Installation

Install From PyPI

For normal use, install the latest released package from PyPI:

pip install AtomVoxelizer

Optional feature groups can be installed with extras:

pip install "AtomVoxelizer[analysis]"
pip install "AtomVoxelizer[examples]"
pip install "AtomVoxelizer[docs]"

The base package includes the NumPy VoxelGrid backend. Acceleration backends are optional packages installed directly when needed:

pip install numba
pip install taichi
# Choose the CuPy package matching your CUDA runtime, for example:
pip install cupy-cuda12x

Install From Source

Use the GitLab repository for development, local documentation builds, or unreleased changes:

git clone https://gitlab.com/tgmaxson/atomvoxelizer.git
cd atomvoxelizer
pip install -e ".[dev,examples]"

The canonical source repository is:

https://gitlab.com/tgmaxson/atomvoxelizer

Optional Feature Map

Feature	Install	Used by
Analysis	pip install "AtomVoxelizer[analysis]" or pip install scikit-image	connected components, marching cubes, scalar mesh extraction
Examples	pip install "AtomVoxelizer[examples]"	ASE structure loading, CIF examples, Wulff and surface examples
Quickstart tutorial	pip install ase wulffpack; install ORB separately for ORB-V3 MCMD	Wulff nanoparticle construction, voxel adsorption sites, and CO MCMD
Numba backend	pip install numba	VoxelGridNumba, FieldVoxelGridNumba, VectorVoxelGridNumba
CuPy backend	pip install cupy-cuda12x or the CuPy package matching your CUDA runtime	VoxelGridCuPy
Taichi backend	pip install taichi	VoxelGridTaichi and VoxelGridTaichiGPU
Documentation	pip install "AtomVoxelizer[docs]"	local Sphinx documentation builds
Publishing	pip install "AtomVoxelizer[publish]"	building and checking PyPI artifacts

See Contributing for development commands, testing, documentation builds, and release publishing.