Fréchet ChEMNet Distance
Project description
Fréchet ChemNet Distance
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_modeldoesn't need an argument any more to load a model.canonicalandcanonical_smilesnow returnNonefor invalid smiles.- Added
get_fcdas 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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
fcd-1.2.2.tar.gz
(15.1 MB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
fcd-1.2.2-py3-none-any.whl
(5.2 MB
view details)
File details
Details for the file fcd-1.2.2.tar.gz.
File metadata
- Download URL: fcd-1.2.2.tar.gz
- Upload date:
- Size: 15.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c76735ed2aba248a54425430cfe95e42c760a8d498c275dbf65a050492fb62fc
|
|
| MD5 |
d94a7bf7c88b2bca4e49d501cde9aada
|
|
| BLAKE2b-256 |
e3a7b367257dfbe60ac39c66fecadb42684c07831f85e2643efbb01e9f491477
|
File details
Details for the file fcd-1.2.2-py3-none-any.whl.
File metadata
- Download URL: fcd-1.2.2-py3-none-any.whl
- Upload date:
- Size: 5.2 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9d8284a4d886778db787bc2653678bd050b358bc0a9c4ff835721edf301facda
|
|
| MD5 |
4406a109d674d42a80734e330b7708ee
|
|
| BLAKE2b-256 |
7f62d487f9a5ffd54ef4e29b3581a252589666e5e56e62fe3336d4b30f3b9c5f
|
