(function () {
  "use strict";

  const CATEGORIES = {
    water: {
      label: "水", title: "水分析", subtitle: "雨洪与水环境",
      summary: "新数据已经形成地形、建筑淹没深度、364条径流路径和海绵设施方案，可直接开展空间雨洪诊断；排水管网和水质仍需新增数据。",
      metrics: [["高倒灌风险", "105栋"], ["最大淹没", "0.55m"], ["径流路径", "364条"], ["海绵设施", "669处"]],
      items: [
        ["flood", "海绵内涝风险评估（多维）", "done", "sponge_risk"],
        ["flood4d", "4D暴雨动态淹没模拟（涨水）", "done", "inundation_sim"], ["flowpath", "地表汇流水动力学脉络", "done", "runoff_streams"],
        ["retention", "雨洪调蓄需求与缺口", "todo"], ["roof", "建筑屋面径流贡献", "todo"],
        ["catchment", "地形与汇水分区", "todo"], ["runoff", "综合径流系数", "todo"],
        ["water_change", "拆违前后径流变化", "todo"],
        ["drainage", "排水管网承载分析", "todo"], ["water_quality", "水质与河道生态分析", "todo"]
      ]
    },
    green: {
      label: "绿", title: "绿色分析", subtitle: "生态与开放空间",
      summary: "新数据已生成雨水花园、生物沟、下凹绿地和蓄水设施方案，可分析海绵增绿节点；现状绿地、树冠和生态连通仍需独立图层。",
      metrics: [["雨水花园", "212处"], ["生物沟", "270处"], ["下凹绿地", "82处"], ["方案投资", "900.47万元"]],
      items: [
        ["sponge_green", "海绵微改造规划布局（669处）", "done", "sponge_plan"], ["planning", "经典规划色系（莫兰迪）", "done", "planning"],
        ["green_potential", "潜在增绿空间", "todo"], ["eco_node", "生态充能节点", "todo"],
        ["released", "拆违释放空间识别", "todo"], ["green_area", "现状绿地面积统计", "todo"],
        ["green_layer", "绿地空间图层", "todo"],
        ["park_service", "公园服务半径", "todo"], ["green_connect", "绿地连通性", "todo"],
        ["eco_corridor", "生态廊道识别", "todo"], ["canopy", "树冠与遮阴分析", "todo"],
        ["heat_island", "热岛缓解效应", "todo"], ["biodiversity", "生物多样性分析", "todo"]
      ]
    },
    people: {
      label: "人", title: "人口分析", subtitle: "人口活动与空间使用",
      summary: "建筑级24小时热力已形成，可比较工作日、周末和昼夜活动，并识别日间闲置与时分复用机会。",
      metrics: [["建筑对象", "369栋"], ["热力时段", "12时段"], ["工作日均值", "41.87"], ["周末均值", "61.85"]],
      items: [
        ["heat24", "24小时时空热力场（动态）", "done", "temporal_heat"], ["weekday", "工作日与周末对比", "todo"],
        ["daynight", "白天与夜间对比", "todo"], ["building_heat", "建筑级人口热度", "todo"],
        ["activity_diff", "昼夜活动差异", "todo"], ["day_idle", "日间闲置建筑识别", "todo"],
        ["sleeping", "睡城特征识别", "todo"], ["time_share", "时分复用潜力", "todo"],
        ["road_heat", "道路活动热力", "todo"], ["crowd_type", "人群类型识别", "todo"],
        ["od", "出行OD与活动轨迹", "todo"], ["access", "公共服务可达性", "todo"],
        ["care_gap", "老幼人群服务缺口", "todo"]
      ]
    },
    industry: {
      label: "产", title: "产业分析", subtitle: "产业商业与空间活力",
      summary: "现有POI与人口热力可用于判断商业供需关系，重点发现高人流低商业和供需双热空间，并提出复用机会。",
      metrics: [["供需平衡", "236栋"], ["僵尸空心", "85栋"], ["供需双热", "46栋"], ["高人流低商业", "2栋"]],
      items: [
        ["overclocking", "城市超频与供需错配", "done", "overclocking"], ["poi", "商业POI数量", "todo"],
        ["poi_mix", "商业类型构成", "todo"], ["price", "平均消费价格", "todo"], ["rating", "商户评分分析", "todo"],
        ["supply", "商业供给指数", "todo"], ["demand", "人流需求指数", "todo"],
        ["highflow_lowbiz", "高人流低商业识别", "todo"], ["double_hot", "供需双热空间", "todo"], ["balance", "商业供需平衡分析", "todo"],
        ["reuse", "空间复用潜力", "todo"],
        ["tidal", "潮汐商业与共享空间", "todo"], ["vacancy", "商铺空置率", "todo"],
        ["rent", "租金与经营收益", "todo"], ["ownership", "产权与资产分析", "todo"],
        ["industry_chain", "产业链关联分析", "todo"]
      ]
    },
    risk: {
      label: "风险", title: "风险分析", subtitle: "建筑安全与城市韧性",
      summary: "新数据识别出39栋高风险、329栋中风险和39栋临时建筑；消防间距与应急疏散字段未包含在本次数据中，应调整为待开发。",
      metrics: [["高风险", "39栋"], ["中风险", "329栋"], ["低风险", "1栋"], ["临时建筑", "39栋"]],
      items: [
        ["risk_level", "结构安全与危房风险", "done", "risk"], ["structure", "建筑楼层与高度分布", "done", "floors"],
        ["height", "建筑高度分析", "todo"], ["temporary", "临时违章建筑识别", "todo"],
        ["risk_reason", "建筑风险原因", "todo"], ["fire", "消防间距分析", "todo"],
        ["nearest", "最近建筑与实际间距", "todo"], ["risk_change", "拆除前后风险对比", "todo"],
        ["friction", "空间阻碍与摩擦分析", "todo"], ["quality", "建筑质量现场检测", "todo"],
        ["fire_network", "消防通道网络分析", "todo"], ["evacuation", "应急疏散模拟", "todo"],
        ["earthquake", "地震与灾害韧性", "todo"], ["monitor", "实时监测与风险预警", "todo"]
      ]
    }
  };

