fix:优化参数指数

crawler/db_merge.py

@@ -14,6 +14,13 @@ from datetime import datetime
 from pathlib import Path
 from typing import Any, Dict, Optional
 
+from crawler.indicator_smooth import (
+    clamp as _indicator_clamp,
+    smooth_retaliation as _smooth_retaliation,
+    smooth_wall_street as _smooth_wall_street,
+    wall_street_should_append as _wall_street_should_append,
+)
+
 PROJECT_ROOT = Path(__file__).resolve().parent.parent
 DB_PATH = os.environ.get("DB_PATH", str(PROJECT_ROOT / "server" / "data.db"))
 
@@ -26,8 +33,7 @@ MAX_DELTA_PER_MERGE = {
     "civilian_ships": 20, "airport_port": 10,
 }
 
-# 反击情绪 / 华尔街：合理区间，避免爬虫单条提取 0 或 100 导致指标归零或打满
-RETALIATION_SMOOTH_WEIGHT = 0.6  # 当前值权重，1 - 此值为新值权重，使更新平滑
+# 反击情绪 / 华尔街：限幅与平滑见 crawler.indicator_smooth
 RETALIATION_HISTORY_MAX_ROWS = 300  # 反击历史条数上限，供前端曲线与回放使用
 WALL_STREET_TREND_MAX_ROWS = 200  # 趋势表保留最近条数，避免无限增长
 VALUE_CLAMP_MIN, VALUE_CLAMP_MAX = 1, 99  # 0/100 视为异常，写入前夹在 [1,99]
@@ -206,17 +212,13 @@ def merge(extracted: Dict[str, Any], db_path: Optional[str] = None) -> bool:
                             updated = True
                     except Exception:
                         pass
-        # retaliation：平滑更新，避免单条新闻 0/100 导致指标归零或打满
+        # retaliation：由 indicator_smooth 计算平滑值 + 单步变化上限，避免爬虫连续更新导致剧烈波动
         if "retaliation" in extracted:
             r = extracted["retaliation"]
-            raw = max(VALUE_CLAMP_MIN, min(VALUE_CLAMP_MAX, int(r.get("value", 50))))
+            raw = _indicator_clamp(int(r.get("value", 50)))
             row = conn.execute("SELECT value FROM retaliation_current WHERE id = 1").fetchone()
             current = int(row[0]) if row else 50
-            current = max(VALUE_CLAMP_MIN, min(VALUE_CLAMP_MAX, current))
-            new_val = round(
-                RETALIATION_SMOOTH_WEIGHT * current + (1 - RETALIATION_SMOOTH_WEIGHT) * raw
-            )
-            new_val = max(VALUE_CLAMP_MIN, min(VALUE_CLAMP_MAX, new_val))
+            new_val = _smooth_retaliation(raw, current)
             ts = (r.get("time") or datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%S.000Z"))[:25]
             conn.execute("INSERT OR REPLACE INTO retaliation_current (id, value) VALUES (1, ?)", (new_val,))
             conn.execute("INSERT INTO retaliation_history (time, value) VALUES (?, ?)", (ts, new_val))
@@ -227,13 +229,19 @@ def merge(extracted: Dict[str, Any], db_path: Optional[str] = None) -> bool:
                     (n_ret - RETALIATION_HISTORY_MAX_ROWS,),
                 )
             updated = True
-        # wall_street_trend：限幅后写入，并保留最近 N 条避免表无限增长
+        # wall_street_trend：由 indicator_smooth 与上一点平滑 + 最小写入间隔，抑制密集报道导致的锯齿
         if "wall_street" in extracted:
             w = extracted["wall_street"]
             raw = int(w.get("value", 50))
-            val = max(VALUE_CLAMP_MIN, min(VALUE_CLAMP_MAX, raw))
             ts = (w.get("time") or datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%S.000Z"))[:25]
-            conn.execute("INSERT INTO wall_street_trend (time, value) VALUES (?, ?)", (ts, val))
+            last_row = conn.execute(
+                "SELECT time, value FROM wall_street_trend ORDER BY time DESC LIMIT 1"
+            ).fetchone()
+            last_time = last_row[0] if last_row else None
+            last_val = int(last_row[1]) if last_row else None
+            if _wall_street_should_append(last_time, ts):
+                val = _smooth_wall_street(raw, last_val)
+                conn.execute("INSERT INTO wall_street_trend (time, value) VALUES (?, ?)", (ts, val))
             n = conn.execute("SELECT COUNT(*) FROM wall_street_trend").fetchone()[0]
             if n > WALL_STREET_TREND_MAX_ROWS:
                 conn.execute(

