old_contents: """
  ===============
  Radon transform
  ===============
  
  The radon transform is a technique widely used in tomography to
  reconstruct an object from different projections. A projection is, for
  example, the scattering data obtained as the output of a tomographic
  scan.
  
  For more information see:
  
    - http://en.wikipedia.org/wiki/Radon_transform
    - http://www.clear.rice.edu/elec431/projects96/DSP/bpanalysis.html
  
  This script performs the radon transform, and reconstructs the
  input image based on the resulting sinogram.
  
  """
  
  import matplotlib.pyplot as plt
  
  from skimage.io import imread
  from skimage import data_dir
  from skimage.transform import radon, iradon
  from scipy.ndimage import zoom
  
  image = imread(data_dir + "/phantom.png", as_grey=True)
  image = zoom(image, 0.4)
  
  plt.figure(figsize=(8, 8.5))
  
  plt.subplot(221)
  plt.title("Original");
  plt.imshow(image, cmap=plt.cm.Greys_r)
  
  plt.subplot(222)
  projections = radon(image, theta=[0, 45, 90])
  plt.plot(projections);
  plt.title("Projections at\n0, 45 and 90 degrees")
  plt.xlabel("Projection axis");
  plt.ylabel("Intensity");
  
  projections = radon(image)
  plt.subplot(223)
  plt.title("Radon transform\n(Sinogram)");
  plt.xlabel("Projection axis");
  plt.ylabel("Intensity");
  plt.imshow(projections)
  
  reconstruction = iradon(projections)
  plt.subplot(224)
  plt.title("Reconstruction\nfrom sinogram")
  plt.imshow(reconstruction, cmap=plt.cm.Greys_r)
  
  plt.subplots_adjust(hspace=0.4, wspace=0.5)
  plt.show()
  
new_contents: """
  ===============
  Radon transform
  ===============
  
  The radon transform is a technique widely used in tomography to
  reconstruct an object from different projections. A projection is, for
  example, the scattering data obtained as the output of a tomographic
  scan.
  
  For more information see:
  
    - http://en.wikipedia.org/wiki/Radon_transform
    - http://www.clear.rice.edu/elec431/projects96/DSP/bpanalysis.html
  
  This script performs the radon transform, and reconstructs the
  input image based on the resulting sinogram.
  
  """
  
  import matplotlib.pyplot as plt
  
  from skimage.io import imread
  from skimage import data_dir
  from skimage.transform import radon, iradon, rescale
  
  
  image = imread(data_dir + "/phantom.png", as_grey=True)
  image = rescale(image, scale=0.4)
  
  plt.figure(figsize=(8, 8.5))
  
  plt.subplot(221)
  plt.title("Original");
  plt.imshow(image, cmap=plt.cm.Greys_r)
  
  plt.subplot(222)
  projections = radon(image, theta=[0, 45, 90])
  plt.plot(projections);
  plt.title("Projections at\n0, 45 and 90 degrees")
  plt.xlabel("Projection axis");
  plt.ylabel("Intensity");
  
  projections = radon(image)
  plt.subplot(223)
  plt.title("Radon transform\n(Sinogram)");
  plt.xlabel("Projection axis");
  plt.ylabel("Intensity");
  plt.imshow(projections)
  
  reconstruction = iradon(projections)
  plt.subplot(224)
  plt.title("Reconstruction\nfrom sinogram")
  plt.imshow(reconstruction, cmap=plt.cm.Greys_r)
  
  plt.subplots_adjust(hspace=0.4, wspace=0.5)
  plt.show()
  
subject: Replace ndimage.zoom function in radon transform example with builtin skimage function