Raise UserWarnings for Unused Numerical Distributions when using `G…

…aussianCopulaSynthesizer` (#2301)

sdv/single_table/copulagan.py

@@ -8,8 +8,8 @@
 from sdv.single_table.copulas import GaussianCopulaSynthesizer
 from sdv.single_table.ctgan import CTGANSynthesizer
 from sdv.single_table.utils import (
-    log_numerical_distributions_error,
     validate_numerical_distributions,
+    warn_missing_numerical_distributions,
 )
 
 LOGGER = logging.getLogger(__name__)
@@ -204,10 +204,7 @@ def _fit(self, processed_data):
             processed_data (pandas.DataFrame):
                 Data to be learned.
         """
-        log_numerical_distributions_error(
-            self.numerical_distributions, processed_data.columns, LOGGER
-        )
-
+        warn_missing_numerical_distributions(self.numerical_distributions, processed_data.columns)
         gaussian_normalizer_config = self._create_gaussian_normalizer_config(processed_data)
         self._gaussian_normalizer_hyper_transformer = rdt.HyperTransformer()
         self._gaussian_normalizer_hyper_transformer.set_config(gaussian_normalizer_config)

sdv/single_table/copulas.py

@@ -17,9 +17,9 @@
 from sdv.single_table.base import BaseSingleTableSynthesizer
 from sdv.single_table.utils import (
     flatten_dict,
-    log_numerical_distributions_error,
     unflatten_dict,
     validate_numerical_distributions,
+    warn_missing_numerical_distributions,
 )
 
 LOGGER = logging.getLogger(__name__)
@@ -132,9 +132,7 @@ def _fit(self, processed_data):
             processed_data (pandas.DataFrame):
                 Data to be learned.
         """
-        log_numerical_distributions_error(
-            self.numerical_distributions, processed_data.columns, LOGGER
-        )
+        warn_missing_numerical_distributions(self.numerical_distributions, processed_data.columns)
         self._num_rows = self._learn_num_rows(processed_data)
         numerical_distributions = self._get_numerical_distributions(processed_data)
         self._model = self._initialize_model(numerical_distributions)

sdv/single_table/utils.py

@@ -330,12 +330,12 @@ def validate_numerical_distributions(numerical_distributions, metadata_columns):
             )
 
 
-def log_numerical_distributions_error(numerical_distributions, processed_data_columns, logger):
-    """Log error when numerical distributions columns don't exist anymore."""
+def warn_missing_numerical_distributions(numerical_distributions, processed_data_columns):
+    """Raise an `UserWarning` when numerical distribution columns don't exist anymore."""
     unseen_columns = numerical_distributions.keys() - set(processed_data_columns)
     for column in unseen_columns:
-        logger.info(
-            f"Requested distribution '{numerical_distributions[column]}' "
-            f"cannot be applied to column '{column}' because it no longer "
-            'exists after preprocessing.'
+        warnings.warn(
+            f"Cannot use distribution '{numerical_distributions[column]}' for column "
+            f"'{column}' because the column is not statistically modeled.",
+            UserWarning,
         )

tests/integration/single_table/test_copulas.py

@@ -500,3 +500,25 @@ def test_support_nullable_pandas_dtypes():
     assert (synthetic_data.dtypes == data.dtypes).all()
     assert (synthetic_data['Float32'] == synthetic_data['Float32'].round(1)).all(skipna=True)
     assert (synthetic_data['Float64'] == synthetic_data['Float64'].round(3)).all(skipna=True)
+
+
+def test_user_warning_for_unused_numerical_distribution():
+    """Ensure that a `UserWarning` is raised when a numerical distribution is not applied.
+
+    This test verifies that the synthesizer warns the user if a specified numerical
+    distribution is not used because the corresponding column does not exist or is not
+    modeled after preprocessing.
+    """
+    # Setup
+    data, metadata = download_demo('single_table', 'fake_hotel_guests')
+    synthesizer = GaussianCopulaSynthesizer(
+        metadata, numerical_distributions={'credit_card_number': 'beta'}
+    )
+
+    # Run and Assert
+    message = (
+        "Cannot use distribution 'beta' for column 'credit_card_number' because the column is not "
+        'statistically modeled.'
+    )
+    with pytest.warns(UserWarning, match=message):
+        synthesizer.fit(data)

tests/unit/single_table/test_copulagan.py

@@ -263,10 +263,10 @@ def test__create_gaussian_normalizer_config(self, mock_rdt):
         assert config == expected_config
         assert mock_rdt.transformers.GaussianNormalizer.call_args_list == expected_calls
 
