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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
Languages
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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 FREE CHAPTER 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

Profiling code with line_profiler


Now that we installed line_profiler, we can start profiling.

How to do it...

Obviously, we will need some code to profile.

  1. Write code to profile.

    We will write code to multiply a random matrix of varying size with itself. Also, the thread will sleep for a few seconds. The function to profile will be annotated with @profile:

    import numpy
    import time
    
    @profile
    def multiply(n):
      A = numpy.random.rand(n, n)
      time.sleep(numpy.random.randint(0, 2))
      return numpy.matrix(A) ** 2
    
    for n in 2 ** numpy.arange(0, 10):
      multiply(n)
  2. Profile the code.

    Run the profiler with the following command:

    $ kernprof.py -l -v mat_mult.py 
    Wrote profile results to mat_mult.py.lprof
    Timer unit: 1e-06 s
    
    File: mat_mult.py
    Function: multiply at line 4
    Total time: 3.19654 s
    Line #      Hits         Time  Per Hit   % Time  Line Contents
    ==============================================================
         4                                           @profile
         5                          ...
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