code: def test_project_lambda_smoke_negatives():
      dp = DemographicParity()
  
      events = ["all"]
      signs = ["+", "-"]
      labels = ["a", "b"]
      midx = pd.MultiIndex.from_product(
          [signs, events, labels], names=[_SIGN, _EVENT, _GROUP_ID]
      )
  
      df = pd.DataFrame()
      # Note that the '-' indices (11 and 19) are larger
      # than the '+' indices (1 and 2)
      df = 0 + pd.Series([1, 2, 11, 19], index=midx, dtype=np.float64)
  
      ls = dp.project_lambda(df)
  
      expected = pd.DataFrame()
      expected = 0 + pd.Series(
          [0, 0, 10, 17], index=midx, dtype=np.float64
      )
      assert expected.equals(ls)
  
file_path: fairlearn/test/unit/reductions/moments/test_moments_demographic_parity.py
imports: import numpy
  import pandas
  from fairlearn.reductions import DemographicParity
  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