Fix test mocks for segment_tissue return value

segment_tissue returns 4 values (polygon, _, coords, attrs) but tests
were mocking it to return only 2 values, causing unpacking errors.

Fixes:
- Mock segment_tissue to return all 4 values
- Mock gr.Warning to avoid argument mismatch errors
- Use tempfile for directory creation in Gradio test
- Mock DataFrame.to_csv to avoid file system issues

All regression tests now pass.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

tests/test_regression_single_slide.py

@@ -53,7 +53,9 @@ class TestSingleSlideRegression:
         # Setup mocks
         mock_coords = np.array([[0, 0], [1, 1]])
         mock_attrs = {"level": 0}
-        mock_segment.return_value = (mock_coords, mock_attrs)
+        mock_polygon = Mock()
+        # segment_tissue returns (polygon, _, coords, attrs)
+        mock_segment.return_value = (mock_polygon, None, mock_coords, mock_attrs)
 
         mock_mask_image = Mock()
         mock_mask.return_value = mock_mask_image
@@ -108,59 +110,65 @@ class TestSingleSlideRegression:
     @patch('mosaic.ui.app.analyze_slide')
     @patch('mosaic.ui.app.create_user_directory')
     @patch('mosaic.ui.app.validate_settings')
+    @patch('pandas.DataFrame.to_csv')  # Mock CSV writing to avoid directory issues
     def test_gradio_single_slide_uses_analyze_slide(
         self,
+        mock_to_csv,
         mock_validate,
         mock_create_dir,
         mock_analyze_slide,
     ):
         """Test that Gradio UI uses analyze_slide for single slide (not batch mode)."""
         # Setup
-        mock_dir = Path("/tmp/test_user")
-        mock_create_dir.return_value = mock_dir
-
-        settings_df = pd.DataFrame({
-            "Slide": ["test.svs"],
-            "Site Type": ["Primary"],
-            "Sex": ["Male"],
-            "Tissue Site": ["Lung"],
-            "Cancer Subtype": ["Unknown"],
-            "IHC Subtype": [""],
-            "Segmentation Config": ["Biopsy"],
-        })
-        mock_validate.return_value = settings_df
-
-        mock_mask = Mock()
-        mock_aeon = pd.DataFrame({"Cancer Subtype": ["LUAD"], "Confidence": [0.9]})
-        mock_paladin = pd.DataFrame({
-            "Cancer Subtype": ["LUAD"],
-            "Biomarker": ["EGFR"],
-            "Score": [0.8]
-        })
-        mock_analyze_slide.return_value = (mock_mask, mock_aeon, mock_paladin)
-
-        from mosaic.ui.app import cancer_subtype_name_map
-
-        # Call analyze_slides with a single slide
-        with patch('mosaic.ui.app.get_oncotree_code_name', return_value="Lung Adenocarcinoma"):
-            masks, aeon, aeon_btn, paladin, paladin_btn, user_dir = analyze_slides(
-                slides=["test.svs"],
-                settings_input=settings_df,
-                user_dir=mock_dir,
-            )
-
-        # Verify analyze_slide was called (not analyze_slides_batch)
-        mock_analyze_slide.assert_called_once()
-
-        # Verify results
-        assert len(masks) == 1
+        import tempfile
+        with tempfile.TemporaryDirectory() as tmpdir:
+            mock_dir = Path(tmpdir) / "test_user"
+            mock_dir.mkdir()
+            mock_create_dir.return_value = mock_dir
+
+            settings_df = pd.DataFrame({
+                "Slide": ["test.svs"],
+                "Site Type": ["Primary"],
+                "Sex": ["Male"],
+                "Tissue Site": ["Lung"],
+                "Cancer Subtype": ["Unknown"],
+                "IHC Subtype": [""],
+                "Segmentation Config": ["Biopsy"],
+            })
+            mock_validate.return_value = settings_df
+
+            mock_mask = Mock()
+            mock_aeon = pd.DataFrame({"Cancer Subtype": ["LUAD"], "Confidence": [0.9]})
+            mock_paladin = pd.DataFrame({
+                "Cancer Subtype": ["LUAD"],
+                "Biomarker": ["EGFR"],
+                "Score": [0.8]
+            })
+            mock_analyze_slide.return_value = (mock_mask, mock_aeon, mock_paladin)
+
+            from mosaic.ui.app import cancer_subtype_name_map
+
+            # Call analyze_slides with a single slide
+            with patch('mosaic.ui.app.get_oncotree_code_name', return_value="Lung Adenocarcinoma"):
+                masks, aeon, aeon_btn, paladin, paladin_btn, user_dir = analyze_slides(
+                    slides=["test.svs"],
+                    settings_input=settings_df,
+                    user_dir=mock_dir,
+                )
+
+            # Verify analyze_slide was called (not analyze_slides_batch)
+            mock_analyze_slide.assert_called_once()
+
+            # Verify results
+            assert len(masks) == 1
 
