[FIX] tests + bump version

BioSystemsUM · Jan 15, 2025 · 9d5e6ab · 9d5e6ab
1 parent 4c0c245
commit 9d5e6ab
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Showing 4 changed files with 14 additions and 14 deletions.
diff --git a/setup.cfg b/setup.cfg
@@ -1,6 +1,6 @@
 [metadata]
 name = deepmol
-version = 1.1.9
+version = 1.1.10
 description = DeepMol: a python-based machine and deep learning framework for drug discovery
 keywords = machine-learning, deep-learning, cheminformatics, drug-discovery
 author = DeepMol Team

diff --git a/src/deepmol/__init__.py b/src/deepmol/__init__.py
@@ -1,2 +1,2 @@
 
-__version__ = '1.1.9'
+__version__ = '1.1.10'
diff --git a/tests/integration_tests/dataset/test_dataset.py b/tests/integration_tests/dataset/test_dataset.py
@@ -23,3 +23,15 @@ def setUp(self):
                            labels_fields=['Class'])
 
         self.small_dataset_to_test_with_invalid = loader.create_dataset(sep=",")
+
+        multilabel_classification_df = os.path.join(TEST_DIR, 'data', "multilabel_classification_dataset.csv")
+        loader = CSVLoader(dataset_path=multilabel_classification_df,
+                           smiles_field='smiles',
+                           id_field='ids',
+                           labels_fields=['C00341', 'C01789', 'C00078', 'C00049', 'C00183', 'C03506', 'C00187',
+                                          'C00079', 'C00047', 'C01852', 'C00407', 'C00129', 'C00235', 'C00062',
+                                          'C00353', 'C00148', 'C00073', 'C00108', 'C00123', 'C00135', 'C00448',
+                                          'C00082', 'C00041'],
+                           mode='auto')
+        # create the dataset
+        self.multilabel_classification = loader.create_dataset(sep=',', header=0, nrows=100)
diff --git a/tests/integration_tests/dataset/test_dataset_models.py b/tests/integration_tests/dataset/test_dataset_models.py
@@ -59,18 +59,6 @@ def model_build_regression(): # num = number of categories
 
 class TestDatasetModels(TestDataset):
 
-    def setUp(self):
-        multilabel_classification_df = os.path.join(TEST_DIR, 'data', "multilabel_classification_dataset.csv")
-        loader = CSVLoader(dataset_path=multilabel_classification_df,
-                           smiles_field='smiles',
-                           id_field='ids',
-                           labels_fields=['C00341', 'C01789', 'C00078', 'C00049', 'C00183', 'C03506', 'C00187',
-                                          'C00079', 'C00047', 'C01852', 'C00407', 'C00129', 'C00235', 'C00062',
-                                          'C00353', 'C00148', 'C00073', 'C00108', 'C00123', 'C00135', 'C00448',
-                                          'C00082', 'C00041'],
-                           mode='auto')
-        # create the dataset
-        self.multilabel_classification = loader.create_dataset(sep=',', header=0, nrows=100)
 
     def _test_model(self, model):
         model.fit(self.small_dataset_to_test_with_invalid)