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fix: update pyproject.toml warnings
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d-a-bunin committed Oct 13, 2023
1 parent e2f0ffd commit aa13dca
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Showing 3 changed files with 2 additions and 3 deletions.
2 changes: 0 additions & 2 deletions pyproject.toml
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Expand Up @@ -229,7 +229,6 @@ filterwarnings = [
"ignore: New behaviour in v1.1.5.* a small bias is added", # ruptures: normal cost
"ignore: Dynamic prediction specified to begin during out-of-sample forecasting period, and so has no effect.",
"ignore::pytorch_lightning.utilities.rank_zero.LightningDeprecationWarning",
# "ignore: All-NaN slice encountered",
"ignore: numpy.ufunc size changed, may indicate binary incompatibility",
"ignore: The register_cmap function was deprecated in Matplotlib 3.7 and will be removed", # seaborn
"ignore: Jupyter is migrating its paths to use standard platformdirs",
Expand All @@ -238,7 +237,6 @@ filterwarnings = [
"ignore: In a future version, `df.* = newvals` will attempt to set the values inplace instead of always setting a new array",
"ignore: In a future version, DataFrame.*mean.* will return a scalar mean over the entire DataFrame",
"ignore: The behavior of indexing on a MultiIndex with a nested sequence of labels is deprecated and will change in a future version",
# "ignore: Using the level keyword in DataFrame and Series aggregations is deprecated",
"ignore: Non-invertible starting MA parameters found",
"ignore: Optimization did not converge :tbats.error.ModelWarning.ModelWarning",
"ignore: The behavior of Timestamp.utcfromtimestamp is deprecated", # prophet
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Expand Up @@ -7,6 +7,7 @@
from etna.transforms.feature_selection import MRMRFeatureSelectionTransform


@pytest.mark.filterwarnings("ignore: Columns from feature_to_use which are out of dataframe columns will be dropped")
@pytest.mark.parametrize(
"features_to_use, expected_features",
(
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Expand Up @@ -83,7 +83,7 @@ def test_save_load(inplace, example_tsds):


def test_get_regressors_info_not_fitted():
transform = AddConstTransform(in_column="target", value=1, out_column="out_column")
transform = AddConstTransform(in_column="target", value=1)
with pytest.raises(ValueError, match="Fit the transform to get the correct regressors info!"):
_ = transform.get_regressors_info()

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