Welcome to S2Generator Discussions!

[wwhenxuan]

👋 Welcome to S2Generator!

We're happy to announce the release of S2Generator 0.0.2! 🎉🎉🎉

We welcome everyone to use our data generation mechanism.

What is the S2Generator

Foundation models for time series analysis (TSA) have attracted significant attention. However, challenges such as training data scarcity and imbalance continue to hinder their development. Inspired by complex dynamic system theories, we design a series-symbol ($S^2$) data generation mechanism, enabling the unrestricted creation of high-quality time series data paired with corresponding symbolic expressions 🥳.

The Usage and Installation of S2Generator

This is the first version of our $S^2$ data generation mechanism that is open source and officially released. We developed it using only data science libraries such as NumPy, Scipy, and Matplotlib. You can install it via pip:

pip install s2generator

For more specific usage, please see our Demo file ✨.

If you encounter any issues while using S2Generator, please contact us immediately. We would be very grateful.

Future Work for S2Generator

We will also accelerate the development of S2Generator's technical documentation, providing more comprehensive and diverse examples and usage instructions 📃.

If you find this $S^2$ data generation method helpful, please cite the following paper:

@misc{wang2025mitigatingdatascarcitytime,
      title={Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation}, 
      author={Wenxuan Wang and Kai Wu and Yujian Betterest Li and Dan Wang and Xiaoyu Zhang and Jing Liu},
      year={2025},
      eprint={2502.15466},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2502.15466}, 
}