This is the offical repository of the LnQM dataset developed by the Grimme group in Bonn.

The data is available under: https://zenodo.org/records/10406124

We provide a dataset class and a sample representation based on pytorch. For this purpose please install the package requirements:

conda env create --file requirements.yml

Basic usage of the dataset:

from lnqm import LnQM_Dataset

# load LnQM from disk
dataset = LnQM_Dataset(path_to_hdf5="/path/to/lnqm.h5")

# loop over each sample in the dataset
for data in dataset:
    # ...
    # do sth. with each sample
    # ...

    # e.g. access properties
    print(data.uid)

For a more detailed description of the features included see the datamodel in LnQM_Sample. If required, a Data object can be converted via:

from lnqm import LnQM_Sample
sample = LnQM_Sample(**data)

When using or referencing to the LnQM please cite:

• C. Hölzer, I. Gordiy, S. Grimme, M. Bursch, J. Chem. Inf. Model., 2024, 1549-9596. DOI: 10.1021/acs.jcim.3c01832

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.