add more integration tests

tests/integration/transformers/test_numerical.py

@@ -7,6 +7,7 @@
     ClusterBasedNormalizer,
     FloatFormatter,
     GaussianNormalizer,
+    LogScaler,
 )
 
 
@@ -560,3 +561,58 @@ def test_out_of_bounds_reverse_transform(self):
 
         # Assert
         assert isinstance(reverse, pd.DataFrame)
+
+
+class TestLogScaler:
+    def test_learn_rounding(self):
+        # Setup
+        data = pd.DataFrame({'test': [1.0, np.nan, 1.5]})
+        transformer = LogScaler(
+            missing_value_generation=None,
+            missing_value_replacement='mean',
+            learn_rounding_scheme=True,
+        )
+        expected = pd.DataFrame({'test': [1.0, 1.2, 1.5]})
+
+        # Run
+        transformer.fit(data, 'test')
+        transformed = transformer.transform(data)
+        reversed = transformer.reverse_transform(transformed)
+
+        # Assert
+        np.testing.assert_array_equal(reversed, expected)
+
+    def test_missing_value_generation_from_column(self):
+        # Setup
+        data = pd.DataFrame({'test': [1.0, np.nan, 1.5]})
+        transformer = LogScaler(
+            missing_value_generation='from_column',
+            missing_value_replacement='mean',
+        )
+
+        # Run
+        transformer.fit(data, 'test')
+        transformed = transformer.transform(data)
+        reversed = transformer.reverse_transform(transformed)
+
+        # Assert
+        np.testing.assert_array_equal(reversed, data)
+
+    def test_missing_value_generation_random(self):
+        # Setup
+        data = pd.DataFrame({'test': [1.0, np.nan, 1.5, 1.5]})
+        transformer = LogScaler(
+            missing_value_generation='random',
+            missing_value_replacement='mode',
+            invert=True,
+            constant=3,
+        )
+        expected = pd.DataFrame({'test': [np.nan, 1.5, 1.5, 1.5]})
+
+        # Run
+        transformer.fit(data, 'test')
+        transformed = transformer.transform(data)
+        reversed = transformer.reverse_transform(transformed)
+
+        # Assert
+        np.testing.assert_array_equal(reversed, expected)