Update scoring_calculation_system.py

scoring_calculation_system.py

@@ -929,69 +929,68 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
             'noise': calculate_noise_score(breed_info.get('Breed', ''), user_prefs.noise_tolerance)
         }
         
-        # 基本權重設定
-        weights = {
-            'space': 0.28,      
-            'exercise': 0.18,   
-            'grooming': 0.12,   
-            'experience': 0.22, 
-            'health': 0.12,     
-            'noise': 0.08      
-        }
+         # 2. 計算品種加分
+        breed_bonus = calculate_breed_bonus(breed_info, user_prefs)
 
-        # 如果有孩童，我們需要調整各個分數，而不是增加新的分數項目
+        # 3. 如果有孩童，計算安全分數，但不直接修改基礎分數
         if user_prefs.has_children:
             family_safety = calculate_family_safety_score(breed_info, user_prefs.children_age)
             
-            # 根據孩童年齡設定不同的調整強度
-            age_adjustments = {
-                'toddler': {
-                    'space': (0.5, 0.5),      # (基礎係數, 安全係數權重)
-                    'experience': (0.4, 0.6),  # 幼童需要更嚴格的經驗要求
-                    'exercise': (0.6, 0.4),
-                    'noise': (0.5, 0.5)
-                },
-                'school_age': {
-                    'space': (0.6, 0.4),
-                    'experience': (0.5, 0.5),
-                    'exercise': (0.7, 0.3),
-                    'noise': (0.6, 0.4)
-                },
-                'teenager': {
-                    'space': (0.7, 0.3),
-                    'experience': (0.6, 0.4),
-                    'exercise': (0.8, 0.2),
-                    'noise': (0.7, 0.3)
-                }
+            # 創建安全性調整係數
+            safety_adjustments = {
+                'toddler': 0.6,      # 對幼童最嚴格
+                'school_age': 0.75,   # 學齡兒童較寬鬆
+                'teenager': 0.85      # 青少年最寬鬆
             }
             
-            adjustments = age_adjustments[user_prefs.children_age]
-            
-            # 應用更嚴格的調整
-            for category, (base_coef, safety_weight) in adjustments.items():
-                scores[category] *= (base_coef + (family_safety * safety_weight))
+            # 調整權重而不是直接修改分數
+            safety_weight = safety_adjustments[user_prefs.children_age]
+            
+            # 修改最終加權計算方式
+            weights = {
+                'space': 0.22,      
+                'exercise': 0.15,   
+                'grooming': 0.10,   
+                'experience': 0.18, 
+                'health': 0.10,     
+                'noise': 0.05
+            }
             
-            # 品種加分也需要根據年齡組進行調整
-            breed_bonus_adjustments = {
-                'toddler': 0.4,      # 幼童情況下品種加分影響最小
-                'school_age': 0.6,
-                'teenager': 0.8
+            # 加入安全性權重
+            final_score = (
+                sum(score * weights[category] for category, score in scores.items()) * safety_weight +
+                family_safety * (1 - safety_weight)
+            )
+            
+            # 品種加分也要考慮安全性
+            breed_bonus *= family_safety
+            
+        else:
+            # 原有的權重
+            weights = {
+                'space': 0.28,      
+                'exercise': 0.18,   
+                'grooming': 0.12,   
+                'experience': 0.22, 
+                'health': 0.12,     
+                'noise': 0.08      
             }
-            breed_bonus *= (breed_bonus_adjustments[user_prefs.children_age] * family_safety)
-        
-        weighted_score = sum(score * weights[category] for category, score in scores.items())
-        weighted_score *= (1 + breed_bonus * 0.2)
+            final_score = sum(score * weights[category] for category, score in scores.items())
+
+        # 4. 應用品種加分
+        final_score *= (1 + breed_bonus * 0.2)
 
+        # 5. 最終分數調整
         def amplify_score(score):
             adjusted = (score - 0.25) * 1.8
             amplified = pow(adjusted, 2.2) / 3.5 + score
             if amplified > 0.85:
                 amplified = 0.85 + (amplified - 0.85) * 0.6
-            final_score = max(0.45, min(0.95, amplified))
-            return round(final_score, 3)
+            return max(0.45, min(0.95, amplified))
 
-        final_score = amplify_score(weighted_score)
+        final_score = amplify_score(final_score)
 
+        # 6. 回傳結果
         scores = {k: round(v, 4) for k, v in scores.items()}
         scores['overall'] = round(final_score, 4)