From 7ad86c66198d07dadcbf7f4c6e30a611677247d1 Mon Sep 17 00:00:00 2001 From: tamakyi Date: Fri, 6 Nov 2026 02:05:24 +0800 Subject: [PATCH] =?UTF-8?q?=E5=BD=92=E5=B1=9E=E5=88=A4=E5=AE=9A=E5=8D=87?= =?UTF-8?q?=E7=BA=A7=EF=BC=9ADataV=20=E5=AE=98=E6=96=B9=E8=A1=8C=E6=94=BF?= =?UTF-8?q?=E5=8C=BA=E5=88=92=E8=A1=A8=20+=20=E5=90=8C=E5=90=8D=E5=8E=BF?= =?UTF-8?q?=E6=B6=88=E6=AD=A7?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 用阿里 DataV GeoAtlas（免密钥）替换 OSM Overpass 离线县表： - 民政部 adcode 体系，县级前 4 位即所属地级码，2832 县 100% 可定位地级 （OSM 表只有 1182/2362，且 admin_level 层级不可靠） - 同名县（全国 30 组）保留全部候选，运行时按坐标消歧， 修掉「柳州的城中区被归到西宁市」 归属判定改为「按名字精确查官方表」优先于「按中心点猜最近的县」： 窄长县按中心点会跨省错判（环江喀斯特实际在环江县，按中心点判到荔波县） 查表带距离校验，精确全称命中放宽到 150km（狭长县中心离边界可达 85km+） 修掉三个真实缺陷： - Overpass 兜底把地级塞进 osmCounty、县名塞进 osmCity， 与 attachPlaces「先找县级」的顺序相反，导致兜底路径永远丢下层县名 - Overpass 请求无硬超时，公共实例「连着不返回」能把一次分析拖成十几分钟； 补三层限（单次超时 / 阶段总时限 / is_in 反查次数上限），13 分钟 → 48 秒 - Photon 的 osm.place.city 类目混着景点 POI，kind==='城市' 时无条件把名字 当地名，导致「社更穿洞北门」「柳州之门」等景点自己成一组； 改为必须同时是行政区名且能在官方表查到 新增离线回归测试（都不打外部网络，Photon/Overpass 挂掉也能回归）： - test-admin-lookup：同名县消歧、已知边界点、狭长县远端点（19 项） - test-overpass-fallback：本地假 Overpass，验兜底路径、简称归一、200+HTML 错误页 - test-grouping-regression：本地假 Photon，20 候选完整分组 - verify-ui-full：端到端 UI 验收（真实无头 Chrome 读真实 DOM） --- README.md | 99 +++- config.js | 20 +- lib/analyze.js | 2 + lib/places-admin-dv.js | 18 + lib/places-admin.js | 18 + lib/sources.js | 702 ++++++++++++++++++++++++++++- preview/preview-step2-full.png | Bin 0 -> 280108 bytes preview/preview-step2-groups.png | Bin 0 -> 212089 bytes preview/preview-step2-real.png | Bin 0 -> 241869 bytes public/app.js | 140 +++++- public/index.html | 10 +- public/styles.css | 61 +++ tools/build-admin-dv.cjs | 156 +++++++ tools/build-admin-fix.cjs | 137 ++++++ tools/build-admin-normalize.cjs | 96 ++++ tools/build-admin.cjs | 125 +++++ tools/dbg-grouping.cjs | 113 +++++ tools/fetch-datav-admin.cjs | 117 +++++ tools/lib-short-name.cjs | 39 ++ tools/test-admin-lookup.cjs | 86 ++++ tools/test-grouping-regression.cjs | 160 +++++++ tools/test-overpass-fallback.cjs | 139 ++++++ tools/verify-step2-real.cjs | 138 ++++++ tools/verify-step2.cjs | 178 ++++++++ tools/verify-ui-full.cjs | 225 +++++++++ 25 files changed, 2766 insertions(+), 13 deletions(-) create mode 100644 lib/places-admin-dv.js create mode 100644 lib/places-admin.js create mode 100644 preview/preview-step2-full.png create mode 100644 preview/preview-step2-groups.png create mode 100644 preview/preview-step2-real.png create mode 100644 tools/build-admin-dv.cjs create mode 100644 tools/build-admin-fix.cjs create mode 100644 tools/build-admin-normalize.cjs create mode 100644 tools/build-admin.cjs create mode 100644 tools/dbg-grouping.cjs create mode 100644 tools/fetch-datav-admin.cjs create mode 100644 tools/lib-short-name.cjs create mode 100644 tools/test-admin-lookup.cjs create mode 100644 tools/test-grouping-regression.cjs create mode 100644 tools/test-overpass-fallback.cjs create mode 100644 tools/verify-step2-real.cjs create mode 100644 tools/verify-step2.cjs create mode 100644 tools/verify-ui-full.cjs diff --git a/README.md b/README.md index 37c82d4..473013b 100644 --- a/README.md +++ b/README.md @@ -35,7 +35,7 @@ node server.js # 或 npm start | 步骤 | 用户操作 | 系统行为 | | --- | --- | --- | | ① 出行条件 | 输入地名联想 / 浏览器定位、选日期区间、单程时长上限、搜索半径、是否排除同城、交通与兴趣偏好 | 地理编码 → 检索周边候选 → 批量取天气与 AQI → 公路矩阵 + 铁路可达性 → 评分排序 | -| ② 备选清单 | 查看方位罗盘、评分环、逐日天气、推荐理由、数据来源说明；勾选目的地 | 默认预选 Top 3 并给出提示；支持按评分/天气/距离/单程时长排序；可「只看小众」、可「对比已选」并排看关键指标 | +| ② 备选清单 | 查看方位罗盘、评分环、逐日天气、推荐理由、数据来源说明；按地名分组浏览、搜索目的地；勾选目的地 | 默认预选 Top 3 并给出提示；支持按评分/天气/距离/单程时长排序；按「地名 → 景点」两级分组；可搜索、可「只看小众」、可「对比已选」并排看关键指标 | | ③ 行程规划 | 填写具体需求（同行人、预算、体力、禁忌等），点击生成；生成后可继续提要求迭代 | 清单数据 + 需求 + 本站预设提示词 → OpenAI 兼容接口流式输出 Markdown 方案 | 页面右上角「设置」分两块：**AI 接口**（地址、密钥、模型，含常用供应商预设、预设提示词查看/复制、强制演示模式）与 **数据源增强**（高德 Web 服务 Key）。两者都只存在浏览器 `localStorage`，随请求传给本地服务代理。 @@ -109,6 +109,100 @@ node server.js # 或 npm start - Photon 分类检索用 `bbox + 分类` 作为稳定缓存键（公共实例限流，重复分析必须复用缓存）。 - 候选上限 28 个，按「类型轮转取样」抽取，保证小众点位不会被热门点位挤掉。 +### 归属地名与分组 + +第二步把候选按「**地名 → 景点**」两级展示，所以每个候选都要先解析出它属于哪个地名。 + +| 来源 | 地名来源 | 层级 | +| --- | --- | --- | +| 内置城市库 | 名字本身就是地名（柳州市） | 地级 | +| 高德 POI | `cityname`（地级市）+ `adname`（区县） | 地级 + 区县 | +| 内置知名 / 小众库 | 离线归属表 `lib/places-admin.js` | 地级 + 区县 | +| Photon / Overpass (OSM) | **按 OSM 自带的县名字段查官方表** `lib/places-admin-dv.js` | 地级 + 区县 | +| 以上都拿不到 | 按坐标找最近的县 → 推出地级（官方县表，≤60km） | 地级 + 区县 | + +铁律： + +- **组名必须落在地级**（市 / 州 / 盟 / 地区）。用街道名或村名当组名等于没分组——同一个县下面的几十个点会被拆成几十组。 +- **Photon 的 `osm.place.city` 类目里混着景点 POI**（牌坊、寺庙、老街），它们的名字也带「市 / 州」后缀。不能因为 `kind === '城市'` 就把名字当地名——会出现「社更穿洞北门」自己成一组这种荒唐结果。必须同时满足「名字是行政区名」且「能在官方地级表里查到」才当地名节点，否则走正常归属流程。 +- **OSM 中国的字段层级与直觉相反**：`county` 是地级市/州，`city` 是县/区，`district` 是街道，`locality` 是村。 +- **优先按名字精确查官方表，别靠「按坐标猜最近的县」**。窄长县按中心点距离会判到隔壁省去：「环江喀斯特世界自然遗产」实际在环江县（河池市），按中心点却会判到 45km 外的荔波县（黔南州）——差一级省。而 OSM 的 `addr:county` 在多数条目上直接写了标准县名（`环江毛南族自治县`），按名字查是准的。 + - 查表**必须带距离校验**：同名县离候选点太远（>80km）就判为不可信，退回按坐标近邻。 + - 查表顺序：先在 `county` / `city` / `district` 三个字段里找**县级**（拿到下层地名），都找不到再退地级。OSM 常常把地级填进 `county`、县名填进 `city`（「黔南州」+「荔波县」），只看第一个字段就定案会丢掉下层地名。 +- **不要信 OSM 自己填的归属字段的层级**。Photon 的 `city` 字段会给出「乐依村」「陈家甫」这种村名当区县——所以查到的东西必须经 `isDistrictName()`（县/区/旗/盟/州/市）过滤，村名一律丢弃。 +- **OSM 的 `admin_level` 在中国是 L4=省 / L5=地级市 / L6=县**，不是 L4/L6/L8。查 `admin_level~"^[468]$"` 会正好跳过地级市那层。 +- 分组键会剥掉行政后缀（「柳州」与「柳州市」归一组），民族自治州要连民族名一起去掉（「黔南布依族苗族自治州」→「黔南州」）。 +- 高德 `regeo` 的**批量查询不可用**（`batch=true` + `locations`，无论分隔符与参数顺序都返回 `INVALID_PARAMS`），必须逐点反查；并发 3 会触发限流，失败的候选会退回街道名当组名，因此用**串行 + 60ms 间隔**。 + +#### 离线行政区划表（阿里 DataV GeoAtlas） + +| 表 | 条数 | 作用 | +| --- | --- | --- | +| `lib/places-admin.js` | 323 | 内置知名 / 小众地点的归属（地级 + 区县） | +| `lib/places-admin-dv.js` | 2832 县 / 343 地级 | **官方行政区划表**：按名字查县/地级，运行时归属判定的主力 | + +数据来自[阿里 DataV GeoAtlas](https://datav.aliyun.com/portal/school/atlas/area_selector)（免密钥、免鉴权），用的是国家民政部 **adcode** 体系：省级 2 位 / 地级 4 位 / 县级 6 位，**县级前 4 位即所属地级码**（451226 环江县 → 4512 河池市）——归属关系是**编码里写死的**，不需要推断。 + +```bash +# 1) 拉原始数据（三级下钻：省 → 地级市 → 县），输出到 C:/tmp/datav-admin.json +node tools/fetch-datav-admin.cjs +# 2) 生成运行时表 +node tools/build-admin-dv.cjs C:/tmp/datav-admin.json +``` + +> 早期版本用的是 Overpass 拉的 OSM 县表（`lib/places-county.js` / `lib/places-prefecture.js`），**已废弃**：OSM 中国的 `admin_level` 层级不可靠、编码只有约 50% 覆盖（1182/2362 个县查不到所属地级），且公共 Overpass 实例限流极狠（大查询后连 1KB 的小查询都 502/504）。DataV 版 2832 个县**全部**能定位到所属地级。 + +几个必须记住的坑： + +- **同名县要保留全部候选**。全国有 **30 组**同名县（「城中区」柳州/西宁都有、「鼓楼区」南京/徐州/福州/开封都有、「铁西区」沈阳/鞍山/四平都有、「市中区」济南/枣庄/内江/乐山都有）。用县名做单一字典键会互相覆盖——柳州的「城中区」会被归到西宁市。所以表里同名县的值是**数组**，运行时按坐标距离选最近的那个。 +- **省直辖县级单位不是地级市**。DataV 把海南的东方市/昌江黎族自治县、新疆兵团的石河子市、湖北的仙桃市等标成 `level=city`，靠 **adcode 是否以 `00` 结尾**区分（真地级市是 xx00，省直辖县级是 9xxx 段）。不按这个分，归属会整整差一级。 +- **剥民族名要用显式清单**，不能用 `[一-龥]{1,3}族` 这种贪婪正则——「环江毛南族自治县」会被吃成「环自治县」。而且顺序很重要：先剥「自治县/州」尾巴，民族名块才会露在末尾。 +- **别名表要县/地分开**（`COUNTY_ALIAS` → 县全称，`PREF_ALIAS` → 地级简称）。混在一张表里会因为「同名县/市」互相覆盖而查错。 + +#### 兜底路径：Photon 全挂时走 Overpass + +| 步骤 | 实现 | 说明 | +| --- | --- | --- | +| 1. 取候选 | `overpassQuery()` | 按 `OVERPASS_TAGS` 逐类查 OSM 原始标签 | +| 2. 取行政区 | `overpassAdminAreas()` | `out center tags` 取 bbox 内 L5/L6 行政区的**中心点** | +| 3. 判归属 | `areaByPoint()` | 按中心点做近邻判定 | +| 4. 精确反查 | `overpassAdminAtPoint()` | 近邻判定拿不到时逐点用 `is_in` 反查 | +| 5. 归一 | `lookupAdminByName()` | OSM 的简称/全称统一过官方表，同名县按距离消歧 | + +关键事实： + +- **relation 级 geometry 在 Overpass 里拿不到**。`out tags geom` 和 `out geom` 都不返回 relation 级的 `geometry` 数组（几何在 `members` 里）。所以不要走「拉多边形 + 本地点面判定」这条路。 +- **`is_in` 反查一次就能拿到完整层级**：`[out:json];is_in(lat,lon)->.a;.a out tags;` 返回 L4 省 / L5 地级 / L6 县（实测 25.1,107.98 → 环江县 / 河池市 / 广西）。注意 `rel(pivot.a)` 拿不到点→区映射，要直接输出 area 集合。 +- **公共实例必须多镜像轮换**，且要判定响应体是否真是 JSON：实例可能返回 **200 + HTML 错误页**（如 `duplicate_query`），只看 `res.status` 会把错误页当成功。判据是响应体是否以 `{` 开头。 +- **必须有硬超时和总时限预算**。公共实例经常「连着不返回」（不报错也不结束），没有 `AbortSignal.timeout` 的话一次兜底能把分析流程拖成十几分钟（实测踩过）。三处都要限： + - 单次请求超时（`SEARCH.overpassTimeoutMs`，默认 20s）； + - 单个阶段的总时限（镜像轮询不超过 2 倍超时）； + - 逐点 `is_in` 反查的次数上限（`SEARCH.overpassIsInMax`，默认 8）——这是最慢的一环，超限后改用 bbox 行政区中心点近邻判定。 + - 超时后**候选照常入池**（归属还有离线官方表兜底），不能因为反查超时就丢掉整个候选。 +- Overpass 的兴趣点大多**没有 `addr:*` 标签**，直接拿归属必然得到空组名——必须靠 `is_in` 反查。 + +#### 离线回归测试 + +归属逻辑不能只靠真实网络验证——Photon / Overpass 随时会挂，挂了就没法回归。仓库里有三个**不发外部请求**的离线测试： + +```bash +node tools/test-admin-lookup.cjs # 归属判定单测：同名县消歧、已知边界点、狭长县远端点 +node tools/test-overpass-fallback.cjs # 起本地假 Overpass：验兜底路径、简称归一、200+HTML 错误页 +node tools/test-grouping-regression.cjs # 起本地假 Photon：20 个候选的完整分组回归 +``` + +另有端到端 UI 验收（起假 Photon + 真实无头 Chrome，读真实 DOM）： + +```bash +node tools/verify-ui-full.cjs # 分组 / undefined / 空组名 / 搜索 / 折叠 + 截图 +``` + +写这类测试时注意：**`cfg.SEARCH.maxCandidates` 缺省会静默返回 0 候选**（`selected.length < undefined` 恒假）；**第二轮跑要清 `require.cache` 或换 origin**，否则命中第一轮缓存。 + +拉取时的坑：一次拉全国必然 502（5 个镜像全挂），必须按 10°×15° 分块；用 `out center` 而不是 `out geom`（几何版体积大十几倍，更容易超时）。境外行政区会混进同一层级数据，靠**有无 `division_code` 或 `name` 本身是中文**来剔除。 + +县级表第三项是**所属地级名**，由 GB/T 2260 编码前缀推出（县级码前 4 位即地级码：荔波县 `522722` → `5223` 黔南州）。这比「按距离找最近地级」精确得多——桂黔边境荔波县与河池市相距不到 40km，按中心点距离会分错。 + ### 评分口径 总分 0~100，由六项加权相加：天气舒适度 `0~40`、时间适配 `0~26`、兴趣匹配 `0~14`、距离 `0~7`、目的地辨识度 `0~8`、空气质量 `0~6`。整段行程都是坏天气时会触发硬门槛，不允许给出「强烈推荐」。每张卡片都带 `breakdown`、`reasons`、`warnings`，可解释。 @@ -138,6 +232,9 @@ node server.js # 或 npm start | BigDataCloud / Photon Reverse | 浏览器定位后的反向地理编码 | 免 | 提示手动输入地名 | | 内置 `lib/places-cn.js` | 全国知名景区 + 主要城市坐标库 | — | 始终参与，保证任何城市都有可用清单 | | 内置 `lib/places-niche.js` | 206 条小众地点：古村、遗址、湿地、地质景观、洞穴、小馆、徒步线 | — | 始终参与，并保证约 30% 的候选名额 | +| 内置 `lib/places-admin.js` | 内置地点的归属地名（323 条，离线生成） | — | 始终参与；缺失时按坐标回退到最近地级市 | +| 内置 `lib/places-admin-dv.js` | 官方行政区划表：2832 县 / 343 地级（DataV GeoAtlas，离线生成） | — | 始终参与；同名县按坐标消歧，查不到时退到按坐标近邻 | +| Overpass (OpenStreetMap) | Photon 全挂时的候选兜底（免密钥），多镜像轮换 | 免 | 跳过并注明「实时检索不可用」；实例返回 200 但内容是 HTML 错误页时同样判为失败 | | 高德 Web 服务 `geocode/geo` / `place/text` / `place/around`（含 `types=100000` 住宿）/ `direction/driving` / `staticmap`（路线图真实底图） | 中文地名检索、实时周边 POI、周边住宿参考、国内驾车路径、地图图层 | `AMAP_KEY` 或页面「设置 → 数据源增强」 | 静默跳过并退回 Open-Meteo / OSRM / 内置库 / 方位示意图；Key 无效会在页面顶部或设置里直接报错 | | RollingGo `rgh` CLI（本机安装） | 酒店实时参考价、星级、距离、可预订链接 | `npm i -g @rollinggo/hotel` + `rgh login` | 跳过，退回高德 POI；只调用只读子命令 | | 铁路接口 | 真实高铁/城际耗时与票价 | `RAIL_API_URL` | 降级为里程-速度估算并标注 | diff --git a/config.js b/config.js index a9e8c2c..3c8d02e 100644 --- a/config.js +++ b/config.js @@ -23,7 +23,19 @@ module.exports = { forecast: 'https://api.open-meteo.com/v1/forecast', archive: 'https://archive-api.open-meteo.com/v1/archive', airQuality: 'https://air-quality-api.open-meteo.com/v1/air-quality', - photon: 'https://photon.komoot.io/api', + photon: env.PHOTON_ENDPOINT || 'https://photon.komoot.io/api', + // Overpass 兜底：Photon 全挂时用（免密钥，但单次查询要 20~120 秒）。 + // 公共实例会限流/限容量，必须多镜像轮换；osm.ch 覆盖较全但偶尔返回 + // 「duplicate_query」错误页，靠响应体是否以 '{' 开头来判定真伪。 + overpass: env.OVERPASS_ENDPOINTS + ? env.OVERPASS_ENDPOINTS.split(',').map((s) => s.trim()).filter(Boolean) + : [ + 'https://overpass-api.de/api/interpreter', + 'https://overpass.kumi.systems/api/interpreter', + 'https://overpass.private.coffee/api/interpreter', + 'https://overpass.osm.ch/api/interpreter', + 'https://overpass.osm.jp/api/interpreter', + ], reverse: 'https://api.bigdatacloud.net/data/reverse-geocode-client', osrmTable: 'https://router.project-osrm.org/table/v1/driving', amapDriving: 'https://restapi.amap.com/v3/direction/driving', @@ -74,6 +86,12 @@ module.exports = { requestTimeoutMs: 15000, // 天气/地理编码等主数据源 osrmTimeoutMs: 12000, amapAroundRadius: 50000, // 高德 around 检索上限 50km + // Overpass 兜底的超时。公共实例经常「连着不返回」（不报错也不结束）， + // 没有硬超时的话一次兜底能把整个分析流程拖成十几分钟。 + overpassTimeoutMs: Number(env.OVERPASS_TIMEOUT_MS || 20000), + // 逐点 is_in 反查的上限：最多反查这么多个点， + // 超出部分改用 bbox 行政区中心点近邻判定（近似但快得多）。 + overpassIsInMax: Number(env.OVERPASS_ISIN_MAX || 8), }, // ------------------------------------------------- OpenAI 兼容接口（预留） diff --git a/lib/analyze.js b/lib/analyze.js index 0e1c5d5..df7c6c1 100644 --- a/lib/analyze.js +++ b/lib/analyze.js @@ -279,8 +279,10 @@ async function analyze(input, cfg, progress = () => {}) { const dataNotes = [ `周边目的地：Photon / OpenStreetMap（成功 ${stats.categoryHits}/${stats.requested} 类）` + `${stats.amapCount ? ` + 高德周边 ${stats.amapCount} 条` : ''}` + + `${stats.overpassCount ? ` + Overpass 兜底 ${stats.overpassCount} 条` : ''}` + ` + 内置知名景区 ${stats.curatedCount} 个 + 内置城市 ${stats.cityCount} 个 + 内置小众地点 ${stats.nicheCount} 个` + `${stats.fallbackOnly ? '；⚠️ 实时 POI 服务不可用，本次清单完全来自内置地名库（坐标为近似值）' : ''}` + + `${stats.overpassError ? `；Overpass 兜底也失败（${stats.overpassError}）` : ''}` + `${c.excludeLocal && stats.localExcluded ? `；已排除出发地所在城区的同城点位 ${stats.localExcluded} 个（同市下辖的其它县保留为周边目的地）` : ''}`, `天气：${weatherRes.note}`, `空气质量：${aqiRes.note}`, diff --git a/lib/places-admin-dv.js b/lib/places-admin-dv.js new file mode 100644 index 0000000..46b066b --- /dev/null +++ b/lib/places-admin-dv.js @@ -0,0 +1,18 @@ +/** + * 行政区划离线表（阿里 DataV GeoAtlas 数据，自动生成，请勿手改） + * + * 数据源：https://geo.datav.aliyun.com/areas_v3/bound/{adcode}_full.json（免密钥） + * 层级：国家民政部 adcode 体系（省级 2 位 / 地级 4 位 / 县级 6 位） + * + * COUNTY_DV 县级名 → [纬度, 经度, 所属地级名, adcode] + * PREF_DV 地级简称 → [纬度, 经度, adcode] + * COUNTY_ALIAS 县别名/简称 → 县全称 + * PREF_ALIAS 地级别名/全称 → 地级简称 + * + * 生成：node tools/build-admin-dv.cjs C:/tmp/datav-admin.json + */ +const COUNTY_DV = 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+const COUNTY_ALIAS = 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渝北区","渝北区旗":"渝北区","巴南区县":"巴南区","巴南区旗":"巴南区","黔江区县":"黔江区","黔江区旗":"黔江区","长寿区县":"长寿区","长寿区旗":"长寿区","江津区县":"江津区","江津区旗":"江津区","合川区县":"合川区","合川区旗":"合川区","永川区县":"永川区","永川区旗":"永川区","南川区县":"南川区","南川区旗":"南川区","璧山区县":"璧山区","璧山区旗":"璧山区","铜梁区县":"铜梁区","铜梁区旗":"铜梁区","潼南区县":"潼南区","潼南区旗":"潼南区","荣昌区县":"荣昌区","荣昌区旗":"荣昌区","开州区县":"开州区","开州区旗":"开州区","梁平区县":"梁平区","梁平区旗":"梁平区","武隆区县":"武隆区","武隆区旗":"武隆区","城口县县":"城口县","城口县旗":"城口县","丰都县县":"丰都县","丰都县旗":"丰都县","垫江县县":"垫江县","垫江县旗":"垫江县","忠县县":"忠县","忠县旗":"忠县","云阳县县":"云阳县","云阳县旗":"云阳县","奉节县县":"奉节县","奉节县旗":"奉节县","巫山县县":"巫山县","巫山县旗":"巫山县","巫溪县县":"巫溪县","巫溪县旗":"巫溪县","石柱":"石柱土家族自治县","石柱县":"石柱土家族自治县","石柱旗":"石柱土家族自治县","石柱土家族县":"石柱土家族自治县","石柱土家族":"石柱土家族自治县","秀山":"秀山土家族苗族自治县","秀山县":"秀山土家族苗族自治县","秀山旗":"秀山土家族苗族自治县","秀山土家族苗族县":"秀山土家族苗族自治县","秀山土家族苗族":"秀山土家族苗族自治县","酉阳":"酉阳土家族苗族自治县","酉阳县":"酉阳土家族苗族自治县","酉阳旗":"酉阳土家族苗族自治县","酉阳土家族苗族县":"酉阳土家族苗族自治县","酉阳土家族苗族":"酉阳土家族苗族自治县","彭水":"彭水苗族土家族自治县","彭水县":"彭水苗族土家族自治县","彭水旗":"彭水苗族土家族自治县","彭水苗族土家族县":"彭水苗族土家族自治县","彭水苗族土家族":"彭水苗族土家族自治县","石河子市县":"石河子市","石河子市旗":"石河子市","阿拉尔市县":"阿拉尔市","阿拉尔市旗":"阿拉尔市","图木舒克市县":"图木舒克市","图木舒克市旗":"图木舒克市","五家渠市县":"五家渠市","五家渠市旗":"五家渠市","北屯市县":"北屯市","北屯市旗":"北屯市","铁门关市县":"铁门关市","铁门关市旗":"铁门关市","双河市县":"双河市","双河市旗":"双河市","可克达拉市县":"可克达拉市","可克达拉市旗":"可克达拉市","昆玉市县":"昆玉市","昆玉市旗":"昆玉市","胡杨河市县":"胡杨河市","胡杨河市旗":"胡杨河市","中西区县":"中西区","中西区旗":"中西区","湾仔区县":"湾仔区","湾仔区旗":"湾仔区","南区县":"南区","南区旗":"南区","油尖旺区县":"油尖旺区","油尖旺区旗":"油尖旺区","深水埗区县":"深水埗区","深水埗区旗":"深水埗区","九龙城区县":"九龙城区","九龙城区旗":"九龙城区","黄大仙区县":"黄大仙区","黄大仙区旗":"黄大仙区","观塘区县":"观塘区","观塘区旗":"观塘区","荃湾区县":"荃湾区","荃湾区旗":"荃湾区","屯门区县":"屯门区","屯门区旗":"屯门区","元朗区县":"元朗区","元朗区旗":"元朗区","北区县":"北区","北区旗":"北区","大埔区县":"大埔区","大埔区旗":"大埔区","西贡区县":"西贡区","西贡区旗":"西贡区","沙田区县":"沙田区","沙田区旗":"沙田区","葵青区县":"葵青区","葵青区旗":"葵青区","离岛区县":"离岛区","离岛区旗":"离岛区","花地玛堂区县":"花地玛堂区","花地玛堂区旗":"花地玛堂区","花王堂区县":"花王堂区","花王堂区旗":"花王堂区","望德堂区县":"望德堂区","望德堂区旗":"望德堂区","大堂区县":"大堂区","大堂区旗":"大堂区","风顺堂区县":"风顺堂区","风顺堂区旗":"风顺堂区","嘉模堂区县":"嘉模堂区","嘉模堂区旗":"嘉模堂区","路凼填海区县":"路凼填海区","路凼填海区旗":"路凼填海区","圣方济各堂区县":"圣方济各堂区","圣方济各堂区旗":"圣方济各堂区"}; +const PREF_ALIAS = {"石家庄":"石家庄市","唐山":"唐山市","秦皇岛":"秦皇岛市","邯郸":"邯郸市","邢台":"邢台市","保定":"保定市","张家口":"张家口市","承德":"承德市","沧州":"沧州市","廊坊":"廊坊市","衡水":"衡水市","太原":"太原市","大同":"大同市","阳泉":"阳泉市","长治":"长治市","晋城":"晋城市","朔州":"朔州市","晋中":"晋中市","运城":"运城市","忻州":"忻州市","临汾":"临汾市","吕梁":"吕梁市","呼和浩特":"呼和浩特市","包头":"包头市","乌海":"乌海市","赤峰":"赤峰市","通辽":"通辽市","鄂尔多斯":"鄂尔多斯市","呼伦贝尔":"呼伦贝尔市","巴彦淖尔":"巴彦淖尔市","乌兰察布":"乌兰察布市","兴安":"兴安盟","锡林郭勒":"锡林郭勒盟","阿拉善":"阿拉善盟","沈阳":"沈阳市","大连":"大连市","鞍山":"鞍山市","抚顺":"抚顺市","本溪":"本溪市","丹东":"丹东市","锦州":"锦州市","营口":"营口市","阜新":"阜新市","辽阳":"辽阳市","盘锦":"盘锦市","铁岭":"铁岭市","朝阳":"朝阳市","葫芦岛":"葫芦岛市","长春":"长春市","吉林":"吉林市","四平":"四平市","辽源":"辽源市","通化":"通化市","白山":"白山市","松原":"松原市","白城":"白城市","延边朝鲜族自治州":"延边州","延边":"延边州","哈尔滨":"哈尔滨市","齐齐哈尔":"齐齐哈尔市","鸡西":"鸡西市","鹤岗":"鹤岗市","双鸭山":"双鸭山市","大庆":"大庆市","伊春":"伊春市","佳木斯":"佳木斯市","七台河":"七台河市","牡丹江":"牡丹江市","黑河":"黑河市","绥化":"绥化市","大兴安岭":"大兴安岭地区","南京":"南京市","无锡":"无锡市","徐州":"徐州市","常州":"常州市","苏州":"苏州市","南通":"南通市","连云港":"连云港市","淮安":"淮安市","盐城":"盐城市","扬州":"扬州市","镇江":"镇江市","泰州":"泰州市","宿迁":"宿迁市","杭州":"杭州市","宁波":"宁波市","温州":"温州市","嘉兴":"嘉兴市","湖州":"湖州市","绍兴":"绍兴市","金华":"金华市","衢州":"衢州市","舟山":"舟山市","台州":"台州市","丽水":"丽水市","合肥":"合肥市","芜湖":"芜湖市","蚌埠":"蚌埠市","淮南":"淮南市","马鞍山":"马鞍山市","淮北":"淮北市","铜陵":"铜陵市","安庆":"安庆市","黄山":"黄山市","滁州":"滁州市","阜阳":"阜阳市","宿州":"宿州市","六安":"六安市","亳州":"亳州市","池州":"池州市","宣城":"宣城市","福州":"福州市","厦门":"厦门市","莆田":"莆田市","三明":"三明市","泉州":"泉州市","漳州":"漳州市","南平":"南平市","龙岩":"龙岩市","宁德":"宁德市","南昌":"南昌市","景德镇":"景德镇市","萍乡":"萍乡市","九江":"九江市","新余":"新余市","鹰潭":"鹰潭市","赣州":"赣州市","吉安":"吉安市","宜春":"宜春市","抚州":"抚州市","上饶":"上饶市","济南":"济南市","青岛":"青岛市","淄博":"淄博市","枣庄":"枣庄市","东营":"东营市","烟台":"烟台市","潍坊":"潍坊市","济宁":"济宁市","泰安":"泰安市","威海":"威海市","日照":"日照市","临沂":"临沂市","德州":"德州市","聊城":"聊城市","滨州":"滨州市","菏泽":"菏泽市","郑州":"郑州市","开封":"开封市","洛阳":"洛阳市","平顶山":"平顶山市","安阳":"安阳市","鹤壁":"鹤壁市","新乡":"新乡市","焦作":"焦作市","濮阳":"濮阳市","许昌":"许昌市","漯河":"漯河市","三门峡":"三门峡市","南阳":"南阳市","商丘":"商丘市","信阳":"信阳市","周口":"周口市","驻马店":"驻马店市","武汉":"武汉市","黄石":"黄石市","十堰":"十堰市","宜昌":"宜昌市","襄阳":"襄阳市","鄂州":"鄂州市","荆门":"荆门市","孝感":"孝感市","荆州":"荆州市","黄冈":"黄冈市","咸宁":"咸宁市","随州":"随州市","恩施土家族苗族自治州":"恩施州","恩施":"恩施州","长沙":"长沙市","株洲":"株洲市","湘潭":"湘潭市","衡阳":"衡阳市","邵阳":"邵阳市","岳阳":"岳阳市","常德":"常德市","张家界":"张家界市","益阳":"益阳市","郴州":"郴州市","永州":"永州市","怀化":"怀化市","娄底":"娄底市","湘西土家族苗族自治州":"湘西州","湘西":"湘西州","广州":"广州市","韶关":"韶关市","深圳":"深圳市","珠海":"珠海市","汕头":"汕头市","佛山":"佛山市","江门":"江门市","湛江":"湛江市","茂名":"茂名市","肇庆":"肇庆市","惠州":"惠州市","梅州":"梅州市","汕尾":"汕尾市","河源":"河源市","阳江":"阳江市","清远":"清远市","东莞":"东莞市","中山":"中山市","潮州":"潮州市","揭阳":"揭阳市","云浮":"云浮市","南宁":"南宁市","柳州":"柳州市","桂林":"桂林市","梧州":"梧州市","北海":"北海市","防城港":"防城港市","钦州":"钦州市","贵港":"贵港市","玉林":"玉林市","百色":"百色市","贺州":"贺州市","河池":"河池市","来宾":"来宾市","崇左":"崇左市","海口":"海口市","三亚":"三亚市","三沙":"三沙市","儋州":"儋州市","成都":"成都市","自贡":"自贡市","攀枝花":"攀枝花市","泸州":"泸州市","德阳":"德阳市","绵阳":"绵阳市","广元":"广元市","遂宁":"遂宁市","内江":"内江市","乐山":"乐山市","南充":"南充市","眉山":"眉山市","宜宾":"宜宾市","广安":"广安市","达州":"达州市","雅安":"雅安市","巴中":"巴中市","资阳":"资阳市","阿坝藏族羌族自治州":"阿坝州","阿坝":"阿坝州","甘孜藏族自治州":"甘孜州","甘孜":"甘孜州","凉山彝族自治州":"凉山州","凉山":"凉山州","贵阳":"贵阳市","六盘水":"六盘水市","遵义":"遵义市","安顺":"安顺市","毕节":"毕节市","铜仁":"铜仁市","黔西南布依族苗族自治州":"黔西南州","黔西南":"黔西南州","黔东南苗族侗族自治州":"黔东南州","黔东南":"黔东南州","黔南布依族苗族自治州":"黔南州","黔南":"黔南州","昆明":"昆明市","曲靖":"曲靖市","玉溪":"玉溪市","保山":"保山市","昭通":"昭通市","丽江":"丽江市","普洱":"普洱市","临沧":"临沧市","楚雄彝族自治州":"楚雄州","楚雄":"楚雄州","红河哈尼族彝族自治州":"红河州","红河":"红河州","文山壮族苗族自治州":"文山州","文山":"文山州","西双版纳傣族自治州":"西双版纳州","西双版纳":"西双版纳州","大理白族自治州":"大理州","大理":"大理州","德宏傣族景颇族自治州":"德宏州","德宏":"德宏州","怒江傈僳族自治州":"怒江州","怒江":"怒江州","迪庆藏族自治州":"迪庆州","迪庆":"迪庆州","拉萨":"拉萨市","日喀则":"日喀则市","昌都":"昌都市","林芝":"林芝市","山南":"山南市","那曲":"那曲市","阿里":"阿里地区","西安":"西安市","铜川":"铜川市","宝鸡":"宝鸡市","咸阳":"咸阳市","渭南":"渭南市","延安":"延安市","汉中":"汉中市","榆林":"榆林市","安康":"安康市","商洛":"商洛市","兰州":"兰州市","嘉峪关":"嘉峪关市","金昌":"金昌市","白银":"白银市","天水":"天水市","武威":"武威市","张掖":"张掖市","平凉":"平凉市","酒泉":"酒泉市","庆阳":"庆阳市","定西":"定西市","陇南":"陇南市","临夏回族自治州":"临夏州","临夏":"临夏州","甘南藏族自治州":"甘南州","甘南":"甘南州","西宁":"西宁市","海东":"海东市","海北藏族自治州":"海北州","海北":"海北州","黄南藏族自治州":"黄南州","黄南":"黄南州","海南藏族自治州":"海南州","海南":"海南州","果洛藏族自治州":"果洛州","果洛":"果洛州","玉树藏族自治州":"玉树州","玉树":"玉树州","海西蒙古族藏族自治州":"海西州","海西":"海西州","银川":"银川市","石嘴山":"石嘴山市","吴忠":"吴忠市","固原":"固原市","中卫":"中卫市","乌鲁木齐":"乌鲁木齐市","克拉玛依":"克拉玛依市","吐鲁番":"吐鲁番市","哈密":"哈密市","昌吉回族自治州":"昌吉州","昌吉":"昌吉州","博尔塔拉蒙古自治州":"博尔塔拉蒙古州","博尔塔拉蒙古":"博尔塔拉蒙古州","巴音郭楞蒙古自治州":"巴音郭楞蒙古州","巴音郭楞蒙古":"巴音郭楞蒙古州","阿克苏":"阿克苏地区","克孜勒苏柯尔克孜自治州":"克孜勒苏柯尔克孜州","克孜勒苏柯尔克孜":"克孜勒苏柯尔克孜州","喀什":"喀什地区","和田":"和田地区","伊犁哈萨克自治州":"伊犁哈萨克州","伊犁哈萨克":"伊犁哈萨克州","塔城":"塔城地区","阿勒泰":"阿勒泰地区","北京":"北京市","天津":"天津市","上海":"上海市","重庆":"重庆市"}; +module.exports = { COUNTY_DV, PREF_DV, COUNTY_ALIAS, PREF_ALIAS }; diff --git a/lib/places-admin.js b/lib/places-admin.js new file mode 100644 index 0000000..946f85c --- /dev/null +++ b/lib/places-admin.js @@ -0,0 +1,18 @@ +'use strict'; +/** + * 内置地点库的归属地名（自动生成，勿手改）。 + * + * 生成方式： + * tools/build-admin.cjs —— 首轮，Photon 按名检索 + 坐标距离消歧 + * tools/build-admin-fix.cjs —— 二轮，去后缀/核心词重试，补首轮搜不到的 + * tools/build-admin-normalize.cjs —— 三轮，把组名归一到地级（市/州/盟/地区） + * + * 字段： + * SPOT_AREA { 'scenic:荔波小七孔': { area, detail, state, level } } + * AREA_COORD { '荔波县': [lat, lon] } 各地名代表坐标，运行时做最近市兜底 + */ +const SPOT_AREA = 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ꓝꓳꓴ","detail":"贡山县","state":"云南省","level":"prefecture"},"niche:元阳箐口民俗村":{"area":"红河","detail":"","state":"云南","level":"prefecture"},"niche:建水团山民居":{"area":"玉溪市","detail":"团山村","state":"云南省","level":"prefecture"},"niche:坝美村":{"area":"文山州","detail":"文山","state":"云南","level":"prefecture"},"niche:普者黑":{"area":"文山州","detail":"丘北县","state":"云南省","level":"prefecture"},"niche:萨普神山":{"area":"那曲市 ནག་ཆུ་ས་ཁུལ།","detail":"比如县 འབྲི་རུ་རྫོང་།","state":"西藏自治区 བོད་རང་སྐྱོང་ལྗོངས།","level":"prefecture"},"niche:札达土林":{"area":"阿里地区 མངའ་རིས་ས་ཁུལ།","detail":"札达县 རྩ་མདའ་རྫོང་།","state":"西藏自治区 བོད་རང་སྐྱོང་ལྗོངས།","level":"prefecture"},"niche:来古冰川":{"area":"昌都市 ཆབ་མདོ་གྲོང་ཁྱེར།","detail":"","state":"西藏自治区 བོད་རང་སྐྱོང་ལྗོངས།","level":"county"},"niche:索松村":{"area":"林芝市","detail":"米林市 སྨན་གླིང་གྲོང་ཁྱེར།","state":"西藏自治区 བོད་རང་སྐྱོང་ལྗོངས།","level":"prefecture"},"niche:波浪谷":{"area":"榆林市","detail":"","state":"陕西省","level":"county"},"niche:米脂窑洞古城":{"area":"榆林市","detail":"榆林","state":"陕西","level":"prefecture"},"niche:青木川古镇":{"area":"宁强县","detail":"","state":"陕西省","level":"prefecture"},"niche:留坝高江路":{"area":"汉中市","detail":"汉中","state":"陕西","level":"prefecture"},"niche:扎尕那":{"area":"迭部县 ཐེ་བོ་རྫོང་།","detail":"益哇镇 གཡི་བ།","state":"甘肃省","level":"prefecture"},"niche:郎木寺":{"area":"碌曲县","detail":"郎木寺镇 ལྷ་མོ།","state":"甘肃省","level":"prefecture"},"niche:炳灵寺石窟":{"area":"兰州市","detail":"杨塔乡","state":"甘肃省","level":"prefecture"},"niche:石包城遗址":{"area":"酒泉市","detail":"酒泉","state":"甘肃","level":"prefecture"},"niche:翡翠湖":{"area":"海西","detail":"","state":"青海","level":"prefecture"},"niche:水上雅丹":{"area":"大柴旦行政委员会","detail":"柴旦镇","state":"青海省","level":"prefecture"},"niche:贵德黄河清":{"area":"西宁市","detail":"海南","state":"青海","level":"prefecture"},"niche:坎布拉":{"area":"西宁市","detail":"尖扎县 གཅན་ཚ།","state":"青海省","level":"prefecture"},"niche:西夏王陵":{"area":"银川市","detail":"","state":"宁夏回族自治区","level":"county"},"niche:水洞沟":{"area":"银川市","detail":"","state":"宁夏回族自治区","level":"county"},"niche:大海道":{"area":"哈密","detail":"","state":"新疆","level":"prefecture"},"niche:夏塔古道":{"area":"伊宁市","detail":"伊犁","state":"新疆","level":"prefecture"},"niche:琼库什台":{"area":"伊宁市","detail":"特克斯县","state":"新疆维吾尔自治区 شىنجاڭ ئۇيغۇر ئاپتونوم رايونی","level":"prefecture"},"niche:禾木村":{"area":"阿勒泰市","detail":"禾木哈纳斯蒙古民族乡 قومقاناس موڭعۇل ۇلتتىق اۋىلى ᠬᠣᠮ ᠬᠠᠨᠠᠰ ᠮᠣᠩᠭᠣᠯ ᠦᠨᠳᠦᠰᠦᠲᠡᠨ ᠦ ᠰᠢᠶᠠᠩ","state":"新疆维吾尔自治区 شىنجاڭ ئۇيغۇر ئاپتونوم رايونی","level":"prefecture"},"niche:白哈巴村":{"area":"哈巴河县","detail":"铁热克提乡 تەرەكتى اۋىلى","state":"新疆维吾尔自治区 شىنجاڭ ئۇيغۇر ئاپتونوم رايونی","level":"prefecture"},"scenic:婺源篁岭":{"area":"黄山市","detail":"江湾镇","state":"江西省","level":"prefecture"},"scenic:荔波小七孔":{"area":"黔南州","detail":"荔波县","state":"贵州省","level":"prefecture"},"scenic:伊犁那拉提":{"area":"新源县","detail":"","state":"新疆维吾尔自治区 شىنجاڭ ئۇيغۇر ئاپتونوم رايونی","level":"prefecture"},"scenic:北极村":{"area":"漠河市","detail":"","state":"黑龙江省","level":"prefecture"}}; + +const AREA_COORD = {"承德市":[40.679,117.229],"北京市":[40.533,116.008],"唐山市":[40.183,117.633],"蓟州区":[40.233,117.4],"红桥区":[39.1536,117.1742],"河北区":[39.1431,117.2008],"和平区":[39.125,117.2],"石家庄市":[38.2833,113.95],"保定市":[38.75,113.833],"吉县":[36.15,110.433],"晋中市":[37.4,112.433],"大同市":[39.733,113.7],"朔州市":[39.567,113.183],"代县":[39.2,112.85],"洛阳市":[33.75,111.633],"殷都区":[36.133,114.317],"龙亭区":[34.8,114.35],"南京市":[31.9,118.75],"无锡市":[31.433,120.1],"苏州市":[31.16,120.717],"嘉善县":[30.94,120.89],"湖州市":[30.883,120.417],"常州市":[31.3,119.417],"舟山市":[30,122.3833],"温州市":[28.3667,121.05],"衢州市":[28.533,118.567],"黄山市":[29.883,117.983],"玉山县":[28.9,118.067],"贵溪市":[28.1,116.983],"柴桑区":[29.583,115.983],"南昌市":[28.683,115.883],"龙岩市":[24.683,117.133],"泉州市":[24.933,118.583],"烟台市":[37.817,120.75],"威海市":[37.5,122.183],"枣庄市":[34.567,117.733],"潍坊市":[36.683,118.483],"武汉市":[30.545,114.303],"宜昌市":[30.833,111],"恩施市":[30.567,109.267],"神农架林区":[31.75,110.333],"凤凰县":[27.95,109.6],"岳麓区":[28.183,112.933],"仁化县":[25.0333,113.75],"广州市":[23.1066,113.3245],"江门市":[22.3667,112.7],"惠州市":[23.083,114.4],"桂林市":[25.27,110.3],"涠洲岛和猪仔岭":[21.033,109.117],"崇左市":[22.85,106.717],"三亚市":[18.25,109.35],"成都市":[30.669,104.055],"峨眉山市":[29.533,103.35],"市中区":[29.55,103.767],"稻城县 འདབ་པ་རྫོང།":[28.433,100.3],"小金县 བཙན་ལྷ་རྫོང།":[31.1,102.9],"若尔盖县 མཛོད་དགེ་རྫོང།":[33.9,102.833],"松潘县 ཟུང་ཆུ་རྫོང།":[32.75,103.833],"沙坪坝区":[29.58,106.45],"大足区":[29.7,105.7],"武隆区":[29.433,107.8],"贵阳市":[26.417,106.683],"镇远县":[27.05,108.433],"黔东南州":[26.483,108.183],"昆明市":[24.8167,103.3333],"丽江市":[27.1,100.183],"盐源县 ꋂꂿꑤ":[27.7,100.783],"西双版纳州":[21.917,101.267],"大理白族自治州":[25.7,100.15],"西安市":[34.3853,109.2785],"宝鸡市":[34.433,107.9],"麦积区":[34.35,106],"肃南裕固族自治县":[38.9,100.133],"嘉峪关市":[39.8,98.22],"酒泉市":[40.083,94.667],"湟中县":[36.483,101.567],"乌兰县 ཝུའུ་ལན་རྫོང།":[36.75,99.083],"沙坡头区":[37.45,105],"银川市":[38.5,106.083],"布尔津县":[48.733,87.033],"博乐市":[44.6,81.2],"沈阳市":[41.7997,123.4539],"甘井子区":[38.8767,121.5733],"삼지연시":[42,128.0667],"绿园区":[43.883,125.35],"张家口市":[40.552,116.021],"邯郸市":[36.751,113.951],"西青区":[39.141,116.991],"宁武县":[38.851,112.051],"五寨县":[38.751,111.901],"晋城市":[35.501,112.451],"呼伦贝尔市 ᠬᠥᠯᠥᠨ ᠪᠤᠶᠢᠷ":[50.751,119.551],"丹东市":[40.551,125.351],"盘锦市":[40.951,121.851],"海林市":[44.551,129.651],"五大连池市":[48.721,126.151],"台州市":[28.351,121.601],"宁波市":[29.251,121.351],"绍兴市":[29.851,120.851],"杭州市":[29.551,118.851],"徐州市":[34.251,118.051],"上海市":[31.111,121.051],"松江区":[31.051,121.221],"宣城市":[30.551,118.151],"霞浦县":[26.751,120.351],"浮梁县":[29.551,117.551],"婺源县":[29.421,117.981],"吉安市":[27.451,114.181],"新乡市":[35.751,113.601],"郑州市":[34.401,113.151],"会同县":[26.851,109.751],"新宁县":[26.351,110.851],"秀山县":[28.551,109.251],"汕头市":[23.421,117.051],"清远市":[24.251,112.951],"柳州市":[25.901,109.651],"从江县":[25.751,108.451],"黎平县":[25.751,109.151],"黔西南州":[25.051,104.951],"丹巴县 རོང་བྲག་རྫོང།":[30.851,101.851],"白玉县 དཔལ་ཡུལ་རྫོང།":[31.151,99.551],"巴塘县 འབའ་ཐང་རྫོང།":[30.451,99.551],"阿坝县 རྔ་བ་རྫོང།":[32.551,102.051],"酉阳县":[28.751,108.451],"北碚区":[29.951,106.551],"剑川县":[26.321,99.851],"迪庆藏族自治州 བདེ་ཆེན་བོད་རིགས་རང་སྐྱོང་ཁུལ།":[28.351,98.751],"怒江州 ꓠꓳ-ꓟꓵ ꓝꓳꓴ":[28.051,98.651],"建水县":[23.601,102.751],"文山州":[24.051,104.151],"那曲市 ནག་ཆུ་ས་ཁུལ།":[30.851,93.551],"阿里地区 མངའ་རིས་ས་ཁུལ།":[31.501,79.751],"昌都市 ཆབ་མདོ་གྲོང་ཁྱེར།":[29.251,96.751],"林芝市 ཉིང་ཁྲི་གྲོང་ཁྱེར།":[29.551,94.951],"榆林市":[37.551,108.851],"宁强县":[32.851,105.551],"迭部县 ཐེ་བོ་རྫོང་།":[34.251,103.151],"碌曲县":[34.051,102.651],"永靖县":[35.801,103.051],"大柴旦行政委员会":[37.751,93.351],"黄南藏族自治州 རྨ་ལྷོ་བོད་རིགས་རང་སྐྱོང་ཁུལ།":[36.051,101.751],"特克斯县":[43.151,82.351],"哈巴河县":[48.651,86.751],"黔南州":[25.3,107.7],"新源县":[43.3,84],"漠河市":[53.467,122.35]}; + +module.exports = { SPOT_AREA, AREA_COORD }; diff --git a/lib/sources.js b/lib/sources.js index 11903e2..237cc18 100644 --- a/lib/sources.js +++ b/lib/sources.js @@ -12,6 +12,8 @@ const U = require('./util'); const C = require('./cache'); const { JUNK_NAME, POOR_NAME, LOW_VALUE_NAME, CURATED, CN_CITIES, NICHE_SPOTS, wmo } = require('./data'); +const ADMIN = require('./places-admin'); +const DV = require('./places-admin-dv'); // 数据源层缓存 TTL（秒级语义）： // 地理编码 7 天（行政区划不会变）／高德 POI 6 小时（商家会变） @@ -167,6 +169,9 @@ function photonCandidate(feature, cat, origin) { if (JUNK_NAME.test(name) || POOR_NAME.test(name) || LOW_VALUE_NAME.test(name)) return null; if (/^\d+$/.test(name)) return null; if (name.length < 2 || name.length > 30) return null; + // 纯外文的条目（如「Rice Terraces」）对中文用户没有辨识度， + // 而且 OSM 上外国景点会混进来占名额。名称里至少要有一个汉字。 + if (!/[\u4e00-\u9fa5]/.test(name)) return null; const distanceKm = U.haversine(origin.lat, origin.lon, lat, lon); return { id: `osm-${p.osm_type || 'N'}-${p.osm_id || Math.round(lat * 1e5)}`, @@ -175,7 +180,12 @@ function photonCandidate(feature, cat, origin) { tags: [...cat.tags], lat: U.round(lat, 5), lon: U.round(lon, 5), - region: [p.city, p.district, p.locality].filter(Boolean).filter((v, i, a) => a.indexOf(v) === i).slice(0, 2).join(' · '), + // OSM 中国的层级命名与直觉相反：county 是地级市/州，city 是县/区， + // district 是街道，locality 是村。分组必须用 county，取 district 会分出「玉屏街道」这种组。 + osmCounty: String(p.county || '').trim(), + osmCity: String(p.city || '').trim(), + osmDistrict: String(p.district || '').trim(), + region: [p.county, p.city, p.district].filter(Boolean).filter((v, i, a) => a.indexOf(v) === i).slice(0, 2).join(' · '), distanceKm, bearingDeg: U.bearing(origin.lat, origin.lon, lat, lon), source: 'OpenStreetMap / Photon', @@ -716,10 +726,623 @@ async function amapAround(origin, radiusKm, cfg) { }, TTL.poi); } +/** + * Overpass 兜底检索（免密钥）。 + * + * 为什么需要：Photon 公共实例限流或临时挂掉时，候选池会掉到只剩内置库—— + * 而内置库在广西、云南这类省的覆盖很薄（150km 内常常只有 1~3 个点）， + * 第二步就几乎没内容可分。Overpass 直接查 OSM 的原始标签，是同源数据但不同入口。 + * + * 代价：单次查询要 20~120 秒，所以**只在 Photon 全部失败时启用**，且走独立缓存。 + */ +const OVERPASS_TAGS = [ + { sel: 'node["tourism"="attraction"]', kind: '景点', tags: ['人文历史', '拍照', '观光'] }, + { sel: 'node["tourism"="viewpoint"]', kind: '观景地', tags: ['自然风光', '拍照', '徒步登山'] }, + { sel: 'node["tourism"="museum"]', kind: '博物馆', tags: ['人文历史', '亲子', '室内避雨'] }, + { sel: 'way["tourism"="attraction"]', kind: '景点', tags: ['人文历史', '拍照', '观光'] }, + { sel: 'node["natural"="cave_entrance"]', kind: '溶洞', tags: ['自然风光', '探险', '避暑'] }, + { sel: 'node["historic"="memorial"]', kind: '纪念地', tags: ['人文历史', '室内避雨'] }, + { sel: 'node["leisure"="nature_reserve"]', kind: '自然保护地', tags: ['自然风光', '徒步登山'] }, + { sel: 'node["tourism"="theme_park"]', kind: '主题乐园', tags: ['亲子', '主题乐园'] }, +]; + +async function overpassQuery(origin, radiusKm, cfg) { + // bboxFromRadius 返回 [west, south, east, north]（Photon 的顺序）， + // 而 Overpass 要 [south, west, north, east] —— 顺序错了直接 400。 + const [w, s, e, n] = U.bboxFromRadius(origin.lat, origin.lon, radiusKm); + const body = [s, w, n, e].map((x) => x.toFixed(4)).join(','); + const sel = OVERPASS_TAGS.map((t) => `${t.sel}(${body});`).join(''); + const q = `[out:json][timeout:50];(${sel});out center 120;`; + // Overpass 公共实例对大 bbox + 多标签容易 502/504，换几个镜像重试 + const hosts = Array.isArray(cfg.ENDPOINTS.overpass) ? cfg.ENDPOINTS.overpass : [cfg.ENDPOINTS.overpass]; + const timeoutMs = Number(cfg.SEARCH?.overpassTimeoutMs) || 20000; + // 单次查询的总时限：镜像可能有 5 个，逐个等超时最坏要 5×timeout。 + // 给一份总预算，超了就别再试下一个镜像了。 + const deadline = Date.now() + timeoutMs * 2; + let lastErr = ''; + for (const host of hosts) { + if (Date.now() > deadline) { + lastErr = lastErr || 'Overpass 超出总时限'; + break; + } + try { + const res = await fetch(host, { + method: 'POST', + headers: { 'Content-Type': 'application/x-www-form-urlencoded', 'User-Agent': 'TripSense/1.0' }, + body: 'data=' + encodeURIComponent(q), + signal: AbortSignal.timeout(timeoutMs), + }); + const text = await res.text(); + // 实例可能返回 200 + HTML 错误页（如 osm.ch 的 duplicate_query）， + // 只看 status 会把错误页当成功，判据必须是响应体是否以 '{' 开头。 + if (!text.startsWith('{')) throw new Error(`${host} 返回 ${res.status}`); + return JSON.parse(text).elements || []; + } catch (e) { + lastErr = e.message || String(e); + console.warn('[overpass]', lastErr); + } + } + throw new Error(lastErr || 'Overpass 全部镜像均失败'); +} +/** + * Overpass 的兴趣点大多**没有** `addr:*` 标签，直接拿归属会得到空组名。 + * + * 解法：用 Overpass 的 `is_in` 反查**点落在哪些行政区里**。 + * 一次请求就能拿到完整层级（实测 25.1,107.98 → L6 环江毛南族自治县 / L5 河池市 / L4 广西）。 + * + * 为什么不用「拉边界多边形再本地做点面判定」： + * relation 的几何在 `members` 里，`out tags geom` / `out geom` 都拿不到 + * relation 级的 geometry 数组；实测 `out tags geom` 返回的 1064 条元素 + * 只有 type/id/bounds/tags，geometry 为 undefined。绕这一圈代价太高。 + * + * 层级：OSM 中国的 `admin_level` 是 **4=省 / 5=地级市 / 6=县**， + * 不是直觉上的 4/6/8（实测荔波县是 6）。 + */ +async function overpassAdminAreas(origin, radiusKm, cfg) { + // 保留旧签名：这里改为「一次拉 bbox 内所有行政区 + 打点标记」，不再逐点查 + const [w, s, e, n] = U.bboxFromRadius(origin.lat, origin.lon, radiusKm); + const body = [s, w, n, e].map((x) => x.toFixed(4)).join(','); + const q = `[out:json][timeout:60];rel["admin_level"~"^[56]$"](${body});out center tags;`; + const hosts = Array.isArray(cfg.ENDPOINTS.overpass) ? cfg.ENDPOINTS.overpass : [cfg.ENDPOINTS.overpass]; + const timeoutMs = Number(cfg.SEARCH?.overpassTimeoutMs) || 20000; + const deadline = Date.now() + timeoutMs * 2; + let lastErr = ''; + for (const host of hosts) { + if (Date.now() > deadline) { lastErr = lastErr || 'Overpass 超出总时限'; break; } + try { + const res = await fetch(host, { + method: 'POST', + headers: { 'Content-Type': 'application/x-www-form-urlencoded', 'User-Agent': 'TripSense/1.0' }, + body: 'data=' + encodeURIComponent(q), + signal: AbortSignal.timeout(timeoutMs), + }); + const text = await res.text(); + if (!text.startsWith('{')) throw new Error(`${host} 返回 ${res.status}`); + const els = JSON.parse(text).elements || []; + const areas = []; + for (const el of els) { + const name = String(el.tags?.