Skip to main content

For on-the-fly active learning of interatomic potentials.

Project description

Carcará logo

License: MIT PyPI

Carcará

🚧 (Under development) 🚧

Machine learning for atomistic simulations.

Installation

From pip

The easiest way to install Carcará is with pip:

pip install carcara

From github

To install Carcará directly from the GitHub repository, run the following commands:

pip install git+https://github.com/seixas-research/carcara.git

Getting started

Training

Evaluation

# TODO

License

This is an open source code under MIT License.

Acknowledgements

We thank financial support from FAPESP (Grant No. 2022/14549-3), INCT Materials Informatics (Grant No. 406447/2022-5), and CNPq (Grant No. 311324/2020-7).

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

carcara-26.4.11.tar.gz (21.7 MB view details)

Uploaded Source

Built Distribution

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

carcara-26.4.11-py3-none-any.whl (24.0 kB view details)

Uploaded Python 3

File details

Details for the file carcara-26.4.11.tar.gz.

File metadata

  • Download URL: carcara-26.4.11.tar.gz
  • Upload date:
  • Size: 21.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for carcara-26.4.11.tar.gz
Algorithm Hash digest
SHA256 3223be201605cac34beb5b355aabd18b2cec3234da9b5ffcf421139ef7bd0a26
MD5 24976d223e3592185116f93b575c89b8
BLAKE2b-256 80dfe07f76024a0ac3d6b8c794d65eef12660b456eb30db0947c9e333827a40c

See more details on using hashes here.

File details

Details for the file carcara-26.4.11-py3-none-any.whl.

File metadata

  • Download URL: carcara-26.4.11-py3-none-any.whl
  • Upload date:
  • Size: 24.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for carcara-26.4.11-py3-none-any.whl
Algorithm Hash digest
SHA256 0a5602580d6e3d0181cac5359d2840b8164757e75c29f56d39a1ea182040cad5
MD5 41f6c654a4af000eb6916db3018886fa
BLAKE2b-256 497e5c7516c06860e27c5cf963b16e20076e755ceca30ea4e5ad61bb10ee6579

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