fix: 修复移动端报错

crawler/db_merge.py

@@ -41,7 +41,7 @@ def _ensure_tables(conn: sqlite3.Connection) -> None:
         conn.execute("ALTER TABLE combat_losses ADD COLUMN updated_at TEXT DEFAULT (datetime('now'))")
     except sqlite3.OperationalError:
         pass
-    for col in ("drones", "missiles", "helicopters", "submarines"):
+    for col in ("drones", "missiles", "helicopters", "submarines", "tanks", "civilian_ships", "airport_port"):
         try:
             conn.execute(f"ALTER TABLE combat_losses ADD COLUMN {col} INTEGER NOT NULL DEFAULT 0")
         except sqlite3.OperationalError:
@@ -79,12 +79,12 @@ def merge(extracted: Dict[str, Any], db_path: Optional[str] = None) -> bool:
                     continue
                 try:
                     row = conn.execute(
-                        "SELECT personnel_killed,personnel_wounded,civilian_killed,civilian_wounded,bases_destroyed,bases_damaged,aircraft,warships,armor,vehicles,drones,missiles,helicopters,submarines FROM combat_losses WHERE side = ?",
+                        "SELECT personnel_killed,personnel_wounded,civilian_killed,civilian_wounded,bases_destroyed,bases_damaged,aircraft,warships,armor,vehicles,drones,missiles,helicopters,submarines,tanks,civilian_ships,airport_port FROM combat_losses WHERE side = ?",
                         (side,),
                     ).fetchone()
                     cur = {"personnel_killed": 0, "personnel_wounded": 0, "civilian_killed": 0, "civilian_wounded": 0,
                            "bases_destroyed": 0, "bases_damaged": 0, "aircraft": 0, "warships": 0, "armor": 0, "vehicles": 0,
-                           "drones": 0, "missiles": 0, "helicopters": 0, "submarines": 0}
+                           "drones": 0, "missiles": 0, "helicopters": 0, "submarines": 0, "tanks": 0, "civilian_ships": 0, "airport_port": 0}
                     if row:
                         cur = {
                             "personnel_killed": row[0], "personnel_wounded": row[1], "civilian_killed": row[2] or 0,
@@ -92,6 +92,7 @@ def merge(extracted: Dict[str, Any], db_path: Optional[str] = None) -> bool:
                             "aircraft": row[6], "warships": row[7], "armor": row[8], "vehicles": row[9],
                             "drones": row[10] if len(row) > 10 else 0, "missiles": row[11] if len(row) > 11 else 0,
                             "helicopters": row[12] if len(row) > 12 else 0, "submarines": row[13] if len(row) > 13 else 0,
+                            "tanks": row[14] if len(row) > 14 else 0, "civilian_ships": row[15] if len(row) > 15 else 0, "airport_port": row[16] if len(row) > 16 else 0,
                         }
                     pk = max(0, (cur["personnel_killed"] or 0) + delta.get("personnel_killed", 0))
                     pw = max(0, (cur["personnel_wounded"] or 0) + delta.get("personnel_wounded", 0))
@@ -107,19 +108,22 @@ def merge(extracted: Dict[str, Any], db_path: Optional[str] = None) -> bool:
                     ms = max(0, (cur["missiles"] or 0) + delta.get("missiles", 0))
                     hp = max(0, (cur["helicopters"] or 0) + delta.get("helicopters", 0))
                     sb = max(0, (cur["submarines"] or 0) + delta.get("submarines", 0))
+                    tk = max(0, (cur["tanks"] or 0) + delta.get("tanks", 0))
+                    cs = max(0, (cur["civilian_ships"] or 0) + delta.get("civilian_ships", 0))
+                    ap = max(0, (cur["airport_port"] or 0) + delta.get("airport_port", 0))
                     ts = datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%S.000Z")
                     if row:
                         conn.execute(
                             """UPDATE combat_losses SET personnel_killed=?, personnel_wounded=?, civilian_killed=?, civilian_wounded=?,
                             bases_destroyed=?, bases_damaged=?, aircraft=?, warships=?, armor=?, vehicles=?,
-                            drones=?, missiles=?, helicopters=?, submarines=?, updated_at=? WHERE side=?""",
+                            drones=?, missiles=?, helicopters=?, submarines=?, tanks=?, civilian_ships=?, airport_port=?, updated_at=? WHERE side=?""",
-                            (pk, pw, ck, cw, bd, bm, ac, ws, ar, vh, dr, ms, hp, sb, ts, side),
+                            (pk, pw, ck, cw, bd, bm, ac, ws, ar, vh, dr, ms, hp, sb, tk, cs, ap, ts, side),
                         )
                     else:
                         conn.execute(
                             """INSERT OR REPLACE INTO combat_losses (side, personnel_killed, personnel_wounded, civilian_killed, civilian_wounded,
-                            bases_destroyed, bases_damaged, aircraft, warships, armor, vehicles, drones, missiles, helicopters, submarines, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
+                            bases_destroyed, bases_damaged, aircraft, warships, armor, vehicles, drones, missiles, helicopters, submarines, tanks, civilian_ships, airport_port, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
-                            (side, pk, pw, ck, cw, bd, bm, ac, ws, ar, vh, dr, ms, hp, sb, ts),
+                            (side, pk, pw, ck, cw, bd, bm, ac, ws, ar, vh, dr, ms, hp, sb, tk, cs, ap, ts),
                         )
                     if conn.total_changes > 0:
                         updated = True

