advanced indexing lets you manipulate arrays elegantly

advanced-indexing.py

import numpy as np

# some sample data in shaped cubic (100, 100, 100)
img = np.random.sample((100, 100, 100))

# set all values between 0.5 and 0.6 to zero
img[(img < 0.6) & (img > 0.5)] = 0

# in a small sub cube (10, 10, 10)..
# .. get index arrays of all elements above 0.6
(x, y, z) = np.where(img[:10,:10,:10] > 0.6)

# apply coordinate transforms (rotation, translation, etc)
xn, yn, zn = x+5, y+2, y+1

# copy the cube to its new position
img[xn, yn, zn] = img[x, y, z]