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Preface to the First Edition viii
Preface to the Second Edition x
1 Introduction to Python 1
1.1 General Information 1
1.2 Core Python 3
1.3 Functions and Modules 15
1.4 Mathematics Modules 17
1.5 numpy Module 18
1.6 Scoping of Variables 24
1.7 Writing and Running Programs 25
2 Systems of Linear Algebraic Equations 27
2.1 Introduction 27
2.2 Gauss Elimination Method 33
2.3 LU Decomposition Methods 40
Problem Set 2.1 51
2.4 Symmetric and Banded Coefficient Matrices 54
2.5 Pivoting 64
Problem Set 2.2 73
*2.6 Matrix Inversion 79
*2.7 Iterative Methods 82
Problem Set 2.3 93
*2.8 Other Methods 97
3 Interpolation and Curve Fitting 99
3.1 Introduction 99
3.2 Polynomial Interpolation 99
3.3 Interpolation with Cubic Spline 114
Problem Set 3.1 121
3.4 Least-Squares Fit 124
Problem Set 3.2 135
4 Roots of Equations 139
4.1 Introduction 139
4.2 Incremental Search Method 140
4.3 Method of Bisection 142
4.4 Methods Based on Linear Interpolation 145
4.5 Newton-Raphson Method 150
4.6 Systems of Equations 155
Problem Set 4.1 160
*4.7 Zeroes of Polynomials 166
Problem Set 4.2 174
5 Numerical Differentiation 177
5.1 Introduction 177
5.2 Finite Difference Approximations 177
5.3 Richardson Extrapolation 182
5.4 Derivatives by Interpolation 185
Problem Set 5.1 189
6 Numerical Integration 193
6.1 Introduction 193
6.2 Newton-Cotes Formulas 194
6.3 Romberg Integration 202
Problem Set 6.1 207
6.4 Gaussian Integration 211
Problem Set 6.2 225
*6.5 Multiple Integrals 227
Problem Set 6.3 239
7 Initial Value Problems 243
7.1 Introduction 243
7.2 Taylor Series Method 244
7.3 Runge-Kutta Methods 249
Problem Set 7.1 260
7.4 Stability and Stiffness 266
7.5 Adaptive Runge-Kutta Method 269
7.6 Bulirsch-Stoer Method 277
Problem Set 7.2 284
7.7 Other Methods 289
8 Two-Point Boundary Value Problems 290
8.1 Introduction 290
8.2 Shooting Method 291
Problem Set 8.1 301
8.3 Finite Difference Method 305
Problem Set 8.2 314
9 Symmetric Matrix Eigenvalue Problems 319
9.1 Introduction 319
9.2 Jacobi Method 321
9.3 Power and Inverse Power Methods 337
Problem Set 9.1 345
9.4 Householder Reduction to Tridiagonal Form 351
9.5 Eigenvalues of Symmetric Tridiagonal Matrices 358
Problem Set 9.2 367
9.6 Other Methods 373
10 Introduction to Optimization 374
10.1 Introduction 374
10.2 Minimization along a Line 376
10.3 Powell's Method 382
10.4 Downhill Simplex Method 392
Problem Set 10.1 399
10.5 Other Methods 406
A1 Taylor Series 407
A2 Matrix Algebra 410
List of Program Modules (by Chapter) 416
Index 419
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Add Numerical Methods in Engineering with Python, Numerical Methods in Engineering with Python, 2nd Edition is a text for engineering students and a reference for practicing engineers, especially those who wish to explore Python. This new edition features 18 additional exercises and the addition of ratio, Numerical Methods in Engineering with Python to the inventory that you are selling on WonderClubX
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Add Numerical Methods in Engineering with Python, Numerical Methods in Engineering with Python, 2nd Edition is a text for engineering students and a reference for practicing engineers, especially those who wish to explore Python. This new edition features 18 additional exercises and the addition of ratio, Numerical Methods in Engineering with Python to your collection on WonderClub |