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Pure Python implementation of d-dimensional AABB tree.

Project description

AABBTree - Axis-Aligned Bounding Box Trees

Continuous Integration Coverage License


GitHub Repository ReadTheDocs Documentation PyPI PyPI

AABBTree is a pure Python implementation of a static d-dimensional axis aligned bounding box (AABB) tree. It is inspired by Introductory Guide to AABB Tree Collision Detection from Azure From The Trenches.


Left: An AABB tree, leaves numbered by insertion order. Right: The AABBs and their bounding boxes.


AABBTree is available through PyPI and can be installed by running:

pip install aabbtree

To test that the package installed properly, run:

python -c "import aabbtree"

Alternatively, the package can be installed from source by downloading the latest release from the AABBTree repository on GitHub. Extract the source and, from the top-level directory, run:

pip install -e .

The --user flag may be needed, depending on permissions.


The following example shows how to build an AABB tree and test for overlap:

>>> from aabbtree import AABB
>>> from aabbtree import AABBTree
>>> tree = AABBTree()
>>> aabb1 = AABB([(0, 0), (0, 0)])
>>> aabb2 = AABB([(-1, 1), (-1, 1)])
>>> aabb3 = AABB([(4, 5), (2, 3)])
>>> tree.add(aabb1, 'box 1')
>>> tree.does_overlap(aabb2)
>>> tree.overlap_values(aabb2)
['box 1']
>>> tree.does_overlap(aabb3)
>>> tree.add(aabb3)
>>> print(tree)
AABB: [(0, 5), (0, 3)]
Value: None
  AABB: [(0, 0), (0, 0)]
  Value: box 1
  Left: None
  Right: None
  AABB: [(4, 5), (2, 3)]
  Value: None
  Left: None
  Right: None


Documentation for the project is available at


Contributions to the project are welcome. Please visit the AABBTree repository to clone the source files, create a pull request, and submit issues.


If you use AABBTree in you work, please consider including this citation in your bibliography:

K. A. Hart and J. J. Rimoli, Generation of statistically representative microstructures with direct grain geomety control, Computer Methods in Applied Mechanics and Engineering, 370 (2020), 113242. (BibTeX) (DOI)

The incremental insertion method is discussed in section 2.2.2 of the paper.

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