feat: 新增热点穿透网状关系图 + 移动端优化

- 新增 /hot-map 热点穿透页：d3-force 力导向网状图展示题材-股票 M:N 关系
  - 股票节点面积/颜色按覆盖题材数分级，穿透核心股高亮
  - 图/核心股列表双视图切换，列表覆盖题材>2 公司降序展示
  - 悬停信息卡、缩放平移、点击跳转股票/题材详情
- 数据采样改为涨幅+热度双榜合并（各 Top50 去重=82 题材），修复覆盖数低估
  （有研新材覆盖数 2→10，核心股 66→1124 家）
- 移动端适配：触屏 tap 选中底部浮层、标签缩放阈值防重叠、自动 fit、紧凑图例
- 主页/题材列表增加热点穿透入口

Co-Authored-By: Claude <noreply@anthropic.com>

backend/routes/themes.py

@@ -25,6 +25,18 @@ async def theme_list(
     )
 
 
+@router.get("/graph", summary="热点穿透：题材-股票网状关系图")
+async def theme_graph(
+    sort_field: int = Query(1, description="题材排序：1=涨幅 4=热度"),
+    top: int = Query(30, ge=1, le=60, description="题材数量"),
+):
+    if sort_field not in (1, 4):
+        raise HTTPException(status_code=400, detail="排序字段仅支持 1(涨幅)/4(热度)")
+
+    result = await themes.fetch_theme_graph(sort_field, top)
+    return JSONResponse(result, headers=_NO_CACHE_HEADERS)
+
+
 @router.get("/{theme_code}/detail", summary="题材详情")
 async def theme_detail(theme_code: str):
     data = await themes.fetch_theme_detail(theme_code)

backend/services/themes.py

@@ -221,3 +221,103 @@ async def fetch_theme_stocks(theme_code: str) -> dict:
         if ttl > 0:
             set_cache(cache_key, json.dumps(result, ensure_ascii=False), ttl_hours=ttl)
     return result
+
+
+# ---- 热点穿透：题材-股票 网状关系图数据 ----
+
+# 合并采样：涨幅榜 Top N + 热度榜 Top N 去重合并，
+# 避免单一榜单导致股票覆盖题材数被低估（如有研新材覆盖 10+ 题材，仅涨幅榜只能采到 2 个）。
+_GRAPH_MERGE_TOP = 50
+
+
+async def fetch_theme_graph(sort_field: int = 1, top_n: int = 30) -> dict:
+    """构建题材-股票网状关系图数据（热点穿透）
+
+    合并采样涨幅榜 + 热度榜 Top N 题材（去重），并发拉取每题材全部股票，
+    统计每股覆盖的题材数（M:N 关系），返回前端可直接渲染的图结构。
+
+    Args:
+        sort_field: 题材排序 1=涨幅, 4=热度（当前榜在前，另一榜合并补充）
+        top_n: 每个榜单的题材数量（1-60）
+
+    Returns:
+        {
+          "themes": [{themeCode, themeName, bf3, hotValue, strengthValue, stockCount}],
+          "stocks": [{securityCode, securityName, coverCount, f3, f2, f62, f100, themeCodes[]}],
+          "edges":  [{themeCode, securityCode}],
+          "stats":  {themeCount, stockCount, coreCount, maxCover}
+        }
+    """
+    cache_key = f"theme_graph:{sort_field}:{top_n}"
+    cached = get_cache(cache_key)
+    if cached is not None:
+        return json.loads(cached)
+
+    # 1. 合并采样涨幅榜 + 热度榜（当前榜优先在前，另一榜补充），按 themeCode 去重
+    primary_list = await fetch_theme_list(sort_field, asc=False)
+    other_field = 4 if sort_field == 1 else 1
+    other_list = await fetch_theme_list(other_field, asc=False)
+    merged: dict[str, dict] = {}
+    for t in primary_list[:top_n]:
+        merged.setdefault(t["themeCode"], t)
+    for t in other_list[:top_n]:
+        merged.setdefault(t["themeCode"], t)
+    themes = list(merged.values())
+    if not themes:
+        return {"themes": [], "stocks": [], "edges": [], "stats": {}}
+
+    # 2. 并发拉取每题材股票（限流保护）
+    sem = asyncio.Semaphore(5)
+
+    async def _fetch_with_limit(code: str):
+        async with sem:
+            return await fetch_theme_stocks(code)
+
+    results = await asyncio.gather(*[_fetch_with_limit(t["themeCode"]) for t in themes])
+
+    # 3. 构建图数据
+    theme_map = {t["themeCode"]: t for t in themes}
+    stock_map: dict[str, dict] = {}  # securityCode -> stock dict
+    edges: list[dict] = []
+
+    for t, res in zip(themes, results):
+        stock_list = res.get("stockList", [])
+        theme_map[t["themeCode"]]["stockCount"] = len(stock_list)
+        for s in stock_list:
+            code = s["securityCode"]
+            edges.append({"themeCode": t["themeCode"], "securityCode": code})
+            if code not in stock_map:
+                stock_map[code] = {
+                    "securityCode": code,
+                    "securityName": s.get("securityName", ""),
+                    "coverCount": 0,
+                    "f3": s.get("f3"),
+                    "f2": s.get("f2"),
+                    "f62": s.get("f62"),
+                    "f100": s.get("f100", ""),
+                    "themeCodes": [],
+                }
+            stock_map[code]["coverCount"] += 1
+            stock_map[code]["themeCodes"].append(t["themeCode"])
+
+    # 4. 排序：覆盖题材数越多（穿透越强）排越前
+    stocks = sorted(stock_map.values(), key=lambda x: (-x["coverCount"], -(x.get("f3") or 0)))
+
+    stats = {
+        "themeCount": len(themes),
+        "stockCount": len(stocks),
+        "coreCount": sum(1 for s in stocks if s["coverCount"] >= 2),
+        "maxCover": max((s["coverCount"] for s in stocks), default=1),
+    }
+
+    result = {
+        "themes": list(theme_map.values()),
+        "stocks": stocks,
+        "edges": edges,
+        "stats": stats,
+    }
+
+    ttl = _dynamic_ttl()
+    if ttl > 0:
+        set_cache(cache_key, json.dumps(result, ensure_ascii=False), ttl_hours=ttl)
+    return result