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(4 reviews)
Author: Hans Petter Langtangen
ISBN : 3642302920
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Format: PDF, EPUB
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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.
Direct download links available for Free A Primer on Scientific Programming with Python
- Series: Texts in Computational Science and Engineering (Book 6)
- Hardcover: 850 pages
- Publisher: Springer; 3rd ed. 2012 edition (July 4, 2012)
- Language: English
- ISBN-10: 3642302920
- ISBN-13: 978-3642302923
- Product Dimensions: 1.5 x 7.9 x 10.2 inches
- Shipping Weight: 4.7 pounds (View shipping rates and policies)
Free A Primer on Scientific Programming with Python
It is really easy to get confused with absolutely stunning dual-purpose books like this: 1. To teach you numerical methods and 2. To also teach you Python.
This wonderful text fills a very much needed niche for Engineering, Math and IT/Computer Science students at the AP High School/ beginning undergrad level, as well as for self study, reference, autodidacts. There are two sets of important (and different) keywords for this huge text: In math: CAS (Computer Algebra Systems), Special Functions, Numerical Analysis, Numerical Methods and Numerical Recipes. In Python: Numeric methods interfaces and Python programming.
There are several types of high level languages following structured/imperative, functional and object oriented programming paradigms respectively: C- Fortran type; Lisp- Haskell- Scheme type; and Java, C++, Python etc. on the object side. MOST IMPORTANTLY: there also are "special function" applications languages like R, MatLab, VHDL and other "calculator" software with interfaces especially designed for math functions. When you learn numerical methods, you don't necessarily "use" a lot of the object functions of your language (inheritance for example). Especially with Python 3 (not covered in this book), but in much more advanced texts like Numerical Methods in Engineering with Python 3, which actually is becoming a competitor for MatLab, much fewer object oriented features are actually used, and the GUI looks a LOT like MatLab, Mathcad, Mathematica, etc. when you're done!
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