Introduction to Computational Models with Python

Book Description

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy modules. The Python source code and data files are available on the author’s website.

The book’s five sections present:

1. An overview of problem solving and simple Python programs, introducing the basic models and techniques for designing and implementing problem solutions, independent of software and hardware tools
2. Programming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithms
3. Python lists, arrays, basic data structures, object orientation, linked lists, recursion, and running programs under Linux
4. Implementation of computational models with Python using Numpy, with examples and case studies
5. The modeling of linear optimization problems, from problem formulation to implementation of computational models

This book introduces the principles of computational modeling as well as the approaches of multi- and interdisciplinary computing to beginners in the field. It provides the foundation for more advanced studies in scientific computing, including parallel computing using MPI, grid computing, and other methods and techniques used in high-performance computing.

Table of Contents

Section 1 Problem Solving
Chapter 1 Problem Solving And Computing
Chapter 2 Simple Python Programs

Section 2 Basic Programming Principles With Python
Chapter 3 Modules And Functions
Chapter 4 Program Structures
Chapter 5 The Selection Program Structure
Chapter 6 The Repetition Program Structure

Section 3 Data Structures, Object Orientation, And Recursion
Chapter 7 Python Lists, Strings, And Other Data Sequences
Chapter 8 Object Orientation
Chapter 9 Object- Oriented Programs
Chapter 10 Linked Lists
Chapter 11 Recursion

Section 4 Fundamental Computational Models With Python
Chapter 12 Computational Models With Arithmetic Growth
Chapter 13 Computational Models With Quadratic Growth
Chapter 14 Models With Geometric Growth
Chapter 15 Computational Models With Polynomial Growth
Chapter 16 Empirical Models With Interpolation And Curve Fitting
Chapter 17 Using Arrays With Numpy
Chapter 18 Models With Matrices And Linear Equations
Chapter 19 Introduction To Models Of Dynamical Systems

Section 5 Linear Optimization Models
Chapter 20 Linear Optimization Modeling
Chapter 21 Solving Linear Optimization Models
Chapter 22 Sensitivity Analysis And Duality
Chapter 23 Transportation Models
Chapter 24 Network Models
Chapter 25 Integer Linear Optimization Models

中文：

书名：Introduction to Computational Models with Python

使用Python建立计算模型简介 解释如何使用灵活且易于使用的Python编程语言实现计算模型。这本书使用了Python编程语言解释器和来自大型Python库的几个包，这些包可以提高数值计算的性能，例如Numpy和Scipy模块。作者的网站上提供了Python源代码和数据文件。

The book’s five sections present:

1. 问题解决和简单的Python程序概述，介绍独立于软件和硬件工具设计和实现问题解决方案的基本模型和技术
2. 使用Python编程语言的编程原则，包括基本编程概念、数据定义、使用流程图和伪代码的编程结构、解决问题和算法
3. Python列表、数组、基本数据结构、面向对象、链表、递归和在Linux下运行程序
4. 用Numpy实现用Python语言实现的计算模型，并附有实例和案例研究
5. 线性优化问题的建模，从问题的表达到计算模型的实现

本书向该领域的初学者介绍了计算建模的原理以及多学科和跨学科计算的方法。它为科学计算中更高级的研究提供了基础，包括使用MPI的并行计算、网格计算以及高性能计算中使用的其他方法和技术。

Table of Contents

第一节解决问题
Chapter 1 Problem Solving And Computing
第2章简单的Python程序

第2节使用Python进行编程的基本原则
第三章模块和功能
Chapter 4 Program Structures
Chapter 5 The Selection Program Structure
Chapter 6 The Repetition Program Structure

第3节数据结构、面向对象和递归
第7章Python列出、字符串和其他数据序列
第八章面向对象
第9章面向对象程序
第十章链表
第十一章递归

第4节使用Python的基本计算模型
第12章算术增长的计算模型
第13章二次增长的计算模型
Chapter 14 Models With Geometric Growth
第15章多项式增长的计算模型
第十六章插值法和曲线拟合法的经验模型
第17章将数组与Numpy一起使用
Chapter 18 Models With Matrices And Linear Equations
第十九章动力系统模型导论

Section 5 Linear Optimization Models
Chapter 20 Linear Optimization Modeling
第21章线性优化模型的求解
第二十二章敏感性分析与二元性
第二十三章运输模式
第24章网络模型
第25章整数线性优化模型