Python Scientific Computing (2nd Edition)

Name: Python Scientific Computing (2nd Edition)
ISBN: 9787302426585

张若愚Tsinghua University Press2016

4.3

Word count: 1.1K words
Chapters: 11
ISBN: 9787302426585

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Summary

Python Scientific Computing (2nd Edition), written by Zhang Ruoyu and published by Tsinghua University Press, is a Python reference book oriented toward scientific computing practice. It runs to about 716 pages and 1,083,000 characters, and the accompanying disc provides Jupyter/IPython Notebook example code for each chapter as well as the author's integrated portable runtime environment, WinPython. The book is organized around "extended libraries plus examples": Chapter 1 introduces Python scientific computing environment setup, an IPython Notebook primer, and an overview of various extension libraries; Chapter 2 systematically covers NumPy's ndarray object, element types, multidimensional array access, ufunc functions and broadcasting, random numbers, and statistical functions; Chapter 3 introduces SciPy's special functions, nonlinear equation solving, least-squares fitting, and optimization; Chapters 4 through 6 cover matplotlib 2D plotting, Pandas data analysis, and SymPy symbolic computation respectively; Chapters 7 through 9 cover Traits/TraitsUI graphical interfaces, TVTK and Mayavi 3D visualization, and OpenCV image processing and computer vision; Chapter 10 is devoted to Cython compilation optimization and speed-up techniques. Chapter 11, "Examples," is a highlight: complete cases such as Poisson image blending, classical mechanics simulations (catenary, brachistochrone, simple pendulum), matrix factorization recommendation algorithms, frequency-domain signal processing and FFT, Boolean satisfiability problem solving (Sudoku, Minesweeper), and fractal generation tie together the whole chain from numerical computation and algorithm implementation to visual presentation. Compared with the first edition, the second edition updates about 40 percent of the content, adding topics such as IPython Notebook, Pandas, and Cython, with nearly every chapter substantially rewritten. The book uses extensive runnable code and rich illustrations to reduce theoretical derivation, making it suitable for engineers and researchers to learn by doing.

Editor's review

在Python科学计算的中文书里，这本书的地位相当稳固：它不是一本只讲语法的入门书，而是一张“工具地图”，把NumPy、SciPy、matplotlib、Pandas、SymPy、Traits、Mayavi、OpenCV、Cython这些库按“做什么事”串成一条线，读者遇到具体问题能直接翻到对应章节。第二版的价值在于更新及时——新增了IPython Notebook交互环境、Pandas数据分析与Cython提速的专门章节，并保留了第1版里最有口碑的三维可视化与界面制作内容，每章改动幅度都不小。作者张若愚长期在工业研究机构做信号处理与控制软件开发，书中示例带着明显的工程味：不是玩具代码，而是能跑出图、跑出结果的完整程序。附赠光盘的Notebook与整合好的WinPython环境，省去了科学计算环境配置中最让人头疼的“装库”环节，对2016年前后刚开始接触Python的读者尤为贴心。Enthought公司CEO Eric Jones作序，也从侧面说明此书在开源科学计算社群中的分量。需要提醒的是，书中示例基于Python 2时代的环境（IPython Notebook、WinPython），软件生态迭代很快，读者照着跑代码时可能需要做版本适配，建议配合各库当前官方文档一起看。

Who it's for

A good fit for

具备Python基础语法、正在做数值计算或数据分析的理工科学生与研究生
需要把实验数据快速处理、绘图、做三维展示的科研人员与工程师
想用Python替代部分MATLAB工作流、扩展工具箱的程序员
希望了解图像处理、界面制作、Cython加速等工程落地方案的开发者

Not a good fit for

完全没有编程经验、需要从零学习Python语法的零基础读者
只关心深度学习框架与模型训练、不涉及数值计算与可视化的读者
需要紧跟最新版本API（如新版Pandas、Python 3.12+）的读者，书内环境已较旧

Reading tips

先读第1章并装好示例环境，再按“NumPy→SciPy→matplotlib→Pandas”的顺序推进，打牢数据处理的底子。
把每一章的Notebook亲手跑一遍，再改参数看输出变化；科学计算的能力多半是在改代码中长出来的。
第11章实例可当作综合练习，按兴趣挑一两个（如分形、频域信号处理）完整复现，检验前面章节的掌握程度。
书中代码基于较老版本环境，遇到报错时对照各库官方文档做适配，并留意Python 2到Python 3的语法差异。

