def test_override_boolean(es):
count = ft.Feature(es['log']['id'], parent_entity=es['sessions'], primitive=Count)
count_lo = ft.Feature(count, primitive=GreaterThanScalar(1))
count_hi = ft.Feature(count, primitive=LessThanScalar(10))
to_test = [[True, True, True],
[True, True, False],
[False, False, True]]
features = []
features.append(count_lo.OR(count_hi))
features.append(count_lo.AND(count_hi))
features.append(~(count_lo.AND(count_hi)))
df = ft.calculate_feature_matrix(entityset=es, features=features, instance_ids=[0, 1, 2])
for i, test in enumerate(to_test):
v = df[features[i].get_name()].values.tolist()
assert v == test
def test_override_boolean(es):
count = ft.Feature(es["log"].ww["id"],
parent_dataframe_name="sessions",
primitive=Count)
count_lo = ft.Feature(count, primitive=GreaterThanScalar(1))
count_hi = ft.Feature(count, primitive=LessThanScalar(10))
to_test = [[True, True, True], [True, True, False], [False, False, True]]
features = []
features.append(count_lo.OR(count_hi))
features.append(count_lo.AND(count_hi))
features.append(~(count_lo.AND(count_hi)))
df = ft.calculate_feature_matrix(entityset=es,
features=features,
instance_ids=[0, 1, 2])
df = to_pandas(df, index="id", sort_index=True)
for i, test in enumerate(to_test):
v = df[features[i].get_name()].tolist()
assert v == test