Numerical Methods in Engineering with Python

Numerical Methods in Engineering with Python
Authors
Jaan Kiusalaas
ISBN
0521191327
Published
29 Jan 2010
Purchase online
amazon.com

Numerical Methods in Engineering with Python, 2nd Edition is a text for engineering students and a reference for practicing engineers, especially those who wish to explore Python. This new edition features 18 additional exercises and the addition of rational function interpolation. Brent's method of root finding was replaced by Ridder's method, and the Fletcher-Reeves method of optimization was dropped in favor of the downhill simplex method.

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  1. Editorial Reviews
  2. Customer Reviews

Customer Reviews

RF RDC said
Here is a book that lives up to its description:
Numerical Methods in Engineering with Python is a text for engineering students and a reference for practicing engineers, especially those who wish to explore the power and efficiency of Python. Examples and applications were chosen for their relevance to real world problems, and where numerical solutions are most efficient.

If you have a background in Numerical Methods and you have experience with Python then you are good to go, but don't expect the book to teach you either. It doesn't say it will do that and it does not do that. The python intro is highly simplified and has some carless mistakes. The numerical methods used via python assume that you know your numerical methods and how, where, when and why to use them.

Great book, just be sure you know what you are getting into.

Keiichi Ito said
The content is typical of an undergraduate course in numerical methods. The author employs Python for that. It doesn't tell you how to use various modules available on the net. Instead, the author sticks to the standard few and explains numerical methods from the very basics. The book is very good for an introduction coursework. However, if you are a researcher looking for tools for serious numerical computation and thinking of using Python as an efficient and convenient organizer(or "glue") rather than a number cruncher, you might as well consult the book by H.P. Langtangen.

This book is also useful if you want to get a hang on how a textbook numerical method would work on Python. You can then use the language for a quick algorithm prototyping in your own work.

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