code: def padone(x, front=0, back=0, axis=0, fillvalue=0):
      """pad with zeros along one axis, currently only axis=0
  
  
      can be used sequentially to pad several axis
  
      Examples
      --------
      >>> padone(np.ones((2,3)),1,3,axis=1)
      array([[ 0.,  1.,  1.,  1.,  0.,  0.,  0.],
             [ 0.,  1.,  1.,  1.,  0.,  0.,  0.]])
  
      >>> padone(np.ones((2,3)),1,1, fillvalue=np.nan)
      array([[ NaN,  NaN,  NaN],
             [  1.,   1.,   1.],
             [  1.,   1.,   1.],
             [ NaN,  NaN,  NaN]])
      """
      # primitive version
      shape = np.array(x.shape)
      shape[axis] += front + back
      shapearr = np.array(x.shape)
      out = np.empty(shape)
      out.fill(fillvalue)
      startind = np.zeros(x.ndim)
      startind[axis] = front
      endind = startind + shapearr
      myslice = [
          slice(startind[k], endind[k]) for k in range(len(endind))
      ]
      # print(myslice
      # print(out.shape
      # print(out[tuple(myslice)].shape
      out[tuple(myslice)] = x
      return out
  
imports: import numpy
  from scipy import signal
  from statsmodels.tsa.tsatools import lagmat
label_desc: Use image node_id 4 for calling a global function with example usage: padone(x, front, back, axis, fillvalue) and returns: out