In the following table, each line/entry contains the code file name, the page number where it can be found in the textbook, and a brief description. Click on the program name to display the source code, which can then be downloaded.
| Chapter 1: Introduction | ||
| horner_symbolic | 3 | Manipulation of Horner polynomial |
| sin_plot | 18-19 | Graph of Taylor series partial sums sin(x) |
| taylor_series | 22 | Taylor series expansion of functions |
| sqrt_approx | 27 | Taylor series expansion of square roots | Chapter 2: Number Representation and Errors |
| convert | 51 | Converting numbers |
| loss_of_significance | 78 | Loss of significance in subtraction |
| accuracy | 81 | Computations with various accuracy |
| Chapter 3: Locating Roots of Equations | ||
| fcn_roots | 97 | Roots of functions |
| newt | 107-108 | Newton's method example |
| poly_roots | 128 | Roots of a 5th degree polynomial |
| Chapter 4: Interpolation and Numerical Differentiation | ||
| newton_interp | 145,152,176 | Newton interpolation polynomial |
| runge_fun | 170-171 | Polynomial interpolation for Runge function |
| derivative | 186 | Symbolic and numerical derivative |
| Chapter 5: Numerical Integration | ||
| num_integ1 | 201 | Numerical integration of exp(-x*x) |
| trapezoid_rule | 208 | Trapezoid rule for an integral |
| comp_trap_rule | 212 | Composite Trapezoid rule for an integral | Chapter 6: More on Numerical Integration |
| num_integ2 | 242 | Numerical integration of cos(2*x)/exp(x) |
| Chapter 7: Systems of Linear Equations | ||
| gauss_elim1 | 266 | Gaussian elimination first example |
| gauss_elim2 | 289-290 | Gaussian elimination second example |
| band | 303 | Banded linear system example |
| penta | 305 | Pentadiagonal example |
| pentasym | 305 | Pentadiagonal symmetric example |
| Chapter 8: More on Systems of Linear Equations | ||
| lu | 325,328 | LU decomposition |
| lufactor | 328-329 | LU factorization |
| cp8-2-8 | 356 | Computer Problem 8.2.8 |
| char | 358 | Eigenvalues via characteristic polynomial |
| null | 359 | Null space, eigenvalues/eigenvectors |
| eigen | 360 | Eivenvalues/eigenvectors (LinearAlgebra) |
| Schur | 362-363 | Schur decomposition (Linear Algebra) |
| Svd | 366 | Singular value decomposition (linalg) |
| sng_val_decomp | 367 | Singular value decomposition (LinearAlgebra) |
| Chapter 9: Approximation by Spline Functions | ||
| cubic_spline1 | 402 | Plot of natural cubic spline curve |
| cubic_spline2 | 407 | Generate and plot cubic spline curve |
| bernstein_poly | 432 | Graph of few Bernstein polynomials |
| ctrl_pt_curve | 433 | Generating curves using control points |
| Chapter 10: Ordinary Differential Equations | ||
| ode0 | 443 | Numerical solution of an IVP: example 0 |
| ode1 | 444 | Numerical solution of an IVP: example 1 |
| euler | 449 | Euler's method for solving an ODE |
| ode2 | 452 | Numerical solution of an IVP: example 2 |
| ode3 | 453 | Taylor series method (order 4) solving ODE: example 3 |
| ode4 | 463 | Numerical solution of an IVP: example 4 |
| adams_mlt_coef | 477 | Adams-Moulton formulas |
| Chapter 11: Systems of Ordinary Differential Equations | ||
| ode_sys1 | 488,494 | Analytic/numerical solution systems of ODE | ode_2nd_order | 501 | Second order IVP |
| ode_sys2 | 514 | Analytic/numerical solution systems of ODE |
| Chapter 12: Smoothing of Data and the Method of Least Squares | ||
| lstsq1 | 524 | Linear least squares example |
| lstsq2 | 524 | Linear least squares example |
| lstsq3 | 526 | Nonpolynomial least squares example |
| minimal_sol | 551-552 | Minimal solution random matrix A/vector b |
| svd_penrose_sol | 553 | Penrose properties for pseudomatrix |
| Chapter 13: Monte Carlo Methods and Simulation | ||
| rand_num | 563 | Generating random numbers |
| rand | 563 | Generating random integers |
| Chapter 14: Boundary Value Problems for Ordinary Differential Equations | ||
| bvp | 607 | Solving broundary value problems |
| Chapter 15: Partial Differential Equations | ||
| heat | 623 | Parabolic PDE: heat equation |
| wave | 631-632 | Hyperbolic PDE: wave equation |
| ell | 645 | Elliptic PDE |
| Chapter 16: Minimization of Functions | ||
| grad_hessian | 674 | Calculate gradient vector and Hessian matrix |
| Chapter 17: Linear Programming | ||
| lin_prog1 | 693 | Maximize subject to inequality constraints |
| lin_prog2 | 697 | Minimize subject to inequality constraints |
| lin_prog3 | 712-713 | Minimize subject to equality constraints |
| lin_prog4 | 715 | Minimize subject to inequality constraints |
Addditional programs can be found at the textbook's anonymous ftp site:
ftp://ftp.ma.utexas.edu/pub/cheney-kincaid/
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