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Replaces v1 wholesale; v1's stateless POST still works unchanged.\n *\n * Model: log(RTH range %) ~ HAR-RV(1d,5d,22d) + log(Asia range %) + log(Europe range %)\n * Fit: 2244 NQ trade days, walk-forward OOS R2 = 0.547\n * Anchor: RTH open (MAD 0.322 sigma vs 0.488 for settlement)\n *\n * ROUTES\n * GET / health check + history status\n * GET /history inspect the stored window\n * POST / compute ladder (omit rthRanges/rthOpens to use stored history)\n * POST /history append one realized session {date,rthRange,rthOpen}\n * POST /history/bulk one-time backfill {days:[{date,rthRange,rthOpen},...]}\n * DELETE /history wipe (dev only)\n *\n * The JAR should: GET / on startup, and if history.ready is false or history.stale\n * is true, read 22 sessions off the chart and POST /history/bulk once. Thereafter\n * POST /history once per session with the day that just closed.\n */\n\nimport { blob } from \"https://esm.town/v/std/blob\";\n\nconst KEY = \"rangeLadder:history:v1\";\nconst WINDOW = 22; // days the model needs\nconst KEEP = 45; // days retained, gives headroom for gaps/holidays\nconst STALE_DAYS = 5; // newest entry older than this => flag for re-backfill\n\nconst COEF = {\n const: 0.321487,\n lp: 0.115356, // prior day log range %\n m5: 0.267034, // 5d mean log range %\n m22: 0.114478, // 22d mean log range %\n la: 0.144729, // Asia log range %\n le: 0.247273, // Europe log range %\n};\n\nconst RESID_SD = 0.385;\n\n// k -> [empirical touch probability, 80th-pct overshoot in sigma units]\nconst LADDER: Array<[number, number, number]> = [\n [0.15, 0.808, 0.794],\n [0.20, 0.743, 0.780],\n [0.25, 0.678, 0.769],\n [0.30, 0.622, 0.754],\n [0.35, 0.573, 0.735],\n [0.40, 0.529, 0.718],\n [0.45, 0.487, 0.706],\n [0.50, 0.440, 0.695],\n [0.55, 0.397, 0.691],\n [0.60, 0.359, 0.687],\n [0.65, 0.323, 0.680],\n [0.70, 0.291, 0.673],\n [0.75, 0.259, 0.671],\n [0.80, 0.231, 0.669],\n [0.85, 0.205, 0.676],\n [0.90, 0.183, 0.684],\n [0.95, 0.162, 0.693],\n [1.00, 0.143, 0.702],\n [1.10, 0.110, 0.707],\n [1.20, 0.088, 0.700],\n [1.30, 0.070, 0.676],\n [1.40, 0.056, 0.692],\n [1.50, 0.045, 0.658],\n [1.60, 0.036, 0.622],\n [1.70, 0.029, 0.557],\n [1.80, 0.023, 0.601],\n];\n\nconst RUNGS = [0.30, 0.45, 0.60, 0.80, 1.00, 1.30];\nconst GATE = { gap: [0.204, 0.476], ovn: [0.599, 0.774] };\n\nconst GATE_STATS: Record = {\n GREEN: {\n fadeWin: 0.556,\n note: \"quiet ON + small gap — fades viable, edge is thin (n=162)\",\n },\n AMBER: {\n fadeWin: 0.416,\n note: \"mixed — no fade edge, levels are targets only\",\n },\n RED: { fadeWin: 0.186, note: \"large gap — do NOT fade, trend day risk\" },\n};\n\n// ---------------------------------------------------------------- history --\n\ntype Day = { date: string; rthRange: number; rthOpen: number };\n\nasync function loadHistory(): Promise {\n try {\n const h = await blob.getJSON(KEY);\n return Array.isArray(h) ? h : [];\n } catch {\n return [];\n }\n}\n\nconst ISO_DATE = /^\\d{4}-\\d{2}-\\d{2}$/;\n\n/**\n * Newest first, de-duplicated by date, trimmed to KEEP.\n * FIRST occurrence of a date wins: callers put the authoritative record first\n * (the append route prepends the new session), so a re-post of a corrected\n * session must override the stored one rather than be discarded by it.\n */\nfunction normalise(days: Day[]): Day[] {\n const seen = new Map();\n for (const d of days) {\n if (!d?.date || !ISO_DATE.test(d.date)) continue;\n if (Number.isNaN(Date.parse(d.date + \"T00:00:00Z\"))) continue;\n if (!(d.rthRange > 0) || !(d.rthOpen > 0)) continue;\n if (seen.has(d.date)) continue;\n seen.set(d.date, {\n date: d.date,\n rthRange: +d.rthRange,\n rthOpen: +d.rthOpen,\n });\n }\n return [...seen.values()]\n .sort((a, b) => (a.date < b.date ? 1 : -1))\n .slice(0, KEEP);\n}\n\nasync function saveHistory(days: Day[]): Promise {\n const clean = normalise(days);\n await blob.setJSON(KEY, clean);\n return clean;\n}\n\nfunction historyStatus(h: Day[]) {\n const newest = h[0]?.date ?? null;\n const ageDays = newest\n ? Math.floor((Date.now() - Date.parse(newest + \"T00:00:00Z\")) / 86_400_000)\n : null;\n\n // Chart-sourced history develops holes on days MotiveWave isn't opened.\n // Count size lies in that case: 22 entries can span far more than 22 sessions.\n // Flag it by comparing the window's calendar span against expected weekdays.\n let gaps: string[] = [];\n const win = h.slice(0, WINDOW);\n if (win.length >= 2) {\n for (let i = 0; i < win.length - 1; i++) {\n const a = Date.parse(win[i].date + \"T00:00:00Z\");\n const b = Date.parse(win[i + 1].date + \"T00:00:00Z\");\n let weekdays = 0;\n for (let t = b + 86_400_000; t < a; t += 86_400_000) {\n const wd = new Date(t).getUTCDay();\n if (wd !