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.

中文翻译：

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SAXSDOG：用于二维散射图像实时方位角积分的开放软件

同步加速器的原位小角和广角散射实验通常仅在几秒钟内产生大量数据。特别是在这样的波束时间期间，在线处理获取的数据，因此没有可提及的延迟，是获得实验失败或成功反馈的关键。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。该软件主要是为专用数据管道设计的：一旦散射图像从探测器传输到存储单元，它就会在几毫秒内使用积分参数自动集成和预评估。底层基于服务器的进程的控制和配置是通过图形用户界面 SAXSLEASH 完成的，它将生成的一维数据与积分分类器实时可视化。SAXSDOG 还包括一个便携式“带回家”版本，供在独立计算机上运行的用户使用，使其能够在实验室或首选工作区中使用。