Skip to main content

ATOM3D: Tasks On Molecules in 3 Dimensions

Documentation Status Package codecov PyPI version

ATOM3D enables machine learning on three-dimensional molecular structure.

Features

  • Access to several datasets involving 3D molecular structure.
  • LMDB data format for storing lots of molecules (and associated metadata).
  • Utilities for splitting/filtering data based on many criteria.

For more detailed information, read the documentation.

Installation

Install with:

pip install atom3d

To use rdkit functionality, please install within conda:

conda create -n atom3d python=3.6 pip rdkit
conda activate atom3d
pip install atom3d

Usage

Downloading a dataset

From python:

import atom3d.datasets as da
da.download_dataset('lba', PATH_TO_DATASET) # Download LBA dataset.

Or, download and unzip from the website.

Loading a dataset

From python:

import atom3d.datasets as da
dataset = da.load_dataset(PATH_TO_DATASET, {'lmdb','pdb','silent','sdf','xyz','xyz-gdb'})
print(len(dataset))  # Print length
print(dataset[0].keys())  # Print keys

LMDB datasets

LMDB allows for compressed, fast, random access to your structures, all within a single database. Currently, we support creating LMDB datasets from PDB files, silent files, and xyz files.

Creating an LMDB dataset

From command line:

python -m atom3d.datasets PATH_TO_PDB_DIR PATH_TO_DATASET --filetype {pdb,silent,xyz,xyz-gdb} 

For more usage, please see the documentation.

Contribute

As a living repository, we welcome contributions of additional datasets, methods, and functionality! See the Contributing section of the documentation for details.

Support

For support, please file an issue at https://github.com/drorlab/atom3d/issues.

License

The project is licensed under the MIT license.

Reference

We provide an overview on ATOM3D and details on the preparation of all datasets in our preprint:

R. J. L. Townshend, M. Vögele, P. Suriana, A. Derry, A. Powers, Y. Laloudakis, S. Balachandar, B. Jing, B. Anderson, S. Eismann, R. Kondor, R. B. Altman, R. O. Dror "ATOM3D: Tasks On Molecules in Three Dimensions", arXiv:2012.04035

Please cite this work if some of the ATOM3D code or datasets are helpful in your scientific endeavours. For specific datasets, please also cite the respective original source(s), given in the preprint.

Metadata

Release files for atom3d 0.2.6

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

Source distribution (sdist)

Source distribution for atom3d 0.2.6
File Size Uploaded Provenance Actions
atom3d-0.2.6.tar.gz 44.9 kB Without provenance Details for atom3d-0.2.6.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for atom3d 0.2.6
File Interpreter ABI Platform Actions
atom3d-0.2.6-py3-none-any.whl Python 3 none any Details for atom3d-0.2.6-py3-none-any.whl

Total release size: 97.6 kB

Release files / atom3d-0.2.6.tar.gz

Download URL atom3d-0.2.6.tar.gz
Size 44.9 kB
Tags Source
SHA-256 checksum
How to use checksums
fdf23811cd08fffea3244b9b1300fc8ffe808c06fa5c69c85d5d4bb21833e256
BLAKE2b-256 checksum
How to use checksums
8c5b787e98992b4f9f99d542315489f043ffbb6874130ae4f165921163d006c7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.10.5

Release files / atom3d-0.2.6-py3-none-any.whl

Download URL atom3d-0.2.6-py3-none-any.whl
Size 52.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
9d26096c245e1ce46262081f5af5e88912eb1cc4d6e319d47b9f4241cb7f73f9
BLAKE2b-256 checksum
How to use checksums
ac07c75ce6b77db7abf8c6a0ebdaaf8f8fb291be5de2214139aa035f51939cd1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.10.5

Security for atom3d 0.2.6

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.

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