code: def test_transform_notNaN(lfrfitmodel, ad):
      """The transformed data should not have any columns or rows summing upto zero."""
      lftransformeddataset = lfrfitmodel.transform(ad, threshold=0.3)
      lstrowsum = np.sum(lftransformeddataset.features, axis=1).tolist()
      expected = False
      allrow_zeros = not np.any(lstrowsum)
      lstcolsum = np.sum(lftransformeddataset.features, axis=0).tolist()
      allcol_zeros = not np.any(lstcolsum)
      assert (allrow_zeros and allcol_zeros) == 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 9 for calling a global function with example usage: test_transform_notNaN(lfrfitmodel, ad) without return types