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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

Blurring images


We can blur images with a Gaussian filter (for more information on Gaussian filter visit http://en.wikipedia.org/wiki/Gaussian_filter). This filter is based on the normal distribution. A corresponding SciPy function requires the standard deviation as a parameter.

In this recipe, we will also plot a polar rose and a spiral (for more information on Polar coordinate system visit http://en.wikipedia.org/wiki/Polar_coordinate_system). These figures are not directly related, but it seemed more fun to combine them here.

How to do it...

We will start by initializing the polar plots, after which we will blur the Lena image and plot in the polar coordinates.

  1. Initialization.

    Initialize the polar plots as follows:

    NFIGURES = int(sys.argv[1])
    k = numpy.random.random_integers(1, 5, NFIGURES)
    a = numpy.random.random_integers(1, 5, NFIGURES)
    
    colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
  2. Blur Lena.

    In order to blur Lena, we will apply the Gaussian filter with standard deviation of four:

    matplotlib...
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