City-Lifeline-Cockpit/.scratch/cockpit-real-data-wayfinding/verify/artifacts/t33/compare-baseline.mjs

/**
 * 票 33：同环境修复前后对照（jitter-report-baseline vs jitter-report-fixed）。
 *
 * 环境说明（诚实口径）：本轮探针环境的白模（cad-bim v8/roofed2 glb 批次）持续流送 +
 * 无 GPU（软件渲染），~680ms/帧的**环境底噪**会污染票面判据 (a)(b) 的绝对阈值
 * （±500ms 无长任务 / p95≤33ms 在该环境物理不可达——静置对照桶同值即证）。
 * 因此用三个**病灶专属**口径对照：
 *   ① 纯 snapshot 长任务：≥100ms 长任务的 ±400ms 伴随请求里含 map-snapshot 且**不含任何
 *      glb/terrain 瓦片**——旧全量重同步的特征形态（白模流送 decode 必然伴随 .glb）；
 *   ② 一轮刷新成簇：纯 snapshot 长任务里时间间隔 <2s 的连簇长度（旧病理：8 批连续）；
 *   ③ 长任务总量与 tick 增量：刷新窗口 p95 − 静置窗口 p95。
 */
import { readFileSync } from 'node:fs'

const [baselinePath, fixedPath] = process.argv.slice(2)
const load = (p) => JSON.parse(readFileSync(p, 'utf8'))

function analyze(report) {
    const tiles = (url) => /\.glb|\.terrain|\/gis\/|\.png|\.jpg/.test(url)
    const snapTimes = report.requests.filter((r) => r.url.includes('map-snapshot')).map((r) => r.t)
    const longTasks = (report.longTasksAll || report.longTaskCorrelation || []).filter((t) => t.dur >= 100)
    const pure = []
    for (const task of longTasks) {
        const rest = (report.longTaskCorrelation.find((c) => Math.abs(c.start - task.start) < 1 && c.dur === task.dur) || {}).rest || []
        const hasSnap = rest.some((u) => u.includes('map-snapshot'))
        const hasTile = rest.some((u) => tiles(u))
        if (hasSnap && !hasTile) pure.push({ start: task.start, dur: task.dur })
    }
    pure.sort((a, b) => a.start - b.start)
    let maxCluster = 0
    let run = 0
    let prev = null
    for (const p of pure) {
        run = prev !== null && p.start - prev < 2000 ? run + 1 : 1
        prev = p.start
        maxCluster = Math.max(maxCluster, run)
    }
    // 帧间隔：刷新窗口 vs 静置窗口（bucket 起点在 30–40s / 60–70s 视为刷新窗口）
    const p95 = (vals) => {
        const s = [...vals].sort((a, b) => a - b)
        return s.length ? s[Math.min(s.length - 1, Math.floor(0.95 * s.length))] : null
    }
    let refreshDts = []
    let idleDts = []
    const buckets = report.frameBuckets || []
    if (buckets.length) {
        for (const b of buckets) {
            const sec = b.from / 1000
            ;(sec >= 30 && sec < 40) || (sec >= 60 && sec < 70) ? refreshDts.push(...b.dts) : idleDts.push(...b.dts)
        }
    } else {
        // 旧版探针没有 frameBuckets：按 fpsWindows 桶近似
        for (const w of report.fpsWindows || []) {
            const sec = w.from / 1000
            const isRefresh = (sec >= 30 && sec < 40) || (sec >= 60 && sec < 70)
            if (isRefresh && w.p95 != null) refreshDts = [w.p95]
            if (!isRefresh && w.p95 != null) idleDts.push(w.p95)
        }
    }
    return {
        longTaskTotal: longTasks.length,
        pureSnapshot: pure.length,
        pureList: pure,
        maxCluster,
        refreshP95: p95(refreshDts),
        idleP95: p95(idleDts),
    }
}

const base = analyze(load(baselinePath))
const fixed = analyze(load(fixedPath))
const fmt = (v) => (v === null ? 'n/a' : Number(v).toFixed(1))
console.log('口径                          基线(无修复)      带修复')
console.log(`≥100ms 长任务总量             ${String(base.longTaskTotal).padEnd(16)} ${fixed.longTaskTotal}`)
console.log(`纯 map-snapshot 长任务(病灶)  ${String(base.pureSnapshot).padEnd(16)} ${fixed.pureSnapshot}`)
console.log(`最长连续簇(≈批数×120ms节拍)   ${String(base.maxCluster).padEnd(16)} ${fixed.maxCluster}`)
console.log(`刷新窗口帧间隔 p95            ${fmt(base.refreshP95).padEnd(16)} ${fmt(fixed.refreshP95)} ms`)
console.log(`静置窗口帧间隔 p95            ${fmt(base.idleP95).padEnd(16)} ${fmt(fixed.idleP95)} ms`)
console.log(`tick 增量(刷新−静置)          ${fmt(base.refreshP95 - base.idleP95).padEnd(16)} ${fmt(fixed.refreshP95 - fixed.idleP95)} ms`)
console.log('\n基线病灶长任务时刻:', base.pureList.map((p) => `${Math.round(p.start)}ms/${p.dur}ms`).join(' ') || '（无）')
console.log('修复后病灶长任务时刻:', fixed.pureList.map((p) => `${Math.round(p.start)}ms/${p.dur}ms`).join(' ') || '（无）')