Update scoring_calculation_system.py

scoring_calculation_system.py

@@ -1377,49 +1377,83 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
             'health': health_score,
             'noise': noise_score
         }
-        print("\n=== 所有基礎分數 ===")
-        for category, score in scores.items():
-            print(f"{category}: {score}")
-
-        # 計算加權分數
-        weights = {
-            'space': 0.28,      
-            'exercise': 0.18,   
-            'grooming': 0.12,   
-            'experience': 0.22, 
-            'health': 0.12,     
-            'noise': 0.08      
-        }
-        
-        weighted_score = sum(score * weights[category] for category, score in scores.items())
-        print(f"\n加權前總分: {weighted_score}")
-
-        # 分數放大
-        def amplify_score(score):
-            print(f"\n開始分數放大，原始分數: {score}")
-            adjusted = (score - 0.35) * 1.8
-            print(f"調整後分數 (adjusted): {adjusted}")
+
+        # 首先處理極端情況
+        def check_critical_issues(scores: dict, breed_info: dict) -> float:
+            """
+            檢查關鍵問題並計算懲罰係數
+            """
+            penalty = 1.0
+            
+            # 檢查經驗分數 - 如果太低表示品種太難駕馭
+            if scores['experience'] < 0.3:
+                penalty *= 0.8
+            
+            # 檢查空間分數 - 特別是對公寓的情況
+            if user_prefs.living_space == 'apartment' and scores['space'] < 0.4:
+                penalty *= 0.85
+            
+            # 檢查健康分數 - 健康問題是重要考量
+            if scores['health'] < 0.4:
+                penalty *= 0.9
+                
+            return penalty
+
+        # 計算權重和加權分數
+        def calculate_weighted_score(scores: dict) -> float:
+            """
+            使用動態權重計算加權分數
+            """
+            base_weights = {
+                'space': 0.28,      
+                'exercise': 0.18,   
+                'grooming': 0.12,   
+                'experience': 0.22, 
+                'health': 0.12,     
+                'noise': 0.08      
+            }
+            
+            # 根據居住環境調整權重
+            if user_prefs.living_space == 'apartment':
+                base_weights['space'] *= 1.2
+                base_weights['noise'] *= 1.2
+            
+            # 根據經驗等級調整權重
+            if user_prefs.experience_level == 'beginner':
+                base_weights['experience'] *= 1.3
+            
+            # 重新正規化權重
+            total_weight = sum(base_weights.values())
+            weights = {k: v/total_weight for k, v in base_weights.items()}
+            
+            # 計算加權分數
+            return sum(score * weights[category] for category, score in scores.items())
+
+        # 計算最終分數
+        def calculate_final_score(base_score: float, penalty: float) -> float:
+            """
+            計算並調整最終分數，確保合理的分數分布
+            """
+            # 應用懲罰係數
+            adjusted_score = base_score * penalty
             
-            amplified = pow(adjusted, 3.2) / 5.8 + score
-            print(f"放大後分數 (amplified): {amplified}")
+            # 將分數映射到期望的範圍（0.55-0.95）
+            mapped_score = 0.55 + (adjusted_score * 0.4)
             
-            if amplified > 0.90:
-                amplified = 0.90 + (amplified - 0.90) * 0.5
+            # 確保分數在合理範圍內
+            final = max(0.55, min(0.95, mapped_score))
             
-            final = max(0.55, min(0.95, amplified))
-            print(f"最終分數: {final}")
-            return round(final, 3)
+            return round(final, 4)
 
-        final_score = amplify_score(weighted_score)
-        print(f"\n=== 最終計算結果 ===")
-        print(f"最終分數: {final_score}")
+        # 執行計算流程
+        penalty = check_critical_issues(scores, breed_info)
+        weighted_score = calculate_weighted_score(scores)
+        final_score = calculate_final_score(weighted_score, penalty)
 
         # 準備返回結果
         scores = {k: round(v, 4) for k, v in scores.items()}
-        scores['overall'] = round(final_score, 4)
+        scores['overall'] = final_score
         
-        print("\n=== 返回結果 ===")
-        print(scores)
         return scores
 
     except Exception as e:
@@ -1428,5 +1462,4 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
         print(f"錯誤訊息: {str(e)}")
         print(f"完整錯誤追蹤:")
         print(traceback.format_exc())
-        print("\n返回默認值...")
         return {k: 0.6 for k in ['space', 'exercise', 'grooming', 'experience', 'health', 'noise', 'overall']}