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A Primer on Scientific Programming with Python

by Langtangen, Hans Petter.
Authors: SpringerLink (Online service) Series: Texts in Computational Science and Engineering, 1611-0994 ; . 6 Physical details: XXX, 706p. 72 illus., 28 illus. in color. online resource. ISBN: 3642183662 Subject(s): Mathematics. | Software engineering. | Computer science. | Mathematics. | Computational Science and Engineering. | Programming Techniques. | Software Engineering/Programming and Operating Systems. | Mathematics of Computing. | Numerical and Computational Physics.
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Item type Location Call Number Status Date Due
E-Book E-Book AUM Main Library 004 (Browse Shelf) Not for loan

Computing with Formulas -- Loops and Lists -- Functions and Branching -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Files, Strings and Dictionaries -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus.- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Technical Topics -- Bibliography -- Index  .

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.

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