code: def test_right_truncated_children(make_aids):
      event, time_enter, time_exit = make_aids("children")
  
      x, y, km_ci = kaplan_meier_estimator(
          event,
          time_exit.values,
          time_enter.values,
          conf_type="log-log",
      )
      true_x = np.array(
          [
              7.75,
              7.50,
              7.25,
              7.0,
              6.75,
              6.50,
              6.25,
              6.0,
              5.75,
              5.50,
              5.25,
              5.00,
              4.75,
              4.50,
              4.25,
              4.0,
              3.75,
              3.5,
              3.0,
              2.75,
              2.50,
              2.25,
              1.5,
              1.0,
          ]
      )
      assert_array_almost_equal(x[::-1], true_x, 2)
  
      true_y = np.array(
          [
              0.0,
              0.022321,
              0.078122,
              0.156244,
              0.227263,
              0.25973,
              0.311675,
              0.370115,
              0.370115,
              0.416379,
              0.442403,
              0.474003,
              0.560185,
              0.611111,
              0.6667,
              0.6667,
              0.6667,
              0.6667,
              0.6667,
              0.6667,
              0.6667,
              1.0,
              1.0,
              1.0,
          ]
      )
      assert_array_almost_equal(y[::-1], true_y, 4)
  
      true_km_var = np.array(
          [
              [
                  0.0,
                  0.002822,
                  0.017862,
                  0.040298,
                  0.058612,
                  0.066127,
                  0.076545,
                  0.085444,
                  0.085444,
                  0.090003,
                  0.091389,
                  0.092039,
                  0.08619,
                  0.074768,
                  0.054073,
                  0.054073,
                  0.054073,
                  0.054073,
                  0.054073,
                  0.054073,
                  0.054073,
                  1.0,
                  1.0,
                  1.0,
              ],
              [
                  0.0,
                  0.085206,
                  0.19892,
                  0.34197,
                  0.461233,
                  0.512167,
                  0.589283,
                  0.66924,
                  0.66924,
                  0.727018,
                  0.757314,
                  0.791658,
                  0.871973,
                  0.910719,
                  0.945206,
                  0.945206,
                  0.945206,
                  0.945206,
                  0.945206,
                  0.945206,
                  0.945206,
                  1.0,
                  1.0,
                  1.0,
              ],
          ]
      )
  
      assert_array_almost_equal(km_ci[:, ::-1], true_km_var, 6)
  
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 18 for calling the TestKaplanMeier obj's underlying member method code with example usage: obj.test_right_truncated_children(make_aids) without return types