtrees.
Development
kdtrees is fully implemented for basic functionality. However, it may not have every utility function or have the most optimized algorithms. We welcome new contributors of all experience lelevels to help grow and improve kdtrees. Guides on development, testing, and contribution are in the works!
Help and Support
Documentation
Documentation for kdtrees can be found here
Issues and Questions
Issues and Questions should be posed to the issue tracker here
Project details
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Source Distribution
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