code: def test_sf_doesnt_return_nans():
      left = [6, 7, 8, 7, 5]
      right = [7, 8, 10, 16, 20]
      results = npmle(left, right)
      npt.assert_allclose(results[1], [interval(7, 7), interval(8, 8)])
      npt.assert_allclose(results[0], [0.5, 0.5])
      sf = reconstruct_survival_function(
          *results, timeline=[6, 7, 8, 16, 20]
      )
      assert not np.isnan(sf.values).any()
  
file_path: lifelines/lifelines/tests/test_npmle.py
imports: import pytest
  from lifelines.fitters.npmle import npmle, is_subset, create_turnbull_intervals, interval, reconstruct_survival_function
  from numpy import testing
  from lifelines.datasets import load_mice
  from lifelines import KaplanMeierFitter
  import numpy
  import pandas
label_desc: Use image node_id 6 for calling a global function with example usage: test_sf_doesnt_return_nans() without return types