  function applyProjectFacts() {
    const data = window.BUILDING_MODEL_DATA || {};
    const buildings = Array.isArray(data.buildings) ? data.buildings : [];
    const streams = Array.isArray(data.runoff_streams) ? data.runoff_streams : [];
    const facilities = Array.isArray(data.sponge_facilities) ? data.sponge_facilities : [];
    const macro = data.macro || {};
    const count = (field, value) => buildings.filter(item => String(item[field] ?? "") === value).length;
    const includes = (field, value) => buildings.filter(item => String(item[field] ?? "").includes(value)).length;
    const facilityCount = value => facilities.filter(item => `${item.name || ""}${item.type || ""}`.includes(value)).length;
    const avgHeat = field => {
      const values = buildings.flatMap(item => Array.isArray(item[field]) ? item[field].map(Number).filter(Number.isFinite) : []);
      return values.length ? (values.reduce((sum, value) => sum + value, 0) / values.length).toFixed(2) : "--";
    };
    const maxFlood = buildings.reduce((max, item) => Math.max(max, Number(item.inundation_depth_m) || 0), 0).toFixed(2);
    CATEGORIES.water.metrics = [["高倒灌风险", `${count("sponge_risk_level", "高倒灌风险")}栋`], ["最大淹没", `${maxFlood}m`], ["径流路径", `${streams.length}条`], ["海绵设施", `${facilities.length}处`]];
    CATEGORIES.water.summary = `${data.target_dataset || "当前项目"}已形成地形、建筑淹没深度、${streams.length}条径流路径和${facilities.length}处海绵设施方案。`;
    CATEGORIES.green.metrics = [["雨水花园", `${facilityCount("雨水花园")}处`], ["生物沟", `${facilityCount("生物沟")}处`], ["下凹绿地", `${facilityCount("下凹绿地")}处`], ["设施总量", `${facilities.length}处`]];
    CATEGORIES.people.metrics = [["建筑对象", `${buildings.length}栋`], ["热力时段", "12时段"], ["工作日均值", avgHeat("heat_wd")], ["周末均值", avgHeat("heat_we")]];
    CATEGORIES.industry.metrics = [["供需平衡", `${includes("mismatch_tag", "平衡")}栋`], ["僵尸空心", `${includes("mismatch_tag", "僵尸")}栋`], ["供需双热", `${includes("mismatch_tag", "双热")}栋`], ["高人流低商业", `${includes("mismatch_tag", "高人流")}栋`]];
    CATEGORIES.risk.metrics = [["高风险", `${count("risk_level", "高风险")}栋`], ["中风险", `${count("risk_level", "中风险")}栋`], ["低风险", `${count("risk_level", "低风险")}栋`], ["临时建筑", `${buildings.filter(item => item.is_temporary).length}栋`]];
    CATEGORIES.risk.summary = `${data.target_dataset || "当前项目"}共识别${buildings.length}栋建筑；建筑结构、层数和风险字段可直接用于当前诊断。`;
    Object.values(CATEGORIES).forEach(category => category.metrics = category.metrics.map(([label, value]) => [label, value]));
    window.ACTIVE_PROJECT_MACRO = macro;
  }
  applyProjectFacts();