 
     @patch('mosaic.analysis.segment_tissue')
-    def test_single_slide_no_tissue_found(self, mock_segment, mock_slide_path, cancer_subtype_name_map):
+    @patch('mosaic.analysis.gr.Warning')
+    def test_single_slide_no_tissue_found(self, mock_warning, mock_segment, mock_slide_path, cancer_subtype_name_map):
         """Test single-slide analysis when no tissue is found."""
         # No tissue tiles found
-        mock_segment.return_value = (np.array([]), {})
+        mock_segment.return_value = None  # segment_tissue returns None when no tissue
 
         slide_mask, aeon_results, paladin_results = analyze_slide(
             slide_path=mock_slide_path,
@@ -176,6 +184,8 @@ class TestSingleSlideRegression:
         assert slide_mask is None
         assert aeon_results is None
         assert paladin_results is None
+        # Verify warning was raised
+        mock_warning.assert_called_once()
 
     @patch('mosaic.analysis.segment_tissue')
     @patch('mosaic.analysis.draw_slide_mask')
@@ -196,7 +206,10 @@ class TestSingleSlideRegression:
     ):
         """Test that single-slide with known subtype skips Aeon inference."""
         # Setup minimal mocks
-        mock_segment.return_value = (np.array([[0, 0]]), {})
+        mock_polygon = Mock()
+        mock_coords = np.array([[0, 0]])
+        mock_attrs = {}
+        mock_segment.return_value = (mock_polygon, None, mock_coords, mock_attrs)
         mock_mask.return_value = Mock()
         mock_ctranspath.return_value = (np.random.rand(10, 768), np.array([[0, 0]]))
         mock_filter.return_value = (None, np.array([[0, 0]]))
@@ -248,20 +261,21 @@ class TestBackwardCompatibility:
 
     def test_analyze_slide_return_type_unchanged(self):
         """Test that analyze_slide returns the same tuple structure."""
-        with patch('mosaic.analysis.segment_tissue', return_value=(np.array([]), {})):
-            result = analyze_slide(
-                slide_path="test.svs",
-                seg_config="Biopsy",
-                site_type="Primary",
-                sex="Unknown",
-                tissue_site="Unknown",
-                cancer_subtype="Unknown",
-                cancer_subtype_name_map={"Unknown": "Unknown"},
-            )
-
-            # Should return tuple of 3 elements
-            assert isinstance(result, tuple)
-            assert len(result) == 3
+        with patch('mosaic.analysis.segment_tissue', return_value=None):  # No tissue
+            with patch('mosaic.analysis.gr.Warning'):  # Mock the warning
+                result = analyze_slide(
+                    slide_path="test.svs",
+                    seg_config="Biopsy",
+                    site_type="Primary",
+                    sex="Unknown",
+                    tissue_site="Unknown",
+                    cancer_subtype="Unknown",
+                    cancer_subtype_name_map={"Unknown": "Unknown"},
+                )
+
+                # Should return tuple of 3 elements
+                assert isinstance(result, tuple)
+                assert len(result) == 3
 
 
 if __name__ == "__main__":