code: def normalise(v):
      
  
      vn = np.sqrt(np.sum(v**2, 0))
      vn[vn == 0] = 1.0
      return np.asarray(v / vn, dtype=v.dtype)
docs: Normalise columns of matrix.
  
      Parameters
      ----------
      v : array_like
        Array with columns to be normalised
  
      Returns
      -------
      vnrm : ndarray
        Normalised array