MC: docs and example fixes

skimage/measure/_marching_cubes_classic.py

@@ -86,24 +86,6 @@ def marching_cubes_classic(volume, level=None, spacing=(1., 1., 1.),
     To quantify the area of an isosurface generated by this algorithm, pass
     outputs directly into `skimage.measure.mesh_surface_area`.
 
-    Regarding visualization of algorithm output, to contour a volume
-    named `myvolume` about the level 0.0, using the ``mayavi`` package::
-
-      >>> from mayavi import mlab # doctest: +SKIP
-      >>> verts, faces = marching_cubes_classic(myvolume, 0.0) # doctest: +SKIP
-      >>> mlab.triangular_mesh([vert[0] for vert in verts],
-      ...                      [vert[1] for vert in verts],
-      ...                      [vert[2] for vert in verts],
-      ...                      faces) # doctest: +SKIP
-      >>> mlab.show() # doctest: +SKIP
-    
-    Similarly using the ``visvis`` package::
-    
-      >>> import visvis as vv # doctest: +SKIP
-      >>> verts, faces = marching_cubes_classic(myvolume, 0.0) # doctest: +SKIP
-      >>> vv.mesh(np.fliplr(verts), faces) # doctest: +SKIP
-      >>> vv.use().Run() # doctest: +SKIP
-      
     References
     ----------
     .. [1] Lorensen, William and Harvey E. Cline. Marching Cubes: A High

skimage/measure/_marching_cubes_lewiner.py

@@ -113,6 +113,27 @@ def marching_cubes(volume, level=None, spacing=(1., 1., 1.),
     keeping the algorithm relatively easy. This implementation is
     written in Cython, ported from Lewiner's C++ implementation.
     
+    To quantify the area of an isosurface generated by this algorithm, pass
+    verts and faces to `skimage.measure.mesh_surface_area`.
+    
+    Regarding visualization of algorithm output, to contour a volume
+    named `myvolume` about the level 0.0, using the ``mayavi`` package::
+
+      >>> from mayavi import mlab # doctest: +SKIP
+      >>> verts, faces, normals, values = marching_cubes(myvolume, 0.0) # doctest: +SKIP
+      >>> mlab.triangular_mesh([vert[0] for vert in verts],
+      ...                      [vert[1] for vert in verts],
+      ...                      [vert[2] for vert in verts],
+      ...                      faces) # doctest: +SKIP
+      >>> mlab.show() # doctest: +SKIP
+    
+    Similarly using the ``visvis`` package::
+    
+      >>> import visvis as vv # doctest: +SKIP
+      >>> verts, faces, normals, values = marching_cubes_classic(myvolume, 0.0) # doctest: +SKIP
+      >>> vv.mesh(np.fliplr(verts), faces, normals, values) # doctest: +SKIP
+      >>> vv.use().Run() # doctest: +SKIP
+    
     References
     ----------
     .. [1] Thomas Lewiner, Helio Lopes, Antonio Wilson Vieira and Geovan