First, you need to install Amesp. You can download it from the official website: https://www.amesp.xyz/download/. We also provide a compatible version of Amesp for your convenience.
We strongly recommend using python==3.9.0 to ensure optimal compatibility. and the datasets in https://zenodo.org/records/19156102
# Add Amesp binary directory to system PATH
export PATH=$PATH:/path/to/amesp/bin/
# Create a dedicated Conda environment with Python 3.9.0
mamba create -n deepatb2 python=3.9.0 -y
# Activate the environment (critical step)
conda activate deepatb2
# Install Python dependencies
pip install -r requirements.txt
# Alternative: Install with Tsinghua PyPI mirror for faster download (China mainland)
pip install -r requirements.txt -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simplecd deepks-kit
cd deepks-kit
python setup.py install
A complete example job for Qm7BT is provided in the job directory. Follow the steps below to run the workflow:
cd job/01_prepare
# Generate Amesp input files (.aip) - charge and spin are set to 0 and 1 for all systems
python 00_xyzaip.py
# Run Amesp calculations - ensure all jobs complete successfully
sh 01_run.sh
# Generate atom.npy file in npydata directory
python 02_xyztoatomnpy.py --dir file
# Generate descriptor (dm_eig) in npydata directory
python 03_get_aTB_decriptor.py --dir file
# Generate energy label file
python 04_get_delta_energy.py
cd ../02_train # Navigate to training directory
# Start model training
sh train.sh
# Calculate predicted energies using the trained DeePaTB model
python get_deepatb_energy.py
! aTB
>ope
deephf on
end
>xyz 0 1
C -4.602780000000000 2.228670000000000 0.000000000000000
H -3.532780000000000 2.228670000000000 0.000000000000000
H -4.959440000000000 1.272170000000000 0.320630000000000
H -4.959440000000000 2.429240000000000 -0.988670000000000
H -4.959440000000000 2.984590000000000 0.668030000000000
end