文件名称：Introduction.to.Computational.Models.with.Python.1498712037
文件大小：11.28MB
文件格式：PDF
更新时间：2018-12-01 08:01:00
Python Models
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: 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 Programming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithms Python lists, arrays, basic data structures, object orientation, linked lists, recursion, and running programs under Linux Implementation of computational models with Python using Numpy, with examples and case studies 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