  const theme3d = {sponge_risk:"sponge_risk", sponge_plan:"sponge_plan", inundation_sim:"inundation_sim", runoff_streams:"runoff_streams", planning:"planning", temporal_heat:"temporal_heat", overclocking:"overclocking", floors:"floors", risk:"risk"};
  const theme2d = {sponge_risk:"sponge", sponge_plan:"sponge", inundation_sim:"inundation", runoff_streams:"elevation", planning:"base", temporal_heat:"heat", overclocking:"mismatch", floors:"floors", risk:"risk"};
  const LEGENDS = {
    sponge_plan:[["#00e676","微型雨水花园 (495处, 下渗滞留)","point"],["#00e5ff","生物滞留下凹绿地 (45处, 蓄水净化)","point"],["#2979ff","地下调蓄池/沉井 (3处, 核心集水)","point"],["#ffd600","透水铺装嵌草坪 (1处, 渗排结合)","point"]],
    sponge_risk:[["#ff1744","高倒灌风险 (>25cm水深, 293栋)"],["#ffab00","中度内涝 (10~25cm, 23栋)"],["#00e676","安全/低风险 (<10cm, 60栋)"],["#00e676","海绵规划设施点位 (544处已联动)","point"]],
    inundation_sim:[["#0055aa","受淹浸没建筑底层"],["#00d2ff","暴雨地表积水面 (2.8m)"],["#e06d63","地势未淹安全建筑"]],
    runoff_streams:[["#00d2ff","3D地表汇流主干水线 (295条)"],["#1e2e42","地表汇水区建筑"]],
    planning:[["#e06d63","核心多层街区"],["#f6cb90","次级商业建筑"],["#a0d8b3","外围组团住宅"],["#6a8db5","高层与公共地标"]],
    temporal_heat:[["#ff1744","高热聚焦点 (>55)"],["#ffd600","活跃中热 (40~55)"],["#00e676","常规流动 (25~40)"],["#00d2ff","低度人流 (<25)"]],
    overclocking:[["#ff1744","高人流-低商业 (潜力洼地)"],["#00e676","供需双热区 (核心商圈)"],["#ffab00","僵尸空心区 (供需双低)"],["#2b3d54","供需平衡区"]],
    floors:[["#00e676","1-2层 (低层)"],["#00d2ff","3-4层 (多层)"],["#ffd600","5-6层 (中多层)"],["#ff6d00","7-8层 (高多层)"]],
    risk:[["#ff1744","高风险危房"],["#ff9100","中风险"],["#00e676","低风险"]]
  };
  let dimension = "risk";
  let itemKey = "risk_level";

  function enrichData() {
    const buildings = window.BUILDING_MODEL_DATA?.buildings || [];
    const byId = new Map(buildings.map(b => [b.id || b.building_id, b]));
    const source = typeof activeGeoJSON !== "undefined" ? activeGeoJSON : null;
    (source?.features || []).forEach(feature => {
      const p = feature.properties || {};
      Object.assign(p, byId.get(p.building_id) || {});
    });
  }