crawler/extractor_ai.py

@@ -33,7 +33,8 @@ def _call_ollama_extract(text: str, timeout: int = 10) -> Optional[Dict[str, Any
   us_bases_destroyed, iran_bases_destroyed, us_bases_damaged, iran_bases_damaged.
   重要：bases_* 仅指已确认损毁/受损的基地数量；"军事目标"/targets 等泛指不是基地，若报道只说"X个军事目标遭袭"而无具体基地名，不填写 bases_*
   us_aircraft, iran_aircraft, us_warships, iran_warships, us_armor, iran_armor, us_vehicles, iran_vehicles,
-  us_drones, iran_drones, us_missiles, iran_missiles, us_helicopters, iran_helicopters, us_submarines, iran_submarines
+  us_drones, iran_drones, us_missiles, iran_missiles, us_helicopters, iran_helicopters, us_submarines, iran_submarines,
+  us_tanks, iran_tanks, us_civilian_ships, iran_civilian_ships, us_airport_port, iran_airport_port
 - retaliation_sentiment: 0-100，仅当新闻涉及伊朗报复情绪时
 - wall_street_value: 0-100，仅当新闻涉及美股/市场反应时
 - key_location_updates: 当新闻提及具体基地/地点遭袭时，数组项 { "name_keywords": "asad|阿萨德|assad", "side": "us", "status": "attacked", "damage_level": 1-3 }
@@ -81,7 +82,7 @@ def extract_from_news(text: str, timestamp: Optional[str] = None) -> Dict[str, A
     # combat_losses 增量（仅数字字段）
     loss_us = {}
     loss_ir = {}
-    for k in ["personnel_killed", "personnel_wounded", "civilian_killed", "civilian_wounded", "bases_destroyed", "bases_damaged", "aircraft", "warships", "armor", "vehicles", "drones", "missiles", "helicopters", "submarines"]:
+    for k in ["personnel_killed", "personnel_wounded", "civilian_killed", "civilian_wounded", "bases_destroyed", "bases_damaged", "aircraft", "warships", "armor", "vehicles", "drones", "missiles", "helicopters", "submarines", "tanks", "civilian_ships", "airport_port"]:
         uk = f"us_{k}"
         ik = f"iran_{k}"
         if uk in parsed and isinstance(parsed[uk], (int, float)):

