kdtree

0.16 verified Fri May 01 auth: no python maintenance

A Python implementation of a kd-tree for efficient spatial searching. Current version 0.16. Intermittent releases, last updated 2017.

pip install kdtree

Common errors

error ModuleNotFoundError: No module named 'kdtree' ↓

cause The library is not installed.

fix

Run 'pip install kdtree'

error AttributeError: 'KDTree' object has no attribute 'search_nn' ↓

cause Method renamed in newer versions.

fix

Use 'search_nearest' instead of 'search_nn'.

error TypeError: __init__() takes at least 2 arguments (1 given) ↓

cause KDTree requires a list of points as argument.

fix

Create tree with points: tree = KDTree([(1,2), (3,4)])

Warnings

breaking The 'search_nn' method returns a single result in older versions; newer versions return a list. ↓

fix Upgrade to >=0.12 and use 'search_nearest' for consistent single-result behavior.

deprecated The 'add' method does not exist in v0.16; use the constructor to build the tree. ↓

fix Pass all points at construction time: KDTree(points).

gotcha Points must be tuples/lists of numbers; mixing types (e.g., int and float) is fine, but non-numeric types cause errors. ↓

fix Ensure all point coordinates are numeric (int or float).

Imports

KDTree
wrong
```
import kdtree
```
correct
```
from kdtree import KDTree
```
Avoid using 'import kdtree' because then you need to qualify everything as kdtree.KDTree, which is not typical usage.
create
```
from kdtree import KDTree
```
There is no 'create' function; you instantiate KDTree directly.

Quickstart

Create a kd-tree from points and perform a nearest neighbor search.

from kdtree import KDTree

# Create a KDTree from a list of points (each point is a tuple)
points = [(2, 3), (5, 4), (9, 6), (4, 7), (8, 1), (7, 2)]
tree = KDTree(points)

# Search for the nearest neighbor to a query point
query = (9, 2)
nearest = tree.search_nearest(query)
print(f'Nearest neighbor to {query}: {nearest}')