The open-source PyNX toolkit [Favre-Nicolin et al (2011) arXiv:1010.2641, Mandula et al (2016)] has been extended to provide tools for coherent X-ray imaging data analysis and simulation. All calculations can be executed on graphical processing units (GPU) to achieve high performance computing speeds. This can be used for Coherent Diffraction Imaging (CDI), Ptychography and wavefront propagation, in the far or near field regime. Moreover, all imaging operations (propagation, projections, algorithm cycles..) can be used in Python as simple mathematical operators, an approach which can be used to easily combine basic algorithms in a tailored chain. Calculations can also be distributed to multiple GPUs, e.g. for large Ptychography datasets. Command-line scripts are also available for on-line CDI and Ptychography analysis, either from raw beamline datasets or using the Coherent X-ray Imaging data format [Maia (2012)].

中文翻译：

---

PyNX：基于算子的相干X射线成像高性能计算工具包

开源 PyNX 工具包 [Favre-Nicolin 等人 (2011) arXiv:1010.2641, Mandula 等人 (2016)] 已扩展为提供相干 X 射线成像数据分析和模拟的工具。所有计算都可以在图形处理单元 (GPU) 上执行，以实现高性能计算速度。这可用于远场或近场区域的相干衍射成像 (CDI)、Ptychography 和波前传播。此外，所有成像操作（传播、投影、算法循环......）都可以在 Python 中用作简单的数学运算符，这种方法可用于在定制链中轻松组合基本算法。计算也可以分布到多个 GPU，例如对于大型 Ptychography 数据集。命令行脚本也可用于在线 CDI 和 Ptychography 分析，