PyCDFT: A Python package for constrained density functional theory

We present PyCDFT, a Python package to compute diabatic states using constrained density functional theory (CDFT). PyCDFT provides an object-oriented, customizable implementation of CDFT, and allows for both single-point self-consistent-field calculations and geometry optimizations. PyCDFT is designed to interface with existing density functional theory (DFT) codes to perform CDFT calculations where constraint potentials are added to the Kohn–Sham Hamiltonian. Here, we demonstrate the use of PyCDFT by performing calculations with a massively parallel first-principles molecular dynamics code, Qbox, and we benchmark its accuracy by computing the electronic coupling between diabatic states for a set of organic molecules. We show that PyCDFT yields results in agreement with existing implementations and is a robust and flexible package for performing CDFT calculations. The program is available at https://dx.doi.org/10.5281/zenodo.3821097 .     

用于SCA ASIC测试的数字读出模块设计

高速开关电容阵列(SCA)具有高速采样、低功耗的特点,基于SCA的高速波形数字化是目前高精度时间测量的一个重要研究方向。为此,我们开展SCA芯片的研究,目前已设计完成原型ASIC设计,并正在进行后续版本的改进设计。为便于未来多版本ASIC的测试和评估,需设计具有一定通用性的数字读出模块,本论文工作主要介绍此模块的设计工作以及相应的数据读出软件。数字读出模块基于FPGA实现对待测ASIC的控制、配置及数据读出,采用DDR3片外存储芯片,使用USB3.0等接口进行数据传输;上位机软件基于Python3.7设计,实现了数据采集与波形绘制等功能。目前已使用设计完成的数字读出模块对第2版SCA ASIC进行了初步的测试,测试结果表明,此读出模块工作正常,且SCA芯片输出结果符合预期。     

Python与Matlab混合语言编程

Python是一种简单、灵活、高效的脚本语言,他特别适合用于原型开发。简单介绍Python与Matlab的特点。针对这两种语言提出几种混合语言编程的方法,旨在结合Python与Matlab各自的优势,通过混合编程提高软件开发的效率。重点介绍了用Matlab COM生成器生成COM组件,并用Python调用该组件的方法。     

pyMolDyn: Identification,structure, and properties of cavities/vacancies in condensed matter and molecules

pyMolDyn is an interactive viewer of atomic systems defined in a unit cell and is particularly useful for crystalline and amorphous materials. It identifies and visualizes cavities (vacancies, voids) in simulation cells corresponding to all seven 3D Bravais lattices, makes no assumptions about cavity shapes, allows for atoms of different size, and locates the cavity centers (the centers of the largest spheres not including an atom center). We define three types of cavity and develop a method based on the split and merge algorithm to calculate all three. The visualization of the cavities uses the marching cubes algorithm. The program allows one to calculate and export pair distribution functions (between atoms and/or cavities), as well as bonding and dihedral angles, cavity volumes and surface areas, and measures of cavity shapes, including asphericity, acylindricity, and relative shape anisotropy. The open source Python program is based on GR framework and GR3 routines and can be used to generate high resolution graphics and videos. © 2016 Wiley Periodicals, Inc.     

嵌入式软件GUI自动化测试平台研究

为实现嵌入式软件的GUI自动化测试,本文对嵌入式软件GUI自动化测试现状深入分析,提出了一种无侵入式的GUI自动化测试框架,利用图像采集与信息识别技术实现测试用例结果判断;利用键盘鼠标模拟技术模拟测试用例执行的人机交互;利用脚本语言嵌入技术实现用例编辑与转换、利用嵌入式软件GUI测试自动化控制技术实现用例的自动驱动与执行。在此基础上,设计并研发了嵌入式软件GUI自动化测试平台,能够方便、有效的实现无侵入式的嵌入式GUI自动化测试。     

高空温度动态采集系统设计

在采集不同高度的温度时,在不同高度安置无线网络传感器成本高,无线传感器的电源替换比较困难,为解决此问题,采用了简易螺旋直升机,内置由AT89C51单片机、DS1820数字芯片,可实时采集不同高度的温度。使用JF24D-B无线传输模块将信号送至ARM7控制系统。监控端通过无线信号接收并解析,在μClinux下进行进程调度和数据处理,并通过Python完成数据图表的实时显示,便于用户查看当前温度做出正确决策。     

Python在热敏电阻测量实验数据处理中的应用

Python语言因为语法简洁、功能全面、开发的程序具有可移植性而拥有十分广阔的应用市场.Python在诸多方面都有应用,如科学计算、应用开发以及计算机科学教育等.本文就热敏电阻测量实验的数据处理问题进行了分析,同时也进行了系统的图形化界面设计以及用Python语言编写相关的脚本来实现了实验数据的数据库存储功能.     

Modeling and Verification of a Sentiment Analysis System Using Aspect-Oriented Petri Nets

An increasing number of social media and networking platforms have been widely used. People usually post the online comments to share their own opinions on the networking platforms with social media. Business companies are increasingly seeking effective ways to mine what people think and feel regarding their products and services. How to correctly understand the online customers’ reviews becomes an important issue. This study aims to propose a method with the aspect-oriented Petri nets (AOPN) to improve the examination correctness without changing any process and program. We collect those comments from the online reviews with Scrapy tools, perform sentiment analysis using SnowNLP, and examine the analysis results to improve the correctness. In this paper, we apply our method for a case of the online movie comments. The experimental results have shown that AOPN is helpful for the sentiment analysis and verifying its correctness.