crawler/extractor_dashscope.py

@@ -36,7 +36,8 @@ def _call_dashscope_extract(text: str, timeout: int = 15) -> Optional[Dict[str,
   us_bases_destroyed, iran_bases_destroyed, us_bases_damaged, iran_bases_damaged.
   重要：bases_* 仅指已确认损毁/受损的基地数量；"军事目标"/"targets"等泛指不是基地，若报道只说"X个军事目标遭袭"而无具体基地名，不填写 bases_*
   us_aircraft, iran_aircraft, us_warships, iran_warships, us_armor, iran_armor, us_vehicles, iran_vehicles,
-  us_drones, iran_drones, us_missiles, iran_missiles, us_helicopters, iran_helicopters, us_submarines, iran_submarines
+  us_drones, iran_drones, us_missiles, iran_missiles, us_helicopters, iran_helicopters, us_submarines, iran_submarines,
+  us_tanks, iran_tanks, us_civilian_ships, iran_civilian_ships, us_airport_port, iran_airport_port
 - retaliation_sentiment: 0-100，仅当新闻涉及伊朗报复/反击情绪时
 - wall_street_value: 0-100，仅当新闻涉及美股/市场反应时
 - key_location_updates: 当新闻提及具体基地/设施遭袭时必填，数组 [{{"name_keywords":"阿萨德|asad|assad|阿因","side":"us","status":"attacked","damage_level":1-3}}]。常用关键词：阿萨德|asad|巴格达|baghdad|乌代德|udeid|埃尔比勒|erbil|因吉尔利克|incirlik|德黑兰|tehran|阿巴斯|abbas|布什尔|bushehr|伊斯法罕|isfahan|纳坦兹|natanz
@@ -85,7 +86,7 @@ def extract_from_news(text: str, timestamp: Optional[str] = None) -> Dict[str, A
     loss_ir = {}
     for k in ["personnel_killed", "personnel_wounded", "civilian_killed", "civilian_wounded",
               "bases_destroyed", "bases_damaged", "aircraft", "warships", "armor", "vehicles",
-              "drones", "missiles", "helicopters", "submarines"]:
+              "drones", "missiles", "helicopters", "submarines", "tanks", "civilian_ships", "airport_port"]:
         uk, ik = f"us_{k}", f"iran_{k}"
         if uk in parsed and isinstance(parsed[uk], (int, float)):
             loss_us[k] = max(0, int(parsed[uk]))

crawler/extractor_rules.py

@@ -172,6 +172,34 @@ def extract_from_news(text: str, timestamp: Optional[str] = None) -> Dict[str, A
         else:
             loss_us["submarines"] = v
 
+    # 坦克 tank / 坦克
+    v = _first_int(t, r"(\d+)[\s\w]*(?:tank|坦克)[\s\w]*(?:destroyed|damaged|lost|hit|摧毁|损毁|击毁)")
+    if v is not None:
+        if "iran" in t or "iranian" in t:
+            loss_ir["tanks"] = v
+        else:
+            loss_us["tanks"] = v
+
+    # 民船 civilian ship / 商船 / 民船
+    v = _first_int(t, r"(\d+)[\s\w]*(?:civilian\s*ship|merchant|商船|民船)[\s\w]*(?:sunk|damaged|hit|击沉|受损)")
+    if v is None:
+        v = _first_int(text or t, r"(?:民船|商船|货船)[\s\w]*(\d+)[\s\w]*(?:艘)?[\s\w]*(?:击沉|受损|袭击)")
+    if v is not None:
+        if "iran" in t or "iranian" in t or "伊朗" in (text or ""):
+            loss_ir["civilian_ships"] = v
+        else:
+            loss_us["civilian_ships"] = v
+
+    # 机/港 airport / port / 机场 / 港口
+    v = _first_int(t, r"(\d+)[\s\w]*(?:airport|port|机场|港口)[\s\w]*(?:destroyed|damaged|hit|struck|摧毁|受损|袭击)")
+    if v is None:
+        v = _first_int(text or t, r"(?:机场|港口)[\s\w]*(\d+)[\s\w]*(?:处|个)?[\s\w]*(?:受损|袭击|摧毁)")
+    if v is not None:
+        if "iran" in t or "iranian" in t or "伊朗" in (text or ""):
+            loss_ir["airport_port"] = v
+        else:
+            loss_us["airport_port"] = v
+
     if loss_us:
         out.setdefault("combat_losses_delta", {})["us"] = loss_us
     if loss_ir:

