What This Book Includes
        Is This Book for You
        What Do You Need to Use This Book
        How This Book is Organized
        Using Code Examples
        Customer Support


Welcome to Practical Numerical Methods with C#. This book is intended for scientists, engineers, and .NET developers who want to create scientific and engineering applications using C# and the .NET Framework. For many years, FORTRAN has been the dominant language of scientific and engineering computation. But as Microsoft C# and .NET Framework gain popularity, you may find that they are also suitable for technical computing. This book presents C#-based procedures that perform fundamental mathematical and numerical computations critical to scientists and engineers.

The power of the C# programming language, combined with the simplicity of implementing Windows Forms, WPF desktop applications, and Silverlight Web applications based on Visual Studio .NET framework, makes real-world .NET program development faster and easier than ever before. Visual C# is a versatile and flexible tool that allows users with even the most elementary programming abilities to not only perform complicated computations, but also to display the calculated results in a variety of graphical representations. In this regard, C# is more powerful than FORTRAN, because it is hard to show results graphically using FORTRAN.

The main advantage of using FORTRAN in scientific and engineering computing is its rich math libraries. These libraries implement a complete collection of mathematical, statistical, and numerical algorithms, which have been evolving steadily for several decades. Each subroutine and algorithm in these libraries has undergone rigorous testing and quality assurance, providing users with more time to focus on their applications. On the other hand, the C# programming language is relatively new to the scientific and engineering community. The lack of C# math libraries prevents many researchers from using the C# programming language in their applications. In this book, I will show you that it is fairly easy to develop math libraries in C#, and that it is worth developing scientific and engineering applications using C# due to its computing power and graphical representations capability.

The aim of this book is to provide scientists and engineers with a comprehensive explanation of scientific computing using C#. Much of the work in this book is original, based on my own programming experience in developing commercial Computer Aided Design (CAD) packages, which involve intensive scientific computations and sophisticated graphical representations. With FORTRAN, developing advanced graphics and chart applications is a difficult and time-consuming task. To add even simple charts or graphs to your applications, you have to waste either effort creating a chart program, or money buying commercial graphics and chart add-on packages. Visual C# and its rich graphics features make it possible to easily implement both powerful math libraries and professional graphics using entirely managed C# codes.

Practical Numerical Methods with C# provides an in-depth introduction to performing complicated scientific computations using C# applications. In this book, I will begin with an overview of the C# and .NET Framework, and then present procedural descriptions of linear algebra, numerical solution of nonlinear and ordinary differential equations, optimization, parameter estimation, and special functions of mathematical physics. I will show you how to create useful C# mathematical and numerical libraries that you can use in real-world scientific and engineering problems. I will try my best to introduce the C# program to scientists and engineers in a simple way--simple enough for C# beginners to follow with ease. From this book, you will learn how to perform complicated scientific computations and create your own math libraries based on C# and the .NET Framework.

Practical Numerical Methods with C# is not simply a book, but a powerful C# math library. You will find that you can immediately use some of the examples in this book to solve your real-world problems, and that you can use others to give you inspiration for adding more advanced math libraries to your applications.

What This Book Includes

This book and its sample code listings, which are available for download at this website, provide you with:

Is This Book for You

You do not have to be an experienced C# developer or expert to use this book. I designed this book to be useful to scientists and engineers of all levels of C# programming experience. In fact, I believe that if you have some experience with programming languages other than C#, you will be able to sit down in front of your computer, start up the Microsoft .NET Framework SDK or Visual Studio .NET, follow the examples provided with this book, and quickly become familiar with C# programming in scientific computing. For those of you who are already experienced C# developers, I believe this book has plenty to offer to you as well. The information in this book about creating C# math libraries is not available in any other C# tutorial and reference book. In addition, most of the example programs provided in this book can be used directly in your own real-world application development. This book will provide you with a level of detail, explanation, instruction, and sample program code that will enable you to do just about anything scientific and engineering computing-related with Visual C#.

This book is specifically designed for scientists and engineers. In fact, my own background is in theoretical physics, a field involving extensive numerical calculations as well as graphical representations of calculated data. I have been dedicated to this field for many years. My first computer experience was with FORTRAN. Later on, I gained programming experience in Basic, C, C++, and MATLAB. I still remember how hard it was in those early days to present computational results graphically. I often spent hours creating a publication-quality chart by hand, using a ruler, graph paper, and rub-off lettering. During that time, I started to pay attention to various development tools that could be used to create integrated applications. I tried to find an ideal development tool that would allow me to not only easily generate data (computation capability) but also easily represent data graphically (graphics and chart power). The C# and Microsoft Visual Studio .NET development environment makes it possible to develop such integrated applications. Ever since Microsoft .NET 1.0 came out, I have been in love with the C# language, and have used this tool to successfully create powerful scientific and plotting applications, including commercial CAD packages.

The majority of the example programs in this book can be used routinely by scientists and engineers. Throughout this book, I will emphasize the usefulness of C# programming in solving real-world scientific and engineering problems. If you follow this book closely, you will be able to easily develop various math and numerical libraries. At the same time, I will not spend too much time discussing program style, execution speed, and code optimization, because there is already a plethora of books out there that deal with these topics. Most of the example programs in this book omit error handling. This makes the code easier to understand by focusing on the key concepts.

Note that this book focuses on numerical computing methods and math library development using C#. It will not address the graphical representations of calculation results, even though the real power of the .NET Framework is its ability to create graphics and user interfaces. If you are interested in graphics and user interface programming in C#, you can read my other books:

Practical C# Charts and Graphics - This book is a perfect guide to learning all the basics for creating advanced chart and graphics applications in C#, GDI+, and Windows Form. It clearly explains practical chart and graphics methods and their underlying algorithms. The 2D and 3D chart packages contained in the book can be directly used in your C# applications.

