Featomic
Featomic is a library for the efficient computing of representations for atomistic machine learning also called “descriptors” or “fingerprints”. These representations can be used for atomistic machine learning (ml) models including ml potentials, visualization or similarity analysis.
The core of the library is written in Rust and we provide APIs for C/C++ and Python as well.
List of implemented representations
representation |
description |
gradients |
|---|---|---|
Spherical expansion |
Atoms are represented by the expansion of their neighbor’s density on radial basis and spherical harmonics. This is the core of representations in SOAP (Smooth Overlap of Atomic Positions) |
positions, strain, cell |
SOAP radial spectrum |
Atoms are represented by 2-body correlations of their neighbors’ density |
positions, strain, cell |
SOAP power spectrum |
Atoms are represented by 3-body correlations of their neighbors’ density |
positions, strain, cell |
LODE Spherical Expansion |
Core of representations in LODE (Long distance equivariant) |
positions |
Sorted distances |
Each atom is represented by a vector of distance to its neighbors within the spherical cutoff |
no |
Neighbor List |
Each pair is represented by the vector between the atoms. This is intended to be used as a starting point for more complex representations |
positions |
AtomicComposition |
Obtaining the stoichiometric information of a system |
positions, strain, cell |
For details, tutorials, and examples, please have a look at our documentation.
Citing featomic
If you found featomic useful for your work, please cite the corresponding article:
F. Bigi, J.W. Abbott, P. Loche et al., Metatensor and metatomic: foundational libraries for interoperable atomistic machine learning, (2026). https://doi.org/10.1063/5.0304911
@article{bigi_metatensor_2026,
title = {Metatensor and Metatomic: {{Foundational}} Libraries for Interoperable Atomistic Machine Learning},
shorttitle = {Metatensor and Metatomic},
author = {Bigi, Filippo and Abbott, Joseph W. and Loche, Philip and Mazitov, Arslan and Tisi, Davide and Langer, Marcel F. and Goscinski, Alexander and Pegolo, Paolo and Chong, Sanggyu and Goswami, Rohit and Febrer, Pol and Chorna, Sofiia and Kellner, Matthias and Ceriotti, Michele and Fraux, Guillaume},
year = 2026,
month = feb,
journal = {J. Chem. Phys.},
volume = {164},
number = {6},
pages = {064113},
issn = {0021-9606},
doi = {10.1063/5.0304911},
}2 maintainers
Metadata
2 maintainers
Release files for featomic 0.6.7
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| featomic-0.6.7.tar.gz | 319.2 kB | Without provenance | Details for featomic-0.6.7.tar.gz |
Built distributions (wheels)
| File | Actions Reset | |||
|---|---|---|---|---|
| featomic-0.6.7-py3-none-win_amd64.whl | Python 3 | none | Windows x86-64 | Details for featomic-0.6.7-py3-none-win_amd64.whl |
| featomic-0.6.7-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64 | Details for featomic-0.6.7-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl |
| featomic-0.6.7-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl | Python 3 | none | Linux glibc 2.17+ ARM64 | Details for featomic-0.6.7-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl |
| featomic-0.6.7-py3-none-macosx_11_0_x86_64.whl | Python 3 | none | macOS 11.0+ x86-64 | Details for featomic-0.6.7-py3-none-macosx_11_0_x86_64.whl |
| featomic-0.6.7-py3-none-macosx_11_0_arm64.whl | Python 3 | none | macOS 11.0+ ARM64 | Details for featomic-0.6.7-py3-none-macosx_11_0_arm64.whl |
Total release size: 6.0 MB
Release files / featomic-0.6.7.tar.gz
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