crawler/panel_schema.py

@@ -19,7 +19,7 @@ TimeSeriesPoint = Tuple[str, int]  # (ISO time, value)
 # AI 可从新闻中提取的字段
 EXTRACTABLE_FIELDS = {
     "situation_update": ["summary", "category", "severity", "timestamp"],
-    "combat_losses": ["personnel_killed", "personnel_wounded", "civilian_killed", "civilian_wounded", "bases_destroyed", "bases_damaged", "aircraft", "warships", "armor", "vehicles", "drones", "missiles", "helicopters", "submarines"],
+    "combat_losses": ["personnel_killed", "personnel_wounded", "civilian_killed", "civilian_wounded", "bases_destroyed", "bases_damaged", "aircraft", "warships", "armor", "vehicles", "drones", "missiles", "helicopters", "submarines", "tanks", "civilian_ships", "airport_port"],
     "retaliation": ["value"],  # 0-100
     "wall_street_trend": ["time", "value"],  # 0-100
     "conflict_stats": ["estimated_casualties", "estimated_strike_count"],

docs/CRAWLER_LOGIC.md

@@ -0,0 +1,137 @@
+# 爬虫逻辑梳理与数据校验
+
+## 一、两条入口，数据流不同
+
+### 1. 入口 A：`npm run crawler`（main.py）
+
+- **流程**：RSS 抓取 → 关键词过滤 → 分类/严重度 → **直接写 situation_update** → 通知 API
+- **不经过**：翻译、news_content、AI 提取（战损/基地等）
+- **写入表**：`situation_update`、`situation.updated_at`
+- **用途**：轻量、只给「事件脉络」喂新条目，不更新战损/基地/报复指数
+
+```
+RSS_FEEDS → fetch_all() → KEYWORDS 过滤 → parser_ai.classify_and_severity
+    → write_updates(items) → situation_update INSERT + situation 表 touch
+    → notify_api()
+```
+
+### 2. 入口 B：`npm run gdelt`（realtime_conflict_service.py）
+
+- **流程**：RSS 抓取 → 翻译 → 清洗 → **news_content 去重** → situation_update → **AI 提取 → db_merge** → GDELT 事件（可选）→ 通知 API
+- **写入表**：`news_content`、`situation_update`、`situation`；提取后还有 `combat_losses`、`key_location`、`retaliation_*`、`wall_street_trend` 等
+- **用途**：完整管线，前端「战损 / 军事基地 / 报复 / 美股」等数据都依赖这条
+
+```
+RSS → fetch_all() → translate_to_chinese → cleaner_ai → save_and_dedup → news_content
+    → write_updates(new_items) → situation_update
+    → _extract_and_merge_panel_data(new_items) → extract_from_news() → db_merge.merge()
+    → (可选) fetch_gdelt_events() → gdelt_events, conflict_stats
+    → _notify_node()
+```
+
+**结论**：要检查「抓回的数据是否有效」且包含战损/基地等，应跑 **入口 B**（gdelt 服务）；若只关心事件脉络条数，可看入口 A。
