Update scoring_calculation_system.py

scoring_calculation_system.py

@@ -23,6 +23,9 @@ class UserPreferences:
     climate: str  # "cold", "moderate", "hot"
     health_sensitivity: str = "medium"
     barking_acceptance: str = None
+    
+    training_commitment: str = "medium"  # "low", "medium", "high" - 訓練投入程度
+    living_environment: str = "ground_floor"  # "ground_floor", "with_elevator", "walk_up" - 居住環境細節
 
     def __post_init__(self):
         """在初始化後運行，用於設置派生值"""
@@ -426,19 +429,19 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
             # 重新設計基礎分數矩陣，降低普遍分數以增加區別度
             base_scores = {
                 "Small": {
-                    "apartment": 0.85,    # 降低滿分機會
-                    "house_small": 0.80,  # 小型犬不應在大空間得到太高分數
-                    "house_large": 0.75   # 避免小型犬總是得到最高分
+                    "apartment": 0.90,    # 降低滿分機會
+                    "house_small": 0.85,  # 小型犬不應在大空間得到太高分數
+                    "house_large": 0.80   # 避免小型犬總是得到最高分
                 },
                 "Medium": {
-                    "apartment": 0.45,    # 維持對公寓環境的限制
-                    "house_small": 0.75,  # 適中的分數
-                    "house_large": 0.85   # 給予合理的獎勵
+                    "apartment": 0.40,    # 維持對公寓環境的限制
+                    "house_small": 0.80,  # 適中的分數
+                    "house_large": 0.90   # 給予合理的獎勵
                 },
                 "Large": {
-                    "apartment": 0.15,    # 加重對大型犬在公寓的限制
-                    "house_small": 0.65,  # 中等適合度
-                    "house_large": 0.90   # 最適合的環境
+                    "apartment": 0.10,    # 加重對大型犬在公寓的限制
+                    "house_small": 0.60,  # 中等適合度
+                    "house_large": 0.95   # 最適合的環境
                 },
                 "Giant": {
                     "apartment": 0.10,    # 更嚴格的限制
@@ -572,7 +575,7 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
             if exercise_time >= breed_level['ideal']:
                 if exercise_time > breed_level['max']:
                     # 運動時間過長，適度降分
-                    time_score = 0.15 - (0.05 * (exercise_time - breed_level['max']) / 30)
+                    time_score = 0.15 - (0.08 * (exercise_time - breed_level['max']) / 30)
                 else:
                     time_score = 0.15
             elif exercise_time >= breed_level['min']:
@@ -582,7 +585,7 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
             else:
                 # 運動時間不足，根據差距程度扣分
                 time_ratio = max(0, exercise_time / breed_level['min'])
-                time_score = -0.15 * (1 - time_ratio)
+                time_score = -0.20 * (1 - time_ratio)
             
             # 運動類型匹配度評估
             type_score = 0.0
@@ -737,19 +740,19 @@ def calculate_compatibility_score(breed_info: dict, user_prefs: UserPreferences)
             # 基礎分數矩陣 - 大幅擴大不同經驗等級的分數差異
             base_scores = {
                 "High": {
-                    "beginner": 0.10,      # 降低起始分，高難度品種對新手幾乎不推薦
-                    "intermediate": 0.60,   # 中級玩家仍需謹慎
+                    "beginner": 0.15,      # 降低起始分，高難度品種對新手幾乎不推薦
+                    "intermediate": 0.65,   # 中級玩家仍需謹慎
                     "advanced": 1.0        # 資深者能完全勝任
                 },
                 "Moderate": {
-                    "beginner": 0.35,      # 適中難度對新手仍具挑戰
-                    "intermediate": 0.80,   # 中級玩家較適合
-                    "advanced": 1.0        # 資深者完全勝任
+                    "beginner": 0.40,      # 適中難度對新手仍具挑戰
+                    "intermediate": 0.85,   # 中級玩家較適合
+                    "advanced": 0.95        # 資深者完全勝任
                 },
                 "Low": {
-                    "beginner": 0.90,      # 新手友善品種
-                    "intermediate": 0.95,   # 中級玩家幾乎完全勝任
-                    "advanced": 1.0        # 資深者完全勝任
+                    "beginner": 0.85,      # 新手友善品種
+                    "intermediate": 0.90,   # 中級玩家幾乎完全勝任
+                    "advanced": 0.85        # 資深者完全勝任
                 }
             }
             
