def test_check_aggregate_top_level(simple_df):
# assert that `check_aggregate` returns None for full data
assert check_aggregate(simple_df, variable="Primary Energy", year=2005) is None
# duplicate scenario, assert `check_aggregate` returns non-matching data
_df = simple_df.rename(scenario={"scen_a": "foo"}, append=True).filter(
scenario="foo", variable="Primary Energy|Coal", keep=False
)
obs = check_aggregate(
_df, variable="Primary Energy", year=2005, exclude_on_fail=True
)
exp = pd.DataFrame([[12.0, 3.0], [8.0, 2.0], [4.0, 1.0]])
np.testing.assert_array_equal(obs.values, exp.values)
# assert that scenario `foo` has correctly been assigned as `exclude=True`
np.testing.assert_array_equal(_df.meta.exclude.values, [True, False])
def test_check_aggregate_top_level(meta_df):
obs = check_aggregate(meta_df, variable='Primary Energy', year=2005)
assert len(obs.columns) == 1
assert obs.index.get_values()[0] == ('model_a', 'scen_a', 'World',
'Primary Energy', 'EJ/y')