+
+---
+
+## 二、入口 B 逐步拆解（用于逐段校验）
+
+### 2.1 RSS 抓取与过滤
+
+| 步骤 | 位置 | 说明 |
+|------|------|------|
+| 源列表 | `config.RSS_FEEDS` | 多国媒体 RSS，见 config.py |
+| 抓取 | `scrapers.rss_scraper.fetch_all()` | feedparser，单源超时 10s |
+| 过滤 | `_matches_keywords(text)` | 标题+摘要 至少命中 `config.KEYWORDS` 中一个才保留 |
+| 去重 | `(title[:80], link)` | 同一条不重复加入当次列表 |
+| 分类 | `parser_ai.classify_and_severity(text)` | 得到 category、severity（Ollama 或规则） |
+
+**校验**：`npm run crawler:test` 看本次抓到的条数；若为 0，查网络或放宽/检查 KEYWORDS。
+
+### 2.2 翻译与清洗（仅入口 B）
+
+| 步骤 | 位置 | 说明 |
+|------|------|------|
+| 翻译 | `translate_utils.translate_to_chinese()` | 标题/摘要译成中文（依赖配置） |
+| 清洗 | `cleaner_ai.clean_news_for_panel()` | 截断、清理；`ensure_category` / `ensure_severity` 合法化 |
+
+### 2.3 落库：news_content（去重）与 situation_update
+
+| 步骤 | 位置 | 说明 |
+|------|------|------|
+| 去重 | `news_storage.save_and_dedup(items)` | 按 `content_hash(title, summary, url)` 判重，只插入新记录 |
+| 表 | `news_content` | id, content_hash, title, summary, url, source, published_at, category, severity |
+| 表 | `situation_update` | 仅对 **去重后的 new_items** 调用 `write_updates()`，供前端「事件脉络」 |
+
+**校验**：
+
+- `news_content`：`SELECT COUNT(*), MAX(published_at) FROM news_content`
+- `situation_update`：`SELECT COUNT(*), MAX(timestamp) FROM situation_update`
+- 服务状态：`GET http://localhost:8000/crawler/status` 看 `last_fetch_items` / `last_fetch_inserted` / `last_fetch_error`
+
+### 2.4 AI 提取与 db_merge（战损 / 基地 / 报复等）
+
+| 步骤 | 位置 | 说明 |
+|------|------|------|
+| 输入 | `_extract_and_merge_panel_data(new_items)` | 仅处理本次 **新增** 的 new_items，前 limit 条（DashScope 10 条，规则 25 条，Ollama 10 条） |
+| 文本 | 每条 `title + " " + summary`，长度 < 20 跳过 |
+| 提取器选择 | 环境变量 | `DASHSCOPE_API_KEY` → extractor_dashscope；`CLEANER_AI_DISABLED=1` → extractor_rules；否则 extractor_ai（Ollama） |
+| 输出结构 | 见 panel_schema / 各 extractor | `situation_update?`, `combat_losses_delta?`, `retaliation?`, `wall_street?`, `key_location_updates?` |
+| 合并 | `db_merge.merge(extracted)` | 见下表 |
+
+**merge 映射概要**：
+
+| 提取字段 | 写入表/逻辑 |
+|----------|-------------|
+| situation_update | situation_update 表 INSERT（id 为 hash） |
