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StreamSAXS: a Python-based workflow platform for processing streaming SAXS/WAXS data.

Jiayi WangZheng DongYi ZhangWenqiang HuaZudeng WangHuilong GuoYiming YangXiaoxue Bi
Published in: Journal of synchrotron radiation (2024)
StreamSAXS is a Python-based small- and wide-angle X-ray scattering (SAXS/WAXS) data analysis workflow platform with graphical user interface (GUI). It aims to provide an interactive and user-friendly tool for analysis of both batch data files and real-time data streams. Users can easily create customizable workflows through the GUI to meet their specific needs. One characteristic of StreamSAXS is its plug-in framework, which enables developers to extend the built-in workflow tasks. Another feature is the support for both already acquired and real-time data sources, allowing StreamSAXS to function as an offline analysis platform or be integrated into large-scale acquisition systems for end-to-end data management. This paper presents the core design of StreamSAXS and provides user cases demonstrating its utilization for SAXS/WAXS data analysis in offline and online scenarios.
Keyphrases
  • data analysis
  • electronic health record
  • big data
  • machine learning
  • healthcare
  • deep learning
  • mass spectrometry
  • magnetic resonance
  • artificial intelligence