Cover Tree
This is a Python implementation of cover trees, a data structure for finding nearest neighbors in a general metric space (e.g., a 3D box with periodic boundary conditions).
Updated for Python 3.7 from Patrick Varilly's code.
The implementation here owes a great deal to PyCoverTree, by Thomas Kollar, Nil Geisweiller, Emanuele Olivetti.
The API follows that of Anne M. Archibald's KD-tree implementation for scipy;
the default metric has been set to euclidean distance, so the CoverTree class
can be used exactly as a drop in replacement for
scipy.spatial.KDTree.
References
Cover trees are described in two papers, for which PDF copies are included
in the references directory:
A. Beygelzimer, S. Kakade, & J. Langford (2006) Cover Trees for Nearest Neighbor, 23rd International Conference on Machine Learning
D. R. Karger & M. Ruhl (2002) Finding Nearest Neighbors in Growth-restricted Metrics, 34th Symposium on the Theory of Computing.
(both originate from this page)
1 maintainer
Metadata
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Release files for covertree 1.0.0
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