== 0 && wd !== 6) weekdays++;\n }\n // >2 intervening weekdays is more than a holiday; treat as a real hole.\n if (weekdays > 2) gaps.push(`${win[i + 1].date}..${win[i].date}`);\n }\n }\n\n return {\n ready: h.length >= WINDOW,\n count: h.length,\n needed: WINDOW,\n newest,\n oldest: h[h.length - 1]?.date ?? null,\n ageDays,\n stale: ageDays === null ? true : ageDays > STALE_DAYS,\n contiguous: gaps.length === 0,\n gaps,\n dates: win.map((d) => d.date),\n };\n}\n\n// ---------------------------------------------------------------- compute --\n\nfunction interp(k: number, col: 1 | 2): number {\n if (k <= LADDER[0][0]) return LADDER[0][col];\n const last = LADDER[LADDER.length - 1];\n if (k >= last[0]) return last[col];\n for (let i = 0; i < LADDER.length - 1; i++) {\n const a = LADDER[i], b = LADDER[i + 1];\n if (k >= a[0] && k <= b[0]) {\n const t = (k - a[0]) / (b[0] - a[0]);\n return a[col] + t * (b[col] - a[col]);\n }\n }\n return last[col];\n}\n\nconst mean = (a: number[]) => a.reduce((s, x) => s + x, 0) / a.length;\nconst round2 = (x: number) => Math.round(x * 100) / 100;\nconst snap = (px: number, tick: number, grid: number) =>\n grid > 0 ? Math.round(px / grid) * grid : Math.round(px / tick) * tick;\n\nexport function computeLadder(b: any, history: Day[] = []) {\n const tick = b.tickSize ?? 0.25;\n const grid = b.strikeGrid ?? 0;\n\n if (!(b.open > 0)) throw new Error(\"open is required and must be positive\");\n if (!(b.asiaRange > 0) || !(b.euRange > 0)) {\n throw new Error(\"asiaRange and euRange are required and must be positive\");\n }\n\n // Inline history wins if supplied (stateless mode); otherwise use the store.\n let ranges: number[], opens: number[], source: string;\n if (b.rthRanges?.length >= WINDOW && b.rthOpens?.length >= WINDOW) {\n ranges = b.rthRanges.slice(0, WINDOW);\n opens = b.rthOpens.slice(0, WINDOW);\n source = \"request\";\n } else if (history.length >= WINDOW) {\n ranges = history.slice(0, WINDOW).map((d) => d.rthRange);\n opens = history.slice(0, WINDOW).map((d) => d.rthOpen);\n source = \"store\";\n } else {\n throw new Error(\n `need ${WINDOW} prior sessions: store has ${history.length}. ` +\n `POST /history/bulk to backfill, or pass rthRanges/rthOpens inline.`,\n );\n }\n\n // Ranges -> % of that day's open -> logs. Scale-free, so it stays valid as\n // NQ's price level drifts across years.\n const lrPct = ranges.map((r, i) => Math.log((100 * r) / opens[i]));\n const lp = lrPct[0];\n const m5 = mean(lrPct.slice(0, 5));\n const m22 = mean(lrPct.slice(0, 22));\n const la = Math.log((100 * b.asiaRange) / b.open);\n const le = Math.log((100 * b.euRange) / b.open);\n\n const logSigPct = COEF.const + COEF.lp * lp + COEF.m5 * m5 + COEF.m22 * m22 +\n COEF.la * la + COEF.le * le;\n\n const sigma = (Math.exp(logSigPct) / 100) * b.open;\n const sigLo = (Math.exp(logSigPct - RESID_SD) / 100) * b.open;\n const sigHi = (Math.exp(logSigPct + RESID_SD) / 100) * b.open;\n\n const gapSig = b.prevSettle ? Math.abs(b.open - b.prevSettle) / sigma : 0;\n const ovnSig = b.ovnRange ? b.ovnRange / sigma : 0;\n let state: \"GREEN\" | \"AMBER\" | \"RED\";\n if (gapSig > GATE.gap[1] || ovnSig > GATE.ovn[1]) state = \"RED\";\n else if (gapSig < GATE.gap[0] && ovnSig < GATE.ovn[0]) state = \"GREEN\";\n else state = \"AMBER\";\n\n const levels = RUNGS.flatMap((k) => {\n const dist = k * sigma;\n const touch = interp(k, 1);\n const band = interp(k, 2) * sigma; // 80th-pct overshoot — the honest error bar\n return [\n {\n side: \"up\",\n k,\n price: snap(b.open + dist, tick, grid),\n touchProb: round2(touch * 100),\n bandOuter: snap(b.open + dist + band, tick, grid),\n },\n {\n side: \"dn\",\n k,\n price: snap(b.open - dist, tick, grid),\n touchProb: round2(touch * 100),\n bandOuter: snap(b.open - dist - band, tick, grid),\n },\n ];\n });\n\n return {\n ok: true,\n model: \"HAR+Asia+Europe\",\n historySource: source,\n anchor: snap(b.open, tick, grid),\n sigma: round2(sigma),\n sigmaLo: round2(sigLo),\n sigmaHi: round2(sigHi),\n gate: {\n state,\n gapSigma: round2(gapSig),\n ovnSigma: round2(ovnSig),\n fadeWinRate: GATE_STATS[state].fadeWin,\n note: GATE_STATS[state].note,\n },\n levels,\n // Seams for v3 — JAR renders these when non-null, ignores them otherwise.\n impliedEM: null,\n gammaState: null,\n disclaimer:\n \"Levels are probability targets, not entries. 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