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Applying Math with Python

You're reading from   Applying Math with Python Practical recipes for solving computational math problems using Python programming and its libraries

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781838989750
Length 358 pages
Edition 1st Edition
Languages
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Authors (2):
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Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
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Table of Contents (12) Chapters Close

Preface 1. Basic Packages, Functions, and Concepts 2. Mathematical Plotting with Matplotlib FREE CHAPTER 3. Calculus and Differential Equations 4. Working with Randomness and Probability 5. Working with Trees and Networks 6. Working with Data and Statistics 7. Regression and Forecasting 8. Geometric Problems 9. Finding Optimal Solutions 10. Miscellaneous Topics 11. Other Books You May Enjoy

Solving equations

Many mathematical problems eventually reduce to solving an equation of the formf(x) = 0, where f is a function of a single variable. Here, we try to find a value of x for which the equation holds. The values of x for which the equation holds are sometimes called roots of the equation. There are numerous algorithms for finding solutions to equations of this form. In this recipe, we will use the Newton-Raphson and secant methods to solve an equation of the form f(x) = 0.

The Newton-Raphson method (Newton's method) and the secant method are good, standard root finding algorithms that can be applied in almost any situation. These areiterative methods that start with an approximation of the root and iteratively improve this approximation until it lies within a given tolerance.

To demonstrate these techniques, we will use the function from the Symbolic calculus using SymPy recipe defined by

which is defined...

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