Python与Matlab语言在测绘程序设计中的对比研究

A Comparative Study of Python and Matlab Languages in Mapping ProgrammingLearning

测绘科学近年伴随着“3S”技术设备的快速发展衍生,不断与前沿科技相接轨。文章以不同坐标系统之间的坐标数据转换为研究内容,利用伪代码并结合布尔莎七参数模型经程序设计。针对两种语言对于测绘数据处理的不同能力和各自的优缺点,将其进行对比与优化。其结果表明:(1)对于大量的矢量数据,Matlab相较于没有自带数据处理模块的Python而言,运算能力与稳定性更强。(2)前者数据转换的精度与算法、代码编辑息息相关。反观Python对第三方库有较强依赖性,处理结果精度可能因此而异。(3)对于数据文件操作,Python语言具有明显优势。可通过代码直接针对不同格式文件进行操作,极大的提升了操作工作效率。(4)良好的第三方软件兼容性,使Python语言具有很强的灵活性。结合其丰富的第三方模块库,更适合用于脚本开发及程序设计。

In recent years,with the rapid development of"3S"technology and equipment,surveying and mapping science has been continuously in line with cutting-edge technology.This paper uses coordinate data between different coordinate systems to be converted into research content,using pseudocode and combined with the Boursa seven-parameter model.Compare and optimize the two languages for their different capabilities and advantages and disadvantages in mapping data processing.The results show that:(1)For a large number of vector data,Matlab has greater computing power and stability than Python without its own data processing module.(2)The accuracy of the data conversion of the former is closely related to the algorithm and code editing.In contrast,Python has a strong dependence on third-party libraries,and the accuracy of the processing results may vary.(3)For data file operations,the Python language has obvious advantages.You can directly operate on different format files through code,which greatly improves the operation efficiency.(4)Good Combined with its rich library of third-party modules,it is more suitable for script development and programming.