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)
def test_project_lambda_smoke_positives():
# This is a repeat of the _negatives method but with
# the '+' indices larger
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 are smaller than
# the '+' ones
df = 0 + pd.Series([23, 19, 5, 7], index=midx, dtype=np.float64)
ls = dp.project_lambda(df)
expected = pd.DataFrame()
expected = 0 + pd.Series([18, 12, 0, 0], index=midx, dtype=np.float64)
assert expected.equals(ls)