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Fix detrend transforms to handle integer timestamp #163

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merged 4 commits into from
Nov 29, 2023
Merged

Fix detrend transforms to handle integer timestamp #163

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6270307
fix: fix detrending transforms to handle integer timestamp
d-a-bunin Nov 27, 2023
d9d0750
chore: update changelog
d-a-bunin Nov 27, 2023
f99d490
chore: update changelog
d-a-bunin Nov 27, 2023
8e90f62
chore: update changelog
d-a-bunin Nov 27, 2023
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2 changes: 1 addition & 1 deletion CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
-
-
-
-
- Update detrend transforms (`LinearTrendTransform`, `TheilSenTrendTransform`) to handle integer timestamp ([#163](https://github.com/etna-team/etna/pull/163))
-
-

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11 changes: 7 additions & 4 deletions etna/transforms/decomposition/detrend.py
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Expand Up @@ -43,10 +43,13 @@ def __init__(self, in_column: str, regressor: RegressorMixin, poly_degree: int =
def _get_x(df) -> np.ndarray:
series_len = len(df)
x = df.index.to_series()
if isinstance(type(x.dtype), pd.Timestamp):
raise ValueError("Your timestamp column has wrong format. Need np.datetime64 or datetime.datetime")
x = x.apply(lambda ts: ts.timestamp())
x = x.to_numpy().reshape(series_len, 1)

if x.dtype == "int":
x = x.astype("float").to_numpy()
else:
x = x.apply(lambda ts: ts.timestamp()).to_numpy()

x = x.reshape(series_len, 1)
return x

def fit(self, df: pd.DataFrame) -> "_OneSegmentLinearTrendBaseTransform":
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5 changes: 3 additions & 2 deletions tests/test_transforms/test_inference/test_inverse_transform.py
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Expand Up @@ -445,6 +445,9 @@ def test_inverse_transform_train_datetime_timestamp_fail_resample(
@pytest.mark.parametrize(
"transform, dataset_name, expected_changes",
[
# decomposition
(LinearTrendTransform(in_column="target"), "regular_ts", {"change": {"target"}}),
(TheilSenTrendTransform(in_column="target"), "regular_ts", {"change": {"target"}}),
# encoders
(LabelEncoderTransform(in_column="weekday", out_column="res"), "ts_with_exog", {}),
(
Expand Down Expand Up @@ -699,8 +702,6 @@ def test_inverse_transform_train_int_timestamp(self, transform, dataset_name, ex
"regular_ts",
{"change": {"target"}},
),
(LinearTrendTransform(in_column="target"), "regular_ts", {"change": {"target"}}),
(TheilSenTrendTransform(in_column="target"), "regular_ts", {"change": {"target"}}),
(STLTransform(in_column="target", period=7), "regular_ts", {"change": {"target"}}),
(DeseasonalityTransform(in_column="target", period=7), "regular_ts", {"change": {"target"}}),
(
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5 changes: 3 additions & 2 deletions tests/test_transforms/test_inference/test_transform.py
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Expand Up @@ -386,6 +386,9 @@ def test_transform_train_datetime_timestamp(self, transform, dataset_name, expec
@pytest.mark.parametrize(
"transform, dataset_name, expected_changes",
[
# decomposition
(LinearTrendTransform(in_column="target"), "regular_ts", {"change": {"target"}}),
(TheilSenTrendTransform(in_column="target"), "regular_ts", {"change": {"target"}}),
# encoders
(LabelEncoderTransform(in_column="weekday", out_column="res"), "ts_with_exog", {"create": {"res"}}),
(
Expand Down Expand Up @@ -671,8 +674,6 @@ def test_transform_train_int_timestamp(self, transform, dataset_name, expected_c
"regular_ts",
{"change": {"target"}},
),
(LinearTrendTransform(in_column="target"), "regular_ts", {"change": {"target"}}),
(TheilSenTrendTransform(in_column="target"), "regular_ts", {"change": {"target"}}),
(STLTransform(in_column="target", period=7), "regular_ts", {"change": {"target"}}),
(DeseasonalityTransform(in_column="target", period=7), "regular_ts", {"change": {"target"}}),
(
Expand Down