def test_delayed_feature_extractor_maxdelay5_gap1(encode_X_as_str, encode_y_as_str, 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({"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),
"feature_delay_4": X_answer.feature.shift(4),
"feature_delay_5": X_answer.feature.shift(5),
"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),
"target_delay_4": y_answer.shift(4),
"target_delay_5": y_answer.shift(5)})
if not encode_X_as_str:
answer["feature"] = X.feature.astype("Int64")
assert_frame_equal(answer, DelayedFeatureTransformer(max_delay=5, gap=1).fit_transform(X, y).to_dataframe())
answer_only_y = 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),
"target_delay_4": y_answer.shift(4),
"target_delay_5": y_answer.shift(5)})
assert_frame_equal(answer_only_y, DelayedFeatureTransformer(max_delay=5, gap=1).fit_transform(X=None, y=y).to_dataframe())
def test_delayed_feature_extractor_maxdelay5_gap1(encode_X_as_str, encode_y_as_str, 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({"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),
"feature_delay_4": X_answer.feature.shift(4),
"feature_delay_5": X_answer.feature.shift(5),
"target_delay_0": y_answer,
"target_delay_1": y_answer.shift(1),
"target_delay_2": y_answer.shift(2),
"target_delay_3": y_answer.shift(3),
"target_delay_4": y_answer.shift(4),
"target_delay_5": y_answer.shift(5)})
pd.testing.assert_frame_equal(DelayedFeatureTransformer(max_delay=5, gap=1).fit_transform(X, y), answer)
answer_only_y = pd.DataFrame({"target_delay_0": y_answer,
"target_delay_1": y_answer.shift(1),
"target_delay_2": y_answer.shift(2),
"target_delay_3": y_answer.shift(3),
"target_delay_4": y_answer.shift(4),
"target_delay_5": y_answer.shift(5)})
pd.testing.assert_frame_equal(DelayedFeatureTransformer(max_delay=5, gap=1).fit_transform(X=None, y=y), answer_only_y)
def test_delay_feature_transformer_supports_custom_index(encode_X_as_str, encode_y_as_str, data_type, make_data_type,
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)
X.index = pd.RangeIndex(50, 81)
X_answer.index = pd.RangeIndex(50, 81)
y.index = pd.RangeIndex(50, 81)
y_answer.index = pd.RangeIndex(50, 81)
answer = 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)}, index=pd.RangeIndex(50, 81))
if not encode_X_as_str:
answer["feature"] = X.feature.astype("Int64")
X = make_data_type(data_type, X)
y = make_data_type(data_type, y)
assert_frame_equal(answer, DelayedFeatureTransformer(max_delay=3, gap=7).fit_transform(X, y).to_dataframe())
answer_only_y = 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)}, index=pd.RangeIndex(50, 81))
assert_frame_equal(answer_only_y, DelayedFeatureTransformer(max_delay=3, gap=7).fit_transform(X=None, y=y).to_dataframe())
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_delay_feature_transformer_supports_custom_index(encode_X_as_str, encode_y_as_str, use_woodwork,
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)
X.index = pd.RangeIndex(50, 81)
X_answer.index = pd.RangeIndex(50, 81)
y.index = pd.RangeIndex(50, 81)
y_answer.index = pd.RangeIndex(50, 81)
answer = 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,
"target_delay_1": y_answer.shift(1),
"target_delay_2": y_answer.shift(2),
"target_delay_3": y_answer.shift(3)}, index=pd.RangeIndex(50, 81))
if use_woodwork:
X = ww.DataTable(X)
y = ww.DataColumn(y)
pd.testing.assert_frame_equal(DelayedFeatureTransformer(max_delay=3, gap=7).fit_transform(X, y), answer)
answer_only_y = pd.DataFrame({"target_delay_0": y_answer,
"target_delay_1": y_answer.shift(1),
"target_delay_2": y_answer.shift(2),
"target_delay_3": y_answer.shift(3)}, index=pd.RangeIndex(50, 81))
pd.testing.assert_frame_equal(DelayedFeatureTransformer(max_delay=3, gap=7).fit_transform(X=None, y=y),
answer_only_y)
def test_delayed_feature_extractor_numpy(encode_X_as_str, encode_y_as_str, 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)
X_np = X.values
y_np = y.values
answer = pd.DataFrame({0: X.feature,
"0_delay_1": X_answer.feature.shift(1),
"0_delay_2": X_answer.feature.shift(2),
"0_delay_3": X_answer.feature.shift(3),
"target_delay_0": y_answer,
"target_delay_1": y_answer.shift(1),
"target_delay_2": y_answer.shift(2),
"target_delay_3": y_answer.shift(3)})
pd.testing.assert_frame_equal(DelayedFeatureTransformer(max_delay=3, gap=7).fit_transform(X_np, y_np), answer)
answer_only_y = pd.DataFrame({"target_delay_0": y_answer,
"target_delay_1": y_answer.shift(1),
"target_delay_2": y_answer.shift(2),
"target_delay_3": y_answer.shift(3)})
pd.testing.assert_frame_equal(DelayedFeatureTransformer(max_delay=3, gap=7).fit_transform(X=None, y=y_np), answer_only_y)
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())
def test_delay_feature_transformer_y_is_none(delayed_features_data):
X, y = delayed_features_data
answer = pd.DataFrame({"feature": X.feature,
"feature_delay_1": X.feature.shift(1),
})
pd.testing.assert_frame_equal(DelayedFeatureTransformer(max_delay=1, gap=11).fit_transform(X, y=None), answer)
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_delay_feature_transformer_y_is_none(delayed_features_data):
X, _ = delayed_features_data
answer = pd.DataFrame({
"feature": X.feature.astype("Int64"),
"feature_delay_1": X.feature.shift(1),
})
assert_frame_equal(
answer,
DelayedFeatureTransformer(max_delay=1,
gap=11).fit_transform(X,
y=None).to_dataframe())
def test_delayed_features_transformer_init():
delayed_features = DelayedFeatureTransformer(max_delay=4,
delay_features=True,
delay_target=False,
random_seed=1)
assert delayed_features.parameters == {
"max_delay": 4,
"delay_features": True,
"delay_target": False,
"gap": 1
}
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_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_delay_feature_transformer_multiple_categorical_columns(delayed_features_data):
X, y = delayed_features_data
X, X_answer, y, y_answer = encode_X_y_as_strings(X, y, True, True)
X['feature_2'] = pd.Categorical(["a"] * 10 + ['aa'] * 10 + ['aaa'] * 10 + ['aaaa'])
X_answer['feature_2'] = pd.Series([0] * 10 + [1] * 10 + [2] * 10 + [3])
answer = pd.DataFrame({"feature": X.feature,
'feature_2': X.feature_2,
"feature_delay_1": X_answer.feature.shift(1),
"feature_2_delay_1": X_answer.feature_2.shift(1),
"target_delay_0": y_answer.astype("Int64"),
"target_delay_1": y_answer.shift(1),
})
assert_frame_equal(answer, DelayedFeatureTransformer(max_delay=1, gap=11).fit_transform(X, y).to_dataframe())