Installation Guide

Installation with pip

One way to install MLatom is to use command:

python3 -m pip install -U MLatom

Then you can use MLatom by simply running command:

mlatom [options]

Installation from a zipped package

Alternatively, you can download a zipped package with MLatomPy (requires Python 3.7+) and a statically compiled binary of MLatomF and for Linux systems. These files can be unpacked in any directory and used directly without any modifications to the environment variables etc. You may need to make files executable by using command line option chmod +x MLatomF

You can also add your MLatom path into the $PATH variable with the command (in bash):

export PATH=$PATH:/path/to/MLatom

It is convenient to add this line to .bashrc file.

Installation instructions for enabling interfaced third-party programs, see below.

To run MLatom provide a path to and the necessary command-line options (see in the next section), i.e. in your terminal type:

$pathToMLatom/ [command-line options or the name of an input file with options]

Installation of third-party packages

MLatom provides interfaces to some third-party software. 


1. download installer for DeePMD-kit from GitHub (tested v1.2.2)

2. run installer

3. add environmetal variable $DeePMDkit that point to the where dp binary is located (bin/ in your installation directory)

e.g. export DeePMDkit=/export/home/fcge/deepmd-kit-1.2/bin


1. compile QUIP and GAP from source

1.1 install prerequisites

sudo apt-get install gcc gfortran python python-pip libblas-dev liblapack-dev (for system uses apt, do equivalent for your OS)
pip install numpy ase f90wrap

1.2 get source code of QUIP and GAP

git clone --recursive

Get source code of GAP from (form-filling required).
Then put source code in QUIP/src/.

1.3 compile

export QUIP_ARCH=linux_x86_64_gfortran_openmp # enable multi-threading, use 'export QUIP_ARCH=linux_x86_64_gfortran' if no OpenMP thus no MT capability
export QUIPPY_INSTALL_OPTS=--user # omit for a system-wide installation
make config 

Enter Y for gap or edit build/linux_x86_64_gfortran/  with HAVE_GAP=1, then:

Built binaries are in QUIP/build/linux_x86_64_gfortran/quip and QUIP/build/linux_x86_64_gfortran/gap_fit.

2. add environmetal variable $quip and $gap_fit for quip and gap_fit

e.g. export quip='/export/home/fcge/GAP-SOAP/QUIP/build/linux_x86_64_gfortran_openmp/quip'
export gap_fit='/export/home/fcge/GAP-SOAP/QUIP/build/linux_x86_64_gfortran_openmp/gap_fit'

visit for more info.


1. install Numpy and nightly version of PyTorch

pip install numpy
pip install --pre torch torchvision -f \

2. install TorchANI

pip install torchani

Visit for more info.


1. clone form PhysNet‘s GitHub page

git clone

2. install TensorFlow:

pip install tensorflow

3. if you useTensorFlow v2, you need to execute the command below in PhysNet’s directory to make the scripts compatible with TFv2.

for i in `find . -name '*.py'`; do sed -i -e 's/import tensorflow as tf/import tensorflow.compat.v1 as tf\ntf.disable_v2_behavior()/g' -e 's/import tensorflow as tf/import tensorflow.compat.v1 as tf\ntf.disable_v2_behavior()/g' $i; done

4. add environmetal variable $PhysNet to the directory

e.g. export PhysNet=/export/home/fcge/PhysNet/


1. install sGDML

pip install sgdml==0.4.4

2. add the path of sGDML binary to environmetal variable $sGDML

e.g. export sGDML=/export/home/fcge/.linuxbrew/bin/sgdml

Visit for more info