Skip to main content
Yanked

This release has been yanked by its maintainers, and will be ignored by installers, except when explicitly specified.
Reason given by maintainers: Non-maintainer uploaded package to pypi without coordinating with maintainers, pypi package ownership was transferred amicably to maintainers. Pypi releases of openforcefield software may be available at a later date, but issues with unavailable dependencies need to be resolved first.

OpenFF Recharge

Test status CI Status pre-commit.ci status
Code quality pre-commit Codecov coverage
Latest release GitHub release (latest by date including pre-releases)
User support Documentation Status Discussions

OpenFF Recharge aims to provide a comprehensive suite of tools for training the partial charges of molecules against quantum chemical electrostatic potential (ESP) and electric field data.

A focus is given to training 'charge-correction models' similar to the popular AM1BCC charge model, but support for other methods such as deriving RESP charges or training virtual sites on top of existing partial charges is also supported.

Warning - although a significant effort has been made to ensure the scientific validity of this framework (especially the hand-converted AM1BCC parameters), it is still under heavy development and much care should be taken when using it in production work.

Getting Started

To start using this framework we recommend looking over the documentation, especially the installation and quick start guides.

How to Cite

Please cite OpenFF Recharge using the Zenodo record of the latest release or the version that was used. The BibTeX reference of the latest release can be found here.

Features

The framework currently supports:

  • Generating QC ESP and electric field data

    • directly by interfacing with the Psi4 quantum chemical code
    • from wavefunctions stored within a QCFractal instance, including the QCArchive
  • Defining new charge models that contain

    • base QC (e.g. AM1 charges) or tabulated library / RESP charges
    • bond-charge corrections
    • virtual sites
  • A SMARTS port of the AM1BCC charge model

  • Generating RESP charges for multi-conformer molecules

  • Training charge(-correction) parameters by

    • the normal linear least squares method (fixed v-site geometries only)
    • gradient descent using pytorch or numpy
    • Bayesian methods using frameworks like pyro

License

The main package is release under the MIT license.

Copyright (c) 2020, Open Force Field Consortium

Metadata

Release files for openff-recharge 0.5.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for openff-recharge 0.5.3
File Size Uploaded
openff_recharge-0.5.3.tar.gz 120.1 kB Details

Release files / openff_recharge-0.5.3.tar.gz

Download URL openff_recharge-0.5.3.tar.gz
Size 120.1 kB
Tags Source
SHA-256 checksum
How to use checksums
3c6e069d8399ea6913c21395b69f460b7ea7ef9f22ab5b28f359f7399d50f0c9
BLAKE2b-256 checksum
How to use checksums
16b60f255c577857cd7bc66dcc6c4406fe28915f9f61cc2c544120b3a78341f6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.13

Release history Release notifications | RSS feed

This release

0.5.3 This release

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page