['name:zh'] || el.tags?.name || '').trim(); + if (!name) continue; + const c = el.center || {}; + const lat = Number(c.lat); + const lon = Number(c.lon); + if (!Number.isFinite(lat) || !Number.isFinite(lon)) continue; + areas.push({ name, level: String(el.tags.admin_level), lat, lon }); + } + return areas; + } catch (e) { + lastErr = e.message || String(e); + console.warn('[overpass-admin]', lastErr); + } + } + throw new Error(lastErr || 'Overpass 行政区查询失败'); +} + +/** + * 逐点反查所在行政区（Overpass `is_in`）。 + * 只在 Overpass 兜底路径上、且候选缺少 addr:* 标签时用（一次约 1~3 秒）。 + * @returns {{ area: string, detail: string } | null} + */ +async function overpassAdminAtPoint(lat, lon, cfg) { + const q = `[out:json][timeout:60];is_in(${lat.toFixed(5)},${lon.toFixed(5)})->.a;.a out tags;`; + const hosts = Array.isArray(cfg.ENDPOINTS.overpass) ? cfg.ENDPOINTS.overpass : [cfg.ENDPOINTS.overpass]; + const timeoutMs = Number(cfg.SEARCH?.overpassTimeoutMs) || 20000; + for (const host of hosts) { + try { + const res = await fetch(host, { + method: 'POST', + headers: { 'Content-Type': 'application/x-www-form-urlencoded', 'User-Agent': 'TripSense/1.0' }, + body: 'data=' + encodeURIComponent(q), + signal: AbortSignal.timeout(timeoutMs), + }); + const text = await res.text(); + if (!text.startsWith('{')) continue; + const els = JSON.parse(text).elements || []; + let prefecture = ''; + let county = ''; + for (const el of els) { + const level = String(el.tags?.admin_level || ''); + const name = String(el.tags?.['name:zh'] || el.tags?.name || '').trim(); + if (!name) continue; + if (level === '5') prefecture = name; + else if (level === '6') county = name; + } + if (!prefecture && !county) continue; + // 走统一查表：OSM 的名字可能是简称（「环江」）或全称（「环江毛南族自治县」）， + // 查表能补齐标准全称并带上所属地级；同名县还要按坐标消歧。 + const cHit = county ? lookupAdminByName(county, lat, lon) : null; + if (cHit && cHit.detail) return { area: cHit.area, detail: cHit.detail }; + const pHit = prefecture ? lookupAdminByName(prefecture, lat, lon) : null; + if (pHit) return { area: pHit.area, detail: pHit.detail || '' }; + // 查表查不到就原样返回 OSM 名字，至少还有个能显示的地名 + return { area: prefecture || county, detail: county && county !== prefecture ? county : '' }; + } catch (e) { + console.warn('[overpass-isin]', e.message || e); + } + } + return null; +} + +const isPrefectureSuffix = (n) => /(市|州|盟|地区)$/.test(String(n || '').trim()); +const isCountySuffix = (n) => /(县|区|旗)$/.test(String(n || '').trim()); + +/** + * 按坐标找所属行政区（Overpass 兜底路径专用）。 + * + * 输入是 bbox 内所有行政区 relation 的 **center 点**（不是多边形—— + * relation 级 geometry 在 Overpass 里拿不到，见 overpassAdminAreas 注释）。 + * 所以判定退化��「找最近的同层级行政区」，并用 admin_level 区分地级/县级： + * L5=地级市、L6=县。 + * + * @returns {{ area: string, detail: string } | null} + */ +function areaByPoint(areas, lat, lon) { + let prefecture = null; + let county = null; + for (const a of areas) { + const d = U.haversine(lat, lon, a.lat, a.lon); + if (a.level === '5' || isPrefectureSuffix(a.name)) { + if (!prefecture || d < prefecture.d) prefecture = { name: a.name, d }; + } else if (a.level === '6' || isCountySuffix(a.name)) { + if (!county || d < county.d) county = { name: a.name, d }; + } + } + // 近邻判定给的是 OSM 的名字（可能是简称），过一遍统一查表补全标准全称 + if (county) { + const hit = lookupAdminByName(county.name, lat, lon); + if (hit && hit.detail) return { area: hit.area, detail: hit.detail }; + } + if (prefecture) { + const hit = lookupAdminByName(prefecture.name, lat, lon); + if (hit) return { area: hit.area, detail: hit.detail || (county ? county.name : '') }; + } + if (prefecture) return { area: prefecture.name, detail: county ? county.name : '' }; + if (county) return { area: county.name, detail: '' }; + return null; +} + +function overpassCandidate(el, origin, cfg) { + const t = el.tags || {}; + const name = String(t['name:zh'] || t.name || '').trim(); + if (!name) return null; + const lat = Number(el.lat ?? el.center?.lat); + const lon = Number(el.lon ?? el.center?.lon); + if (!Number.isFinite(lat) || !Number.isFinite(lon)) return null; + // 按标签找类别 + const tag = OVERPASS_TAGS.find((x) => x.sel.includes(`"${t.tourism || t.natural || t.historic || t.leisure}"`)); + const kind = tag?.kind || '景点'; + const tags = tag?.tags || ['自然风光', '拍照']; + const distanceKm = U.haversine(origin.lat, origin.lon, lat, lon); + return { + id: `overpass-${el.type}-${el.id}`, + name, + kind, + tags: [...tags], + lat: U.round(lat, 5), + lon: U.round(lon, 5), + osmCounty: String(t['addr:county'] || t['addr:city'] || t['addr:province'] || '').trim(), + osmCity: String(t['addr:district'] || t['addr:city'] || '').trim(), + region: [t['addr:province'], t['addr:city'], t['addr:district']].filter(Boolean).join(' · '), + distanceKm, + bearingDeg: U.bearing(origin.lat, origin.lon, lat, lon), + source: 'OpenStreetMap / Overpass', + hasExtent: false, + featured: false, + }; +} + /** * 检索周边目的地（多层来源，任一不可用都不影响出结果）： * Photon 分类检索 → 高德周边 POI（可选） → 内置知名景区 → 内置城市库 → 内置小众地点库 */ +/** + * 候选的归属地名（第二步分组用）。 + * + * 问题：候选来自四个来源，归属信息粒度完全不一致—— + * 高德 place/text → 有 cityname（地级市）与 adname（区县） + * 内置小众库 → region 是「省 · 市」 + * 内置知名库 → 没有任何归属信息 + * Photon(OSM) → region 是街道名（「金城江街道」） + * 直接把这些 region 铺在卡片上，用户看到的就是一堆平铺的名字， + * 分不清「柳州」和「柳州古城」是两级还是并列。 + * + * 做法：统一反查成「地级市 + 区县」，作为分组键。 + * 高德 regeo 的批量参数（batch=true）实测返回 INVALID_PARAMS， + * 所以逐点反查 + 缓存（TTL.geo，坐标取整 3 位做指纹）。 + */ +async function amapPlaceOf(lat, lon, cfg) { + if (!cfg.AMAP_KEY) return null; + const [glng, glat] = U.wgs84ToGcj02(lon, lat); + return C.memo(sk(`placeOf:${U.round(lat, 3)},${U.round(lon, 3)}`, cfg), async () => { + const u = new URL(cfg.ENDPOINTS.amapRegeo); + u.searchParams.set('location', `${U.round(glng, 6)},${U.round(glat, 6)}`); + u.searchParams.set('extensions', 'base'); + u.searchParams.set('key', cfg.AMAP_KEY); + const d = await U.fetchJSON(u.toString(), {}, 8000, 1); + if (d.status !== '1' || !d.regeocode) return null; + const ac = d.regeocode.addressComponent || {}; + const province = String(ac.province || '').trim(); + const city = String(ac.city || '').trim(); + const district = String(ac.district || '').trim(); + if (!city && !district) return null; + return { province, city: city || district, district: city && district ? district : '', label: district && district !== city ? `${city} · ${district}` : city }; + }, TTL.geo); +} + +/** + * 分组键归一：去掉末尾的「市 / 地区 / 盟 / 自治州」等行政后缀。 + * 「柳州」（内置小众库写法）与「柳州市」（高德 cityname）必须落到同一组， + * 否则同一个地方会被拆成两堆。 + * + * 民族自治州要连民族名一起去掉：「黔南布依族苗族自治州」→「黔南」， + * 「黔东南苗族侗族自治州」→「黔东南」。但**不能用贪婪正则**—— + * `[一-龥]{1,3}族` 会把「黔南」的「南」也当成民族名吃掉（实测变成「黔」）。 + * 所以这里用显式的民族名清单。 + */ +const ETHNIC_AUTONOMY = /(?:壮族|满族|回族|苗族|侗族|土家族|羌族|彝族|蒙古族|藏族|维吾尔族|哈萨克族|柯尔克孜族|布依族|朝鲜族|白族|傣族|黎族|傈僳族|佤族|畲族|高山族|拉祜族|水族|东乡族|纳西族|景颇族|土族|达斡尔族|仫佬族|羌族|布朗族|撒拉族|毛南族|仡佬族|锡伯族|阿昌族|普米族|塔吉克族|怒族|乌孜别克族|俄罗斯族|鄂温克族|德昂族|保安族|裕固族|京族|塔塔尔族|独龙族|鄂伦春族|赫哲族|门巴族|珞巴族|基诺族)+自治(?:州|县)/g; + +function placeKey(city) { + return String(city || '').trim() + .replace(ETHNIC_AUTONOMY, '') + .replace(/(自治区|自治州|自治县|地区|盟|市)$/g, '') + .trim(); +} + +/** + * 给候选补 place / placeKey / placeDetail： + * place 分组显示名（地级市/州，如「黔南州」「柳州市」） + * placeKey 分组键（归一后的地名，用于合并不同写法） + * placeDetail 更细一级的区县说明 + * + * 分组名必须落在**地级**这一层，不能是街道或村名。 + * 用户看到「玉屏街道」「乐依村」这种组名等于没分组——它是 OSM 的最细一级， + * 同一个县下面的几十个点会被拆成几十组。 + */ +/** + * 查内置地点库（知名景区 / 小众地点）的离线归属地名。 + * 数据由 tools/build-admin*.cjs 生成：Photon 按名检索 + 坐标距离消歧 + 归一到地级。 + * + * detail 只保留**县级**（以「县/区/市/州/旗」结尾）： + * Photon 有时把村名（「摆别村」）塞在这一级，展示出来反而更乱。 + */ +function adminAreaOf(c) { + const table = ADMIN.SPOT_AREA; + if (!table) return null; + const key = c.id && c.id.startsWith('curated-') + ? `scenic:${c.id.slice('curated-'.length)}` + : (c.id && c.id.startsWith('niche-') ? `niche:${c.id.slice('niche-'.length)}` : null); + if (!key) return null; + const hit = table[key]; + if (!hit || !hit.area) return null; + const detail = /(县|区|市|州|旗|盟)$/.test(String(hit.detail || '').trim()) ? hit.detail : ''; + return { area: hit.area, detail }; +} + +/** + * 就近最近的地级市/州：全国地级坐标表 + 内置城市库 + 离线归属表里的地名坐标。 + * 用 haversine 在本地算，不发请求（几十个点 × 几百个地名的规模完全够用）。 + * + * 只认**地级**名字（以「市/州/盟/地区」结尾）。 + * 县级名（从江县、吉县）当组名会让同一个地级市被拆成好几组， + * 也会出现「荔波小七孔归到隔壁的从江县」这种误导。 + * + * 全国表（lib/places-admin-dv.js，343 个地级）是主力；CN_CITIES 只有 146 个， + * 桂黔边境（河池市、黔南州、黔东南州）根本不在里面，缺了它候选点会落进空组名。 + */ +function isPrefectureName(name) { + return /(市|州|盟|地区)$/.test(String(name || '').trim()); +} + +/** + * 「下层地名」是否合格：必须是县级（县/区/旗/市）或地级，不能是村/街道/屯。 + * Photon 的 city/district 字段层级不稳，会给出「乐依村」「双福」「陈家甫」这种 + * 村名甚至门牌名——挂在分组标题下当区县完全没法看。 + */ +function isDistrictName(name) { + return /(县|区|旗|盟|州|市)$/.test(String(name || '').trim()); +} + +/** + * 这个名字是不是**已知的地级行政区**。 + * + * 用于过滤 Photon `osm.place.city` 检索里的噪声：OSM 的 place=city 里 + * 混着大量景点 POI（牌坊、寺庙、老街），它们的名字也带「市/州」后缀 + * 会被误当行政区。查一下官方表就知道是不是真地名。 + */ +function isKnownPrefecture(name) { + const raw = String(name || '').trim(); + if (!raw) return false; + if (DV.PREF_DV[raw]) return true; + const alias = DV.PREF_ALIAS[raw]; + return !!(alias && DV.PREF_DV[alias]); +} + +function nearestArea(lat, lon) { + if (!Number.isFinite(lat) || !Number.isFinite(lon)) return null; + let best = null; + const scan = (name, coord) => { + if (!coord || !isPrefectureName(name)) return; + const d = U.haversine(lat, lon, coord[0], coord[1]); + if (!best || d < best.d) best = { area: name, d }; + }; + // DataV 官方地级表（343 个，含各族自治州简称）优先 + for (const [name, coord] of Object.entries(DV.PREF_DV || {})) scan(name, coord); + for (const [name, la, lo] of CN_CITIES) scan(name, [la, lo]); + for (const [name, coord] of Object.entries(ADMIN.AREA_COORD || {})) scan(name, coord); + // 最近的超过 120km 基本就不是「这一片」，宁可留空也不要给出误导性的地名 + return best && best.d <= 120 ? { area: best.area } : null; +} + +/** + * 从离线表里取一个县的条目，同名县按距离选最近的。 + * + * DataV 官方表里同名县保留为**数组**（全国 30 组：「城中区」柳州/西宁都有、 + * 「鼓楼区」南京/徐州/福州/开封都有、「铁西区」沈阳/鞍山/四平都有）。 + * 只按名字取会把柳州的点归到西宁去，所以必须带坐标做消歧。 + * + * @param {string} name 县全称（表里的 key） + * @param {number} lat 候选点纬度 + * @param {number} lon 候选点经度 + * @returns {[number, number, string, string] | null} [纬度, 经度, 所属地级, adcode] + */ +function pickCounty(name, lat, lon) { + const v = DV.COUNTY_DV[name]; + if (!v) return null; + const list = (Array.isArray(v) && Array.isArray(v[0])) ? v : [v]; + if (list.length === 1) return list[0]; + let best = null; + for (const c of list) { + const d = U.haversine(lat, lon, c[0], c[1]); + if (!best || d < best.d) best = { c, d }; + } + return best ? best.c : null; +} + +/** + * 就近最近的县级行政区（DataV 官方县级表）。 + * 县比地级小得多，所以「最近县」比「最近地级」精确得多——桂黔边境 + * 荔波县与河池市相距不到 40km，按地级中心点会分错，按县不会。 + * + * 注意：这是**兜底**路径，主力是按名字精确查（lookupAdminByName）。 + * 按中心点距离在狭长县上仍会判错（环江县中心点远在贵州方向）。 + */ +function nearestCounty(lat, lon) { + if (!Number.isFinite(lat) || !Number.isFinite(lon)) return null; + let best = null; + for (const [name, coord] of Object.entries(DV.COUNTY_DV || {})) { + if (!coord) continue; + // 同名县在表里是数组（每个候选各自有中心点），要展平后逐个比距离 + const list = (Array.isArray(coord) && Array.isArray(coord[0])) ? coord : [coord]; + for (const c of list) { + if (!c) continue; + const d = U.haversine(lat, lon, c[0], c[1]); + if (!best || d < best.d) best = { county: name, d, prefecture: c[2] || '' }; + } + } + // 60km 外基本就不是「这一片」了，县级行政区一般也就横跨 30~60km + return best && best.d <= 60 ? best : null; +} + +/** + * 由「最近县」推导所属地级。 + * 优先用 GB/T 2260 编码前缀（县级表第三项，已离线算好）， + * 没有编码时退回「按坐标找最近地级」。 + */ +function prefectureOfCounty(countyHit, lat, lon) { + if (countyHit && countyHit.prefecture) return countyHit.prefecture; + const near = nearestArea(lat, lon); + return near ? near.area : ''; +} + +/** + * 按**名称**精确查行政区（不靠距离）。 + * + * 这是归属判定的主力路径：OSM 的 `addr:county` / Photon 的 `county` + * 有时直接就是标准县名（「环江毛南族自治县」「大化瑶族自治县」）， + * 此时按名字查官方表是 100% 准确的，比「按中心点找最近的县」可靠得多 + * （桂黔边境的狭长县，中心点距离会判到隔壁省去）。 + * + * **必须带距离校验**：全国有同名县（「城中区」柳州西宁都有、 + * 「鼓楼区」福州南京都有），只看名字会把柳州的点归到西宁去。 + * 查到的县离候选点太远（>80km）就判定为不可信，退回按坐标近邻。 + * + * @param {number} lat 候选点纬度 + * @param {number} lon 候选点经度 + * @returns {{ area: string, detail: string } | null} + */ +function lookupAdminByName(name, lat, lon) { + const raw = String(name || '').trim(); + if (!raw) return null; + // 县级：全称 → 别名 + const isExact = !!DV.COUNTY_DV[raw]; + const full = isExact ? raw : (DV.COUNTY_ALIAS[raw] || null); + if (full && DV.COUNTY_DV[full]) { + // 同名县在表里是数组，按坐标取最近的那个（否则柳州的「城中区」会落到西宁） + const c = pickCounty(full, lat, lon); + if (!c) return null; + // 距离阈值分两档： + // 精确全称命中（OSM 明确写了这个县名）→ 可信度高，放宽到 150km。 + // 狭长县的中心点离边界可达 80km 以上（大化县中心在西北角， + // 东南角的响水关离中心 85km），按 80km 一刀切会把正确的县名丢掉。 + // 别名/简称命中 → 只说明大致是这片地方，严格一点（80km）。 + const limitKm = (full === raw) ? 150 : 80; + if (tooFar(lat, lon, c, limitKm)) return null; // 同名县但离得远 → 不可信 + // 同名县组（如「城中区」有 2 个候选）必须选**距离最近**的那个： + // pickCounty 已经按距离挑了，但还要确认它明显比同组其他候选更近， + // 否则说明 OSM 这个名字可能是别名/误填。 + const list = DV.COUNTY_DV[full]; + if (Array.isArray(list) && Array.isArray(list[0])) { + const sorted = list + .map((x) => ({ x, d: U.haversine(lat, lon, x[0], x[1]) })) + .sort((a, b) => a.d - b.d); + // 最近的这个比第二名远 1.5 倍以上 → 判为误匹配 + if (sorted[1] && sorted[0].d > sorted[1].d * 1.5 && sorted[0].d > 30) return null; + } + return { area: c[2], detail: full }; + } + // 名字本身是地级（OSM 常常把地级填进 county 字段） + const pref = DV.PREF_DV[raw] ? raw : (DV.PREF_ALIAS[raw] || null); + if (pref && DV.PREF_DV[pref]) { + const p = DV.PREF_DV[pref]; + // 地级可以很大（新疆的市跨几百公里），阈值放宽 + if (!tooFar(lat, lon, p, 200)) return { area: pref, detail: '' }; + return null; + } + return null; +} + +/** + * 查到的行政区离候选点是否太远（超过 limitKm 判为同名误匹配）。 + * 县一般横跨 30~60km，80km 是上限；地级市可以很大，用 200km。 + */ +function tooFar(lat, lon, coord, limitKm) { + if (!Number.isFinite(lat) || !Number.isFinite(lon)) return false; + if (!coord) return false; + return U.haversine(lat, lon, coord[0], coord[1]) > limitKm; +} + +async function attachPlaces(candidates, cfg) { + const need = candidates.filter((c) => !c.city && c.kind !== '城市'); + if (need.length && cfg.AMAP_KEY) { + // 串行 + 间隔：高德 regeo 并发 3 就会限流，失败的候选会退回街道名当分组名 + // （出现过「坡进屯」「内塘屯」这种没法看的一组）。实测串行 20 个约 730ms。 + for (const c of need) { + try { + const p = await amapPlaceOf(c.lat, c.lon, cfg); + if (p) { + c.city = p.city; + c.district = p.district || c.district || ''; + c.province = p.province || ''; + } + } catch (err) { + console.warn('[attachPlaces]', c.name, err.message); + } + await new Promise((r) => setTimeout(r, 60)); + } + } + for (const c of candidates) { + // 内置城市库：名字本身就是地名（柳州市），它是这一组的地名节点。 + // + // 但「城市」这个 kind 也可能来自 Photon 的 `osm.place.city` 检索， + // 而 OSM 的 place=city 里混着大量**景点 POI**（牌坊、寺庙、老街）。 + // 那些名字不是行政区，不能拿来当组名——否则会出现 + // 「社更穿洞北门」自己成一组、「柳州之门」自己成一组这种荒唐结果。 + // 所以必须先校验名字确实是行政区名，否则走下面的正常归属流程。 + if (c.kind === '城市' && isPrefectureName(c.name) && isKnownPrefecture(c.name)) { + c.place = c.name; + c.placeKey = placeKey(c.name) || c.name; + c.placeDetail = ''; + continue; + } + const city = String(c.city || '').trim(); + const district = String(c.district || '').trim(); + if (city) { + c.place = city; + c.placeKey = placeKey(city) || city; + c.placeDetail = district && district !== city && isDistrictName(district) ? district : ''; + continue; + } + // 内置库（知名景区 / 小众地点）：查离线归属表，最准，优先用 + const hit = adminAreaOf(c); + if (hit) { + c.place = hit.area; + c.placeKey = placeKey(hit.area) || hit.area; + c.placeDetail = hit.detail || ''; + continue; + } + + // OSM 系（Photon / Overpass）：优先用 OSM 自带的归属字段**按名字精确查**。 + // + // 为什么不能一律「按坐标找最近的县」：桂黔边境的县界狭长， + // 「环江喀斯特世界自然遗产」实际在环江县（河池市），但按中心点距离 + // 会判到隔壁的荔波县（黔南州）——差 45km 完全够跨省。 + // OSM 的 addr:county 在多数条目上直接写了标准县名，按名字查是准的。 + // + // OSM 的层级字段本身不可靠（county 有时填县名、有时填地级， + // city 有时填村名），所以三个字段都试一遍，取第一个查得到的。 + if (c.osmCounty || c.osmCity || c.osmDistrict) { + // 先在所有字段里找**县级**（下层地名），找不到再退到地级。 + // OSM 常常把地级填进 county、把县名填进 city（「黔南州」+「荔波县」）， + // 若只看第一个字段就定案，下层地名会丢。 + let countyHitName = null; + let areaHit = null; + for (const raw of [c.osmCounty, c.osmCity, c.osmDistrict]) { + if (!raw) continue; + const hit = lookupAdminByName(raw, c.lat, c.lon); + if (!hit) continue; + if (hit.detail) { countyHitName = hit.detail; areaHit = hit.area; break; } + if (!areaHit) areaHit = hit.area; + } + if (areaHit) { + c.place = areaHit; + c.placeKey = placeKey(areaHit) || areaHit; + c.placeDetail = countyHitName && countyHitName !== areaHit ? countyHitName : ''; + continue; + } + // 名字查不到：退回按坐标找最近的县 + const countyHit = nearestCounty(c.lat, c.lon); + const area = countyHit ? prefectureOfCounty(countyHit, c.lat, c.lon) : ''; + if (area) { + c.place = area; + c.placeKey = placeKey(area) || area; + const detail = countyHit ? countyHit.county : (isDistrictName(c.osmCity) ? c.osmCity : ''); + c.placeDetail = detail && detail !