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NumPy Cookbook

You're reading from   NumPy Cookbook If you're a Python developer with basic NumPy skills, the 70+ recipes in this brilliant cookbook will boost your skills in no time. Learn to raise productivity levels and code faster and cleaner with the open source mathematical library.

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Product type Paperback
Published in Oct 2012
Publisher Packt
ISBN-13 9781849518925
Length 226 pages
Edition 1st Edition
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Table of Contents (17) Chapters Close

NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Winding Along with IPython 2. Advanced Indexing and Array Concepts FREE CHAPTER 3. Get to Grips with Commonly Used Functions 4. Connecting NumPy with the Rest of the World 5. Audio and Image Processing 6. Special Arrays and Universal Functions 7. Profiling and Debugging 8. Quality Assurance 9. Speed Up Code with Cython 10. Fun with Scikits Index

Approximating factorials with Cython


The last example is about approximating factorials with Cython. We will use two approximation methods. First, we will use the Stirling approximation method (see http://en.wikipedia.org/wiki/Stirling%27s_approximation for more information). The formula for the Stirling approximation is:

Secondly, we will be using the approximation due to Ramanujan, with the following formula:

How to do it...

This section describes how to approximate factorials using Cython. In this recipe, we will be using types, which as you may remember, is optional in Cython. In theory, declaring static types should speed things up. Static typing offers interesting challenges that you may not encounter when writing Python code, but don't worry, we will try to keep it simple.

  1. Write the Cython code.

    The Cython code that we will write looks like regular Python code, except that we declare function parameters and a local variable to be an ndarray array. In order to get the static types to...

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