feat: show ops-map summaries as detailed period tables

Replace paragraph text with day-hit stats (days/days_hit/pct) so leverage and move charts list each hour with counts.

Co-authored-by: Cursor <cursoragent@cursor.com>

packages/domain/aggregate.py

@@ -6,7 +6,7 @@ import math
 from collections import defaultdict
 from typing import Any, Iterable, Sequence
 
-from packages.domain.buckets import shanghai_bucket
+from packages.domain.buckets import shanghai_bucket, shanghai_day
 from packages.domain.leverage import LEVERAGE_FORMULA_VERSION
 
 
@@ -87,9 +87,15 @@ def aggregate_leverage(
     """
     rows: 需含 ts_ms, leverage, side。
     返回按桶排序的聚合列表（含空桶）。
+    额外字段：
+      days — 该时段有样本的上海自然日数
+      days_hit — 当日该时段均值 ≥ min_leverage 的天数
+      pct_days_hit — days_hit / days
     """
     want = (side or "both").upper()
     by_bucket: dict[int, list[float]] = defaultdict(list)
+    # bucket -> day_ymd -> leverages
+    by_bucket_day: dict[int, dict[str, list[float]]] = defaultdict(lambda: defaultdict(list))
 
     for r in rows:
         lev = r.get("leverage")
@@ -106,18 +112,32 @@ def aggregate_leverage(
             continue
         if want == "BOTH" and s not in ("C", "P"):
             continue
-        b = shanghai_bucket(int(r["ts_ms"]), bucket_minutes)
+        ts = int(r["ts_ms"])
+        b = shanghai_bucket(ts, bucket_minutes)
+        day = shanghai_day(ts)
         by_bucket[b].append(lev_f)
+        by_bucket_day[b][day].append(lev_f)
 
     out: list[dict[str, Any]] = []
+    thr = float(min_leverage)
     for b in all_bucket_starts(bucket_minutes):
         stats = summarize_values(by_bucket.get(b, []), min_leverage=min_leverage)
+        day_map = by_bucket_day.get(b, {})
+        days = len(day_map)
+        days_hit = 0
+        for vals in day_map.values():
+            if vals and (sum(vals) / len(vals)) >= thr:
+                days_hit += 1
+        pct_days = (days_hit / days) if days else None
         out.append(
             {
                 "bucket_start_min": b,
                 "bucket_hour": b // 60 if bucket_minutes >= 60 else None,
                 "label": bucket_label(b, bucket_minutes),
                 **stats,
+                "days": days,
+                "days_hit": days_hit,
+                "pct_days_hit": pct_days,
             }
         )
     return out
@@ -156,9 +176,11 @@ def aggregate_move_points(
     """
     samples: {ts_ms, move_signed, move_abs}
     桶内同时给出 signed / abs 分布。
+    额外：days — 该时段有结算样本的自然日数。
     """
     by_signed: dict[int, list[float]] = defaultdict(list)
     by_abs: dict[int, list[float]] = defaultdict(list)
+    by_bucket_days: dict[int, set[str]] = defaultdict(set)
     for s in samples:
         ts = s.get("ts_ms")
         signed = s.get("move_signed")
@@ -174,6 +196,7 @@ def aggregate_move_points(
         b = shanghai_bucket(int(ts), bucket_minutes)
         by_signed[b].append(signed_f)
         by_abs[b].append(abs_f)
+        by_bucket_days[b].add(shanghai_day(int(ts)))
 
     out: list[dict[str, Any]] = []
     for b in all_bucket_starts(bucket_minutes):
@@ -185,6 +208,7 @@ def aggregate_move_points(
                 "bucket_hour": b // 60 if bucket_minutes >= 60 else None,
                 "label": bucket_label(b, bucket_minutes),
                 "n": signed_stats["n"],
+                "days": len(by_bucket_days.get(b, set())),
                 "signed": signed_stats,
                 "abs": abs_stats,
                 # 便捷字段（看板默认用 abs 均值）