  function currentItem() {
    return CATEGORIES[dimension].items.find(item => item[0] === itemKey) || CATEGORIES[dimension].items[0];
  }

  function numeric(value, fallback = 0) {
    const n = Number(value);
    return Number.isFinite(n) ? n : fallback;
  }

  function heatValue(p) {
    const values = Array.isArray(p.heat_wd) ? p.heat_wd : (Array.isArray(p.heat_hours) ? p.heat_hours : []);
    if (values.length) return values.reduce((sum, value) => sum + numeric(value), 0) / values.length;
    return numeric(p.pop_day, numeric(p.pop_density_day));
  }

  function ramp(value, max, hue = 18) {
    const ratio = Math.max(0, Math.min(1, max ? value / max : 0));
    return `hsl(${hue + (1-ratio)*92} 58% ${72-ratio*30}%)`;
  }

  function styleFeature(feature) {
    const p = feature.properties || {};
    const theme = theme2d[currentItem()[3]] || "base";
    let fill = "#f7f5ef", color = "#777", weight = 1.1, fillOpacity = .55;
    if (theme === "risk") fill = ({"高风险":"#d9534f", "中风险":"#f0ad4e", "低风险":"#5b8a60"})[p.risk_level] || "#aaa";
    if (theme === "fire") { fill = p.fire_spacing_issue ? "#d9534f" : "#dfe8df"; color = p.fire_spacing_issue ? "#b63f3b" : "#718071"; weight = p.fire_spacing_issue ? 2.6 : 1; }
    if (theme === "temporary") { fill = p.is_temporary ? "#d9534f" : "#dfe7df"; color = p.is_temporary ? "#a73232" : "#889188"; weight = p.is_temporary ? 3 : 1; }
    if (theme === "floors") fill = ramp(numeric(p.layers || p.floors), 8, 22);
    if (theme === "spacing") fill = ramp(Math.max(0, 6-numeric(p.actual_spacing)), 6, 5);
    if (theme === "roof") fill = ramp(numeric(p.footprint_area), 600, 175);
    if (theme === "elevation") fill = ramp(numeric(p.elevation_m)-1067, 26, 165);
    if (theme === "inundation") fill = ramp(numeric(p.inundation_depth_m), .55, 190);
    if (theme === "sponge") {
      fill = p.sponge_risk_level === "高倒灌风险" ? "#d9534f" : p.sponge_risk_level === "中度内涝风险" ? "#f0ad4e" : "#5b8a60";
    }
    if (theme === "heat" || theme === "daynight") fill = ramp(heatValue(p), 100, 0);
    if (theme === "idle") fill = String(p.multiplex_tag || "").includes("日间闲置") ? "#55798b" : "#dfe6df";
    if (theme === "sleeping") fill = ramp(numeric(p.sleeping_town_index), 1, 205);
    if (theme === "multiplex") fill = String(p.multiplex_tag || "").includes("日间闲置") ? "#f0ad4e" : "#6e8b68";
    if (["poi", "supply", "price", "rating"].includes(theme)) {
      const field = {poi:"poi_count", supply:"poi_count", price:"poi_avg_price", rating:"poi_score"}[theme];
      const max = {poi:18, supply:18, price:253, rating:5}[theme];
      fill = ramp(numeric(p[field]), max, 25);
    }
    if (theme === "mismatch") {
      const tag = p.mismatch_tag || p.mismatch_type || "";
      fill = tag.includes("高人流") ? "#d9534f" : tag.includes("双热") ? "#f0ad4e" : "#6f8e6c";
    }
    return {fillColor:fill, color, weight, fillOpacity};
  }

  function statusText(status) {
    return status === "done" ? "已完成" : status === "base" ? "已有基础" : "正在开发";
  }

