Book Image

NumPy Cookbook

Book Image

NumPy Cookbook

Overview of this book

Today's world of science and technology is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy will give you both speed and high productivity. "NumPy Cookbook" will teach you all about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, it is free and open source. "Numpy Cookbook" will teach you to write readable, efficient, and fast code that is as close to the language of Mathematics as much as possible with the cutting edge open source NumPy software library. You will learn about installing and using NumPy and related concepts. At the end of the book, we will explore related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project through examples. "NumPy Cookbook" will help you to be productive with NumPy and write clean and fast code.
Table of Contents (17 chapters)
NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
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...