Fix overflow warnings and improve error handling

- Convert pixel values to int to prevent numpy overflow warnings
- Add defensive programming with .get() for safe dictionary access
- Add debug output to track analysis result structure
- Handle missing keys gracefully in analysis display

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

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

app.py

@@ -48,20 +48,26 @@ class RadarAnalysisApp:
             # Analyze the radar image
             result = self.analyzer.analyze_radar(radar_file, "radar_legend.png")
             
-            # Create analysis summary
+            # Debug: Print what we actually got
+            print("Analysis result keys:", result.keys())
+            print("Analysis keys:", result['analysis'].keys())
+            
+            # Create analysis summary with safe access
+            analysis = result['analysis']
             analysis_text = f"""
             **Radar Analysis Results:**
             
-            - **Precipitation Pixels:** {result['analysis']['precipitation_pixels']:,}
-            - **Total Image Pixels:** {result['analysis']['total_pixels']:,}
-            - **Coverage:** {result['analysis']['precipitation_percentage']:.2f}%
-            - **Regions Found:** {len(result['regions'])}
+            - **Precipitation Pixels:** {analysis.get('precipitation_pixels', 0):,}
+            - **Total Image Pixels:** {analysis.get('total_pixels', 0):,}
+            - **Coverage:** {analysis.get('precipitation_percentage', 0):.2f}%
+            - **Regions Found:** {len(result.get('regions', []))}
             
             **Detected Precipitation Levels:**
             """
             
             # Add intensity breakdown
-            for intensity, count in result['analysis']['intensity_levels'].items():
+            intensity_levels = analysis.get('intensity_levels', analysis.get('pixel_statistics', {}))
+            for intensity, count in intensity_levels.items():
                 if count > 0:
                     analysis_text += f"\n- {intensity}: {count:,} pixels"
             

radar_analyzer.py

@@ -133,7 +133,10 @@ class CanadianRadarAnalyzer:
     
     def color_distance(self, color1: Tuple[int, int, int], color2: Tuple[int, int, int]) -> float:
         """Calculate Euclidean distance between two RGB colors."""
-        return np.sqrt(sum((c1 - c2) ** 2 for c1, c2 in zip(color1, color2)))
+        # Convert to int to prevent overflow
+        c1_int = [int(c) for c in color1]
+        c2_int = [int(c) for c in color2]
+        return np.sqrt(sum((c1 - c2) ** 2 for c1, c2 in zip(c1_int, c2_int)))
     
     def find_precipitation_value(self, rgb_color: Tuple[int, int, int]) -> Optional[ColorRange]:
         """
@@ -177,10 +180,11 @@ class CanadianRadarAnalyzer:
             
         for y in range(height):
             for x in range(width):
-                pixel_rgb = tuple(radar_image[y, x])
+                pixel_rgb = tuple(int(c) for c in radar_image[y, x])
                 
                 # Skip transparent/background pixels
-                if sum(pixel_rgb) < 30:  # Very dark pixels are likely background
+                pixel_sum = sum(pixel_rgb)
+                if pixel_sum < 30:  # Very dark pixels are likely background
                     continue
                     
                 match = self.find_precipitation_value(pixel_rgb)
@@ -244,10 +248,11 @@ class CanadianRadarAnalyzer:
         for y in range(height):
             for x in range(width):
                 if not visited[y, x]:
-                    pixel_rgb = tuple(radar_image[y, x])
+                    pixel_rgb = tuple(int(c) for c in radar_image[y, x])
                     
                     # Skip background pixels
-                    if sum(pixel_rgb) < 30:
+                    pixel_sum = sum(pixel_rgb)
+                    if pixel_sum < 30:
                         visited[y, x] = True
                         continue