Introduction to Computational Models with Python

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Название:Introduction to Computational Models with Python

Автор:Jose M. Garrido

Издательство: CRC Press

Серия:Chapman & Hall/CRC Computational Scienc

Год: 2015

Страниц: 466

Язык: English

Формат: pdf

Размер: 11 Mb

Features

Presents the fundamental principles for developing computational models for a wide variety of applications

Emphasizes analytical skill development and problem solving, including reasoning about and conceptualizing problems, mathematical formulation, and computational solutions that involve computing results and visualization

Shows how to implement the computational models using open-source and platform-independent software tools

Offers the Python source code, data files, and some output files on the author’s website

Summary

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.