code: def test_classification_pseudofilter():
      (
          _,
          min_percent,
          max_percent,
          threshold,
      ) = get_default_pseudo_test_args()
      middle_percent = (max_percent + min_percent) / 2
      num_rows = 100
      num_above_threshold = int(middle_percent * num_rows)
      num_below_threshold = num_rows - num_above_threshold
      y_reg_fake = np.ones((num_above_threshold))
  
      # Test if percent preds is below min threshold
      y_reg_fake_below_min = np.zeros((num_rows, 2))
      y_reg_fake_below_min = pd.DataFrame(data=y_reg_fake_below_min)
      pseudo_indicies_ans = filter_pseudo(
          y_reg_fake_below_min, "binary"
      )
      assert num_rows == len(pseudo_indicies_ans)
  
      # Test if percent preds is above max threshold
      y_reg_fake_above_max = pandas.DataFrame(data=y_reg_fake)
      pseudo_indicies_ans = filter_pseudo(
          y_reg_fake_above_max, "binary"
      )
      num_rows_threshold = max(
          np.ceil(max_percent * len(y_reg_fake_above_max)), 1
      )
      curr_threshold = y_reg_fake_above_max.loc[num_rows_threshold - 1]
      answer = len(y_reg_fake_above_max >= curr_threshold)
      assert answer == len(pseudo_indicies_ans)
  
      # Test if normal functionality beginning
      y_reg_fake = np.column_stack(
          (y_reg_fake, np.zeros((num_above_threshold)))
      )
      y_reg_fake = np.row_stack(
          (y_reg_fake, np.zeros((num_below_threshold, 2)))
      )
  
      y_reg_fake = pandas.DataFrame(data=y_reg_fake)
      pseudo_flag = y_reg_fake.max(axis=1) > threshold
      pseudo_indices_ans = pseudo_flag[pseudo_flag == True]
  
      pseudo_idxes = filter_pseudo(y_reg_fake, "binary")
      assert len(pseudo_idxes) == len(pseudo_indices_ans)
  
file_path: autogluon/tabular/tests/unittests/pseudolabel/pseudo_filter.py
imports: import inspect
  import numpy
  import pandas
  import pandas
  from autogluon.core.pseudolabeling.pseudolabeling import filter_pseudo
label_desc: Use image node_id 4 for calling a global function with example usage: test_classification_pseudofilter() without return types