完成模型更新

core/scoring/features/v3_4_features.py

@@ -1,9 +1,10 @@
 """
-扩展特征 v3.4 (16维)
+扩展特征 v3.4 + v6.7新增 (20维: 16维 v3.4 + 4维 v6.7新增)
 """
 import numpy as np
 import pandas as pd
 from core.scoring.features.v3_2_features import _ols_slope
+from core.scoring.features.v3_3_features import _grid_touch_count
 from core.scoring.config import GRID_LOW, GRID_HIGH
 
 
@@ -104,6 +105,29 @@ def calculate_features_v3_4(ctx) -> pd.DataFrame:
         feat['wick_ratio_20d'] = np.mean(
             wick_len / np.where(total_len > 0, total_len, 1)) * 100
 
+        # ── v6.7 新增 4 维特征 ──────────────────────────────
+        # 53. vol_decay_5d: 近5日波动率 / 近20日波动率 (波动率用对数收益std)
+        log_ret = np.diff(np.log(np.maximum(closes, 1e-10)))
+        vol_5d = np.std(log_ret[-5:], ddof=1) if len(log_ret) >= 5 else 0
+        vol_20d = np.std(log_ret[-20:], ddof=1) if len(log_ret) >= 20 else vol_5d
+        feat['vol_decay_5d'] = float(vol_5d / vol_20d) if vol_20d > 0 else 0.0
+
+        # 54. grid_touch_relative_10d: 10日振幅比 / 60日振幅比
+        range_10d = float(np.max(highs[-10:]) - np.min(lows[-10:]))
+        range_60d = float(np.max(highs[-60:]) - np.min(lows[-60:])) if len(highs) >= 60 else range_10d
+        close_now = float(closes[-1])
+        close_60d_mean = float(np.mean(closes[-60:])) if len(closes) >= 60 else close_now
+        if close_now > 0 and close_60d_mean > 0 and range_60d > 0:
+            feat['grid_touch_relative_10d'] = (range_10d / close_now) / (range_60d / close_60d_mean)
+        else:
+            feat['grid_touch_relative_10d'] = 0.0
+
+        # 55. vol_decay_x_grid_balance: vol_decay × 网格均衡度
+        feat['vol_decay_x_grid_balance'] = feat['vol_decay_5d'] * feat.get('grid_room_balance', 0.0)
+
+        # 56. vol_decay_x_dist_lower: vol_decay × 下轨距离
+        feat['vol_decay_x_dist_lower'] = feat['vol_decay_5d'] * feat.get('dist_to_grid_lower', 0.0)
+
         features[code] = feat
 
     return pd.DataFrame.from_dict(features, orient='index')