Programming with Python for Engineers

Foreword
Preface
	Target Audience of the Book
	A Note on the Python Version Used in This Book
	How to Use the Book
	Interactive Web Page of the Book
	Solutions Manual
	Textual Conventions in the Book
Acknowledgements
Contents
1 Computing and Computers
	1.1 An Overview
		1.1.1 What Is Computing?
		1.1.2 Are all ``Computing Machinery\'\' Alike?
		1.1.3 What Is a ``Computer\'\'?
		1.1.4 What Is Programming?
	1.2 The Organization of Contemporary Computers
		1.2.1 The von Neumann Architecture
		1.2.2 Peripherals of a Computer
	1.3 The Running of a Computer
		1.3.1 Start-Up Process
		1.3.2 The Operating System (OS)
	1.4 Important Concepts
	1.5 Further Reading
	1.6 Exercises
	References
2 Programming and Programming  Languages
	2.1 How Do We Solve Problems with Programs?
	2.2 Algorithm
		2.2.1 The Origin of the Word ``Algorithm\'\'
		2.2.2 Are Algorithms the Same Thing as Programs?
		2.2.3 How to Write Algorithms?
		2.2.4 How to Compare Algorithms?
	2.3 Data Representation
	2.4 The World of Programming Languages
		2.4.1 Low-Level Languages
		2.4.2 High-Level Languages
		2.4.3 Implementing with a High-Level Language: Interpreter Versus Compiler
		2.4.4 Programming-Language Paradigms
	2.5 Introducing Python
	2.6 Important Concepts
	2.7 Further Reading
	2.8 Exercises
	References
3 Representation of Data
	3.1 Representing Integers
		3.1.1 Sign-Magnitude Notation
		3.1.2 Two\'s Complement Notation
		3.1.3 Why Does Two\'s Complement Work?
		3.1.4 Benefits of the Two\'s Complement Notation
	3.2 Representing Real Numbers
		3.2.1 The IEEE 754 Representation
		3.2.2 Information Loss in Floating-Point Representations
	3.3 Numbers in Python
	3.4 Representing Truth Values (Booleans)
	3.5 Representing Text
		3.5.1 Characters
		3.5.2 Strings
	3.6 Containers
	3.7 Important Concepts
	3.8 Further Reading
	3.9 Exercises
	References
4 Dive into Python
	4.1 Basic Data
		4.1.1 Numbers in Python
		4.1.2 Boolean Values
	4.2 Container Data (str, tuple, list, dict, set)
		4.2.1 Accessing Elements in Sequential Containers
		4.2.2 Useful and Common Container Operations
		4.2.3 String (str)
		4.2.4 List and Tuple
		4.2.5 Dictionary
		4.2.6 Set
	4.3 Expressions
		4.3.1 Arithmetic, Logic, Container, and Comparison Operations
		4.3.2 Bitwise Operators
		4.3.3 Exercise
		4.3.4 Evaluating Expressions
		4.3.5 Implicit and Explicit Type Conversion (Casting)
	4.4 Basic Statements
		4.4.1 Assignment Statement and Variables
		4.4.2 Variables and Aliasing
		4.4.3 Naming Variables
		4.4.4 Other Basic Statements
	4.5 Compound Statements
	4.6 Basic Actions for Interacting with the Environment
		4.6.1 Actions for Input
		4.6.2 Actions for Output
	4.7 Actions That Are Ignored
		4.7.1 Comments
		4.7.2 pass Statement
	4.8 Actions and Data Packaged in Libraries
	4.9 Providing Actions to the Interpreter
		4.9.1 Directly Interacting with the Interpreter
		4.9.2 Writing Actions in a File (Script)
		4.9.3 Using Actions from Libraries (Modules)
	4.10 Important Concepts
	4.11 Further Reading
	4.12 Exercises
	References
5 Conditional and Repetitive Execution
	5.1 Conditional Execution
		5.1.1 The if Statement
		5.1.2 Exercise
		5.1.3 Nested if Statements
		5.1.4 Practice
		5.1.5 Conditional Expression
	5.2 Repetitive Execution
		5.2.1 The while Statement
		5.2.2 Examples with the while Statement
		5.2.3 The for Statement
		5.2.4 Examples with the for Statement
		5.2.5 The continue and break Statements
		5.2.6 Set and List Comprehension
	5.3 Important Concepts
	5.4 Further Reading
	5.5 Exercises
	Reference
6 Functions
	6.1 Why Define Functions?
	6.2 Defining Functions
	6.3 Passing Parameters to Functions
		6.3.1 Default Parameters
	6.4 Scope of Variables
	6.5 Higher-Order Functions
	6.6 Functions in Programming Versus Functions in Mathematics
	6.7 Recursion
	6.8 Function Examples
