-
Notifications
You must be signed in to change notification settings - Fork 80
Conversation
…nts and raise error on new segments (#1107)
# Conflicts: # .github/workflows/test.yml # CHANGELOG.md # etna/models/base.py # etna/pipeline/base.py # etna/pipeline/hierarchical_pipeline.py # etna/pipeline/pipeline.py # etna/transforms/base.py # etna/transforms/encoders/mean_segment_encoder.py # etna/transforms/encoders/segment_encoder.py # etna/transforms/math/differencing.py # etna/transforms/math/sklearn.py # etna/transforms/outliers/base.py # etna/transforms/timestamp/special_days.py # etna/transforms/utils.py # tests/test_datasets/test_dataset.py # tests/test_models/test_base.py # tests/test_models/test_inference/common.py # tests/test_models/test_inference/test_forecast.py # tests/test_models/test_inference/test_predict.py # tests/test_pipeline/test_hierarchical_pipeline.py # tests/test_transforms/test_encoders/conftest.py # tests/test_transforms/test_encoders/test_mean_segment_encoder_transform.py # tests/test_transforms/test_math/test_differencing_transform.py # tests/test_transforms/test_math/test_sklearn_transform_interface.py # tests/test_transforms/test_outliers/test_outliers_transform.py
Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
🚀 Deployed on https://deploy-preview-1177--etna-docs.netlify.app |
Codecov Report
📣 This organization is not using Codecov’s GitHub App Integration. We recommend you install it so Codecov can continue to function properly for your repositories. Learn more @@ Coverage Diff @@
## master #1177 +/- ##
==========================================
+ Coverage 87.17% 87.58% +0.40%
==========================================
Files 177 177
Lines 10090 10267 +177
==========================================
+ Hits 8796 8992 +196
+ Misses 1294 1275 -19
... and 4 files with indirect coverage changes 📣 We’re building smart automated test selection to slash your CI/CD build times. Learn more |
# Conflicts: # etna/ensembles/direct_ensemble.py # etna/ensembles/stacking_ensemble.py # etna/ensembles/voting_ensemble.py # etna/pipeline/autoregressive_pipeline.py # etna/pipeline/base.py # etna/pipeline/hierarchical_pipeline.py # etna/pipeline/pipeline.py # tests/test_ensembles/test_direct_ensemble.py # tests/test_ensembles/test_stacking_ensemble.py # tests/test_ensembles/test_voting_ensemble.py # tests/test_models/test_inference/test_forecast.py # tests/test_models/test_inference/test_predict.py # tests/test_pipeline/conftest.py # tests/test_pipeline/test_autoregressive_pipeline.py # tests/test_pipeline/test_hierarchical_pipeline.py # tests/test_pipeline/test_pipeline.py # tests/utils.py
@@ -390,17 +391,56 @@ def test_forecast_given_ts(model, transforms, reconciliator, product_level_const | |||
because it is difficult to set it up for hierarchy. |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Can't we use assert_pipeline_forecasts_given_ts
here?
@@ -128,8 +128,6 @@ def _forecast(self, ts: TSDataset, return_components: bool) -> TSDataset: | |||
In each point in the future, forecast of the ensemble is forecast of base pipeline with the shortest horizon, | |||
which covers this point. | |||
""" | |||
if self.ts is None: |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Is it the only redundant check like this?
Before submitting (must do checklist)
Proposed Changes
Add
refit
parameter intobacktest
(#1159)stride
parameter intobacktest
(#1165)ts
intoforecast
method of pipelines (#1071)transform
method of transforms on subset of segments, on new segments, on future with gap (#1094)inverse_transform
method of transforms on subset of segments, on new segments, on future with gap (#1127)Change
SeasonalMovingAverageModel
fromPerSegmentModelMixin
(#1132)DeadlineMovingAverageModel
fromPerSegmentModelMixin
(#1140)Fix
DeepARModel
andTFTModel
(#1109)MLPNet
(#1108)MeanSegmentEncoderTransform
to work with subset of segments and raise error on new segments (#1104)SegmentEncoderTransform
to work with subset of segments and raise error on new segments (#1103)SklearnTransform
in per-segment mode to work on subset of segments and raise error on new segments (#1107)OutliersTransform
and its children to raise error on new segments (#1139)DifferencingTransform
to raise error on new segments duringtransform
andinverse_transform
in inplace mode (#1141)DifferencingTransform
toinverse_transform
with NaNs (#1155)Closing issues