Fix inconsistencies in examples and many more improvements

doc/examples/plot_swirl.py

@@ -8,7 +8,7 @@ effect.  This example describes the implementation of this transform in
 ``skimage``, as well as the underlying warp mechanism.
 
 Image warping
-`````````````
+-------------
 When applying a geometric transformation on an image, we typically make use of
 a reverse mapping, i.e., for each pixel in the output image, we compute its
 corresponding position in the input.  The reason is that, if we were to do it
@@ -19,7 +19,7 @@ image, and even if that position is non-integer, we may use interpolation to
 compute the corresponding image value.
 
 Performing a reverse mapping
-````````````````````````````
+----------------------------
 To perform a geometric warp in ``skimage``, you simply need to provide the
 reverse mapping to the ``skimage.transform.warp`` function.  E.g., consider the
 case where we would like to shift an image 50 pixels to the left.  The reverse
@@ -35,7 +35,7 @@ The corresponding call to warp is::
     warp(image, shift_left)
 
 The swirl transformation
-````````````````````````
+------------------------
 Consider the coordinate :math:`(x, y)` in the output image.  The reverse
 mapping for the swirl transformation first computes, relative to a center
 :math:`(x_0, y_0)`, its polar coordinates,
@@ -63,12 +63,13 @@ the swirl extent in pixels, and ``rotation`` adds a rotation angle.  The
 transformation of ``radius`` into :math:`r` is to ensure that the
 transformation decays to :math:`\approx 1/1000^{\mathsf{th}}` within the
 specified radius.
+
 """
+import matplotlib.pyplot as plt
 
 from skimage import data
 from skimage.transform import swirl
 
-import matplotlib.pyplot as plt
 
 image = data.checkerboard()
 swirled = swirl(image, rotation=0, strength=10, radius=120, order=2)