Introduction to computational models with python

書誌事項

Introduction to computational models with python

José M. Garrido

(Chapman & Hall/CRC computational science series / series editer, Horst Simon)

CRC Press, c2016

  • : hardback

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注記

Includes bibliographical references (p. 459-460) and index

"A Chapman & Hall book."

内容説明・目次

内容説明

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.

目次

Problem Solving Problem Solving and Computing INTRODUCTION COMPUTER PROBLEM SOLVING ELEMENTARY CONCEPTS DEVELOPING COMPUTATIONAL MODELS TEMPERATURE CONVERSION AREA AND PERIMETER OF A CIRCLE CATEGORIES OF COMPUTATIONAL MODELS GENERAL PROCESS OF SOFTWARE DEVELOPMENT MODULAR DESIGN PROGRAMMING LANGUAGES PRECISION, ACCURACY, AND ERRORS Simple Python Programs INTRODUCTION COMPUTING WITH PYTHON PROGRAMS DATA DEFINITIONS SIMPLE PYTHON PROGRAMS A SIMPLE PROBLEM: TEMPERATURE CONVERSION DISTANCE BETWEEN TWO POINTS GENERAL STRUCTURE OF A PYTHON PROGRAM SIMPLE FUNCTIONS Basic Programming Principles with Python Modules and Functions INTRODUCTION MODULAR DECOMPOSITION FUNCTIONS CATEGORIES OF FUNCTIONS BUILT-IN MATHEMATICAL FUNCTIONS Program Structures INTRODUCTION ALGORITHMS IMPLEMENTING ALGORITHMS ALGORITHM DESCRIPTION DESIGN STRUCTURES COMPUTING AREA AND CIRCUMFERENCE The Selection Program Structure INTRODUCTION CONDITIONAL EXPRESSIONS THE SELECTION STRUCTURE A COMPUTATIONAL MODEL WITH SELECTION MULTI-LEVEL SELECTION The Repetition Program Structure INTRODUCTION REPETITION WITH THE WHILE-LOOP REPEAT-UNTIL LOOP FOR-LOOP STRUCTURE Data Structures, Object Orientation, and Recursion Python Lists, Strings, and Other Data Sequences INTRODUCTION LISTS TEMPERATURE CONVERSION PROBLEM LIST COMPREHENSIONS LISTS OF LISTS TUPLES DICTIONARIES STRINGS SIMPLE NUMERICAL APPLICATIONS USING LISTS Object Orientation INTRODUCTION OBJECTS IN THE PROBLEM DOMAIN DEFINING CLASSES DESCRIBING OBJECTS INTERACTION BETWEEN TWO OBJECTS DESIGN WITH CLASSES Object-Oriented Programs INTRODUCTION PROGRAMS DEFINITION OF CLASSES CLASS DEFINITIONS IN PYTHON CREATING AND MANIPULATING OBJECTS COMPLETE PROGRAM WITH A CLASS SCOPE OF VARIABLES CLASS HIERARCHY WITH INHERITANCE DEFINING CLASSES WITH INHERITANCE OVERLOADING AND OVERRIDING METHODS Linked Lists INTRODUCTION NODES AND LINKED LISTS LINKED LISTS WITH TWO ENDS DOUBLE-LINKED LISTS STACKS AND QUEUES DATA STRUCTURES Recursion INTRODUCTION RECURSIVE APPROACH TO PROBLEM SOLVING RECURSIVE DEFINITION OF FUNCTIONS ANALYZING RECURSION Fundamental Computational Models with Python Computational Models with Arithmetic Growth INTRODUCTION MATHEMATICAL MODELING MODELS WITH ARITHMETIC GROWTH USING THE PYTHON LANGUAGE AND NUMPY PRODUCING THE CHARTS OF THE MODEL VALIDATION OF A MODEL FILE I/O Computational Models with Quadratic Growth INTRODUCTION DIFFERENCES OF THE DATA DIFFERENCE EQUATIONS FUNCTIONAL EQUATIONS EXAMPLES OF QUADRATIC MODELS Models with Geometric Growth INTRODUCTION BASIC CONCEPTS FUNCTIONAL EQUATIONS IN GEOMETRIC GROWTH Computational Models with Polynomial Growth INTRODUCTION GENERAL FORMS OF POLYNOMIAL FUNCTIONS THE polynomial MODULE OF THE numpy PACKAGE EVALUATION OF POLYNOMIAL FUNCTIONS SOLVING POLYNOMIAL FUNCTIONS Empirical Models with Interpolation and Curve Fitting INTRODUCTION INTERPOLATION CURVE FITTING MODELING THE HEAT CAPACITY OF CARBON DIOXIDE Using Arrays with Numpy INTRODUCTION VECTORS AND OPERATIONS VECTOR PROPERTIES AND CHARACTERISTICS USING ARRAYS IN PYTHON WITH NUMPY SIMPLE VECTOR OPERATIONS Models with Matrices and Linear Equations INTRODUCTION MATRICES MATRIX MANIPULATION WITH NUMPY SOLVING SYSTEMS OF LINEAR EQUATIONS INDUSTRIAL MIXTURES IN MANUFACTURING Introduction to Models of Dynamical Systems INTRODUCTION AVERAGE AND INSTANTANEOUS RATE OF CHANGE THE FREE-FALLING OBJECT DERIVATIVE OF A FUNCTION NUMERICAL INTEGRATION WORK PRODUCED IN A PISTON WITH AN IDEAL GAS DIFFERENTIAL EQUATIONS MODELS OF DYNAMICAL SYSTEMS FORMULATING SIMPLE EXAMPLES SOLUTION OF DIFFERENTIAL EQUATIONS Linear Optimization Models Linear Optimization Modeling INTRODUCTION GENERAL FORM OF A LINEAR OPTIMIZATION MODEL THE SIMPLEX ALGORITHM DESCRIPTION OF THE SIMPLEX ALGORITHM FORMULATION OF LINEAR OPTIMIZATION MODELS EXAMPLE PROBLEMS Solving Linear Optimization Models INTRODUCTION LINEAR OPTIMIZATION MODELS WITH PYTHON MODELING WITH PYOMO MODELING WITH PULP SOFTWARE LINEAR OPTIMIZATION SOLVERS SHORT LIST OF OPTIMIZATION SOLVERS Sensitivity Analysis and Duality INTRODUCTION SENSITIVITY ANALYSIS DUALITY Transportation Models INTRODUCTION MODEL OF A TRANSPORTATION PROBLEM TRANSPORTATION CASE STUDY 1 UNBALANCED PROBLEM: CASE STUDY 2 UNBALANCED PROBLEM: CASE STUDY 3 TRANSSHIPMENT MODELS TRANSSHIPMENT PROBLEM: CASE STUDY 4 ASSIGNMENT PROBLEMS 7 ASSIGNMENT PROBLEM: CASE STUDY 5 Network Models INTRODUCTION GRAPHS SHORTEST PATH PROBLEM SHORTEST PATH: CASE STUDY 1 MAXIMUM FLOW PROBLEMS CRITICAL PATH METHOD REDUCING THE TIME TO COMPLETE A PROJECT Integer Linear Optimization Models INTRODUCTION MODELING WITH INTEGER VARIABLES APPLICATIONS OF INTEGER LINEAR OPTIMIZATION INTEGER LINEAR OPTIMIZATION: CASE STUDY 1 INTEGER LINEAR OPTIMIZATION: CASE STUDY 2 A Summary and Exercises appear at the end of each chapter.

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