fix parentheses

aimclub · Feb 8, 2024 · 459041e · 459041e
1 parent 5f98ed8
commit 459041e
Showing 1 changed file with 21 additions and 19 deletions.
diff --git a/test/unit/data/test_data_split.py b/test/unit/data/test_data_split.py
@@ -202,25 +202,27 @@ def test_multivariate_time_series_splitting_correct():
         assert np.allclose(test_series_data.target, np.array([16, 17, 18, 19]))
 
 
-@pytest.mark.parametrize(('datas_funs', 'cv_folds', 'shuffle', 'stratify'),
-                         [
-    # classification + stratify + shuffle + cv_folds
-    ([partial(get_tabular_classification_data, 100, 5)] * 3, 4, True, True),
-    # classification + shuffle + cv_folds
-    ([partial(get_tabular_classification_data, 100, 5)] * 3, 4, True, False),
-    # classification + cv_folds
-    ([partial(get_tabular_classification_data, 100, 5)] * 3, 4, False, False),
-    # classification + stratify + shuffle
-    ([partial(get_tabular_classification_data, 100, 5)] * 3, None, True, True),
-    # classification + shuffle
-    ([partial(get_tabular_classification_data, 100, 5)] * 3, None, True, False),
-    # classification
-    ([partial(get_tabular_classification_data, 100, 5)] * 3, None, False, False),
-    # timeseries + cv_folds
-    ([partial(get_ts_data_to_forecast, 10, 100)] * 3, 3, False, False),
-    # timeseries
-    ([partial(get_ts_data_to_forecast, 10, 100)] * 3, None, False, False),
-])
+@pytest.mark.parametrize(
+    ("datas_funs", "cv_folds", "shuffle", "stratify"),
+    [
+        # classification + stratify + shuffle + cv_folds
+        ([partial(get_tabular_classification_data, 100, 5)] * 3, 4, True, True),
+        # classification + shuffle + cv_folds
+        ([partial(get_tabular_classification_data, 100, 5)] * 3, 4, True, False),
+        # classification + cv_folds
+        ([partial(get_tabular_classification_data, 100, 5)] * 3, 4, False, False),
+        # classification + stratify + shuffle
+        ([partial(get_tabular_classification_data, 100, 5)] * 3, None, True, True),
+        # classification + shuffle
+        ([partial(get_tabular_classification_data, 100, 5)] * 3, None, True, False),
+        # classification
+        ([partial(get_tabular_classification_data, 100, 5)] * 3, None, False, False),
+        # timeseries + cv_folds
+        ([partial(get_ts_data_to_forecast, 10, 100)] * 3, 3, False, False),
+        # timeseries
+        ([partial(get_ts_data_to_forecast, 10, 100)] * 3, None, False, False),
+    ],
+)
 def test_multimodal_data_splitting_is_correct(datas_funs, cv_folds, shuffle, stratify):
     mdata = MultiModalData({f'data_{i}': data_fun() for i, data_fun in enumerate(datas_funs)})
     data_splitter = DataSourceSplitter(cv_folds=cv_folds, shuffle=shuffle, stratify=stratify)