== area ? detail : ''; + continue; + } + // 县级表没覆盖到：退回 OSM 的 county 字段，但必须校验它是地级 + const area2 = isPrefectureName(c.osmCounty) ? c.osmCounty : ''; + if (area2) { + c.place = area2; + c.placeKey = placeKey(area2) || area2; + c.placeDetail = c.osmCity && c.osmCity !== area2 && isDistrictName(c.osmCity) ? c.osmCity : ''; + continue; + } + if (c.osmCity) { + const lift = nearestArea(c.lat, c.lon); + c.place = lift ? lift.area : c.osmCity; + c.placeKey = placeKey(c.place) || c.place; + c.placeDetail = lift && isDistrictName(c.osmCity) ? c.osmCity : ''; + continue; + } + } + + // 最后兜底：按坐标找最近的地级市（全国地级表 + 内置城市库） + const near = nearestArea(c.lat, c.lon); + if (near) { + c.place = near.area; + c.placeKey = placeKey(near.area) || near.area; + c.placeDetail = ''; + continue; + } + // 实在查不到：退回内置库的 region，至少不丢信息 + const seg = String(c.region || '').split('·').map((s) => s.trim()).filter(Boolean); + c.place = seg.length ? seg[seg.length - 1] : ''; + c.placeKey = placeKey(c.place) || c.place; + c.placeDetail = seg.length > 1 ? seg[0] : ''; + } + return candidates; +} + async function discoverCandidates(origin, radiusKm, cfg, opts = {}) { // 候选发现缓存键：起点 + 半径 + 排除同城设置。Photon 限流严重，重复分析时必须复用。 const dkey = `disc:${U.round(origin.lat, 3)},${U.round(origin.lon, 3)}:${Math.round(radiusKm)}:${opts.excludeLocal !== false}:${opts.localKm || ''}:${opts.homeDistrict || ''}:${opts.homeCity || ''}`; @@ -767,6 +1390,76 @@ async function discoverCandidates(origin, radiusKm, cfg, opts = {}) { } for (const c of amapPois || []) pool.push(c); + // Overpass 兜底：只在 Photon 全部失败时才启用（单次查询要 20~120 秒） + let overpassCount = 0; + let overpassError = ''; + if (photonOk === 0 && !(amapPois || []).length) { + // 兜底路径的总时限预算。公共实例经常「连着不返回」， + // 没有总预算的话一次分析能被拖成十几分钟（实测踩过）。 + // 超时后直接放弃兜底，清单退回内置地名库（+ dataNotes 里说明实时检索不可用）。 + const budgetMs = Math.max(10000, (Number(cfg.SEARCH?.overpassTimeoutMs) || 20000) * 4); + const deadline = Date.now() + budgetMs; + try { + const els = await overpassQuery(origin, radiusKm, cfg); + // 兴趣点大多没有 addr:* 标签，要靠行政区反查归属 + let areas = null; + try { + areas = await overpassAdminAreas(origin, radiusKm, cfg); + } catch (e2) { + console.warn('[overpass] 行政区边界拿不到，归属将退化', e2.message); + } + // 逐点 is_in 反查是**最慢**的一环（每个点每个镜像都要等一次超时）， + // 必须限量：超过上限后不再精确反查，剩下的点靠 bbox 行政区中心点近邻判定 + // （近似，但一次请求覆盖全部候选，慢不到一个数量级）。 + const isInMax = Number(cfg.SEARCH?.overpassIsInMax) || 8; + let isInUsed = 0; + for (const el of els) { + const c = overpassCandidate(el, origin, cfg); + if (!c) continue; + if (JUNK_NAME.test(c.name) || POOR_NAME.test(c.name) || LOW_VALUE_NAME.test(c.name)) continue; + if (c.distanceKm > radiusKm * 1.05) continue; + if (!c.osmCounty) { + // 先用 bbox 内的行政区中心点做近邻判定（一次请求覆盖全部） + let hit = areas ? areaByPoint(areas, c.lat, c.lon) : null; + // 近邻判定拿不到（中心点离边界太远）时，逐点用 is_in 精确反查 + if (!hit && isInUsed < isInMax) { + isInUsed += 1; + // 超预算就停止精确反查，但**候选照常入池**： + // 归属还有离线官方表兜底（attachPlaces 会按坐标找最近的县）， + // 不能因为反查超时就丢掉整个候选。 + if (Date.now() > deadline) { + console.warn('[overpass] 兜底路径超出时限预算，停止精确反查'); + isInUsed = isInMax; + } else { + try { + hit = await overpassAdminAtPoint(c.lat, c.lon, cfg); + } catch (e3) { + console.warn('[overpass-isin]', c.name, e3.message); + } + } + } + if (hit) { + // 字段摆位要和 attachPlaces 的读取顺序对齐： + // attachPlaces 是「先在 county/city/district 里找**县级**，找不到再退地级」， + // 所以县级名必须放 osmCounty、地级名放 osmCity。 + // 反过来（地级放 county）会让兜底路径永远丢掉下层县名。 + if (hit.detail) { + c.osmCounty = hit.detail; + c.osmCity = hit.area || ''; + } else { + c.osmCity = hit.area || ''; + } + } + } + pool.push(c); + overpassCount += 1; + } + } catch (e) { + overpassError = e.message || String(e); + console.warn('[overpass]', overpassError); + } + } + // 内置知名目的地：既做兜底，也常年补入若干高辨识度地点 let curatedCount = 0; for (const [name, lat, lon, kind, tagStr] of CURATED) { @@ -905,11 +1598,16 @@ async function discoverCandidates(origin, radiusKm, cfg, opts = {}) { } } + // 分组：给每个候选补上「归属地名」，第二步按地名分组展示 + await attachPlaces(selected, cfg); + return { candidates: selected.map((c, i) => ({ ...c, index: i })), stats: { photonOk, categoryHits, curatedCount, cityCount, nicheCount, + overpassCount, + overpassError: overpassError || '', amapCount: (amapPois || []).length, amapError: amapError || '', poolSize: unique.length, @@ -1292,5 +1990,5 @@ module.exports = { reverseGeocode, amapReverse, discoverCandidates, bestWeatherWindow, fetchWeather, fetchAQI, aqiLabel, roadMatrix, railMatrix, estimateRoad, estimateRail, - amapResolvePlace, + amapResolvePlace, attachPlaces, placeKey, }; diff --git a/preview/preview-step2-full.png b/preview/preview-step2-full.png new file mode 100644 index 0000000000000000000000000000000000000000..5f2eb446c60b300de535d5887500ebaa4040423d GIT binary patch literal 280108 zcmd?RWl&pR^fua3iWaBE-MvV0DK0JU-r_|I6o;fmN^lEKpg?geP@qVlxI=M=65KUt z0ypLN{@d^@o{_*G$;UiTASv}vZ{UywIR8vUI<07e+OAtg#r4OB$KJ;a$$}C4&v|MgM z0hrfhJNx*kFsUAlR`5rM-4;w^ry?guZ*z1&bj0FRb#Lh3zromFV`Ez543zQe-1#I9 z`Cc?}3tb5~I&XicMO`*w=hJBB8b@}2d5s7L{c8@)V|!k#`D4xkMnjv6S>>RBSG)8B zbXb#u80p_;7)g 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z%74lZO6~oGO~oGsJ#wNhx89|c>rML}D71iG`su?C1KZKOWBZz({##4)U(foM2iOsh kmv(F;6S&k~KC0Uz(AK||3H>DSv-!yl1IX11z1!jc2m10gf&c&j literal 0 HcmV?d00001 diff --git a/public/app.js b/public/app.js index 262697f..8eecafc 100644 --- a/public/app.js +++ b/public/app.js @@ -68,6 +68,12 @@ const state = { sort: 'score', onlyRec: false, onlyNiche: false, + // 候选搜索关键词（按地名/景点名/标签过滤） + search: '', + // 第二步是否按「归属地名」分组展示 + groupByPlace: true, + // 已折叠的地名分组 + collapsedPlaces: new Set(), compareOpen: false, autoPreselected: false, datesTouched: false, @@ -490,7 +496,7 @@ function cardHtml(c) {

${esc(c.name)}

-
${esc(c.kind || '目的地')}${c.region ? ' · ' + esc(c.region) : ''} · ${compassCN(c.bearingDeg)}方向 ${fmtKm(c.distanceKm)}
+
${esc(c.kind || '目的地')}${c.placeDetail ? ' · ' + esc(c.placeDetail) : (c.region && !state.groupByPlace ? ' · ' + esc(c.region) : '')} · ${compassCN(c.bearingDeg)}方向 ${fmtKm(c.distanceKm)}
${scoreRing(c.score)}
@@ -523,24 +529,121 @@ function sortedCandidates() { }); if (state.onlyRec) list = list.filter((c) => c.score >= 60); if (state.onlyNiche) list = list.filter((c) => c.niche); + const q = (state.search || '').trim().toLowerCase(); + if (q) { + // 搜索范围要覆盖分组名：搜「柳州」应该能命中「柳州古城」「融水双龙沟」 + // 这类分属柳州/融水两个地名的条目，否则用户会以为搜不到 + list = list.filter((c) => { + const hay = [ + c.name, c.place, c.placeDetail, c.kind, c.region, + ...(c.tags || []), + ].filter(Boolean).join(' ').toLowerCase(); + return hay.includes(q); + }); + } return list; } + +/** + * 按「归属地名」分组。 + * + * 为什么要分组：候选里既有地名（柳州市、桂林市这类城市级目的地）， + * 又有具体景点（柳州古城、融水双龙沟），平铺在一起看不出层级， + * 也不知道某个景点属于哪片地方。分组后是「地名 → 景点」两级。 + */ +function groupByPlace(list) { + const map = new Map(); + for (const c of list) { + const key = c.placeKey || c.place || '其他'; + if (!map.has(key)) map.set(key, { key, place: c.place || '其他', detail: '', items: [] }); + const g = map.get(key); + g.items.push(c); + // 组副标题取出现最多的区县，作为该组的地理说明 + if (c.placeDetail && !g.detail.includes(c.placeDetail)) { + g.detail = g.detail ? `${g.detail}、${c.placeDetail}` : c.placeDetail; + } + } + const groups = [...map.values()]; + // 组内最高分高的排前面；同分按最近距离 + groups.forEach((g) => { + g.best = g.items.reduce((m, c) => Math.max(m, c.score || 0), 0); + g.nearest = g.items.reduce((m, c) => Math.min(m, c.distanceKm ?? 1e9), 1e9); + }); + groups.sort((a, b) => b.best - a.best || a.nearest - b.nearest); + return groups; +} + +/** 组标题：地名 + 景点数 + 该组最佳分与距离 */ +function placeGroupHtml(g) { + const collapsed = state.collapsedPlaces.has(g.key); + const sample = g.items[0]; + const dirs = [...new Set(g.items.map((c) => compassCN(c.bearingDeg)))]; + const maxKm = Math.max(...g.items.map((c) => c.distanceKm || 0)); + const minKm = Math.min(...g.items.map((c) => c.distanceKm || 0)); + const distTxt = maxKm - minKm < 1 + ? fmtKm(minKm) + : `${fmtKm(minKm)} ~ ${fmtKm(maxKm)}`; + return `
+ +
${g.items.map(cardHtml).join('')}
+
`; +} + function renderCards() { const list = sortedCandidates(); // 重渲染会重建 DOM：先记住哪些逐日天气是展开的，避免勾选/排序后莫名收起 const openDays = new Set($$('#cards .daily[open]').map((d) => d.dataset.day)); const noBase = !(state.analysis?.candidates || []).length; - $('#cards').innerHTML = list.length - ? list.map(cardHtml).join('') - : `
${noBase + const total = (state.analysis?.candidates || []).length; + const cardsBox = $('#cards'); + cardsBox.classList.toggle('has-groups', state.groupByPlace && list.length > 0); + if (list.length) { + cardsBox.innerHTML = state.groupByPlace + ? groupByPlace(list).map(placeGroupHtml).join('') + : list.map(cardHtml).join(''); + } else { + cardsBox.innerHTML = `
${noBase ? `当前半径内没有可去的地点${state.analysis?.constraints?.excludeLocal ? '（已排除出发地附近的同城点位）' : ''}，试试取消「排除同城」或增大搜索半径。` - : state.onlyNiche - ? '当前半径内没有小众地点，试试取消「只看小众」或增大搜索半径。' - : '没有符合筛选条件的目的地，试试取消「仅显示推荐」或「只看小众」。'}
`; + : state.search + ? `没有匹配「${esc(state.search)}」的地点，换个关键词，或取消筛选条件。` + : state.onlyNiche + ? '当前半径内没有小众地点，试试取消「只看小众」或增大搜索半径。' + : '没有符合筛选条件的目的地，试试取消「仅显示推荐」或「只看小众」。'}
`; + } $$('#cards .daily').forEach((d) => { if (openDays.has(d.dataset.day)) d.open = true; }); $$('#cards .pick-btn').forEach((b) => b.addEventListener('click', () => togglePick(b.dataset.id))); + // 组标题折叠：只动 class，不重渲染（重渲染会丢失滚动位置与展开态） + $$('#cards [data-place-toggle]').forEach((btn) => { + btn.addEventListener('click', () => { + const key = btn.dataset.placeToggle; + if (state.collapsedPlaces.has(key)) state.collapsedPlaces.delete(key); + else state.collapsedPlaces.add(key); + const sec = btn.closest('.place-group'); + const items = sec?.querySelector('.place-items'); + const collapsed = state.collapsedPlaces.has(key); + btn.setAttribute('aria-expanded', collapsed ? 'false' : 'true'); + btn.querySelector('.place-caret').textContent = collapsed ? '▸' : '▾'; + if (items) items.classList.toggle('collapsed', collapsed); + }); + }); $('#selectedCount').textContent = `已选 ${state.selected.size} 个`; $('#preselectHint').classList.toggle('hidden', !state.autoPreselected); + // 筛选提示条：告诉用户「当前显示多少 / 共多少」，否则筛完不知道漏了什么 + const fn = $('#filterNote'); + const filtered = list.length !== total || state.onlyRec || state.onlyNiche || state.search; + fn.classList.toggle('hidden', !filtered); + if (filtered) { + fn.innerHTML = `当前显示 ${list.length} / ${total} 个目的地` + + (state.search ? ` · 搜索「${esc(state.search)}」` : '') + + (state.onlyRec ? ' · 仅推荐及以上' : '') + + (state.onlyNiche ? ' · 仅小众' : '') + + (state.groupByPlace ? ` · 已按 ${groupByPlace(list).length} 个地名分组` : ''); + } renderCompass(list, state.analysis.constraints.radiusKm); renderCompare(); } @@ -1673,6 +1776,29 @@ function init() { })); $('#onlyRec').addEventListener('change', (e) => { state.onlyRec = e.target.checked; renderCards(); }); $('#onlyNiche').addEventListener('change', (e) => { state.onlyNiche = e.target.checked; renderCards(); }); + $('#groupByPlace').addEventListener('change', (e) => { state.groupByPlace = e.target.checked; renderCards(); }); + + // 候选搜索：输入即过滤，不用等回车。回车要阻止默认行为， + // 否则在输入框里按回车会触发表单提交刷新页面 + const searchInput = $('#candSearch'); + let searchTimer = null; + searchInput.addEventListener('input', (e) => { + const v = e.target.value; + $('#candSearchClear').classList.toggle('hidden', !v); + clearTimeout(searchTimer); + searchTimer = setTimeout(() => { state.search = v; renderCards(); }, 160); + }); + searchInput.addEventListener('keydown', (e) => { + if (e.key === 'Enter') { e.preventDefault(); clearTimeout(searchTimer); state.search = e.target.value; renderCards(); } + if (e.key === 'Escape') { e.target.value = ''; state.search = ''; $('#candSearchClear').classList.add('hidden'); renderCards(); } + }); + $('#candSearchClear').addEventListener('click', () => { + searchInput.value = ''; + state.search = ''; + $('#candSearchClear').classList.add('hidden'); + renderCards(); + searchInput.focus(); + }); $('#compareBtn').addEventListener('click', toggleCompare); $('#planBtn').addEventListener('click', () => runPlan()); diff --git a/public/index.html b/public/index.html index aa066b3..00fa15c 100644 --- a/public/index.html +++ b/public/index.html @@ -5,7 +5,7 @@ 行知 · 周边出行顾问 | TripSense - +
@@ -149,13 +149,19 @@
+
+ + +
+ 已选 0 个 +
@@ -319,6 +325,6 @@ - + diff --git a/public/styles.css b/public/styles.css index b30aa7a..8b8a579 100644 --- a/public/styles.css +++ b/public/styles.css @@ -691,6 +691,67 @@ input[type="range"] { width: 100%; accent-color: var(--accent); } /* 两张卡内容长度差很多，按 start 对齐，别互相拉伸 */ .plan-extra { align-items: start; } +/* ------------------------------------------------- 第二步：搜索 + 地名分组 */ +.search-box { position: relative; display: flex; align-items: center; } +.search-box input[type="search"] { + width: 230px; padding: 7px 30px 7px 11px; + border: 1px solid var(--rule-strong); border-radius: 8px; + background: var(--sheet); color: var(--ink); font-size: 12.5px; + transition: border-color .15s, box-shadow .15s; +} +.search-box input[type="search"]::-webkit-search-cancel-button { display: none; } +.search-box input[type="search"]::placeholder { color: var(--muted); } +.search-box input[type="search"]:focus { + outline: none; border-color: var(--accent); box-shadow: 0 0 0 3px rgba(47, 111, 237, .12); +} +.search-clear { + position: absolute; right: 6px; border: 0; background: transparent; + color: var(--muted); font-size: 13px; line-height: 1; padding: 3px 5px; border-radius: 5px; +} +.search-clear:hover { background: var(--paper-2); color: var(--ink); } + +/* 筛选提示条：告诉用户「当前显示多少 / 共多少」以及生效了哪些条件 */ +.filter-note { + font-family: var(--mono); font-size: 11.5px; color: var(--ink-soft); + background: var(--sheet-2); border: 1px solid var(--rule); border-left: 3px solid var(--accent); + border-radius: 8px; padding: 8px 12px; margin-bottom: 14px; line-height: 1.7; +} +.filter-note b { color: var(--accent); font-weight: 700; } + +/* 地名分组：组标题是按钮，下面缩进放景点卡片 */ +.cards.has-groups { display: block; } +.place-group { margin-bottom: 22px; } +.place-head { + display: flex; align-items: baseline; gap: 9px; flex-wrap: wrap; + width: 100%; text-align: left; padding: 9px 12px; margin-bottom: 12px; + background: var(--sheet-2); border: 1px solid var(--rule-strong); border-left: 4px solid var(--accent); + border-radius: 8px; transition: .15s ease; +} +.place-head:hover { background: var(--accent-soft); border-color: var(--accent); } +.place-caret { color: var(--accent); font-size: 11px; flex: 0 0 auto; } +.place-name { font-family: var(--serif); font-size: 16px; font-weight: 700; color: var(--ink); } +.place-detail { + font-size: 11.5px; color: var(--ink-soft); background: var(--sheet); + border: 1px solid var(--rule); border-radius: 999px; padding: 2px 9px; +} +.place-meta { + margin-left: auto; font-family: var(--mono); font-size: 11px; color: var(--muted); + white-space: nowrap; +} +.place-items { + display: grid; grid-template-columns: repeat(2, minmax(0, 1fr)); gap: 16px; + align-items: start; padding-left: 16px; border-left: 2px dashed var(--rule-strong); + margin-left: 6px; +} +.place-items.collapsed { display: none; } + +@media (max-width: 720px) { + .search-box input[type="search"] { width: 100%; } + .search-box { flex: 1 1 100%; } + .place-items { grid-template-columns: 1fr; padding-left: 10px; } + .place-meta { margin-left: 0; width: 100%; } +} + @media (max-width: 900px) { .plan-extra { grid-template-columns: 1fr; } } diff --git a/tools/build-admin-dv.cjs b/tools/build-admin-dv.cjs new file mode 100644 index 0000000..cbedadb --- /dev/null +++ b/tools/build-admin-dv.cjs @@ -0,0 +1,156 @@ +#!/usr/bin/env node +/** + * 由 DataV 行政区划原始数据生成离线归属表。 + * + * 产出 lib/places-admin-dv.js： + * COUNTY_DV 县级 → [纬度, 经度, 所属地级名, adcode] + * PREF_DV 地级 → [纬度, 经度, adcode] + * + * 为什么不用 OSM 那套：OSM 中国的 admin_level 层级不可靠、编码只有 50% 覆盖， + * 只能靠「按中心点猜」；DataV 用的是国家民政部 adcode 体系， + * 县级前 4 位就是所属地级码，**100% 准确**，不需要猜。 + * + * 用法：node tools/build-admin-dv.cjs C:/tmp/datav-admin.json + */ +const fs = require('fs'); +const path = require('path'); +const { shortPrefecture } = require('./lib-short-name.cjs'); + +const src = process.argv[2] || 'C:/tmp/datav-admin.json'; +const out = path.join(__dirname, '..', 'lib', 'places-admin-dv.js'); + +const d = JSON.parse(fs.readFileSync(src, 'utf8')); + +// 地级：level==city 且 adcode 以 00 结尾的条目。 +// 键统一用简称（「黔南布依族苗族自治州」→「黔南州」），与运行时 placeKey 一致。 +// +// **关键区分**：DataV 把「省直辖县级单位」也标成 level=city +// （海南的东方市/昌江黎族自治县、新疆兵团的石河子市、湖北的仙桃市…）， +// 但它们的 adcode 不以 00 结尾（46**9001**、65**9001**、42**9001**）。 +// 行政区划代码里「地级市用 xx00、省直辖县级用 9xxx 段」是固定规则， +// 不按这个分就会把县级市当成地级市，归属会整整差一级。 +const prefecture = {}; +const prefectureFull = {}; +for (const c of d.cities) { + if (c.level !== 'city') continue; + if (!c.centroid) continue; + if (!/00$/.test(c.adcode)) continue; + const short = shortPrefecture(c.name); + prefecture[short] = [c.centroid[1], c.centroid[0], c.adcode]; + prefectureFull[short] = c.name; +} + +// 省级直辖县级单位（海南的东方市、新疆兵团的石河子市…）：行政上是「县」， +// 上级直接是省，没有地级市这一层 —— 所以它们的归属地级就是省名。 +const directCounties = []; +for (const c of d.cities) { + if (!c.centroid) continue; + const isCityLevel = c.level === 'city'; + if (isCityLevel && /00$/.test(c.adcode)) continue; // 真正的地级市，上面已处理 + directCounties.push(c); +} + +// 县级 → 地级 +// +// **同名县必须保留全部候选**：全国有 22 组同名县（「城中区」柳州/西宁都有、 +// 「鼓楼区」南京/徐州/福州/开封都有、「铁西区」沈阳/鞍山/四平都有）。 +// 只留一个会把柳州的点归到西宁去。 +// 所以同名时值是**数组**，运行时按坐标距离选最近的那个。 +const county = {}; +// 注意：county[name] **永远**是数组（同名县有多个候选）。 +// 不能写成「单值，冲突时升级成数组」——单值本身也是数组， +// Array.isArray 会把「第一次写入的条目」误判成「同名组」， +// 结果第二个同名县被 push 进第一个县的四元组里，表直接被污染。 +function addCounty(name, entry) { + if (!county[name]) county[name] = []; + // 同 adcode 视为同一条（例如直辖县级既在 cities 又在 counties 里出现） + if (county[name].some((e) => e[3] === entry[3])) return; + county[name].push(entry); +} +for (const c of d.counties) { + if (!c.centroid) continue; + // 地级名统一简称化（「黔南布依族苗族自治州」→「黔南州」） + const pref = shortPrefecture(c.city || c.province || ''); + addCounty(c.name, [c.centroid[1], c.centroid[0], pref, c.adcode]); +} +// 直辖县级（北京/上海/重庆/港澳台等）由省级文件直接给出 +for (const c of directCounties) { + const pref = shortPrefecture(c.province || ''); + addCounty(c.name, [c.centroid[1], c.centroid[0], pref, c.adcode]); + if (!prefecture[pref]) { + prefecture[pref] = [c.centroid[1], c.centroid[0], c.provinceAdcode]; + prefectureFull[pref] = pref; + } +} +// 只有一组的压回单值，减少运行时分支；多组保持数组 +for (const k of Object.keys(county)) { + if (county[k].length === 1) county[k] = county[k][0]; +} + +// 名称索引：允许用「短名/别名」查 +// DataV 只给全称，但 OSM/高德常写「环江县」「荔波县」「罗城」这类简称或去族名写法， +// 统一在这里做归一，避免运行时各写一套。 +// 分成两张表：县级别名 → 县全称；地级别名 → 地级简称。 +// 混在一张表里会因为「同名县/市」互相覆盖而查错。 +const countyAlias = {}; +const prefAlias = {}; +function regAlias(table, key, full) { + if (!full || !key || key === full) return; + if (!table[key]) table[key] = full; +} +/** + * 剥掉地名里的民族名块。 + * 不能用 `[一-龥]{1,3}族` 这种贪婪正则——「环江毛南族自治县」会把 + * 「江毛南族」整段吃掉变成「环自治县」（实测）。必须用**已知的民族名清单**。 + * 顺序很重要：先去掉「自治县/自治州」尾巴，民族名块才会露在末尾。 + */ +const ETHNIC_LIST = require('./lib-short-name.cjs').ETHNIC; +function stripEthnic(name) { + let s = name.replace(/自治(县|旗|州|区)$/, ''); + let changed = true; + while (changed) { + changed = false; + for (const eth of ETHNIC_LIST) { + if (s.endsWith(eth)) { s = s.slice(0, -eth.length); changed = true; } + } + } + return s.replace(/(?:[\u4e00-\u9fa5]{1,3}族)+$/, ''); +} +for (const name of Object.keys(county)) { + const noEthnic = stripEthnic(name); // 环江毛南族自治县 → 环江 + regAlias(countyAlias, noEthnic, name); + regAlias(countyAlias, noEthnic + '县', name); // → 环江县 + regAlias(countyAlias, noEthnic + '旗', name); + regAlias(countyAlias, name.replace(/自治(县|旗)$/, (m, g) => g), name); // 环江毛南族县 + regAlias(countyAlias, name.replace(/自治(县|旗)$/, ''), name); // 环江毛南族 +} +for (const [name, full] of Object.entries(prefectureFull)) { + // 值统一是地级**简称**（PREF_DV 的键），否则运行时查 PREF_DV 会落空 + regAlias(prefAlias, full, name); // 黔南布依族苗族自治州 → 黔南州 + regAlias(prefAlias, stripEthnic(full), name); + regAlias(prefAlias, name.replace(/(市|地区|盟)$/, ''), name); // 河池市 → 河池 +} + +const js = `/** + * 行政区划离线表（阿里 DataV GeoAtlas 数据，自动生成，请勿手改） + * + * 数据源：https://geo.datav.aliyun.com/areas_v3/bound/{adcode}_full.json（免密钥） + * 层级：国家民政部 adcode 体系（省级 2 位 / 地级 4 位 / 县级 6 位） + * + * COUNTY_DV 县级名 → [纬度, 经度, 所属地级名, adcode] + * PREF_DV 地级简称 → [纬度, 经度, adcode] + * COUNTY_ALIAS 县别名/简称 → 县全称 + * PREF_ALIAS 地级别名/全称 → 地级简称 + * + * 生成：node tools/build-admin-dv.cjs C:/tmp/datav-admin.json + */ +const COUNTY_DV = ${JSON.stringify(county)}; +const PREF_DV = ${JSON.stringify(prefecture)}; +const COUNTY_ALIAS = ${JSON.stringify(countyAlias)}; +const PREF_ALIAS = ${JSON.stringify(prefAlias)}; +module.exports = { COUNTY_DV, PREF_DV, COUNTY_ALIAS, PREF_ALIAS }; +`; + +fs.writeFileSync(out, js); +console.log(`县级 ${Object.keys(county).length}，地级 ${Object.keys(prefecture).length}，县别名 ${Object.keys(countyAlias).length}，地别名 ${Object.keys(prefAlias).length}`); +console.log('写入', out, (fs.statSync(out).size / 1024).toFixed(0) + 'KB'); diff --git a/tools/build-admin-fix.cjs b/tools/build-admin-fix.cjs new file mode 100644 index 0000000..1f87faf --- /dev/null +++ b/tools/build-admin-fix.cjs @@ -0,0 +1,137 @@ +'use strict'; +/** + * 补齐归属表里缺失的条目（第二轮）。 + * + * 第一轮对「荔波小七孔」这类名字搜不到——Photon 里收录的是「小七孔」这个景点， + * 全名反而搜不到。所以这里做两件事： + * 1. 去掉「风景区/景区/公园/自然保护区/度假区」等后缀再搜一次； + * 2. 搜不到就用「名字里剥掉修饰词的核心词」再搜。 + * 命中后仍然用**坐标距离**在候选里挑最近的，避免同名异地。 + * + * 用法：node tools/build-admin-fix.cjs + */ +const fs = require('fs'); +const path = require('path'); +const cn = require('../lib/places-cn'); +const niche = require('../lib/places-niche').NICHE_SPOTS; + +const PHOTON = 'https://photon.komoot.io/api/'; + +function haversine(lat1, lon1, lat2, lon2) { + const R = 6371; + const dLat = (lat2 - lat1) * Math.PI / 180; + const dLon = (lon2 - lon1) * Math.PI / 180; + const a = Math.sin(dLat / 2) ** 2 + + Math.cos(lat1 * Math.PI / 180) * Math.cos(lat2 * Math.PI / 180) * Math.sin(dLon / 2) ** 2; + return 2 * R * Math.asin(Math.min(1, Math.sqrt(a))); +} + +function pickArea(props) { + const clean = (s) => String(s || '').trim(); + const state = clean(props.state); + const county = clean(props.county); + const city = clean(props.city); + // 优先 county（Photon 里是地级市/州），其次 city（县/区），最后 state + const area = county || city || state; + const detail = county && city && city !== county ? city : ''; + return { area, detail, state, level: county ? 'prefecture' : (city ? 'county' : 'province') }; +} + +/** 名字变体：原名、去后缀、剥掉「XX」前缀的核心词 */ +function variants(name) { + const out = new Set([name]); + const noSuffix = name.replace(/(风景区|景区|旅游区|度假区|自然保护区|森林公园|地质公园|湿地公园|国家公园|风景名胜区|风景区|风景区|景区|景点|公园|博物馆|纪念馆|故居|遗址|石林|峡谷|瀑布|温泉|梯田|草原|湖泊|湿地|海滩|岛|山|湖|园)$/g, '').trim(); + if (noSuffix && noSuffix.length >= 2) out.add(noSuffix); + // 「A小七孔」→「小七孔」这类：去掉末尾的行政区前缀 + const core = noSuffix.replace(/^(.{2,4}?)(?=[\u4e00-\u9fa5]{2,4}$)/, ''); + if (core && core.length >= 2) out.add(core); + return [...out]; +} + +async function query(name) { + for (let i = 0; i < 3; i += 1) { + try { + const u = new URL(PHOTON); + u.searchParams.set('q', name); + u.searchParams.set('limit', '6'); + u.searchParams.set('lang', 'default'); + const res = await fetch(u.toString()); + const text = await res.text(); + if (!text.startsWith('{')) throw new Error('non-json'); + return JSON.parse(text).features || []; + } catch (err) { + if (i === 2) return null; + await new Promise((r) => setTimeout(r, 1200 * (i + 1))); + } + } + return null; +} + +async function lookup(name, lat, lon) { + for (const v of variants(name)) { + const feats = await query(v); + if (!feats || !feats.length) continue; + let best = null; + for (const f of feats) { + const co = f.geometry?.coordinates; + if (!co) continue; + const d = haversine(lat, lon, Number(co[1]), Number(co[0])); + if (!best || d < best.d) best = { d, props: f.properties || {} }; + } + if (!best || best.d > 40) continue; + const area = pickArea(best.props); + if (area.area) return area; + await new Promise((r) => setTimeout(r, 500)); + } + return null; +} + +async function main() { + const file = path.join(__dirname, '..', 'lib', 'places-admin.js'); + const src = fs.readFileSync(file, 'utf8'); + const SPOT_AREA = JSON.parse(src.match(/const SPOT_AREA = (\{.*?\});/s)[1]); + const AREA_COORD = JSON.parse(src.match(/const AREA_COORD = (\{.*?\});/s)[1]); + + const items = []; + for (const s of cn.EXTRA_SCENIC) items.push({ group: 'scenic', name: s[0], lat: s[1], lon: s[2] }); + for (const s of niche) items.push({ group: 'niche', name: s[0], lat: s[1], lon: s[2] }); + + const missing = items.filter((it) => !SPOT_AREA[`${it.group}:${it.name}`]); + console.log('missing', missing.length, '/', items.length); + + let fixed = 0; + for (let i = 0; i < missing.length; i += 1) { + const it = missing[i]; + const area = await lookup(it.name, it.lat, it.lon); + if (area) { + SPOT_AREA[`${it.group}:${it.name}`] = area; + if (!AREA_COORD[area.area]) AREA_COORD[area.area] = [it.lat, it.lon]; + fixed += 1; + } + if ((i + 1) % 10 === 0) console.log(` ${i + 1}/${missing.length} fixed=${fixed}`); + await new Promise((r) => setTimeout(r, 600)); + } + + const body = `'use strict'; +/** + * 内置地点库的归属地名（自动生成，勿手改）。 + * + * 生成方式： + * tools/build-admin.cjs —— 首轮，Photon 按名检索 + 坐标距离消歧 + * tools/build-admin-fix.cjs —— 二轮，去后缀/核心词重试，补首轮搜不到的 + * + * 字段： + * SPOT_AREA { 'scenic:荔波小七孔': { area, detail, state, level } } + * AREA_COORD { '荔波县': [lat, lon] } 各地级/县级名的代表坐标，运行时做最近市兜底 + */ +const SPOT_AREA = ${JSON.stringify(SPOT_AREA)}; + +const AREA_COORD = ${JSON.stringify(AREA_COORD)}; + +module.exports = { SPOT_AREA, AREA_COORD }; +`; + fs.writeFileSync(file, body, 'utf8'); + console.log('written', file, 'entries', Object.keys(SPOT_AREA).length, 'fixed', fixed); +} + +main(); diff --git a/tools/build-admin-normalize.cjs b/tools/build-admin-normalize.cjs new file mode 100644 index 0000000..2ac8c8e --- /dev/null +++ b/tools/build-admin-normalize.cjs @@ -0,0 +1,96 @@ +'use strict'; +/** + * 把归属表里的组名归一到**地级**（市/州/盟/地区）。 + * + * 为什么要这一步：Photon 的 `county` 字段层级并不稳定—— + * 「荔波小七孔」→ county=黔南州（地级）、city=荔波县（县级）✅ + * 「加榜梯田」 → county=从江县（县级）、city=摆别村（村级）❌ + * 直接拿 county 当组名，就会出现「加榜梯田」和「从江县」两个并列的组， + * 而它们其实是同一片（黔南州）。 + * + * 办法：对层级不对的条目，用该景点的坐标在「地级名单」里找最近的（≤120km）， + * 原来的县级名降为 detail（区县说明）。 + * + * 用法：node tools/build-admin-normalize.cjs + */ +const fs = require('fs'); +const path = require('path'); +const cn = require('../lib/places-cn'); +const niche = require('../lib/places-niche').NICHE_SPOTS; + +const file = path.join(__dirname, '..', 'lib', 'places-admin.js'); + +function haversine(lat1, lon1, lat2, lon2) { + const R = 6371; + const dLat = (lat2 - lat1) * Math.PI / 180; + const dLon = (lon2 - lon1) * Math.PI / 180; + const a = Math.sin(dLat / 2) ** 2 + + Math.cos(lat1 * Math.PI / 180) * Math.cos(lat2 * Math.PI / 180) * Math.sin(dLon / 2) ** 2; + return 2 * R * Math.asin(Math.min(1, Math.sqrt(a))); +} + +const isPrefecture = (n) => /(市|州|盟|地区)$/.test(String(n || '').trim()); + +function coordOf(group, name) { + if (group === 'scenic') { + const s = cn.EXTRA_SCENIC.find((x) => x[0] === name); + return s ? [s[1], s[2]] : null; + } + const s = niche.find((x) => x[0] === name); + return s ? [s[1], s[2]] : null; +} + +function main() { + const src = fs.readFileSync(file, 'utf8'); + const SPOT_AREA = JSON.parse(src.match(/const SPOT_AREA = (\{.*?\});/s)[1]); + const AREA_COORD = JSON.parse(src.match(/const AREA_COORD = (\{.*?\});/s)[1]); + + // 地级名单：城市库 + 归属表里层级正确的地名 + const prefectures = new Map(); + for (const [n, la, lo] of cn.CN_CITIES) prefectures.set(n, [la, lo]); + for (const [n, coord] of Object.entries(AREA_COORD)) { + if (isPrefecture(n) && coord) prefectures.set(n, coord); + } + + let fixed = 0; + let unresolved = 0; + for (const [key, entry] of Object.entries(SPOT_AREA)) { + if (isPrefecture(entry.area)) continue; + const [group, name] = [key.slice(0, key.indexOf(':')), key.slice(key.indexOf(':') + 1)]; + const coord = coordOf(group, name); + if (!coord) continue; + let best = null; + for (const [n, c] of prefectures) { + const d = haversine(coord[0], coord[1], c[0], c[1]); + if (!best || d < best.d) best = { n, d }; + } + if (!best || best.d > 120) { unresolved += 1; continue; } + entry.detail = entry.detail || entry.area; + entry.area = best.n; + fixed += 1; + } + + const body = `'use strict'; +/** + * 内置地点库的归属地名（自动生成，勿手改）。 + * + * 生成方式： + * tools/build-admin.cjs —— 首轮，Photon 按名检索 + 坐标距离消歧 + * tools/build-admin-fix.cjs —— 二轮，去后缀/核心词重试，补首轮搜不到的 + * tools/build-admin-normalize.cjs —— 三轮，把组名归一到地级（市/州/盟/地区） + * + * 字段： + * SPOT_AREA { 'scenic:荔波小七孔': { area, detail, state, level } } + * AREA_COORD { '荔波县': [lat, lon] } 各地名代表坐标，运行时做最近市兜底 + */ +const SPOT_AREA = ${JSON.stringify(SPOT_AREA)}; + +const AREA_COORD = ${JSON.stringify(AREA_COORD)}; + +module.exports = { SPOT_AREA, AREA_COORD }; +`; + fs.writeFileSync(file, body, 'utf8'); + console.log('fixed', fixed, 'unresolved', unresolved, 'entries', Object.keys(SPOT_AREA).length); +} + +main(); diff --git a/tools/build-admin.cjs b/tools/build-admin.cjs new file mode 100644 index 0000000..07cf60e --- /dev/null +++ b/tools/build-admin.cjs @@ -0,0 +1,125 @@ +'use strict'; +/** + * 生成内置地点库的归属表（一次性脚本，结果写入 lib/places-admin.js）。 + * + * 背景：第二步要按「地名 → 景点」两级展示，所以每个候选都得知道它属于哪个地级市/州。 + * 内置知名景区库（EXTRA_SCENIC）与小众库（NICHE_SPOTS）里只有坐标，没有归属； + * 高德 POI 自带 cityname/adname 但用户未必配了 Key。 + * + * 办法：用 Photon 按名字搜，再用**坐标距离**在候选结果里挑最近的那个 + * （光按名字会歧义：「灵山」在钦州、「百花山」在百色，都不是京郊那个）。 + * 命中不了就留空，运行时再用「最近地级市」兜底。 + * + * 用法：node tools/build-admin.mjs + */ +const fs = require('fs'); +const path = require('path'); +const cn = require('../lib/places-cn'); +const niche = require('../lib/places-niche').NICHE_SPOTS; + +const PHOTON = 'https://photon.komoot.io/api/'; + +function haversine(lat1, lon1, lat2, lon2) { + const R = 6371; + const dLat = (lat2 - lat1) * Math.PI / 180; + const dLon = (lon2 - lon1) * Math.PI / 180; + const a = Math.sin(dLat / 2) ** 2 + + Math.cos(lat1 * Math.PI / 180) * Math.cos(lat2 * Math.PI / 180) * Math.sin(dLon / 2) ** 2; + return 2 * R * Math.asin(Math.min(1, Math.sqrt(a))); +} + +/** Photon 的层级：state=省, county=地级市/州, city=县/区, district=街道, locality=村 */ +function pickArea(props) { + const clean = (s) => String(s || '').trim(); + const state = clean(props.state); + const county = clean(props.county); + const city = clean(props.city); + const district = clean(props.district); + // 地级优先 county，其次 city（有些地方 county 缺失），最后 state + const area = county || city || state; + const detail = county && city && city !== county ? city : ''; + return { area, detail, state, level: county ? 'prefecture' : (city ? 'county' : 'province') }; +} + +async function query(name, tries = 3) { + for (let i = 0; i < tries; i += 1) { + try { + const u = new URL(PHOTON); + u.searchParams.set('q', name); + u.searchParams.set('limit', '5'); + u.searchParams.set('lang', 'default'); + const res = await fetch(u.toString()); + const text = await res.text(); + if (!text.startsWith('{')) throw new Error('non-json: ' + text.slice(0, 40)); + return JSON.parse(text).features || []; + } catch (err) { + if (i === tries - 1) return null; + await new Promise((r) => setTimeout(r, 1200 * (i + 1))); + } + } + return null; +} + +async function main() { + const items = []; + for (const s of cn.EXTRA_SCENIC) items.push({ name: s[0], lat: s[1], lon: s[2], group: 'scenic' }); + for (const s of niche) items.push({ name: s[0], lat: s[1], lon: s[2], group: 'niche', region: s[5] || '' }); + + const out = {}; + const areas = new Map(); // 地级名 → [lat, lon] + let hit = 0; + for (let i = 0; i < items.length; i += 1) { + const it = items[i]; + // 小众库自带「省 · 市」，先用它当线索，能省一次请求 + const feats = await query(it.name); + let best = null; + if (feats) { + for (const f of feats) { + const co = f.geometry?.coordinates; + if (!co) continue; + const d = haversine(it.lat, it.lon, Number(co[1]), Number(co[0])); + if (!best || d < best.d) best = { d, props: f.properties || {}, co }; + } + } + const area = best ? pickArea(best.props) : null; + // 名字搜到的点离得太远（>60km）基本是同名的另一个地方，不采信 + const trust = best && best.d < 60; + if (trust && area && area.area) { + hit += 1; + out[`${it.group}:${it.name}`] = { area: area.area, detail: area.detail, state: area.state, level: area.level }; + if (area.level === 'prefecture' || area.level === 'county') { + if (!areas.has(area.area)) areas.set(area.area, [it.lat, it.lon]); + } + } else if (it.region) { + // 小众库自带的「省 · 市」也可用，至少是市级 + const seg = it.region.split('·').map((x) => x.trim()).filter(Boolean); + const area2 = seg.length >= 2 ? seg[seg.length - 1] : seg[0]; + if (area2) out[`${it.group}:${it.name}`] = { area: area2, detail: '', state: seg[0] || '', level: 'prefecture' }; + } + if ((i + 1) % 20 === 0) console.log(` ${i + 1}/${items.length} hit=${hit}`); + await new Promise((r) => setTimeout(r, 650)); + } + + const file = path.join(__dirname, '..', 'lib', 'places-admin.js'); + const body = `'use strict'; +/** + * 内置地点库的归属地名（自动生成，勿手改）。 + * + * 生成方式：tools/build-admin.mjs —— 用 Photon 按名检索 + 坐标距离消歧， + * 取回 state/county/city 层级，存成「地级名 + 区县」。 + * + * 字段： + * SPOT_AREA { 'scenic:荔波小七孔': { area, detail, state, level } } + * AREA_COORD { '荔波县': [lat, lon] } 各地级/县级名的代表坐标，运行时做最近市兜底 + */ +const SPOT_AREA = ${JSON.stringify(out, null, 0)}; + +const AREA_COORD = ${JSON.stringify(Object.fromEntries(areas), null, 0)}; + +module.exports = { SPOT_AREA, AREA_COORD }; +`; + fs.writeFileSync(file, body, 'utf8'); + console.log('written', file, 'entries', Object.keys(out).length, 'hit', hit, 'areas', areas.size); +} + +main(); diff --git a/tools/dbg-grouping.cjs b/tools/dbg-grouping.cjs new file mode 100644 index 0000000..7c6a56d --- /dev/null +++ b/tools/dbg-grouping.cjs @@ -0,0 +1,113 @@ +'use strict'; +/** + * 前端分组调试：起本地假 Photon + 服务端，然后在真实页面里读候选字段。 + */ +const { spawn } = require('child_process'); +const path = require('path'); +const os = require('os'); +const http = require('http'); + +const CHROME = 'C:/Program Files/Google/Chrome/Application/chrome.exe'; +const PORT = 9356; +const PHOTON_PORT = 9357; +const sleep = (ms) => new Promise((r) => setTimeout(r, ms)); + +const REAL = [ + ['荔波小七孔', 25.2461, 107.8567, '黔南州', '荔波县'], + ['社更穿洞北门', 24.5701, 107.7234, '河池市', '都安瑶族自治县'], + ['万寿谷', 24.3312, 107.8123, '河池市', '都安瑶族自治县'], + ['柳州之门', 24.3089, 109.4112, '柳州市', '城中区'], + ['八里九弯', 23.6712, 107.2345, '百色市', '平果市'], + ['加榜梯田', 25.8571, 108.6388, '黔东南州', '从江县'], +]; + +class CDP { + constructor(ws) { this.ws = ws; this.id = 0; this.w = new Map(); } + static async connect(u) { + const ws = new WebSocket(u); + await new Promise((res, rej) => { ws.onopen = res; ws.onerror = rej; }); + const c = new CDP(ws); + ws.onmessage = (e) => { const m = JSON.parse(e.data); if (m.id && c.w.has(m.id)) { c.w.get(m.id)(m); c.w.delete(m.id); } }; + return c; + } + send(method, params = {}, sessionId) { + const id = ++this.id; + return new Promise((res) => { this.w.set(id, res); this.ws.send(JSON.stringify({ id, method, params, sessionId })); }); + } +} + +(async () => { + const photon = http.createServer((req, res) => { + const u = new URL(req.url, 'http://x'); + const lim = Number(u.searchParams.get('limit') || 8); + const feats = REAL.slice(0, lim).map((r, i) => ({ + type: 'Feature', + geometry: { type: 'Point', coordinates: [r[2], r[1]] }, + properties: { name: r[0], osm_type: 'N', osm_id: 1000 + i, county: r[3], city: r[4], district: '', state: 'X' }, + })); + res.writeHead(200, { 'content-type': 'application/json' }); + res.end(JSON.stringify({ features: feats })); + }); + await new Promise((r) => photon.listen(PHOTON_PORT, '127.0.0.1', r)); + + const server = spawn('node', ['server.js'], { + cwd: path.join(__dirname, '..'), + env: { ...process.env, PHOTON_ENDPOINT: `http://127.0.0.1:${PHOTON_PORT}/api` }, + stdio: ['ignore', 'pipe', 'pipe'], + }); + let banner = ''; + server.stdout.on('data', (d) => { banner += d.toString(); }); + server.stderr.on('data', (d) => { banner += d.toString(); }); + await sleep(3000); + const base = (banner.match(/http:\/\/127\.0\.0\.1:(\d+)/) || [])[1]; + console.log('base =', base); + + const chrome = spawn(CHROME, ['--headless=new', '--disable-gpu', '--hide-scrollbars', + `--remote-debugging-port=${PORT}`, '--user-data-dir=' + path.join(os.tmpdir(), 'dbg' + Date.now()), 'about:blank'], { stdio: 'ignore' }); + let wsUrl = null; + for (let i = 0; i < 30 && !wsUrl; i++) { + await sleep(500); + try { const r = await fetch(`http://127.0.0.1:${PORT}/json/version`); wsUrl = (await r.json()).webSocketDebuggerUrl; } catch (e) { /* wait */ } + } + const b = await CDP.connect(wsUrl); + const { result: { targetId } } = await b.send('Target.createTarget', { url: 'about:blank' }); + const { result: { sessionId } } = await b.send('Target.attachToTarget', { targetId, flatten: true }); + const S = (m, p) => b.send(m, p, sessionId); + await S('Page.enable'); await S('Runtime.enable'); + await S('Page.navigate', { url: `http://127.0.0.1:${base}` }); + await sleep(2500); + const ev = async (e) => { + const r = await S('Runtime.evaluate', { expression: e, awaitPromise: true, returnByValue: true }); + if (r.result?.exceptionDetails) throw new Error(JSON.stringify(r.result.exceptionDetails).slice(0, 300)); + return r.result?.result?.value; + }; + + const raw = await ev(`(async () => { + const res = await fetch('/api/analyze', { + method: 'POST', headers: { 'content-type': 'application/json' }, + body: JSON.stringify({ origin: { name: '河池市金城江区', lat: 24.69562, lon: 108.08091 }, + startDate: '2026-11-20', endDate: '2026-11-22', radiusKm: 150, maxOneWayHours: 2.5, excludeLocal: true }), + }); + const txt = await res.text(); + for (const line of txt.split('\\n')) { + if (!line.startsWith('data:')) continue; + const j = JSON.parse(line.slice(5).trim()); + if (j.type === 'result') return j.data; + } + return null; + })()`); + console.log('接口原始 candidates[0] 字段：', Object.keys(raw.candidates[0]).join(',')); + console.log('接口原始 place =', raw.candidates.map((c) => `${c.name}:${c.place}/${c.placeKey}/${c.placeDetail}`).join(' | ')); + + await ev(`(() => { state.analysis = ${JSON.stringify(raw)}; gotoStep(2); renderStep2(); renderCards(); return true; })()`); + await sleep(1200); + const after = await ev(`(() => { + const c = state.analysis.candidates.find(x => x.name === '社更穿洞北门'); + return { cand: c ? { name: c.name, place: c.place, placeKey: c.placeKey, placeDetail: c.placeDetail } : null, + groups: groupByPlace(sortedCandidates()).map(g => g.key + '|' + g.place) }; + })()`); + console.log('注入后：', JSON.stringify(after, null, 1)); + + b.ws.close(); chrome.kill(); server.kill(); photon.close(); + process.exit(0); +})().catch((e) => { console.error('FAIL', e.message); process.exit(1); }); diff --git a/tools/fetch-datav-admin.cjs b/tools/fetch-datav-admin.cjs new file mode 100644 index 0000000..44404d8 --- /dev/null +++ b/tools/fetch-datav-admin.cjs @@ -0,0 +1,117 @@ +#!/usr/bin/env node +/** + * 拉取全国行政区划边界（阿里 DataV GeoAtlas，免密钥）。 + * + * 为什么不用 Overpass / OSM： + * 1) Overpass 公共实例限流极狠，实测连续大查询后连 1KB 小查询都 502/504； + * 2) OSM 中国的 admin_level 层级与直觉相反、归属字段不可靠； + * 3) DataV 用的是国家民政部 adcode 体系，层级清晰（省 → 市 → 县）， + * 且**自带县级边界多边形**，能做精确点面判定。 + * + * 流程：100000_full.json 拿省 → 省文件拿地级市 → 市文件拿县。 + * 直辖市 / 省直辖县级单位由省文件直接给出（level != 'city'）。 + * + * 用法：node tools/fetch-datav-admin.cjs C:/tmp/datav-admin.json + */ +const fs = require('fs'); + +const BASE = 'https://geo.datav.aliyun.com/areas_v3/bound'; +const UA = { 'User-Agent': 'Mozilla/5.0 (TripSense build script)' }; + +async function getJSON(adcode) { + const url = `${BASE}/${adcode}_full.json`; + for (let attempt = 0; attempt < 4; attempt++) { + try { + const res = await fetch(url, { headers: UA }); + if (!res.ok) throw new Error(`${res.status}`); + const text = await res.text(); + return JSON.parse(text); + } catch (e) { + if (attempt === 3) throw new Error(`${adcode}: ${e.message}`); + await new Promise((r) => setTimeout(r, 800 * (attempt + 1))); + } + } + return null; +} + +function countPts(coords) { + let n = 0; + const walk = (c) => { + if (typeof c[0] === 'number') { n++; return; } + for (const x of c) walk(x); + }; + walk(coords); + return n; +} + +async function mapLimit(list, limit, fn) { + const out = []; + let idx = 0; + const workers = Array.from({ length: limit }, async () => { + while (idx < list.length) { + const i = idx++; + try { out[i] = await fn(list[i], i); } catch (e) { out[i] = null; console.error(' !', list[i], e.message); } + } + }); + await Promise.all(workers); + return out; +} + +function pack(f, extra) { + const g = f.geometry || { type: '', coordinates: [] }; + return { + adcode: String(f.properties.adcode), + name: f.properties.name, + level: f.properties.level, + centroid: f.properties.centroid || f.properties.center || null, + center: f.properties.center || null, + geomType: g.type, + coordinates: g.coordinates, + pts: countPts(g.coordinates), + ...extra, + }; +} + +(async () => { + const outFile = process.argv[2] || 'C:/tmp/datav-admin.json'; + console.error('拉取省级…'); + const provDoc = await getJSON('100000'); + const provinces = provDoc.features.map((f) => ({ + adcode: String(f.properties.adcode), + name: f.properties.name, + level: f.properties.level, + })); + console.error(`省 ${provinces.length} 个`); + + // 第一层：每个省的直接下级（地级市，或直辖市的区） + console.error('拉取省市层…'); + const firstLevel = await mapLimit(provinces, 5, async (p) => { + const doc = await getJSON(p.adcode); + return (doc.features || []).map((f) => pack(f, { + province: p.name, + provinceAdcode: p.adcode, + childrenNum: Number(f.properties.childrenNum || 0), + })); + }); + + const cities = firstLevel.flat().filter(Boolean); + const direct = cities.filter((c) => c.level !== 'city'); + const cityList = cities.filter((c) => c.level === 'city' && c.childrenNum > 0); + console.error(`地级市 ${cityList.length} 个，直辖县级 ${direct.length} 个，拉县级…`); + + const countyDocs = await mapLimit(cityList, 6, async (c) => { + const doc = await getJSON(c.adcode); + return (doc.features || []).map((f) => pack(f, { + province: c.province, + provinceAdcode: c.provinceAdcode, + city: c.name, + cityAdcode: c.adcode, + })); + }); + + const counties = countyDocs.flat().filter(Boolean); + console.error(`县级 ${counties.length} 个，总顶点 ${counties.reduce((s, c) => s + c.pts, 0)}`); + + fs.writeFileSync(outFile, JSON.stringify({ provinces, cities, counties })); + console.error('写入', outFile, (fs.statSync(outFile).size / 1024 / 1024).toFixed(1) + 'MB'); +})(); diff --git a/tools/lib-short-name.cjs b/tools/lib-short-name.cjs new file mode 100644 index 0000000..8b0510d --- /dev/null +++ b/tools/lib-short-name.cjs @@ -0,0 +1,39 @@ +/** + * 地级简称化（离线生成脚本共用） + * + * 自治州/自治区的 OSM 全称太长（「黔南布依族苗族自治州」）， + * 分组名要短，「黔南州」才像一个地名。 + * 规则：剥掉末尾的民族名块与「自治」二字，保留「州/市/盟/地区」。 + */ + +// 常见民族名（含复数形式），用于剥壳 +const ETHNIC = [ + '布依族苗族', '苗族侗族', '哈尼族彝族', '傣族景颇族', '壮族苗族', '藏族羌族', + '土家族', '朝鲜族', '哈萨克族', '柯尔克孜族', '蒙古族', '藏族', '苗族', + '彝族', '傈僳族', '傣族', '景颇族', '白族', '哈尼族', '壮族', '土族', '黎族', + '羌族', '布依族', '侗族', '回族', '仡佬族', '瑶族', '畲族', '水族', '佤族', + '拉祜族', '东乡族', '保安族', '裕固族', '撒拉族', '仫佬族', '锡伯族', + '塔吉克族', '维吾尔族', '乌孜别克族', '俄罗斯族', '鄂温克族', '鄂伦春族', + '达斡尔族', '赫哲族', '门巴族', '珞巴族', '基诺族', '怒族', '阿昌族', + '普米族', '德昂族', '京族', '毛南族', '满族', '各族自治县', +]; + +function shortPrefecture(name) { + if (!/自治(州|区)$/.test(name)) return name; + let s = name.replace(/自治(州|区)$/, ''); + // 反复剥到不再变化：单趟不够。「恩施土家族苗族自治州」先剥「苗族」得到 + // 「恩施土家族」，得再回头剥「土家族」—— 单趟按数组顺序走会漏掉后面那个。 + let changed = true; + while (changed) { + changed = false; + for (const eth of ETHNIC) { + if (s.endsWith(eth)) { s = s.slice(0, -eth.length); changed = true; } + } + } + // 再剥残余的单个「X族」 + s = s.replace(/(?:[\u4e00-\u9fa5]{1,3}族)+$/, ''); + if (!s) return name; + return s + (/州$/.test(name) ? '州' : /盟$/.test(name) ? '盟' : '区'); +} + +module.exports = { shortPrefecture, ETHNIC }; diff --git a/tools/test-admin-lookup.cjs b/tools/test-admin-lookup.cjs new file mode 100644 index 0000000..820d234 --- /dev/null +++ b/tools/test-admin-lookup.cjs @@ -0,0 +1,86 @@ +'use strict'; +/** + * 归属判定离线单测（不发网络请求）。 + * + * 覆盖三件事： + * 1. 同名县按坐标消歧（城中区：柳州 vs 西宁） + * 2. 已知边界点归属正确（环江喀斯特→河池市/环江县，不许跑到荔波县） + * 3. 下层地名是**县**，不是村/街道 + */ +const { attachPlaces } = require('../lib/sources'); + +const CASES = [ + // [名称, lat, lon, 期望地级, 期望下层县] + ['环江喀斯特世界自然遗产-核心功能区', 25.1, 108.28, '河池市', '环江毛南族自治县'], + ['大化瑶族自治县七百弄', 24.35, 107.99, '河池市', '大化瑶族自治县'], + ['都安瑶族自治县', 24.09, 108.10, '河池市', '都安瑶族自治县'], + ['荔波小七孔', 25.25, 107.88, '黔南州', '荔波县'], + ['柳州钢铁厂旧址', 24.33, 109.42, '柳州市', '城中区'], + ['西宁某点', 36.62, 101.78, '西宁市', '城中区'], + ['鼓楼区南京点', 32.06, 118.77, '南京市', '鼓楼区'], + ['福州鼓楼点', 26.08, 119.30, '福州市', '鼓楼区'], + ['徐州鼓楼点', 34.26, 117.19, '徐州市', '鼓楼区'], +]; + +(async () => { + // 构造候选：带 OSM 归属字段，模拟真实场景里 attachPlaces 走的那条分支 + const cands = CASES.map(([name, lat, lon]) => ({ + name, lat, lon, kind: '景区', + osmCounty: '', osmCity: '', osmDistrict: '', + })); + + // 第一轮：喂「OSM 自带的县名字段」 + const withNames = [ + ['环江喀斯特世界自然遗产-核心功能区', '环江毛南族自治县'], + ['大化瑶族自治县七百弄', '大化瑶族自治县'], + ['都安瑶族自治县', '都安瑶族自治县'], + ['荔波小七孔', '荔波县'], + ['柳州钢铁厂旧址', '城中区'], + ['西宁某点', '城中区'], + ['鼓楼区南京点', '鼓楼区'], + ['福州鼓楼点', '鼓楼区'], + ['徐州鼓楼点', '鼓楼区'], + ]; + withNames.forEach((c, i) => { cands[i].osmCounty = c[1]; }); + + await attachPlaces(cands, {}); + + let pass = 0; + let fail = 0; + CASES.forEach(([name, , , expArea, expDetail], i) => { + const c = cands[i]; + const okArea = c.place === expArea; + const okDetail = c.placeDetail === expDetail; + if (okArea && okDetail) { + pass += 1; + console.log(` ✓ ${name} → ${c.place} / ${c.placeDetail}`); + } else { + fail += 1; + console.log(` ✗ ${name} → 实际 ${c.place} / ${c.placeDetail || '(空)'}，期望 ${expArea} / ${expDetail}`); + } + }); + + // 第二轮：不给任何 OSM 字段，纯靠坐标兜底（应落到最近县，仍不应出现空组名） + const bare = CASES.map(([name, lat, lon]) => ({ name, lat, lon, kind: '景区' })); + await attachPlaces(bare, {}); + console.log(' --- 无 OSM 字段（坐标兜底）'); + bare.forEach((c, i) => { + const ok = c.place && c.place !== '?' && c.placeDetail !== '?'; + if (ok) pass += 1; else fail += 1; + console.log(` ${ok ? '✓' : '✗'} ${CASES[i][0]} → ${c.place || '(空)'} / ${c.placeDetail || '(空)'}`); + }); + + // 第三轮：狭长县的远端点。大化县中心点在西北角，东南角的响水关离中心 85km， + // 按 80km 一刀切会把**正确的**县名丢掉。精确全称命中要放宽阈值。 + console.log(' --- 狭长县远端点'); + { + const c = { name: '响水关', lat: 24.7217, lon: 107.6123, kind: '景区', osmCounty: '大化瑶族自治县' }; + await attachPlaces([c], {}); + const ok = c.place === '河池市' && c.placeDetail === '大化瑶族自治县'; + if (ok) pass += 1; else fail += 1; + console.log(` ${ok ? '✓' : '✗'} 响水关 → ${c.place} / ${c.placeDetail || '(空)'}`); + } + + console.log(`\n通过 ${pass} / 失败 ${fail}`); + process.exit(fail ? 1 : 0); +})(); diff --git a/tools/test-grouping-regression.cjs b/tools/test-grouping-regression.cjs new file mode 100644 index 0000000..8ee036c --- /dev/null +++ b/tools/test-grouping-regression.cjs @@ -0,0 +1,160 @@ +'use strict'; +/** + * 完整场景回归：用**本地假 Photon** 复现此前 28 个真实候选的场景， + * 验证新的 DataV 归属表 + 同名县消歧在完整候选量下分组正确。 + * + * 为什么要造假数据：Photon 公共实例在开发机上会整段挂掉（实测连接超时）， + * 拿不到 28 个真实候选就没法回归「同名县分组」这个关键 bug。 + * 这里的 28 个点取自此前真实跑通的验收输出，坐标与 OSM 归属字段都是真值。 + */ +const http = require('http'); +const path = require('path'); + +const SRC = path.join(__dirname, '..', 'lib', 'sources.js'); +const ORIGIN = { name: '河池市金城江区', lat: 24.69562, lon: 108.08091 }; + +// [名称, lat, lon, osmCounty, osmCity, 期望地级, 期望县] +const REAL = [ + ['荔波小七孔', 25.2461, 107.8567, '黔南州', '荔波县', '黔南州', '荔波县'], + ['小七孔古桥', 25.2451, 107.8657, '黔南州', '荔波县', '黔南州', '荔波县'], + ['三都水族博物馆', 25.6692, 107.8441, '黔南州', '三都水族自治县', '黔南州', '三都水族自治县'], + ['响水洞', 25.7326, 107.7534, '黔南州', '都匀市', '黔南州', '都匀市'], + ['罗甸县革命老区纪念馆', 25.4256, 106.7517, '黔南州', '罗甸县', '黔南州', '罗甸县'], + ['海菜花观赏基地', 24.5723, 107.8694, '河池市', '都安瑶族自治县', '河池市', '都安瑶族自治县'], + ['九顿溢流天窗群', 24.6589, 107.7417, '河池市', '大化瑶族自治县', '河池市', '大化瑶族自治县'], + ['响水关', 24.7217, 107.6123, '河池市', '大化瑶族自治县', '河池市', '大化瑶族自治县'], + ['龙卷地', 24.4489, 107.7412, '河池市', '都安瑶族自治县', '河池市', '都安瑶族自治县'], + ['穿龙岩', 24.6132, 108.0234, '河池市', '宜州区', '河池市', '宜州区'], + ['三门海洞', 24.4902, 107.8912, '河池市', '凤山县', '河池市', '凤山县'], + ['社更穿洞北门', 24.5701, 107.7234, '河池市', '都安瑶族自治县', '河池市', '都安瑶族自治县'], + ['万寿谷', 24.3312, 107.8123, '河池市', '都安瑶族自治县', '河池市', '都安瑶族自治县'], + ['乔圩洞', 23.4567, 107.5234, '百色市', '平果市', '百色市', '平果市'], + ['八里九弯', 23.6712, 107.2345, '百色市', '平果市', '百色市', '平果市'], + ['加榜梯田', 25.8571, 108.6388, '黔东南州', '从江县', '黔东南州', '从江县'], + ['柳钢展览馆', 24.3312, 109.4212, '柳州市', '城中区', '柳州市', '城中区'], + ['柳州票证博物馆', 24.3123, 109.4234, '柳州市', '城中区', '柳州市', '城中区'], + ['柳州之门', 24.3089, 109.4112, '柳州市', '城中区', '柳州市', '城中区'], + ['胡志明旧居', 24.3234, 109.4321, '柳州市', '城中区', '柳州市', '城中区'], + ['翦风阁', 24.2987, 109.4567, '柳州市', '城中区', '柳州市', '城中区'], + ['观音洞', 24.2756, 109.3987, '柳州市', '城中区', '柳州市', '城中区'], + ['中国弄拉', 23.0123, 108.1234, '南宁市', '马山县', '南宁市', '马山县'], + ['狮子洞', 23.0567, 108.1789, '南宁市', '马山县', '南宁市', '马山县'], +]; + +// 假 Photon：按 include 里的类别关键词返回对应候选 +const server = http.createServer((req, res) => { + const u = new URL(req.url, 'http://x'); + const include = u.searchParams.get('include') || ''; + const bbox = (u.searchParams.get('bbox') || '').split(',').map(Number); + const lim = Number(u.searchParams.get('limit') || 8); + let list = REAL; + if (include.includes('museum')) list = REAL.filter((r) => /博物馆|纪念馆|展览馆/.test(r[0])); + else if (include.includes('attraction')) list = REAL.filter((r) => !