make release-tag: Merge branch 'main' into stable

Author: amontanez24

HISTORY.md

@@ -1,5 +1,11 @@
 # History
 
+## v0.21.0 - 2025-05-29
+
+### New Features
+
+* Add a violin plot visualizations to compare a pair of columns - Issue [#759](https://github.com/sdv-dev/SDMetrics/issues/759) by @R-Palazzo
+
 ## v0.20.1 - 2025-04-14
 
 ### Bugs Fixed

pyproject.toml

@@ -141,7 +141,7 @@ convention = 'google'
 add-ignore = ['D107', 'D407', 'D417']
 
 [tool.bumpversion]
-current_version = "0.20.1"
+current_version = "0.21.0.dev1"
 parse = '(?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\.(?P<release>[a-z]+)(?P<candidate>\d+))?'
 serialize = [
     '{major}.{minor}.{patch}.{release}{candidate}',

sdmetrics/__init__.py

@@ -4,7 +4,7 @@
 
 __author__ = 'MIT Data To AI Lab'
 __email__ = 'dailabmit@gmail.com'
-__version__ = '0.20.1'
+__version__ = '0.21.0.dev1'
 
 import sys
 import warnings as python_warnings

sdmetrics/visualization.py

@@ -153,6 +153,33 @@ def _generate_box_plot(all_data, columns):
     return fig
 
 
+def _generate_violin_plot(data, columns):
+    """Return a violin plot for a given column pair."""
+    fig = px.violin(
+        data,
+        x=columns[0],
+        y=columns[1],
+        box=False,
+        violinmode='overlay',
+        color='Data',
+        color_discrete_map={
+            'Real': PlotConfig.DATACEBO_DARK,
+            'Synthetic': PlotConfig.DATACEBO_GREEN,
+        },
+    )
+
+    unique_values = data['Data'].unique()
+    title = ' vs. '.join(unique_values)
+    title += f" Data for columns '{columns[0]}' and '{columns[1]}'"
+    fig.update_layout(
+        title=title,
+        plot_bgcolor=PlotConfig.BACKGROUND_COLOR,
+        font={'size': PlotConfig.FONT_SIZE},
+    )
+
+    return fig
+
+
 def _generate_scatter_plot(all_data, columns):
     """Generate a scatter plot for column pair plot.
 
@@ -615,10 +642,10 @@ def get_column_pair_plot(real_data, synthetic_data, column_names, plot_type=None
             )
         synthetic_data = synthetic_data[column_names]
 
-    if plot_type not in ['box', 'heatmap', 'scatter', None]:
+    if plot_type not in ['box', 'heatmap', 'scatter', 'violin', None]:
         raise ValueError(
             f"Invalid plot_type '{plot_type}'. Please use one of "
-            "['box', 'heatmap', 'scatter', None]."
+            "['box', 'heatmap', 'scatter', 'violin', None]."
         )
 
     if plot_type is None:
@@ -654,6 +681,8 @@ def get_column_pair_plot(real_data, synthetic_data, column_names, plot_type=None
         return _generate_scatter_plot(all_data, column_names)
     elif plot_type == 'heatmap':
         return _generate_heatmap_plot(all_data, column_names)
+    elif plot_type == 'violin':
+        return _generate_violin_plot(all_data, column_names)
 
     return _generate_box_plot(all_data, column_names)
 

static_code_analysis.txt

@@ -1,4 +1,4 @@
-Run started:2025-04-14 17:22:41.156789
+Run started:2025-05-29 18:58:21.274050
 
 Test results:
 >> Issue: [B101:assert_used] Use of assert detected. The enclosed code will be removed when compiling to optimised byte code.
@@ -117,7 +117,7 @@ Test results:
 --------------------------------------------------
 
