A fast ball tree implementation for three dimensional (weighted) data with an Euclidean distance norm. The base implementation is in C and there is a wrapper for Python. The tree is optimised towards spatial correlation function calculations since it provides fast counting routinge, e.g. by implementing a dualtree query algorithm.

• Code: https://github.com/jlvdb/balltree.git
• Docs: https://balltree.readthedocs.io/
• PyPI: https://pypi.org/project/balltree/

Installation

A C library can be built with the provided make file, the python wrapper is automatically compiled and installed with pip install balltree.

The installation does not require any external C libraries, the python wrapper requires the Python.h header (which should be included in a default python installation) and numpy (including numpy/arrayobject.h).

Maintainers

• Jan Luca van den Busch (author, Ruhr-Universit??t Bochum, Astronomisches Institut)