Installation & Set-up

Installation

Note

For the installation of the ænet binaries and library see the ænet website and the GitHub repository.

Note

PyTorch is only installed when requested explicitly, since it is a large dependency that can sometimes be difficult to install.

1. Package Install

Download the source code repository from GitHub aenet-python.

Install as usual. For example with

$ pip install .

from the repository’s root directory.

Per default, PyTorch and other requirements of the PyTorch-based features are not installed. To request those requirements as well, select them explicitly with

$ pip install ".[torch]"

This installs the core PyTorch dependency only. The PyTorch-based featurization and neighbor-list features also require the PyG extension packages torch-scatter and torch-cluster matched to the local torch build.

Recommended installation matrix:

# Core PyTorch support only
$ pip install ".[torch]"

# Full CPU PyTorch stack
$ pip install ".[torch]"
$ pip install torch-scatter torch-cluster -f https://data.pyg.org/whl/torch-${TORCH}+cpu.html

# Full CUDA PyTorch stack
$ pip install ".[torch]"
$ pip install torch-scatter torch-cluster -f https://data.pyg.org/whl/torch-${TORCH}+${CUDA}.html

Replace ${TORCH} with the installed torch version (for example 2.9.0) and ${CUDA} with the matching CUDA tag (for example cu124). If you are developing from a source checkout, the equivalent editable install is:

$ pip install -e ".[dev]"
$ pip install ".[torch]"
$ pip install torch-scatter torch-cluster -f https://data.pyg.org/whl/torch-${TORCH}+cpu.html

2. Configure ænet Fortran Binaries

To make aenet-python aware of the ænet binaries, the paths need to be configured. The following command runs an interactive dialog that works for standard installations

$ aenet config --set-aenet-path [path-to-aenet]

where [path-to-aenet] is the path pointing to the aenet root directory.