J. Garrido. Chapman & Hall/CRC Computational Science CRC Press, (2016)
Abstract
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. Divided ed into five sections, the book first introduces the basic models and techniques for designing and implementing problem solutions, independent of software and hardware tools. The second section discusses programming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithms. The third section describes Python lists, arrays, basic data structures, object orientation, linked lists and recursion, and running programs under Linux. In the fourth section, examples and case studies demonstrate the application of programming principles and fundamental techniques to relatively simple computational models. The final section focuses on the modeling of linear optimization problems, from problem formulation to implementation of computational models.
%0 Book
%1 citeulike:14168750
%A Garrido, José M.
%B Chapman & Hall/CRC Computational Science
%D 2016
%I CRC Press
%K python 00a71-theory-of-mathematical-modeling 68n15-programming-languages 93a30-systems-theory-mathematical-modeling 68u20-computational-simulation
%T Introduction to Computational Models with Python
%U http://www.worldcat.org/isbn/1498712045
%X 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. Divided ed into five sections, the book first introduces the basic models and techniques for designing and implementing problem solutions, independent of software and hardware tools. The second section discusses programming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithms. The third section describes Python lists, arrays, basic data structures, object orientation, linked lists and recursion, and running programs under Linux. In the fourth section, examples and case studies demonstrate the application of programming principles and fundamental techniques to relatively simple computational models. The final section focuses on the modeling of linear optimization problems, from problem formulation to implementation of computational models.
%@ 1498712045
@book{citeulike:14168750,
abstract = {{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. Divided ed into five sections, the book first introduces the basic models and techniques for designing and implementing problem solutions, independent of software and hardware tools. The second section discusses programming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithms. The third section describes Python lists, arrays, basic data structures, object orientation, linked lists and recursion, and running programs under Linux. In the fourth section, examples and case studies demonstrate the application of programming principles and fundamental techniques to relatively simple computational models. The final section focuses on the modeling of linear optimization problems, from problem formulation to implementation of computational models.}},
added-at = {2017-06-29T07:13:07.000+0200},
author = {Garrido, Jos\'{e} M.},
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keywords = {python 00a71-theory-of-mathematical-modeling 68n15-programming-languages 93a30-systems-theory-mathematical-modeling 68u20-computational-simulation},
posted-at = {2016-10-19 23:44:32},
priority = {2},
publisher = {CRC Press},
series = {Chapman \& Hall/CRC Computational Science},
timestamp = {2019-05-01T06:14:12.000+0200},
title = {Introduction to Computational Models with {P}ython},
url = {http://www.worldcat.org/isbn/1498712045},
year = 2016
}