+| combat_losses_delta | combat_losses 表，按 side 增量叠加 |
+| retaliation | retaliation_current 替换 + retaliation_history 追加 |
+| wall_street | wall_street_trend 表 INSERT |
+| key_location_updates | key_location 表 UPDATE status/damage_level（name LIKE 关键词） |
+
+**校验**：
+
+- 战损：`SELECT * FROM combat_losses`
+- 基地：`SELECT id, name, side, status, damage_level FROM key_location WHERE status != 'operational' OR damage_level > 0`
+- 报复：`SELECT * FROM retaliation_current` 与 `retaliation_history` 最近几条
+- 事件脉络：`SELECT id, timestamp, category, summary, severity FROM situation_update ORDER BY timestamp DESC LIMIT 20`
+
+### 2.5 GDELT（可选）
+
+- `GDELT_DISABLED=1` 时跳过 GDELT，仅用 RSS；可用 `_rss_to_gdelt_fallback()` 用 RSS 标题生成 gdelt_events。
+- 未禁用时：`fetch_gdelt_events()` 拉 GDELT → 写 `gdelt_events`、`conflict_stats`。
+
+**校验**：`SELECT COUNT(*), MAX(event_time) FROM gdelt_events`；`SELECT * FROM conflict_stats WHERE id=1`。
+
+---
+
+## 三、如何检查「抓回的数据是否有效」
+
+1. **确认跑的入口**  
+   - 只跑 `npm run crawler`：只有 situation_update 会有新数据，战损/基地不会变。  
+   - 跑 `npm run gdelt` 且服务常驻：才会既有 situation_update，又有 combat_losses、key_location 等。
+
+2. **看 DB 与 API**  
+   - 同上：查 `news_content`、`situation_update`、`combat_losses`、`key_location`、`retaliation_*`、`gdelt_events`、`conflict_stats`。  
+   - 前端数据来源：`GET /api/situation`（见 server/situationData.js），对照上述表即可。
+
+3. **看提取是否触发**  
+   - 若 `combat_losses` / `key_location` 一直不更新：确认是入口 B、有 new_items、提取器未报错；可对单条新闻跑 `extract_from_news(text)` 看是否产出 combat_losses_delta / key_location_updates。
+
+4. **重跑历史提取（补数据）**  
+   - `POST http://localhost:8000/crawler/backfill`：用当前 situation_update 最近 50 条重新做一次提取并 merge，可用来修历史未提取的数据。
+
+---
+
+## 四、配置与环境变量（与数据有效性相关）
+
+| 变量 | 作用 |
+|------|------|
+| DB_PATH | 与 server 共用的 SQLite 路径，必须一致 |
+| API_BASE | 通知 Node 的地址，merge 后通知前端 |
+| DASHSCOPE_API_KEY | 有则用 DashScope 提取；无则用 Ollama 或规则 |
+| CLEANER_AI_DISABLED=1 | 用规则提取（extractor_rules），不用 Ollama |
+| GDELT_DISABLED=1 | 不用 GDELT，仅 RSS；RSS 可转 gdelt_events 占位 |
+| CRAWL_INTERVAL | main.py 抓取间隔（秒） |
+| RSS_INTERVAL_SEC / FETCH_INTERVAL_SEC | realtime 服务里 RSS / GDELT 间隔 |
+
+按上述顺序对照「入口 → RSS → 去重 → situation_update → 提取 → merge → 表」即可逐段检查爬虫抓回的数据是否有效。

