Skip to main content

Graph Atomic Cluster Expansion (GRACE)

Project description

News

Important Note

If a model was fitted with gracemaker version < 0.5.1, it will not be compatible with newer versions due to a format change.
You can convert it to the new format using the following command:

grace_utils -p seed/1/model.yaml -c seed/1/checkpoint/checkpoint.best_test_loss.index update_model

This will generate new files with the "-converted" suffix, which you can replace the old files (model.yaml and checkpoints) with.

GRACE - GRaph Atomic Cluster Expansion

Project GRACEmaker is a heavily modified and in large parts rewritten version of the PACEmaker software geared towards support for multi-component materials and graph architectures.

Documentation

Please see documentation for installation instructions and examples.

Tutorial

You can find tutorial materials here

Also in a video format

Support

Also, you may join ACE support Zulip channel for additional resources: https://acesupport.zulipchat.com/join/xtwxu2grjbtg64m3vnhypi6p/

Reference

Please see

@article{lysogorskiy2025graph,
  title={Graph atomic cluster expansion for foundational machine learning interatomic potentials},
  author={Lysogorskiy, Yury and Bochkarev, Anton and Drautz, Ralf},
  journal={arXiv preprint arXiv:2508.17936},
  year={2025}
}
@article{PhysRevX.14.021036,
  title = {Graph Atomic Cluster Expansion for Semilocal Interactions beyond Equivariant Message Passing},
  author = {Bochkarev, Anton and Lysogorskiy, Yury and Drautz, Ralf},
  journal = {Phys. Rev. X},
  volume = {14},
  issue = {2},
  pages = {021036},
  numpages = {28},
  year = {2024},
  month = {Jun},
  publisher = {American Physical Society},
  doi = {10.1103/PhysRevX.14.021036},
  url = {https://link.aps.org/doi/10.1103/PhysRevX.14.021036}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tensorpotential-0.5.9.tar.gz (271.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tensorpotential-0.5.9-py3-none-any.whl (250.5 kB view details)

Uploaded Python 3

File details

Details for the file tensorpotential-0.5.9.tar.gz.

File metadata

  • Download URL: tensorpotential-0.5.9.tar.gz
  • Upload date:
  • Size: 271.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for tensorpotential-0.5.9.tar.gz
Algorithm Hash digest
SHA256 595d31c6993bf1fa2c34fd9c0b1876b66141b893add838c960f9f1e3c4464d26
MD5 0fc12563839dd261dda18a0b91ca6e03
BLAKE2b-256 7d4db3b2536c0ff68c23a800d392f721e836dbe7ba39c07b4811d001a4609cd6

See more details on using hashes here.

File details

Details for the file tensorpotential-0.5.9-py3-none-any.whl.

File metadata

File hashes

Hashes for tensorpotential-0.5.9-py3-none-any.whl
Algorithm Hash digest
SHA256 3db58c6b2ab4e208b4b9af5d88418f651ac897304aa14bc9078727c5b00fa5cd
MD5 858ef6f16cbe4fff76e8fb15c1dd722c
BLAKE2b-256 21d3db0bf79f139c1f802eb3f00ca6ce35cccc492cc9473facab6bd46fc29f91

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page