Fixed multiseries prediction interval labels (#4377)

* Inital commit * Updated test * Update release notes * Added coverage for column labels
alteryx · Jan 25, 2024 · c7843cd · c7843cd
1 parent 8349680
commit c7843cd
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Showing 5 changed files with 17 additions and 9 deletions.
diff --git a/docs/source/release_notes.rst b/docs/source/release_notes.rst
@@ -4,6 +4,7 @@ Release Notes
  * Enhancements
  * Fixes
  * Fixed bug in `_downcast_nullable_y` causing woodwork initialization issues :pr:`4369`
+ * Fixed multiseries prediction interval labels :pr:`4377`
  * Changes
  * Pinned scipy version to under 1.12.0 :pr:`4380`
  * Documentation Changes

diff --git a/evalml/pipelines/components/transformers/preprocessing/stl_decomposer.py b/evalml/pipelines/components/transformers/preprocessing/stl_decomposer.py
@@ -340,6 +340,7 @@ def transform(
  # Convert the list to a DataFrame
  # For multiseries, return tuple[pd.DataFrame, pd.Dataframe] where each column is a series_id
  detrending_df = pd.DataFrame(detrending_list).T
+ detrending_df.columns = y.columns
  return X, detrending_df
 
  def inverse_transform(

diff --git a/evalml/pipelines/time_series_regression_pipeline.py b/evalml/pipelines/time_series_regression_pipeline.py
@@ -226,7 +226,6 @@ def _get_series_intervals(intervals, residuals, trend_pred_intervals, y):
 
  if self.problem_type == ProblemTypes.MULTISERIES_TIME_SERIES_REGRESSION:
  from evalml.pipelines.utils import (
- MULTISERIES_SEPARATOR_SYMBOL,
  stack_data,
  unstack_multiseries,
  )
@@ -271,11 +270,7 @@ def _get_series_intervals(intervals, residuals, trend_pred_intervals, y):
 
  # `pred_intervals` are in {series_id: {coverage_label: bound_value}} form
  for series_id, series_intervals in pred_intervals.items():
- series_id_target_name = (
- self.input_target_name
- + MULTISERIES_SEPARATOR_SYMBOL
- + str(series_id)
- )
+ series_id_target_name = str(series_id)
  series_id_prediction_intervals = _get_series_intervals(
  series_intervals,
  residuals[series_id],

diff --git a/evalml/tests/component_tests/decomposer_tests/test_stl_decomposer.py b/evalml/tests/component_tests/decomposer_tests/test_stl_decomposer.py
@@ -148,8 +148,15 @@ def test_stl_fit_transform_in_sample(
 
  stl = STLDecomposer(period=period)
 
+ series_id_columns = ["series_1", "series_2"]
+ if variateness == "multivariate":
+ y.columns = series_id_columns
+
  X_t, y_t = stl.fit_transform(X, y)
 
+ if variateness == "multivariate":
+ assert all(y_t.columns == series_id_columns)
+
  # If y_t is a pd.Series, give it columns
  if isinstance(y_t, pd.Series):
  y_t = y_t.to_frame()
@@ -179,7 +186,11 @@ def test_stl_fit_transform_in_sample(
  # Check the trend to make sure STL worked properly
  pd.testing.assert_series_equal(
  pd.Series(expected_trend),
- pd.Series(stl.trends[0]),
+ pd.Series(
+ stl.trends["series_1"]
+ if variateness == "multivariate"
+ else stl.trends[0],
+ ),
  check_exact=False,
  check_index=False,
  check_names=False,

diff --git a/...ml/tests/pipeline_tests/regression_pipeline_tests/test_multiseries_regression_pipeline.py b/...ml/tests/pipeline_tests/regression_pipeline_tests/test_multiseries_regression_pipeline.py
@@ -347,7 +347,7 @@ def test_time_series_pipeline_get_prediction_intervals(
  )
  X_train, y_train = X[:65], y[:65]
  X_validation, y_validation = X[65:], y[65:]
- mock_X, _ = unstack_multiseries(
+ mock_X, mock_y = unstack_multiseries(
  X_train,
  y_train,
  series_id="series_id",
@@ -356,7 +356,7 @@ def test_time_series_pipeline_get_prediction_intervals(
  )
  mock_transform_return_value = (
  mock_X,
- pd.DataFrame(np.random.rand(13, 5)),
+ mock_y,
  )
  with patch(
  "evalml.pipelines.components.transformers.preprocessing.stl_decomposer.STLDecomposer.transform",