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 m

part |2 pages

Section 1 Problem Solving

chapter 1|22 pages

Problem Solving And Computing

chapter 2|20 pages

Simple Python Programs

part |2 pages

Section 2 Basic Programming Principles With Python

chapter 3|10 pages

Modules And Functions

chapter 4|12 pages

Program Structures

chapter 5|14 pages

The Selection Program Structure

chapter 6|16 pages

The Repetition Program Structure

part |2 pages

Section 3 Data Structures, Object Orientation, And Recursion

chapter 8|6 pages

Object Orientation

chapter 9|14 pages

Object-Oriented Programs

chapter 10|16 pages

Linked Lists

chapter 11|8 pages

Recursion

part |2 pages

Section 4 Fundamental Computational Models With Python

chapter 12|14 pages

Computational Models With Arithmetic Growth

chapter 13|12 pages

Computational Models With Quadratic Growth

chapter 14|10 pages

Models With Geometric Growth

chapter 15|10 pages

Computational Models With Polynomial Growth

chapter 17|16 pages

Using Arrays With Numpy

chapter 18|28 pages

Models With Matrices And Linear Equations

chapter 19|38 pages

Introduction To Models Of Dynamical Systems

part |2 pages

Section 5 Linear Optimization Models

chapter 20|16 pages

Linear Optimization Modeling

chapter 21|16 pages

Solving Linear Optimization Models

chapter 22|12 pages

Sensitivity Analysis And Duality

chapter 23|38 pages

Transportation Models

chapter 24|32 pages

Network Models

chapter 25|20 pages

Integer Linear Optimization Models