adapt test to new function structure

tests/test_data_generators.py

@@ -7,7 +7,8 @@
 from ms2deepscore import SpectrumBinner
 from ms2deepscore.data_generators import (DataGeneratorAllInchikeys,
                                           DataGeneratorAllSpectrums,
-                                          DataGeneratorBase)
+                                          _exclude_nans_from_labels,
+                                          _validate_labels)
 from tests.test_user_worfklow import load_processed_spectrums, get_reference_scores
 
 
@@ -316,11 +317,11 @@ def test_validate_labels():
     # Test case 1: reference_scores_df with different index and column names
     ref_scores = pd.DataFrame({'A1': [0.5, 0.6], 'A2': [0.7, 0.8]}, index=['B1', 'B2'])
     with pytest.raises(ValueError):
-        DataGeneratorBase._validate_labels(ref_scores)
+        _validate_labels(ref_scores)
 
     # Test case 2: reference_scores_df with identical index and column names
     ref_scores = pd.DataFrame({'A1': [0.5, 0.6], 'A2': [0.7, 0.8]}, index=['A1', 'A2'])
-    DataGeneratorBase._validate_labels(ref_scores)  # Should not raise ValueError
+    _validate_labels(ref_scores)  # Should not raise ValueError
 
 
 def test_exclude_nans_from_labels():
@@ -334,7 +335,7 @@ def test_exclude_nans_from_labels():
     reference_scores_df = pd.DataFrame(data, index=["A", "B", "C", "D"])
 
     # Call the _exclude_nans_from_labels method
-    clean_df = DataGeneratorBase._exclude_nans_from_labels(reference_scores_df)
+    clean_df = _exclude_nans_from_labels(reference_scores_df)
 
     # Expected DataFrame after removing rows and columns with NaN values
     expected_data = {