Skip to main content

Semi-empirical potential fitting in Python

Project description

ForgeFF: semi-empirical potential fitting in Python

PyPI version Downloads GitHubActions

ForgeFF is a Python toolkit for fitting semi-empirical interatomic potentials. It keeps the model equations, parameter order, and fitting workflow explicit so the fundamentals stay easy to inspect and explain.

Install from PyPI with:

pip install ForgeFF

The recommended user-facing format is TOML:

  • custom analytic pair potentials
  • built-in analytical forms such as Morse and double-Morse
  • tabulated EAM and ADP term blocks
  • beginner-friendly examples for training, evaluation, grading, and calculators

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

forgeff-1.1.1.tar.gz (11.5 MB view details)

Uploaded Source

Built Distribution

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

forgeff-1.1.1-py3-none-any.whl (98.2 kB view details)

Uploaded Python 3

File details

Details for the file forgeff-1.1.1.tar.gz.

File metadata

  • Download URL: forgeff-1.1.1.tar.gz
  • Upload date:
  • Size: 11.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for forgeff-1.1.1.tar.gz
Algorithm Hash digest
SHA256 8cdd4be0796c69ab0b7180741ffb48ff03a8a03ff20e38a6bc31436d01346475
MD5 fa333ebaa806014b332c46a299b8c001
BLAKE2b-256 5249cafdcb7addf0cb0d5135e1b761713d2798317f594cf4a407f81dfaf67825

See more details on using hashes here.

Provenance

The following attestation bundles were made for forgeff-1.1.1.tar.gz:

Publisher: pypi.yml on prnvrvs/ForgeFF

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file forgeff-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: forgeff-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 98.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for forgeff-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4f4b580706a7b0dcfef92adf9f3799c93eb102b0c477532b9844f4da9946d30e
MD5 078242287140a0997993987c7cf993a2
BLAKE2b-256 60bf6cafaeabe9ba5209247a2d7ab6fa31d6c0eb9f97076957a91e23a6cfccc3

See more details on using hashes here.

Provenance

The following attestation bundles were made for forgeff-1.1.1-py3-none-any.whl:

Publisher: pypi.yml on prnvrvs/ForgeFF

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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