  function rowsFor(category, item) {
    const data = window.BUILDING_MODEL_DATA || {};
    const buildingCount = Array.isArray(data.buildings) ? data.buildings.length : 0;
    const streamCount = Array.isArray(data.runoff_streams) ? data.runoff_streams.length : 0;
    const facilityCount = Array.isArray(data.sponge_facilities) ? data.sponge_facilities.length : 0;
    const common = {
      water: [["数据能力", "地形 + 淹没 + 径流"], ["当前对象", `${buildingCount}栋 / ${streamCount}条路径`], ["当前图层", item[1]]],
      green: [["数据能力", `${facilityCount}处海绵设施方案`], ["项目数据", data.target_dataset || "当前项目"], ["当前图层", item[1]]],
      people: [["时间粒度", "每2小时"], ["日期类型", "工作日 / 周末"], ["当前图层", item[1]]],
      industry: [["分析单元", "建筑对象"], ["数据来源", "热力 + 商业POI"], ["当前图层", item[1]]],
      risk: [["分析对象", `${buildingCount}栋建筑`], ["现有字段", "结构 / 层数 / 风险"], ["当前图层", item[1]]]
    };
    return common[category];
  }

  function countBy(items, getter, preferred = []) {
    const counts = new Map();
    items.forEach(entry => {
      const key = String(getter(entry) || "未分类");
      counts.set(key, (counts.get(key) || 0) + 1);
    });
    const keys = preferred.length ? preferred.filter(key => counts.has(key)) : [...counts.keys()].sort((a,b) => counts.get(b) - counts.get(a)).slice(0, 7);
    return {labels:keys, values:keys.map(key => counts.get(key) || 0)};
  }

  function chartSeries(item) {
    const data = window.BUILDING_MODEL_DATA || {};
    const buildings = Array.isArray(data.buildings) ? data.buildings : [];
    const facilities = Array.isArray(data.sponge_facilities) ? data.sponge_facilities : [];
    const theme = item[3];
    if (theme === "sponge_risk") return countBy(buildings, b => b.sponge_risk_level, ["高倒灌风险","中度内涝风险","安全排水区"]);
    if (theme === "sponge_plan") return countBy(facilities, f => f.type || f.name);
    if (theme === "inundation_sim") {
      const bins = [0,0,0,0];
      buildings.forEach(b => { const v=numeric(b.inundation_depth_m); bins[v<=0?0:v<=.15?1:v<=.3?2:3]++; });
      return {labels:["未淹没","≤0.15m","0.15–0.30m",">0.30m"],values:bins};
    }
    if (theme === "runoff_streams") return {labels:["汇流路径","海绵设施","高倒灌建筑"],values:[(data.runoff_streams||[]).length,facilities.length,buildings.filter(b=>b.sponge_risk_level==="高倒灌风险").length]};
    if (theme === "planning") return countBy(buildings, b => b.structure);
    if (theme === "temporal_heat") {
      const labels=["00","02","04","06","08","10","12","14","16","18","20","22"];
      const values=labels.map((_,i)=>{const vals=buildings.map(b=>numeric((b.heat_wd||[])[i],NaN)).filter(Number.isFinite);return vals.length?vals.reduce((a,v)=>a+v,0)/vals.length:0;});
      return {labels,values};
    }
    if (theme === "overclocking") return countBy(buildings, b => b.mismatch_tag || b.mismatch_type);
    if (theme === "floors") return countBy(buildings, b => `${numeric(b.layers || b.floors)}层`, ["1层","2层","3层","4层","5层","6层","7层","8层"]);
    return countBy(buildings, b => b.risk_level, ["高风险","中风险","低风险"]);
  }

