Programming for Computations - Python

A Gentle Introduction to Numerical Simulations with Python 3.6

by Svein Linge, Hans Petter Langtangen

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Book Description

This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected.

The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students.

The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.

This open book is licensed under a Creative Commons License (CC BY). You can download Programming for Computations - Python ebook for free in PDF format (7.3 MB).

Table of Contents

Chapter 1
The First Few Steps
1.1 What Is a Program? And What Is Programming?
1.2 A Python Program with Variables
1.3 A Python Program with a Library Function
1.4 Importing from Modules and Packages
1.5 A Python Program with Vectorization and Plotting
1.6 Plotting, Printing and Input Data
1.7 Error Messages and Warnings
1.8 Concluding Remarks
1.9 Exercises
Chapter 2
A Few More Steps
2.1 Using Python Interactively
2.2 Variables, Objects and Expressions
2.3 Numerical Python Arrays
2.4 Random Numbers
2.5 Exercises
Chapter 3
Loops and Branching
3.1 The for Loop
3.2 The while Loop
3.3 Branching (if, elif and else)
3.4 Exercises
Chapter 4
Functions and the Writing of Code
4.1 Functions: How to Write Them?
4.2 Programming as a Step-Wise Strategy
4.3 Exercises
Chapter 5
Some More Python Essentials
5.1 Lists and Tuples: Alternatives to Arrays
5.2 Exception Handling
5.3 Symbolic Computations
5.4 Making Our Own Module
5.5 Files: Read and Write
5.6 Measuring Execution Time
5.7 Exercises
Chapter 6
Computing Integrals and Testing Code
6.1 Basic Ideas of Numerical Integration
6.2 The Composite Trapezoidal Rule
6.3 The Composite Midpoint Method
6.4 Vectorizing the Functions
6.5 Rate of Convergence
6.6 Testing Code
6.7 Double and Triple Integrals
6.8 Exercises
Chapter 7
Solving Nonlinear Algebraic Equations
7.1 Brute Force Methods
7.2 Newton's Method
7.3 The Secant Method
7.4 The Bisection Method
7.5 Rate of Convergence
7.6 Solving Multiple Nonlinear Algebraic Equations
7.7 Exercises
Chapter 8
Solving Ordinary Differential Equations
8.1 Filling a Water Tank: Two Cases
8.2 Population Growth: A First Order ODE
8.3 Spreading of Disease: A System of First Order ODEs
8.4 Oscillating 1D Systems: A Second Order ODE
8.5 Rate of Convergence
8.6 Exercises
Chapter 9
Solving Partial Differential Equations
9.1 Example: Temperature Development in a Rod
9.2 Finite Difference Methods
9.3 Exercises

Book Details

Computer Science
ISBN13 Digital
ISBN10 Digital
PDF Size
7.3 MB

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