论文标题
SAXSDOG：2D散射图像实时方位角集成的开放软件
SAXSDOG: open software for real-time azimuthal integration of 2D scattering images
论文作者
论文摘要
同步基因的原位小角度和广角散射实验通常仅在几秒钟内才会产生大量数据。尤其是在此类束缚期间，在线处理获得的数据，因此在不提及的情况下，是获得实验失败或成功的反馈的关键。因此，我们开发了SAXSDOG，这是一种基于Python的环境，用于大面积散射图像的实时方位角集成。该软件主要是针对专用数据流程设计的：一旦将散射图像从检测器转移到存储单元上，它就会使用毫秒内的积分参数自动集成并预先评估。基于基于服务器的过程的控制和配置是通过图形用户界面Saxsleash完成的，该图形用户界面可视化所得的1D数据与积分分类器实时可视化。 SAXSDOG还包括用于独立计算机上运行的用户的便携式“带屋”版本，可在实验室或首选工作区中使用。
In-situ small- and wide-angle scattering experiments at synchrotrons often result in massive amounts of data within seconds only. Especially during such beamtimes, processing of the acquired data online, so without mentionable delay, is key to obtain feedback on failure or success of the experiment. We thus developed SAXSDOG, a python based environment for real-time azimuthal integration of large-area scattering-images. The software is primarily designed for dedicated data-pipelines: once a scattering image is transferred from the detector onto the storage-unit, it is automatically integrated and pre-evaluated using integral parameters within milliseconds. The control and configuration of the underlying server-based processes is done via a graphical user interface SAXSLEASH, which visualizes the resulting 1D data together with integral classifiers in real time. SAXSDOG further includes a portable 'take-home' version for users that runs on standalone computers, enabling its use in labs or at the preferred workspace.
