old_contents: """
  ===============================
  Piecewise Affine Transformation
  ===============================
  
  This example shows how to use the Piecewise Affine Transformation.
  """
  
  import numpy as np
  import matplotlib.pyplot as plt
  from skimage.transform import PiecewiseAffineTransform, warp
  from skimage import data
  
  
  image = data.lena()
  rows, cols = image.shape[0], image.shape[1]
  
  src_cols = np.linspace(0, cols, 20)
  src_rows = np.linspace(0, rows, 20)
  src_rows, src_cols = np.meshgrid(src_rows, src_cols)
  src = np.dstack([src_cols.flat, src_rows.flat])[0]
  
  # add sinusoidal oscillation to row coordinates
  dst_rows = src[:, 1] - np.sin(np.linspace(0, 3 * np.pi, src.shape[0])) * 50
  dst_cols = src[:, 0]
  dst_rows *= 1.5
  dst_rows -= 1.5 * 50
  dst = np.vstack([dst_cols, dst_rows]).T
  
  
  tform = PiecewiseAffineTransform()
  tform.estimate(src, dst)
  
  output_shape = (image.shape[0] - 1.5 * 50, image.shape[1])
  out = warp(image, tform, output_shape=output_shape)
  
  plt.imshow(out)
  plt.show()
  
new_contents: """
  ===============================
  Piecewise Affine Transformation
  ===============================
  
  This example shows how to use the Piecewise Affine Transformation.
  """
  
  import numpy as np
  import matplotlib.pyplot as plt
  from skimage.transform import PiecewiseAffineTransform, warp
  from skimage import data
  
  
  image = data.lena()
  rows, cols = image.shape[0], image.shape[1]
  
  src_cols = np.linspace(0, cols, 20)
  src_rows = np.linspace(0, rows, 10)
  src_rows, src_cols = np.meshgrid(src_rows, src_cols)
  src = np.dstack([src_cols.flat, src_rows.flat])[0]
  
  # add sinusoidal oscillation to row coordinates
  dst_rows = src[:, 1] - np.sin(np.linspace(0, 3 * np.pi, src.shape[0])) * 50
  dst_cols = src[:, 0]
  dst_rows *= 1.5
  dst_rows -= 1.5 * 50
  dst = np.vstack([dst_cols, dst_rows]).T
  
  
  tform = PiecewiseAffineTransform()
  tform.estimate(src, dst)
  
  out_rows = image.shape[0] - 1.5 * 50
  out_cols = cols
  out = warp(image, tform, output_shape=(out_rows, out_cols))
  
  plt.imshow(out)
  plt.plot(tform.inverse(src)[:, 0], tform.inverse(src)[:, 1], '.b')
  plt.axis((0, out_cols, out_rows, 0))
  plt.show()
  
subject: Add mesh points to plot