  function drawAnalysisChart(item) {
    const canvas = document.getElementById("analysisChart");
    if (!canvas) return;
    const box = canvas.getBoundingClientRect();
    const dpr = Math.min(2, window.devicePixelRatio || 1);
    canvas.width = Math.max(1, Math.round(box.width*dpr)); canvas.height = Math.max(1, Math.round(box.height*dpr));
    const ctx = canvas.getContext("2d"); ctx.scale(dpr,dpr); ctx.clearRect(0,0,box.width,box.height);
    const {labels,values}=chartSeries(item); const max=Math.max(1,...values); const left=28,right=5,top=10,bottom=39; const width=box.width-left-right; const height=box.height-top-bottom; const gap=6; const barW=Math.max(8,(width-gap*(values.length-1))/Math.max(1,values.length));
    ctx.strokeStyle="rgba(17,17,17,.10)";ctx.lineWidth=1;ctx.beginPath();ctx.moveTo(left,top+height+.5);ctx.lineTo(left+width,top+height+.5);ctx.stroke();
    values.forEach((value,index)=>{const h=Math.max(2,value/max*height);const x=left+index*(barW+gap);const y=top+height-h;ctx.fillStyle=index===0?"#315842":"#9fb4a4";ctx.beginPath();ctx.roundRect(x,y,barW,h,Math.min(5,barW/3));ctx.fill();ctx.fillStyle="#5f655f";ctx.font="9px Microsoft YaHei";ctx.textAlign="center";ctx.fillText(String(Math.round(value)),x+barW/2,Math.max(9,y-4));ctx.save();ctx.translate(x+barW/2,top+height+10);ctx.rotate(-.42);ctx.textAlign="right";ctx.fillText(String(labels[index]).slice(0,9),0,0);ctx.restore();});
    document.getElementById("analysisChartCaption").textContent = `${item[1]} · 当前项目`;
  }

  function renderRight() {
    const category = CATEGORIES[dimension];
    const item = currentItem();
    const data = window.BUILDING_MODEL_DATA || {};
    const macro = data.macro || {};
    const buildings = Array.isArray(data.buildings) ? data.buildings : [];
    const streams = Array.isArray(data.runoff_streams) ? data.runoff_streams : [];
    const fixedMetrics = [
      ["建筑总栋数", `${numeric(macro.total_buildings, buildings.length)}栋`],
      ["总建筑面积", `${(numeric(macro.total_gross_area_m2) / 10000).toFixed(2)}万㎡`],
      ["DEM地势落差", `${numeric(macro.elevation_delta_m).toFixed(1)}m`],
      ["汇流水系脉络", `${numeric(macro.streams_count, streams.length)}条`],
      ["高倒灌风险", `${numeric(macro.sponge_high_risk_buildings)}栋`],
      ["安全排水区", `${numeric(macro.sponge_safe_buildings)}栋`],
      ["海绵调蓄需求", `${numeric(macro.sponge_water_demand_m3).toLocaleString(undefined,{maximumFractionDigits:1})}m³`],
      ["建筑密度 / FAR", `${numeric(macro.building_density_pct).toFixed(2)}% / ${numeric(macro.far).toFixed(2)}`]
    ];
    document.getElementById("analysisTitle").textContent = "项目总体数据";
    document.getElementById("analysisState").textContent = `${category.title} · ${category.subtitle}`;
    document.getElementById("analysisScore").textContent = category.label;
    document.getElementById("analysisItemLabel").textContent = data.target_dataset || "测试地形图260821002";
    document.getElementById("analysisSummary").textContent = `当前查看：${item[1]}。总体数据保持固定，专题数据与地图图层同步切换。`;
    document.getElementById("analysisKpis").innerHTML = fixedMetrics.map(([label, value]) => `<div class="kpi"><span>${label}</span><b>${value}</b></div>`).join("");
    document.getElementById("analysisSubitemTitle").textContent = item[1];
    document.getElementById("analysisData").innerHTML = `<h3>${item[1]} <span class="status-chip ${item[2]}">${statusText(item[2])}</span></h3>${rowsFor(dimension, item).map(([label,value]) => `<div class="data-row"><span>${label}</span><b>${value}</b></div>`).join("")}`;
    const detail = document.getElementById("detail");
    if (!detail.dataset.buildingId) detail.innerHTML = `<h3>建筑体块数据</h3><p>点击中间三维模型中的建筑，查看“${item[1]}”对应的完整数据。</p>`;
    requestAnimationFrame(() => drawAnalysisChart(item));
  }