About the publisher

Tsinghua University Press China · Founded in 1980

Founded in 1980, Tsinghua University Press has 57 titles in our collection, covering popular science, medicine, health, law, philosophy and social sciences. Representative works include medical popular-science books such as Cancer Truth: Doctors Are Reading It Too and New Knowledge on Cancer by Bo Luo (Li Zhizhong), legal titles such as Sunshine Is the Best Preservative: Express Delivery of Major Global Anti-Corruption Cases, and works like Qi Ge's A Brief History of Philosophy with Big Ideas and Liu Yunhao's From the Internet to a New Industrial Revolution. Its authors include science writers, medical researchers, the Renmin University of China anti-corruption master's class and university scholars, reflecting a publishing profile that balances academic seriousness with accessible reading. As public information is limited, this profile is based only on the titles in our collection.

Chapter 1 Installation and Introduction to the Python Scientific Computing Environment (Python introduction, IPython Notebook primer, introduction to extension libraries)
Chapter 2 NumPy—Fast Data Processing (ndarray object, ufunc functions, subscript access, function library, practical tips)
Chapter 3 SciPy—Numerical Computing Library (constants and special functions, fitting and optimization)
Chapter 4 matplotlib—Plotting Charts
Chapter 5 Pandas—Data Analysis Library
Chapter 6 SymPy—Symbolic Computation Library
Chapter 7 Traits & TraitsUI—Building Graphical Interfaces
Chapter 8 TVTK and Mayavi—3D Data Visualization
Chapter 9 OpenCV—Image Processing and Computer Vision
Chapter 10 Cython—Compiling Python Programs (extension types, Cython tips collection)
Chapter 11 Examples (Poisson image blending, classical mechanics simulation, recommendation algorithms, frequency-domain signal processing, Boolean satisfiability solver, fractals)

FAQ

这本书有没有配代码和运行环境？

有。第2版附赠光盘，内含各章Notebook实例代码以及作者整合的便携式运行环境WinPython，可直接运行书中示例，省去逐一安装NumPy、SciPy等扩展库的麻烦。

读这本书需要什么基础？

作者在前言中给出了自检清单：需要了解import、for/while循环、if判断、函数定义，熟悉列表、字典、元组、字符串等类型和基本的类与继承语法，并具备C语言基础，这样阅读实例代码会比较顺畅。

第二版和第一版有什么区别？

第二版于2016年出版，更新内容约四成：新增IPython Notebook、Pandas数据分析库和Cython编译优化章节，保留并大幅修订NumPy、SciPy、matplotlib、Traits、TVTK/Mayavi等章节，实例部分也换成图像处理、推荐系统、扫雷等多个新案例。

书里的例子现在还能跑通吗？

这些示例最初面向Python 2时代的IPython Notebook和WinPython环境，如今部分库的API已有变化，直接运行可能报错。建议以书中思路为主，按当前版本官方文档调整少量语法与函数名。

这本书适合替代MATLAB吗？

书中前言专门比较了Python与MATLAB：Python免费开源、通用性更强、可与其他系统集成，大部分常用功能都有对应扩展库。若工作主要依赖MATLAB的专业工具箱，仍需具体评估，但用Python搭建数据处理与可视化流程是可行的。

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About the author

张若愚 Author

Public information about Zhang Ruoyu is currently limited, and details such as his nationality, dates of birth and death, and educational background cannot be confirmed. Among the works held in the collection is a single title, A Study of the Dasheng Cotton Mill During the Occupation Period, which is classified as a history reading. The book takes the Dasheng Cotton Mill during the occupation period as its subject, placing it within the overlap of modern Chinese business history and local history. A study of this kind typically relies on careful examination of archives, newspapers, factory records, and other primary sources. It may therefore be inferred that the author's writing emphasizes factual reconstruction and case analysis, with attention to how an enterprise actually operated and fared under particular historical circumstances. For readers interested in the situation of modern national industry during wartime, such a topic offers some reference value. Since this is the only work by the author in the collection, a fuller picture of his overall style and research scope must await further material.