高职院校“Python语言”课程教学探讨

计算机编程是计算机专业的学生必须掌握的一种重要技能。对于非计算机专业的高职生来说,传统的编程语言如C语言、VB语言等都是比较难学的、枯燥的编程语言。作为当今最流行的编程语言,"Python语言"具有开源、易学等特点。为了提高非计算机专业的高职生的编程兴趣,以更好地培养学生的逻辑思维,调动学生的学习兴趣为目的,文章对高职院校"Python语言"课程教学进行了探讨。     

cclib: a library for package-independent computational chemistry algorithms

There are now a wide variety of packages for electronic structure calculations, each of which differs in the algorithms implemented and the output format. Many computational chemistry algorithms are only available to users of a particular package despite being generally applicable to the results of calculations by any package. Here we present cclib, a platform for the development of package-independent computational chemistry algorithms. Files from several versions of multiple electronic structure packages are automatically detected, parsed, and the extracted information converted to a standard internal representation. A number of population analysis algorithms have been implemented as a proof of principle. In addition, cclib is currently used as an input filter for two GUI applications that analyze output files: PyMOlyze and GaussSum.     

Scikit-Dimension: A Python Package for Intrinsic Dimension Estimation

Dealing with uncertainty in applications of machine learning to real-life data critically depends on the knowledge of intrinsic dimensionality (ID). A number of methods have been suggested for the purpose of estimating ID, but no standard package to easily apply them one by one or all at once has been implemented in Python. This technical note introduces scikit-dimension, an open-source Python package for intrinsic dimension estimation. The scikit-dimension package provides a uniform implementation of most of the known ID estimators based on the scikit-learn application programming interface to evaluate the global and local intrinsic dimension, as well as generators of synthetic toy and benchmark datasets widespread in the literature. The package is developed with tools assessing the code quality, coverage, unit testing and continuous integration. We briefly describe the package and demonstrate its use in a large-scale (more than 500 datasets) benchmarking of methods for ID estimation for real-life and synthetic data.     

基于Python-Abaqus的自适应网格重划分算法实现及其应用

在有限元分析中,当选取了合适单元类型后,若采用的网格尺寸太大则达不到计算精度要求,尺寸太小则往往需要非常庞大的单元数而导致求解自由度的迅速增长,利用自适应网格可以减轻计算精度与计算量的矛盾。本文采用基于后验误差估计的自适应网格重划算法,并结合Abaqus二次开发,编写了相应的自适应有限元Python脚本,从数值上分析了误差控制标准对计算结果的影响,实现了自适应求解全过程。通过Python脚本应用于几类典型问题的有限元分析,数值验证了基于Abaqus网格重划技术的自适应方法对求解应力集中问题的有效性。Python二次开发自适应计算与模拟,可绕过Abaqus/CAE的图形用户界面(GUI)直接对Abaqus内核进行操作,实现从几何建模、网格剖分到自适应求解的自动化处理,进而可方便多次修改模型和参数,提高建模效率。     

Python在分析化学实验数据处理中的应用*——以铁和铋的络合滴定实验为例

分析化学实验是化学和化工专业的核心基础课之一,其中数据分析处理是分析化学实验课程的重难点。基于此,以铁、铋的络合滴定实验数据处理为例,讨论了如何运用Python处理分析化学实验数据。将编程好的Python程序直接用于实验数据处理,能够快速、准确、高效地得到物质含量及相对平均偏差等数值,并仅需通过对关键代码的修改就能将程序扩展到其他实验应用中。Python程序应用于分析化学数据处理中能为实验的高效进行提供切实的保障,并具有较好的普适性和推广性,同时能够激发学生的探究兴趣和培养学生的创新能力。     

tCONCOORD-GUI: visually supported conformational sampling of bioactive molecules

Conformational flexibility of bioactive molecules poses a major challenge to computational biology. tCONCOORD generates structure ensembles based on geometrical considerations and has been successfully applied to predict protein conformational flexibility and essential degrees of freedom. We have now developed a graphical user interface (GUI) for tCONCOORD, which substantially facilitates the simulation setup and provides valuable insights into the structure analysis and constraint definition process in tCONCOORD. Moreover, users can influence the constraint definition process by interactively turning interactions on and off, defining completely rigid or flexible regions, or by applying artifical constraints that cause a biased sampling of the conformational space. This interface offers a versatile environment not only for the setup and analysis of tCONCOORD simulations, but also for molecular modeling and structure analysis in general. Both tCONCOORD* and the tCONCOORD-GUI(dagger) are distributed freely.     

Python在自动化运维业务中的设计与实现

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。     

基于树莓派和Python的数字均衡器实验设计

传统的实时性数字音效处理系统主要基于DSP硬件平台进行开发，对于本科生而言开发难度和成本都较高，针对此问题，提出了基于树莓派和Python的数字均衡器综合实验设计方案。首先，提出了一种基于尖峰滤波器模型的均衡器方法；其次，从理论角度阐述了IIR数字滤波器形式的设计过程，并通过窗函数法转换为FIR数字滤波器；最后，借助树莓派数字音效处理系统，印证了实验方案的可行性和拓展性，提高了学生的理论应用能力和创新实践兴趣。     

基于Python的Web数据采集技术

针对Web数据采集技术进行了介绍,分析了Web数据采集技术在将非结构化数据转换为结构化数据方面的优势:速度快、准确性高。从HTTP协议层分析了Web数据抓取的原理,并重点介绍了如何实现基于Python的Web数据采集方案。Web数据采集系统可以分为:HTTP交互和数据解析两个模块。