Applying Math with Python : Over 70 Practical Recipes for Solving Real-World Computational Math Problems.
The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by...
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| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Birmingham :
Packt Publishing, Limited,
2022.
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| Edition: | 2nd ed. |
| Subjects: | |
| Online Access: | CONNECT |
Table of Contents:
- Cover
- Title Page
- Copyright
- Dedication
- Contributors
- Table of Contents
- Preface
- Chapter 1: An Introduction to Basic Packages, Functions, and Concepts
- Technical requirements
- Exploring Python numerical types
- Decimal type
- Fraction type
- Complex type
- Understanding basic mathematical functions
- Diving into the world of NumPy
- Element access
- Array arithmetic and functions
- Useful array creation routines
- Higher-dimensional arrays
- Working with matrices and linear algebra
- Basic methods and properties
- Matrix multiplication
- Determinants and inverses
- Systems of equations
- Eigenvalues and eigenvectors
- Sparse matrices
- Summary
- Further reading
- Chapter 2: Mathematical Plotting with Matplotlib
- Technical requirements
- Basic plotting with Matplotlib
- Getting ready
- How to do it...
- How it works...
- There's more...
- Adding subplots
- Getting ready
- How to do it...
- How it works...
- There's more...
- See also
- Plotting with error bars
- Getting ready
- How to do it...
- How it works...
- There's more...
- Saving Matplotlib figures
- Getting ready
- How to do it...
- How it works...
- There's more...
- See also
- Surface and contour plots
- Getting ready
- How to do it...
- How it works...
- There's more...
- See also
- Customizing three-dimensional plots
- Getting ready
- How to do it...
- How it works...
- There's more...
- Plotting vector fields with quiver plots
- Getting ready
- How to do it...
- How it works...
- There's more...
- Further reading
- Chapter 3: Calculus and Differential Equations
- Technical requirements
- Primer on calculus
- Working with polynomials and calculus
- Getting ready
- How to do it...
- How it works...
- There's more...
- See also
- Differentiating and integrating symbolically using SymPy
- Getting ready
- How to do it...
- How it works...
- There's more...
- Solving equations
- Getting ready
- How to do it...
- How it works...
- There's more...
- Integrating functions numerically using SciPy
- Getting ready
- How to do it...
- How it works...
- There's more...
- Solving simple differential equations numerically
- Getting ready
- How to do it...
- How it works...
- There's more...
- See also
- Solving systems of differential equations
- Getting ready
- How to do it...
- How it works...
- There's more...
- Solving partial differential equations numerically
- Getting ready
- How to do it...
- How it works...
- There's more...
- See also
- Using discrete Fourier transforms for signal processing
- Getting ready
- How to do it...
- How it works...
- There's more...
- See also
- Automatic differentiation and calculus using JAX
- Getting ready
- How to do it...
- How it works...
- There's more...
- See also
- Solving differential equations using JAX
- Getting ready
- How to do it...
- How it works...
- See also
- Further reading
