Installation

pip

dxtb can easily be installed with pip.

pip install dxtb[libcint]

Installing the libcint interface is highly recommended, as it is significantly faster than the pure PyTorch implementation and provides access to higher-order multipole integrals and their derivatives. However, the interface is currently only available on Linux.

conda

dxtb is also available on conda from the conda-forge channel.

mamba install dxtb

Don’t forget to install the libcint interface (not on conda) via pip install tad-libcint.

For Windows, dxtb is not available via conda, because PyTorch itself is not registered in the conda-forge channel.

From source

This project is hosted on GitHub at grimme-lab/dxtb. Obtain the source by cloning the repository with

git clone https://github.com/grimme-lab/dxtb
cd dxtb

We recommend using a conda environment to install the package. You can setup the environment manager using a mambaforge installer. Install the required dependencies from the conda-forge channel.

mamba env create -n torch -f environment.yaml
mamba activate torch

Install this project with pip in the environment

pip install .

Without pip

If you want to install the package without pip, start by cloning the repository.

DEST=/opt/software
git clone https://github.com/grimme-lab/dxtb $DEST/dxtb

Next, add <path to dxtb>/dxtb/src to your $PYTHONPATH environment variable. For the command line interface, add <path to dxtb>/dxtb/bin to your $PATH environment variable.

export PYTHONPATH=$PYTHONPATH:$DEST/dxtb/src
export PATH=$PATH:$DEST/dxtb/bin

Dependencies

The following dependencies are required

• numpy

• opt_einsum

• psutil

• scipy

• tad-mctc

• tad-multicharge

• tad-dftd3

• tad-dftd4

• tad-libcint

• torch

For tests, we also require

• pytest

• pyscf

• tox