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Adapt Unittest for new splits parameters #103

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sfluegel05 merged 1 commit into from
Jul 14, 2025
Merged

Adapt Unittest for new splits parameters #103

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17 changes: 13 additions & 4 deletions tests/unit/dataset_classes/testDynamicDataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -85,8 +85,10 @@ def test_get_test_split_valid(self) -> None:
"""
Test splitting the dataset into train and test sets and verify balance and non-overlap.
"""
self.dataset.train_split = 0.5
# self.dataset.train_split = 0.5
# Test size will be 0.25 * 16 = 4
self.dataset.test_split = 0.25
self.dataset.validation_split = 0.25
train_df, test_df = self.dataset.get_test_split(self.data_df, seed=0)

# Assert the correct number of rows in train and test sets
Expand Down Expand Up @@ -149,7 +151,9 @@ def test_get_train_val_splits_given_test(self) -> None:
Test splitting the dataset into train and validation sets and verify balance and non-overlap.
"""
self.dataset.use_inner_cross_validation = False
self.dataset.train_split = 0.5
# self.dataset.train_split = 0.5
self.dataset.test_split = 0.25
self.dataset.validation_split = 0.25
df_train_main, test_df = self.dataset.get_test_split(self.data_df, seed=0)
train_df, val_df = self.dataset.get_train_val_splits_given_test(
df_train_main, test_df, seed=42
Expand Down Expand Up @@ -220,7 +224,9 @@ def test_get_test_split_stratification(self) -> None:
"""
Test that the split into train and test sets maintains the stratification of labels.
"""
self.dataset.train_split = 0.5
# self.dataset.train_split = 0.5
self.dataset.test_split = 0.25
self.dataset.validation_split = 0.25
train_df, test_df = self.dataset.get_test_split(self.data_df, seed=0)

number_of_labels = len(self.data_df["labels"][0])
Expand Down Expand Up @@ -288,7 +294,10 @@ def test_get_train_val_splits_given_test_stratification(self) -> None:
Test that the split into train and validation sets maintains the stratification of labels.
"""
self.dataset.use_inner_cross_validation = False
self.dataset.train_split = 0.5
# self.dataset.train_split = 0.5
self.dataset.test_split = 0.25
self.dataset.validation_split = 0.25

df_train_main, test_df = self.dataset.get_test_split(self.data_df, seed=0)
train_df, val_df = self.dataset.get_train_val_splits_given_test(
df_train_main, test_df, seed=42
Expand Down