XenonPy

XenonPy is a Python library with implemented machine learning tools for materials informatics. It provides a library to compute material descriptors using compositional, structural, and RDKit descriptors. The library also has a heat map visualization function to help users easily understand the correlation between the descriptors and the desired properties. Pre-trained models using neural networks are available to predict various compound properties, and a framework for transition learning is also provided. Combining with iqspr, it is also possible to search for unknown materials with desired properties.

基本情報

公式サイト https://github.com/yoshida-lab/XenonPy
公開度 ★★★
ライセンス

BSD 3-Clause License

開発者

Liu Chang(NIMS), Ryo Yoshida(ISM), Yukinori Koyama(NIMS)

対応OS・利用環境

Python>=3.5, PyTorch>=0.4

関連サイト

MateriApps: https://ma.issp.u-tokyo.ac.jp/en/app/1435

外部フォーラム https://ma.issp.u-tokyo.ac.jp/en/app/1435
その他

External Link