 Code scanned:
-	Total lines of code: 11344
+	Total lines of code: 11374
 	Total lines skipped (#nosec): 0
 	Total potential issues skipped due to specifically being disabled (e.g., #nosec BXXX): 0
 

tests/unit/test_visualization.py

@@ -15,6 +15,7 @@
     _generate_heatmap_plot,
     _generate_line_plot,
     _generate_scatter_plot,
+    _generate_violin_plot,
     _get_cardinality,
     _get_max_between_datasets,
     _get_min_between_datasets,
@@ -1004,6 +1005,47 @@ def test__generate_box_plot_title_one_dataset_only(px_mock):
     assert fig_real == mock_figure
 
 
+@patch('sdmetrics.visualization.px')
+def test__generate_violin_plot(px_mock):
+    """Test the ``_generate_violin_plot`` method."""
+    # Setup
+    real_column = pd.DataFrame({
+        'col1': [1, 2, 3, 4],
+        'col2': ['a', 'b', 'c', 'd'],
+        'Data': ['Real'] * 4,
+    })
+    synthetic_column = pd.DataFrame({
+        'col1': [1, 2, 4, 5],
+        'col2': ['a', 'b', 'c', 'd'],
+        'Data': ['Synthetic'] * 4,
+    })
+    columns = ['col1', 'col2']
+    all_data = pd.concat([real_column, synthetic_column], axis=0, ignore_index=True)
+
+    mock_figure = Mock()
+    px_mock.violin.return_value = mock_figure
+
+    # Run
+    fig = _generate_violin_plot(all_data, columns)
+
+    # Assert
+    px_mock.violin.assert_called_once_with(
+        DataFrameMatcher(all_data),
+        x='col1',
+        y='col2',
+        box=False,
+        violinmode='overlay',
+        color='Data',
+        color_discrete_map={'Real': '#000036', 'Synthetic': '#01E0C9'},
+    )
+    mock_figure.update_layout.assert_called_once_with(
+        title="Real vs. Synthetic Data for columns 'col1' and 'col2'",
+        plot_bgcolor='#F5F5F8',
+        font={'size': 18},
+    )
+    assert fig == mock_figure
+
+
 def test_get_column_pair_plot_invalid_column_names():
     """Test ``get_column_pair_plot`` method with invalid ``column_names``."""
     # Setup
@@ -1049,12 +1091,34 @@ def test_get_column_pair_plot_invalid_plot_type():
 
     # Run and Assert
     match = re.escape(
-        "Invalid plot_type 'distplot'. Please use one of ['box', 'heatmap', 'scatter', None]."
+        "Invalid plot_type 'distplot'. Please use one of ['box', 'heatmap', 'scatter',"
+        " 'violin', None]."
     )
     with pytest.raises(ValueError, match=match):
         get_column_pair_plot(real_data, synthetic_data, columns, plot_type='distplot')
 
 
+@patch('sdmetrics.visualization._generate_violin_plot')
+def test_get_column_pair_plot_violin(mock__generate_violin_plot):
+    """Test ``get_column_pair_plot`` with ``plot_type`` set to ``violin``."""
+    # Setup
+    columns = ['amount', 'price']
+    real_data = pd.DataFrame({'amount': [1, 2, 3], 'price': [4, 5, 6]})
+    synthetic_data = pd.DataFrame({'amount': [1.0, 2.0, 3.0], 'price': [4.0, 5.0, 6.0]})
+    all_data = pd.concat([real_data, synthetic_data], axis=0, ignore_index=True)
+    all_data['Data'] = ['Real'] * 3 + ['Synthetic'] * 3
+
+    # Run
+    fig = get_column_pair_plot(real_data, synthetic_data, columns, plot_type='violin')
+
+    # Assert
+    mock__generate_violin_plot.assert_called_once_with(
+        DataFrameMatcher(all_data),
+        ['amount', 'price'],
+    )
+    assert fig == mock__generate_violin_plot.return_value
+
+
 @patch('sdmetrics.visualization._generate_scatter_plot')
 def test_get_column_pair_plot_plot_type_none_continuous_data(mock__generate_scatter_plot):
     """Test ``get_column_pair_plot`` with continuous data and ``plot_type`` ``None``."""