This paper details a software ecosystem comprising three free and open-source Python packages for processing raw ultrafast electron scattering (UES) data and interactively exploring the processed data. The first package, iris, is graphical user-interface program and library for interactive exploration of UES data. Under the hood, iris makes use of npstreams, an extensions of numpy to streaming array-processing, for high-throughput parallel data reduction. Finally, we present scikit-ued, a library of reusable routines and data structures for analysis of UES data, including specialized image processing algorithms, simulation routines, and crystal structure manipulation operations. In this paper, some of the features or all three packages are highlighted, such as parallel data reduction, image registration, interactive exploration. The packages are fully tested and documented and are released under permissive licenses.

中文翻译：

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用于交互式探索超快电子散射数据的开源软件生态系统。

本文详细介绍了一个软件生态系统，包括三个免费和开源的 Python 包，用于处理原始超快电子散射 (UES) 数据并交互式地探索处理后的数据。第一个包 iris 是用于交互探索 UES 数据的图形用户界面程序和库。在底层，iris 利用 npstreams，一个 numpy 对流式数组处理的扩展，用于高吞吐量并行数据缩减。最后，我们介绍了 scikit-ued，这是一个用于分析 UES 数据的可重用例程和数据结构库，包括专门的图像处理算法、模拟例程和晶体结构操作操作。本文重点介绍了其中的一些特性或全部三个包，例如并行数据缩减、图像配准、交互式探索。