code: def test_estimator_fit_without_ci(random_survival_data):
      est = SurvivalFunctionEstimator().fit(random_survival_data)
      msg = "If return_conf_int is True, SurvivalFunctionEstimator must be fitted with conf_int != None"
      with pytest.raises(ValueError, match=msg):
          est.predict_proba(
              np.unique(random_survival_data["time"]),
              return_conf_int=True,
          )
  
imports: from os.path import dirname, join
  import numpy
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  import pandas
  import pytest
  from sksurv.nonparametric import CensoringDistributionEstimator, SurvivalFunctionEstimator, kaplan_meier_estimator, nelson_aalen_estimator
  from sksurv.testing import FixtureParameterFactory
  from sksurv.util import Surv
label_desc: Use image node_id 7 for calling the TestKaplanMeier obj's underlying member method code with example usage: obj.test_estimator_fit_without_ci(random_survival_data) without return types