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OneScience-Group/ani1x

ANI-1x Dataset Description The ANI-1x dataset is a molecular-configuration dataset for training and evaluation. The data package contains training, validation, and test HDF5 shards, along with a statistics JSON file and auxiliary extxyz files. Its fields are consistent with the energy and force fields in the MACE ANI-1x configuration, making it a standard benchmark dataset for learning and validating machine-learning interatomic potentials with MACE. The element set… See the full description on the dataset page: https://huggingface.co/datasets/OneScience-Group/ani1x.

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Dataset Card

ANI-1x

Dataset Description

The ANI-1x dataset is a molecular-configuration dataset for training and evaluation. The data package contains training, validation, and test HDF5 shards, along with a statistics JSON file and auxiliary extxyz files. Its fields are consistent with the energy and force fields in the MACE ANI-1x configuration, making it a standard benchmark dataset for learning and validating machine-learning interatomic potentials with MACE.

The element set consists of H, C, N, and O. The original ANI-1x data comes from ANI-1x datasets (FigShare); this repository is the companion data package for OneScience MACE training and evaluation examples.

The current data package contains approximately 30 files.

Supported Tasks

This standardized data repository provides the complete data package for the ANI-1x example, including training, validation, and test sets. It can be used for:

—Training and validation of potential-energy-surface models for molecular configurations
—Potential-energy-surface fitting for molecular dynamics simulations
—Functional testing and benchmark evaluation of the MACE framework

Dataset Format and Structure

The data files are located in the data/ani1x/ directory:

File Path	Format	shape / Content	Description
`ani1x/ANI1x_cc_DFT_rc5_train/train_*.h5`	HDF5	`[N_frames, N_atoms]`	Training set, with 8 shards in total
`ani1x/ANI1x_cc_DFT_rc5_val/val_*.h5`	HDF5	`[N_frames, N_atoms]`	Validation set, with 8 shards in total
`ani1x/ANI1x_cc_DFT_rc5_test/Default__*.h5`	HDF5	`[N_frames, N_atoms]`	Test set, with 8 shards in total
`ani1x/ANI1x_cc_DFT_rc5_statistics.json`	JSON	Statistical information	Contains `atomic_energies`, `avg_num_neighbors`, `mean`, `std`, `atomic_numbers`, and `r_max`
`ani1x/ani1x_train.xyz`	extxyz	`[N_frames, N_atoms]`	Auxiliary training-set file
`ani1x/ani1x_test.xyz`	extxyz	`[N_frames, N_atoms]`	Auxiliary test-set file
`ani1x/ani1x_cc_dft.xyz`	extxyz	`[N_frames, N_atoms]`	Auxiliary file for the full dataset
`metadata/sha256_manifest.txt`	SHA256	Checksum manifest	File-integrity verification

HDF5 Data Format

The HDF5 file structure is config_batch_*/config_*. Each configuration contains:

Path	dtype	shape	Description
`atomic_numbers`	`int64`	`[N_atoms]`	Atomic numbers
`positions`	`float64`	`[N_atoms, 3]`	Atomic coordinates, in Å
`cell`	`float64`	`[3, 3]`	Periodic cell matrix
`pbc`	`bool`	`[3]`	Periodic boundary conditions
`properties/energy`	`float64`	Scalar	Total configuration energy, in eV
`properties/forces`	`float64`	`[N_atoms, 3]`	Atomic forces, in eV/Å

How to Use the Dataset

Download the dataset:

bash

hf download OneScience-Group/ani1x --repo-type dataset

Official OneScience Information

Platform	OneScience Main Repository	Skills Repository
Gitee	https://gitee.com/onescience-ai/onescience	https://gitee.com/onescience-ai/oneskills
GitHub	https://github.com/onescience-ai/OneScience	https://github.com/onescience-ai/oneskills

Limitations and License

This dataset is the example data for MACE ANI-1x; it does not contain any newly generated samples or alter the original data. The original data comes from ANI-1x datasets (FigShare), with calculations performed at the wB97X/6-31G(d) level.

—Original Source: https://springernature.figshare.com/collections/TheANI-1ccxandANI-1xdatasetscoupled-clusteranddensityfunctionaltheorypropertiesfor_molecules/4712477
—GitHub Repository: https://github.com/aiqm/ANI1x_datasets
—License: CC0 1.0 Universal (public domain dedication)

When using the ANI-1x dataset, please cite:

—Smith, J. S.; Nebgen, B.; Lubbers, N.; Isayev, O.; Roitberg, A. E. Less Is More: Sampling Chemical Space with Active Learning. J. Chem. Phys. 2018, 148 (24), 241733. https://doi.org/10.1063/1.5023802
—Smith, J. S.; Zubatyuk, R.; Nebgen, B.; Lubbers, N.; Barros, K.; Roitberg, A. E.; Isayev, O.; Tretiak, S. The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules. Sci. Data 2020, 7, 134. https://doi.org/10.1038/s41597-020-0473-z