A package implementing a vantage-point data structure, for efficient nearest neighbor searching.
Project description
This package contains an implementation of a vantage-point tree data structure.
Installation
Simply install through pip:
pip install vptree
Example
Example usage:
import numpy as np
import vptree
# Define distance function.
def euclidean(p1, p2):
return np.sqrt(np.sum(np.power(p2 - p1, 2)))
# Generate some random points.
points = np.random.randn(20000, 10)
query = [.5] * 10
# Build tree in O(n log n) time complexity.
tree = vptree.VPTree(points, euclidean)
# Query single point.
tree.get_nearest_neighbor(query)
# Query n-points.
tree.get_n_nearest_neighbors(query, 10)
# Get all points within certain distance.
tree.get_all_in_range(query, 3.14)
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
vptree-1.3.tar.gz
(4.4 kB
view details)
File details
Details for the file vptree-1.3.tar.gz
.
File metadata
- Download URL: vptree-1.3.tar.gz
- Upload date:
- Size: 4.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.0 CPython/3.9.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a412a833a6ab18936b96c5e21177a462fb438b26d285e258cb836df8fd01a97d |
|
MD5 | 9684daa84576d299f4301918b871b552 |
|
BLAKE2b-256 | 38f5535b223cc11368d7b30059a72fc4a23797d509a6d491df6f3f3d99652bea |