mir-flare 0.0.1

Fast Learning of Atomistic Rare Events

FLARE: Fast Learning of Atomistic Rare Events

FLARE is an open-source Python package for creating fast and accurate atomistic potentials. Documentation of the code is in progress, and can be accessed here: https://flare.readthedocs.io/

Prerequisites

1. To train a potential on the fly, you need a working installation of Quantum ESPRESSO or CP2K.
2. FLARE requires Python 3 with the packages specified in requirements.txt. This is taken care of by pip.

Installation

FLARE can be installed in two different ways.

1. Download and install automatically:

   pip install git+https://github.com/mir-group/flare.git
   

2. Download this repository and install (required for unit tests):

   git clone https://github.com/mir-group/flare
   cd flare
   pip install .
   

Tests

We recommend running unit tests to confirm that FLARE is running properly on your machine. We have implemented our tests using the pytest suite. You can call pytest from the command line in the tests directory to validate that Quantum ESPRESSO or CP2K are working correctly with FLARE.

Instructions (either DFT package will suffice):

pip install pytest
cd tests
PWSCF_COMMAND=/path/to/pw.x CP2K_COMMAND=/path/to/cp2k pytest

References

[1] Jonathan Vandermause, Steven B. Torrisi, Simon Batzner, Alexie M. Kolpak, and Boris Kozinsky. On-the-fly Bayesian active learning of interpretable force fields for atomistic rare events. https://arxiv.org/abs/1904.02042