code: def test_project_lambda_smoke_negatives():
      eqo = EqualizedOdds()
  
      events = ["label=False", "label=True"]
      signs = ["+", "-"]
      labels = ["a", "b"]
      midx = pd.MultiIndex.from_product(
          [signs, events, labels], names=[_SIGN, _EVENT, _GROUP_ID]
      )
  
      df = pd.DataFrame()
      # Note that the '-' labels are larger
      df = 0 + pd.Series(
          [1, 2, 11, 19, 1001, 1110, 1230, 1350],
          index=midx,
          dtype=np.float64,
      )
  
      ls = eqo.project_lambda(df)
  
      expected = pd.DataFrame()
      expected = 0 + pd.Series(
          [0, 0, 0, 0, 1000, 1108, 1219, 1331],
          index=midx,
          dtype=np.float64,
      )
      assert expected.equals(ls)
  
file_path: fairlearn/test/unit/reductions/moments/test_moments_equalized_odds.py
imports: import numpy
  import pandas
  from fairlearn.reductions import EqualizedOdds
  from fairlearn.reductions._moments.moment import _EVENT, _GROUP_ID, _SIGN
  from .data_generator import simple_binary_threshold_data
label_desc: Use image node_id 2 for calling a global function with example usage: test_project_lambda_smoke_negatives() without return types