A student's guide to Python for physical modeling
著者
書誌事項
A student's guide to Python for physical modeling
Princeton University Press, c2018
Update ed
- : pbk
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注記
Includes bibliographical references and index
内容説明・目次
- 巻冊次
-
ISBN 9780691180564
内容説明
A fully updated tutorial on the basics of the Python programming language for science students
Python is a computer programming language that is rapidly gaining popularity throughout the sciences. This fully updated edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed.
This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including:
Basic Python programming and scripting
Numerical arrays
Two- and three-dimensional graphics
Monte Carlo simulations
Numerical methods, including solving ordinary differential equations
Image processing
Animation
Numerous code samples and exercises--with solutions-illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. This current edition brings the discussion of the Python language, Spyder development environment, and Anaconda distribution up to date. In addition, a new appendix introduces Jupyter notebooks.
- 巻冊次
-
: pbk ISBN 9780691180571
内容説明
A fully updated tutorial on the basics of the Python programming language for science students
Python is a computer programming language that is rapidly gaining popularity throughout the sciences. This fully updated edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed.
This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including:
Basic Python programming and scripting
Numerical arrays
Two- and three-dimensional graphics
Monte Carlo simulations
Numerical methods, including solving ordinary differential equations
Image processing
Animation
Numerous code samples and exercises-with solutions-illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. This current edition brings the discussion of the Python language, Spyder development environment, and Anaconda distribution up to date. In addition, a new appendix introduces Jupyter notebooks.
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