crawler/indicator_smooth.py

@@ -0,0 +1,83 @@
+# -*- coding: utf-8 -*-
+"""
+华尔街财团投入指数 & 反击情绪指数：从爬虫实时数据计算稳定指标，抑制单条报道导致的剧烈波动。
+供 db_merge.merge() 调用，写入同一批 DB 表，前端契约不变。
+"""
+from typing import Optional, Tuple
+
+VALUE_CLAMP_MIN = 1
+VALUE_CLAMP_MAX = 99
+
+# 华尔街：与上一点平滑，新点权重
+WALL_STREET_NEW_WEIGHT = 0.35  # raw 权重；1 - 此值 = 上一点权重，越大曲线越平滑
+# 华尔街：两次写入最小间隔（分钟），避免短时间多条报道造成密集锯齿
+WALL_STREET_MIN_INTERVAL_MINUTES = 20
+
+# 反击情绪：当前值权重（1 - 此值 = 新 raw 权重）
+RETALIATION_CURRENT_WEIGHT = 0.8
+# 反击情绪：单次更新相对当前值的最大变化幅度（绝对值）
+RETALIATION_MAX_STEP = 5
+
+
+def clamp(value: int) -> int:
+    return max(VALUE_CLAMP_MIN, min(VALUE_CLAMP_MAX, int(value)))
+
+
+def smooth_wall_street(
+    raw_value: int,
+    last_value: Optional[int],
+    *,
+    new_weight: float = WALL_STREET_NEW_WEIGHT,
+) -> int:
+    """
+    华尔街投入指数：用上一点做平滑，避免单条报道 30/80 导致曲线骤变。
+    若尚无上一点，直接使用限幅后的 raw。
+    """
+    raw = clamp(raw_value)
+    if last_value is None:
+        return raw
+    w = 1.0 - new_weight
+    return clamp(round(w * last_value + new_weight * raw))
+
+
+def wall_street_should_append(
+    last_time_iso: Optional[str],
+    new_time_iso: str,
+    min_interval_minutes: int = WALL_STREET_MIN_INTERVAL_MINUTES,
+) -> bool:
+    """
+    是否应追加一条华尔街趋势点。若与上一条间隔不足 min_interval_minutes 则跳过，
+    减少因爬虫短时间多篇报道导致的密集锯齿。
+    """
+    if not last_time_iso:
+        return True
+    try:
+        from datetime import datetime
+        last = datetime.fromisoformat(last_time_iso.replace("Z", "+00:00"))
+        new = datetime.fromisoformat(new_time_iso.replace("Z", "+00:00"))
+        delta_min = (new - last).total_seconds() / 60
+        return delta_min >= min_interval_minutes
+    except Exception:
+        return True
+
+
+def smooth_retaliation(
+    raw_value: int,
+    current_value: int,
+    *,
+    current_weight: float = RETALIATION_CURRENT_WEIGHT,
+    max_step: int = RETALIATION_MAX_STEP,
+) -> int:
+    """
+    反击情绪指数：先与当前值平滑，再限制单步变化幅度，避免连续多条报道导致快速漂移或抖动。
+    """
+    raw = clamp(raw_value)
+    cur = clamp(current_value)
+    smoothed = round(current_weight * cur + (1.0 - current_weight) * raw)
+    smoothed = clamp(smoothed)
+    # 单步变化上限
+    delta = smoothed - cur
+    if abs(delta) > max_step:
+        step = max_step if delta > 0 else -max_step
+        smoothed = clamp(cur + step)
+    return smoothed