@@ -1229,12 +1232,20 @@ def calculate_breed_compatibility_score(scores: dict, user_prefs: UserPreference
     }
 
     # 動態調整權重
+    if user_prefs.has_children:
+        if user_prefs.children_age == 'toddler':
+            weights['noise'] *= 1.5     # 幼童對噪音更敏感
+            weights['experience'] *= 1.3 # 需要更有經驗的飼主
+        
     if user_prefs.living_space == 'apartment':
-        weights['space'] *= 1.5
-        weights['noise'] *= 1.3
-    
-    if abs(user_prefs.exercise_time - 120) > 60:  # 運動時間極端情況
-        weights['exercise'] *= 1.4
+        weights['space'] *= 1.4        # 公寓空間限制更重要
+        weights['noise'] *= 1.3        # 噪音問題更重要
+
+    # 運動時間極端情況
+    if user_prefs.exercise_time < 30:
+        weights['exercise'] *= 1.5     # 運動時間極少時加重權重
+    elif user_prefs.exercise_time > 150:
+        weights['exercise'] *= 1.3     # 運動時間充足時略微加重
 
     # 正規化權重
     total_weight = sum(weights.values())
@@ -1252,32 +1263,31 @@ def calculate_breed_compatibility_score(scores: dict, user_prefs: UserPreference
 
 def amplify_score_extreme(score: float) -> float:
     """
-    改進的分數轉換函數
-    提供更大的分數範圍和更明顯的差異
+    改進的分數轉換函數，提供更大的分數區間和更明顯的差異
     
     轉換邏輯：
-    - 極差匹配 (0.0-0.3) -> 60-68%
-    - 較差匹配 (0.3-0.5) -> 68-75%
-    - 中等匹配 (0.5-0.7) -> 75-85%
-    - 良好匹配 (0.7-0.85) -> 85-92%
-    - 優秀匹配 (0.85-1.0) -> 92-95%
+    - 極差匹配 (0.0-0.2) -> 50-60%
+    - 較差匹配 (0.2-0.4) -> 60-70%
+    - 中等匹配 (0.4-0.6) -> 70-82%
+    - 良好匹配 (0.6-0.8) -> 82-90%
+    - 優秀匹配 (0.8-1.0) -> 90-98%
     """
-    if score < 0.3:
-        # 極差匹配：快速線性增長
-        return 0.60 + (score / 0.3) * 0.08
-    elif score < 0.5:
+    if score < 0.2:
+        # 極差匹配：更低的起始分數
+        return 0.50 + (score / 0.2) * 0.10
+    elif score < 0.4:
         # 較差匹配：緩慢增長
-        position = (score - 0.3) / 0.2
-        return 0.68 + position * 0.07
-    elif score < 0.7:
-        # 中等匹配：穩定線性增長
-        position = (score - 0.5) / 0.2
-        return 0.75 + position * 0.10
-    elif score < 0.85:
-        # 良好匹配：加速增長
-        position = (score - 0.7) / 0.15
-        return 0.85 + position * 0.07
+        position = (score - 0.2) / 0.2
+        return 0.60 + position * 0.10
+    elif score < 0.6:
+        # 中等匹配：較大的分數增長
+        position = (score - 0.4) / 0.2
+        return 0.70 + position * 0.12
+    elif score < 0.8:
+        # 良好匹配：快速增長
+        position = (score - 0.6) / 0.2
+        return 0.82 + position * 0.08
     else:
-        # 優秀匹配：最後衝刺
-        position = (score - 0.85) / 0.15
-        return 0.92 + position * 0.03
+        # 優秀匹配：達到更高分數
+        position = (score - 0.8) / 0.2
+        return 0.90 + position * 0.08