-    @patch('sdv.single_table.copulagan.LOGGER')
+    @patch('sdv.single_table.utils.warnings')
     @patch('sdv.single_table.copulagan.CTGANSynthesizer._fit')
     @patch('sdv.single_table.copulagan.rdt')
-    def test__fit_logging(self, mock_rdt, mock_ctgansynthesizer__fit, mock_logger):
+    def test__fit_logging(self, mock_rdt, mock_ctgansynthesizer__fit, mock_warnings):
         """Test a message is logged.
 
         A message should be logged if the columns passed in ``numerical_distributions``
@@ -284,10 +284,11 @@ def test__fit_logging(self, mock_rdt, mock_ctgansynthesizer__fit, mock_logger):
         instance._fit(processed_data)
 
         # Assert
-        mock_logger.info.assert_called_once_with(
-            "Requested distribution 'gamma' cannot be applied to column 'col' "
-            'because it no longer exists after preprocessing.'
+        warning_message = (
+            "Cannot use distribution 'gamma' for column 'col' because the column is not "
+            'statistically modeled.'
         )
+        mock_warnings.warn.assert_called_once_with(warning_message, UserWarning)
 
     @patch('sdv.single_table.copulagan.CTGANSynthesizer._fit')
     @patch('sdv.single_table.copulagan.rdt')

tests/unit/single_table/test_copulas.py

@@ -159,11 +159,11 @@ def test_get_parameters(self):
             'default_distribution': 'beta',
         }
 
-    @patch('sdv.single_table.copulas.LOGGER')
-    def test__fit_logging(self, mock_logger):
-        """Test a message is logged.
+    @patch('sdv.single_table.utils.warnings')
+    def test__fit_warning_numerical_distributions(self, mock_warnings):
+        """Test that a warning is shown when fitting numerical distributions on a dropped column.
 
-        A message should be logged if the columns passed in ``numerical_distributions``
+        A warning message should be printed if the columns passed in ``numerical_distributions``
         were renamed/dropped during preprocessing.
         """
         # Setup
@@ -180,10 +180,11 @@ def test__fit_logging(self, mock_logger):
         instance._fit(processed_data)
 
         # Assert
-        mock_logger.info.assert_called_once_with(
-            "Requested distribution 'gamma' cannot be applied to column 'col' "
-            'because it no longer exists after preprocessing.'
+        warning_message = (
+            "Cannot use distribution 'gamma' for column 'col' because the column is not "
+            'statistically modeled.'
         )
+        mock_warnings.warn.assert_called_once_with(warning_message, UserWarning)
 
     @patch('sdv.single_table.copulas.warnings')
     @patch('sdv.single_table.copulas.multivariate')

tests/unit/single_table/test_utils.py

@@ -14,6 +14,7 @@
     handle_sampling_error,
     unflatten_dict,
     validate_file_path,
+    warn_missing_numerical_distributions,
 )
 
 
@@ -328,3 +329,18 @@ def test_validate_file_path(mock_open):
     assert output_path in result
     assert none_result is None
     mock_open.assert_called_once_with(result, 'w+')
+
+
+def test_warn_missing_numerical_distributions():
+    """Test the warn_missing_numerical_distributions function."""
+    # Setup
+    numerical_distributions = {'age': 'beta', 'height': 'uniform'}
+    processed_data_columns = ['height', 'weight']
+
+    # Run and Assert
+    message = (
+        "Cannot use distribution 'beta' for column 'age' because the column is not "
+        'statistically modeled.'
+    )
+    with pytest.warns(UserWarning, match=message):
+        warn_missing_numerical_distributions(numerical_distributions, processed_data_columns)