def test_as_dict(foo_extractor):
rs = FeatureSet(
features_names=["foo"],
values={"foo": 1},
timeserie=TIME_SERIE,
extractors={"foo": foo_extractor},
)
assert rs.as_dict() == {"foo": 1}
def test_plot(foo_extractor):
rs = FeatureSet(
features_names=["foo"],
values={"foo": 1},
timeserie=TIME_SERIE,
extractors={"foo": foo_extractor},
)
assert isinstance(rs.plot("foo"), axes.Axes)
def test_as_dataframe(foo_extractor):
rs = FeatureSet(
features_names=["foo"],
values={"foo": 1},
timeserie=TIME_SERIE,
extractors={"foo": foo_extractor},
)
expected = pd.DataFrame([{"foo": 1.0}])
assert rs.as_dataframe().equals(expected)
def test_as_array(foo_extractor):
rs = FeatureSet(
features_names=["foo"],
values={"foo": 1},
timeserie=TIME_SERIE,
extractors={"foo": foo_extractor},
)
feats, values = rs.as_arrays()
assert list(feats) == unordered(["foo"])
assert list(values) == unordered([1])
def test_invalid_feature():
with pytest.raises(FeatureNotFound):
FeatureSet(
features_names=["Fail"],
values={"fail": 1},
timeserie=TIME_SERIE,
extractors={},
)
def test_getitem(foo_extractor):
rs = FeatureSet(
features_names=["foo"],
values={"foo": 1},
timeserie=TIME_SERIE,
extractors={"foo": foo_extractor},
)
assert rs["foo"] == 1
with pytest.raises(KeyError):
rs["faaa"]
def test_repr(foo_extractor):
timeserie = TIME_SERIE.copy()
timeserie.update(time=1, error=2)
rs = FeatureSet(
features_names=["foo"],
values={"foo": 1},
timeserie=timeserie,
extractors={"foo": foo_extractor},
)
expected = "FeatureSet(features=<foo>, timeserie=<time, error>)"
assert repr(rs) == str(rs) == expected