Update scoring_calculation_system.py

scoring_calculation_system.py

@@ -1,6 +1,7 @@
 from dataclasses import dataclass
 from breed_health_info import breed_health_info
 from breed_noise_info import breed_noise_info
+import traceback
 
 @dataclass
 class UserPreferences:
@@ -829,14 +830,6 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
             'noise': calculate_noise_score(breed_info.get('Breed', ''), user_prefs.noise_tolerance)
         }
         
-        # 如果有孩童，計算家庭安全分數
-        if user_prefs.has_children:
-            scores['family_safety'] = calculate_family_safety_score(breed_info, user_prefs.children_age)
-        
-        # 計算品種額外加分
-        breed_bonus = calculate_breed_bonus(breed_info, user_prefs)
-        
-        # 調整權重配置
         weights = {
             'space': 0.28,      
             'exercise': 0.18,   
@@ -845,43 +838,60 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
             'health': 0.12,     
             'noise': 0.08      
         }
-        
+
         # 計算基礎加權分數
         weighted_score = sum(score * weights[category] for category, score in scores.items())
-        
-        # 如果有孩童，將 family_safety_score 作為調整因子
+
+        # 如果有孩童，加入家庭安全考量
         if user_prefs.has_children:
-            family_safety = calculate_family_safety_score(breed_info, user_prefs.children_age)
-            
-            # 使用更溫和的安全分數影響
-            # 0.8 是基礎保留率，確保即使最差的安全分數也只會降低 20% 的總分
-            safety_modifier = (family_safety * 0.2) + 0.8
-            
-            # 調整基礎分數
-            weighted_score *= safety_modifier
-        
-        # 加入品種額外加分的影響
-        breed_bonus = calculate_breed_bonus(breed_info, user_prefs)
-        final_weighted_score = weighted_score * (1 + breed_bonus)
-        
-        # 最終分數放大函數也需要調整
+            try:
+                family_safety = calculate_family_safety_score(breed_info, user_prefs.children_age)
+                # family_safety 作為調整因子，而不是新的分數項目
+                # 這裡的 0.4 表示 family_safety 最多可以降低 60% 的分數
+                safety_modifier = (family_safety * 0.6) + 0.4
+                weighted_score *= safety_modifier
+            except Exception as e:
+                print(f"Family safety calculation error: {str(e)}")
+                # 發生錯誤時使用較保守的預設值
+                weighted_score *= 0.7
+
+        # 加入品種加分的影響
+        try:
+            breed_bonus = calculate_breed_bonus(breed_info, user_prefs)
+            # breed_bonus 作為加成效果，但限制其影響範圍
+            bonus_modifier = 1 + (breed_bonus * 0.3)  # 品種加分最多提升 30%
+            weighted_score *= bonus_modifier
+        except Exception as e:
+            print(f"Breed bonus calculation error: {str(e)}")
+
         def amplify_score(score):
-            # 基礎調整，使用更溫和的曲線
-            adjusted = (score - 0.3) * 1.6
+            """
+            優化後的分數放大函數，確保分數範圍合理且結果一致。
+            主要目的是將分數轉換到更容易理解的範圍，並增加差異性。
+            """
+            # 基礎調整 - 降低基準點使差異更明顯
+            adjusted = (score - 0.25) * 1.8
             
-            # 使用較小的指數，避免過度放大差異
-            amplified = pow(adjusted, 2.5) / 4.0 + score
+            # 使用較溫和的指數來放大差異，但不會過度誇大
+            amplified = pow(adjusted, 2.2) / 3.5 + score
             
-            # 更寬鬆的高分處理
+            # 處理高分區間，避免分數過度集中
             if amplified > 0.85:
                 amplified = 0.85 + (amplified - 0.85) * 0.6
             
-            # 擴大分數範圍（0.50-0.95）
-            final_score = max(0.50, min(0.95, amplified))
+            # 確保分數在合理範圍內（0.45-0.95）
+            final_score = max(0.45, min(0.95, amplified))
             
             return round(final_score, 3)
+
+        # 計算最終分數
+        final_score = amplify_score(weighted_score)
+        
+        # 準備回傳結果
+        scores = {k: round(v, 4) for k, v in scores.items()}
+        scores['overall'] = round(final_score, 4)
         
-        final_score = amplify_score(final_weighted_score)
+        return scores
 
     # except Exception as e:
     #     print(f"Error details: {str(e)}")
@@ -890,7 +900,22 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
     #     return {k: 0.5 for k in ['space', 'exercise', 'grooming', 'experience', 'health', 'noise', 'overall']}
 
     except Exception as e:
-        print(f"Error details: {str(e)}")
-        print(f"breed_info: {breed_info}")
-        print(f"Stack trace:", traceback.format_exc())  
-        raise e  
+        print(f"Critical error in compatibility score calculation:")
+        print(f"Error type: {type(e).__name__}")
+        print(f"Error message: {str(e)}")
+        print(f"Breed info: {breed_info}")
+        print(f"User preferences: {user_prefs.__dict__}")
+        
+        # 嘗試返回已計算的分數，若完全失敗則返回預設值
+        try:
+            return scores
+        except:
+            return {
+                'space': 0.7,
+                'exercise': 0.7,
+                'grooming': 0.7,
+                'experience': 0.7,
+                'health': 0.7,
+                'noise': 0.7,
+                'overall': 0.7
+            }