PyPI version zenodo

calorine#

calorine is a Python library for constructing and sampling neuroevolution potential (NEP) models via the GPUMD package. It provides ASE calculators, IO functions for reading and writing GPUMD input and output files, as well as a Python interface that allows inspection of NEP models.

Training analysis
_images/parity-plot.png
Training NEP models
Model manipulation
_images/model-analysis.png
Analyzing NEP models
Phonon dispersions
_images/phonon-dispersion.png
Working with NEP models
Free energy analysis
_images/phase-diagram.png
Working with NEP models

The following snippet illustrates how a CPUNEP calculator instance can be created given a NEP potential file, and how it can be used to predict the potential energy, forces, and stress for a structure.

from ase.io import read
from ase.build import bulk
from calorine.calculators import CPUNEP

structure = bulk('PbTe', crystalstructure='rocksalt', a=6.7)
calc = CPUNEP('nep-PbTe.txt')
structure.calc = calc

print('Energy (eV):', structure.get_potential_energy())
print('Forces (eV/Å):\n', structure.get_forces())
print('Stress (eV/Å^3):\n', structure.get_stress())

Information on how to install calorine as well as a large number of tutorials can be found in the get started section. A detailed function reference is provided in the reference section.

Note

Please consult the credits page for information on how to cite calorine if you use it in your publications or derived packages. calorine and its development are hosted on gitlab.