[日本語](https://ohara-lab-su.github.io/aenet_env/ja/index.html) | [English](https://ohara-lab-su.github.io/aenet_env/en/index.html) | [GitHub](https://github.com/ohara-lab-su/aenet_env)

# Installation and environment

## aenet_env

From the repository root, run `python -m pip install -e .`. Check the actual `pyproject.toml` for dependencies. Use `aenet_env-install` to copy packaged workflow templates into the working directory; existing files are protected by default. Use `aenet_env-install --force` only when intentional replacement is required. Verify the command is available in the installed release.

## Build and install ænet

```bash
git clone https://github.com/atomisticnet/aenet.git
cd aenet
cmake -S . -B build -DBUILD_AENET=ON
cmake --build build --target build_all
```

Example with Intel oneAPI Fortran and MKL (compiler path is site-specific):

```bash
cd ~/aenet
git clone https://github.com/atomisticnet/aenet.git build_aenet
cd build_aenet
cmake -S . -B build \
  -DCMAKE_Fortran_COMPILER=/opt/intel/oneapi/compiler/2023.2.1/linux/bin/ifx \
  -DUSE_MKL=ON -DBUILD_AENET=ON
cmake --build build --target build_all -j 8
cmake --install build --prefix /home/hpc/aenet
```

The installation places `generate.x`, `train.x`, and `predict.x` under `/home/hpc/aenet/bin/`, with tools such as `fingerprint.x`, `neighbors.x`, `trnset_info.x`, and `trnset2ASCII.x` under `tools/`. **After installation**, run `aenet config --set-aenet-path /home/hpc/aenet` and verify the executable paths configured by the Python frontend. An unqualified `cmake --install build` may install to a different prefix.

## External requirements

VASP (separate license), PAW datasets, `vasp_util`, ænet Python bindings, and optionally PyTorch are required for the relevant stages. `b03` needs a cluster scheduler and job script. The standalone ænet-PyTorch path needs a separate trainer and format converters. Fortran and PyTorch training paths are not interchangeable by assumption.

## Build the bilingual documentation locally

```bash
python -m pip install -e .
python -m pip install sphinx myst-parser sphinx-rtd-theme linkify-it-py
bash docs/build.sh
```

Output is under `docs/_build/html/en/` and `docs/_build/html/ja/`.


Related: [v0.0.3 project guide based on the current README](project_readme.md).