	6.9 Programming Style
	6.10 Important Concepts
	6.11 Further Reading
	6.12 Exercises
	References
7 A Gentle Introduction to Object-Oriented  Programming
	7.1 Properties of Object-Oriented Programming
		7.1.1 Encapsulation
		7.1.2 Inheritance
		7.1.3 Polymorphism
	7.2 Basic OOP in Python
		7.2.1 The Class Syntax
		7.2.2 Special Methods and Operator Overloading
		7.2.3 Example 1: Counter
		7.2.4 Example 2: Rational Number
		7.2.5 Inheritance with Python
		7.2.6 Interactive Example: A Simple Shape Drawing Program
		7.2.7 Useful Short Notes on Python\'s OOP
	7.3 Widely-Used Member Functions of Containers
		7.3.1 Strings
		7.3.2 Lists
		7.3.3 Dictionaries
		7.3.4 Sets
	7.4 Important Concepts
	7.5 Further Reading
	7.6 Exercises
	References
8 File Handling
	8.1 First Example
	8.2 Files and Sequential Access
	8.3 Data Conversion and Parsing
	8.4 Accessing Text Files Line by Line
	8.5 Termination of Input
	8.6 Example: Processing CSV Files
	8.7 Formatting Files
	8.8 Binary Files
	8.9 Notes on Files, Directory Organization and Paths
	8.10 List of File Class Member Functions
	8.11 Important Concepts
	8.12 Further Reading
	8.13 Exercises
	References
9 Error Handling and Debugging
	9.1 Types of Errors
		9.1.1 Syntax Errors
		9.1.2 Type Errors
		9.1.3 Run-Time Errors
		9.1.4 Logical Errors
	9.2 How to Work with Errors
		9.2.1 Program with Care
		9.2.2 Place Controls in Your Code
		9.2.3 Handle Exceptions
		9.2.4 Write Verification Code and Raise Exceptions
		9.2.5 Debug Your Code
		9.2.6 Write Test Cases
	9.3 Debugging
		9.3.1 Debugging Using Debugging Outputs
		9.3.2 Handle the Exception to Get More Information
		9.3.3 Use the Python Debugger
	9.4 Important Concepts
	9.5 Further Reading
	9.6 Exercises
	References
10 Scientific and Engineering  Libraries
	10.1 Numerical Computing with NumPy
		10.1.1 Arrays and Their Basic Properties
		10.1.2 Working with Arrays
		10.1.3 Linear Algebra with NumPy
		10.1.4 Why Use NumPy? Efficiency Benefits
	10.2 Scientific Computing with SciPy
	10.3 Data Handling and Analysis with Pandas
		10.3.1 Supported File Formats
		10.3.2 Data Frames
		10.3.3 Accessing Data with DataFrames
		10.3.4 Modifying Data with DataFrames
		10.3.5 Analyzing Data with DataFrames
		10.3.6 Presenting Data in DataFrames
	10.4 Plotting Data with Matplotlib
		10.4.1 Parts of a Figure
		10.4.2 Preparing Your Data for Plotting
		10.4.3 Drawing Single Plots
		10.4.4 Drawing Multiple Plots in a Figure
		10.4.5 Changing the Elements of a Plot
	10.5 Important Concepts
	10.6 Further Reading
	10.7 Exercises
	References
11 An Application: Approximation  and Optimization
	11.1 Approximating Functions with Taylor Series
		11.1.1 Taylor Series Example in Python
	11.2 Finding the Roots of a Function
		11.2.1 Newton\'s Method for Finding the Roots
		11.2.2 Misc Details on Newton\'s Method for the Curious
		11.2.3 Newton\'s Method in Python
		11.2.4 Newton\'s Method in SciPy
	11.3 Finding a Minimum of Functions
		11.3.1 Newton\'s Method for Finding the Minimum of a Function
		11.3.2 Misc Details for the Curious
		11.3.3 Newton\'s Method in Python
		11.3.4 Newton\'s Method for Finding Minima in SciPy
	11.4 Important Concepts
	11.5 Further Reading
	11.6 Exercises
	References
12 An Application: Solving a Simple  Regression Problem
	12.1 Introduction
		12.1.1 Why Is Regression Important?
		12.1.2 The Form of the Function
	12.2 Least-Squares Regression
	12.3 Linear Regression with SciPy
		12.3.1 Create Artificial Data
		12.3.2 Download and Visualize Data
		12.3.3 Fit a Linear Function with SciPy
		12.3.4 Analyze the Solution
	12.4 Non-linear Regression with SciPy
		12.4.1 Create Artificial Data
		12.4.2 Download and Visualize Data
		12.4.3 Fitting a Non-linear Function with SciPy
		12.4.4 Analyzing the Solution
	12.5 Important Concepts
	12.6 Further Reading
	12.7 Exercises
	References
Glossary
Index