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NumPy Beginner's Guide

You're reading from NumPy Beginner's Guide An action packed guide using real world examples of the easy to use, high performance, free open source NumPy mathematical library.

Product type Paperback

Published in Apr 2013

Publisher Packt

ISBN-13 9781782166085

Length 310 pages

Edition 2nd Edition

Languages

Python

Tools

NumPy

Concepts

Data Analysis

Author (1):

Ivan Idris

View More author details

Table of Contents (19) Chapters

Numpy Beginner's Guide Second Edition

Credits

About the Author

About the Reviewers

www.PacktPub.com

Preface

1. NumPy Quick Start FREE CHAPTER

2. Beginning with NumPy Fundamentals

3. Get in Terms with Commonly Used Functions

4. Convenience Functions for Your Convenience

5. Working with Matrices and ufuncs

6. Move Further with NumPy Modules

7. Peeking into Special Routines

8. Assure Quality with Testing

9. Plotting with Matplotlib

10. When NumPy is Not Enough – SciPy and Beyond

11. Playing with Pygame

Pop Quiz Answers

Index

Special mathematical functions

We will end this chapter with some special mathematical functions. Bessel functions are solutions of the Bessel differential equations (visit http://en.wikipedia.org/wiki/Bessel_function). The modified Bessel function of the first kind 0th order is represented in NumPy by i0. The sinc function is represented in NumPy by a function with the same name and there is also a two-dimensional version of this function. sinc is a trigonometric function; for more details visit http://en.wikipedia.org/wiki/Sinc_function.

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Authors (1)

Ivan Idris

Ivan Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

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