code: """
  ====================
  Build image pyramids
  ====================
  
  The ``pyramid_gaussian`` function takes an image and yields successive images
  shrunk by a constant scale factor. Image pyramids are often used, e.g., to
  implement algorithms for denoising, texture discrimination, and scale-
  invariant detection.
  
  """
  import numpy as np
  import matplotlib.pyplot as plt
  
  from skimage import data
  from skimage.transform import pyramid_gaussian
  
  
  image = data.astronaut()
  rows, cols, dim = image.shape
  pyramid = tuple(pyramid_gaussian(image, downscale=2))
  
  composite_image = np.zeros((rows, cols + cols / 2, 3), dtype=np.double)
  
  composite_image[:rows, :cols, :] = pyramid[0]
  
  i_row = 0
  for p in pyramid[1:]:
      n_rows, n_cols = p.shape[:2]
      composite_image[i_row:i_row + n_rows, cols:cols + n_cols] = p
      i_row += n_rows
  
  fig, ax = plt.subplots()
  ax.imshow(composite_image)
  plt.show()
  
apis: matplotlib.pyplot.show matplotlib.pyplot.subplots numpy.zeros