Indexing with booleans

Boolean indexing is indexing based on a boolean array and falls in the category fancy indexing.

How to do it...

We will apply this indexing technique to an image:

1. Image with dots on the diagonal.

   This is in some way similar to the Fancy indexing recipe, in this chapter. This time we select modulo 4 points on the diagonal of the image:

   def get_indices(size):
      arr = numpy.arange(size)
      return arr % 4 == 0

   Then we just apply this selection and plot the points:

   lena1 = lena.copy() 
   xindices = get_indices(lena.shape[0])
   yindices = get_indices(lena.shape[1])
   lena1[xindices, yindices] = 0
   matplotlib.pyplot.subplot(211)
   matplotlib.pyplot.imshow(lena1)

2. Set to 0 based on value.

   Select array values between quarter and three-quarters of the maximum value and set them to 0:

   lena2[(lena > lena.max()/4) & (lena < 3 * lena.max()/4)] = 0

The plot with the two new images will look like the following screenshot:

The following is the complete code for this recipe:

import scipy.misc...