def test_delay_feature_transformer_woodwork_custom_overrides_returned_by_components(X_df, fit_transform):
y = pd.Series([1, 2, 1])
override_types = [Integer, Double, Categorical, Datetime, Boolean]
for logical_type in override_types:
try:
X = ww.DataTable(X_df, logical_types={0: logical_type})
except TypeError:
continue
dft = DelayedFeatureTransformer(max_delay=1, gap=11)
if fit_transform:
transformed = dft.fit_transform(X, y)
else:
dft.fit(X, y)
transformed = dft.transform(X, y)
assert isinstance(transformed, ww.DataTable)
if logical_type in [Integer, Double, Categorical]:
assert transformed.logical_types == {0: logical_type,
'0_delay_1': Double,
'target_delay_0': Integer,
'target_delay_1': Double}
else:
assert transformed.logical_types == {0: logical_type,
'0_delay_1': logical_type,
'target_delay_0': Integer,
'target_delay_1': Double}
def test_lagged_feature_extractor_delay_features_delay_target(
encode_y_as_str, encode_X_as_str, delay_features, delay_target,
delayed_features_data):
X, y = delayed_features_data
X, X_answer, y, y_answer = encode_X_y_as_strings(X, y, encode_X_as_str,
encode_y_as_str)
all_delays = pd.DataFrame({
"feature": X.feature,
"feature_delay_1": X_answer.feature.shift(1),
"feature_delay_2": X_answer.feature.shift(2),
"feature_delay_3": X_answer.feature.shift(3),
"target_delay_0": y_answer.astype("Int64"),
"target_delay_1": y_answer.shift(1),
"target_delay_2": y_answer.shift(2),
"target_delay_3": y_answer.shift(3)
})
if not encode_X_as_str:
all_delays["feature"] = X.feature.astype("Int64")
if not delay_features:
all_delays = all_delays.drop(
columns=[c for c in all_delays.columns if "feature_" in c])
if not delay_target:
all_delays = all_delays.drop(
columns=[c for c in all_delays.columns if "target" in c])
transformer = DelayedFeatureTransformer(max_delay=3,
gap=1,
delay_features=delay_features,
delay_target=delay_target)
assert_frame_equal(all_delays,
transformer.fit_transform(X, y).to_dataframe())
def test_target_delay_when_gap_is_0(gap, delayed_features_data):
X, y = delayed_features_data
expected = pd.DataFrame({"feature": X.feature.astype("Int64"),
"feature_delay_1": X.feature.shift(1),
"target_delay_0": y.astype("Int64"),
"target_delay_1": y.shift(1)})
if gap == 0:
expected = expected.drop(columns=["target_delay_0"])
transformer = DelayedFeatureTransformer(max_delay=1, gap=gap)
assert_frame_equal(expected, transformer.fit_transform(X, y).to_dataframe())
expected = pd.DataFrame({"target_delay_0": y.astype("Int64"),
"target_delay_1": y.shift(1)})
if gap == 0:
expected = expected.drop(columns=["target_delay_0"])
assert_frame_equal(expected, transformer.fit_transform(None, y).to_dataframe())
def test_target_delay_when_gap_is_0(gap, delayed_features_data):
X, y = delayed_features_data
answer = pd.DataFrame({"feature": X.feature,
"feature_delay_1": X.feature.shift(1),
"target_delay_0": y,
"target_delay_1": y.shift(1)})
if gap == 0:
answer = answer.drop(columns=["target_delay_0"])
transformer = DelayedFeatureTransformer(max_delay=1, gap=gap)
pd.testing.assert_frame_equal(transformer.fit_transform(X, y), answer)
answer = pd.DataFrame({"target_delay_0": y,
"target_delay_1": y.shift(1)})
if gap == 0:
answer = answer.drop(columns=["target_delay_0"])
pd.testing.assert_frame_equal(transformer.fit_transform(None, y), answer)
def test_lagged_feature_extractor_delay_target(encode_y_as_str, encode_X_as_str, delay_features,
delay_target, delayed_features_data):
X, y = delayed_features_data
X, X_answer, y, y_answer = encode_X_y_as_strings(X, y, encode_X_as_str, encode_y_as_str)
answer = pd.DataFrame()
if delay_target:
answer = pd.DataFrame({"target_delay_0": y_answer.astype("Int64"),
"target_delay_1": y_answer.shift(1),
"target_delay_2": y_answer.shift(2),
"target_delay_3": y_answer.shift(3)})
transformer = DelayedFeatureTransformer(max_delay=3, gap=1,
delay_features=delay_features, delay_target=delay_target)
assert_frame_equal(answer, transformer.fit_transform(None, y).to_dataframe())
