code: def test_npmle_with_weights_is_identical_if_uniform_weights():
      left, right = [1, 8, 8, 7, 7, 17, 37, 46, 46, 45], [
          7,
          8,
          10,
          16,
          14,
          np.inf,
          44,
          np.inf,
          np.inf,
          np.inf,
      ]
      weights = 2 * np.ones_like(right)
      npt.assert_allclose(
          npmle(left, right, verbose=True)[0],
          np.array([0.16667016, 0.33332984, 0.125, 0.375]),
          rtol=1e-4,
      )
  
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 4 for calling a global function with example usage: test_npmle_with_weights_is_identical_if_uniform_weights() without return types