## CPICANN Datasets

This repository contains the data sets described in the CPICANN paper, available at [GitHub](https://github.com/WPEM/CPICANN).


CPICANN is evaluated on four distinguished datasets, denoted as D1, D2, D3, and D4, with the following characteristics:

- **D1**: 0% background ratio and Gaussian noise (σ=0.25) (v chosen in paper)
- **D2**: 3% background ratio and Gaussian noise (σ=0.25)
- **D3**: 0% background ratio and Gaussian noise (σ=1)
- **D4**: 0% background ratio and Gaussian noise (σ=3)

Contribution and suggestions are always welcome. You can also contact the authors for research collaboration.

## 📚 Citation & License

**Commercial use is strictly prohibited.**  
All access will be logged.  
If you use this dataset in your research, please cite **all** the following works:

```bibtex

@article{zhang2024crystallographic,
  title={Crystallographic phase identifier of a convolutional self-attention neural network (CPICANN) on powder diffraction patterns},
  author={Zhang, Shouyang and Cao, Bin and Su, Tianhao and Wu, Yue and Feng, Zhenjie and Xiong, Jie and Zhang, Tong-Yi},
  journal={IUCrJ},
  volume={11},
  number={Pt 4},
  pages={634},
  year={2024}
}

@inproceedings{binsimxrd,
  title={SimXRD-4M: Big Simulated X-ray Diffraction Data and Crystal Symmetry Classification Benchmark},
  author={Bin, CAO and Liu, Yang and Zheng, Zinan and Tan, Ruifeng and Li, Jia and Zhang, Tong-yi},
  booktitle={The Thirteenth International Conference on Learning Representations}
}
```