server/db.js

@@ -149,6 +149,9 @@ try {
   if (!lossNames.includes('missiles')) db.exec('ALTER TABLE combat_losses ADD COLUMN missiles INTEGER NOT NULL DEFAULT 0')
   if (!lossNames.includes('helicopters')) db.exec('ALTER TABLE combat_losses ADD COLUMN helicopters INTEGER NOT NULL DEFAULT 0')
   if (!lossNames.includes('submarines')) db.exec('ALTER TABLE combat_losses ADD COLUMN submarines INTEGER NOT NULL DEFAULT 0')
+  if (!lossNames.includes('tanks')) db.exec('ALTER TABLE combat_losses ADD COLUMN tanks INTEGER NOT NULL DEFAULT 0')
+  if (!lossNames.includes('civilian_ships')) db.exec('ALTER TABLE combat_losses ADD COLUMN civilian_ships INTEGER NOT NULL DEFAULT 0')
+  if (!lossNames.includes('airport_port')) db.exec('ALTER TABLE combat_losses ADD COLUMN airport_port INTEGER NOT NULL DEFAULT 0')
 } catch (_) {}
 
 // 迁移：所有表添加 updated_at 用于数据回放

server/seed.js

@@ -149,9 +149,9 @@ function seed() {
 
   try {
     db.exec(`
-      INSERT OR REPLACE INTO combat_losses (side, bases_destroyed, bases_damaged, personnel_killed, personnel_wounded, civilian_killed, civilian_wounded, aircraft, warships, armor, vehicles, drones, missiles, helicopters, submarines) VALUES
+      INSERT OR REPLACE INTO combat_losses (side, bases_destroyed, bases_damaged, personnel_killed, personnel_wounded, civilian_killed, civilian_wounded, aircraft, warships, armor, vehicles, drones, missiles, helicopters, submarines, tanks, civilian_ships, airport_port) VALUES
-      ('us', 0, 27, 127, 384, 18, 52, 2, 0, 0, 8, 4, 12, 1, 0),
+      ('us', 0, 27, 127, 384, 18, 52, 2, 0, 0, 8, 4, 12, 1, 0, 0, 0, 0),
-      ('iran', 3, 8, 2847, 5620, 412, 1203, 24, 12, 18, 42, 28, 156, 8, 2);
+      ('iran', 3, 8, 2847, 5620, 412, 1203, 24, 12, 18, 42, 28, 156, 8, 2, 0, 0, 0);
     `)
   } catch (_) {
     db.exec(`

server/situationData.js

@@ -24,6 +24,9 @@ function toLosses(row) {
     missiles: row.missiles ?? 0,
     helicopters: row.helicopters ?? 0,
     submarines: row.submarines ?? 0,
+    tanks: row.tanks ?? 0,
+    civilianShips: row.civilian_ships ?? 0,
+    airportPort: row.airport_port ?? 0,
   }
 }
 
@@ -39,6 +42,9 @@ const defaultLosses = {
   missiles: 0,
   helicopters: 0,
   submarines: 0,
+  tanks: 0,
+  civilianShips: 0,
+  airportPort: 0,
 }
 
 function getSituation() {

src/components/CombatLossesOtherPanel.tsx

@@ -9,6 +9,9 @@ import {
   Rocket,
   Asterisk,
   Amphora,
+  Layers,
+  Sailboat,
+  Warehouse,
 } from 'lucide-react'
 import type { CombatLosses } from '@/data/mockData'
 
@@ -25,6 +28,9 @@ export function CombatLossesOtherPanel({ usLosses, iranLosses, className = '' }:
     { label: '战舰', icon: Ship, iconColor: 'text-blue-500', us: usLosses.warships, ir: iranLosses.warships },
     { label: '装甲', icon: Shield, iconColor: 'text-emerald-500', us: usLosses.armor, ir: iranLosses.armor },
     { label: '车辆', icon: Car, iconColor: 'text-slate-400', us: usLosses.vehicles, ir: iranLosses.vehicles },
+    { label: '坦克', icon: Layers, iconColor: 'text-amber-600', us: usLosses.tanks ?? 0, ir: iranLosses.tanks ?? 0 },
+    { label: '民船', icon: Sailboat, iconColor: 'text-cyan-400', us: usLosses.civilianShips ?? 0, ir: iranLosses.civilianShips ?? 0 },
+    { label: '机/港', icon: Warehouse, iconColor: 'text-orange-400', us: usLosses.airportPort ?? 0, ir: iranLosses.airportPort ?? 0 },
     { label: '无人机', icon: Drone, iconColor: 'text-violet-400', us: usLosses.drones ?? 0, ir: iranLosses.drones ?? 0 },
     { label: '导弹', icon: Rocket, iconColor: 'text-orange-500', us: usLosses.missiles ?? 0, ir: iranLosses.missiles ?? 0 },
     { label: '直升机', icon: Asterisk, iconColor: 'text-teal-400', us: usLosses.helicopters ?? 0, ir: iranLosses.helicopters ?? 0 },

src/components/WarMap.tsx

@@ -127,11 +127,25 @@ function toFeature(loc: KeyLoc, side: 'us' | 'iran', status?: BaseStatus) {
 
