Fréchet ChemNet Distance

PyPI Tests (master) Tests (dev) PyPI - Downloads GitHub release (latest by date) GitHub release date GitHub

Code for the paper "Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery" JCIM / ArXiv

Installation

You can install FCD using

pip install fcd

or run the example notebook on Google Colab .

Requirements

numpy
torch
scipy
rdkit

Updates

Version 1.1 changes

Got rid of unneeded imports
load_ref_model doesn't need an argument any more to load a model.
canonical and canonical_smiles now return None for invalid smiles.
Added get_fcd as a quick way to get a the fcd score from two lists of smiles.

Version 1.2 changes

Ported the package to pytorch with the help of https://github.com/insilicomedicine/fcd_torch
pytorch allows a lighter package and is more popular than Tensorflow which saves an additional install

Metadata

Release files for fcd 1.2.2

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

Source distribution (sdist)

Source distribution for fcd 1.2.2
File	Size	Uploaded	Provenance
fcd-1.2.2.tar.gz	15.1 MB	Apr 1, 2024	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for fcd 1.2.2
File	Interpreter	ABI	Platform	Reset
fcd-1.2.2-py3-none-any.whl 5.2 MB Apr 1, 2024 Without provenance	Python 3	none	any	Details

Total release size: 20.4 MB

Release files / fcd-1.2.2.tar.gz

Download URL	fcd-1.2.2.tar.gz
Size	15.1 MB
Tags	Source
SHA-256 checksum How to use checksums	`c76735ed2aba248a54425430cfe95e42c760a8d498c275dbf65a050492fb62fc`
BLAKE2b-256 checksum How to use checksums	`e3a7b367257dfbe60ac39c66fecadb42684c07831f85e2643efbb01e9f491477`
Upload date	Apr 1, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.0.0 CPython/3.11.3`

Release files / fcd-1.2.2-py3-none-any.whl

Download URL	fcd-1.2.2-py3-none-any.whl
Size	5.2 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`9d8284a4d886778db787bc2653678bd050b358bc0a9c4ff835721edf301facda`
BLAKE2b-256 checksum How to use checksums	`7f62d487f9a5ffd54ef4e29b3581a252589666e5e56e62fe3336d4b30f3b9c5f`
Upload date	Apr 1, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.0.0 CPython/3.11.3`

Security for fcd 1.2.2

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.