  function renderMapLegend(item) {
    const legend = LEGENDS[item[3]] || [];
    const title = document.getElementById("mapLegendTitle");
    const items = document.getElementById("mapLegendItems");
    const panel = document.getElementById("mapLegend");
    if (!title || !items || !panel) return;
    title.textContent = `${item[1]}图例`;
    items.innerHTML = legend.map(([color,label,shape]) => `<div class="map-legend-item"><i class="map-legend-swatch${shape === "point" ? " point" : ""}" style="background:${color}"></i><span>${label}</span></div>`).join("");
    panel.hidden = legend.length === 0;
  }

  function selectItem(key) {
    itemKey = key;
    const item = currentItem();
    document.querySelectorAll("#analysisSubnav .layer").forEach(button => button.classList.toggle("active", button.dataset.analysis === key));
    document.getElementById("layerName").textContent = item[1];
    renderRight();
    renderMapLegend(item);
    window.renderMap?.();
    const targetTheme = theme3d[item[3]] || "planning";
    window.sendThreeCommand?.("theme", {value:targetTheme});
  }

  function renderSubnav() {
    const nav = document.getElementById("analysisSubnav");
    const items = CATEGORIES[dimension].items;
    nav.innerHTML = items.map((item, index) => `<button class="layer${index === 0 ? " active" : ""}" data-analysis="${item[0]}" data-status="${item[2]}" ${item[2] === "todo" ? "disabled" : `onclick="window.AnalysisHierarchy.selectItem('${item[0]}')"`}>${item[1]}</button>`).join("");
    nav.onclick = event => {
      const button = event.target.closest("button[data-analysis]:not(:disabled)");
      if (button && nav.contains(button)) selectItem(button.dataset.analysis);
    };
  }

  function selectDimension(next) {
    dimension = next;
    itemKey = CATEGORIES[next].items.find(item => item[2] === "done")?.[0] || CATEGORIES[next].items[0][0];
    document.querySelectorAll("#twoDimensionGrid [data-dimension]").forEach(button => button.classList.toggle("active", button.dataset.dimension === next));
    renderSubnav();
    selectItem(itemKey);
  }

  function propertyText(p) {
    const item = currentItem();
    const theme = theme2d[item[3]] || item[3];
    if (theme === "roof") return `屋面面积 ${Math.round(numeric(p.footprint_area))}㎡，50mm降雨下估算屋面径流 ${(numeric(p.footprint_area)*0.05*0.85).toFixed(2)}m³。`;
    if (theme === "heat" || theme === "daynight") return `建筑热力均值 ${heatValue(p).toFixed(1)}，包含工作日与周末各12个时段。`;
    if (["poi","supply","price","rating","mismatch","multiplex"].includes(theme)) return `POI ${numeric(p.poi_count)}个，供需类型：${p.mismatch_tag || p.mismatch_type || "暂无分类"}，复用判断：${p.multiplex_tag || "暂无"}。`;
    if (theme === "fire" || theme === "spacing") return `实际间距 ${numeric(p.actual_spacing).toFixed(2)}m，${p.fire_spacing_issue ? "存在消防间距隐患" : "消防间距相对正常"}。`;
    if (theme === "temporary") return `${p.is_temporary ? "临时建筑，可作为减法更新和空间释放候选。" : "非临时建筑，当前专题下作为背景对象。"}`;
    if (theme === "inundation" || theme === "sponge" || theme === "elevation") return `建筑高程 ${numeric(p.elevation_m).toFixed(2)}m，模拟淹没深度 ${numeric(p.inundation_depth_m).toFixed(2)}m，海绵风险：${p.sponge_risk_level || "暂无"}。${p.sponge_recommendation || ""}`;
    return `风险等级 ${p.risk_level || "暂无"}，结构类型：${p.structure || "暂无"}。`;
  }