 const FLIGHT_DURATION_MS = 2500 // 光点飞行单程时间
 
+/** 移动端/小屏降低动画更新频率以减轻卡顿；返回最小间隔 ms */
+function getAnimIntervalMs(): number {
+  try {
+    if (typeof window === 'undefined') return 33
+    const reducedMotion =
+      window.matchMedia('(prefers-reduced-motion: reduce)').matches
+    if (reducedMotion) return 100 // 约 10fps，兼顾可访问性
+    return window.innerWidth <= 768 ? 50 : 33 // 移动端约 20fps，桌面约 30fps
+  } catch {
+    return 33
+  }
+}
+
 export function WarMap() {
   const mapRef = useRef<MapRef>(null)
   const containerRef = useRef<HTMLDivElement>(null)
   const animRef = useRef<number>(0)
   const startRef = useRef<number>(0)
+  const lastAnimUpdateRef = useRef<number>(0)
   const attackPathsRef = useRef<[number, number][][]>([])
   const lincolnPathsRef = useRef<[number, number][][]>([])
   const fordPathsRef = useRef<[number, number][][]>([])
@@ -293,6 +307,11 @@ export function WarMap() {
 
     const tick = (t: number) => {
       const elapsed = t - startRef.current
+      const intervalMs = getAnimIntervalMs()
+      const shouldUpdate = t - lastAnimUpdateRef.current >= intervalMs
+      if (shouldUpdate) lastAnimUpdateRef.current = t
+
+      if (shouldUpdate) {
         const zoom = map.getZoom()
         const zoomScale = Math.max(0.5, zoom / 4.2) // 随镜头缩放：放大变大、缩小变小（4.2 为默认 zoom）
         try {
@@ -409,6 +428,7 @@ export function WarMap() {
           map.setPaintProperty('gdelt-events-red-pulse', 'circle-opacity', opacity)
         }
         } catch (_) {}
+      }
       animRef.current = requestAnimationFrame(tick)
     }
 

src/data/mockData.ts

@@ -42,6 +42,12 @@ export interface CombatLosses {
   missiles?: number
   helicopters?: number
   submarines?: number
+  /** 坦克 */
+  tanks?: number
+  /** 民船 */
+  civilianShips?: number
+  /** 机/港（机场/港口） */
+  airportPort?: number
 }
 
 export interface SituationUpdate {
@@ -161,6 +167,9 @@ export const INITIAL_MOCK_DATA: MilitarySituation = {
       missiles: 12,
       helicopters: 1,
       submarines: 0,
+      tanks: 0,
+      civilianShips: 0,
+      airportPort: 0,
     },
     wallStreetInvestmentTrend: [
       { time: '2025-03-01T00:00:00', value: 82 },
@@ -215,6 +224,9 @@ export const INITIAL_MOCK_DATA: MilitarySituation = {
       missiles: 156,
       helicopters: 8,
       submarines: 2,
+      tanks: 0,
+      civilianShips: 0,
+      airportPort: 0,
     },
     retaliationSentiment: 78,
     retaliationSentimentHistory: [

src/hooks/useReplaySituation.ts

@@ -80,6 +80,9 @@ export function useReplaySituation(): MilitarySituation {
       missiles: lerp(0, usLoss.missiles ?? 0),
       helicopters: lerp(0, usLoss.helicopters ?? 0),
       submarines: lerp(0, usLoss.submarines ?? 0),
+      tanks: lerp(0, usLoss.tanks ?? 0),
+      civilianShips: lerp(0, usLoss.civilianShips ?? 0),
+      airportPort: lerp(0, usLoss.airportPort ?? 0),
     }
     const irLossesAt = {
       bases: {
@@ -99,6 +102,9 @@ export function useReplaySituation(): MilitarySituation {
       missiles: lerp(0, irLoss.missiles ?? 0),
       helicopters: lerp(0, irLoss.helicopters ?? 0),
       submarines: lerp(0, irLoss.submarines ?? 0),
+      tanks: lerp(0, irLoss.tanks ?? 0),
+      civilianShips: lerp(0, irLoss.civilianShips ?? 0),
+      airportPort: lerp(0, irLoss.airportPort ?? 0),
     }
 
     // 被袭基地：按 damage_level 排序，高损毁先出现；根据 progress 决定显示哪些为 attacked