xviii
Introduction
I was always drawn to math and computers, ever since I was a kid playing computer games
on my Sinclair ZX81. When I attended university, I had a special interest in numerical analy-
sis, a field that I felt combines math and computers ideally. During my career, I learned of
MATLAB, widely popular for digital signal processing, numerical analysis, and feedback and
control. MATLAB’s strong suits include a high-level programming language, excellent graph-
ing capabilities, and numerous packages from almost every imaginable engineering field. But
I found that MATLAB wasn’t enough. I worked with very large files and needed the ability to
manipulate both text and data. So I combined Perl, AWK, and Bash scripts to write programs
that automate data analysis and visualization. And along the way, I’ve developed practices and
ideas involving the organization of data—for example, ways to ensure file names are unique
and self-explanatory.
With the increasing popularity of the Internet, I learned of GNU/Linux and the open
source movement. I made an effort to use open source software whenever possible, and so I’ve
learned of GNU-Octave and gnuplot, which together provide excellent scientific computing
functionality. That fit well on my Linux machine: Bash scripts, Perl and AWK, GNU-Octave and
gnuplot.
Knowing I was interested in programming languages and open source software, a friend
suggested I give Python a try. My first impression was that it’s just another programming lan-
guage: I can do most anything I need with Perl and Bash, resorting to C/C++ if things got hairy.
And I’d still need GNU-Octave and gnuplot, so what’s to gain? Eventually, I did learn Python
and discovered that it is far better than my collection of tools. Python provides something that
is extremely appealing: it’s a one-stop shop—you can do it all in Python.
I’ve shared my enthusiasm with friends and colleagues. Many who expressed interest with
the ideas of data processing and visualization would ask, “Can you recommend a book that
teaches the ideas you’re preaching?” And I would tell them, “Of course, numerous books cover
this subject!” But they didn’t want numerous books, just one, with information distilled to
focus on data analysis and visualization. I realized there wasn’t such a title, and this was how
the idea for this book originated.
Who This Book Is For
Although this book is about software, the target audience is not necessarily programmers or
computer scientists. The reader’s main line of work is research or R&D, in his or her field of
interest, be it astrophysics, signal and image processing, or biology. The audience includes
剩余377页未读，继续阅读
drjiachen
- 粉丝: 171
- 资源: 2139
我的内容管理
展开
最新资源
- 新型矿用本安直流稳压电源设计：双重保护电路
- 煤矿掘进工作面安全因素研究：结构方程模型
- 利用同位素位移探测原子内部新型力
- 钻锚机钻臂动力学仿真分析与优化
- 钻孔成像技术在巷道松动圈检测与支护设计中的应用
- 极化与非极化ep碰撞中J/ψ的Sivers与cos2φ效应：理论分析与COMPASS验证
- 新疆矿区1200m深孔钻探关键技术与实践
- 建筑行业事故预防：综合动态事故致因理论的应用
- 北斗卫星监测系统在电网塔形实时监控中的应用
- 煤层气羽状水平井数值模拟：交替隐式算法的应用
- 开放字符串T对偶与双空间坐标变换
- 煤矿瓦斯抽采半径测定新方法——瓦斯储量法
- 大倾角大采高工作面设备稳定与安全控制关键技术
- 超标违规背景下的热波动影响分析
- 中国煤矿选煤设计进展与挑战：历史、现状与未来发展
- 反演技术与RBF神经网络在移动机器人控制中的应用
资源上传下载、课程学习等过程中有任何疑问或建议，欢迎提出宝贵意见哦~我们会及时处理！
点击此处反馈