  function showBuildingDetail(p) {
    const item = currentItem();
    const id = p.building_id || p.id || "建筑对象";
    const area = numeric(p.total_area || p.building_area);
    const heatWd = Array.isArray(p.heat_wd) ? p.heat_wd.map(numeric) : [];
    const heatWe = Array.isArray(p.heat_we) ? p.heat_we.map(numeric) : [];
    const heatBars = values => {
      const max = Math.max(1, ...values);
      return values.map(value => `<i style="height:${Math.max(8, value / max * 100)}%"></i>`).join("");
    };
    const food = Math.max(0, numeric(p.food_ratio));
    const entertainment = Math.max(0, numeric(p.ent_ratio));
    const service = Math.max(0, numeric(p.service_ratio, 100 - food - entertainment));
    const ratioTotal = Math.max(1, food + entertainment + service);
    const ratioWidth = value => `${value / ratioTotal * 100}%`;
    const detail = document.getElementById("detail");
    detail.dataset.buildingId = id;
    detail.classList.remove("empty");
    document.getElementById("analysisSubitemTitle").textContent = id;
    detail.innerHTML = `<div class="building-detail-title"><h3>${id}</h3><small>CAD标注 · ${p.raw_text || "-"}</small></div><div class="building-detail-tags"><span>${p.is_temporary ? "临时违章建筑" : "永久性建筑"}</span><span class="${String(p.sponge_risk_level).includes("高") ? "alert" : ""}">${p.sponge_risk_level || "海绵风险待判定"}</span><span class="${p.risk_level === "高风险" ? "alert" : ""}">${p.risk_level || "结构风险待判定"}</span></div><div class="building-attribute-grid"><div><span>层数 / 高度</span><b>${numeric(p.layers || p.floors)}层 / ${numeric(p.height).toFixed(1)}m</b></div><div><span>DEM基底高程</span><b>${numeric(p.elevation_m).toFixed(2)}m</b></div><div><span>结构体系</span><b>${p.structure || "暂无"}</b></div><div><span>占地 / 总建面</span><b>${numeric(p.footprint_area).toLocaleString()}㎡ / ${area.toLocaleString()}㎡</b></div><div><span>周边商户 POI</span><b>${numeric(p.poi_count)}个 · ¥${numeric(p.poi_avg_price).toFixed(1)}</b></div><div><span>消费评分 / 错配</span><b>${numeric(p.poi_score).toFixed(1)} · ${p.mismatch_tag || "暂无"}</b></div><div><span>受淹内涝深度</span><b>${numeric(p.inundation_depth_m).toFixed(2)}m</b></div><div><span>当前专题</span><b>${item[1]}</b></div></div><div class="building-recommendation"><b>海绵城市体检与工程治理指引</b><br>${p.sponge_recommendation || propertyText(p)}</div><div class="building-data-section"><span>24小时人群流动 · 工作日</span><div class="heat-strip">${heatBars(heatWd)}</div></div><div class="building-data-section"><span>24小时人群流动 · 周末</span><div class="heat-strip weekend">${heatBars(heatWe)}</div></div><div class="building-data-section"><span>消费业态比例</span><div class="ratio-track"><i style="width:${ratioWidth(food)}"></i><i style="width:${ratioWidth(entertainment)}"></i><i style="width:${ratioWidth(service)}"></i></div><div class="ratio-labels"><span>餐饮 ${food}%</span><span>娱乐 ${entertainment}%</span><span>服务 ${service}%</span></div></div>`;
  }

  window.AnalysisHierarchy = {selectDimension, selectItem, styleFeature, showBuildingDetail};
  enrichData();
  selectDimension("risk");
  document.getElementById("threeView")?.addEventListener("load", () => {
    const item = currentItem();
    window.sendThreeCommand?.("theme", {value:theme3d[item[3]] || "planning"});
  });
  const buildingModal = document.getElementById("buildingModal");
  const closeBuildingModal = () => { buildingModal?.classList.remove("open"); buildingModal?.setAttribute("aria-hidden","true"); };
  document.getElementById("buildingModalClose")?.addEventListener("click", closeBuildingModal);
  buildingModal?.addEventListener("click", event => { if (event.target === buildingModal) closeBuildingModal(); });
  document.addEventListener("keydown", event => { if (event.key === "Escape") closeBuildingModal(); });
  window.addEventListener("resize", () => requestAnimationFrame(() => drawAnalysisChart(currentItem())));
})();