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Learning NumPy Array

You're reading from   Learning NumPy Array Supercharge your scientific Python computations by understanding how to use the NumPy library effectively

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783983902
Length 164 pages
Edition Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (14) Chapters Close

Learning NumPy Array
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with NumPy FREE CHAPTER 2. NumPy Basics 3. Basic Data Analysis with NumPy 4. Simple Predictive Analytics with NumPy 5. Signal Processing Techniques 6. Profiling, Debugging, and Testing 7. The Scientific Python Ecosystem Index

Fancy indexing


Fancy indexing is indexing that does not involve integers or slices, which is normal indexing. In this section, we will apply fancy indexing to set the diagonal values of the Lena image to 0. This will draw black lines along the diagonals, crossing it through, not because there is something wrong with the image, but just as an exercise. Perform the following steps for fancy indexing:

  1. Set the values of the first diagonal to 0. To set the diagonal values to 0, we need to define two different ranges for the x and y values as follows:

    lena[range(xmax), range(ymax)] = 0
  2. Now, set the values of the other diagonal to 0. To set the values of the other diagonal, we require a different set of ranges, but the principles stay the same, as follows:

    lena[range(xmax-1,-1,-1), range(ymax)] = 0

At the end we get the following image with the diagonals crossed out:

The following code for this section is without comments. The complete code for this is in the fancy.py file in the Chapter02 folder of...

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