Numerical Methods in Engineering with Python 3

"This book is an introduction to numerical methods for students in engineering. It covers solution of equations, interpolation and data fitting, solution of differential equations, eigenvalue problems and optimisation. The algorithms are implemented in Python 3, a high-level programming language that rivals MATLAB in readability and ease of use. All methods include programs showing how the computer code is utilised in the solution of problems. The book is based on Numerical Methods in Engineering with Python, which used Python 2. This new edition demonstrates the use of Python 3 and includes an introduction to the Python plotting package Matplotlib. This comprehensive book is enhanced by the addition of numerous examples and problems throughout"-- Provided by publisher Contents Preface 1 Introduction to Python 1.1 General Information 1.2 Core Python 1.3 Functions and Modules 1.4 Mathematics Modules 1.5 numpy Module 1.6 Plotting with matplotlib.pyplot 1.7 Scoping of Variables 1.8 Writing and Running Programs 2 Systems of Linear Algebraic Equations 2.1 Introduction 2.2 Gauss Elimination Method 2.3 LU Decomposition Methods Problem Set 2.1 2.4 Symmetric and Banded Coefficient Matrices 2.5 Pivoting Problem Set 2.2 2.6 Matrix Inversion 2.7 Iterative Methods Problem Set 2.3 2.8 Other Methods 3 Interpolation and Curve Fitting 3.1 Introduction 3.2 Polynomial Interpolation 3.3 Interpolation with Cubic Spline Problem Set 3.1 3.4 Least-Squares Fit Problem Set 3.2 4 Roots of Equations 4.1 Introduction 4.2 Incremental Search Method 4.3 Method of Bisection 4.4 Methods Based on Linear Interpolation 4.5 Newton-Raphson Method 4.6 Systems of Equations Problem Set 4.1 4.7 Zeros of Polynomials Problem Set 4.2 4.8 Other Methods 5 Numerical Differentiation 5.1 Introduction 5.2 Finite Difference Approximations 5.3 Richardson Extrapolation 5.4 Derivatives by Interpolation Problem Set 5.1 6 Numerical Integration 6.1 Introduction 6.2 Newton-Cotes Formulas 6.3 Romberg Integration Problem Set 6.1 6.4 Gaussian Integration Problem Set 6.2 6.5 Multiple Integrals Problem Set 6.3 7 Initial Value Problems 7.1 Introduction 7.2 Euler's Method 7.3 Runge-Kutta Methods Problem Set 7.1 7.4 Stability and Stiffness 7.5 Adaptive Runge-Kutta Method 7.6 Bulirsch-Stoer Method Problem Set 7.2 7.7 Other Methods 8 Two-Point Boundary Value Problems 8.1 Introduction 8.2 Shooting Method Problem Set 8.1 8.3 Finite Difference Method Problem Set 8.2 9 Symmetric Matrix Eigenvalue Problems 9.1 Introduction 9.2 Jacobi Method 9.3 Power and Inverse Power Methods Problem Set 9.1 9.4 Householder Reduction to Tridiagonal Form 9.5 Eigenvalues of Symmetric Tridiagonal Matrices Problem Set 9.2 9.6 Other Methods 10 Introduction to Optimization 10.1 Introduction 10.2 Minimization Along a Line 10.3 Powell's Method 10.4 Downhill Simplex Method Problem Set 10.1 Appendices A1 Taylor Series A2 Matrix Algebra List of Program Modules (by Chapter) Index "Baseball is much more than a game. As the American national pastime, it has reflected the political and cultural concerns of US society for over 200 years, and generates passions and loyalties unique in American society. This Companion examines baseball in culture, baseball as culture, and the game's global identity. Contributors contrast baseball's massive, big-business present with its romanticized origins and its evolution against the backdrop of American and world history. The chapters cover topics such as baseball in the movies, baseball and mass media, and baseball in Japan and Latin America. Between the chapters are vivid profiles of iconic characters including Babe Ruth, Ichiro and Walter O'Malley. Crucial moments in baseball history are revisited, ranging from the 1919 Black Sox gambling scandal to recent controversies over steroid use. A unique book for fans and scholars alike, this Companion explains the enduring importance of baseball in America and beyond"-- Provided by publisher This book is an introduction to numerical methods for students in engineering. It covers the usual topics found in an engineering solution of equations, interpolation and data fitting, solution of differential equations, eigenvalue problems, and optimization. The algorithms are implemented in Python 3, a high-level programming language that rivals MATLAB in readability and ease of use. All methods include programs showing how the computer code is utilized in the solution of problems. The book is based on Numerical Methods in Engineering with Python, which used Python 2. This new text demonstrates the use of Python 3 and includes an introduction to the Python plotting package Matplotlib. This comprehensive book is enhanced by the addition of numerous examples and problems throughout. Provides an introduction to numerical methods for students in engineering courses. This book covers the solution of equations, interpolation and data fitting, solution of differential equations, eigenvalue problems and optimisation. The algorithms are implemented in Python 3, a high-level programming language that rivals MATLAB® in readability and ease of use. Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language. Jaan Kiusalaas. Includes Bibliographical References And Index.