排序方式: 共有83条查询结果,搜索用时 15 毫秒
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H. H. Slepicka H. F. Canova D. B. Beniz J. R. Piton 《Journal of synchrotron radiation》2015,22(5):1182-1189
In this report, Py4Syn, an open‐source Python‐based library for data acquisition, device manipulation, scan routines and other helper functions, is presented. Driven by easy‐to‐use and scalability ideals, Py4Syn offers control system agnostic solution and high customization level for scans and data output, covering distinct techniques and facilities. Here, most of the library functionalities are described, examples of use are shown and ideas for future implementations are presented. 相似文献
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自动化运维是指把IT运维中原有重复性、周期性、规律性的工作交给工具或软件,由工具或软件实现对应用系统软硬件的自动化巡检、业务故障处理、数据备份及恢复等。随着人工智能及各种运维工具的产生,自动化运维必将替代人工运维,利用Python第三方库,介绍Python语言在自动化运维中的应用。 相似文献
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《电子技术与软件工程》2020,(1)
本文通过使用Python批量的绘制FY-4卫星沙尘产品,能够快速有效的查看沙尘产品。为了监测沙尘事件,利用卫星数据已经对沙尘暴进行了监控。FY-4A卫星通过监测中国区,将获得的数据进行处理,产生了沙尘产品,使用Swap等软件打开文件较为繁琐,不能够快速的查看文件,本文使用Python语言解析FY-4A的沙尘产品资料,可批量的生成沙尘产品图。 相似文献
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《电子技术与软件工程》2020,(1)
本文主要讨论了基于python的民国报刊图像中TIFF、JPGA类图像的数字化信息处理。民国报刊作为近代资料中的重要一环,在内容上相对客观、准确,在长期积累中形成完整系统的史料,已经成为近代资料专藏的主体之一,民国报刊的数字化有着十分重要而紧迫的意义。Python语言作为近来较为流行的脚本语言,具有良好的一致性,可以在多种平台上移植,而且采用Python语言进行编程时,编程人员不需要考虑内存占用等底层的细节问题,能够有效提升编程效率,可以对于国民报刊图像数字化信息处理提供新的思路和方法。 相似文献
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Franz Schreier 《Journal of Quantitative Spectroscopy & Radiative Transfer》2011,112(6):1010-1025
Rational functions are frequently used as efficient yet accurate numerical approximations for real and complex valued functions. For the complex error function w(x+iy), whose real part is the Voigt function K(x,y), code optimizations of rational approximations are investigated. An assessment of requirements for atmospheric radiative transfer modeling indicates a y range over many orders of magnitude and accuracy better than 10−4. Following a brief survey of complex error function algorithms in general and rational function approximations in particular the problems associated with subdivisions of the x, y plane (i.e., conditional branches in the code) are discussed and practical aspects of Fortran and Python implementations are considered. Benchmark tests of a variety of algorithms demonstrate that programming language, compiler choice, and implementation details influence computational speed and there is no unique ranking of algorithms. A new implementation, based on subdivision of the upper half-plane in only two regions, combining Weideman's rational approximation for small |x|+y<15 and Humlicek's rational approximation otherwise is shown to be efficient and accurate for all x, y. 相似文献