code: def test_transform_notNaN2(lfrfitmodel, ad):
      """The transformed data should not contain nan's. Using the threshold value of 0.3."""
      lftransformeddataset = lfrfitmodel.transform(ad, threshold=0.3)
      expected = False
      res = np.isnan(lftransformeddataset.features).any()
      assert res == expected
  
file_path: AIF360/tests/test_lfr.py
imports: import os
  import sys
  import numpy
  import pytest
  from aif360.algorithms.preprocessing import LFR
  from aif360.algorithms.preprocessing.optim_preproc_helpers.data_preproc_functions import load_preproc_data_adult
label_desc: Use image node_id 10 for calling a global function with example usage: test_transform_notNaN2(lfrfitmodel, ad) without return types