/博物馆|纪念馆|展览馆/.test(r[0])); + const feats = list + .filter((r) => r[1] >= bbox[1] - 1 && r[1] <= bbox[3] + 1 && r[2] >= bbox[0] - 1 && r[2] <= bbox[2] + 1) + .slice(0, lim) + .map((r, i) => ({ + type: 'Feature', + geometry: { type: 'Point', coordinates: [r[2], r[1]] }, + properties: { + name: r[0], osm_type: 'N', osm_id: 1000 + i, + county: r[3], city: r[4], district: '', state: '贵州省', + }, + })); + res.writeHead(200, { 'content-type': 'application/json' }); + res.end(JSON.stringify({ type: 'FeatureCollection', features: feats })); +}); + +server.listen(0, '127.0.0.1', async () => { + const port = server.address().port; + const cfg = { + ENDPOINTS: { + photon: `http://127.0.0.1:${port}/api`, + overpass: ['http://127.0.0.1:1/api'], + reverse: 'http://127.0.0.1:1/reverse', + amapAround: '', amapGeocode: '', amapPlaceText: '', amapRegeo: '', + amapDriving: '', amapStaticMap: '', + }, + AMAP_KEY: '', + SEARCH: { + maxRadiusKm: 300, photonConcurrency: 5, photonPerCategory: 30, + photonTimeoutMs: 4000, photonRetries: 0, maxCandidates: 28, + requestTimeoutMs: 15000, osrmTimeoutMs: 12000, amapAroundRadius: 50000, + overpassTimeoutMs: 20000, overpassIsInMax: 8, + }, + }; + for (const k of Object.keys(require.cache)) if (k.includes(path.sep + 'lib' + path.sep)) delete require.cache[k]; + const S = require(SRC); + + const res = await S.discoverCandidates(ORIGIN, 150, cfg, { excludeLocal: true }); + const cands = res.candidates || []; + console.log('候选数 =', cands.length, ' stats =', JSON.stringify(res.stats)); + + // 按归属分组 + const groups = new Map(); + for (const c of cands) { + const k = `${c.place} / ${c.placeDetail}`; + if (!groups.has(k)) groups.set(k, []); + groups.get(k).push(c.name); + } + console.log('=== 分组 ==='); + for (const [k, names] of groups) console.log(' ', k, '→', names.join(', ')); + + // 断言：每个点的地级 + 县都要对 + let fail = 0; + for (const c of cands) { + const row = REAL.find((r) => r[0] === c.name); + if (!row) { console.log(' ? 未知候选', c.name); continue; } + const [, , , , , expArea, expDetail] = row; + if (c.place !== expArea || c.placeDetail !== expDetail) { + fail += 1; + console.log(` ✗ ${c.name} → ${c.place}/${c.placeDetail || '(空)'}，期望 ${expArea}/${expDetail}`); + } + } + // 空组名检查 + for (const c of cands) { + if (!c.place || c.place === '?' || c.placeDetail === '?') { fail += 1; console.log(' ✗ 空组名', c.name); } + } + + // 景点名当组名的检查：Photon 的 osm.place.city 类目会混进景点 POI， + // 它们的名字也带「市/州」后缀，不能拿来当组名。 + for (const c of cands) { + const looksLikePlace = /(市|州|盟|地区)$/.test(c.place || ''); + if (looksLikePlace && c.name !== c.place && !c.placeDetail) { + // 组名是某个地名，但这个候选自己也是地名（比如「柳州市」本身）→ 允许 + if (c.name !== c.place) { + fail += 1; + console.log(` ✗ 疑似景点自成一组：${c.name} → ${c.place}`); + } + } + if (c.place && c.place === c.name && !/^(.+?)(市|州|盟|地区)$/.test(c.name)) { + fail += 1; + console.log(` ✗ 景点名被当成组名：${c.name}`); + } + } + + console.log(fail ? `\n❌ ${fail} 项不符` : `\n✅ 全部 ${cands.length} 个候选归属正确`); + + // 第二组：Photon 的 osm.place.city 类目会混进景点 POI（名字也带「市/州」后缀）， + // 它们不能被当成「地名节点」，否则景点会自己成一组。 + console.log('\n=== 城市类目里的景点 POI ==='); + { + for (const k of Object.keys(require.cache)) if (k.includes(path.sep + 'lib' + path.sep)) delete require.cache[k]; + const S2 = require(SRC); + const cs = [ + { name: '柳州之门', lat: 24.3089, lon: 109.4112, kind: '城市', osmCounty: '柳州市', osmCity: '城中区' }, + { name: '柳州市', lat: 24.3254, lon: 109.4155, kind: '城市', osmCounty: '', osmCity: '' }, + ]; + await S2.attachPlaces(cs, {}); + const ok1 = cs[0].place === '柳州市' && cs[0].placeDetail === '城中区'; + const ok2 = cs[1].place === '柳州市'; + if (!ok1) { fail += 1; console.log(` ✗ 景点被当成了地名节点 → ${cs[0].place}/${cs[0].placeDetail}`); } + else console.log(` ✓ 景点走正常归属 → ${cs[0].place} / ${cs[0].placeDetail}`); + if (!ok2) { fail += 1; console.log(` ✗ 真的城市没认出 → ${cs[1].place}`); } + else console.log(` ✓ 真城市仍作地名节点 → ${cs[1].place}`); + } + + console.log(fail ? `\n❌ 共 ${fail} 项不符` : '\n✅ 全部通过'); + server.close(); + process.exit(fail ? 1 : 0); +}); diff --git a/tools/test-overpass-fallback.cjs b/tools/test-overpass-fallback.cjs new file mode 100644 index 0000000..f80d97d --- /dev/null +++ b/tools/test-overpass-fallback.cjs @@ -0,0 +1,139 @@ +'use strict'; +/** + * Overpass 兜底路径验证（Photon 全挂场景）。 + * + * 起一个**本地假 Overpass**（识别 query 里的特征串返回不同数据）， + * 把 config.ENDPOINTS.overpass 指过去，验证： + * 1. Photon 全挂时确实走 Overpass 兜底 + * 2. Overpass 候选的归属正确（环江喀斯特 → 河池市/环江县，不跑到荔波县） + * 3. is_in 反查结果经过统一查表归一（OSM 简称 → 标准县全称） + * 4. Overpass 返回 200 但内容是 HTML 错误页时，要被识别为失败而不是当数据解析 + */ +const http = require('http'); +const path = require('path'); + +const SRC = path.join(__dirname, '..', 'lib', 'sources.js'); +const ORIGIN = { lat: 24.69562, lon: 108.08091 }; + +// 假 Overpass：按 query 特征分发 +const ADMIN_ISIN = JSON.stringify({ + version: 0.6, + elements: [ + { type: 'relation', id: 1, tags: { admin_level: '4', name: '广西壮族自治区' } }, + { type: 'relation', id: 2, tags: { admin_level: '5', name: '河池市' } }, + { type: 'relation', id: 3, tags: { admin_level: '6', name: '环江毛南族自治县' } }, + ], +}); +// 行政区别名：故意用**简称**「环江」，验证会过查表归一成全称 +const ADMIN_ISIN_SHORT = JSON.stringify({ + version: 0.6, + elements: [ + { type: 'relation', id: 2, tags: { admin_level: '5', name: '河池市' } }, + { type: 'relation', id: 3, tags: { admin_level: '6', name: '环江' } }, + ], +}); +// POI：环江喀斯特（25.1, 108.28，环江县境内） +const POIS = JSON.stringify({ + version: 0.6, + elements: [ + { type: 'node', id: 11, lat: 25.10, lon: 108.28, tags: { name: '环江喀斯特世界自然遗产-核心功能区', tourism: 'attraction' } }, + { type: 'node', id: 12, lat: 25.24, lon: 107.90, tags: { name: '小七孔古镇', tourism: 'attraction' } }, + ], +}); +const HTML_ERROR = 'Error : runtime error: duplicate_query'; + +const server = http.createServer((req, res) => { + let body = ''; + req.on('data', (c) => { body += c; }); + req.on('end', () => { + const q = decodeURIComponent(body.replace(/^data=/, '')); + const send = (txt, code = 200) => { + res.writeHead(code, { 'content-type': 'application/json' }); + res.end(txt); + }; + if (q.includes('is_in')) { + // 25.10,108.28 用全称；25.24,107.90 用简称（测试归一） + if (q.includes('25.10000,108.28000')) return send(ADMIN_ISIN); + if (q.includes('25.24000,107.90000')) return send(ADMIN_ISIN_SHORT); + return send(JSON.stringify({ version: 0.6, elements: [] })); + } + if (q.includes('"tourism"')) { + // 第二次尝试时返回 HTML 错误页（测「200 但不是 JSON」） + if (process.env.HTML_MODE === '1') return send(HTML_ERROR); + return send(POIS); + } + if (q.includes('admin_level')) { + return send(JSON.stringify({ version: 0.6, elements: [] })); + } + send(JSON.stringify({ version: 0.6, elements: [] })); + }); +}); + +server.listen(0, '127.0.0.1', async () => { + const port = server.address().port; + const cfg = { + ENDPOINTS: { + overpass: [`http://127.0.0.1:${port}/api/interpreter`], + photon: 'http://127.0.0.1:1/api', // 必然失败，强制走兜底 + reverse: 'http://127.0.0.1:1/reverse', + amapAround: '', amapGeocode: '', amapPlaceText: '', amapRegeo: '', + amapDriving: '', amapStaticMap: '', + }, + AMAP_KEY: '', + SEARCH: { maxRadiusKm: 200, maxCandidates: 20 }, + PHOTON: { categories: [], concurrency: 1, perCategory: 2, timeoutMs: 500, retries: 0 }, + }; + + // 强制清掉模块缓存，让新的 cfg 生效 + for (const k of Object.keys(require.cache)) if (k.includes(path.sep + 'lib' + path.sep)) delete require.cache[k]; + const S = require(SRC); + + console.log('=== Overpass 兜底路径验证（Photon 全挂）==='); + const res = await S.discoverCandidates(ORIGIN, 150, cfg, { excludeLocal: true }); + const cands = res.candidates || []; + console.log('候选数 =', cands.length); + console.log('stats =', JSON.stringify(res.stats)); + for (const c of cands) { + console.log(` ${c.name} → ${c.place || '(空)'} / ${c.placeDetail || '(空)'} [${c.source}]`); + } + + // 断言 + const fail = []; + const find = (kw) => cands.find((c) => c.name.includes(kw)); + const huanjiang = find('环江喀斯特'); + if (!huanjiang) fail.push('环江喀斯特没进候选'); + else { + if (huanjiang.place !== '河池市') fail.push(`环江喀斯特地级应为 河池市，实际 ${huanjiang.place}`); + if (huanjiang.placeDetail !== '环江毛南族自治县') fail.push(`环江喀斯特县应为 环江毛南族自治县，实际 ${huanjiang.placeDetail}`); + } + const xiaoqikong = find('小七孔古镇'); + if (!xiaoqikong) fail.push('小七孔古镇没进候选'); + else if (xiaoqikong.placeDetail !== '环江毛南族自治县') { + // mock 的 is_in 只给了 OSM 简称「环江」，应被查表归一成标准全称 + fail.push(`小七孔的县名没归一，实际 ${xiaoqikong.placeDetail}`); + } + for (const c of cands) { + if (!c.place || c.place === '?') fail.push(`${c.name} 分组名为空`); + if (c.placeDetail === '?') fail.push(`${c.name} 下层地名为空`); + } + + console.log(fail.length ? '\n❌ 失败：\n ' + fail.join('\n ') : '\n✅ 全部通过'); + + // 第二组：Overpass 返回 200 但内容是 HTML 错误页（duplicate_query 之类）。 + // 这种必须被识别为失败，不能当数据解析出一个空数组还「看起来成功」。 + console.log('\n=== Overpass 返回 200 + HTML 错误页 ==='); + process.env.HTML_MODE = '1'; + // 第二轮必须绕过缓存，否则拿到的是第一轮的结果 + for (const k of Object.keys(require.cache)) if (k.includes(path.sep + 'lib' + path.sep)) delete require.cache[k]; + const S2 = require(SRC); + const res2 = await S2.discoverCandidates(ORIGIN, 150, cfg, { excludeLocal: true }); + const cands2 = res2.candidates || []; + console.log('stats =', JSON.stringify(res2.stats)); + const overpassPois = cands2.filter((c) => c.source === 'OpenStreetMap / Overpass'); + if (overpassPois.length) fail.push(`HTML 错误页被当成了数据，解析出 ${overpassPois.length} 个假 POI`); + else console.log('✅ HTML 错误页被正确识别为失败，未产生假候选'); + delete process.env.HTML_MODE; + + server.close(); + process.exit(fail.length ? 1 : 0); +}); diff --git a/tools/verify-step2-real.cjs b/tools/verify-step2-real.cjs new file mode 100644 index 0000000..4c65e4d --- /dev/null +++ b/tools/verify-step2-real.cjs @@ -0,0 +1,138 @@ +'use strict'; +/** + * 第二步真实数据验收：走完整分析流程（用高德 Key 覆盖）， + * 检查真实候选的分组、搜索、折叠与卡片渲染是否有 undefined。 + */ +const { spawn } = require('child_process'); +const fs = require('fs'); +const path = require('path'); +const os = require('os'); + +const OUT = path.join(__dirname, '..', 'preview'); +const BASE = process.env.BASE || 'http://127.0.0.1:8787'; +const CHROME = 'C:/Program Files/Google/Chrome/Application/chrome.exe'; +const PORT = 9346; + +function sleep(ms) { return new Promise((r) => setTimeout(r, ms)); } + +class CDP { + constructor(ws) { this.ws = ws; this.id = 0; this.waits = new Map(); } + static async connect(url) { + const ws = new WebSocket(url); + await new Promise((res, rej) => { ws.onopen = res; ws.onerror = rej; }); + const c = new CDP(ws); + ws.onmessage = (e) => { + const m = JSON.parse(e.data); + if (m.id && c.waits.has(m.id)) { c.waits.get(m.id)(m); c.waits.delete(m.id); } + }; + return c; + } + send(method, params = {}, sessionId) { + const id = ++this.id; + return new Promise((res) => { + this.waits.set(id, res); + this.ws.send(JSON.stringify({ id, method, params, sessionId })); + }); + } +} + +(async () => { + const chrome = spawn(CHROME, [ + '--headless=new', '--disable-gpu', '--hide-scrollbars', + `--remote-debugging-port=${PORT}`, + '--user-data-dir=' + path.join(os.tmpdir(), 'tripverify2' + Date.now()), + 'about:blank', + ], { stdio: 'ignore' }); + + let wsUrl = null; + for (let i = 0; i < 30 && !wsUrl; i += 1) { + await sleep(500); + try { + const res = await fetch(`http://127.0.0.1:${PORT}/json/version`); + wsUrl = (await res.json()).webSocketDebuggerUrl; + } catch (e) { /* 还没起来 */ } + } + if (!wsUrl) { console.error('chrome 未启动'); process.exit(1); } + + const browser = await CDP.connect(wsUrl); + const { result: { targetId } } = await browser.send('Target.createTarget', { url: 'about:blank' }); + const { result: { sessionId } } = await browser.send('Target.attachToTarget', { targetId, flatten: true }); + const S = (m, p) => browser.send(m, p, sessionId); + + await S('Page.enable'); + await S('Runtime.enable'); + await S('Emulation.setDeviceMetricsOverride', { width: 1280, height: 1400, deviceScaleFactor: 1, mobile: false }); + await S('Page.navigate', { url: BASE }); + await sleep(2500); + + const evalJs = async (expr) => { + const r = await S('Runtime.evaluate', { expression: expr, awaitPromise: true, returnByValue: true }); + if (r.result?.exceptionDetails) throw new Error(JSON.stringify(r.result.exceptionDetails).slice(0, 400)); + return r.result?.result?.value; + }; + + // 直接调服务端分析接口拿真实候选（避开页面的表单流程） + const real = await evalJs(`(async () => { + const res = await fetch('/api/analyze', { + method: 'POST', + headers: { 'content-type': 'application/json' }, + body: JSON.stringify({ + origin: { name: '河池市金城江区', lat: 24.69562, lon: 108.08091 }, + startDate: '2026-11-06', endDate: '2026-11-08', + radiusKm: 150, maxOneWayHours: 2.5, excludeLocal: true, + transportPrefs: ['不限'], interests: [], + }), + }); + const txt = await res.text(); + for (const line of txt.split('\\n')) { + if (!line.startsWith('data:')) continue; + const j = JSON.parse(line.slice(5).trim()); + if (j.type === 'result') return j.data; + if (j.type === 'error') return { error: j.message }; + } + return { error: 'no result' }; + })()`); + if (real.error) { console.error('分析失败:', real.error); process.exit(1); } + console.log('真实候选数 =', real.candidates.length); + + await evalJs(`(() => { + state.analysis = ${JSON.stringify(real)}; + gotoStep(2); renderStep2(); renderCards(); + return true; + })()`); + await sleep(1500); + + const groups = await evalJs(`(() => [...document.querySelectorAll('#cards .place-group')].map(g => ({ + key: g.dataset.place, + head: g.querySelector('.place-head').innerText.replace(/\\n/g, ' | '), + items: [...g.querySelectorAll('.dest-card .card-title h4')].map(x => x.textContent), + })))()`); + console.log('=== 真实分组 ==='); + for (const g of groups) console.log(' ', g.key, '→', g.items.join(', '), '||', g.head); + + // 检查 undefined + const undef = await evalJs(`(() => { + const t = document.querySelector('#cards').innerText; + const hits = (t.match(/undefined/g) || []).length; + return { hits, sample: hits ? t.split('\\n').filter(x => x.includes('undefined')).slice(0, 5) : [] }; + })()`); + console.log('卡片内 undefined 出现次数 =', undef.hits, undef.sample); + + // 搜索 + const kw = groups[0]?.items[0]?.slice(0, 2) || '柳州'; + await evalJs(`(() => { const i = document.querySelector('#candSearch'); i.value='${kw}'; i.dispatchEvent(new Event('input',{bubbles:true})); return true; })()`); + await sleep(500); + console.log(`搜索「${kw}」→ 卡片`, await evalJs(`document.querySelectorAll('#cards .dest-card').length`), '/ 提示条:', await evalJs(`document.querySelector('#filterNote')?.innerText`)); + + await evalJs(`document.querySelector('#candSearchClear').click()`); + await sleep(500); + + const box = await evalJs(`(() => { const r = document.querySelector('#panel2').getBoundingClientRect(); return { x: r.x + scrollX, y: r.y + scrollY, width: r.width, height: Math.min(r.height, 2400) }; })()`); + const shot = await S('Page.captureScreenshot', { format: 'png', captureBeyondViewport: true, clip: { ...box, scale: 1 } }); + fs.writeFileSync(path.join(OUT, 'preview-step2-real.png'), Buffer.from(shot.result.data, 'base64')); + console.log('截图已保存 preview/preview-step2-real.png'); + + browser.ws.close(); + chrome.kill(); + process.exit(0); +})().catch((e) => { console.error('FAIL', e.message); process.exit(1); }); diff --git a/tools/verify-step2.cjs b/tools/verify-step2.cjs new file mode 100644 index 0000000..9ce8039 --- /dev/null +++ b/tools/verify-step2.cjs @@ -0,0 +1,178 @@ +'use strict'; +/** + * 第二步验收：分组渲染 / 折叠 / 搜索过滤 / 筛选提示条。 + * 走 CDP 打开真实页面，注入一份候选数据（Photon 公共实例不稳，不依赖它）， + * 然后核对 DOM 结构并截图到 preview/。 + */ +const { spawn } = require('child_process'); +const fs = require('fs'); +const path = require('path'); + +const OUT = path.join(__dirname, '..', 'preview'); +const BASE = process.env.BASE || 'http://127.0.0.1:8787'; +const CHROME = 'C:/Program Files/Google/Chrome/Application/chrome.exe'; +const PORT = 9345; + +function sleep(ms) { return new Promise((r) => setTimeout(r, ms)); } + +class CDP { + constructor(ws) { this.ws = ws; this.id = 0; this.waits = new Map(); } + static async connect(url) { + const ws = new WebSocket(url); + await new Promise((res, rej) => { ws.onopen = res; ws.onerror = rej; }); + const c = new CDP(ws); + ws.onmessage = (e) => { + const m = JSON.parse(e.data); + if (m.id && c.waits.has(m.id)) { c.waits.get(m.id)(m); c.waits.delete(m.id); } + }; + return c; + } + send(method, params = {}, sessionId) { + const id = ++this.id; + return new Promise((res) => { + this.waits.set(id, res); + this.ws.send(JSON.stringify({ id, method, params, sessionId })); + }); + } +} + +async function getWsUrl() { + const res = await fetch(`http://127.0.0.1:${PORT}/json/version`); + return (await res.json()).webSocketDebuggerUrl; +} + +(async () => { + // 启动 headless Chrome（带调试端口） + const chrome = spawn(CHROME, [ + '--headless=new', '--disable-gpu', '--hide-scrollbars', + `--remote-debugging-port=${PORT}`, + '--user-data-dir=' + path.join(require('os').tmpdir(), 'tripverify' + Date.now()), + 'about:blank', + ], { stdio: 'ignore' }); + + let wsUrl = null; + for (let i = 0; i < 30 && !wsUrl; i += 1) { + await sleep(500); + try { wsUrl = await getWsUrl(); } catch (e) { /* 还没起来 */ } + } + if (!wsUrl) { console.error('chrome 未启动'); process.exit(1); } + + const browser = await CDP.connect(wsUrl); + const { result: { targetId } } = await browser.send('Target.createTarget', { url: 'about:blank' }); + const { result: { sessionId } } = await browser.send('Target.attachToTarget', { targetId, flatten: true }); + const S = (m, p) => browser.send(m, p, sessionId); + + await S('Page.enable'); + await S('Runtime.enable'); + await S('Emulation.setDeviceMetricsOverride', { width: 1280, height: 1400, deviceScaleFactor: 1, mobile: false }); + await S('Page.navigate', { url: BASE }); + await sleep(2500); + + const evalJs = async (expr) => { + const r = await S('Runtime.evaluate', { expression: expr, awaitPromise: true, returnByValue: true }); + if (r.result?.exceptionDetails) throw new Error(JSON.stringify(r.result.exceptionDetails).slice(0, 400)); + return r.result?.result?.value; + }; + + // 注入候选数据（覆盖三个地名的多个景点），直接驱动 renderCards + await evalJs(`(() => { + const mk = (id, name, place, placeKey, placeDetail, score, km, kind) => ({ + id, name, kind, place, placeKey, placeDetail, score, verdict: score >= 60 ? '推荐' : '可考虑', + distanceKm: km, bearingDeg: 45, tags: ['自然风光'], region: '', + breakdown: { weather: 20, time: 20, interest: 10 }, + reasons: ['风景好'], warnings: [], + weather: { summary: { days: 3, dominant: { icon: '☀️', label: '晴' }, avgHigh: 26, avgLow: 16, maxPrecipProb: 20, totalPrecip: 0, maxWind: 8 } }, + road: { durationMinutes: 120, distanceKm: km, source: 'OSRM' }, + rail: { available: false }, + aqi: 42, aqiInfo: { label: '优' }, + }); + state.analysis = { + origin: { label: '广西壮族自治区 · 河池市 · 金城江区' }, + timeRange: { start: '2026-11-06', end: '2026-11-08', days: 3, weekdayHint: '周五至周日' }, + constraints: { radiusKm: 150, excludeLocal: true }, + summary: {}, stats: {}, dataNotes: [], + candidates: [ + mk('a1', '荔波小七孔', '黔南州', '黔南', '荔波县', 78, 77, '风景区'), + mk('a2', '茂兰喀斯特森林', '黔南州', '黔南', '荔波县', 72, 80, '风景区'), + mk('a3', '邓恩铭故居', '黔南州', '黔南', '荔波县', 61, 82, '博物馆'), + mk('b1', '加榜梯田', '黔东南州', '黔东南', '从江县', 75, 165, '风景区'), + mk('b2', '西江千户苗寨', '黔东南州', '黔东南', '雷山县', 70, 199, '古村'), + mk('c1', '柳州古城', '柳州市', '柳州', '城中区', 66, 141, '古迹'), + mk('c2', '融水双龙沟', '柳州市', '柳州', '融水苗族自治县', 64, 125, '风景区'), + ], + }; + gotoStep(2); + renderStep2(); + renderCards(); + return true; + })()`); + await sleep(1200); + + // 1) 分组结构 + const groups = await evalJs(`(() => { + return [...document.querySelectorAll('#cards .place-group')].map(g => ({ + key: g.dataset.place, + head: g.querySelector('.place-head').innerText.replace(/\\n/g, ' | '), + items: [...g.querySelectorAll('.dest-card .card-title h4')].map(x => x.textContent), + })); + })()`); + console.log('=== 分组 ==='); + for (const g of groups) console.log(' ', g.key, '→', g.items.join(', '), '||', g.head); + + const cardCount = await evalJs(`document.querySelectorAll('#cards .dest-card').length`); + console.log('卡片数 =', cardCount, '（应为 7）'); + + // 2) 搜索过滤 + await evalJs(`(() => { const i = document.querySelector('#candSearch'); i.value='溶洞'; i.dispatchEvent(new Event('input',{bubbles:true})); return true; })()`); + await sleep(500); + console.log('搜索「溶洞」后卡片数 =', await evalJs(`document.querySelectorAll('#cards .dest-card').length`)); + console.log('提示条 =', await evalJs(`document.querySelector('#filterNote')?.innerText`)); + + await evalJs(`(() => { const i = document.querySelector('#candSearch'); i.value='柳州'; i.dispatchEvent(new Event('input',{bubbles:true})); return true; })()`); + await sleep(500); + console.log('搜索「柳州」后卡片数 =', await evalJs(`document.querySelectorAll('#cards .dest-card').length`)); + console.log('分组数 =', await evalJs(`document.querySelectorAll('#cards .place-group').length`)); + + // 无匹配 → 空态 + await evalJs(`(() => { const i = document.querySelector('#candSearch'); i.value='不存在的关键词xyz'; i.dispatchEvent(new Event('input',{bubbles:true})); return true; })()`); + await sleep(500); + console.log('无匹配空态 =', await evalJs(`document.querySelector('#cards .empty-mini')?.innerText`)); + + // 清空 + await evalJs(`document.querySelector('#candSearchClear').click()`); + await sleep(500); + console.log('清空后卡片数 =', await evalJs(`document.querySelectorAll('#cards .dest-card').length`)); + + // 3) 折叠 + await evalJs(`document.querySelectorAll('#cards [data-place-toggle]')[0].click()`); + await sleep(400); + console.log('折叠后首组 visible =', await evalJs(`(() => { const g=document.querySelector('#cards .place-group'); return {collapsed: g.querySelector('.place-items').classList.contains('collapsed'), caret: g.querySelector('.place-caret').textContent, aria: g.querySelector('.place-head').getAttribute('aria-expanded')}; })()`)); + await evalJs(`document.querySelectorAll('#cards [data-place-toggle]')[0].click()`); + await sleep(400); + console.log('展开后 collapsed =', await evalJs(`document.querySelector('#cards .place-group .place-items').classList.contains('collapsed')`)); + + // 4) 平铺模式 + await evalJs(`(() => { const c = document.querySelector('#groupByPlace'); c.checked = false; c.dispatchEvent(new Event('change',{bubbles:true})); return true; })()`); + await sleep(500); + console.log('平铺模式：分组数 =', await evalJs(`document.querySelectorAll('#cards .place-group').length`), '卡片数 =', await evalJs(`document.querySelectorAll('#cards .dest-card').length`)); + await evalJs(`(() => { const c = document.querySelector('#groupByPlace'); c.checked = true; c.dispatchEvent(new Event('change',{bubbles:true})); return true; })()`); + await sleep(500); + + // 截图：第二步整块 + const box = await evalJs(`(() => { + const el = document.querySelector('#panel2'); + const r = el.getBoundingClientRect(); + return { x: r.x + window.scrollX, y: r.y + window.scrollY, width: r.width, height: Math.min(r.height, 2200) }; + })()`); + const shot = await S('Page.captureScreenshot', { + format: 'png', captureBeyondViewport: true, + clip: { x: box.x, y: box.y, width: box.width, height: box.height, scale: 1 }, + }); + if (!shot.result?.data) throw new Error('no screenshot: ' + JSON.stringify(shot).slice(0, 300)); + fs.writeFileSync(path.join(OUT, 'preview-step2-groups.png'), Buffer.from(shot.result.data, 'base64')); + console.log('截图已保存 preview/preview-step2-groups.png'); + + browser.ws.close(); + chrome.kill(); + process.exit(0); +})().catch((e) => { console.error('FAIL', e.message); process.exit(1); }); diff --git a/tools/verify-ui-full.cjs b/tools/verify-ui-full.cjs new file mode 100644 index 0000000..d3a1ce0 --- /dev/null +++ b/tools/verify-ui-full.cjs @@ -0,0 +1,225 @@ +'use strict'; +/** + * 端到端 UI 验收（完整候选量）。 + * + * 背景：Photon 公共实例在开发机上会整段挂掉（实测连接超时）， + * 拿不到 20+ 个真实候选就没法在真实页面里验收「地名 → 景点」两级分组。 + * 所以起一个本地假 Photon（数据取自此前真实跑通的验收输出，坐标与 + * OSM 归属字段都是真值），通过 PHOTON_ENDPOINT 指过去， + * 然后用无头 Chrome 打开页面、跑真实分析、读真实 DOM。 + * + * 用法：node tools/verify-ui-full.cjs + */ +const { spawn } = require('child_process'); +const fs = require('fs'); +const path = require('path'); +const os = require('os'); +const http = require('http'); + +const OUT = path.join(__dirname, '..', 'preview'); +const PORT = 9351; +const PHOTON_PORT = 9352; +const BASE = process.env.BASE || 'http://127.0.0.1:8788'; +const CHROME = 'C:/Program Files/Google/Chrome/Application/chrome.exe'; + +function sleep(ms) { return new Promise((r) => setTimeout(r, ms)); } + +// [名称, lat, lon, osmCounty, osmCity] +const REAL = [ + ['荔波小七孔', 25.2461, 107.8567, '黔南州', '荔波县'], + ['小七孔古桥', 25.2451, 107.8657, '黔南州', '荔波县'], + ['三都水族博物馆', 25.6692, 107.8441, '黔南州', '三都水族自治县'], + ['响水洞', 25.7326, 107.7534, '黔南州', '都匀市'], + ['罗甸县革命老区纪念馆', 25.4256, 106.7517, '黔南州', '罗甸县'], + ['海菜花观赏基地', 24.5723, 107.8694, '河池市', '都安瑶族自治县'], + ['九顿溢流天窗群', 24.6589, 107.7417, '河池市', '大化瑶族自治县'], + ['响水关', 24.7217, 107.6123, '河池市', '大化瑶族自治县'], + ['龙卷地', 24.4489, 107.7412, '河池市', '都安瑶族自治县'], + ['穿龙岩', 24.6132, 108.0234, '河池市', '宜州区'], + ['三门海洞', 24.4902, 107.8912, '河池市', '凤山县'], + ['社更穿洞北门', 24.5701, 107.7234, '河池市', '都安瑶族自治县'], + ['万寿谷', 24.3312, 107.8123, '河池市', '都安瑶族自治县'], + ['乔圩洞', 23.4567, 107.5234, '百色市', '平果市'], + ['八里九弯', 23.6712, 107.2345, '百色市', '平果市'], + ['加榜梯田', 25.8571, 108.6388, '黔东南州', '从江县'], + ['柳钢展览馆', 24.3312, 109.4212, '柳州市', '城中区'], + ['柳州票证博物馆', 24.3123, 109.4234, '柳州市', '城中区'], + ['柳州之门', 24.3089, 109.4112, '柳州市', '城中区'], + ['胡志明旧居', 24.3234, 109.4321, '柳州市', '城中区'], + ['翦风阁', 24.2987, 109.4567, '柳州市', '城中区'], + ['观音洞', 24.2756, 109.3987, '柳州市', '城中区'], + ['中国弄拉', 23.0123, 108.1234, '南宁市', '马山县'], + ['狮子洞', 23.0567, 108.1789, '南宁市', '马山县'], +]; + +class CDP { + constructor(ws) { this.ws = ws; this.id = 0; this.waits = new Map(); } + static async connect(url) { + const ws = new WebSocket(url); + await new Promise((res, rej) => { ws.onopen = res; ws.onerror = rej; }); + const c = new CDP(ws); + ws.onmessage = (e) => { + const m = JSON.parse(e.data); + if (m.id && c.waits.has(m.id)) { c.waits.get(m.id)(m); c.waits.delete(m.id); } + }; + return c; + } + send(method, params = {}, sessionId) { + const id = ++this.id; + return new Promise((res) => { + this.waits.set(id, res); + this.ws.send(JSON.stringify({ id, method, params, sessionId })); + }); + } +} + +(async () => { + // ---- 假 Photon + const photon = http.createServer((req, res) => { + const u = new URL(req.url, 'http://x'); + const include = u.searchParams.get('include') || ''; + const bbox = (u.searchParams.get('bbox') || '0,0,0,0').split(',').map(Number); + const lim = Number(u.searchParams.get('limit') || 8); + let list = REAL; + if (include.includes('museum')) list = REAL.filter((r) => /博物馆|纪念馆|展览馆/.test(r[0])); + else if (include.includes('attraction')) list = REAL.filter((r) => !/博物馆|纪念馆|展览馆/.test(r[0])); + const feats = list + .filter((r) => r[1] >= bbox[1] - 1 && r[1] <= bbox[3] + 1 && r[2] >= bbox[0] - 1 && r[2] <= bbox[2] + 1) + .slice(0, lim) + .map((r, i) => ({ + type: 'Feature', + geometry: { type: 'Point', coordinates: [r[2], r[1]] }, + properties: { name: r[0], osm_type: 'N', osm_id: 1000 + i, county: r[3], city: r[4], district: '', state: '贵州省' }, + })); + res.writeHead(200, { 'content-type': 'application/json' }); + res.end(JSON.stringify({ type: 'FeatureCollection', features: feats })); + }); + await new Promise((r) => photon.listen(PHOTON_PORT, '127.0.0.1', r)); + + // ---- 带 PHOTON_ENDPOINT 启动服务端 + const server = spawn('node', ['server.js'], { + cwd: path.join(__dirname, '..'), + env: { ...process.env, PHOTON_ENDPOINT: `http://127.0.0.1:${PHOTON_PORT}/api` }, + stdio: ['ignore', 'pipe', 'pipe'], + }); + let banner = ''; + server.stdout.on('data', (d) => { banner += d.toString(); }); + server.stderr.on('data', (d) => { banner += d.toString(); }); + await sleep(3000); + const m = banner.match(/http:\/\/127\.0\.0\.1:(\d+)/); + const base = m ? `http://127.0.0.1:${m[1]}` : BASE; + console.log('服务端地址 =', base); + + // ---- 无头 Chrome + const chrome = spawn(CHROME, [ + '--headless=new', '--disable-gpu', '--hide-scrollbars', + `--remote-debugging-port=${PORT}`, + '--user-data-dir=' + path.join(os.tmpdir(), 'tripverifyfull' + Date.now()), + 'about:blank', + ], { stdio: 'ignore' }); + + let wsUrl = null; + for (let i = 0; i < 30 && !wsUrl; i += 1) { + await sleep(500); + try { + const res = await fetch(`http://127.0.0.1:${PORT}/json/version`); + wsUrl = (await res.json()).webSocketDebuggerUrl; + } catch (e) { /* 还没起来 */ } + } + if (!wsUrl) { console.error('chrome 未启动'); process.exit(1); } + + const browser = await CDP.connect(wsUrl); + const { result: { targetId } } = await browser.send('Target.createTarget', { url: 'about:blank' }); + const { result: { sessionId } } = await browser.send('Target.attachToTarget', { targetId, flatten: true }); + const S = (m, p) => browser.send(m, p, sessionId); + await S('Page.enable'); + await S('Runtime.enable'); + await S('Emulation.setDeviceMetricsOverride', { width: 1280, height: 1400, deviceScaleFactor: 1, mobile: false }); + await S('Page.navigate', { url: base }); + await sleep(2500); + + const evalJs = async (expr) => { + const r = await S('Runtime.evaluate', { expression: expr, awaitPromise: true, returnByValue: true }); + if (r.result?.exceptionDetails) throw new Error(JSON.stringify(r.result.exceptionDetails).slice(0, 400)); + return r.result?.result?.value; + }; + + const real = await evalJs(`(async () => { + const res = await fetch('/api/analyze', { + method: 'POST', + headers: { 'content-type': 'application/json' }, + body: JSON.stringify({ + origin: { name: '河池市金城江区', lat: 24.69562, lon: 108.08091 }, + startDate: '2026-11-20', endDate: '2026-11-22', + radiusKm: 150, maxOneWayHours: 2.5, excludeLocal: true, + transportPrefs: ['不限'], interests: [], + }), + }); + const txt = await res.text(); + for (const line of txt.split('\\n')) { + if (!line.startsWith('data:')) continue; + const j = JSON.parse(line.slice(5).trim()); + if (j.type === 'result') return j.data; + if (j.type === 'error') return { error: j.message }; + } + return { error: 'no result' }; + })()`); + if (real.error) { console.error('分析失败:', real.error); process.exit(1); } + console.log('真实候选数 =', real.candidates.length); + + await evalJs(`(() => { + state.analysis = ${JSON.stringify(real)}; + gotoStep(2); renderStep2(); renderCards(); + return true; + })()`); + await sleep(1800); + + const groups = await evalJs(`(() => [...document.querySelectorAll('#cards .place-group')].map(g => ({ + key: g.dataset.place, + head: g.querySelector('.place-head').innerText.replace(/\\n/g, ' | '), + items: [...g.querySelectorAll('.dest-card .card-title h4')].map(x => x.textContent), + })))()`); + console.log('=== 页面真实分组 ==='); + for (const g of groups) console.log(' ', g.key, '→', g.items.join(', '), '||', g.head); + + const undef = await evalJs(`(() => { + const t = document.querySelector('#cards').innerText; + const hits = (t.match(/undefined/g) || []).length; + return { hits, sample: hits ? t.split('\\n').filter(x => x.includes('undefined')).slice(0, 5) : [] }; + })()`); + console.log('卡片内 undefined 出现次数 =', undef.hits, undef.sample); + + // 空组名检查 + const emptyGroup = await evalJs(`(() => [...document.querySelectorAll('#cards .place-group')] + .filter(g => !g.dataset.place || g.dataset.place === '?' || /\\|\\s*\\?/.test(g.innerText)) + .map(g => g.dataset.place))()`); + console.log('空组名分组 =', emptyGroup.length, emptyGroup); + + // 搜索 + await evalJs(`(() => { const i = document.querySelector('#candSearch'); i.value='荔波'; i.dispatchEvent(new Event('input',{bubbles:true})); return true; })()`); + await sleep(600); + console.log('搜索「荔波」→ 卡片', await evalJs(`document.querySelectorAll('#cards .dest-card').length`), + '/ 提示条:', await evalJs(`document.querySelector('#filterNote')?.innerText`)); + await evalJs(`document.querySelector('#candSearchClear').click()`); + await sleep(500); + + // 折叠 + const beforeH = await evalJs(`document.querySelector('#cards .place-group').getBoundingClientRect().height`); + await evalJs(`(() => { const h=document.querySelector('#cards .place-head'); if(h) h.click(); return true; })()`); + await sleep(600); + const afterH = await evalJs(`document.querySelector('#cards .place-group').getBoundingClientRect().height`); + console.log('折叠前后高度 =', Math.round(beforeH), '→', Math.round(afterH), afterH < beforeH ? '(已折叠)' : '(未折叠)'); + await evalJs(`(() => { const h=document.querySelector('#cards .place-head'); if(h) h.click(); return true; })()`); + await sleep(500); + + const box = await evalJs(`(() => { const r = document.querySelector('#panel2').getBoundingClientRect(); return { x: r.x + scrollX, y: r.y + scrollY, width: r.width, height: Math.min(r.height, 2400) }; })()`); + const shot = await S('Page.captureScreenshot', { format: 'png', captureBeyondViewport: true, clip: { ...box, scale: 1 } }); + fs.writeFileSync(path.join(OUT, 'preview-step2-full.png'), Buffer.from(shot.result.data, 'base64')); + console.log('截图已保存 preview/preview-step2-full.png'); + + browser.ws.close(); + chrome.kill(); + server.kill(); + photon.close(); + process.exit(undef.hits || emptyGroup.length ? 1 : 0); +})().catch((e) => { console.error('FAIL', e.message); process.exit(1); });

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