code: def vert_connectivity(self):
          
          import numpy as np
          import scipy.sparse as sp
          from blmath.numerics.matlab import row
          vpv = sp.csc_matrix((len(self.v), len(self.v)))
          # for each column in the faces...
          for i in range(3):
              IS = self.f[:, i]
              JS = self.f[:, (i+1)%3]
              data = np.ones(len(IS))
              ij = np.vstack((row(IS.flatten()), row(JS.flatten())))
              mtx = sp.csc_matrix((data, ij), shape=vpv.shape)
              vpv = vpv + mtx + mtx.T
          return vpv
docs: Returns a sparse matrix (of size #verts x #verts) where each nonzero
          element indicates a neighborhood relation. For example, if there is a
          nonzero element in position (15, 12), that means vertex 15 is connected
          by an edge to vertex 12.