Update scoring_calculation_system.py

scoring_calculation_system.py

@@ -1460,65 +1460,80 @@ def calculate_environmental_fit(breed_info: dict, user_prefs: UserPreferences) -
         
     return min(0.2, adaptability_score)
 
-def calculate_final_weighted_score(scores: dict, user_prefs: UserPreferences, 
-                                 breed_info: dict, adaptability_bonus: float) -> float:
-    """計算最終加權分數"""
+def calculate_final_weighted_score(
+    scores: dict,
+    user_prefs: UserPreferences,
+    breed_info: dict,
+    adaptability_bonus: float
+) -> float:
+    """
+    計算最終加權分數，強化條件變化的影響力
+    """
+    # 基礎權重設定 - 更極端化
     base_weights = {
-        'space': 0.30,      
-        'exercise': 0.25,   
+        'space': 0.30,        # 提高空間權重
+        'exercise': 0.25,     # 提高運動權重
         'grooming': 0.15,
-        'experience': 0.15, 
+        'experience': 0.15,
         'health': 0.10,
-        'noise': 0.05     
+        'noise': 0.05
     }
 
-    # 根據居住環境動態調整權重
+    # 條件特殊化加權
+    special_conditions = 0.0
+    
+    # 1. 極端條件加權
+    if user_prefs.noise_tolerance == 'low':
+        if scores['noise'] < 0.7:  # 對低噪音容忍度更嚴格
+            special_conditions -= 0.15
+    
+    if user_prefs.grooming_commitment == 'high':
+        if breed_info.get('Grooming Needs', '').upper() == 'HIGH':
+            special_conditions += 0.12  # 獎勵高美容需求品種
+    
+    # 2. 專業度差異化
+    if user_prefs.experience_level == 'advanced':
+        if breed_info.get('Care Level', '').upper() == 'HIGH':
+            special_conditions += 0.15  # 資深者配高難度品種加分
+        elif breed_info.get('Care Level', '').upper() == 'LOW':
+            special_conditions -= 0.10  # 資深者配低難度品種扣分
+    
+    # 3. 居住環境極端匹配
     if user_prefs.living_space == 'apartment':
-        base_weights['space'] *= 1.4
-        base_weights['noise'] *= 1.3
-        base_weights['exercise'] *= 0.8
-    elif user_prefs.living_space == 'house_large':
-        base_weights['exercise'] *= 1.3
-        base_weights['space'] *= 0.9
-        base_weights['noise'] *= 0.8
-
-    # 根據經驗等級調整權重
-    if user_prefs.experience_level == 'beginner':
-        base_weights['experience'] *= 1.5
-        base_weights['health'] *= 1.2
-    elif user_prefs.experience_level == 'advanced':
-        base_weights['exercise'] *= 1.2
-        base_weights['experience'] *= 0.8
-
-    if user_prefs.exercise_time > 120:  # 高運動時間
-        base_weights['exercise'] *= 1.5
-        base_weights['space'] *= 1.3
-    elif user_prefs.exercise_time < 45:  # 低運動時間
-        base_weights['exercise'] *= 0.7
-        base_weights['health'] *= 1.2
-
-    # 有孩童時的特殊調整
-    if user_prefs.has_children:
-        base_weights['noise'] *= 1.3
-        base_weights['health'] *= 1.2
-
-    # 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()}
-
-    # 計算基礎加權分數
-    weighted_base = sum(score * weights[category] for category, score in scores.items())
+        if breed_info.get('Size', '') == 'Large':
+            special_conditions -= 0.20  # 大型犬在公寓嚴重扣分
+        elif breed_info.get('Size', '') == 'Small':
+            special_conditions += 0.10  # 小型犬在公寓額外加分
+    
+    # 4. 品種特色加權
+    breed_traits = breed_info.get('Temperament', '').lower()
+    description = breed_info.get('Description', '').lower()
+    
+    if user_prefs.exercise_time > 120:  # 高運動量使用者
+        if 'athletic' in breed_traits or 'energetic' in breed_traits:
+            special_conditions += 0.15
+    elif user_prefs.exercise_time < 45:  # 低運動量使用者
+        if 'calm' in breed_traits or 'lazy' in breed_traits:
+            special_conditions += 0.12
+    
+    # 重新計算加權總分
+    weighted_base = sum(score * base_weights[category] for category, score in scores.items())
     
     # 品種特性加成
     breed_bonus = calculate_breed_bonus(breed_info, user_prefs)
     
-    # 計算最終分數
-    final_score = (weighted_base * 0.75) + (breed_bonus * 0.15) + (adaptability_bonus * 0.10)
+    # 最終分數計算 - 加大特殊條件的影響
+    final_score = (weighted_base * 0.65) + (breed_bonus * 0.15) + 
+                 (adaptability_bonus * 0.10) + (special_conditions * 0.10)
+    
+    # 分數放大，使差異更明顯
+    if final_score > 0.8:
+        final_score = 0.8 + (final_score - 0.8) * 1.5
+    elif final_score < 0.6:
+        final_score = 0.6 - (0.6 - final_score) * 1.5
     
-    # 擴大分數範圍
-    amplified_score = amplify_score_range(final_score)
+    return round(min(0.95, max(0.45, final_score)), 4)
     
-    return round(amplified_score, 4)
 
 def amplify_score_range(score: float) -> float:
     """擴大分數範圍，使差異更明顯"""