code: def log_relative_gauss(z):
      """
      log_relative_gauss
      """
      if z < -6:
          return 1, -1.0e12, -1
      if z > 6:
          return 0, 0, 1
      else:
          logphi = -0.5 * (z * z + l2p)
          logPhi = np.log(0.5 * special.erfc(-z / sq2))
          e = np.exp(logphi - logPhi)
      return e, logPhi, 0
  
imports: import numpy
  from scipy import special
label_desc: Use image node_id 4 for calling a global function with example usage: log_relative_gauss(z) and returns: e,  logPhi,  int, int,  unknown,  unknown, int,  int,  int