code: def rmsd(V, W):
      
      D = len(V[0])
      N = len(V)
      result = 0.0
      for v, w in zip(V, W):
          result += sum([(v[i] - w[i])**2.0 for i in range(D)])
      return np.sqrt(result/N)
docs: Calculate Root-mean-square deviation from two sets of vectors V and W.
  
      Parameters
      ----------
      V : array
          (N,D) matrix, where N is points and D is dimension.
      W : array
          (N,D) matrix, where N is points and D is dimension.
  
      Returns
      -------
      rmsd : float
          Root-mean-square deviation between the two vectors