text: import sys
  sys.path.insert(1, "../../../")
  import h2o, tests
  import random
  
  def test_get_future_model():
      
      
  
      covtype=h2o.upload_file(tests.locate("smalldata/covtype/covtype.altered.gz"))
  
      myY=54
      myX=list(set(range(54)) - set([20,28]))   # Cols 21 and 29 are constant, so must be explicitly ignored
  
      # Set response to be indicator of a particular class
      res_class=random.sample(range(1,5), 1)[0]
      covtype[myY] = covtype[myY] == res_class
      covtype[myY] = covtype[myY].asfactor()
  
      # L2: alpha=0, lambda=0
      covtype_h2o1 = h2o.start_glm_job(y=covtype[myY], x=covtype[myX], family="binomial", alpha=[0], Lambda=[0])
  
      # Elastic: alpha=0.5, lambda=1e-4
      covtype_h2o2 = h2o.start_glm_job(y=covtype[myY], x=covtype[myX], family="binomial", alpha=[0.5], Lambda=[1e-4])
  
      # L1: alpha=1, lambda=1e-4
      covtype_h2o3 = h2o.start_glm_job(y=covtype[myY], x=covtype[myX], family="binomial", alpha=[1], Lambda=[1e-4])
  
      covtype_h2o1 = h2o.get_future_model(covtype_h2o1)
      print(covtype_h2o1)
      covtype_h2o2 = h2o.get_future_model(covtype_h2o2)
      print(covtype_h2o2)
      covtype_h2o3 = h2o.get_future_model(covtype_h2o3)
      print(covtype_h2o3)
  
  if __name__ == "__main__":
      tests.run_test(sys.argv, test_get_future_model)
  