A Student?s Guide to Python for Physical Modeling

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9780691170503: A Student?s Guide to Python for Physical Modeling
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"The text serves as an excellent stepping stone into the world of using Python in computational science for undergraduate students with a strong background in mathematics."--Kevin Thielen and Vivienne Tien, Computing in Science & Engineering

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Python is a computer programming language that is rapidly gaining popularity throughout the sciences. 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. A website that accompanies this guide provides additional resources, including data sets and sample code.

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Jesse M. Kinder
Verlag: Princeton University Press Okt 2015 (2015)
ISBN 10: 0691170509 ISBN 13: 9780691170503
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Buchbeschreibung Princeton University Press Okt 2015, 2015. Taschenbuch. Buchzustand: Neu. 253x202x10 mm. Neuware - Python is a computer programming language that is rapidly gaining popularity throughout the sciences. A Students 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. 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. 160 pp. Englisch. Artikel-Nr. 9780691170503

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