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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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Toc

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

Calling C functions


We can call C functions from Cython. For instance, in this example, we will call the C log function. This function works on a single number only. Remember that the NumPy log function can also work with arrays. We will compute the so-called log returns of stock prices.

How to do it...

We will start by writing some Cython code:

  1. Write the .pyx file.

    First, we need to import the C log function from the libc namespace. Second, we will apply this function to numbers in a for loop. Finally, we will use the NumPy diff function to get the first order difference between the log values in the second step.

    from libc.math cimport log
    import numpy
    
    def logrets(numbers):
       logs = [log(x) for x in numbers] 
       return numpy.diff(logs)

    Building has been covered in the previous recipes already. We only need to change some values in the setup.py file.

  2. Plot the log returns.

    Let's download stock price data with matplotlib, again. Apply the Cython logrets function that we just created on the...

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