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Remove to_be_fixed from inference tests on SpecialDaysTransform #1283

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Jun 8, 2023
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Remove to_be_fixed from inference tests on SpecialDaysTransform #1283

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6327c30
test: remove to_be_fixed from inference tests on SpecialDaysTransform
Jun 7, 2023
fac9bf4
chore: update changelog
Jun 7, 2023
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3 changes: 3 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -19,6 +19,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Update requirements for `holidays` and `scipy`, change saving library from `pickle` to `dill` in `SaveMixin` ([#1268](https://github.com/tinkoff-ai/etna/pull/1268))
- Update requirement for `ruptures`, add requirement for `sqlalchemy` ([#1276](https://github.com/tinkoff-ai/etna/pull/1276))
- Optimize `make_samples` of `RNNNet` and `MLPNet` ([#1281](https://github.com/tinkoff-ai/etna/pull/1281))
- Remove `to_be_fixed` from inference tests on `SpecialDaysTransform` ([#1283](https://github.com/tinkoff-ai/etna/pull/1283))
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Not really sure that wee need to ad it in the Changeling

-
-
-
### Fixed
- Fix `plot_backtest` and `plot_backtest_interactive` on one-step forecast ([1260](https://github.com/tinkoff-ai/etna/pull/1260))
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32 changes: 4 additions & 28 deletions tests/test_transforms/test_inference/test_inverse_transform.py
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Expand Up @@ -691,6 +691,8 @@ def test_inverse_transform_train_new_segments(self, transform, dataset_name, exp
(DensityOutliersTransform(in_column="target"), "ts_with_outliers"),
(MedianOutliersTransform(in_column="target"), "ts_with_outliers"),
(PredictionIntervalOutliersTransform(in_column="target", model=ProphetModel), "ts_with_outliers"),
# timestamp
(SpecialDaysTransform(), "regular_ts"),
],
)
def test_inverse_transform_train_new_segments_not_implemented(self, transform, dataset_name, request):
Expand All @@ -700,20 +702,6 @@ def test_inverse_transform_train_new_segments_not_implemented(self, transform, d
ts, transform, train_segments=["segment_1", "segment_2"], expected_changes={}
)

@to_be_fixed(raises=NotImplementedError, match="Per-segment transforms can't work on new segments")
@pytest.mark.parametrize(
"transform, dataset_name",
[
# timestamp
(SpecialDaysTransform(), "regular_ts"),
],
)
def test_inverse_transform_train_new_segments_failed_not_implemented(self, transform, dataset_name, request):
ts = request.getfixturevalue(dataset_name)
self._test_inverse_transform_train_new_segments(
ts, transform, train_segments=["segment_1", "segment_2"], expected_changes={}
)


class TestInverseTransformFutureNewSegments:
"""Test inverse transform on future part of new segments.
Expand Down Expand Up @@ -1027,6 +1015,8 @@ def test_inverse_transform_future_new_segments(self, transform, dataset_name, ex
(DensityOutliersTransform(in_column="target"), "ts_with_outliers"),
(MedianOutliersTransform(in_column="target"), "ts_with_outliers"),
(PredictionIntervalOutliersTransform(in_column="target", model=ProphetModel), "ts_with_outliers"),
# timestamp
(SpecialDaysTransform(), "regular_ts"),
],
)
def test_inverse_transform_future_new_segments_not_implemented(self, transform, dataset_name, request):
Expand All @@ -1036,20 +1026,6 @@ def test_inverse_transform_future_new_segments_not_implemented(self, transform,
ts, transform, train_segments=["segment_1", "segment_2"], expected_changes={}
)

@to_be_fixed(raises=NotImplementedError, match="Per-segment transforms can't work on new segments")
@pytest.mark.parametrize(
"transform, dataset_name",
[
# timestamp
(SpecialDaysTransform(), "regular_ts"),
],
)
def test_inverse_transform_future_new_segments_failed_not_implemented(self, transform, dataset_name, request):
ts = request.getfixturevalue(dataset_name)
self._test_inverse_transform_future_new_segments(
ts, transform, train_segments=["segment_1", "segment_2"], expected_changes={}
)

@to_be_fixed(raises=Exception)
@pytest.mark.parametrize(
"transform, dataset_name, expected_changes",
Expand Down
33 changes: 4 additions & 29 deletions tests/test_transforms/test_inference/test_transform.py
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Expand Up @@ -56,7 +56,6 @@
from etna.transforms.decomposition import RupturesChangePointsModel
from tests.test_transforms.test_inference.common import find_columns_diff
from tests.utils import select_segments_subset
from tests.utils import to_be_fixed

# TODO: figure out what happened to TrendTransform

Expand Down Expand Up @@ -652,6 +651,8 @@ def test_transform_train_new_segments(self, transform, dataset_name, expected_ch
(DensityOutliersTransform(in_column="target"), "ts_with_outliers"),
(MedianOutliersTransform(in_column="target"), "ts_with_outliers"),
(PredictionIntervalOutliersTransform(in_column="target", model=ProphetModel), "ts_with_outliers"),
# timestamp
(SpecialDaysTransform(), "regular_ts"),
],
)
def test_transform_train_new_segments_not_implemented(self, transform, dataset_name, request):
Expand All @@ -661,20 +662,6 @@ def test_transform_train_new_segments_not_implemented(self, transform, dataset_n
ts, transform, train_segments=["segment_1", "segment_2"], expected_changes={}
)

@to_be_fixed(raises=NotImplementedError, match="Per-segment transforms can't work on new segments")
@pytest.mark.parametrize(
"transform, dataset_name",
[
# timestamp
(SpecialDaysTransform(), "regular_ts"),
],
)
def test_transform_train_new_segments_failed_not_implemented(self, transform, dataset_name, request):
ts = request.getfixturevalue(dataset_name)
self._test_transform_train_new_segments(
ts, transform, train_segments=["segment_1", "segment_2"], expected_changes={}
)


class TestTransformFutureNewSegments:
"""Test transform on future part of new segments.
Expand Down Expand Up @@ -981,6 +968,8 @@ def test_transform_future_new_segments(self, transform, dataset_name, expected_c
(DensityOutliersTransform(in_column="target"), "ts_with_outliers"),
(MedianOutliersTransform(in_column="target"), "ts_with_outliers"),
(PredictionIntervalOutliersTransform(in_column="target", model=ProphetModel), "ts_with_outliers"),
# timestamp
(SpecialDaysTransform(), "regular_ts"),
],
)
def test_transform_future_new_segments_not_implemented(self, transform, dataset_name, request):
Expand All @@ -990,20 +979,6 @@ def test_transform_future_new_segments_not_implemented(self, transform, dataset_
ts, transform, train_segments=["segment_1", "segment_2"], expected_changes={}
)

@to_be_fixed(raises=NotImplementedError, match="Per-segment transforms can't work on new segments")
@pytest.mark.parametrize(
"transform, dataset_name",
[
# timestamp
(SpecialDaysTransform(), "regular_ts"),
],
)
def test_transform_future_new_segments_failed_not_implemented(self, transform, dataset_name, request):
ts = request.getfixturevalue(dataset_name)
self._test_transform_future_new_segments(
ts, transform, train_segments=["segment_1", "segment_2"], expected_changes={}
)


class TestTransformFutureWithTarget:
"""Test transform on future dataset with known target.
Expand Down