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NumPy Cookbook

You're reading from  NumPy Cookbook

Product type Book
Published in Oct 2012
Publisher Packt
ISBN-13 9781849518925
Pages 226 pages
Edition 1st Edition
Languages

Table of Contents (17) Chapters

NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Winding Along with IPython 2. Advanced Indexing and Array Concepts 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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