old_contents: """
  ============
  Thresholding
  ============
  
  Thresholding is used to create a binary image. This example uses Otsu's method
  to calculate the threshold value.
  
  Otsu's method calculates an "optimal" threshold (marked by a red line in the
  histogram below) by maximizing the variance between two classes of pixels,
  which are separated by the threshold. Equivalently, this threshold minimizes
  the intra-class variance.
  
  .. [1] http://en.wikipedia.org/wiki/Otsu's_method
  
  """
  import matplotlib.pyplot as plt
  
  from skimage.data import camera
  from skimage.filter import threshold_otsu
  
  
  image = camera()
  thresh = threshold_otsu(image)
  binary = image > thresh
  
  plt.figure(figsize=(8, 2.5))
  plt.subplot(1, 3, 1)
  plt.imshow(image, cmap=plt.cm.gray)
  plt.title('Original')
  plt.axis('off')
  
  plt.subplot(1, 3, 2, aspect='equal')
  plt.hist(image)
  plt.title('Histogram')
  plt.axvline(thresh, color='r')
  
  plt.subplot(1, 3, 3)
  plt.imshow(binary, cmap=plt.cm.gray)
  plt.title('Thresholded')
  plt.axis('off')
  
  plt.show()
  
new_contents: """
  ============
  Thresholding
  ============
  
  Thresholding is used to create a binary image. This example uses Otsu's method
  to calculate the threshold value.
  
  Otsu's method calculates an "optimal" threshold (marked by a red line in the
  histogram below) by maximizing the variance between two classes of pixels,
  which are separated by the threshold. Equivalently, this threshold minimizes
  the intra-class variance.
  
  .. [1] http://en.wikipedia.org/wiki/Otsu's_method
  
  """
  import matplotlib
  import matplotlib.pyplot as plt
  
  from skimage.data import camera
  from skimage.filter import threshold_otsu
  
  
  matplotlib.rcParams['font.size'] = 9
  
  
  image = camera()
  thresh = threshold_otsu(image)
  binary = image > thresh
  
  plt.figure(figsize=(8, 2.5))
  plt.subplot(1, 3, 1)
  plt.imshow(image, cmap=plt.cm.gray)
  plt.title('Original')
  plt.axis('off')
  
  plt.subplot(1, 3, 2, aspect='equal')
  plt.hist(image)
  plt.title('Histogram')
  plt.axvline(thresh, color='r')
  
  plt.subplot(1, 3, 3)
  plt.imshow(binary, cmap=plt.cm.gray)
  plt.title('Thresholded')
  plt.axis('off')
  
  plt.show()
  
subject: Fix overlapping xtick labels