Add some more comments

skimage/transform/_geometric.py

@@ -1031,21 +1031,24 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
 
     out = None
 
-    # use fast Cython version for specific interpolation orders
+    # use fast Cython version for specific interpolation orders and input
     if order in range(4) and not map_args:
+
         matrix = None
 
+        # inverse_map is a transformation matrix as numpy array
         if isinstance(inverse_map, np.ndarray) and inverse_map.shape == (3, 3):
             matrix = inverse_map
 
+        # inverse_map is a homography
         elif isinstance(inverse_map, HOMOGRAPHY_TRANSFORMS):
             matrix = inverse_map._matrix
 
+        # inverse_map is the inverse of a homography
         elif (hasattr(inverse_map, '__name__')
               and inverse_map.__name__ == 'inverse'
               and get_bound_method_class(inverse_map)
                   in HOMOGRAPHY_TRANSFORMS):
-
             matrix = np.linalg.inv(six.get_method_self(inverse_map)._matrix)
 
         if matrix is not None:
@@ -1067,6 +1070,7 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
 
         rows, cols = output_shape[:2]
 
+        # inverse_map is a transformation matrix as numpy array
         if isinstance(inverse_map, np.ndarray) and inverse_map.shape == (3, 3):
             inverse_map = ProjectiveTransform(matrix=inverse_map)
 
@@ -1075,7 +1079,7 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
 
         coords = warp_coords(coord_map, (rows, cols, bands))
 
-        # Prefilter not necessary for order 0, 1 interpolation
+        # Pre-filtering not necessary for order 0, 1 interpolation
         prefilter = order > 1
         out = ndimage.map_coordinates(image, coords, prefilter=prefilter,
                                       mode=mode, order=order, cval=cval)