Jose M Garrido

Introduction to Computational Models with Python

• Gebundenes Buch

Produktbeschreibung

Emphasizing analytical skill development and problem solving, this book shows how to implement computational models using the flexible and easy-to-use Python programming language. It provides the foundation for more advanced work in scientific computing. 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.

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Produktdetails

• Verlag: CRC Press
• Seitenzahl: 496
• Erscheinungstermin: 4. September 2015
• Englisch
• Abmessung: 240mm x 164mm x 32mm
• Gewicht: 873g
• ISBN-13: 9781498712033
• ISBN-10: 1498712037
• Artikelnr.: 42998566

Autorenporträt

José M. Garrido is a professor in the Department of Computer Science at Kennesaw State University. Dr. Garrido is the author of several books and numerous research papers. His research interests include software development, operating systems, computational modeling, object-oriented simulation, and system formal specification.

Inhaltsangabe

Problem Solving: Problem Solving and Computing. Simple Python Programs.
Basic Programming Principles with Python: Modules and Functions. Program
Structures. The Selection Program Structure. The Repetition Program
Structure. Data Structures, Object Orientation, and Recursion: Python
Lists, Strings, and Other Data Sequences. Object Orientation.
Object-Oriented Programs. Linked Lists. Recursion. Fundamental
Computational Models with Python: Computational Models with Arithmetic
Growth. Computational Models with Quadratic Growth. Models with Geometric
Growth. Computational Models with Polynomial Growth. Empirical Models with
Interpolation and Curve Fitting. Using Arrays with Numpy. Models with
Matrices and Linear Equations. Introduction to Models of Dynamical Systems.
Linear Optimization Models: Linear Optimization Modeling. Solving Linear
Optimization Models. Sensitivity Analysis and Duality. Transportation
Models. Network Models. Integer Linear Optimization Models.