Introduction to Computational Models with Python (Hardcover)

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.

《使用Python介紹計算模型》解釋了如何使用靈活且易於使用的Python程式語言來實現計算模型。該書使用Python程式語言解譯器以及Python庫中的幾個套件，這些套件可以提高數值計算的性能，例如Numpy和Scipy模組。作者的網站上提供了Python原始碼和數據文件。

該書的五個部分包括：

1. 問題解決和簡單Python程式的概述，介紹設計和實現問題解決的基本模型和技術，獨立於軟體和硬體工具。
2. 使用Python程式語言的程式設計原則，包括基本程式設計概念、資料定義、流程圖和偽代碼的程式設計結構、問題解決和演算法。
3. Python列表、陣列、基本資料結構、物件導向、鏈結列表、遞迴以及在Linux下運行程式。
4. 使用Numpy在Python中實現計算模型，並提供示例和案例研究。
5. 線性優化問題的建模，從問題定義到計算模型的實現。

該書向初學者介紹了計算模型的原則以及多學科和跨學科計算的方法。它為科學計算的更高級研究奠定了基礎，包括使用MPI進行並行計算、網格計算和高性能計算中使用的其他方法和技術。