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Applying Math with Python

You're reading from   Applying Math with Python Over 70 practical recipes for solving real-world computational math problems

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804618370
Length 376 pages
Edition 2nd Edition
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Concepts
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Author (1):
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Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
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Table of Contents (13) Chapters Close

Preface 1. Chapter 1: An Introduction to Basic Packages, Functions, and Concepts 2. Chapter 2: Mathematical Plotting with Matplotlib FREE CHAPTER 3. Chapter 3: Calculus and Differential Equations 4. Chapter 4: Working with Randomness and Probability 5. Chapter 5: Working with Trees and Networks 6. Chapter 6: Working with Data and Statistics 7. Chapter 7: Using Regression and Forecasting 8. Chapter 8: Geometric Problems 9. Chapter 9: Finding Optimal Solutions 10. Chapter 10: Improving Your Productivity 11. Index 12. Other Books You May Enjoy

Solving partial differential equations numerically

Partial differential equations are differential equations that involve partial derivatives of functions in two or more variables, as opposed to ordinary derivatives in only a single variable. Partial differential equations are a vast topic, and could easily fill a series of books. A typical example of a partial differential equation is the (one-dimensional) heat equation:

Here, is a positive constant and is a function. The solution to this partial differential equation is a function , which represents the temperature of a rod, occupying the range , at a given time . To keep things simple, we will take , which amounts to saying that no heating/cooling is applied to the system, , and . In practice, we can rescale the problem to fix the constant , so this is not a restrictive problem. In this example, we will use boundary conditions:

These are equivalent to saying that the ends...

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