code: def test_predict(self):
      # All smoke tests. We should be able to convert the lhr and hr
      # tests into real tests against R.  There are many options to
      # this function that may interact in complicated ways.  Only a
      # few key combinations are tested here.
      np.random.seed(34234)
      endog = 50 * np.random.uniform(size=200)
      status = np.random.randint(0, 2, 200).astype(np.float64)
      exog = np.random.normal(size=(200, 4))
  
      mod = PHReg(endog, exog, status)
      rslt = mod.fit()
      rslt.predict()
      for pred_type in "lhr", "hr", "cumhaz", "surv":
          rslt.predict(pred_type=pred_type)
          rslt.predict(endog=endog[0:10], pred_type=pred_type)
          rslt.predict(
              endog=endog[0:10], exog=exog[0:10, :], pred_type=pred_type
          )
  
imports: import itertools
  import os
  import numpy
  from statsmodels.duration.hazard_regression import PHReg
  from numpy.testing import assert_allclose, assert_equal, assert_
  import pandas
  import pytest
  from .results import survival_r_results
  from .results import survival_enet_r_results
label_desc: Use image node_id 11 for calling the TestPHReg obj's underlying member method code with example usage: obj.test_predict() without return types