Practical WPF Graphics Programming - This book provides all the information you need to add advanced graphics to your .NET applications using C# and Windows Presentation Foundation (WPF), which comes with the new version (3.0 or later) of .NET framework. From 2D shapes and charts to complex interactive 3D models, this book uses code examples to explain every step it takes to build a variety of WPF graphics applications.

Practical Silverlight Programming - This book shows you how to develop rich interactive applications (RIAs) for Web using C# and Silverlight. Silverlight is a subset of WPF and enables you to create advanced graphics and user interfaces for Web applications. You will learn from this book how to display your computation results graphically and interactively over the internet.

What Do You Need to Use This Book

You will need no special equipment to make the best use of this book and understand the algorithms. To run and modify the sample programs, you will need a computer capable of running either the Windows Vista or XP operating system. The software installed on your computer should include .NET Framwork SDK 2.0 or later, which is available for free at the Microsoft Website. It is best to have Visual Studio 2005 or 2008 standard edition or higher. Please note that all of the example programs and math libraries were created and tested in Visual Studio 2008. However, the example code should be independent of the platform you use.

How This Book is Organized

This book is organized into fifteen chapters, each of which covers a different topic of numerical computing. The following summaries of each chapter should give you an overview of the book?s contents:

Chapter 1, Overview of C# Programming
This chapter introduces the basics of C# programming, including the basic types, properties, methods, mathematical operations, and how to create branches and loops.

Chapter 2, Complex Numbers and Functions
This chapter demonstrates how to implement a complex structure, which contains the definition of complex numbers, complex operators, and commonly used complex functions. This structure allows you to perform various computations using complex numbers and functions.

Chapter 3, Vectors and Matrices
This chapter introduces a more general n-dimensional vector class and a general matrix class with the n×m dimension, which can be used in many scientific and engineering computations involving the solution of linear equations with multiple variables. Matrix analysis is a basic theory of these linear operations.

Chapter 4, LinearAlgebraic Equations
This chapter introduces various numerical methods for solving linear equations with an arbitrary number of unknowns. Solving linear equations is one of the most commonly used operations in numerical analysis and scientific and engineering applications.

Chapter 5, Nonlinear Equations
This chapter describes several numerical methods for solving nonlinear equations. These numerical methods are all iterative in nature, and may be used for equations that contain one or several variables.

Chapter 6, Special Functions
This chapter discusses a special function class, which contains popular special functions such as the gamma function, beta function, error function, elliptic integral, Laguerre function, Hermit function, Chebyshev function, Legendre function, and Bessel function, among others.

Chapter 7, Random Numbers and Distribution Functions
This chapter covers a variety of random number generators and different probability distribution functions, which can be used to simulate the different chaotic circumstances that can be found in the real world.

Chapter 8, Interpolation
This chapter explains the implementation of several interpolation methods, which can be used to construct new data points within the range of a discrete set of known data points. Interpolation can be regarded as a special case of curve fitting, in which the function must go exactly through the data points.

Chapter 9, Curve Fitting
This chapter explains a variety of curve fitting approaches that can be applied to data containing noise, usually due to measurement errors. Curve fitting tries to find the best fit to a set of given data. Thus, the curve does not necessarily pass through all of the given data points.

Chapter 10, Optimization
This chapter covers several popular methods for optimizing functions with multiple variables, including the golden search, Newton, simplex, simulated annealing, and differential evolution techniques. In particular, simulated annealing and differential evolution can deal with highly nonlinear models, chaotic and noisy data, and constraints.

Chapter 11, Numerical Differentiation
This chapter discusses several methods of numerical differentiation, such as forward and backward difference, central difference, extended central difference, Richardson extrapolation, and derivatives by interpolation. These methods provide you with different tools for estimating the derivative of a function.

Chapter 12, Numerical Integration
This chapter covers a variety of methods for numerical integration, including methods based on Newton-Cotes formulas, Romberg integration, and Gaussian quadrature methods. These methods can be used to estimate the finite and infinite integrals of functions.

Chapter 13, Ordinary Differential Equations
This chapter focuses on solving ordinary differential equations numerically. It presents several popular methods including the Euler method, second- and fourth-order Runge-Kutta methods, the adaptive Runge-Kutta method, and the Runge-Kutta methods that can be used to solve a system of ordinary differential equations.

Chapter 14, Boundary Value Problems
This chapter discusses two methods for solving boundary value problems: the shooting method and the finite differences method. The shooting method involves guessing the missing values, and the resulting solution is very unlikely to satisfy boundary conditions at the other end. The finite difference method involves approximating the differential equations by finite differences at evenly spaced mesh points.

Chapter 15, Eigenvalue Problems
This chapter presents several popular methods for solving eigenvalue problems, including the Jacobi method, power iteration, Rayleigh method, Rayleigh-quotient method, and matrix tridiagonalization method. These methods offer you nontrivial tools for calculating eigenvalues and eigenvectors of real symmetric matrix systems.

Using Code Examples

You may use the code in this book in your applications and documentation. You do not need to contact me or the publisher for permission unless you are reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing the example code listings does require permission. Incorporating a significant amount of example code from this book into your applications and documentation does require permission. Integrating the example code from this book into your commercial products is not allowed without the written permission from the author.

Customer Support

I am always interested in hearing from readers, and would like to hear your thoughts on this book. You can send me comments by email: jxu at I will also provide updates, bug fixes, and ongoing support on this very website.

You can also obtain the complete source code for all of examples in this book from this website, here.