update tests

Author: OlivieFranklova

similarity_framework/src/impl/comparator/comparator_by_column.py

@@ -273,7 +273,7 @@ def compare_constants(
             value: float = 0 if metadata1.value == metadata2.value else 1
         else:
             value = 1 - cosine_sim(
-                metadata1.value_embeddings[0], # todo 0 nebo 1
+                metadata1.value_embeddings[0],  # todo 0 nebo 1
                 metadata2.value_embeddings[0],
             )
         # if nulls are equal and exist

similarity_framework/src/impl/comparator/comparator_by_type.py

@@ -353,7 +353,7 @@ def compare_constants(self, metadata1: Metadata, metadata2: Metadata) -> pd.Data
                     value_re.loc[column1, column2] = int(meta1.value != meta2.value)
                 else:
                     value_re.loc[column1, column2] = 1 - cosine_sim(
-                        meta1.value_embeddings[0], #todo 0 nebo 1
+                        meta1.value_embeddings[0],  # todo 0 nebo 1
                         meta2.value_embeddings[0],
                     )
 

similarity_framework/src/impl/comparator/distance_functions.py

@@ -19,6 +19,7 @@ def compute(self, distance_table: pd.DataFrame) -> float:
         column_mins = distance_table.min(axis=0)
         return min(row_mins.max(), column_mins.max())
 
+
 class AverageDist(DistanceFunction):
     """Hausdorff distance class"""
 
@@ -33,4 +34,4 @@ def compute(self, distance_table: pd.DataFrame) -> float:
         row_avg = distance_table.min(axis=1)
         # column_avg = distance_table.min(axis=0)
         # return min(row_avg.mean(), column_avg.mean())
-        return row_avg.mean()
+        return row_avg.mean()

similarity_framework/src/models/metadata.py

@@ -114,7 +114,7 @@ def __init__(
         self.nulls = null_values
         self.value = value
         self.distribution = distribution
-        #model.encode(list(value)).view(-1, 1)
+        # model.encode(list(value)).view(-1, 1)
         self.value_embeddings = None if type(value[0]) is not str else model.encode(list(value))
 
     def __str__(self):

tests/similarity_framework/test_similarity_comparator.py

@@ -11,7 +11,8 @@
                                                       ColumnExactNamesHandler as ColumnExactNamesHandlerByColumn,
                                                       ColumnKindHandler, ColumnEmbeddingsHandler
                                                       )
-from similarity_framework.src.impl.comparator.utils import concat
+from similarity_framework.src.impl.comparator.distance_functions import AverageDist
+from similarity_framework.src.impl.comparator.utils import concat, cosine_sim, fill_result, are_columns_null, create_string_from_columns
 from similarity_framework.src.models.metadata import MetadataCreatorInput
 from similarity_framework.src.models.similarity import Settings
 from similarity_framework.src.impl.metadata.type_metadata_creator import TypeMetadataCreator
@@ -40,12 +41,85 @@ def test_hausdorff_min(self):
         self.assertEqual(HausdorffDistanceMin().compute(df3), 1)
         self.assertEqual(HausdorffDistanceMin().compute(df4), 3)
 
+    def test_average_dist(self):
+        df1 = pd.DataFrame([(2, 3, 3), (1, 4, 2), (5, 1, 2)])
+        df2 = pd.DataFrame([(7, 2, 2), (8, 3, 4), (9, 2, 5)])
+        df3 = pd.DataFrame([(1, 1, 3), (1, 2, 3), (1, -1, 2)])
+        df4 = pd.DataFrame([(5, 3, 4), (2, 8, 8), (1, 100, 100)])
+        self.assertEqual(AverageDist().compute(df1), 4/3)
+        self.assertEqual(AverageDist().compute(df2), 7/3)
+        self.assertEqual(AverageDist().compute(df3), 1/3)
+        self.assertEqual(AverageDist().compute(df4), 6/3)
+
     def test_get_ratio(self):
         self.assertEqual(round(get_ratio(3, 5), 2), 1.67)
         self.assertEqual(round(get_ratio(5, 3), 2), 1.67)
         self.assertEqual(round(get_ratio(15, 9), 2), 1.67)
         self.assertEqual(round(get_ratio(9, 15), 2), 1.67)
 
+    def test_cosine_sim(self):
+        self.assertEqual(cosine_sim([1, 2, 3], [1, 2, 3]), 1)
+        self.assertEqual(cosine_sim([1, 2, 3], [3, 2, 1]), 0.714)
+        self.assertEqual(cosine_sim([1, 2, 3], [1, 2, 4]), 0.991)
+        self.assertEqual(cosine_sim([1, 2, 3], [1, 2, 2]), 0.98)
+        self.assertEqual(cosine_sim([1, 2, 3], [-1, -2, -3]),  -1)
+
+    def test_fill_result(self):
+        metadata1_names = {0: 'a', 1: 'b', 2: 'c'}
+        metadata2_names = {0: 'a', 1: 'b', 2: 'd'}
+        data = {
+            0: [0.0, 1.0, 1.0],
+            1: [1.0, 0.0, 1.0],
+            2: [1.0, 1.0, 1.0]
+        }
+
+        res = pd.DataFrame(data)
+        print(res)
+        self.assertTrue(fill_result(metadata1_names, metadata2_names).equals(res))
+
+    def test_create_string_from_columns(self):
+        # Create sample data
+        df1 = pd.DataFrame({
+            'col1': [1, 2, 3],
+            'col2': [4, 5, 6]
+        })
+        df2 = pd.DataFrame({
+            'col1': [7, 8, 9],
+            'col2': [10, 11, 12]
+        })
+        database = [df1, df2]
+        table_names = ['table1', 'table2']
+
+        # Expected results
+        expected_sentences = [
+            '1, 2, 3', '4, 5, 6',
+            '7, 8, 9', '10, 11, 12'
+        ]
+        expected_sentences_datasets = [
+            'table1', 'table1',
+            'table2', 'table2'
+        ]
+
+        # Run the function
+        sentences, sentences_datasets = create_string_from_columns(database, table_names)
+
+        # Assert the results
+        self.assertEqual(sentences, expected_sentences)
+        self.assertEqual(sentences_datasets, expected_sentences_datasets)
+
+class TestAreColumnsNull(unittest.TestCase):
+    def test_both_columns_empty(self):
+        self.assertEqual(are_columns_null(set(), set(), "Test message"), (True, 0))
+
+    def test_first_column_empty(self):
+        self.assertEqual(are_columns_null(set(), {1, 2, 3}, "Test message"), (True, 1))
+
+    def test_second_column_empty(self):
+        self.assertEqual(are_columns_null({1, 2, 3}, set(), "Test message"), (True, 1))
+
+    def test_both_columns_non_empty(self):
+        self.assertEqual(are_columns_null({1, 2, 3}, {4, 5, 6}, "Test message"), (False, 0))
+
 
 class TestSingleSpecificComparator(unittest.TestCase):
     def setUp(self):