NMR-GCN
A code to predict atomic NMR chemical shift based GCN and QM calculation
This code was based on https://github.com/tencent-alchemy/Alchemy. If this script is of any help to you, please cite them.
- K.T. Schütt. P.-J. Kindermans, H. E. Sauceda, S. Chmiela, A. Tkatchenko, K.-R. Müller. SchNet: A continuous-filter convolutional neural network for modeling quantum interactions. Advances in Neural Information Processing Systems 30, pp. 992-1002 (2017) link
- @article{chen2019alchemy,
title={Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models},
author={Chen, Guangyong and Chen, Pengfei and Hsieh, Chang-Yu and Lee, Chee-Kong and Liao, Benben and Liao, Renjie and Liu, Weiwen and Qiu, Jiezhong and Sun, Qiming and Tang, Jie and Zemel, Richard and Zhang, Shengyu},
journal={arXiv preprint arXiv:1906.09427},
year={2019}
}
Dependencies
- PyTorch
- dgl
- RDKit
- Numpy
- Pandas
- argparse
Usage:
How to preprocess the dataset:
python dataset_split.py --dataset ./DATA/C_NMR/C-NMR
How to train the model:
python train_qm.py --model sch_qm --epochs 10000 --train_file ./DATA/C_NMR/C-NMR_train.csv --test_file ./DATA/C_NMR/C-NMR_valid.csv --save saved_model/C-C
How to eval the model:
python eval.py -M sch_qm -S saved_model/N-N/model_200 -E DATA/N_NMR/N-NMR_valid.csv