A Student's Guide to Python for Physical Modeling, by Jesse M. Kinder, Philip Nelson
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A Student's Guide to Python for Physical Modeling, by Jesse M. Kinder, Philip Nelson
Read and Download A Student's Guide to Python for Physical Modeling, by Jesse M. Kinder, Philip Nelson
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. Web-based resources also accompany this guide and include code samples, data sets, and more.
A Student's Guide to Python for Physical Modeling, by Jesse M. Kinder, Philip Nelson- Amazon Sales Rank: #57711 in Books
- Published on: 2015-09-22
- Original language: English
- Number of items: 1
- Dimensions: 9.90" h x .40" w x 7.80" l, .0 pounds
- Binding: Paperback
- 160 pages
From the Back Cover
"Kinder and Nelson's engaging introduction to scientific programming in Python is careful and thorough, and focuses on actual essentials. Bread-and-butter concepts and techniques, belonging in every computational scientist's toolbox, are presented with well-thought-out examples drawn from daily research practice. This is a clever text, inviting students to take that most important step: to dive right in and start coding."--Cornelis Storm, Eindhoven University of Technology
"Kinder and Nelson have written a friendly and succinct, yet surprisingly comprehensive, introduction to scientific programming in Python. It's written not just for computational scientists, but for anyone who needs to plot and analyze experimental data, numerically solve equations, or learn the basics of programming. Even students who have experience in programming will appreciate the thought-provoking exercises and guidelines for getting the most out of Python." --Vinothan N. Manoharan, Harvard University
"This book is tailor-made for physical scientists beginning to do computation. More than in any other programming book I've read, the authors are conscientious--they anticipate and troubleshoot the areas of confusion readers might encounter. Kinder and Nelson carefully and effectively guide readers toward the goal of formulating a computational problem and solving it."--Justin Bois, California Institute of Technology
"Like patient driving instructors, Kinder and Nelson guide the hands of novice programming students from the get-go, helping them to avoid obstacles and crashes. By the end of the book, students should be racing around confidently like pros, using Python to solve scientific problems of data analysis, modeling, and visualization. A great textbook for a first course in modern scientific programming in any context, and one that I'll be using myself."--Garnet Kin-Lic Chan, Princeton University
"This book covers the basics of Python programming language, with an emphasis on physical modeling. It provides a very useful introduction to Python for undergraduate students and others who have never programmed before."--Zeljko Ivezic, University of Washington
"This is an excellent introductory text, aimed at those with little to no experience in programming. In a clear and concise manner, the authors cover or touch upon all the important aspects of computational science in Python. They guide readers by explaining how to best perform certain common tasks in scientific computing. The book's examples and user exercises are well selected."--Quentin Caudron, Princeton University
About the Author Jesse M. Kinder earned his PhD in physics and astronomy at the University of Pennsylvania, completed a postdoctoral fellowship in quantum chemistry at Cornell University, and taught physics at Case Western Reserve University. He currently works as a consultant in Rio Rancho, New Mexico. Philip Nelson is professor of physics at the University of Pennsylvania. He is the author of Biological Physics and Physical Models of Living Systems.
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Most helpful customer reviews
14 of 15 people found the following review helpful. Finally a well-written and presented Python book for scientific computing - for student's and practitioners alike! By SeferTech I just found this by "accident" while googling a question about python. I am so very happy to have found this book - I purchased the kindle version within minutes of finding it (the paper version is not available for another month) - I just knew this would be a great book. My hunch was right - I love this book! I have been on and off using Python for at least 6 or 7 years as needed for scientific computing. I have perused many of the most popular Python books and purchased a good many. What usually happens is I lose interest quickly and never finish the book. But this book seems different. It is written in a very clear language and gets right to the point of programming with Python and uses the latest packages such as Anaconda or Enthought Canopy with focus on numpy and matplotlib. I really like the style of the book and the content. The level is for beginning programmers (which I am not) but suitable for intermediate and advanced programmers for sure. I highly recommend this for self-study as all the programs are available online and they actually work out of the box. I am sure I will finish this book and refer back to it for years to come.
6 of 7 people found the following review helpful. Excellent introduction to the quantitative features available in Python By Amazon Customer I just finished reading and working all examples in this book. I highly recommend it for anyone interested in scientific computing. The authors' style is straightforward and economical. The topics are well chosen, starting from the simple and working up to the meaty.
0 of 0 people found the following review helpful. Good starter text By MSE fanatic Not a bad quick starter to python for undergraduates in natural sciences and engineering. You will get an overview of programming basics and the necessary python libraries such as NumPy, SciPy, and Matplotlib. I do wish there was more content on the SymPy package.
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