code: def get_train(self):
      lap_mat = self.getLap()
      w, vec = np.linalg.eigh(lap_mat)
  
      start = 0
      for i in range(self.node_size):
          if w[i] > 1e-10:
              start = i
              break
      vec = vec[:, start : start + self.rep_size]
  
      return vec
  
file_path: OpenNE/src/openne/lap.py
imports: import numpy
  import networkx
label_desc: Use image node_id 4 for calling the LaplacianEigenmaps obj's underlying member method code with example usage: obj.get_train() and returns: vec