A Student`s Guide to Python for Physical Modeling: Second Edition, Nelson Philip, Kinder Jesse M.
Старое издание
Автор: Kinder Jesse M., Nelson Philip Название: A Student`s Guide to Python for Physical Modeling ISBN: 0691180571 ISBN-13(EAN): 9780691180571 Издательство: Wiley Цена: 21120 T Наличие на складе: Поставка под заказ. Описание:
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.
A fully updated tutorial on the basics of the Python programming language for science students
Python is a computer programming language that has gained popularity throughout the sciences. This fully updated second 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 guide introduces a wide range of useful tools, including:
Basic Python programming and scripting
Numerical arrays
Two- and three-dimensional graphics
Animation
Monte Carlo simulations
Numerical methods, including solving ordinary differential equations
Image processing
Numerous code samples and exercises--with solutions--illustrate new ideas as they are introduced. This guide also includes supplemental online resources: code samples, data sets, tutorials, and more. This edition includes new material on symbolic calculations with SymPy, an introduction to Python libraries for data science and machine learning (pandas and sklearn), and a primer on Python classes and object-oriented programming. A new appendix also introduces command line tools and version control with Git.
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