code: def _get_min_distance_numpy(element):
      
      xys = element.array([0, 1])
      with warnings.catch_warnings():
          warnings.filterwarnings('ignore', r'invalid value encountered in')
          xys = xys.astype('float32').view(np.complex64)
          distances = np.abs(xys.T-xys)
          np.fill_diagonal(distances, np.inf)
          distances = distances[distances>0]
          if len(distances):
              return distances.min()
      return 0
docs: NumPy based implementation of get_min_distance